role of type vi secretion system in stress adaptations and

Role of Type VI Secretion System in Stress

Adaptations and Developing Control Strategies

for Campylobacter jejuni

By

Zobia Noreen

CIIT/SP13-PBS-009/ISB

PhD Thesis

In

Biosciences

COMSATS University Islamabad

Islamabad Campus-Pakistan

Spring, 2019

ii

COMSATS University Islamabad


Adaptations and Developing Control Strategies for

Campylobacter jejuni

A Thesis Presented to

COMSATS University, Islamabad

In partial fulfillment

of the requirement for the degree of

PhD (Biosciences)

By

Zobia Noreen


Spring, 2019

iii


Adaptations and Developing Control Strategies for

Campylobacter jejuni

_________________________________________

A Post Graduate Thesis submitted to the Department of Biosciences as partial

fulfillment of the requirement for the award of the Degree of PhD in Biosciences.

Name Registration Number

Zobia Noreen CIIT/SP13-PBS-009/ISB

Supervisor

Dr. Syed Habib Bokhari

Professor, Department of Biosciences

COMSATS University Islamabad (CUI)

Islamabad Campus.

viii

DEDICATION

To My Loving Brother Zeeshan Khurshid (Late)

ix

ACKNOWLEDGEMENTS

I bow my head in profound gratitude to my Almighty Allah Who in His infinite mercy

bestowed upon me the strength and potential to complete this task. I do greatly

acknowledge hereby the Holy Prophet Muhammad (P.B.U.H), whose life and

principles served as a beacon of knowledge for the whole mankind.

I would like to thank COMSATS University, Islamabad for providing me In-House

study leave for carrying out my PhD work. I would also like to acknowledge HEC for

providing me the opportunity to complete a part of my PhD research in National

University of Singapore (NUS) under IRSIP scholarship.

I would delectably present my sincere gratitude to my worthy supervisor, Prof. Dr.

Habib Bokhari, Professor, Department of Biosciences, for his dynamic supervision,

able guidance, illustrious advice, genuine interest, constructive criticism and

encouragement during my research work and thesis write up. I wish to pay my most

sincere regards to Dr. Sivaraman (National University of Singapore) providing

guidance and facilities to complete my work in his lab during my IRSIP visit. I would

also like to say thanks to Assistant Professor, Dr. Sundus Javed and Dr. Aamira Tariq

for their timely help and sincere guidance.

Heartfelt mention goes to amiable lab fellows Dr. Fariha Siddiqui, Kashaf Javed,

Salma Saeed, Sidra Siddiqui, Sobia Kanwal, Qurat ul Ain, Junaid Akhtar, Nighat

Parveen, Yasir, Kamran, Fizza, Kalsoom and Tahira for their support. I sincerely

acknowledge Dr. Jobichen Chacko, Edem, Kannupriya Mishra, YC, Sunil, and Digant

for their cooperation and generous help in NUS, Singapore.

I owe a special debt of gratitude to my friends Bushra Ijaz and Sadaf Azad who have

shared all my worries and happiness and for being there whenever I needed any help.

Now I would like to express my love, appreciation and deep sense of gratitude from the

citadel of my heart to my sweet and affectionate father Khurshid Ali khan and mother

Saeeda Akhtar for their prayers and consistent encouragement throughout the PhD

course. I would also acknowledge my Mother for her unparalleled effort in helping me

raise my two little kids along with my PhD work. I would like to thank my sister Dr.

Ayisha Khurshid for been always there for me when all seemed quite lost.

x

I would like to acknowledge my eternal gratitude, love, and deepest appreciation to my

husband Dr. Imran Ahmed who provide unparalleled support and encouragement and

gave me the strength to go on and complete this research work.

In the end I would like to say sorry, to my kids, Shahmeer Hassan and Aaiza Imran for

not giving them their due attention and time due to my busy PhD scheduled, but I

promise I will make up for it in near future.

“Much of what is right about this dissertation owe in my part to my teacher. All

errors of course, are mine”

Zobia Noreen


xi

ABSTRACT

Role of Type VI Secretion System in Stress Adaptations and

Developing Control Strategies for Campylobacter jejuni

The human Gram-negative enteropathogen Campylobacter jejuni is the leading cause

of gastroenteritis, with 25% of the cases worldwide being attributed to this organism.

C. jejuni, due to emergence of multidrug resistances, has also been classified as “high

priority pathogens” thus making surveillance system as an essential key for the control

of disease. However, in developing countries like Pakistan, the prevalence and source

prediction of MDR C. jejuni isolates has been under reported due to lack of proper

surveillance program. Therefore, the first section of the present study was conducted to

determine the prevalence of C. jejuni isolates among pediatric diarrheal cases in

Pakistan, their origin through source tracking as well as associated antibiotic resistance

patterns. C. jejuni was detected in 54.6% of the total samples and more than 75% of the

isolated strains were resistant to panel of 8 out of 13 antibiotics tested however; high

level of susceptibility was observed against imipenem (12.2%) and tigecycline (9.7%).

Moreover, six isolates (7.3%) were metallo-beta lactamase (MBL) producer and were

positive for at least one of the five screened metallo-beta lactamase genes. Source

tracking using source predictive PCR, showed that 57.3% of the isolates belonged to

livestock associated cluster (C1 to C6) and 42.8% were assigned to non-

livestock/environmental clusters (C7-C9). Isolates belonging to livestock cluster had

high MAR index as compared to non-livestock suggesting possible transmission of

antimicrobial resistant C. jejuni strains to human population via food chain. Moreover,

it also suggests that extensive use of antibiotics for disease control and growth

promotion in livestock especially in poultry industry results in the emergence and

spread of AMR C. jejuni and the genes associated with resistance.

C. jejuni, although being a fastidious microorganism, is able to survive and maintain its

pathogenesis in the harsh environments. However, the mechanisms of stress adaptations

and pathogenesis is C. jejuni are not fully elucidated. Type VI secretion system among

several gram-negative bacteria have been associated with virulence and stress

xii

adaptations but its role in stress tolerance and pathogenesis of C. jejuni is still unknown.

Moreover, in contrast to the other T6SS positive bacteria, C. jejuni has only one

hemolysin coregulated protein (Hcp) protein, the hallmark of a functional T6SS system,

whose structure and secretory function was not known. Therefore, the second aim of

this study was to determine the role of type VI secretion system in biofilm formation (a

stress adaptive mechanism) and pathogenesis. Moreover, the structure and function of

Hcp protein was also elucidated. Comparative analysis of effect of different sub-lethal

stresses on biofilm forming potential of isolates having fully functional T6SS (Hcp+)

and those lacking functional T6SS (Hcp-) showed that the biofilm formation was

significantly more enhanced in T6SS positive (Hcp+) groups as compared to T6SS

negative (Hcp-) group under heat (55ºC) and oxidative stresses (8mM of H2O2).

Structural analysis of Hcp showed similarities between the hexameric ring structure of

Hcp-Cj and that of Hcp3 from Pseudomonas aeruginosa. Through functional studies,

two roles for Hcp-Cj were identified i.e., in cytotoxicity toward HepG2 cells and in

biofilm formation in C. jejuni. Structure-based mutational analyses showed that an

Arginine to Alanine mutation at position 30 within the extended loop of Hcp-Cj resulted

in a significant decrease in cytotoxicity. However, biofilm formation function remained

unaffected by this mutation. Collectively, this study supports the dual role of Hcp-Cj as

a structural and effector protein in C. jejuni.

High prevalence of C. jejuni associated diarrhea in both developed and developing

countries can be attributed towards three major factors i) emergence of multidrug

resistant C. jejuni isolates making WHO recommended antibiotics ineffective for

treatment; ii) lack of control strategies at poultry level (as poultry meat consumption is

the major source of infection in human); iii) persistence of C. jejuni as biofilm in poultry

processing units and water reservoirs.. Therefore, third part of the present study was to

develop control strategies against C. jejuni at three different levels i.e., 1) In-silico drug

target identification was done using comparative proteomics and metabolomics

approach by which ten essential non-homologous drug targets were identified which

can be used in future to develop safe and effective drug against MDR C. jejuni ; 2) pH

sensitive alginate coated chitosan nanoparticles were designed for targeted delivery of

anti-campylobacter hexane fraction (PE-CANP) of Trachyspermum ammi (ajwain) into

the chicken caecum without loss of its activity in gizzard to control C. jejuni at poultry

farm level. The PE-CANP nanoparticles were able to reduce C. jejuni load to 6 logs (in

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CFU/g of caecal content) as compared to control group in chicken after 21 days of post

infection and can therefore be used as a good alternative to conventional antibiotics for

on-farm control of C. jejuni; 3) Three different metallic nanoparticles i.e.,

Silver/Graphene/TiO2, Erbium doped Li-Ni Ferrites and ZnO nanoparticle were tested

for their antibacterial activity against C. jejuni which showed excellent antibacterial and

anti-biofilm activity. All these nanoparticles can serve as an excellent coating material

for control of C. jejuni biofilms in food processing setups and hence may control the

transmission of C. jejuni to humans.

Overall the present study helps in better understanding the disease transmission patterns

and associated drug resistance traits as well as provides a better insight into the role of

T6SS in C. jejuni in stress adaptation and thereafter developing control strategies for

tackling C. jejuni both at farm and food processing level to reduce the burden of

campylobacteriosis in humans.

xiv

TABLE OF CONTENTS

1. Introduction .................................................................................................. 1

1.1 Campylobacter spp ........................................................................ 2

1.1.1 History and Taxonomy ....................................................... 2

1.1.2 General Characteristics ...................................................... 3

1.1.3 Epidemiology of Campylobacter jejuni ............................ 3

1.2 Transmission of Campylobacteriosis ........................................... 5

1.2.1 Sources and Reservoirs ..................................................... 5

1.2.1.1 Poultry as a major source of C. jejuni infections 7

1.2.2 Source Tracking of C. jejuni Infections ............................ 7

1.2.3 Antibiotic Resistance ........................................................ 8

1.3 Pathogenesis of C. jejuni .............................................................. 9

1.3.1 Motility .............................................................................. 9

1.3.2 Adhesion and Invasion Factors ....................................... 11

1.3.3 Toxin Production .............................................................. 12

1.3.4 Surface Carbohydrates .................................................... 12

1.3.5 Secretion Systems ........................................................... 13

1.3.5.1 Type III Secretion System (T3SS) .................. 13

1.3.5.2 Type IV Secretion System (T4SS) ................. 14

1.3.5.3 Type VI Secretion System (T6SS) ................. 14

1.3.5.3.1 Type VI Secretion System (T6SS) in

C. jejuni .......................................... 17

1.3.5.3.2 Hemolysin Coregulated Protein ..... 17

1.4 Stress Adaptations in C. jejuni ................................................... 18

1.4.1 Viable but Non-culturable Form (VBNC) ....................... 19

1.4.2 Transition from Spiral to Coccoid Shape ........................ 19

1.4.3 Adaptive Tolerance Response (ATR) .............................. 19

1.4.4 Genetic Heterogeneity ..................................................... 20

1.4.5 Biofilm Formation ........................................................... 20

1.4.5.1 T6SS and Biofilm Formation ............................ 21

1.5 Control of C. jejuni ..................................................................... 22

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1.5.1 Biosecurity Measures ....................................................... 22

1.5.2 Vaccination ..................................................................... 22

1.5.3 Antimicrobial Alternatives ............................................... 23

1.5.3.1 Bacteriophage Therapy ..................................... 23

1.5.3.2 Probiotics and Prebiotics .................................. 24

1.5.3.3 Antimicrobial Peptides ..................................... 25

1.5.3.4 Natural Antimicrobial Compounds .................. 25

1.6 Aims and Objectives ................................................................. 26

2. Materials and Methods ............................................................................. 27

2.1 Antibiotic Resistance Profiling and Source Attribution of C. jejuni

Isolates from Paediatric Diarrhoeal Cases ................................. 28

2.1.1 Sample Collection ............................................................ 28

2.1.2 Isolation of C. jejuni ........................................................ 28

2.1.4 Biochemical Identification of C. jejuni ........................... 28

2.1.5 PCR based for the Detection of C. jejuni ........................ 29

2.1.5.1 DNA Isolation .................................................. 29

2.1.5.2 Species Specific PCR ....................................... 29

2.1.6 Antimicrobial Resistance Profiling ................................... 30

2.1.6.1 Kirby-Bauer Disc Diffusion Method................. 30

2.1.6.2 Detection of Metallo-β-Lactamase .................... 30

2.1.7 Source Attribution ............................................................. 31

2.2 Stress Adaptation in Type Six Secretion System Positive and

Negative C. jejuni Isolates ......................................................... 33

2.2.1 Growth of Bacterial Strains ............................................. 33

2.2.2 Determination of Sub-lethal Level of pH, Temperature and

Oxidative Stress ............................................................... 33

2.2.3 Motility Assay .................................................................. 33

2.2.4 Hydrophobicity Assay ..................................................... 34

2.2.5 Auto-aggregation Assay ............................................. 34

2.2.6 Biofilm Assay ................................................................... 34

2.3 Structural and Functional analysis of Hcp: Hallmark Protein of

T6SS ............................................................................................ 35

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2.3.1 Plasmids and Bacterial Strain .......................................... 35

2.3.2 Point Mutations ................................................................ 35

2.3.3 Expression and Purification of Recombinant and Mutant

Hcp Protein ...................................................................... 37

2.3.4 Dynamic Light Scattering (DLS) ...................................... 37

2.3.5 Crystallization and Structure Determination ................... 38

2.3.6 Cytotoxicity towards Prokaryotic Cells ........................... 38

2.3.7 RBC Lysis Assay ............................................................. 38

2.3.8 Cytotoxicity towards Eukaryotic Cells (HepG2) .............. 39

2.3.9 Motility Assay .................................................................. 39

2.3.10 Biofilm Assay ................................................................ 39

2.4 In silico Drug Target Identification of C. jejuni ......................... 40

2.4.1 Complete Proteome Retrieval .......................................... 40

2.4.2Determination of Non-Homologous Essential

Genes/Proteins .................................................................. 40

2.4.3 Metabolic Pathway Analyses ............................................ 40

2.4.4 Drugability Potential of Shortlisted Proteins ................... 40

2.4.5 Prioritization of Druggable Target ................................... 41

2.4.5.1 Functional Categorization ................................... 41

2.4.5.2 Virulence Factor .................................................. 41

2.4.5.3 Molecular Weight ............................................... 41

2.4.5.4 Subcellular Localization ..................................... 41

2.4.5.5 Availability of Protein 3D Structure ................... 41

2.4.5.6 Chicken Proteome Homology Analysis .............. 41

2.4.5.7 Gut Flora Non-Homology Analysis .................... 43

2.5 Control of C. jejuni in Poultry by pH Sensitive Plant Extract

Encapsulated Alginate-Chitosan Nanoparticles ......................... 43

2.5.1 Screening of Plant extracts for Anti-campylobacter

Activity .................................................................................... 43

2.5.2 Fractioning of Trachyspermum ammi .............................. 44

2.5.3 Antibacterial activity of Trachyspermum ammi Fractions 44

xvii

2.5.3.1 Determination of Minimum Inhibitory

Concentration ...................................................... 44

2.5.3.2 Influence on Growth of Bacteria and Cell Survival

............................................................................. 44

2.5.4 Gas Chromatography- Mass Spectroscopy Analysis ....... 46

2.5.5 Preparation Plant Extract Loaded Alginate Coated

Chitosan Nanoparticles as a Nanocarrier System for

Targeted Delivery ............................................................ 46

2.5.6 Characterization of plant extract loaded Alginate Coated

Chitosan Nanoparticles ................................................... 47

2.5.6.1 Scanning Electron Microscopy ........................... 47

2.5.6.2 Atomic Force Microscopy .................................. 47

2.5.6.3. Fourier Transform Infrared Spectroscopy ......... 48

2.5.6.4 Encapsulation Efficiency .................................... 48

2.5.6.5 Cytotoxicity Assay .............................................. 48

2.5.6.6 pH Dependent Release Profile ............................ 49

2.5.7 In-vivo Trial in Chicken .......................................... 49

2.6 Metallic Nanoparticle as Control of C. jejuni Biofilms ............. 50

2.6.1 Nanoparticles Used .......................................................... 50

2.6.2 Test Microorganisms ....................................................... 50

2.6.3 Determination of Minimal Inhibitory Concentration ....... 50

2.6.4 Growth Kinetics ............................................................... 52

2.6.5 Hydrophobicity Assay ..................................................... 52

2.6.6 Auto-aggregation Assay .................................................. 52

2.6.7 Motility Assay .................................................................. 52

2.6.8 DNA and Protein Leakage Assay .................................... 53

2.6.9 Antibiofilm Activity ........................................................ 53

2.6.10 Cytotoxicity Assay ......................................................... 54

3. Results ........................................................................................................ 55


Isolates from Paediatric Diarrhoeal Cases ................................. 56

3.1.1 Isolation and Identification of C. jejuni ........................... 56

xviii

3.1.2 Antimicrobial Resistance Profiling .................................. 56

3.1.2.1 Multiple Drug Resistant Isolates ......................... 56

3.1.2.2 Detection of Metallo-β-Lactamase....................... 59

3.1.3 Source Attribution ............................................................ 59


Negative C. jejuni Isolates ......................................................... 63

3.2.1 Determination of Sub-lethal Level of pH ......................... 63

3.2.2 Effect of Sub-lethal pH 4.5 on Motility ............................ 63

3.2.3 Effect of Sub-lethal pH 4.5 on Auto-aggregation and

Hydrophobicity ................................................................ 65

3.2.4 Effect of Sub-lethal pH 4.5 on Biofilm Formation ........... 65

3.2.5 Determination of Sub-lethal Level of Oxidative Stress ... 67

3.2.6 Effect of Sub-lethal Oxidative Stress (8mM of H2O2) on

Motility ............................................................................. 67


Auto-aggregation and Hydrophobicity ............................ 69


Biofilm Formation ............................................................ 69

3.2.9 Determination of Sub-lethal Temperature ....................... 71

3.2.10 Effect of Sub-lethal Temperature 55ºC on Motility ....... 71

3.2.11 Effect of Sub-lethal Temperature 55ºC on Auto-

aggregation and Hydrophobicity ................................... 73

3.2.12 Effect of Sub-lethal Temperature 55ºC on Biofilm

Formation ....................................................................... 73


T6SS ............................................................................................ 75

3.3.1 Expression and Purification of Recombinant and Mutant

Hcp Proteins .................................................................... 75

3.3.2 Confirmation of Eluted Protein as Hcp Protein by Mass

Spectroscopy ................................................................... 75

3.3.3 Dynamic Light Scattering (DLS).................................... 75

3.3.4 Crystallization ................................................................ 78

3.3.5 The Overall Structure of C. jejuni Hcp ........................... 84

xix

3.3.6 Comparison with Hcp-Cj with Known Crystal Structures

of Hcp ............................................................................. 87

3.3.7 Functional Analysis of Secretory Hcp Protein ............... 93

3.3.7.1 Cytotoxicity towards Prokaryotic Cells ............. 93

3.3.7.2 RBC Lysis Assay ............................................... 93

3.3.7.3 Cytotoxicity towards Eukaryotic Cells (HepG2) 93

3.3.7.4 Motility Assay ................................................... 96

3.3.7.5 Biofilm Assay ..................................................... 96

3.4 In silico Drug Target Identification of C. jejuni ......................... 99

3.4.1 Essential Non-homology Protein in C. jejuni ................. 99

3.4.2 KEGG Pathway Analysis .............................................. 99

3.4.3 Drugability Potential of the Shortlisted Proteins ......... 101

3.4.4 Prioritization of Druggable Target ............................... 101


Encapsulated Alginate-Chitosan Nanoparticles ....................... 108

3.5.1 Screening of Plant for Anti-campylobacter Activity ..... 108

3.5.2 Active Anti-campylobacter fraction of Trachyspermum

ammi ............................................................................... 108

3.5.3 Influence on Bacterial Cell Survival .............................. 108

3.5.4 Gas Chromatography- Mass Spectroscopy Analysis ..... 111

3.5.5 Characterization of plant extract loaded Alginate Coated

Chitosan Nanoparticles ................................................. 115

3.5.5.1 Scanning Electron Microscopy ......................... 115

3.5.5.2 Atomic Force Microscopy ................................ 118

3.5.5.4 Encapsulation Efficiency .................................. 118

3.5.5.5 Cytotoxicity Assay ............................................ 118

3.5.5.6 pH Dependent Release Profile .......................... 118

3.5.5.3 Fourier Transform Infrared Spectroscopy ......... 121

3.5.7 In-vivo Trial in Chicken ................................................. 124

3.6 Metallic Nanoparticle as Control of C. jejuni Biofilms ........... 127

3.6.1 TiO2-Ag-Graphene Nanocomposites ............................. 127

xx

3.6.1.1 Minimal Inhibitory Concentration ..................... 127

3.6.1.2 Cell Survival ...................................................... 127

3.6.1.3 Hydrophobicity and Auto-aggregation .............. 127

3.6.1.4 Motility Assay .................................................... 129

3.6.1.5 DNA and Protein Leakage ................................ 129

3.6.1.6 Anti-biofilm Activity ......................................... 129

3.6.1.7 Cytotoxicity Assay ............................................. 129

3.6.2 Erbium doped Lithium Nickel Ferrite Nanoparticles .... 132


3.6.2.2 Cell Survival ...................................................... 132

3.6.2.3 DNA and Protein Leakage ................................ 132

3.6.2.4 Motility Assay .................................................... 132



3.6.3 Zinc Oxide Nanoparticles .............................................. 137


3.6.3.2 Cell Survival ...................................................... 137



4. Discussion ................................................................................................. 140

4.1 Conclusions ............................................................................... 155

4.2 Future Prospects ........................................................................ 156

5. References ................................................................................................ 157

Annexure (Meta data and publications) .......................................................... 188

xxi

LIST OF FIGURES

Fig. 1.1 Sources and transmission pathway of C. jejuni infections in human ......... 6

Fig. 1.2 Schematic model for T6SS components, assembly and effector translocation

into (a) the prey cell (b) and environment (adapted from Gallique et al., 2017) ........ 15

Fig. 2.1 Pet22b+ construct showing the insertion site of Hcp gene ...................... 36

Fig. 2.2 The overall scheme for identification of drug targets ............................ 40

Fig. 2.3 Scheme of Fractioning of Trachyspermum ammi extract ........................ 45

Fig. 3.1 Identification of C. jejuni isolates a) characteristics growth of C. jejuni on

mCCDA media; b) positive hippurate hydrolysis test; c) Species specific PCR for hipO

gene Lane 1- 1 kb ladder, Lane 2- 3, Isolates positive for hipO genes; Lane 4- Positive

control (Cj 255) ................................................................................................... 57

Fig. 3.2 Antibiotic resistance pattern of isolates C. jejuni against 13 tested antibiotics

........................................................................................................................... 58

Fig. 3.3 Detection of metallo-β-lactamases in C. jejuni using multiplex PCR assay

for MBL encoding genes i.e., IMP (188bp), SIM (390bp), and VIM (570bp) .......... 60

Fig. 3.4 Source predictive multiplex PCR: lane 1, 100-bp ladder; lane 2, strain BH20

(mPCR 1); lane 3, strain BH20 (mPCR 2); lane 4, strain SH11 (mPCR 1); lane 5, strain

SH11 (mPCR 2). mPCR 1 involved amplification of genes Cj1422, Cj1139 and Cj0056.

mPCR 2 involved amplification of genes Cj1324, Cj1720 and Cj0485. .................... 60

Fig. 3.4 Dendrogram displaying source attribution clusters of C. jejuni strains, based

on binary data of PCR profiles by using UPGMA analysis (PAST3.16 Software); Green

strain labels MAR=0.35-0.45, Blue strain labels- MAR=0.5-0.65, Red strain

labels=0.7-0.8; *** indicate isolates which are MBL producers ................................. 61

Fig. 3.5 Percentage and average MAR index of isolates attributed to livestock and

non-livestock clusters .................................................................................................. 62

Fig. 3.6 Average percentage survival of T6SS positive and negative strains at

different pH .................................................................................................................. 64

Fig. 3.7 Effect of sub-lethal pH (4.5) on motility of T6SS positive and negative

strains expressed in terms of fold change with respect to control .............................. 64

xxii

Fig. 3.8 Effect of sub-lethal pH (4.5) on hydrophobicity and auto aggregation of

T6SS positive and negative C. jejuni isolates (shown in term of average fold change in

each group)................................................................................................................... 66

Fig. 3.9 Effect of sub-lethal pH (4.5) on biofilm formation of T6SS positive and

negative C. jejuni isolates (shown in term of average fold change in each group). .... 66


different oxidative stress (2-12mM H2O2). .................................................................. 68

Fig. 3.11 Effect of sub-lethal oxidative stress (8mM) on motility of T6SS positive and

negative strains in terms of fold change with respect to control ................................. 68

Fig. 3.12 Effect of sub-lethal oxidative stress (8mM) on hydrophobicity and auto

aggregation of T6SS positive and negative C. jejuni isolates (shown in term of average

fold change in each group) ........................................................................................... 70

Fig. 3.13 Effect of sub-lethal oxidative stress (8mM) on biofilm formation of T6SS

positive and negative isolate (shown in term of average fold change in each group) . 70


different temperature stress (42-65ºC). ........................................................................ 72

Fig. 3.15 Effect of sub-lethal heat stress (55ºC) on average motility rate of T6SS

positive and negative strains with respect to control. .................................................. 72

Fig. 3.16 Effect of sub-lethal temperature stress (55⁰C) on hydrophobicity and auto


fold change in each group) ........................................................................................... 74

Fig. 3.17 Effect of sub-lethal temperature stress (55⁰C) on biofilm formation of

individual T6SS positive and negative isolate (shown in term of average fold change in

each group)................................................................................................................... 74

Fig. 3.18 Hcp-Cj protein expression and purification a) BL21 cells showing

expression of Hcp protein (18kDa) in induced culture (IN) and no expression in

uninduced cells (UIN) b) Showing fraction obtained in Ni-NTA coulmn purification;

Lane M: marker, 1: elution, 2: Soluble fraction of cell lysate, 3: insoluble fraction of

cell lysate, 4: flow through after binding with Ni-NTA, Lane 5-7 three subsequent

wahes with imidazole, 8: Hcp protein bonded to beads after elution ......................... 76

Fig. 3.19 Size exclusion chromatography a) elution profile of Hcp protein b) SDS-

PAGE analysis of the eluted fractions of SEC (chosen from the shaded region) showing

purified Hcp-Cj protein. ............................................................................................... 76

xxiii

Fig. 3.20 Mass spectroscopy analysis a) Mass spectrum of tryptic peptide digest of

purified Hcp protein; b) peptides that matched with hcp protein of C. jejuni using

Mascot are underlined ................................................................................................. 77

Fig. 3.21 Dynamic light scattering analysis of Hcp-Cj at 10mg/ml concentration

showing the protein is homogenous with polydispersity index of 0.03 ....................... 77

Fig. 3.22 Overall structure of the Hcp-Cj from C. jejuni Cartoon representation of the

Hcp monomer (a) and hexameric ring (b).................................................................... 85

Fig. 3.23 Multiple sequence alignment of Hcp-Cj with its homologs ..................... 88

Fig. 3.24 Structural alignment (a) showing that Hcp-Cj (with homolog protein) vary

greatly in length and composition especially the overhang loops L1,2 and L2,3 [Green:

Hcp_Cj, Magenta: EvpC (3EAA), Brown: B. pseudomallei (3WX6), Hot pink: E. coli

(4HKH), Yellow: P. aeruginosa Hcp3(3HE1), Cyan: P. aeruginosa Hcp1 (1Y12),

Blue: A. baumannii (4W64)]. b) Showing residues 30R and 31Y which were mutated

to Alanine ..................................................................................................................... 89

Fig. 3.25 Conserved residues on the Hcp surface. Deep red color represents highly

conserved residues and blue represent variable residues. External surface of the

hexamer is moderately conserved (a, b, e) as whereas the internal surface has

comparatively more variable residues (d). Conserved region mainly lies in the beta

sheets and helix (c)....................................................................................................... 90

Fig. 3.26 Effect of Hcp exposure on the growth of T6SS positive (strain ID 77, 255);

T6SS negative (strain ID 301, Akc27) and Dh5α. ....................................................... 94

Fig. 3.27 Hemolysis assay depicting that exposure of recombinant type hcp,

HcpR30A mutant and HcpY31A mutant protein didn’t caused lysis of Sheep

erythrocytes. Control group show lysis of RBC by 1% SDS ..................................... 94

Fig. 3.28 Cytotoxicity of recombinant and mutant Hcp-Cj towards HepG2 cells. A)

Showing reduction in HepG2 cells viability (%) on exposure to recombinant type and

mutant Hcp-Cj. B) Microscopic image of untreated and treated (Hcp-Cj exposed)

HepG2 cells. ................................................................................................................. 95

Fig. 3.29 Motility assay showing that recombinant and mutant Hcp-Cj didn’t cause

significant change in zone of motility of both type six positive (77, 255) and type six

negative strains (301, akc27) ....................................................................................... 97

Fig. 3.30 Effect of recombinant and mutant Hcp-Cj on Biofilm formation in C. jejuni.

a) Biofilm formation was significantly enhanced on exposure to Hcp-Cj as compared

xxiv

to unexposed cells. b) No significant difference in biofilm formation on exposure to

mutant and recombinant type Hcp-Cj was observed. .................................................. 97

Fig. 3.31 Number of essential non-homologous proteins of C. jejuni involved in

common (blue) and unique pathways ....................................................................... 100

Fig. 3.32 Anti-campylobacter activity of crude extract of A) positive control

Ampicillin, B) Trachyspermum annum (28.5mm), C) Mentha longifolia (17mm), D)

Camellia sinensis (23mm) E) Berberis lycium (26.5mm) F) Nigella sativa (25.5mm)

.................................................................................................................................... 109

Fig. 3.33 MTT assay showing the anti-campylobacter activity of different fraction of

Trachyspermum annum (seeds). Four fractions were found to be active with i.e.,

methanolic fraction (MF), hexane fraction (HF), butanol fraction (BF) and ethyl acetate

fraction (EF) with minimum inhibitory concentration of 0.125, 0.0362, 0.25 and 0.5

mg/ml respectively ..................................................................................................... 109

Fig. 3.34 Time dependent cell survival assay a) graph showing log reduction in

CFU/ml on exposure to hexane fraction of T. annum ............................................. 110

Fig. 3.35 The GC analysis of n-hexane fraction of Trachyspermum ammi seeds

showing four major peaks .......................................................................................... 112

Fig. 3.36 Mass spectra of peaks with retention time of a) 2.23 minutes identified as

4—Cyclohexadiene b)2.54 minutes identified as Mitozolomide c) 4.08 minutes

identified as Thymol) 4.151 minutes identified as 4 Hydroxy,3 methyl acetophenone.

.................................................................................................................................... 113

Fig. 3.37 Scanning Electron Microscopy (SEM) images of a) empty chitosan

nanoparticles (CNP) b) alginate coated chitosan nanoparticles (PE-CNP) c) plant

extract loaded chitosan alginate nanoparticles (PE-CANP) showing that the size of the

nanoparticles was below 100nm and nanoparticles were evenly distributed ............ 116

Fig. 3.38 Atomic force microscopic images showing surface topography and 3-

Dimensional (3D) structures of a) Chitosan nanoparticle (CNP) b) Alginate coated

chitosan nanoparticles (CANP) c) Alginate coated chitosan nanoparticle loaded with

plant extract (PE-CANP). .......................................................................................... 119

Fig. 3.39 Cytotoxicity assay of plant extract (PE), empty alginate coated chitosan

nanoparticles (CANP) and plant extract loaded chitosan alginate nanoparticles (PE-

CANP) using Human neuroblastoma cells (SH-SY5Y). Untreated cells were used as

negative controls ........................................................................................................ 120

xxv

Fig. 3.40 pH dependent release profile showing percentage release of plant extract

from Alginate coated chitosan nanoparticles (PE-CANP) at acidic (3.0) and neutral

(7.0) pH ..................................................................................................................... 120

Fig. 3.41 Fourier-transform infrared spectroscopy analysis showing spectra of a)

Plant extract (PE) b) Alginate coated chitosan nanoparticles (CANP) c) Alginate coated

chitosan nanoparticle loaded with plant extract (PE-CANP) ............................ 122

Fig. 3.42 Log reduction in C. jejuni CFU/g of chicken fecal samples at day 7 and 14

post infection in CANP (empty alginate coated chitosan nanoparticles), PE group (Plant

extract as feed additive), PE-CANP (Plant extract encapsulated alginate coated chitosan

nanoparticles as feed additive). .................................................................................. 125

Fig. 3.43 Average feed to gain ratio of chickens at day 7 and 14 post infection in

CANP group (empty alginate coated chitosan nanoparticles), PE group (Plant extract

as feed additive), and PE-CANP group (Plant extract encapsulated alginate coated

chitosan nanoparticles as feed additive). ................................................................... 125

Fig. 3.44 Log reduction in C. jejuni CFU/g of chicken caecum at day 21st post

infection in CANP (empty alginate coated chitosan nanoparticles), PE group (Plant


nanoparticles as feed additive) ................................................................................... 126




chitosan nanoparticles as feed additive). ................................................................... 126

Fig. 3.46 Influence of TiO2, TiO2-graphene (TiO2/GR), Ag-TiO2 (TiO2/AG) and

Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on the growth of C. jejuni ............ 128

Fig. 3.47 Effect of TiO2, TiO2-graphene (TiO2/GR), Ag-TiO2 (TiO2/AG) and

Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on hydrophobicity and aggregation of

C. jejuni ...................................................................................................................... 128


Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on C. jejuni motility ..................... 130

Fig. 3.49 Inhibition of biofilm activity of C. jejuni by TiO2, TiO2-graphene

(TiO2/GR), Ag-TiO2 (TiO2/AG) and Ag/TiO2-graphene (TiO2/GR/AG nanoparticles

.................................................................................................................................... 130

xxvi

Fig. 3.50 Leakage of DNA and protein in response to 2 and 4 h exposure of Ag/TiO2-

graphene (TiO2/GR/AG nanoparticles) expressed in terms of cytoplasmic leakage

index ........................................................................................................................... 131

Fig. 3.51 Cytotoxicity of TiO2, TiO2-graphene (TiO2/GR), Ag-TiO2 (TiO2/AG) and

Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles towards Human neuroblastoma cells

(SH-SY5Y) ................................................................................................................ 131

Fig. 3.52 Size dependent antibacterial activity of Erbium doped Li-Ni ferrite

nanoparticles shown in terms of Minimum inhibitory concentration (MIC) ............. 133

Fig. 3.53 Influence of Erbium doped Li-Ni ferrite nanoparticles on the growth of C.

jejuni .......................................................................................................................... 133

Fig. 3.54 Leakage of DNA and protein in response to 2 and 4 hrs exposure of

Ag/TiO2-graphene (TiO2/GR/AG nanoparticles) expressed in terms of cytoplasmic

leakage index ............................................................................................................ 134

Fig. 3.55 Inhibition of biofilm activity of C. jejuni by erbium doped Li-Ni ferrite

nanoparticles .............................................................................................................. 136

Fig. 3.56 Cytotoxicity of different sized erbium doped Li-Ni ferrite towards Human

neuroblastoma cells (SH-SY5Y) ................................................................................ 136

Fig. 3.57 Determination of Minimum Inhibitory Concentration of ZnO nanoparticles

using tetrazolium chloride based micro-dilution method .......................................... 138

Fig. 3.58 Influence of ZnO nanoparticles on the growth of C. jejuni ..................... 138

Fig. 3.59 Inhibition of biofilm activity of C. jejuni by ZnO nanoparticles ............. 139

Fig. 3.60 Cytotoxicity of ZnO nanoparticles towards Human neuroblastoma cells

(SH-SY5Y) ................................................................................................................ 139

xxvii

LIST OF TABLES

Table 1.1 Virulence factors of C. jejuni ............................................................... 10

Table 2.1 Detail of Primers and PCR conditions used in this study .................... 32

Table 2.2 Detail of nanoparticles used ................................................................. 51

Table 3.1 Screening of crystal condition using Index Screens (Hampton Research)

HR2-110 conditions 1-24 .......................................................................................... 79

Table 3.2 Sub-optimization of Crystal Screen HR2-110 condition no. 4 i.e., 0.1

Tris-HCl 8.5, 2M Ammonium Sulphate .................................................................... 81

Table 3.3 Sub-optimization of Crystal Screen HR2-110 condition no. 17 i.e., 0.2M

Lithium Sulphate monohydrate, 0.1 M Tris-HCl 8.5, 30% PEG ............................... 82

Table 3.4 Sub-optimization of Crystal Screen HR2-110 condition no. 22 i.e., 0.2M

Sodium acetate trihydrate, 0.1 M Tris-HCl 8.5, 30% PEG ........................................ 83

Table 3.5 Data collection and refinement statistics. ............................................ 86

Table 3.6 Sequence and structural comparison of Hcp-Cj with its homologs ..... 91

Table 3.7 Druggable target of C. jejuni before prioritization ........................... 103

Table 3.8 List of Druggable target of C. jejuni after prioritization .................... 106

Table 3.9 Statistical summary of drug target identification of C. jejuni. .......... 107

xxviii

LIST OF ABBREVIATIONS

Å Angstrom

AF Aqueous Fraction

AFM Atomic Force Microscopic

Ag Silver

AGDP Agricultural Gross Domestic product

Ag-TiO2 Silver-Titanium Oxide

AMR Antimicrobial Resistant

Amu Atomic Mass Unit

ATCC American Type Culture Collection

BF n-Butanol

BHI Brain Heart Infusion

bp Base Pair

CAMP Cationic Antimicrobial Peptide (CAMP) Resistance

CANP Alginate Coated Chitosan Nanoparticles

CDT Cytolethal Distending Toxin

CF Chloroform

CFU Colony Forming Unit

CLSI Clinical and Laboratory Standards Institute

CNP Empty Chitosan Nanoparticles

DEG Database of Essential Genes

DLS Dynamic Light Scattering Analysis

DMEM Dulbecco’s Modified Eagle Medium

DMSO Dimethyl Sulfoxide

DNA Deoxyribonucleic Acid

dNTPs Deoxyribose Nucleotide Triphosphates

DTT Dithiothreitol

EDTA Ethylenediamine Tetra acetic acid

EE Encapsulation Efficiency

xxix

EF Ethyl Acetate

EFSA European Food Safety Authority

ESBL Extended-spectrum β-Lactamase

FBS Fetal bovine serum

FCR Feed to Gain Ratio

FDA Food and Drug Administration

FTIR Fourier-transform Infrared Spectroscopy

GBS Guillain Barre’ Syndrome

GC-MS Gas Chromatography Mass Spectrometry

GIM German Imipenemase

GRAS Generally Recognized as Safe

H2O2 Hydrogen per Oxide

hcp Hemolysin Coregulated Protein

Hcp-Cj Hemolysin Coregulated Protein- C. jejuni

HepG2 Hepatoma G2 cell line

HF n-Hexane

HipO Hippurate Hydrolysis

IBS Irritable Bowel Syndrome

IcmF Intracellular Multiplication Factor

IMP Imipenemase

IPTG Isopropyl β-D-1-Thiogalactopyranoside

KBr Potassium Bromide

kDa Kilo Dalton

KEGG Kyoto Encyclopedia of Genes and Genomes

LB Lauria Broth

Li-Ni Lithium-Nickel

LOS Lipooligosaccharide

LPS Lipopolysaccharide

MBL Metallo-β-lactamases

mCCDA Modified Charcoal Cefoperazone Deoxycholate Agar

MDR Multi Drug Resistant

xxx

MF Methanolic Fraction

MFS Miller Fisher Syndrome

MH Mueller Hinton

MIC Minimum Inhibitory Concentration

mL Milliliter

MLST Multi Locus Sequence Typing

mM Millimolar

mPCR Multiplex Polymerase Chain Reaction

MRSA Methicillin Resistant Staphylococcus aureus

μL Microliter

µm Micrometer

MTT [3-(4, 5-Dimethylthiazol-2yl)-2, 5-Diphenyltetrazolium Bromide]

NCS Non-Crystallographic Symmetry

NCTC National Collection of Type Cultures Xii

Ni-NTA Nickel-nitrilotriacetic acid.

nm Nanometer

O. D Optical Density

PAGE Polyacrylamide Gel Electrophoresis

PBS Phosphate Buffered Saline

PCR Polymerase Chain Reaction

PDB Protein Data Bank

PE Plant Extract

PE-CANP Plant Extract Encapsulated Chitosan Alginate Nanoparticles

PEG Poly Ethylene Glycol

pH Power of Hydrogen Ion

RBC Red Blood Cells

RMSD Root Mean Square Deviation

SDS Sodium Dodecyl Sulfate (SDS)

SEM Scanning Electronic Microscopy

SIM Sao Paulo Metallo-beta-lactamase

SPM Seoul Imipenemase

xxxi

SRB Sulforhodamine B

STE Sodium Chloride Tris-EDTA

T3SS Type Three Secretion System

T4SS Type Four Secretion System

T6SS Type Six Secretion System

Taq Thermus Aquaticus

TE Tris EDTA

TiO2 Titanium Oxide

TiO2/Ag/Gr Titanium-Silver- Oxide-Graphene

TiO2/Gr Titanium Oxide-Graphene

TPP Sodium Tripolyphosphate

TTC Triphenyl tetrazolium Chloride

UPGMA Unweighted Pair Group Method Analysis

UV Ultra Violet

VBNC Viable But Non Culturable

vgrG Valine Glycine Repeats G

VIM Verona Imipenemase

WHO World Health Organization

ZDC Zone of Motility in Control

ZDT Zone of Motility in Treated

ZnO Zinc Oxide

Chapter 1 Introduction

1

Chapter 1

Introduction


2

Diarrhoea, is considered as the leading cause of death among children below 5 years of

age worldwide, accounting for 525,000 deaths per annum (WHO, 2017a). Diarrhoea,

the passage of three or more loose or liquid stools per day, is a preventable and treatable

disease. Mortalities linked to diarrhoea mostly occur due to acute dehydration or fluid

loss, and less commonly due to bacteremia. Diarrhoeal infections are transmitted

through contaminated food, water and even from person to person. Poor sanitation,

unsafe drinking water, malnutrition and low immunity are the major risk factors

associated with diarrhoea, thus making developing countries more susceptible to such

infections as compared to developed countries. Diarrhoeal infections are caused by a

variety of gastrointestinal bacteria (Campylobacter spp, Salmonella spp, Vibrio

cholera, Shigella spp and enterotoxigenic Escherichia coli,), viruses (rotavirus,

norovirus, adenovirus and asterovirus) and parasites (Giardia lamblia, Entamoeba

histolytica, Isospora belli, Cryptosporidium spp) (Platts-Mills et al., 2015). Among all

the listed causative agents of diarrhoea Campylobacter spp. is classified as the most

common cause of bacterial associated with acute diarrhoea worldwide (WHO, 2012,

Platts-Mills et al., 2015).

1.1 Campylobacter spp

1.1.1 History and Taxonomy

Campylobacter was first identified in 1886 by Theodor Escherich in the stool samples

of children suffering from a disease he called ‘cholera infantum’ (Friedman et al.,

2000). In 1909, McFadyean and Stockman isolated Campylobacter from aborted ewes’

fetuses and later the same microaerophilic spiral bacterium was also reported to be

associated with infectious abortions in sheep and calves by several researchers

(McFadyean and Stockman, 1913; Vinzent et al., 1950; Fox, 1982; Franco, 1988).

Smith isolated and named these bacteria as ‘Vibrio fetus’ based on its spiral morphology

(Smith, 1919). In 1957 and 1972, similar Vibrios were reported to be isolated from

blood and stool of diarrhoeal patient respectively. In 1963, these Vibrios were grouped

as a new genus i.e., Campylobacter, based on differences in carbohydrate fermentation

and DNA guanine-cytosine (GC) content, by Sebald and Véron (Veron, 1973). First C.

jejuni from the blood and stool sample of diarrhoeal patient was isolated in 1972 by

Dekeyser and coworkers using differential filtration using 0.65-µm filters (Dekeyser et


3

al., 1972). In 1977, Skirrow developed a method for selective recovery of C. jejuni from

stool specimens which further led to introduction of easy and reliable method of

isolation used nowadays (Skirrow, 1977). Campylobacter from stool samples, in

modern day laboratories, are routinely isolated by growing them using selective culture

media supplemented with antibiotics and incubating them under microaerophilic

conditions at elevated temperature (42oC). Campylobacter spp. belongs to genus

“Campylobacter”, of epsilon class of proteobacteria, which comprises of 26 species and

nine subspecies. C. jejuni and C. coli are major foodborne pathogens and are associated

with gastroenteritis. C. jejuni is further divided into two subspecies, namely C. jejuni

subspecies jejuni and C. jejuni doylei (Hendrixson and Rita, 2004).

1.1.2 General Characteristics

Members of Campylobacter spp. are non-spore forming, curved or spiral rod with size

ranging from 0.2-0.5 µm in diameter and 0.5-5µm in length (Hansson et al., 2007).

Campylobacters are pleomorphic as they appear as short spiral in log phase, long spiral

in mid stationary phase and coccoid in late stationary phase (Griffiths, 1993;

Tangwatcharin et al., 2006). The cells are highly motile and have unipolar or bipolar

flagella which help them to move in a corkscrew-like motion (Silva et al., 2011;

Kaakoush et al., 2015). C. jejuni are fastidious in nature and are microaerophilic i.e.,

can grow in the presence of low oxygen (5% O2, 10% CO2, and 85% N2) (Kelly, 2001,

Garénaux et al., 2008). These bacteria are catalase and oxidase positive but do not

possess urease enzyme. C. jejuni are thermotolerant with optimum growth temperature

of 42ºC, as they do not possess cold shock protein therefore cannot grow below 30 0C

(Hazeleger et al., 1998). C. jejuni can hydrolyze hippurate which help it differentiate it

from C. coli that are otherwise phenotypically and genotypically similar (Roop et al.,

1984).

1.1.3 Epidemiology of Campylobacter jejuni

Campylobacteriosis, diarrhoeal illness caused by Campylobacter spp, is considered as

a major public health concern worldwide with estimated cases of 500 million per annum

(Chlebicz et al., 2018). More than 90% of campylobacteriosis cases reported in human

are associated with C. jejuni, therefore accounting for the major burden of the disease


4

(Friedman et al., 2000; Gillespie et al., 2002; Moore et al., 2005). Campylobacteriosis

is generally self-limiting, with symptoms like watery or bloody diarrhoea, abdominal

cramps, fever, myalgia, headache, nausea and vomiting (Black et al., 1988).

Sometimes, C. jejuni infection may lead to sequel with long term consequences like

Guillain-Barré syndrome (GBS), Miller Fisher syndrome (MFS) and Irritable Bowel

syndrome (IBS) (Blaser and Engberg, 2008). The infection dose of C. jejuni in humans

is low; as few as 500 organisms can cause infection (Chlebicz et al., 2018). Although

the infection may occur among individuals of all age groups, however, children under

5 years of age are the major risk group (Butzler, 2004). Moreover,

immunocompromised individuals are more likely to suffer from campylobacteriosis as

compared to normal individuals. Though campylobacteriosis can occur throughout the

year but the incidence of disease is markedly increased in late spring and early summers

(Hudson et al., 1999).

The exact global burden of bacterial gastroenteritis due to Campylobacter spp. is

unknown, especially in low income countries, but in high-income countries the annual

incidence has been estimated to be 4.4-9.3 per 1000 population. This incidence varies

from region to region i.e., in the European Union 59.8 cases have been reported per

100,000 persons, in the US 14.3 cases/100,000, whereas 161 cases/100,000 are reported

in New Zealand (Ailes et al., 2008; Sears et al., 2011; Havelaar et al., 2013). Similarly,

C. jejuni has been reported as one of the most common cause of gastroenteritis in China,

Japan and India (Huang et al., 2009; Chen et al., 2011; Kubota et al., 2011; Mukherjee

et al., 2013; Mukherjee et al., 2014). In Pakistan, the high prevalence of

Campylobacter spp has been reported among food commodities such as chicken meat,

vegetable/fruit salad, beef and milk (Hussain et al., 2007; Nisar et al., 2018). C. jejuni

has also been the most frequently reported cause of childhood diarrhoea and dysentery

in Karachi and Rawalpindi, Pakistan (Ali et al., 2003; Soofi et al., 2011). The

epidemiological data of campylobacteriosis from Asia and the Middle East is under

reported due to the lack of proper surveillance system, diagnostic system and public

awareness. However, the numbers of campylobacteriosis cases have increased

significantly worldwide during the last two decades making it the most common


5

zoonotic infection surpassing both salmonella and shigella (EFSA, 2011; Havelaar et

al., 2013).

C. jejuni infections are generally sporadic but rare outbreaks have been reported in the

UK, Denmark, USA, China, Korea, and Canada which are mostly associated with

consumption of contaminated water, milk and meat (Gubbel et al., 2012; Taylor et al.,

2013; Kaakoush et al., 2015).

1.2 Transmission of Campylobacteriosis

Campylobacteriosis is a zoonotic food-borne disease as it has a broad host range

including domestic (poultry, cattle, sheep) and wild animals; and usual routes of

infection for humans are raw meat or cross-contaminated food products. The disease

(50-70% of reported cases) is mainly transmitted by consumption of contaminated raw

and undercooked poultry meat, unpasteurized milk, raw vegetables and unhygienic

water. Cases of campylobacteriosis transmitted via direct contact with domesticated

animals, especially birds and cats, have also been reported (Ketley, et al., 1997;

Kapperud et al., 2003). Apart from zoonotic transmission, traveling to endemic regions

can also be an additional risk factor for acquiring the infection. Several cases have been

associated with recent travel to other countries and such acquired infections are

generally more resistant to antibiotics than domestic cases (Kassenborg et al., 2004;

Evans et al., 2009). However, the source of approximately 50% of all infections is still

unknown (Janssen et al., 2008).

1.2.1 Sources and Reservoirs

C. jejuni, despite being fastidious in nature, is widespread in nature as it has number of

host and reservoirs which protect them against harsh environment. C. jejuni is a normal

commensal in the gut of animals like chicken, cattle, wild birds, pig, dog and sheep.

But when transmitted to a human host it can cause disease (Whiley et al., 2013). The

sources and transmission pathways of C. jejuni infection are summarized in Fig 1.1.


6

Fig. 1.1 Sources and transmission pathway of C. jejuni infections in human

(adapted from Kaakoush et al., 2015)


7

1.2.1.1 Poultry as a major source of C. jejuni infections

Poultry is considered the major source of campylobacteriosis in humans. C. jejuni,

being a thermotolerant, prefer poultry as host due to its high metabolic temperature (40-

42oC) (Horrocks et al., 2009). Generally, C. jejuni resides in the gut of chicken, turkeys,

ducks, goose game foul and ostrich without causing any illness in the host organisms.

Out of all poultry products, chicken is a major risk of campylobacteriosis accounting

for more than 50% of food born transmission. Consumption of non-chlorinated water

by the chickens exposes them to C. jejuni. The microbe spreads from one chicken to

whole flock within 3-5 days through infected faeces, water, insects, rodents or farm

workers, hence becomes very difficult to contain (Ridley et al., 2011; Saint-Cyr et al.,

2016). C. jejuni generally colonize the mucosa of the caecum of infected chickens but

has also been reported to be present in the blood, liver and spleen. One gram of fecal

matter of infected chicken can contain up to 1010 CFU of bacteria (Lin et al., 2009,

Bolton et al., 2015). The bacterium is transmitted from the meat of carrier birds to

originally non-carriers after encountering dropping during slaughtering process.

It has been estimated that 60% of retailer chicken meat in the EU and the US are

infected with C. jejuni (Epps et al., 2013; Whiley et al., 2013). Although, the disease

can be transmitted to human through direct contact with infected chicken and

consumption of infected eggs, but majority of the cases have been attributed to eating

of raw or undercooked chicken (Epps et al., 2013). It has been estimated that human

campylobacteriosis can be reduced by 30-fold by reducing the load of C. jejuni CFU

broiler carcass by 2-log (Rosenquist et al., 2003).

1.2.2 Source Tracking of C. jejuni Infections

Source attribution can help identify the origin of C. jejuni infection and antibiotic

resistance acquisition which will in turn help prevent the spread of disease. Due to high

genetic diversity and low host specificity among C. jejuni strains, it is challenging to

estimate the contribution of a specific source in human infections. Nevertheless, several

microbial typing methods have been used to track the source of C. jejuni infections in

human such as multilocus sequence typing (MLST), microarrays analysis, source

predictive PCR and whole genomes sequences (WGS) (Dingle et al., 2001; Dorrell et

al., 2001; Colles et al., 2003; Leonard et al., 2003; Pearson et al., 2003; Champion et


8

al., 2005; Kwan et al., 2008; Foley et al., 2009; Stabler et al., 2013). Although, the

multilocus sequence typing is the most widely used typing method for strain

comparison but in developing countries like Pakistan, source predictive PCR provide

reliable and cheap alternate for genotyping of human isolates to predict their source of

origin.

1.2.3 Antibiotic Resistance

Campylobacteriosis is generally a self-limiting disease but antibiotics like macrolides

(azithromycin and erythromycin) and fluoroquinolones (ciprofloxacin) are

recommended in immunocompromised, invasive or asymptomatic cases (Allos, 2001;

Smith and Fratamico, 2010). Majority of the C. jejuni isolates have been reported

worldwide to be intrinsically resistant to a few antibiotics, including bacitracin,

novobiocin, rifampin, streptogramin B, trimethoprim, vancomycin, and usually

cephalothin. Over the past two decades, the emergence of multidrug resistant C. jejuni

especially against erythromycin, fluoroquinolones and tetracycline have been reported

from both developing and developed countries (Alfredson and Korolik, 2007;

Wieczorek and Osek, 2013). Being a zoonotic pathogen, antimicrobial resistance

acquired by C. jejuni isolates has been mainly attributed towards use of these antibiotics

as prophylaxis in animal farming (Wilson et al., 2008; Mughini-Gras et al., 2013).

Disproportionate use of antibiotics in livestock industry results in development of more

resistant isolates on bacterial pathogens by either mutation or by acquisition of

antibiotic resistance genes through horizontal gene transfer (Holmes et al., 2016).

Antibiotics belonging to β-Lactams class have been used as preferably due to their high

efficacy and low toxicity to humans. The choice of β-Lactams is reduced to

carbapenems when infections are caused by extended-spectrum β-Lactamase (ESBL)

producing organisms (Dalhoff and Thomson, 2003). Such extended-spectrum β-

Lactamase (ESBL) producing isolates have also been reported in C. jejuni.

Carbapenems are β-lactam antibiotics that are highly effective against number of gram

positive and negative bacteria which are resistant to other β-lactam antibiotics. So far,

carbapenem resistant Pseudomonas spp, K. pneumoniae, Acinetobacter baumannii and

Escherichia coli have been reported which produce Carbapenemases or AmpC enzyme

to hydrolyze the antibiotics (Brink et al., 2004; Yong et al., 2009). Till date, no strain


9

belonging to Campylobacter genus have been reported to be shown resistance to

carbapenem making it an effective choice of control of severe infection.

In Pakistan data related to prevalence, antibiotic resistance and source prediction of C.

jejuni infection s is very limited due to lack of proper surveillance program (Ali et al.,

2003; Soofi et al., 2011; Siddiqui et al., 2015a). Such epidemiological data may provide

a better insight into to the current status of disease in the local population and will also

help develop better control strategies against it.

1.3 Pathogenesis of C. jejuni

Ingestion of as few as 500 CFU of C. jejuni is enough to establish an infection in the

gastrointestinal tract of human. The adhesion and invasion of intestinal epithelial cells

triggering pro-inflammatory response, by inducing the production of interleukin (IL)-

8, and eventual recruitment of dendritic cells, macrophages and neutrophils. Virulence

factor like motility, chemotaxis, adhesion, invasion and toxin production play a vital

role in successful colonization but the precise mechanism of pathogenesis of C. jejuni

is still unknown (Bouwman et al., 2013). The whole genome sequence of the C. jejuni

NCTC11168 has provided valuable insight into the pathogenesis, by verifying that

cytolethal distending toxin (CDTs) is the only toxins produced by the bacterium

(Parkhill et al., 2000). Furthermore, presence of homopolymeric G/C repeats and lack

of DNA repair genes in the genome may lead to phase variation which in turn may

enhances virulence potential and adaptation responses to environmental stresses

(Bayliss et al., 2012). Some of the key virulence factors associated with C. jejuni is

discussed in the following section (Table 1.1).

1.3.1 Motility

C. jejuni are highly motile bacteria and this ability helps them reach, invade and

colonize the host intestinal cells. Motility of C. jejuni is due to presence of polar flagella

which allows the bacterium to invade the mucosal barrier of intestinal epithelial cell

and hence considered essential for invasion and colonization


10

Table 1.1 Virulence factors of C. jejuni

Virulence Factors

Genes

References

Motility FlaA and FlaB

FlgR, RpoN and

FliA

Guerry et al., 1990; Nuijten et

al., 1990b; Alm et al., 1993;

Nuijten et al., 1995; Wösten et

al., 2004

Adhesion and Invasion CadF, FlpA, JlpA,

CiaA, CiaB, CiaI,

FlaC, FspA, flgB

and FlgE

Konkel et al., 1999; Jin et al.,

2003, Konkel et al., 2004; Song

et al., 2004, Poly et al., 2007;

Christensen et al., 2009;

Flanagan et al., 2009; Konkel et

al., 2010; Buelow et al., 2011;

Eucker and Konkel, 2012

Toxin production

Cytolethal distending toxin

(CDT)

CdtA, CdtB and

CdtC

Whitehouse, 1998; Hickey et

al., 2000; Lai et al., 2016.

Asakura et al., 2008

Flagellin O-linked

glycosylation proteins.

Cj1321-Cj1325/6 Champion et al, 2005.

Capsule KspM Bacon et al., 2001


11

(Nachamkin et al., 1993). The flagellum is composed of subunits of flagellin proteins,

encoded by two genes flaA and flaB which share a high degree of sequence homology

(Wassenaar and Blaser, 1999). Although expression of both flaA and flaB is crucial for

colonization of C. jejuni, but flaA is highly expressed as compared to flaB (Guerry et

al., 1990). Expression of both protein are independent of each other as gene expression

of flaA is regulated by r28 promoter, whereas that of flaB gene by r54 promoter (Guerry

et al., 1990; Nuijten et al., 1990b; Alm et al., 1993; Nuijten et al., 1995). Moreover,

flaA has also been shown to be linked with auto-agglutination (AAG) ability of

bacterium as flaA mutant lack this ability (Guerry et al., 2006). The regulation of

flagellin protein is very complex as flaA regulon is composed of 32 individual loci.

Although a few flagellar transcription activators like FlgR, RpoN and FliA have been

identified but the precise mechanism of their regulation and assemble is unknown

(Wösten et al., 2004).

1.3.2 Adhesion and Invasion Factors

After penetrating intestinal mucosal lining, adhesion and invasion of the epithelial cells

is crucial for long term establishment of infection (Jin et al., 2001). Very few adhesin

proteins with known host cell receptor are identified in C. jejuni which include CadF,

FlpA and JlpA. Fibronectin binding protein (CadF) and fibronectin-like protein A

(FlpA) help C. jejuni to bind to fibronectin (Fn) of host gastrointestinal tract (Konkel

et al., 2010; Flanagan et al., 2009). Both these genes are crucial for adherence as

mutation in either of the gene leads to reduction in the adherence of C. jejuni to human

INT 407 cells (Monteville et al., 2003; Flanagan et al., 2009). Jejuni lipoprotein (JlpA)

is an outer membrane protein which binds to heat shock protein 90 (Hsp90) of HEp-2

epithelial host cells and activates NF-κB and p38 MAP kinase (Jin et al., 2003). JlpA

mutant strains have shown reduced adherence to HEp-2 epithelial cells (Jin et al.,

2001).

Invasion of host epithelial cells is the key difference that leads to infection by C. jejuni

in humans as compared to chickens (Young et al., 2007). On contact with host cells or

serum factors, C. jejuni secrete a class of secreted factor proteins called Campylobacter

invasion antigen (Cia) (Konkel et al., 1999b). CiaB is an effector protein which helps

internalization of bacterium into the INT-407 cells and its secretion is dependent upon


12

flagellar subunits (Konkel et al., 1999, Konkel et al., 2004). CiaC is essential for

maximal invasion of INT-407 cells, whereas CiaI is involved in intracellular survival

of C. jejuni (Christensen et al., 2009; Buelow et al., 2011; Eucker and Konkel, 2012).

Secretory protein FlaC binds to Hep2 cells and help in bacterial invasion (Song et al.,

2004). The FspA protein is secreted by flagellum and induces apoptosis in INT-407

cells (Poly et al., 2007). Several flagellar proteins also take part in invasion mechanism

in host epithelial cells like flaA, flaB, flgB and flgE (Konkel et al., 2004; Poly and

Guerry, 2008).

1.3.3 Toxin Production

C. jejuni produce cytolethal distending toxin (CDT) which is a genotoxin composed of

three subunits namely CdtA, CdtB and CdtC (Whitehouse, 1998; Asakura et al., 2008).

CdtB is a DNase that induces double-strand breaks in the DNA, and which eventually

leads to cell apoptosis. CdtA and CdtC subunits are involved in delivery of CdtB to the

host cells by binding to cholesterol-rich microdomains of the host cell membrane (Lai

et al., 2016). Cytolethal distending toxin (Cdt) has also been associated with prolonged

survival in macrophages (Hickey et al., 2000).

1.3.4 Surface Carbohydrates

C. jejuni display several carbohydrate-based structures on its surface such as

lipopolysaccharides (LOS), capsule and O- and N-linked glycans which act as

important virulence factors. Lipopolysaccharides (LOS) are composed of

oligosaccharides and lipids that play major role in host immune system evasion,

adhesion to host cell and invasion. Sialylation of LOS causes increase in cell adhesion

of C. jejuni and reduces immunogenicity (Guerry et al., 2000; Louwen et al., 2008).

Polysaccharide capsule of C. jejuni helps in survival of bacteria, adherence to the cell

and evasion of immune system (Karlyshev et al., 2004). Mutation gene encoding for

polysaccharide transport protein (KspM) results in reduced invasion and colonization

of C. jejuni (Bacon et al., 2001). C. jejuni possess both O and N linked protein

glycosylation systems which are encoded by pgl gene and (Szymanski et al., 2003). O-

linked glycosylation system in C. jejuni is apparently associated with the modification

of only flagellin subunits and hence is essential for filament biogenesis (Goon et al.,


13

2003). On the other hand, N-linked glycosylation system is responsible for post

translational modification of more than 60 periplasmic proteins. Mutant C. jejuni with

defective N-linked glycosylation system show reduced invasion and colonization in

intestinal epithelial cells and in animals respectively (Szymanski et al., 2002;

Hendrixson and DiRita 2004).

1.3.5 Secretion Systems

Secretion systems provide selective advantage to both pathogenic and non-pathogenic

bacteria by enhancing their virulence potential and environmental adaptation

respectively (Aschtgen et al., 2010; Schwarz et al., 2010). Bacterial secretion systems

are designed to translocate proteins across single (bacterial inner membrane), two

(bacterial inner membrane and outer membrane) or even three membranes (bacterial

cell membrane, LPS and host cell membrane). Some proteins are translocated in two

steps i.e., 1) from cytoplasm to periplasm and 2) periplasm to outside via Sec and Tat

dependent pathways (Green and Mecsas, 2016). The Tat pathway translocate folded

whereas Sec pathway translocate unfolded proteins (Palmer and Berks, 2012). In Gram

negative bacteria, proteins can be translocated directed through channels that span both

the inner and outer bacterial membranes (Sec- or Tat-independent protein secretion)

into the host cell or environment. Six such secretion systems have been identified in

Gram negative bacteria (Type I-VI) out of which C. jejuni has been reported to possess

type III, IV and VI secretion systems (Bleumink-Pluym et al., 2013). These secretion

systems are briefly discussed as follows.

1.3.5.1 Type III Secretion System (T3SS)

Type III secretion system is a complex nano-injectisome composed of component

similar to that of flagella (Young et al., 1999). T3SS helps bacterium to deliver effector

proteins into host cells (both prokaryotic and eukaryotic) and to evade host immune

system (Gophna et al., 2003; Cornelis, 2006). C. jejuni lacks the classical T3SS system

and its flagellum (which is homologous to the classical T3SS) plays the role of sole

T3SS machinery (Parkhill et al., 2000). Proteins exported through the flagellar T3SS

of C. jejuni include CiaB, CiaC, CiaI, FlaC, and FspA (Song et al., 2004; Poly et al.,

2007; Konkel et al., 1999; Christensen et al., 2009).


14

1.3.5.2 Type IV Secretion System

Type IV secretion system facilitates transport of macromolecules such as proteins,

DNA or nucleoprotein across bacterial membranes to other bacteria, eukaryotic cell or

environment. The T4SS machinery is an ancestral homolog of bacterial conjugation

machinery (Rego et al., 2010). Functionally, T4SS is of three types 1) class 1 helps

transfer of DNA between cells by conjugation 2) class 2 helps uptake of DNA by

transformation and its release from extracellular milieu 3) class 3 helps transfer of

proteins (Alvarez-Martinez and Christie, 2009). In C. jejuni, T4SS is encoded by two

plasmids i.e., tetO and pVir. pTet encoded T4SS is involved in the conjugational

transfer of the tetO plasmid between strains thus transferring tetracycline resistance.

pVir encoded T4SS work in non-conjugative manner and is involved in natural

transformation and invasion of host cells (Bacon et al., 2002).

1.3.5.3 Type VI Secretion System

Type six secretion system, present in more than 20% of gram negative bacteria, acts

like a nanomachinery, injecting bacterial proteins/toxins into the host cell (eukaryotic

cell or bacterial competitor) and into the environment to affect virulence, inter-bacterial

communication, symbiosis, biofilm formation, antipathogenesis and environmental

stress response (Jani and Cotter 2010; Lertpiriyapong et al., 2012; Ho et al., 2014). To

perform different functions many bacteria possess more than one T6SS gene cluster in

the genome (Lertpiriyapong et al., 2012). T6SS is mainly functions in a contact

dependent manner; however, some effectors can exert their effect extracellularly

(Durand et al., 2014; Russell et al., 2014; Cianfanelli et al., 2016; Lin et al., 2017).

Needle like assembly of T6SS is composed of 13 core components (Fig 1.3) that

transverse across the bacterial cell membranes and delivers proteins into different type

of host cells (Cascales and Cambillau, 2012; Silverman et al., 2012). Hcp (Hemolysin

coregulated protein) is a hexameric protein that forms the core tube of needle like T6SS

machinery and help transport substrate through its channel. VgrG (Valine-glycine rich

repeats G) is present at the distil tip of Hcp tube and act like a puncturing device

(Pukatzki et al., 2009). ImpB (TssB) and ImpC (TssC) form the


15

Fig. 1.2 Schematic model for T6SS components, assembly and effector

translocation into (a) the prey cell (b) and environment (adapted from Gallique et al.,

2017a)


16

tubular sheath around the Hcp core (Bonemann et al., 2009; Basler et al., 2012). PAAR

((Pro-Ala-Ala-Arg) protein sharpens the spike of VgrG (Shneider et al., 2013). Trans-

periplasmic membrane complex of T6SS is responsible for binding of T6SS to cell

envelope and is made up of inner membrane proteins VasF and IcmF (TssL and TssM)

and outer membrane protein VasD (TssJ). Five proteins i.e., ImpA (TssA), ImpG (TssF),

ImpH (TssG), TssE (gp25) and VasE (TssK) form the basal complex (Bonemann et al.,

2009, Basler et al., 2012). Hcp and VgrG act as both structural and secretory proteins

which are released into the host cells along with T6SS effectors. Presence of Hcp (TssD)

and VgrG (TssI) is considered as market of functional T6SS (Pukatzki et al., 2007;

Zheng and Leung, 2007; Hachani et al., 2011).

T6SS start assembling by formation of membrane complex which is followed by

baseplate positioning. Tail is then formed onto the base plate by addition of Hcp

subunits and sheath proteins. The T6SS spear (Hcp-VgrG-PAAR complex) makes a

contact with the prey cell by contraction of sheath and punctures the host cell to deliver

effector proteins (Pukatzki et al., 2007; Ma and Mekalanos 2010 and Suarez et al.,

2010). Two types of effectors are delivered via T6SS i.e., ‘cargo’ or ‘specialized’

(Cianfanelli et al., 2016). Cargo effectors directly or with the help of adaptor attach

themselves to the Hcp-VgrG-PAAR complex for delivery whereas specialized effectors

are modified or evolved Hcp, VgrG or PAAR having C terminus effector domains

(Durand et al., 2015). After the delivery of these effector proteins the T6SS assemble

is dismantled by ClpV which can then be reused for new assembly cycle (Gallique et

al., 2017).

Type six secretion system is versatile machinery which can be used to combat other

bacteria and for invasion of eukaryotic cell host to establish infection. T6SS can work

in a defensive or offensive manner to fight against other bacteria. In P. aeruginosa,

T6SS system works as defensive mechanism and help fight off attack from T6SS

positive V. cholerae or A. baylyi. On the contrary T6SS in V. cholerae it works as

aggressive strategy to attack bacteria lacking T6SS system (Gallique et al., 2017).


17

1.3.5.3.1 Type VI Secretion System in C. jejuni

The T6SS has been recently discovered in C. jejuni and is associated with bloody

diarrhoeal cases (Lertpiriyapong et al., 2012, Harrison et al., 2013). Whole genome

sequencing has revealed that although core T6SS genes are conserved among different

strains of C. jejuni, but their arrangement shows great degree of variability. However,

all C. jejuni isolates possesses only one T6SS gene cluster in their genome assembly

(Harrison et al., 2014). T6SS in C. jejuni has been shown to enhance cytotoxicity,

hemolysis and colonization of mice but still very less work is done on the role of T6SS

component in the pathogenesis of the bacterium (Lertpiriyapong et al., 2012; Bleumink-

Pluym et al., 2013). This cytotoxicity toward red blood cell has been reported to be

contact dependent. The C. jejuni T6SS is unique from other T6SSs as it is seemingly

not essential for bacterial survival or growth, even though it is active. Moreover, it lacks

the T6SS secretion ATPase, ClpV, which is thought to provide energy to the T6SS

machinery (Bonemann et al., 2009). However, the structure and function of T6SS in C.

jejuni is not fully known.

1.3.5.3.2 Hemolysin Coregulated Protein

Out of the 13 core T6SS proteins, the hemolysin coregulated protein (Hcp) is

considered the hallmark of a functional system. Hcp protein in some bacteria e.g. P.

aeruginosa V. cholerae, A. hydrophila, and B. pseudomallei has been associated with

providing selective advantage to bacteria by killing other competing bacteria. Hcp is

essential for both T6SS assembly and function and plays both structural and effector

role. Many gram-negative bacteria possess more than one type of Hcp that encodes

either a structural or an effector protein; however, C. jejuni has only one Hcp protein

purposed to play both functions (Lertpiriyapong et al., 2012). Individual Hcp protein

forms a hexameric rings with an inner diameter of 40 Å which stack on top of each to

make a hollow tube, allowing effectors to pass through. Although all Hcp structures

resolved so far show the same architecture, the function of Hcp varies greatly in

different bacteria. Hcp of A. hydrophila helps evade host innate immunity by preventing

phagocytosis via macrophages (Suarez et al., 2010). Secretory Hcp1 of Escherichia coli

K1 causes actin rearrangement and apoptosis whereas non-secretory Hcp2 play role in

bacterial adherence and invasion of human brain microvascular endothelial cells (Zhou


18

et al., 2012). Hcp1 in B. pseudomallei induces cytotoxicity against macrophages and

induce multinucleated giant cell formation (Burtnick et al., 2011). Hcp family proteins

of P. fluorescens provide competitive advantage against Dickeya dadantii and play a

vital part in biofilm maturation (Decoin et al., 2015; Gallique et al., 2017b).

Functional studies have shown that Hcp in C. jejuni mediates in vivo colonization by

enhancing adhesion and invasion into the eukaryotic host cell and providing resistance

to bile salts and deoxycholic acids (Lertpiriyapong et al., 2012; Bleumink-Pluym et al.,

2013). Furthermore, it enhances contact-dependent hemolysis (Bleumink-Pluym et al.,

2013). All these functional studies on Hcp in C. jejuni are based on Hcp mutant strains

(which harbor the T6SS assembly), whereby mutation of Hcp shut down the functioning

of all T6SS component, therefore, it is difficult to analyze the potential effector role of

Hcp based on previous findings (Noreen et al., 2018).

1.4 Stress Adaptations in C. jejuni

Despite being fastidious in nature, C. jejuni faces and withstand a variety of stresses

during the process of transmission from reservoirs (poultry, cattle) to humans. These

stresses include nutrient limitation (in water reservoirs), cold and heat stress (in

processing plants), acidic pH (in both processing plant and host gut) and exposure to

atmospheric level of oxygen (Murphy et al., 2006; Jackson et al., 2009). C. jejuni do

not possess the usual stress response machinery found in other Gram negative

pathogenic bacteria such as oxidative stress response factors (SoxRS and OxyR), global

stationary phase response factor (RpoS), cold shock proteins (CspA) and the global heat

shock response regulator (RpoH). It is still not known that how C. jejuni is able to resist

stresses by just possessing only three sigma factors (RpoD, FliA and RpoN) (Parkhill

et al., 2000). Better understanding of the stress adaptation and survival mechanisms

of C. jejuni will help in control and treatment of campylobacteriosis. Several

mechanisms have been proposed that might help C. jejuni to survive under harsh

environmental stresses which are discussed as follows.


19

1.4.1 Viable but Non-culturable Form (VBNC)

The Viable but non-culturable form of bacteria is a state in which the bacteria are viable

but metabolic less active therefore it is very difficult to grow them under laboratory

conditions (Barer and Harwood, 1999; Oliver, 2005). Bacteria like C. jejuni convert

themselves into a viable non culturable state (VBNC) upon exposure to harsh

environmental stresses (Rollins and Colwell 1986; Korhonen and Martikainen 1991).

C. jejuni retains its virulence potential even in VBNC state and can regain its culturable

form upon favorable condition or after in-vivo passage through mice (Baffone et al.,

2006; Skovgaard, 2007).

1.4.2 Transition from Spiral to Coccoid Shape

C. jejuni in the late stationary phase of growth in laboratory culture and under hostile

environmental condition undergo a transition from spiral/rod shape (RF) to coccoid

form (CF) (Moran and Upton, 1987). This transition is induced by stresses such as

starvation, suboptimal temperature, pH, and osmotic stress (Reezal et al., 1998; Ikeda

and Karlyshev 2012). These coccoid cells are non-motile, low cultivability in laboratory

condition and may lead to viable but non culturable phenotype (Oliver, 2005; He and

Chen, 2010). Cell culture-based assay have shown that coccoid C. jejuni are less

virulent than the spiral form and rapidly convert back to spiral form as soon as they

become intracellular (Kiehlbauch et al., 1985). Coccoid cell in C. jejuni have reduced

level of protein synthesis and may lead to programmed cell death as in case of H. pylori

(Benaissa et al., 1996).

1.4.3 Adaptive Tolerance Response (ATR)

Exposure to sub-lethal dose of stresses (pH, temperature, oxidative, bile salts) is known

to induce an adaptive tolerance response (ATR) in several bacterial species which

provides protection to subsequent exposure to lethal dose of same (homologous) or

different (heterologous) stresses (Murphy et al., 2003b). Stress related proteins are

generally overexpressed in ATR which in turn contribute towards providing bacterial

immunity to subsequent exposure of stresses (Bieche et al., 2010). Adaptive tolerance

response helps C. jejuni withstand different stresses like acidic pH, heat and aerobic

stress (Murphy et al., 2003a; Murphy et al., 2003b). Heterologous adaptive response


20

in cold adapted C. jejuni cells helps it to survive not only at 4ºC but also provide

resistant to oxidative stress. Similarly, starvation adapted C. jejuni cells develop

resistance to heat stress via this cross-protection mechanism (Klančnik et al., 2006;

Garénaux et al., 2008).

1.4.4 Genetic Heterogeneity

C. jejuni show a great degree of genotypic plasticity which has been linked to survival

under harsh conditions (Murphy et al., 2006). This genetic diversity can be acquired

through DNA mutation, genetic recombination or by horizontal gene transfer (Arber,

2000).

C. jejuni has been shown to undergo both intra and interspecies genetic recombination

(Dingle et al., 2001; Ridley et al., 2008; Wilson et al., 2009). C. jejuni isolates are

considered highly competent and can easily take up DNA from the surrounding

environment leading to high level of genomic diversity (Vegge et al., 2012). Whole

genome analysis of C. jejuni showed that the bacteria possess many hyper-variable

regions which can be one of the causes of genetic diversity (Parkhill et al., 2000).

Hypervariable regions mainly comprise of tandem repeats of nucleotide (homo-

polymeric tracts) which result in slip stranded mutation and eventual differential

expression of genes related to flagella, capsule and lipo-oligosaccharide (Parkhill et al.,

2000; Hendrixson, 2006).

1.4.5 Biofilm Formation

Biofilms are defined as multilayered bacterial population (belonging to same or

different species) encapsulated in extracellular polymeric matrix composed of proteins

polysaccharides and nucleic acids (Donlan and Costerton, 2002). Biofilms are

irreversibly attached to interface or substratum help bacteria survive under unfavorable

conditions (Costerton, 1995; Donlan and Costerton, 2002, Nguyen et al., 2012;

Turonova et al., 2015). Moreover, theses biofilms provide bacteria resistance to

antibiotics and host defenses (Costerton et al., 1995). Multiple environmental stresses

such as the starvation, iron depletion and oxidative stress may trigger establishment of

biofilms (Yoon et al., 2002; Sauer et al., 2004; Oh et al., 2018).


21

Many strains of C. jejuni have been shown to possess biofilm forming capability, but

degree of biofilm formation varies from strain to strain (Joshua et al., 2006; Kalmokoff

et al., 2006; Gunther and Chen 2009). Morphologically biofilms of C. jejuni can exist

as surface adherent, pellicle or aggregates but the composition of extracellular

polymeric matrix secreted by them is still unknown (Joshua et al., 2006). C. jejuni are

capable of both initiate biofilm formation as well as becoming part of pre-established

biofilm of other bacteria (Hanning et al., 2008). Compared with other biofilm forming

bacteria, C. jejuni are not very strong biofilm former under normal conditions.

However, under aerobic conditions biofilm formation is enhanced in C. jejuni which

not only protects bacteria from harsh conditions but also act as planktonic cell reservoir

(Reuter et al., 2010). C. jejuni can form biofilms on both non-biological (stainless

steel and glass) and biological (human intestinal tissue) substrate which may play an

important part in transmission as well as pathogenesis of the bacterium (Sanders et al.,

2008; Haddock et al., 2010). Better understanding of biofilm formation dynamics in

C. jejuni can lead to development of control measure for its spread and transmission in

food chain.

1.4.5.1 T6SS and Biofilm Formation

The T6SS enhances environmental adaptation and the survival of gram-negative

bacteria (Ho et al., 2014). Biofilm formation helps bacteria contend with harsh

environmental stressors in natural, clinical and industrials setups (Nguyen et al., 2012;

Turonova et al., 2015). The T6SS has a diverse impact on biofilm formation in various

bacteria; in some bacteria, it enhances biofilm formation (Acinetobacter baumannii;

Avian-pathogenic Escherichia coli, Acidovorax citrulli, enteroaggregative Escherichia

coli); in others, it aids in biofilm maturation (Pseudomonas fluorescens) or has no effect

(Vibrio alginolyticus) (de Pace et al., 2011; Tian et al., 2015; Gallique et al., 2017; Kim

et al., 2017). Hcp has been reported to secreted and accumulation in sister cells in a

manner similar to auto-inducer accumulation in quorum sensing (Vettiger and Basler,

2016; Gallique et al., 2017). Bacteria possessing T6SS perceive environmental stress

via T6SS dependent quorum sensing and trigger biofilm formation. (Gallique et al.,

2017). However, the role of T6SS in C. jejuni biofilm formation had yet to be reported.


22

1.5 Control of C. jejuni

Among all reservoirs, poultry has the highest prevalence of C. jejuni and thus is

considered the major cause of campylobacteriosis (Friedman et al., 2000). Studies have

shown that more than 90% of human cases of campylobacteriosis have been associated

with contaminated chicken consumption whereas other sources like water, cattle, wild

animal and pets are responsible for remaining 10% cases (Gillespie et al., 2002, Wilson

et al., 2008). Chicken intestine is the only amplifying point of C. jejuni in the whole

food chain, therefore reduction at poultry level will has the major impact in the spread

of campylobacteriosis (Wagenaar et al., 2006). According to quantitative risk

assessment models, a 2-log reduction of C. jejuni CFU broiler carcass can lead to

reduction of human campylobacteriosis cases by 30 folds (Rosenquist et al., 2003).

Therefore, most of the approaches have been designed to control campylobacteriosis

are targeted to reduce the load of C. jejuni in poultry (Lin, 2009; Ghareeb et al., 2013).

Till date there is no safe, effective, reliable, and practical intervention measure available

to reduce C. jejuni colonization in poultry as well in humans, however some of the

control strategies designed so far are discussed as follows.

1.5.1 Biosecurity Measures

Reduction of chances to exposure of C. jejuni to chickens can prevent colonization in

poultry. General biosafety measures which are known to reduce C. jejuni load in poultry

include physical step-over barriers, pest/rodent management, house-specific

boots/clothing, restricted access to farm and better hygiene of farm workers (Gibbens

et al., 2001; Hald et al., 2007; Newell et al., 2011). Strict implantation of on-farm

biosecurity practices has been shown to reduce C. jejuni prevalence up to 50% at first

slaughter (Gibbens et al., 2001; Katsma et al., 2007; Newell et al., 2011). However,

effectiveness of these measures is dependent upon better knowledge of potential

sources and risk factors associated with poultry (Wagenaar et al., 2006). Moreover,

these measures are costly and unpractical in free-range flocks.

1.5.2 Vaccination

Vaccination of poultry is one of the promising alternate to reduce C. jejuni loads by

enhancing chicken immunity. Live attenuated vaccine, killed whole-cell vaccines and


23

subunit vaccines have been tested for their effectiveness in chicken but have limited

success (Lin, 2009; de Zoete et al., 2007; Saxena et al., 2013). No vaccine has been

marketed till date to reduce the intestinal load of C. jejuni (>2 log units) in broiler

chicken (de Zoete et al., 2007). Similarly, vaccine for human protection against C.

jejuni has been designed based on killed whole cell, recombinant protein and flagellin

antigen but all of them failed to provide protection in Phase II human challenge study.

Live attenuated vaccines are not good choice for human use as lipo-oligosaccharides

(LOS) of many C. jejuni strains can lead to GBS via cross-reactivity with human

peripheral gangliosides (Riddle and Guerry, 2016). Among all current vaccines under

trail, capsule-conjugate vaccine CRM197 as the protein carrier has shown promising

immunogenicity in mice (Riddle and Guerry, 2016). Still new antigens need to be

identified and evaluated to make an effective vaccine against C. jejuni which help to

control spread of campylobacteriosis in both developing and developed countries

1.5.3 Antimicrobial Alternatives

The use of antibiotics as prophylactic and growth promoter in animal feed has resulted

in undesirable consequences such as emergence of multidrug resistant bacteria,

persistence of drug residue in the food and environment. These multidrug resistant

bacteria and antibiotic residue adversely affect human health; therefore, member

countries of the European Union (EU) have banned the use of all antibiotic-based

growth promoters (Cheng et al., 2014). However, this banning resulted in decrease

animal production and quality as well as increased infections among farm animals. To

overcome the resultant increase in morbidity and mortality, several replacement

strategies of antibiotics have been proposed (Seal et al., 2013). Some of the strategies

involve use of bacteriophages, probiotics, prebiotics, synbiotics, antimicrobial peptides

(AMPs), plant extracts and feed enzymes, etc. (Millet and Maertens, 2011).

1.5.3.1 Bacteriophage therapy

Bacteriophages are host specific natural predator of specific pathogenic bacteria which

can be utilized to control infection without effecting the environmental and intestinal

bacteria in poultry (El-Shibiny et al., 2009). Bacteriophages can be easily administered

via oral route and do not produce residues. Campylobacter-specific bacteriophages


24

have been shown to reduce C. jejuni load by 2–3 log units under experimental

conditions in chicken (Lin, 2009). The major concerns of bacteriophages therapy, is

that C. jejuni can readily uptake virulence genes using phage-mediated horizontal gene

transfer and development of quick resistance to phage therapy (Oechslin, 2018).

1.5.3.2 Probiotics and Prebiotics

Probiotics are becoming an attractive antimicrobial alternate for reduction of

colonization of C. jejuni in chicken. Several probiotic microbes such as Lactobacillus

plantarum, Bifidobacterium bifidum, Bacillus subtilius, Lactobacillus gallinarum, S.

cerevisiae and Lactobacillus helveticus etc. have been studied both in isolation and in

cocktail form for their ability to inhibit C. jejuni colonization in animal models

(Johnson et al., 2017). These probiotics use several mechanisms such as competitive

exclusion, modification of microbial community, change in luminal pH, production of

antimicrobial peptides (bacteriocins), enhancement of host barrier defenses, and

alteration of host signaling to reduce growth of pathogenic bacteria in host. Lactic acid

bacteria such as L. acidophilus, L. crispatus, L. gallinarum, and L. helveticus, reduce

the pH of lumen to 4.7, by producing lactic acid, at which the growth of C. jejuni is

inhibited (Bratz et al., 2015). B. subtilius with its enhanced velocity colonizes chicken

gut faster than C. jejuni. Moreover, some of these prokaryotic bacteria can also reduce

colonization of C. jejuni by releasing anti-campylobacter metabolites and by

stimulating host adaptive immunity and gut microbiome. Prebiotics promote growth of

beneficial gut bacteria and have been reported to decrease the load of C. jejuni in broiler

chicken when administered along with consortia of probiotic bacteria (Arsi et al., 2015;

Gracia et al., 2016).

1.5.3.3 Antimicrobial Peptides

Antimicrobial peptides are peptide antibiotics produced by commensal gut bacteria to

inhibit colonization of pathogenic bacteria in host. The antimicrobial peptides disrupt

the bacterial membrane and form a transmembrane pore which eventually leads to cell

death. Bacteriocins are one of such antimicrobial peptides having both narrow and

broad spectrum antibacterial effect host ranges. Several anti-campylobacter

bacteriocins (OR-7, SRCAM 602, E-760, E 50–52), produced by chicken gut bacteria,


25

have shown excellent ability to reduce C. jejuni load up to 8 logs in chickens (Stern et

al., 2005; Stern et al., 2006; Line et al., 2008; Svetoch et al., 2008). Despite their

effectiveness in controlling C. jejuni load at farm level, emergence of bacteriocins

resistance among C. jejuni is a major concern in administration of antimicrobial

peptides. Functional genomic analysis has shown that some C. jejuni strains harbor a

group of genes which may confers resistance to antimicrobial peptides, thus reducing

the effectiveness of this strategy in future (Hoang et al., 2012).

1.5.3.4 Natural Antimicrobial Compounds

Over the past few decades there has been decreased acceptability among consumers of

administration of synthetic additives in food chain which has led to development and

use of natural antimicrobial compounds as animal feed additive (Verbeke et al., 2007;

Brenes and Roura, 2010; Navarro et al., 2015). Several plant extracts have shown anti-

campylobacter activity including clove, basil, cinnamon bark, garlic, capsicum, lemon,

lemon grass, orange, rosemary, sage, thyme and oregano (Navarro et al., 2015). These

active compounds in these plants are mainly phenolics (anethole, carvacrol,

cinnamaldehyde, curcumin, eugenol, thymol, and vanillin), acids (rosmarinic and

carnosic acids) and organosulfur compounds (Lu et al., 2011; Klanènik et al., 2012;

Navarro et al., 2015). Due to its low cost and toxicity, natural anti-campylobacter

compounds offer a promising strategy for the control of C. jejuni in chicken.


26

1.6 Aims and Objectives

The present study was designed to study three aspects of C. jejuni. First aim was to

determine the extent of C. jejuni infections among pediatric patients by evaluating the

antibiotic resistance and source tracking of the isolates. Second aim was to study the

role of type VI secretion system in stress adaptation in general by comparing biofilm

formation of T6SS positive and negative isolates in response to stresses; more

specifically by determining the structure and function of Hcp protein (both in biofilm

formation and pathogenesis). Third aim was to develop control strategies against C.

jejuni which included in-silico drug target identification, nanocarrier based targeted

delivery of natural anti-campylobacter products as an on-farm control strategy to reduce

load of C. jejuni among chicken and metallic nanoparticles as a coating material for

control of C. jejuni biofilms.

This study will provide a better insight into the role of T6SS in C. jejuni in stress

adaptation which will, in future, help prevent persistence of C. jejuni in the

environment. Moreover, the control strategies proposed in this study will lead to

development of effective preventive approach to control C. jejuni both at farm and food

processing level which will in turn help reduce the burden of campylobacteriosis in

humans.

Chapter 2 Materials and Methods

27

Chapter 2

Materials & Methods


28


Isolates from Paediatric Diarrhoeal Cases

2.1.1 Sample Collection

A total of one hundred and fifty human diarrhoeal stool samples (including both non-

bloody and bloody diarrhoeal cases) were collected from hospitalized pediatric patients

from November 2014 to September 2015. Children’s age varied from 2 months to 5

years. All the cases were domestic in origin. Stool samples were collected and

transported in sterile cotton swabs containing Carry-Blair medium to Microbiology and

Public Health Laboratory of COMSATS University, Islamabad. The samples were

processed within 24 h of collection.

2.1.2 Isolation of C. jejuni

The fecal samples were streaked onto modified charcoal cefoperazone deoxycholate

agar (mCCDA) (Oxoid, CM0739) amended with CCDA selective supplement (Oxoid,

SR0155). The processed samples were incubated for 48-72 h at 42°C under

microaerophilic conditions generated by Campygen sachets (Oxoid, CN025A).

Colonies having translucent and watery morphology were selected as suspected

colonies belonging to Campylobacter spp. and were sub-cultured on Muller Hinton

Agar plates (Oxoid, CM0337) supplemented by 5% sheep blood (Siddiqui et al.,

2015a). Glycerol stocks (20%) of the purified cultures were made using brain heart

infusion broth (Oxoid, CM11035) and stored at -80ºC.

2.1.4 Biochemical Identification of C. jejuni

Suspected colonies of C. jejuni were preliminary identified using biochemical tests i.e.,

oxidase, indoxyl acetate, catalase and hippurate hydrolysis test. Strains showing

positive test results of all these four reactions were further processed for molecular

analysis (Chaban et al., 2010).


29

2.1.5 PCR based for the Detection of C. jejuni

2.1.5.1 DNA Isolation

Phenol-chloroform method was used to isolate DNA from suspected C. jejuni colonies

(Englen and Kelley, 2000). Briefly, fresh grain size C. jejuni growth were picked and

washed with 1 ml STE buffer [150 mM NaCl, 10 mM Tris-HCl, 15 mM EDTA (pH

8.0)]. The cell suspension was centrifuged for 5 minutes at 4659 x g and the resultant

pellet was then dissolved in 570 µL of STE buffer supplemented with 30 µL Sodium

dodecyl sulfate (SDS) and 3 µL of proteinase K (20 mg/ml stock). The suspension

was briefly mixed and incubated for 2 h at 50oC. Then, 600 µL of PCI [phenol (25):

chloroform (24): isoamyl alcohol (1)] was thoroughly mixed with the suspension and

the mixture was centrifuged at 12,300 x g for 8 min. Approximately, 550µL of upper

aqueous phase was aspirated and added to a new 1.5 ml tube. An equal volume of

chloroform was added followed by thorough mixing and centrifugation at 12,300 x g

for 8 minutes. This washing step with chloroform was repeated twice. The upper phase

(approx.500 µL) was collected in new tube to which 50 µL sodium acetate (3M, pH

5.3) and 1 ml absolute ethanol was added followed by incubation at –20oC for 30 min.

Precipitated DNA was separated by centrifugation at 12,300 x g for 10 min and finally

resuspended in 200 ml of TE buffer (10 mM Tris-HCl, 1 mM EDTA, pH 8.0) containing

RNase at 10 mg/ml. After incubation for 1 h at 37oC, the purified DNA was stored at –

20oC.

2.1.5.2 Species Specific PCR

C. jejuni was detected in the samples based on the amplification of species specific gene

i.e., hippurate hydrolysis gene using oligonucleotide primers (Harrison et al., 2014).

The primers and conditions used are listed in Table 2.1. PCR amplification was done

using 25 µL reaction mixture comprising of 3 µL isolated DNA, 1X PCR buffer

(Fermentas, UAB), 200 µM of each of dNTPs (Fermentas, UAB), 2.5mM of MgCl2

(Invitrogen), 0.4 µM of each primer, 0.25 U of Taq DNA polymerase (Fermentas,

UAB). The rest of the volume was attained with nuclease free water. The PCR reaction

was carried out in a MJ MiniTM Thermocycler (Bio-Rad, USA). C. jejuni strain 255

(Siddiqui et al., 2015) was used as a positive control in the PCR. The PCR products

were loaded onto 2% agarose gel and run at 100V for 35 mins along with 100 bp DNA


30

ladder (Fermentas, Lithuania, UAB). BDA digital gel documentation system (Core Life

Sciences, CA) was used for visualization of amplified PCR products.

2.1.6 Antimicrobial Resistance Profiling

Antibiotics resistance pattern of C. jejuni isolates were assessed by Kirby-Bauer disc

diffusion method. Detection metallo Beta lactamase in C. jejuni isolates was done using

combined disk method and PCR based on resistance genes. Details of these methods

are described below.

2.1.6.1 Kirby-Bauer Disc Diffusion Method

Antibiotic resistance profiling of the identified C. jejuni isolates was carried out using

the following antibiotics: Ceftriaxone (30µg) Ampicillin (10µg), Chloramphenicol (C)

(30 µg), Tetracycline (TE) (30 µg), Streptomycin (S) (10 µg), Ciprofloxacin (CIP) (5

µg), Nalidixic acid (NA) (30 µ g), Erythromycin (E) (30 µg), Gentamycin (CN) (10

µg), Sulphomethoxazole + trimethoprim (SXT) (25 µg), Tigecycline (15µg), Imipenem

(10µg) and Colistin (Oxoid, UK) as described by Fariha et al., 2015. The analysis of

zone diameter was done according to the CLSI (2010). Multiple antibiotic resistance

(MAR) was calculated using the following formula

MAR Index = a/b

Where ‘a’ is the number of antibiotics to which an isolate is resistant and ‘b’ is the total

number of antibiotics tested (Riaz et al., 2011).

2.1.6.2 Detection of Metallo-β-Lactamase

Phenotypic identification of Metallo-β-lactamase (MBL) enzyme in imipenem resistant

isolates was detected according to the combined disk method (CDT) (Yong et al.,

2002). Briefly overnight cultures of the imipenem resistant strains were exposed to one

imipenem (10 µg) alone and one imipenem (10 µg) disk amended with 750µg of

ethylene diamine tetra-acetic acid (EDTA). These disks were placed 25mm apart on

Muller Hinton plates. An increase of ≥7mm in the zone size of imipenem compared to

imipenem-EDTA disk after incubation of 24 h was used as a confirmation of a metallo-

β-lactamase positive organism. A multiplex PCR was used to verify the presence MBL

genes at molecular level. Five primer pairs, specific for each family of acquired MBLs,

were used for detection of IMP (188bp), VIM (390 bp), SPM (271 bp), GIM (477 bp)


31

and SIM (570 bp) (Ellington et al., 2007). The details of primers and conditions used

are listed in Table 2.1. PCR amplification was done using 25 µL reaction mixture

comprising of 2 µL DNA, 1X DreamTaq Green PCR Master Mix (Thermo Scientific),

and 0.2 µM of each primer. The PCR reaction was carried out in a MJ MiniTM

Thermocycler (Bio-Rad, USA). The PCR products were run on 2% agarose gel at 100V

for 30 mins along with 100 bp DNA ladder (Fermentas, UAB). BDA digital gel

documentation system (Core Life Sciences, CA) was used for visualization of the

amplified PCR products.

2.1.7 Source Attribution

To predict the possible origin of these C. jejuni in human samples, source predictive

markers were used as described by Stabler et al. (2013). Six source discriminatory

genes i.e., Cj0056c (415 bps; hypothetical protein), Cj0485 (406 bps; putative

oxidoreductase), Cj1139c (703 bps; beta- 1, 3 galactosyltransferase), Cj1324 (765 bps;

hypothetical protein), Cj1422c (900 bps; putative sugar transferase), and Cj1720 (595

bps; hypothetical protein) were amplified in two sets of multiplex PCRs (M1 and M2).

The strain Cj255 was used as a positive control. The detail of primers and conditions

used are listed in Table 2.1. The PCR amplification was done using 25 µL reaction

mixture containing 2 µL DNA, 1X DreamTaq Green PCR Master Mix (Thermo

Scientific) and 0.2 µM of each primer. The PCR reaction was carried out in a MJ

MiniTM Thermocycler (Bio-Rad, USA). The PCR products were loaded onto 2%

agarose gel and run at 100V for 30 mins along with 100 bps DNA ladder (Fermentas,

UAB). BDA digital gel documentation system (Core Life Sciences, CA) was used for

visualization of the PCR products. The results of PCR were converted into binary data

and were clustered with the help of binary code provided by Stabler et al., 2013.


32

Table 2.1: Detail of Primers and PCR conditions used in this study

Primers Product

size

Annealing

Temp (ºC)

Reference

Species specific primer

HipO-F

GACTTCGTGCAGATATGGATGCTT

HipO-R

GCTATAACTATCCGAAGAAGCCATCA

344 bp 59 Persson and

Olsen, 2005

Metallobeta-lactamase detection primers

Imp-F GGA ATA GAG TGG CTT AAY TCT

C

Imp-R CCA AAC YAC TAS GTT ATC T

188 bp

52 Ellington et

al., 2007

Vim-F GAT GGT GTT TGG TCG CAT A

Vim-R CGA ATG CGC AGC ATC CAG

390 bp

Spm-F AAA ATC TGG GTA CGC AAA CG

Spm-R ACA TTA TCC GCT GGA ACA GG

271 bp

Gim-F TCG ACA CAC CTT GGT CTG AA

Gim-R AAC TTC CAA CTT TGC CAT GC

477 bp

Sim-F TAC AAG GGA TTC GGC ATC G

Sim-R TAA TGG CCT GTT CCC ATG TG

570 bp

Source Prediction Primers

M1

Cj0056-cl-F GAAAGAAGTGAAGGGTGGGT

Cj0056-cl-R

TTATTCAAAGACAGGACTTGA

Cj1139-cl-F ATGAGTCAAATTTCCATCAT

Cj1139-cl-R GTTCTTGAATATTAGCTTCT

Cj1422-cl-F ATGCTCAACCCAAATTCAGC

Cj1422-cl-R

GCAAATTTTAAATCATTGCATG

415 bp

703 bp

900 bp

53 Stabler et al.,

(2013)

M2

Cj0485-cl-F

GATCTATGCCTAAAGAGCACG

Cj0485-cl-R

TCCTTAGCAAAAGCACAAGCC

Cj1324-cl-F GTGATCACTGCGTGATGCCA

Cj1324-cl-R

CAGTAAAACCACGACTTTTAGC

Cj1720-cl-F AAATGGAACCTGTTATCCAC

Cj1720-cl-R TCAACCTCCACCGATAAAGT

406 bp

765 bp

595 bp

.


33


Negative C. jejuni Isolates

2.2.1 Growth of Bacterial Strains

To study the role Type Six Secretion system in stress adaption five T6SS positive and

five T6SS negative isolates (reported by Siddiqui et al., 2015) were selected and were

grown on mCCDA agar plates as described in section 2.1. These strains were then used

in the following studies

2.2.2 Determination of Sub-lethal Level of pH, Temperature and Oxidative

Stress

Overnight cultures of C. jejuni were adjusted at an optical density of 0.05 (approx. 107

CFU/ml) using BHI broth and was used for following stress assays. To determine sub

lethal level of acidic stress, the bacterial strains were exposed to different pH (2.5, 3.5,

4.5, 5.5, 7.0) followed by incubation for 15 min at 42oC under microaerophilic

conditions. The cells were harvested by centrifugation for 5 min at 3000 x g and washed

twice with phosphate buffer saline (PBS). The cells were then re-suspended in fresh

BHI and viable cell count was done after serial dilution. To calculate the sub-lethal

temperature, the bacterial strains were exposed to different temperatures i.e., 42oC,

50oC, 55oC and 60oC for 15 min under microaerophilic conditions. The cultures were

serial diluted and plated to count viable cell count. To determine the sub-lethal level of

oxidative stress the bacterial strains were exposed to of H2O2 (2-12mM) for 15 min

after which the cells were washed twice and CFU count was done as described above.

The stress level which reduced the cell viability to 50% was considered as a sub-lethal

dose.

2.2.3 Motility Assay

Motility assay was performed on 0.45% Muller Hinton (MH) agar as described by

Golden and Acheson (2002). In brief, Optical density of C. jejuni suspension was

adjusted to 0.05 (~107 CFU). Five µL of the stress induced and normal cultures were

stabbed in Muller Hinton (MH) agar. The plates were incubated at 42ºC under

microaerophilic condition for 48 h and zone of motility (diameter) was measured in

mm.


34

2.2.4 Hydrophobicity Assay

To study the effect of sub-lethal stresses on C. jejuni hydrophobicity, stress induced

and un-induced cells (107 CFU) were inoculated in Brain heart infusion (BHI) broth

and allowed to grow at 42 ºC for 24 h under microaerophilic conditions. The cells were

harvested in phosphate buffer saline (PBS, pH 7.2) (Ht0 OD570= 0.5). The bacterial

suspension was then mixed with n-hexadecane and incubated for 5 min at room

temperature (Rosenberg et al., 1980; Thies and Champlin, 1989). The optical density

of the aqueous phase was measured at 570 nm (Ht5) using a microtiter plate reader.

Hydrophobicity was calculated by the equation:

Hydrophobicity (%) = (1-Ht5/Ht0) x 100

2.2.5 Auto-aggregation Assay

To study the effect of sub-lethal stress on auto-aggregation, the stress-induced and un-

induced bacterial cells were grown for 24 h at 42ºC under microaerophilic conditions

(Collado et al., 2007). The cells were harvested and re-suspended in PBS (pH 7.2) to

adjust the OD570 to 0.5 (At0). Saline bacterial suspensions were incubated at 42ºC for 2

h. O.D of supernatants was assessed (At2) and aggregation potential calculated by the

following formula:

Auto-aggregation (%) = (1-At2/At0) x 100.

2.2.6 Biofilm Assay

Biofilm formation by stress induced C. jejuni cultures was studied using method

described by O’Toole and Kolter, 1998. Briefly overnight culture of bacterial were

adjusted to an O.D600 of 0.05 (~107 CFU) and exposed to the sub-lethal dose of either

of these stresses i.e., pH 4.5, Temperature 55ºC or 8 mM of H2O2. One ml of each of

these stress induced cultures was incubated for 48 h in sterile borosilicate glass tubes at

42ºC under microaerophilic conditions. After incubation, the planktonic cells were

discarded, and the tubes were gently washed thrice with PBS. The biofilms were stained

using 0.1% Crystal violet (Sigma) for 15 min and then excess stain was vigorously

washed with distilled water. The stained adherent cells were suspended in 80%

dimethyl sulfoxide (DMSO). The quantification of biofilm was carried out using UV-

VIS spectrophotometer at a wavelength of 570 nm. All the experiments were done

thrice, and each sample was tested in triplicate.


35


T6SS

2.3.1 Plasmids and Bacterial Strain

The hcp gene (534bp) of C. jejuni was synthesized by Genscript (USA) in pET-22b

plasmid and was transformed into DH5α for propagation. The plasmid was then isolated

and transformed in BL21 (DE3) for expression of Hcp protein. The construct is shown

in Fig 2.1.

2.3.2 Point Mutations

Site-specific mutations in Hcp were introduced at positions 30 and 31 the extended loop

(L2,3) of hcp protein to generate HcpR30A and HcpY31A mutants by overlapping PCR

as previously described (Ho et al., 1989) and verified by the DNA sequencing. Breifly,

Mutant Hcp proteins were generated using the proof reading HiFi PCR kit (Kapa

Biosystems). The PCR amplification was done using 50 µL reaction mixture

comprising of 1 µL plasmid DNA, 1X Hifi Fidelity Buffer PCR buffer, 300 µM of each

of dNTPs (KAPA dNTP Mix), 0.3 µM of each T7 forward and reverse primer, 0.5 U

of HiFi DNA Polymerase and rest of the volume was attained with nuclease free water.

The PCR reaction was carried out in a MJ MiniTM Thermocycler (Bio-Rad, USA). The

PCR amplification conditions were initial denaturation of template DNA at 95ºC for 3

min; followed by 30 cycles of denaturation at 98ºC for 20 sec, annealing at 58ºC for 20

sec, and elongation step at 72ºC for 3 min; and a final extension at 72ºC for 5 mins. The

PCR products were loaded onto 1% agarose gel containing Syber safe (Thermo Fisher

Scientific) and run at 100V for 35 mins. The product was carefully cut with sterile blade

and was purified by E.Z.N.A.® Gel Extraction Kit. The purifed product was digested

using DpnI using 1x FD buffer followed by incubaction for 1 h. at room temperature.

Ten microliter of the digest was transformed in DH5α competent cells. The clones were

verified by DNA sequencing using Applied Biosystems 3130xl sequencer. Briefly, in

5 µL of reaction mixture was prepared using 100ng of template DNA (isolated from

mutant clones), 1 µM of either T7 forward or reverse primer and 1 µL BigDye® Ready

Reaction Mix. PCR was performed using following conditions: initial denaturation at

96°C for 1 minute followed by 35 cycles of denaturation at 96°C for 10 seconds,

annealing at 50°C for 5


36

Fig. 2.1 Pet22b+ construct showing the insertion site of Hcp gene


37

seconds, extention at 60°C for 4 minutes 4°C. The product was cleaned up by intial

precipitation using absolute ethanola and 3M sodium acetate folllowed by twice

washing with 70% ethanol. Ethanol was dried at 52 °C for 5 min and resuspended in

18ul of Hi-Di™ Formamide (Thermo Fisher Scientific). The mixture was dispensed in

96 well plate and analyzed using Applied Biosystems 3130xl sequencer.

2.3.3 Expression and Purification of Recombinant and Mutant Hcp Protein

Primary culture of BL21 carrying Hcp protein was prepared by inoculating single

colony of transformed cells in 100 ml of LB medium with 100 μg/ml ampicillin,

followed by incubation for 16-18 h. Twenty-five ml of this primary culture was used to

inoculate 1L of LB broth containing 100 μg/ml ampicillin and was allowed to grow at

37°C till an OD600 of 0.6 was attained. The culture was then induced using 0.3 mM

Isopropyl β-D-1-thiogalactopyranoside (IPTG, Sigma Aldrich) followed by incubation

at 16°C for 18h. The bacterial cells were harvested by centrifugation at 4000× g for

20 min at 4°C. The pellet was re-suspended in lysis buffer containing 50 mM Tris, pH

7.5, 200 mM NaCl, 5% glycerol, 5 mM DTT, 0.1% (vol/vol) Triton X-100, and one

tablet of complete protease inhibitor mixture (Roche Diagnostics). Following

sonication, the cell lysate was centrifuged at 20,000 × g for 10 min at 4°C and the clear

cell lysate was bound to Ni-NTA affinity beads pre-equilibrated with 200 mM NaCl,

50 mM Tris-HCl [pH 7.5], 5 mM DTT and 20 mM Imidazole. The protein was eluted

from the column using buffer containing 600 mM of imidazole. The Hcp protein was

further purified using a Superdex-200 column (GE Healthcare, UK) pre-equilibrated

with a buffer comprising of 50 mM NaCl, 50 mM Tris-HCl (pH 8.0), 2 mM DTT and

5% w/v Glycerol. Amicon Ultra 10,000 MCWO centrifugal filter units (Millipore) were

used to concentrate pooled peak fractions up to 20 mg/ml. The purified product was

analyzed by 12.5% SDS-PAGE and verified by Mass spectroscopy.

2.3.4 Dynamic Light Scattering (DLS)

Dynamic Light Scattering (DLS) is used to determine the homogeneity of the protein

as proteins which show extensive aggregation are difficult to crystallize under normal

circumstances. DLS measurements of the purified protein were performed on a

DynaPro at room temperature as described by Jobichen et al., 2010.


38

2.3.5 Crystallization and Structure Determination

The initial crystallization conditions for the protein were identified by Index Screens

(Hampton Research) using the hanging-drop vapor-diffusion technique at 25°C.

Crystallization drops containing 1 µl protein solution (10 mg/ml) and 1 µl reservoir

solution were used. The diffraction quality crystals were obtained with the condition

consists of 0.2 M sodium acetate trihydrate, 0.1 M Tris-HCl (pH 8.5) and 32%

Polyethylene glycol after two days. Crystals were cryoprotected in the reservoir

solution supplemented with 25 % glycerol and flash cooled at 100 K. The Hcp-Cj

crystals diffracted to 2.8 Å resolution. A complete dataset was collected using a

Saturn944 CCD detector mounted on Rigaku X-ray generator and in the National

Synchrotron Light Source II, New York, USA. The data set was processed and scaled

using HKL2000 (Otwinowski and Minor, 1997). The structure of secreted protein Hcp3

from Pseudomonas aeruginosa (PDB code 3HE1) was used for molecular replacement

using the MORDA program. There were six molecules in the asymmetric unit. The

resultant electron density map was of good quality. Several cycles of model

building/refitting using the program Coot (Emsley and Cowtan, 2004), and alternated

with refinement using the program Phenix (Adams et al., 2010), lead to the convergence

of R-values. Non-crystallographic symmetry (NCS) restraints were used throughout the

refinement process.

2.3.6 Cytotoxicity towards Prokaryotic Cells

To determine the toxicity of Hcp-Cj towards other bacteria, overnight cultures of E.

coli (DH5α) and T6SS negative strains of C. jejuni (strain ID 301 and 27 from our

previous study) were incubated with 50 µg/ml of purified Hcp proteins (Siddiqui et al.,

2015). The samples were serially diluted and spotted on LB agar (DH5α) and mCCDA

(C. jejuni) agar. Growth of bacteria in terms of CFU/ml was recorded after 24-48h of

incubation. The cytotoxicity assays were done in collaboration with Institute of

Biomedical and genetic Engineering, KRL Hospital Islamabad.

2.3.7 RBC Lysis Assay

RBC lysis assay was done using Sheep erythrocytes prewashed thrice with phosphate

buffer saline (pH 7.5) and adjusted to a final concentration of 1% (v/v). The erythrocyte


39

suspension (0.1 ml) was incubated with 50 µg/ml of purified Hcp protein for 4 h at

37°C. The samples were then centrifuged at 1,000 × g for 5 min and optical density of

the supernatant was measured at 550nm as an indicator of hemolysis degree (Moonah

et al., 2014).

2.3.8 Cytotoxicity towards Eukaryotic Cells (HepG2)

Cytotoxicity of purified Hcp protein against HepG2 (Liver Cancer cells) was evaluated

using sulforhodamine B (SRB) assay as described by Skehan et al., (1990). Briefly,

pre-seeded HepG2 cells (1.2 x 104 cells/well) were exposed to 50 µg/ml of normal and

mutant Hcp protein per well and incubated for 24 h at 37°C in 5% CO2 incubator. The

cells were then fixed using pre-chilled trichloroacetic acid (50%) at 4°C for a period of

1 hour and subsequently washed 5X with deionized water. The cells were stained with

SRB solution (0.4%) for 30 min at room temperature washed with 1% acetic acid and

air dried. The air-dried samples were photographed using Olympus IMT-2 inverted

microscope. The dye incorporated in the samples was solubilized in Tris (10 mM, pH

8.0) and absorbance (565 nm) was measured using microtiter plate reader (AMP

PLATOS R-496). Untreated cells were used as negative control.


The motility of bacterial strains in response to Hcp-Cj exposure was compared using

method described by Golden and Acheson, 2002. Briefly, semi-solid BHI plates

(0.45%) were inoculated in the center with 5 µl of culture (pre-exposed to Hcp-Cj). The

bacterial strains unexposed to Hcp-Cj and PBS were used as controls. After incubation

of 48 h the diameter of growth zone was measured.

2.3.10 Biofilm Assay

To study the effect of Hcp-Cj on biofilm formation overnight cultures of C. jejuni

(T6SS positive strains (255, 77); T6SS negative isolates (301, 27) and E. coli (DH5α)

were exposed to 50 µg/ml of purified recombinant Hcp and mutant proteins in 96-well

polystyrene plates (Corning™ Costar™ Clear Polystyrene 96-Well Plates) for a period

of 24 hours (O’Toole and Kolter, 1998). After incubation, the planktonic cells were

discarded, and the wells were washed thrice with PBS. The biofilms were stained with

Crystal violet (0.1%) (Sigma) and then excess stain was washed with distilled water.


40

The stained biofilms were dissolved in dimethyl sulfoxide (DMSO). Quantification of

biofilm was carried out using microtiter plate reader at a wavelength of 570nm. All

assays were performed in triplicate.

2.4 In silico Drug Target Identification of C. jejuni

2.4.1 Complete Proteome Retrieval

The complete proteome sequences of C. jejuni (NCTC 11168) and H. sapiens were

downloaded from UniProtKB (www.uniprot.org).

2.4.2 Determination of Non-Homologous Essential Genes/Proteins

Total proteins of C. jejuni were subjected to BLASTP against humans using threshold

expectation value (E-value 10−3) (Kerfeld and Scott, 2011). The protein sequences

which showed significant homology to human were eliminated and the remaining

proteins were considered as non-homologous sequences. Database of essential gene

(DEG) contain dataset of essential genes and their expressed proteins of 20 bacteria

(Zhang and Lin, 2009). The non-homologous protein sequences were subjected to

BLASTP against DEG (E-value 10−5) and minimum bit score cut off 100 to find out

essential genes (Acharya and Garg, 2016) (Fig 2.2). The protein which had significant

hit was then considered as non-homologous essential genes or Set 1.

2.4.3 Metabolic Pathway Analyses

KEGG metabolic pathway analysis helps identify proteins which are involved in unique

or common pathway (between host/s and pathogen). The metabolic pathway of the

proteins in Set 1 was analyzed by performing a BLASTP similarity search against

periodically updated KEGG database (Moriya et al., 2007). Proteins involved in

metabolic pathways were selected for further analysis (Set 2)

2.4.4 Drugability Potential of Shortlisted Proteins

Drug Bank database contains number of protein targets with respect to the drug IDs

approved by FDA (Wishart et al., 2006). In order to reach the novel drug targets, default

parameter for screening of protein sequences in Set 3 as potential drug target was done

by BLASTP (E-value 10−3) comparison against Drug Bank database. The proteins

http://www.uniprot.org/


41

which showed significant hits against both approved and experimental drugs were

classified as Set 3.

2.4.5 Prioritization of Druggable Targets

2.4.5.1 Functional Categorization

Functional family prediction of proteins in Set 3 was done by using InterPro server

which uses the primary sequence of protein to group them into families and predict the

presence of domains and important sites. Proteins sequences which were classified as

enzymes were listed (Mulder and Apweiler, 2007).

2.4.5.2 Virulence Factor

The potential targets were analyzed for their role in virulence potential of C. jejuni by

using BLASTP against using Virulence Factor DataBase (VFDB) which comprises of

virulence factors of 24 genera of pathogenic bacteria (Chen et al., 2012).

2.4.5.3 Molecular Weight

The identified targets were characterized on the basis for their molecular weight using

UniProtKB as most drug-able targets are of ≤110 kDa (Butt et al., 2012).

2.4.5.4 Subcellular Localization

Sub cellular localization of non-homologous essential proteins was predicted using

PSORTb v.3.0 (Nancy et al., 2010) into five major localization sites viz. cytoplasmic,

periplasmic inner membrane, extracellular, and outer membrane. The results were

further validated by CELLO v2.5. TMHMM server to identify transmembrane helices

in the proteins using Hidden Markov Model (HMM) based tool (Krogh et al., 2001).

2.4.5.5 Availability of Protein 3D Structure

Protein Data Bank and ModBase databases were used to find the experimentally and

computationally solved 3D structures of the proteins in Set 5 respectively (Berman et

al., 2007; Pieper et al., 2006).


42

Fig. 2.2 The overall scheme for identification of drug targets


43

2.4.5.6 Chicken Proteome Homology Analysis

Shortlisted drug targets were subjected to BLASTP against Gallus gallus (chicken)

using threshold expectation value (E-value 10−3) (Altschul et al., 1990). Protein

sequences which showed significant homology to chicken proteome were eliminated

from further analysis

2.4.5.7 Gut Flora Non-Homology Analysis

Normal gut flora of humans includes approximately 1014 harmless microorganisms,

which help maintain human health by providing protection against pathogenic bacteria

(Fujimura et al., 2010). The use of drug which results in inhibition of these beneficial

bacteria along with the pathogen will eventually adversely affect the host. To prevent

such adverse reactions from drug, the shortlisted drug targets were subjected to

BLASTP against a list of gut flora proteome (E-value=0.0001) reported by Altschul et

al., 1990 and Raman et al., 2008 for homology search. The proteins which showed

homology to less than 10 hits were selected as potential targets (Shanmugham and Pan,

2013).


Encapsulated Alginate-Chitosan Nanoparticles

2.5.1 Screening of Plant Extracts for Anti-Campylobacter Activity

Five plants i.e., Berberis lycium (bark), Trachyspermum annum (seeds), Nigella sativa

(Seeds), Camellia sinensis (leaves), Mentha longifolia (leaves) were screened for their

antibacterial activity against C. jejuni. Plant parts of these plants (bark, seed or leaves)

purchased from local market of Islamabad, Pakistan and were dried in shade. The plant

material was then grounded and passed through 100 mm sieve to get a fine powder.

The resultant fine powder (50g) was soaked in 200 ml of methanol for 5 days and was

filtered first through double layers of muslin and then by Whatman filter paper No.1.

The clear filtrate was dried by rotary evaporator and the yield was measured. The stock

solution of 50 mg/ml of plant extracts were made in DMSO and then tested for its anti-

campylobacter activity using agar well diffusion method (Sokmen et al., 2013). Briefly,

overnight culture of C. jejuni was spread on MH plates and 10mm well were made by


44

sterile corker borer. 100µL of stock solutions was added to each well and the petri plates

were incubated under microaerophilic condition at 42ºC. Zone of inhibition was

measure after 48 h. Ampicillin was used as control.

2.5.2 Fractioning of Trachyspermum ammi

To determine the active fraction of T. ammi seeds, crude methanolic extract was

subjected to bio-guided fractionation as described by Shah et al., 2014. Briefly, the

dried crude extract (5g) was suspended in distilled water (200 ml) and was subject to

sequential partition (1:1, v: v) with n-hexane, chloroform, ethyl acetate, acetone, and n-

butanol as indicated in Fig 2.3. The leftover residue after the last fraction was classified

as aqueous fraction. Each fraction was concentrated using rotary evaporator and dried

under dark.

2.5.3 Antibacterial activity of Trachyspermum ammi Fractions

2.5.3.1 Determination of Minimum Inhibitory Concentration

The Minimal Inhibitory Concentration (MIC) of all fractions of Trachyspermum ammi

was determined by “Micro-titer assay” (Sarker et al., 2007) using 2, 3, 5- triphenyl

tetrazolium chloride (TTC) as an indicator of metabolic activity. Various doubling

concentrations of each fraction of T. ammi were made in DMSO i.e., 0.312, 0.625, 1.25,

2.5, 5 and 10 mg/ml. Twenty micro liters from the stock solutions was added to 180 µl

of bacterial suspension (108 CFU/ml) such that each test compound was checked at the

final concentration of 1.0, 0.5, 0.125, 0.0625 and 0.0312 mg/mL in respective well of

microtiter plate. After incubation of 48 h, 20 µl of TTC indicator solution (prepared as

5 mg/ml in H2O) was added to each well and change in color was recorded after 15-20

min. Pink color indicated the presence of viable bacteria whereas no change in color

was considered as nonviable bacteria. Twenty micro liters from each of the well with

no color change were inoculated on to nutrient agar plate. The experiment was repeated

thrice and the average of three readings was calculated as MIC for the test compound.

2.5.3.2 Influence on Growth of Bacteria and Cell Survival

Overnight culture of the C. jejuni (~107 CFU) were used to inoculate Brain Heart

Infusion (BHI) broth media with and without addition of hexane fraction of T. ammi


45

Fig. 2.3 Scheme of Fractioning of Trachyspermum ammi seed extract adapted

from Shah et al., 2014.


46

(concentration 2x less than MIC) in the individual flasks. The culture flasks were placed

in shaker incubator (100rpm) at 42ºC. To study the influence on growth of bacteria,

samples were drawn at regular time interval of 30 min. Each drawn sample was serially

diluted, and these dilutions were spotted on Muller Hinton Agar plate. The colony

forming units (CFU) were counted after 48h of incubation. The un-inoculated media

was used as negative control.

2.5.4 Gas Chromatography- Mass Spectroscopy Analysis

The GC-MS analysis of n-hexane fraction of Trachyspermum ammi seeds was

performed using a GC-Mass spectrometer system (Model, Thermo GC-Trace ultra-

version 5.0; Department of Chemistry Quaid-iAzam University Islamabad) equipped

with a fused silica gel column (30 m×0.25mm ID, film thickness 0.25 µm) coupled with

a Thermo MS DSQ-II (Thermo Fisher, USA). The detection of data or spectra was done

using an electron ionization system with ionization energy of 70 eV. The n-hexane (l00

mg/ml) was filtered with 0.22 µm Millex membrane filter paper (Millipore, France) to

remove any dust/suspended particles before injection. One ml of the sample was

injected at a rate of 1 μl/min using split mode. Oven temperature was programmed from

50 to 280 °C at 10 °C/min increment. Helium gas was used as a carrier at rate of 1.5

ml/min and detection limit was set at 50-800 amu. The constituents of the n-hexane

fraction of Trachyspermum ammi seeds were identified by comparing their mass spectra

with NIST 02 spectral library. The relative percentage (%) of each constituent was

expressed in terms of percentage by peak area.

2.5.5 Preparation Plant Extract Loaded Alginate Coated Chitosan

Nanoparticles as a Nanocarrier System for Targeted Delivery

pH sensitive alginate coated chitosan nanoparticles were prepared for targeted delivery

of plant extract (hexane fraction) to the intestine of chicken gut to prevent degradation

at acidic pH of gizzard. From hereafter, the term “plant extract” refers to the hexane

fraction of Trachyspermum ammi seeds. Chitosan (92% deacetylated-Sigma) was

dissolved in 1% (v/v) aqueous acetic acid solution at concentration of 3 mg/ml by

stirring at 400rpm for 2 h at 60ºC. An aqueous solution of 0.2% Sodium

tripolyphosphate (Sigma, USA) was prepared in deionized water. TPP was added drop


47

wise into Chitosan solution in a ratio of 3:1 (Chitosan: TPP) under continuous stirring

at 400rpm for spontaneous formation of Chitosan nanoparticle (CNP). The CNP was

isolated by centrifugation 4000g for 20 min and pellet was stored after suspending in

deionized water. To prepare plant extract loaded chitosan nanoparticles (PE-CNP),

30mg of hexane fraction plant extract was dissolved in TPP solution which was then

drop wise added in chitosan solution and processed as above. For synthesis of alginate

coated nanoparticles (CANP), sodium alginate (Sigma, USA) was dissolved in

Phosphate buffer saline (PBS) at a concentration of 5 mg/ml by stirring at 400rpm for

2 h at room temperature. This sodium alginate solution added drop wise into the

Chitosan nanoparticle solution under mild agitation (400rpm) at room temperature

followed by centrifugation at 12000rpm for 10 min. The pellet of alginate coated

Chitosan nanoparticles was re-suspended in 0.262mM CaCl2 to promote cross linking

between alginate layer and Chitosan nanoparticles. To prepare plant extract loaded

alginate coated chitosan nanoparticles (PE-CANP), plant extract loaded Chitosan

nanoparticles (PE-CNP) was used for coating by sodium alginate using the same

protocol for alginate coated nanoparticles (CANP).

2.5.6 Characterization of plant extract loaded Alginate Coated Chitosan

Nanoparticles

2.5.6.1 Scanning Electron Microscopy

Scanning electron microscopy (Jeol JSM; Central Resource Laboratory Peshawar

University, KPK) was used to study the size of the prepared nanoparticles. Briefly, 10µl

were placed on sterile glass slide (1 x1 cm) and was vacuum dried. Gold coating of the

dried sample was done using Jeol Quick Auto Coater (JFC-1500) ion sputtering device

6 s only. The prepared samples were analyzed at the resolution of 20 kV and 3000–

50000× magnification.

2.5.6.2 Atomic Force Microscopy

The 3D image of the of CANP, PE-CNP, PE-CANP nanoparticles was studied using

Molecular Imaging’s PicoPlus AFM using tapping mode equipped with Si tip (100 Å

diameter) coated with Al and a 200µ long Cantilever.


48

2.5.6.3. Fourier Transform Infrared Spectroscopy

Fourier Transform Infrared Spectroscopy (FT-IR) (Perkin Elmer; IIUI Univeristy,

Islamabaad) was used to determine the functional groups and interactions in CANP,

PE-CNP, PE-CANP nanoparticles. A pellet/disc was prepared using nanoparticle and

KBr (FTIR grade Merck) in a ratio of 1:5. Spectra were acquired in a range between

4000 and 600 cm-1.

2.5.6.4 Encapsulation Efficiency

The encapsulation efficiency (EE) of PE-CNP and PE-CANP nanoparticles was

calculated using indirect method as described by Jain et al., 2011. Briefly, plant extract

chitosan alginate nanoparticles (PE-CANP) were centrifuged at 12,000 g for 20 min

(Eppendorf 5415D, Germany) to separate un-trapped hexane fraction. The supernatant

was quantified using UV/VIS spectrophotometer at wavelength of 450nm (maximum

absorption wavelength of plant extract obtained from wave scan analysis in a range of

200-700nm) and concentration of plant extract determined using the standard curve of

known concentration of plant extract. Encapsulation efficiency (EE) was calculated

using the following formula

EE (%) =Total PE loaded − PE in the supernatant

Total PE Loaded𝑥 100

2.5.6.5 Cytotoxicity Assay

Human neuroblastoma cells SH-SY5Y (ATCC2266) cells were maintained in

Dulbecco’s Modified Eagle Medium (DMEM) supplemented with FBS (10%) at

standard conditions (37°C / 5% CO2). To assess the cytotoxicity of pre-seeded SH-

SY5Y cells (15,000 cells/well) were exposed to the CNP, PE-CNP and PE-CANP

nanoparticles, (10 µg/ml) for 24 h. Untreated cells were used as negative controls. Cell

viability was estimated using MTT assay as described earlier (Mosmann, 1983). SH-

SY5Y cells were treated with the nanoparticles for 24 h. 10 µL of the MTT stock

solution (12 mM) was added to each well and further allowed to incubate at 37°C for 4

hours. 100 µL of SDS-HCl solution was added in each well and the microtiter plate

was incubated overnight in a humidified chamber. Absorbance was recorded at 565

nm and percentage viability of the cells was determined using the following formula:

Viability(%) =Abs(TS) − Abs (NPC)

Abs (UTS) − Abs(B)X 100


49

Where “Abs(TS)” and “Abs(UTS)” represent the optical density at 565 nm for the

treated samples and untreated control samples, respectively. “Abs (NPC)” and

“Abs(B)” represent the background optical density at 565 nm of nanoparticles + media

and media only samples respectively. A percentage viability of 50 and above was

categorized as having ‘no effect’, viability between 50 and 25% as “moderate effect”

and below 25% having a ‘strong effect’. These assay were done in collaboration with

Institute of Biomedical and genetic Engineering, KRL Hospital Islamabad.

2.5.6.6 pH Dependent Release Profile

PE-CANP nanoparticle was suspended in 1 mL of phosphate-buffered saline at adjusted

pH of 3.5 and 7.0 to determine its behavior at simulated chicken crop and colon

respectively. At defined time intervals, the nanoparticles were centrifuged to remove

supernatant and fresh phosphate buffer was replaced. The concentration of plant extract

in the supernatant was measured by using UV-VIS spectrophotometer at a wavelength

of 450 nm (Gaonkar et al., 2017).

2.5.7 In-vivo Trial in Chicken

Day old chicks were purchased from commercial hatcheries and randomly distributed

into 4 groups of 15 chicks each i.e., Control group (no feed additive), PE group (Plant

extract as feed additive), CANP group (empty alginate coated nanoparticles as feed

additive), and PE-CANP (Plant extract encapsulated alginate coated chitosan

nanoparticles as feed additive). Individual bird in each group was orally gavage with

107 CFU of mid log culture of C. jejuni (strain Cj255) at day 3rd of post hatch. The feed

was manipulated with 1% (w/w) of the feed additive (Plant extracts/ CANP / CANP)

and was provided ad libitum for 3 days starting from day 3rd of post hatch. Fecal

samples (1g) collected on day 7 and day 14 post infection were serially diluted in PBS

and spot plated on mCCDA for calculation of C. jejuni load (CFU/g) in each group.

The plates were incubated at 42ºC for 48 h under microaerophilic conditions and

confirmation of representative colonies as C. jejuni was done using hippurate

hydrolysis test and species specific. The birds were euthanized by cervical dislocation

at day 21st post infection and cecum samples were collected (1g) by dissection. The

caecal samples serially diluted in PBS and spot plated on mCCDA for calculation of C.

jejuni load (CFU/g) in each group.


50

2.6.1 Metallic Nanoparticle as Control of C. jejuni Biofilms

2.6.1 Nanoparticles Used

Three different types of synthesized nanoparticle were used in this study i.e., TiO2 based

(TiO2, TiO2-Ag, TiO2-graphene and TiO2-Ag-Graphene), Ferrite based (Erbium doped

Lithium nickel of various sizes) and Zinc oxide nanoparticles. Detail of these

nanoparticles is given in Table 2.2

2.6.2 Test Microorganisms

The antibacterial activity of synthesized nanoparticles was tested primarily against C.

jejuni (cj255). To further access its broad-spectrum action, the nanoparticles they were

screened against gram negative Vibrio cholerae, Enteropathogenic Escherichia coli,

and gram-positive Staphylococcus aureus (MRSA). All the tested strains were resistant

against multiple drugs (MDR) and were obtained from Microbiology and Public Health

Laboratory culture collection at COMSATS University, Islamabad, Pakistan (Manzoor

et al., 2016)

2.6.3 Determination of Minimal Inhibitory Concentration

The Minimum inhibitory concentration (MIC) of the above-mentioned nanoparticles

was determined by Micro-titer assay using 2, 3, 5-triphenyltetrazolium chloride (TTC)

as cell viability indicator (Sarker et al., 2007). Twenty micro liters from the stock

solutions was added to 180µl of bacterial suspension (108 CFU/ml) such that each test

compound was checked at the final concentration of 1.0 mg/mL, 0.5mg/mL, 0.125

mg/ml, 0.0625 mg/mL and 0.0312 mg/mL in respective well of microtiter plate. After

incubation of 48 h, 20 µl of TTC indicator solution (prepared as 5 mg/ml in H2O) was

added to each well and change in color was recorded after 15-20 min. Pink color

indicated the presence of viable bacteria whereas no change in color was considered as

nonviable bacteria. Twenty micro liters from each of the well with no color change

were inoculated onto nutrient agar plate. The experiment was done thrice and the

average of three readings was referred as MIC.


51

Table 2.2 Detail of nanoparticles used

Nanoparticles ID Composition Size (nm)

TiO2 TiO2 10.5

TiO2/Gr TiO2/Graphene 9

TiO2/Ag TiO2/Silver 8.5

TiO2/Gr/Ag TiO2/Graphene/Silver 7.2

ErLiNiF3O4-24 Erbium doped Lithium Nickel Ferrite 24





ZnO Zinc Oxide 29


52

2.6.4 Growth Kinetics

To study the influence of nanoparticles on the growth, overnight culture of C. jejuni

was used to inoculate Brain heart infusion (BHI) broth with and without addition of

nanoparticle (2X less than the MIC). The culture flasks were placed in shaker incubator

(100rpm) at 42oC for 6 h. One microliter of sample was drawn and serially diluted was

serially diluted and these dilutions were spotted on Muller Hinton Agar plate. The

colony forming units (CFU) were counted after 24-48h of incubation. The un-

inoculated media was used as negative control.

2.6.5 Hydrophobicity Assay

To study the effect of nanoparticles on C. jejuni hydrophobicity, cells (107 CFU) were

inoculated in Brain heart infusion (BHI) broth supplemented with nanoparticles (2X

less than the MIC) and allowed to grow at 42 ºC for 24 h under microaerophilic

conditions.

The cells were harvested in phosphate buffer saline (PBS, pH 7.2) (Ht0 OD570= 0.5).

The bacterial suspension was then mixed with n-hexadecane and incubated for 5 min

at room temperature (Rosenberg et al., 1980; Thies and Champlin, 1989). The optical

density of the aqueous phase was measured at 570 nm (Ht5) using a microtiter plate

reader. Hydrophobicity was calculated by the equation:

Hydrophobicity (%) = (1-Ht5/Ht0) x 100

2.6.6 Auto-aggregation Assay

To study the effect on auto-aggregation, the bacterial cells were grown for 24 h in the

absence and presence of nanoparticles (2X less than the MIC) at 42ºC under

microaerophilic conditions (Collado et al., 2007). The cells were harvested and re-

suspended in PBS (pH 7.2) to adjust the OD570 to 0.5 (At0). Saline bacterial suspensions

were incubated at 42ºC for 2 h. O.D of supernatants was assessed (At2) and aggregation

potential calculated by the following formula:

Auto-aggregation (%) = (1-At2/At0) x 100.


Overnight culture of C. jejuni (O.D 0.05) exposed to nanoparticles (2X less than the

MIC) was used to stab semi-solid Muller Hinton agar plates (0.45%) and incubated at


53

42 0C for 24 h under microaerophilic conditions (Golden and Acheson, 2002). Zone of

motility in control (ZDC) (i.e. without nanoparticles) and treated (ZDT) (i.e.; with

different nanoparticle exposure) was measured and the motility rate was calculated

using the following the equation:

Motility rate %= ZDT/ZDC x100

2.6.8 DNA and Protein Leakage Assay

Overnight cultures of C. jejuni (107 CFU) were exposed to nanoparticles (at MIC

values) for 4 h and sample was centrifuged at 123000 x g and the resultant supernatant

(TC) was passed through a 0.22 µm. DNA quantification was done 260nm using

nanodrop and for detection of protein in the supernatant Bradford assay was used

(Sampathkumar et al., 2003). Briefly 100 µL of the filtered supernatant were added to

500µL of Bradford reagent and absorbance was read at 595nm using

spectrophotometer. Untreated cell (UTC) and cells treated with Triton X-100 (TTC)

was used as negative and positive control (Singh et al., 2016). The experiment was

repeated three times. Total leakage of DNA or protein leakage was expressed in terms

of leakage index by using the following formula:

DNA Leakage Index = (TCO.D 260 - UTCO.D 260)/ TTCO.D 260

Protein Leakage Index = (TCO.D 595- UTCO.D 595)/ TTCO.D 595

2.6.9 Antibiofilm Activity

C. jejuni overnight culture was re-suspended in LB broth at an OD600 of ∼0.05. Both

borosilicate tubes as well as sterile 96-well polystyrene plates (Corning™ Costar™

Clear Polystyrene 96-Well Plates) were inoculated with bacteria along with

nanoparticles (2X less than the MIC) and incubated for 48h at 42°C (O’Toole and

Kolter, 1998). Following the incubation, the planktonic cells were discarded, and the

wells were rinsed thrice with PBS. Crystal violet (0.1%) (Sigma) was used to stain the

biofilm for 30 min followed by through washing with distilled water. The biofilm was

dissolved in dimethyl sulfoxide (DMSO) and quantified using spectrophotometer

(OD570). All assays were performed in triplicate.


54

2.6.10 Cytotoxicity Assay

Human neuroblastoma cells SH-SY5Y (ATCC2266) cells were maintained in

Dulbecco’s Modified Eagle Medium (DMEM) supplemented with FBS (10%) at

standard conditions (37°C / 5% CO2). To assess the cytotoxicity of nanoparticles, pre-

seeded SH-SY5Y cells (>90% viability; 15,000 cells/well) were exposed to the

nanoparticles at 10 µg/ml for 24 h. The untreated cells were used as negative controls.

Cell viability was estimated using MTT assay as described in section 2.5.6.5 in

collaboration with Institute of Biomedical and genetic Engineering, KRL Hospital

Islamabad.

Chapter 3 Results

55

Chapter 3

Results

Chapter 3 Results

56


Isolates from Paediatric Diarrhoeal Cases

In Pakistan, the epidemiological data related to campylobacteriosis is under reported

due to the lack of proper surveillance system. Therefore, this section was designed to

investigate the current status of C. jejuni infections among pediatrics patients by

evaluating the antibiotic resistance and source tracking of the isolates.

3.1.1 Isolation and Identification of C. jejuni

To study the prevalence of C. jejuni among diarrheal patients a total of 150 stool

samples, of children suffering from diarrhoea, were collected and processed to detect

the presence of C. jejuni. Biochemically identified C. jejuni strains (positive for

oxidase, catalase, indoxyl acetate and hippurate hydrolysis test) were further confirmed

by PCR using primers against hipO gene (344 bps) as shown in Fig. 3.1. C. jejuni was

found to be present in 82 samples indicating a high campylobacteriosis incident rate

(i.e., 52.4%). Cj255 was used as positive control.

3.1.2 Antimicrobial Resistance Profiling

3.1.2.1 Multiple Drug Resistant Isolates

In order to study multidrug resistance among the isolated C. jejuni their susceptibility

was tested against an array of 13 antibiotics. The results showed that most of the C.

jejuni isolates were resistant to tested antibiotics at the rate ranging from 9-96%. More

than 80% of the isolates were found to be resistance to the following antibiotics:

ampicillin (96%), erythromycin (96%), streptomycin (91%) and tetracycline (87),

trimethoprim/sulfamethoxazole (87%), cefotaxime (86%), gentamycin (79%), nalidixic

acid (79%), ciprofloxacin (69%) (Fig.3.2). Moderate percentages of isolates were

resistant to chloramphenicol (36%) and colistin (37%). However, imipenem and

tigecycline were found to be the most sensitive antibiotic with resistance of 12% and

9% respectively. Overall 75% of isolates were resistant to more than 8 antibiotics.

Chapter 3 Results

57

Fig. 3.1 Identification of C. jejuni isolates a) characteristics growth of C. jejuni

on mCCDA media; b) positive hippurate hydrolysis test; c) Species specific PCR for

hipO gene Lane 1- 1 kb ladder, Lane 2- 3, Isolates positive for hipO genes; Lane 4-

Positive control (Cj 255)

Chapter 3 Results

58

Fig. 3.2 Antibiotic resistance pattern of isolates C. jejuni against 13 tested

antibiotics expressed in terms of percentage of resistant isolates. AMP (Ampicillin

10µg), SXT (Sulphomethoxazole + trimethoprim; 25 µg), CIP (Ciprofloxacin; 5 µg),

CT (Colistin), TE (Tetracycline; 30 µg), C (Chloramphenicol; 30 µg), NA (Nalidixic

acid; 30 µ g), E (Erythromycin; 30 µg), CTX (Ceftriaxone; 30µg), TGC (Tigecycline;

15µg), IMP (Imipenem; 10µg), CN (Gentamycin; 10 µg), and S (Streptomycin; 10 µg),

Chapter 3 Results

59

3.1.2.2 Detection of Metallo-β-Lactamase

Metallo-β-lactamase (MBL) enzyme detection through combined disk method (CDT)

showed that 10% (n=8) were MBL positive. Molecular identification using MBL genes

(IMP, SIM, VIM, GIM and SPM) showed that 7.3% (n=6) of the total isolates were

MBL positive. Out of these six isolates, three isolates carried both IMP and VIM genes

and three isolates carried VIM, IMP or SIM gene alone. None of the isolates were

positive for GIM or SPM (Fig. 3.3).

3.1.3 Source Attribution

All the C. jejuni isolates were assigned to strain clusters using the binary code based on

the presence or absence of amplified products of six source predictive genes sequences

(Fig. 3.4, 3.5). The results showed that isolates were well distributed among all groups

i.e., C1/C2/C3 (14.6%), C4/C6 (26.8%), C5 (15.8%), C6/C7 (24.3%) and C9 (18.2%)

(Fig. 3.5). Overall 57.3% of the isolates belonging to C1 to C6 which have been

previously described as livestock-associated cluster (Fig. 3.6) comparatively 42.8% of

isolates belonging to C7 to C9 were predicted to be of non-livestock /environmental in

origin (Champion et al., 2005; Stabler et al., 2013). The relationship of livestock and

non-livestock associated strains along with MAR Index is shown in phenogram

(Hammer et al., 2001) (Fig. 3.6). The isolates belonging to livestock cluster had high

MAR index (p<0.0001) as compared to non-livestock isolates.

Chapter 3 Results

60

Fig. 3.3 Detection of Metallo-β-lactamases in C. jejuni using multiplex PCR

assay for MBL encoding genes i.e., IMP (188bp), SIM (390bp), and VIM (570bp)

Fig. 3.4 Source predictive multiplex PCR: lane 1, 100-bp ladder; lane 2, strain BH20

(mPCR 1); lane 3, strain BH20 (mPCR 2); lane 4, strain SH11 (mPCR 1); lane 5, strain

SH11 (mPCR 2). mPCR 1 involved amplification of genes Cj1422, Cj1139 and Cj0056.

mPCR 2 involved amplification of genes Cj1324, Cj1720 and Cj0485.

Chapter 3 Results

61

Fig. 3.4 Dendrogram displaying source attribution clusters of C. jejuni strains,

based on binary data of PCR profiles by using UPGMA analysis (PAST3.16 Software);

Green strain labels MAR=0.35-0.45, Blue strain labels- MAR=0.5-0.65, Red strain

labels=0.7-0.8; *** indicate isolates which are MBL producers.

Chapter 3 Results

62

Fig. 3.5 Percentage and average MAR index of isolates attributed to livestock

and non-livestock clusters. MAR index of the isolates belonging to livestock cluster

was significantly higher as compared to those associated with non-livestock origin

(Student’s t-test; P<0.005)

Chapter 3 Results

63


Negative C. jejuni Isolates

Although C. jejuni lacks the general stress response machinery present in other gram-

negative bacteria but high prevalence of C. jejuni infections indicate some underlying

alternate mechanisms which may provide it protection against harsh environment.

Therefore, this section was designed to investigate the role of the Type Six Secretion

system (T6SS), which has been recently identified in C. jejuni, adaptation to different

stresses acidic pH, high temperature and oxidative stress. The effect of each of these

stresses on factor such as motility, hydrophobicity, auto aggregation and eventual

biofilm formation was investigated. Bacterial cells unexposed to these stresses and un-

inoculated media was used as positive and negative control respectively.

3.2.1 Determination of Sub-lethal Level of pH

C. jejuni encounters acid stress in host stomach and during food processing. To study

the behavior of T6SS positive and negative C. jejuni isolates under acidic stress,

bacterial strains were exposed to different pH 2.5, 3.5, 4.5, 5.5, 6.5 and the sub-lethal

level of acidic stress was determined. Both T6SS positive and negative isolates were

able to resist acidic pH up to 3.5 whereas no growth was observed in cultures exposed

to pH 2.5 (Fig. 3.6). Sub-lethal pH, at which bacterial cell survival rate is more than

50%, was found to be 5.5 for both T6SS positive and negative isolates.

3.2.2 Effect of Sub-lethal pH 4.5 on Motility

Motility is an important virulence factor in C. jejuni; therefore, T6SS positive and

negative C. jejuni isolates were exposed to sub-lethal pH to observe any differential

response between the two groups. Results showed that motility of both Type six

secretion system positive and negative isolates slightly decreased with exposure to sub-

lethal pH of 4.5 as indicated by a nearly negligible fold change (Student’s t-test; p>0.05)

in the Fig. 3.7.

Chapter 3 Results

64


different pH stress (2.5-6.5). Bacterial cells unexposed to stress and un-inoculated

media were used as positive and negative controls. Sub-lethal pH was found to be 5.5

for both T6SS positive and negative isolates.

Fig. 3.7 Effect of sub-lethal pH (4.5) on motility of T6SS positive and negative

strains (shown in term of average fold change in each group with respect to control i.e.,

bacterial cells unexposed to stress). No significant difference in motility among T6SS

positive and negative groups was observed.

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65

3.2.3 Effect of Sub-lethal pH 4.5 on Auto-aggregation and Hydrophobicity

Both auto aggregation and hydrophobicity play a vital role in adherence of bacterial

cells to host cells and substrates; therefore, the differential effect of acidic stress on

these factors was evaluated in both T6SS positive and negative groups. Our results

showed that auto-aggregation and hydrophobicity of both T6SS positive and negative

isolates increased to a very small extent in response to exposure to sub-lethal pH of 4.5

(Student’s t-test; p>0.05) (Fig. 3.8).

3.2.4 Effect of Sub-lethal pH 4.5 on Biofilm Formation

Biofilm formation ability of both T6SS positive and negative isolates under sub-lethal

dose of pH 4.5 was evaluated in order to study the adaptive advantage of T6SS under

acidic stress. Biofilm formation potential was slightly increased in both T6SS positive

and negative isolates. However, no significant difference in average fold change in

biofilm formation among T6SS positive and negative groups was observed (Student’s

t-test; p>0.05) (Fig. 3.9).

Chapter 3 Results

66

Fig. 3.8 Effect of sub-lethal pH (4.5) on hydrophobicity and auto aggregation of

T6SS positive and negative C. jejuni isolates (shown in term of average fold change in

each group with respect to control i.e., bacterial cells unexposed to stress). No

significant difference in hydrophobicity/auto-aggregation among T6SS positive and

negative groups was observed.

Fig. 3.9 Effect of sub-lethal pH (4.5) on biofilm formation of T6SS positive and

negative C. jejuni isolates (shown in term of average fold change in each group with

respect to control i.e., bacterial cells unexposed to stress). No significant difference in

biofilm formation among T6SS positive and negative groups was observed.

Chapter 3 Results

67

3.2.5 Determination of Sub-lethal Level of Oxidative Stress

C. jejuni, being microaerophilic bacteria, faces unavoidably harsh oxygen stress under

normal environmental condition. Such oxidative stress has been previously reported to

enhance stimulate biofilm formation, however in this study the role of T6SS in

oxidative stress adaptation was evaluated (which was previously unknown). Sub lethal

oxidative stress was determined as measure of resistance to H2O2 concentration. The

average growth of both T6SS positive and negative isolates decreased with the increase

in concentration of H2O2. Sub lethal dose of H2O2, at which bacterial cell survival rate

is more than 50%, was recorded as 8mM for both T6SS positive and negative isolates.

No growth was observed at an exposure above 10 mM (Fig. 3.10).

3.2.6 Effect of Sub-lethal Oxidative Stress (8mM of H2O2) on Motility

Motility is a key factor in stress adaptation and biofilm formation in this experiment we

evaluated the influence of sub lethal oxidative stress on T6SS positive and negative

groups. Motility of T6SS positive isolates slightly decreased with exposure to sub lethal

oxidative stress; however, no significant change in the average motility among T6SS

negative group was observed (student’s t-test; P>0.05) (Fig. 3.11).

Chapter 3 Results

68


different oxidative stress (2-12mM H2O2). Sub lethal dose of H2O2, was recorded as

8mM for both T6SS positive and negative isolates.

Fig. 3.11 Effect of sub-lethal oxidative stress (8mM) on motility of T6SS positive

and negative strains in terms of fold change with respect to control i.e., bacterial cells

unexposed to stress. No significant difference in motility among T6SS positive and


Chapter 3 Results

69

3.2.7 Effect of Sub-lethal Oxidative Stress (8mM of H2O2) on Auto-

aggregation and Hydrophobicity

Effect of sub-lethal oxidative stress on auto aggregation and hydrophobicity was

evaluated in to get a better insight into role of T6SS in stress adaptations. Auto-

aggregation and hydrophobicity of both T6SS positive and negative isolates increased

in response to exposure of sub- lethal dose of oxidative stress (8mM of H2O2). Marked

difference in both autoaggregation (student’s t-test; P<0.01) and hydrophobicity

(student’s t-test; P<0.005) among T6SS positive and negative groups was observed

(Fig. 3.12).

3.2.8 Effect of Sub-lethal Oxidative Stress (8mM of H2O2) on Biofilm

Formation

Comparative effect of sub-lethal dose of oxidative stress on the biofilm forming

potential of T6SS positive and negative isolates was done. Biofilm formation was

enhanced among isolates belonging to T6SS positive group in response to sub-lethal

dose of oxidative stress i.e., 8mM, whereas no effect on biofilm formation was observed

among T6SS negative isolates (student’s t-test; P<0.005) (Fig. 3.13).

Chapter 3 Results

70

Fig. 3.12 Effect of sub-lethal oxidative stress (8mM) on hydrophobicity and auto


fold change in each group i.e., bacterial cells unexposed to stress). Significant

difference in hydrophobicity/auto-aggregation among T6SS positive and negative

groups was observed. Student’s t-test; **P<0.01

Fig. 3.13 Effect of sub-lethal oxidative stress (8mM) on biofilm formation of

T6SS positive and negative isolate (shown in term of average fold change in each group

with respect to control i.e., bacterial cells unexposed to stress). Significant increase in

biofilm formation among T6SS positive groups as compared to T6SS negative groups

was observed. Student’s t-test; *** P<0.005

Chapter 3 Results

71

3.2.9 Determination of Sub lethal Temperature

C. jejuni are temperature sensitive bacteria which grow optimally at body temperature

of human and birds i.e., 37 ºC and 42 ºC respectively. However, majority of

Campylobacteriosis cases in human have been reported to be due to ingestion of under

cooked meat and vegetables suggesting its survival under heat stress. In this study the

role of T6SS in heat stress adaptation was evaluated. To determine sub lethal

temperature, bacterial strains were exposed for 15 minutes to different temperature i.e.,

42 ºC, 50 ºC, 55 ºC, 60 ºC, and 65 ºC. Both T6SS positive and negative isolates were

able to resist heat up to 60 ºC whereas no growth was observed in culture exposed to

65 ºC (Fig. 3.14). No significant difference in survival response to heat stress was

observed among T6SS positive and negative isolates (student’s t-test; P>0.05). Sub

lethal temperature, at which bacterial cell survival rate is more than 50%, of all isolates

was recorded as 55 ºC.

3.2.10 Effect of Sub-lethal Temperature 55ºC on Motility

The effect of sub-lethal heat stress on motility of T6SS positive and negative bacteria

was studied to any differential response between the two groups. The motility of T6SS

positive strain reduced upon exposure to sub lethal heat stress of 55ºC. On the contrary,

heat stress did not affect the motility of T6SS negative isolates (Fig. 3.15).

Chapter 3 Results

72


different temperature stress (42-65ºC). Bacterial cells unexposed to stress and un-

inoculated media were used as positive and negative controls. Sub lethal temperature

was recorded as 55 ºC.

Fig. 3.15 Effect of sub-lethal heat stress (55ºC) on average motility rate of T6SS

positive and negative strains with respect to control i.e., bacterial cells unexposed to

stress. No significant difference in biofilm formation among T6SS positive and


Chapter 3 Results

73

3.2.11 Effect of Sub-lethal Temperature 55ºC on Auto-aggregation and

Hydrophobicity

Change in auto aggregation and hydrophobicity of T6SS positive and negative bacteria

under sub lethal heat stress was evaluated to study whether T6SS enhances virulence/

adherence potential of C. jejuni or not? Hydrophobicity of both T6SS positive and

negative isolates increased in response to exposure to sub lethal temperature of 55ºC.

However, marked effect was observed in case of T6SS positive group (student’s t-test;

P<0.01). Auto aggregation increased slightly in case of T6SS positive group whereas a

slightly negative effect on auto aggregation ability of T6SS negative group was

observed (student’s t-test; P<0.05) (Fig. 3.16).

3.2.12 Effect of Sub-lethal Temperature 55ºC on Biofilm Formation

Biofilms helps bacteria withstand heat stress; therefore, to analyze the role of T6SS in

heat stress induce biofilm formation both T6SS positive and negative bacteria were

exposed to sub lethal temperature of 55ºC and biofilm formation was recorded.

Biofilm formation was enhanced among all T6SS positive and T6SS negative isolates

in response to sub lethal temperature i.e., 55ºC. Significant difference (student’s t-test;

P <0.01) in average fold change in biofilm formation among T6SS positive and negative

group was observed (Fig. 3.17).

Chapter 3 Results

74

Fig. 3.16 Effect of sub-lethal temperature stress (55⁰C) on hydrophobicity and

auto aggregation of T6SS positive and negative C. jejuni isolates (shown in term of

average fold change in each group with respect to control i.e., bacterial cells unexposed

to stress). Significant difference in hydrophobicity/auto-aggregation among T6SS

positive and negative groups was observed. Student’s t-test; *P<0.05, ** P<0.01

Fig. 3.17 Effect of sub-lethal temperature stress (55⁰C) on a) biofilm formation of

individual T6SS positive and negative isolate (shown in term of average fold change

with respect to control i.e., bacterial cells unexposed to stress in each group) Significant

increase in biofilm formation among T6SS positive groups as compared to T6SS

negative groups was observed. student’s t-test; **P<0.01.

Chapter 3 Results

75


T6SS

Both oxidative and temperature stresses caused significant increase in biofilm

formation in T6SS positive isolates. To further validate the role of T6SS in biofilm

formation the structure and function of hemolysin co-regulatory protein (Hcp) was

studied in detail. Moreover, virulence potential of secretory Hcp was also evaluated.

3.3.1 Expression and Purification of Recombinant and Mutant Hcp Proteins

To determine the structure of Hcp Protein the protein was overexpressed in BL21 cells

and purified using both His Tag and size exclusion chromatography. The hcp gene

(534bp) of Campylobacter jejuni cloned in pET-22b plasmid was expressed using 0.3

mM IPTG and was purified using Ni-NTA affinity beads (Fig. 3.18). The eluted protein

(shown in lane 1; Fig. 3.18b) was further purified using Superdex-200 column (GE

Healthcare, Buckinghamshire, UK). The purified protein was eluted as a single peak

corresponding to hexameric form of Hcp-Cj protein (Fig. 3.19a).

3.3.2 Confirmation of Eluted Protein as Hcp Protein by Mass Spectroscopy

The eluted protein fractions were run on 12.5% SDS which showed that all fractions

were pure and of same size (Fig. 3.19b). One band was cut and was analyzed by Mass

spectroscopy to confirm the identity of purified protein. Peptides mass fingerprints

showed highest score with Hcp-Cj protein of C. jejuni (Fig. 3.20).

3.3.3 Dynamic Light Scattering

All the fractions corresponding to the peak area shown in the SEC graph (3.19a) were

collected, pooled and concentrated to 10mg/ml. Dynamic Light Scattering (DLS) was

used to determine the homogeneity of the protein. The percentage of poly dispersity of

Hcp-Cj protein was recorded as 3% and the SOS error as 18.3 at 10 mg/ml concentration

(Fig. 3.21).

Chapter 3 Results

76

Fig. 3.18 Hcp-Cj protein expression and purification a) BL21 cells showing

expression of Hcp protein (18kDa) in induced culture (IN) and no expression in

uninduced cells (UIN) b) Showing fraction obtained in Ni-NTA coulmn purification;

Lane M: marker, 1: elution, 2: Soluble fraction of cell lysate, 3: insoluble fraction of

cell lysate, 4: flow through after binding with Ni-NTA, Lane 5-7 three subsequent

wahes with imidazole, 8: Hcp protein bonded to beads after elution

Fig. 3.19 Size exclusion chromatography a) elution profile of Hcp protein b) SDS-

PAGE analysis of the eluted fractions of SEC (chosen from the shaded region) showing

purified Hcp-Cj protein.

Chapter 3 Results

77

Fig. 3.20 Mass spectroscopy analysis a) Mass spectrum of tryptic peptide digest

of purified Hcp protein; b) peptides that matched with hcp protein of C. jejuni using

Mascot are underlined

Fig. 3.21 Dynamic light scattering analysis of Hcp-Cj at 10mg/ml concentration

showing the protein is homogenous with polydispersity index of 0.03.

Peptide

R.LPTVEVHWFR.T

R.VHKPFSFTCSLNK.S

K.VVWEHTAAGTSGSDDWR.E

R.KVVWEHTAAGTSGSDDWR.E

K.IEGSTQGLISSGASTEASIGNR.Y

K.LEDAIITNIELIMPNAQESSNHDKTELLK.V

K.SGHEDEIMAQEVSHIVTVPVDQQSGQPSGQR.V

Sequence of HCP-Cj

MAEPAFIKIEGSTQGLISSGASTEASIGNRYKSGHEDEIMAQEVSHIVTVPVDQQSGQPSGQRVHKPFSFTCS

LNKSVPLLYNALTKGERLPTVEVHWFRTATSGGSEHFFTTKLEDAIITNIELIMPNAQESSNHDKTELLKVS

MSYRKVVWEHTAAGTSGSDDWREGKA

a

b

Chapter 3 Results

78

3.3.4 Crystallization

The purified Hcp protein was then used to prepare crystals for structure determination.

The initial crystallization conditions for the Hcp-Cj protein were screened by Index

Screens (Hampton Research) using the hanging-drop vapor-diffusion technique at

25°C. Crystals were formed in four different screens i.e. HR110 screen 4 i.e., 0.1M

Tris-HCl 8.5 2.0 M Ammonium sulfate, screen 17 i.e., and screen no 22 i.e., 0.2M

Sodium acetate trihydrate, 0.1 M Tris-HCl 8.5, 30% PEG (Table 3.1). These screens

were sub-optimized using various conditions shown in (Table 3.2-3.4). The diffraction

quality crystals were obtained with relatively more stringent condition i.e. 0.2 M

sodium acetate trihydrate, 0.1 M Tris-HCl (pH 8.5) and 32% Polyethylene glycol after

two days. The size of the crystal was recorded as 1160µm

Chapter 3 Results

79

Table 3.1 Screening of crystal condition using Index Screens (Hampton Research)

HR2-110 conditions 1-24

Screen

no.

Conditions Results

1 0.02 M Calcium chloride dehydrate, 0.1 M

Sodium acetate trihydrate pH 4.6, 30% v/v (+/-)-

2-Methyl-2,4-pentanediol

Precipitates

2 0.4 M Potassium sodium tartrate tetrahydrate Clear

3 0.4 M Ammonium phosphate monobasic Clear

4 0.1M Tris-HCl 8.5, 2.0 M Ammonium sulfate 2 large Crystals used

for diffraction

Tuning issues

5 0.1 M HEPES sodium pH 7.5, 0.2 M Sodium

citrate tribasic dehydrate, 30% v/v (+/-)-2-

Methyl-2,4-pentanediol

Precipitates

6 0.1 M Tris hydrochloride pH 8.5, 0.2 M

Magnesium chloride hexahydrate, 30% w/v

Polyethylene glycol 4,000

Precipitates

7 0.1 M Sodium cacodylate trihydrate pH 6.5, 1.4

M Sodium acetate trihydrate

Clear


M Sodium citrate tribasic dehydrate, 30% v/v 2-

Propanol

Precipitates

9 0.1 M Sodium citrate tribasic dihydrate pH 5.6,

0.2 M Ammonium acetate, 30% w/v


very small crystals

numerous

10 0.1 M Sodium acetate trihydrate pH 4.6, 0.2 M

Ammonium acetate

30% w/v Polyethylene glycol 4,000

Clear

11 0.1 M Sodium citrate tribasic dihydrate pH 5.6,

1.0 M Ammonium phosphate monobasic,

Crystals

12 0.2 M Magnesium chloride hexahydrate, 0.1 M

HEPES sodium pH 7.5, 30% v/v 2-Propanol

Precipitates

13 0.1M Tris-HCl 8.6, 0.2 M Sodium citrate

tribasic dehydrate, 30% v/v Polyethylene glycol

400

Clear

14 0.1 M HEPES sodium pH 7.5, 0.2 M Calcium

chloride dehydrate, 28% v/v Polyethylene glycol

400

Clear


M Ammonium sulfate, 30% w/v Polyethylene

glycol 8,000

Not done

16 0.1 M HEPES sodium pH 7.5, 1.5 M Lithium

sulfate monohydrate

Not done

17 0.1M Tris-HCl 8.5, 0.2m Lithium sulphate,

PEG=30

Crystals-checked for

further optimization

Chapter 3 Results

80

Large but many

fewer in number

Screen

no.

Conditions Results

18 0.2 M Magnesium acetate tetrahydrate, 0.1 M

Sodium cacodylate trihydrate pH 6.5, 20% w/v


Not done

19 0.2 M Ammonium acetate, 0.1 M TRIS

hydrochloride pH 8.5, 30% v/v 2-Propanol

Precipitates

20 0.2 M Ammonium sulfate, 0.1 M Sodium

acetate trihydrate pH 4.6, 25% w/v Polyethylene

glycol 4,000

Precipitates

21 0.2 M Magnesium acetate tetrahydrate, 0.1 M

Sodium cacodylate trihydrate pH 6.5, 30% v/v

(+/-)-2-Methyl-2,4-pentanedio1

Precipitates

22 0.2 M Sodium acetate trihydrate, 0.1 M TRIS

hydrochloride pH 8.5, 30% w/v Polyethylene

glycol 4,000

Crystals-checked for

further optimization

Large but few

23 0.2 M Magnesium chloride hexahydrate, 0.1 M

HEPES sodium pH 7.5, 30% v/v Polyethylene

glycol

Clear

24 0.2 M Calcium chloride dihydrate, 0.1 M

Sodium acetate trihydrate pH 4.6, 20% v/v 2-

Propanol

Crystals

Chapter 3 Results

81

Table 3.2 Sub-optimization of Crystal Screen HR2-110 condition no. 4 i.e., 0.1 Tris-HCl 8.5, 2M Ammonium Sulphate

1 2 3 4 5 6

A 0.1M Tris-HCl 8.4

2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

2M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

2M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

2M Ammonium

Sulphate

2:1 protein: buffer

Clear

B

0.1M Tris-HCl 8.4

1.8M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

1.8M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

1.8M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

1.8M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

1.8M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

1.8M Ammonium

Sulphate

2:1 protein: buffer

Clear

C 0.1M Tris-HCl 8.4

1.6M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

1.6M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

1.6M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

1.6M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

1.6M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

1.6M Ammonium

Sulphate

2:1 protein: buffer

Clear

D 0.1M Tris-HCl 8.4

2.2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

2.2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

2.2M Ammonium

Sulphate

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

2.2M Ammonium

Sulphate

2:1 protein: buffer

One large crystal

954.51 um

0.1M Tris-HCl 8.5

2.2M Ammonium

Sulphate

2:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

2.2M Ammonium

Sulphate

2:1 protein: buffer

One large crystal

Chapter 3 Results

82

Table 3.3 Sub-optimization of Crystal Screen HR2-110 condition no. 17 i.e., 0.2M Lithium Sulphate monohydrate, 0.1 M Tris-HCl 8.5,

30% PEG

1 2 3 4 5 6

A 0.1M Tris-HCl 8.4

0.2m CaCL2

PEG=22 %

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.4

0.2m CaCL2

PEG=24

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.4

0.2m CaCL2

PEG=26

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.4

0.2m CaCL2

PEG=28

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.4

0.2m Lithium Sulphate

PEG=30

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.4

0.2m Lithium sulphate

PEG=32

1:1 protein: buffer

Crystals

B

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5


PEG=30

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.5


PEG=32

1:1 protein: buffer

Crystals

C 0.1M Tris-HCl 8.6

0.2m Lithium

sulphate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2m Lithium

sulphate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2m Lithium

sulphate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2m Lithium

sulphate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6


PEG=30

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.6


PEG=32

1:1 protein: buffer

Crystals

D 0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2m Lithium

sulphate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5


PEG=30

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5


PEG=32

1:1 protein: buffer

Crystals

Chapter 3 Results

83

Table 3.4 Sub-optimization of Crystal Screen HR2-110 condition no. 22 i.e., 0.2M Sodium acetate trihydrate, 0.1 M Tris-HCl 8.5, 30%

PEG

1 2 3 4 5 6

A 0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=22%

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=30

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.4

0.2 Sodium acetate

trihydrate

PEG=32

1:1 protein: buffer

Clear

B

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=30

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=32

1:1 protein: buffer

Crystal-used for final

XRD

C 0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=28

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=30

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.6

0.2 Sodium acetate

trihydrate

PEG=32

1:1 protein: buffer

Crystals

D 0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=22

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=24

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=26

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=28

1:1 protein: buffer

Clear

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=30

1:1 protein: buffer

Crystals

0.1M Tris-HCl 8.5

0.2 Sodium acetate

trihydrate

PEG=32

1:1 protein: buffer

Crystals

Chapter 3 Results

84

3.3.5 The Overall Structure of C. jejuni Hcp

The structure of Hcp from C. jejuni was solved by molecular replacement and was

refined to a 2.8 Å resolution (Table 3.5). Overall structure shows six molecules which

form a hexamer ring in asymmetric unit with a diameter of approx. 80 Å and internal

pore of 40Å (Fig. 3.22). Each monomer in a hexamer ring comprising of 1) a tight β-

barrel domain (two β sheets) 2) one turn helix (H1) and 3) 11-residue α-helix (H2). The

β-barrel domain is (approx. 12 Å diameter) formed by 8 strands of antiparallel β strands

(β1- β8) and has both hydrophobic and hydrophilic residues. Four β strands i.e., β2, β3,

β6 and β7 of each monomer form the inner surface of the hexamer ring. The region

from Val44 to Thr49 (β2) of one monomer interacts with residues Asn122 to Met127

(β8) of the adjacent monomer to form a ring. The beta barrel is connected to a 5-residue

one turn helix H1 (Glu24 to Ile27) which act like a cap over Helix 2. H2 (11 residue

Helix) from Ser77 to Lys87 act as interlocking element between chains of the hexamer

rings because on one hand it interacts with β strands (β6, β 7) with in same chain (by

Val78, Leu81, Tyr82, Leu85) and on other hand with the β strands (β8) of adjacent

chain (by Pro79, Asn83, Tyr86, Lys87). Loop 3 between β2 and β3 is an extended loop

that comprises of 17 residues (Pro51-Pro67) and protrudes approximately 25 Å from

the core beta barrel.

Chapter 3 Results

85

a)

b)

Fig. 3.22 Overall structure of the Hcp-Cj from C. jejuni Cartoon representation of

the Hcp monomer (a) and hexameric ring (b)

Chapter 3 Results

86

Table 3.5 Data collection and refinement statistics.

Hcp_CJ

Data Collection Space group P212121

Cell Dimensions a,b,c (Å) 92.37 91.92 165.74

α,,β,γ(o) 90 90 90

Resolution (Å) 50.0-2.6 (2.64-2.6) Rsym/Rmerge 0.12 (0.56)

I/ sI 15.4 (1.9)

Completeness (%)* 87.5 (83.1)

Redundancy* 2.7 (2.7)

No. reflections 180663(73986)

Refinement Resolution (Å) 19.9-2.6 (2.64-2.6) R work/ R free 0.21/0.25

No. atoms Proteins 7174

Water 109

B-factors Proteins 65

Water 57.8

R.m.s deviations Bond lengths (Å) 0.009

Bond angles (o) 1.21

*Values in parentheses are for highest-resolution shell.

Chapter 3 Results

87

3.3.6 Comparison with Hcp-Cj with Known Crystal Structures of Hcp

A total of six Hcp crystal structures are available in protein data bank (PDB) so far i.e.,

Pseudomonas aeruginosa Hcp1 (PDB code: 1Y12), Hcp3 (PDB code: 3HE1),

Edwardsiella tarda (PDB code: 3EAA), enteroaggregative Escherichia coli (PDB

code: 4HKH), Burkholderia pseudomallei (PDB code: 3WX6) and Acinetobacter

baumannii (PDB code: 4W64). The Hcp protein of C. jejuni showed limited sequence

identities to the six other Hcps ranging from 8.49% to 46.5% (Table 3.6). However, the

crystal structures alignment showed that all of them shared the same basic architecture

of hexamer ring with RMSD values falling in between 1.90 Å and 4.84 Å. The main

differences in the secondary structures are i) the number of beta sheets, ii)

presence/absence of one turn helix and iii) especially the overhang loops L1,2 and L2,3

which vary greatly in length and composition (3.23 and 3.24). Conserved residues in

the hexamer ring of Hcp-Cj and other hcps were calculated using Clustal Omega and

Consurf. Few residues were found to be highly conserved among all Hcp proteins i.e.,

Gly28, S26, His35, Gly57, Thr71, Ala84 and Trp166. All of them are exposed except

Thr71 and Ala 84 which are buried and not solvent accessible. Residues Lys72, Asp75,

Glu142 were found to be highly conserve in all Hcp sequences but Hcp-Cj showed

variation at these points (Cys72, Asn75, Leu142). Slight conserved residues are Ile17,

Asn29, Ile39, Gly57, Pro79, Leu81, Gly88, Glu95, Lys114, Glur116 and Tyr148 (Fig.

3.25). Most of the conserved amino acids are on external side of the ring and exposed

while the residues in the inner side/channel of the ring shows more variable residues.

Chapter 3 Results

88

Fig. 3.23 Multiple sequence alignment of Hcp-Cj (Cj255) with its homologs i.e., 1Y12 (Pseudomonas aeruginosa Hcp1), 3HE1

(Pseudomonas aeruginosa Hcp3), 3EAA (Edwardsiella tarda Hcp), 4HKH (enteroaggregative Escherichia coli Hcp), 3WX6

(Burkholderia pseudomallei Hcp) and 4W64 (Acinetobacter baumannii Hcp).

Chapter 3 Results

89

a) b)

Fig. 3.24 Structural alignment (a) showing that Hcp-Cj (with homolog protein) vary greatly in length and composition especially

the overhang loops L1,2 and L2,3 [Green: Hcp_Cj, Magenta: EvpC (3EAA), Brown: B. pseudomallei (3WX6), Hot pink: E. coli

(4HKH), Yellow: P. aeruginosa Hcp3(3HE1), Cyan: P. aeruginosa Hcp1 (1Y12), Blue: A. baumannii (4W64)]. b) Showing residues

30R and 31Y which were mutated to Alanine

Chapter 3 Results

90

Fig. 3.25 Conserved residues on the Hcp surface. Deep red color represents highly conserved residues and blue represent variable

residues. External surface of the hexamer is moderately conserved (a, b, e) as whereas the internal surface has comparatively more

variable residues (d). Conserved region mainly lies in the beta sheets and helix (c)

Chapter 3 Results

91

Table 3.6 Sequence and structural comparison of Hcp-Cj with its homologs

C. jejuni

Hcp-Cj

P. aeruginosa

Hcp3

(3HE1)

P. aeruginosa

Hcp1

(1Y12)

A. baumannii

(4W64)

EvpC

(3EAA)

E. coli EAEC

042 pathovar

(4HKH)

B. pseudomallei

(3WX6)

Sequence comparison

Sequence

length (aa)

171 173 162 171 163 163 169

Sequence

identity

- 46.55% 8.49% 2.85% 11.17% 10.35% 11.90%

Size(kDa) 18.75 19.18 17.41 19.08 17.86 18.85 18.74

pI 5.78 5.49 6.29 6.59 5.71 5.67 5.68

Signature

features

(Prosite

prediction)

N-myristoylation

site (4)

Casein kinase II

phosphorylation

(6)

N-glycosylation

site (1)

Protein kinase C

(2)

Microbodies C-

terminal

targeting signal

(1)

N-

myristoylation

site (4)

Casein kinase II

phosphorylation

(6)

Protein kinase

C (1)

cAMP-

dependent

protein kinase

phosphorylation

site (1)

N-

myristoylation

site (5)

Casein kinase II

phosphorylation

(3)

N-glycosylation

site (1)

Protein kinase C

(3)

N-

myristoylation

site (3)

Casein kinase II

phosphorylation

(3)

N-glycosylation

site (2)

Protein kinase

C (4)

cAMP-

dependent

protein kinase

phosphorylation

site (1)

N-

myristoylation

site (3)

Casein kinase II

phosphorylation

(1)

Protein kinase

C (4)

Casein kinase II

phosphorylation

(2)

N-glycosylation

site (1)

Protein kinase

C (3)

Tyrosine

kinase

phosphorylation

site (1)

N-

myristoylation

site (4)

Casein kinase II

phosphorylation

(3)

N-glycosylation

site (1)

Protein kinase C

(1)

Amidation site

(1)

Chapter 3 Results

92

C. jejuni

Hcp-Cj

P. aeruginosa

Hcp3

(3HE1)

P. aeruginosa

Hcp1

(1Y12)

A. baumannii

(4W64)

EvpC

(3EAA)

E. coli EAEC

042 pathovar

(4HKH)

B. pseudomallei

(3WX6)

Crystal structure comparison

Rmsd*

-- 1.02 4.84 4.18 4.24 2.77 1.90

Space

group

P212121 P321 P6 P6 P6 P2 P6

Resolution

(Å)

2.8 2.098 1.95 1.55 2.8 3.5 2.7

No of Beta

strands

8 11 10 10 11 9 10

Alpha

helix (No.)

11aa helix (1)

One turn helix

(1)

12aa helix (1)

One turn helix

(2)

11 aa alpha

helices (1)

10 aa alpha

helix (1)

One turn

helix(1)

11 aa alpha

helix (1)

One turn helix

(1)

12aa helix (1) 12aa helix (1)

One turn helix

(1)

Inner

channel of

hexamer

40 Å 40 Å 40 Å 40 Å 40 Å 40 Å 40 Å

Diameter

of

hexamer

85 Å 90 Å 85 Å 80 Å 80 Å 80 Å 80 Å

Chapter 3 Results

93

3.3.7 Functional Analysis of Secretory Hcp Protein

3.3.7.1 Cytotoxicity towards Prokaryotic Cells

To study the role of secreted Hcp-Cj in providing any competitive advantage to T6SS

harboring C. jejuni, T6SS C. jejuni strains and E. coli (DH5α) were grown in the

presence of purified Hcp-Cj. No significant change in growth (student’s t-test; P >0.05)

was observed in any of the test bacteria showing that the protein is not bactericidal to

other prokaryotic cells (Fig. 3.26)

3.3.7.2 RBC Lysis Assay

To study the effect of Secreted Hcp-Cj protein on viability of Sheep’s red blood cells,

RBC lysis assay was performed. No significant difference in O.D. of the cell

supernatant in negative control, Hcp-Cj (recombinant) and mutant Hcp-Cj (Hcp-R30A

and Hcp-Y31A) exposure group (student’s t-test; P>0.05) was observed indicating that

the Hcp-Cj protein did not cause lysis of sheep erythrocytes (Fig. 3.27).

3.3.7.3 Cytotoxicity towards Eukaryotic Cells (HepG2)

Purified Hcp-Cj (recombinant type) exposure caused significant reduction in cell

viability of HepG2 cells as to 41.8% as compared to 100% survival in untreated control

group. Mutant Hcp-R30A showed significant increase in cell viability i.e., 47.3%

(student’s t-test; P<0.01) as compared to recombinant type Hcp-Cj. However, mutant

Hcp-Y31A didn’t show significant difference in cytotoxicity as compared to

recombinant Hcp protein as shown by Fig. 3.28.

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94

Fig. 3.26 Effect of Hcp exposure on the growth of T6SS positive (strain ID 77,

255); T6SS negative (strain ID 301, Akc27) and Dh5α. Bacterial cells unexposed to

Hcp were used as control. No significant change in growth (student’s t-test; P>0.05)

was observed in any of the test bacteria in response to Hcp exposure.

Fig. 3.27 Hemolysis assay depicting that exposure of recombinant type hcp,

HcpR30A mutant and HcpY31A mutant protein didn’t caused lysis of Sheep

erythrocytes. Control group show lysis of RBC by 1% SDS. No significant difference

in O.D. of the cell supernatant in negative control, Hcp-Cj (rHcp) and mutant Hcp-Cj

(Hcp-R30A and Hcp-Y31A) exposure group (student’s t-test; P>0.05) was observed.

Chapter 3 Results

95

a)

b)

Fig. 3.28 Cytotoxicity of recombinant and mutant Hcp-Cj towards HepG2 cells.

A) Showing reduction in HepG2 cells viability (%) on exposure to recombinant type

and mutant Hcp-Cj. B) Microscopic image of untreated control (NTC) and treated (Hcp,

exposed) HepG2 cells. Mutant Hcp-R30A showed significant increase in cell viability

i.e., (student’s t-test; P<0.01) as compared to recombinant type Hcp-Cj.

Chapter 3 Results

96

3.3.7.4 Motility Assay

Motility of all T6SS harboring C. jejuni, T6SS negative isolates and control E. coli

(DH5α) remained unaffected by the exposure to both mutant and recombinant type

Hcp-Cj (Hcp-R30A and Hcp-Y31A) proteins Fig. 3.29 (student’s t-test; P >0.05).

3.3.7.5 Biofilm Assay

The effect of secretory Hcp-Cj on biofilm forming ability of both T6SS positive and

negative strains was studied which showed that establishment of biofilm was not

dependent on presence or absence of Hcp-Cj in both types of strains. However, volume

of biofilm formation was significantly enhanced in all C. jejuni (student’s t-test;

P<0.01) isolates. The effect of Hcp-Cj exposure and reduction in biofilm formation was

more pronounced in T6SS positive isolates as compared to T6SS negative isolates

(student’s t-test; P<0.05). This is likely because all the T6SS‐positive strains were weak

biofilm formers in the absence of Hcp as compared to T6SS‐negative strains (Fig. 3.30

a, b). A change in biofilm formation was observed in HcpR30A and HcpY31A mutants

as compared to recombinant type Hcp-Cj; however, this difference was not statistically

significant.

Chapter 3 Results

97

.

Fig. 3.29 Motility assay showing that recombinant and mutant Hcp-Cj didn’t

cause significant change in zone of motility of both type six positive (77, 255) and type

six negative strains (301, Akc27). No significant change in motility was observed in

response to Hcp exposure (student’s t-test; P >0.05)

.

Chapter 3 Results

98

a)

b)

Fig. 3.30 Effect of recombinant and mutant Hcp-Cj on Biofilm formation in C. jejuni.

a) Biofilm formation was significantly enhanced on exposure to Hcp-Cj as compared

to unexposed cells (student’s t-test; *P<0.05, **P<0.01); b) No significant difference

in biofilm formation on exposure to mutant and recombinant type Hcp-Cj was observed

(student’s t-test; P>0.05).

Chapter 3 Results

99

3.4 In silico Drug Target Identification of C. jejuni

Insilico drug designing using genomics, proteomes, microarray, and metabolomics data

provides an alternate strategy to identify novel and essential drug target in pathogenic

bacteria to combact multidrug (Zhang et al., 2005). In the present study a combination

of subtractive proteomics and comparative metabolic pathway analysis was done to

identify potential drug targets in C. jejuni (11168) to develop alternative treatment for

multidrug resistant isolates.

3.4.1 Essential Non-homology Protein in C. jejuni

The first step involved elimination of all those protein in C. jejuni which shared

homology to human proteome in order to prevent potential side effects of the drug

designed against these targets. The proteome of C. jejuni 11168 consisting of 1722

proteins was retrieved and subjected to BLASTP against H. sapiens proteome. Out of

which 235 proteins, which showed significant similarity with that of H. sapiens were

excluded (E-value cutoff of 10-3). All the non-homologous proteins (n=1487) were then

filtered based on their essentiality using DEG server to identify proteins in C. jejuni

which are essential for survival and are evolutionary conserved. A total of 173 proteins

showed hits against DEG database were regarded to be essential for C. jejuni whereas

the remaining proteins 1314 proteins with no hits were excluded from further analysis

as they were nonessential.

3.4.2 KEGG Pathway Analysis

Non-homologous essential proteins were then analyzed for their role in metabolic

pathways using KEGG Metabolic pathway analysis as targeting such proteins will

affect the growth of bacteria. Eighty-seven protein sequences were found to be

involved the metabolic pathways of C. jejuni out of which 68 proteins belonged to

pathway which are common in Human and C. jejuni. Whereas 19 proteins belonged to

unique pathways (only present in C. jejuni). i.e., Beta-lactam resistance, Bacterial

secretion system, Two-component system, Cationic antimicrobial peptide (CAMP)

resistance, Methane metabolism flagellar assembly, Biosynthesis of secondary

metabolites, Microbial metabolism in diverse environments (Fig. 3.31). Proteins

involved in metabolic pathways were selected for further analysis.

Chapter 3 Results

100

Fig. 3.31 Number of essential non-homologous proteins of C. jejuni involved in

common (blue) and unique pathways determined through KEGG Pathway analysis.

Chapter 3 Results

101

3.4.3 Drugability Potential of the Shortlisted Proteins

The shortlisted protein sequences tested for their drugability potentially using Drug

bank database to study whether they can act as drug targets. This resulted in

identification of 38 proteins which showed significant similarity with the available

targets in the DrugBank database. Out of these 7 drug targets had FDA approved drugs,

however drugs for remaining 31 drug targets are still under experimental investigation

(Table 3.7).

3.4.4 Prioritization of Druggable Targets

Druggable targets were prioritized by functional analysis which showed that 28 of

proteins were enzymes, 4 were ribosome associated proteins, 3 were involved in

transcription and 2 were penicillin binding protein and 1 was ATP binding protein. In

the present study, all the proteins (except rpoB and was thus eliminated from further

analysis) had molecular weight less than 110 kDa. Only one out of 38 protein targets

i.e., kpsT was identified as virulence factor protein using Virulence Factor DataBase

(VFDB) (Chen et al., 2012). Most of druggable targets in this study belong to cytoplasm

and 5 proteins were associated with cytoplasmic membrane and remaining 1 had

unknown location. Out of 5 cytoplasmic membrane associated protein, three had

transmembrane helices. Of the target three had experimentally resolved or crystal

structure, whereas structures of 31 targets have been so far predicted by homology

model. Structure of two drug target is still unknown i.e., ispH and glyS. Non-homology

analysis of drug target against chicken proteome was indicated that 33 drug targets were

unique to C. jejuni and absent in chicken proteome. Only 10 drug targets were found

to be non-homologous to human gut microflora thus after prioritization process, 10

proteins out of 38 druggable target were shortlisted as the most potential drug targets

(Table 3.8). The proteins include acnB; bifunctional aconitate hydratase 2/2-

methylisocitrate dehydratase (COG1049 ), frdC; fumarate reductase subunit C

(COG2009), folK; 2-amino-4-hydroxy-6-hydroxymethyldihydropteridine

pyrophosphokinase (COG0801), ispDF; bifunctional 2-C-methyl-D-erythritol 4-

phosphate cytidylyltransferase/2-C-methyl-D-erythritol 2,4-cyclodiphosphate synthase

(COG0245,COG1211), nadE; NAD synthetase (COG0171), pbpB; penicillin-binding

Chapter 3 Results

102

protein (COG0768), pbpC; penicillin-binding protein, pycB; pyruvate carboxylase B

subunit (COG5016), cj0915 hydrolase (COG1607), cj0353c phosphatase (COG0248).

All these proteins were enzymes except pbpB and pbpC (Table 3.8). A statistical

summary of drug target identification of C. jejuni is shown in (Tablen3.9).

Chapter 3 Results

103

Table 3.7 Druggable target of C. jejuni before prioritization

Sr.

No

Protein Name COG DrugBank

ID

Name of drug Drug group

1 acnB COG1049 DB04351 Aconitate Ion Experimental

2 aroA COG0128 DB04328

DB04539

Shikimate-3-Phosphate

Glyphosate

Experimental

Experimental

3 aroB COG0337 DB02592 Carbaphosphonate Experimental

4 dxr COG0743

COG0331

DB02496

DB02948

DB03649

DB04272

1-Deoxy-D-xylulose 5-phosphate

Fosmidomycin

[{(5-Chloro-2-Pyridinyl) Amino} Methylene]-1,1-

Bisphosphonate

Citric Acid

Experimental

Experimental

Experimental

Nutraceutical

5 fabd COG0331 DB07344 3,6,9,12,15-Pentaoxaheptadecan-1-OL Experimental

6 fba COG0191 DB03026 Phosphoglycolohydroxamic Acid Experimental

7 fbp COG0158 DB00131

DB02778

Adenosine monophosphate

2,5-Anhydroglucitol-1,6-Biphosphate

Approved, nutraceutical

Experimental

8 fmt COG0223 DB04464 N-Formylmethionine Experimental

9 frda COG1053 DB07669 2,3-Dimethyl-1,4-Naphthoquinone Experimental

10 frdc COG2009 DB07669 2,3-Dimethyl-1,4-Naphthoquinone Experimental

11 folK COG0801 DB02119 6-Hydroxymethyl-7, 8-Dihydropterin Experimental

12 galU COG1210 DB01643 Thymidine-5'-Phosphate Experimental

14 ispDF COG0245

COG1211

DB02552 Geranyl Diphosphate Experimental

15 ispH COG0761 DB01785

DB04714

Dimethylallyl Diphosphate

Isopentenyl Pyrophosphate

Experimental

Experimental

16 kpsT COG1134 DB00864 Tacrolimus Approved, investigational

Chapter 3 Results

104

17 murB COG0812 DB03147 Flavin adenine dinucleotide Approved

18 murC COG0773 DB01673

DB03909

DB04395

Uridine-5'-Diphosphate-N-Acetylmuramoyl-L-Alanine

Adenosine-5'- [Beta, Gamma-Methylene] Triphosphate

Phosphoaminophosphonic Acid-Adenylate Ester

Experimental

Experimental

Experimental

19 murl COG0796 DB08698 1-[(3S)-5-Phenyl-3-Thiophen-2-YL-3H-1,4-Benzodiazepin-2-

YL] Azetidi-3-OL

Experimental

20 nadE COG0171 DB04099 Deamido-Nad+ Experimental

21 nrdF COG0208 DB04077 Glycerol Experimental

22 nusB COG0781 DB04272 Citric Acid Nutraceutical

23 pbpA COG0744 DB00229

DB00267

DB00301

Cefotiam

Cefmenoxime

Flucloxacillin

Approved

Approved

Approved

25 pbpB COG0768 DB00535 Cefdinir Approved

25 pbpC COG0768 DB00303

DB00671

DB00142

Ertapenem

Cefixime

L-Glutamic Acid

Approved, investigational

Approved

Nutraceutical

26 PFS COG0775 DB07463 (3R,4S)-1-[(4-amino-5H-pyrrolo[3,2-d] pyrimidin-7-yl)

methyl]-4-[(butylsulfanyl)methyl] pyrrolidin-3-ol

Experimental

27 pheA COG1605

COG0077

DB08648 8-Hydroxy-2-Oxa-Bicyclo [3.3.1] NON-6-ENE-3,5-

Dicarboxylic Acid

Experimental

28 purQ COG0047 DB00130 L-Glutamine Approved, investigational,

nutraceutical

29 pycB COG5016 DB02637

DB03801

DB04553

Oxaloacetate Ion

Lysine N-Carboxylic Acid

2-Oxobutanoic Acid

Experimental

Experimental

Experimental

30 rplC COG0087 DB01256 Retapamulin Approved

Chapter 3 Results

105

31 rpsF COG0087 DB08185 2-MethylThio-N6-Isopentenyl-Adenosine-5'-Monophosphate Experimental

32 rpsH COG0085 DB08185 2-MethylThio-N6-Isopentenyl-Adenosine-5'-Monophosphate Experimental

33 rpsN COG0199 DB08185 2-MethylThio-N6-Isopentenyl-Adenosine-5'-Monophosphate Experimental

34 thisD COG0351 DB02022 4-Amino-5-Hydroxymethyl-2-Methylpyrimidine Experimental

35 tyrS COG0162 DB03978 Tyrosinal Experimental

36 valS COG0525 DB00161 L-Valine Approved, nutraceutical

37 CJ0915

Hydrolase

COG1607 DB01992 Coenzyme A Nutraceutical

38 Cj0353c

Phosphatase

COG0248 DB03382 S-Oxy Cysteine Experimental

Chapter 3 Results

106

Table 3.8 List of Druggable target of C. jejuni after prioritization

Sr.

No

.

Protein

Name

DrugBank

ID

Name of Drug Group of drugs Functional

category

Cellular

localization/

Trans-

membrane

domain

KEGG

Unique/

common

pathway

Availability of 3D

Structure

1 acnB DB04351 Aconitate Ion Experimental Enzyme Cytoplasmic CPP Homology model

2 frdc DB07669 2,3-Dimethyl-1,4-

Naphthoquinone

Experimental Enzyme Cytoplasmic

membrane

5 TMMH

UPP Homology model

3 folK DB02119 6-Hydroxymethyl-7, 8-

Dihydropterin

Experimental Enzyme Cytoplasmic CPP Homology model

4 ispDF DB02552 Geranyl Diphosphate Experimental Enzyme Cytoplasmic UPP Crystal structure

5 nadE DB04099 Deamido-Nad+ Experimental Enzyme Cytoplasmic CPP Crystal structure

6 pbpB DB00535 Cefdinir Approved Penicillin

Binding

Protein

Cytoplasmic

membrane

1 TMMH

UPP Homology model

7 pbpC DB00303

DB00671

DB00142

Ertapenem

Cefixime

L-Glutamic Acid

Approved,

Approved,

Nutraceutical

Penicillin

Binding

Protein

Cytoplasmic UPP Homology model

8 pycB DB02637

DB03801

DB04553

Oxaloacetate Ion

Lysine Nz-Carboxylic

Acid

2-Oxobutanoic Acid

Experimental

Experimental

Experimental

Enzyme Cytoplasmic CPP Homology model

9 CJ0915

Hydrolase

DB01992 Coenzyme A Nutraceutical Enzyme Unknown CPP Crystal structure

10 Cj0353c

Phosphatase

DB03382 S-Oxy Cysteine Experimental Enzyme Cytoplasmic CPP Homology model

Chapter 3 Results

107

Table 3.9 Statistical summary of drug target identification of C. jejuni.

Total Proteins 1722

Non-homologous proteins (to human proteome) 1487

Essential and Non-homologous proteins 174

Essential and Non-homologous proteins in KEGG pathway 88

Unique pathway proteins 19

Druggable targets 39

Chapter 3 Results

108


Encapsulated Alginate Chitosan Nanoparticles

C. jejuni infections are mainly caused by consumption of undercooked poultry meat

and reduction of C. jejuni load in the intestines/carcass of chickens can lead to drastic

decrease in campylobacteriosis case (Rosenquist et al., 2003; EFSA, 2011). Therefore,

this section of the study was designed to use of nano-encapsulated natural antimicrobial

plant extract for targeted release in the chicken intestine to reduce the load of C. jejuni

in poultry.

3.5.1 Screening of Plant for Anti-campylobacter Activity

Five medicinal plants i.e., Berberis lycium (bark), Trachyspermum annum (seeds),

Nigella sativa (Seeds), Camellia sinensis (leaves), Mentha longifolia (leaves) were

screened for their antibacterial activity against C. jejuni. Among all these plant

materials, T. annum (seeds) showed best anti-campylobacter activity as indicated by

larger zone of inhibition (28.5mm) compared to that of M. longifolia, B. lycium, N.

sativa and C. sinensis respectively. Therefore, T. annum (seeds) was selected for further

studies (Fig. 3.32).

3.5.2 Active Anti-campylobacter fraction of Trachyspermum ammi

All six fractions i.e., methanolic (MF), n-hexane (HF), chloroform (CF), ethyl acetate

(EF), n-butanol (BF) and aqueous fraction (AF) were then evaluated for their anti-

campylobacter activity. Methanolic, n-hexane, ethyl acetate and butanol fraction

showed anti-campylobacter activity with MIC value of 0.125, 0.0362, 0.5, 0.25 mg/ml

respectively. Hexane fraction was found to be the most active as indicated by lowest

MIC (Fig. 3.33).

3.5.3 Influence on Bacteria Cell Survival

The influence of exposure of hexane fraction of Trachyspermum annum (seeds), on the

bacteria survival was studied for a period of 4 hours. The number of colony forming

units (CFU) decreased with increasing time of exposure. During first 150 minutes of

exposure the bacterial count decreased from 107 to 103 and after which no colonies were

observed indicating complete killing of all C. jejuni cells (Fig. 3.34).

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109

Fig. 3.32 Anti-campylobacter activity of crude extract of A) positive control

Ampicillin, B) Trachyspermum annum (28.5mm), C) Mentha longifolia (17mm), D)

Camellia sinensis (23mm) E) Berberis lycium (26.5mm) F) Nigella sativa (25.5mm).

T. annum (seeds) showed best anti-campylobacter activity as indicated by largest zone

of inhibition.

Fig. 3.33 MTT assay showing the anti-campylobacter activity of different fraction

of Trachyspermum annum (seeds). Four fractions were found to be active with i.e.,

methanolic fraction (MF), hexane fraction (HF), butanol fraction (BF) and ethyl acetate

fraction (EF) with minimum inhibitory concentration of 0.125, 0.0362, 0.25 and 0.5

mg/ml respectively. Hexane fraction was found to be the most active as indicated by

lowest MIC i.e. 0.0362 mg/ml. Untreated bacterial cultures were used as positive

control.

Chapter 3 Results

110

Fig. 3.34 Time dependent cell survival assay a) graph showing log reduction in

CFU/ml on exposure to hexane fraction of T. annum. The bacterial count decreased

from 107 to 103 during first 150 minutes of exposure and 100% killing was observed at

180 min. Un-treated bacterial cultures were used as positive control.

Chapter 3 Results

111

3.5.4 Gas Chromatography-Mass Spectroscopy Analysis

The GC-MS analysis of n-hexane fraction of Trachyspermum ammi seeds was done to

identify the components of the active hexane fraction. The analysis showed that it is

composed of four major constituent giving distinct peaks at retention time of 2.23, 2.54,

4.08 and 4.14 minutes (Fig. 3.35). The mass spectra of each peak were compared with

NIST 02 spectral library for identification and identified as Mitozolomide with

retention peak of 2.23, 1-4 Cyclohexadiene with retention peak of 2.54, Thymol with

retention peak of 4.08 and 4 Hydroxy, 3 methyl acetophenone with retention peak of

4.14 (Fig. 3.36)

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112

Fig. 3.35 The GC analysis of n-hexane fraction of Trachyspermum ammi seeds

showing four major peaks i.e. at 2.23, 2.54, 4.08 and 4.151 minutes.

Chapter 3 Results

113

a)

b)

Fig. 3.36 a) Mass spectral analysis of peaks with retention time of 2.23 minutes

which was identified as 4—Cyclohexadiene by comparing it with NIST 02 spectral

library b) Mass spectral analysis of peaks with retention time 2.54 minutes which was

identified as Mitozolomide by comparing it with NIST 02 spectral library

Chapter 3 Results

114

c)

d)

Fig. 3.36 c) Mass spectral analysis of peaks with retention time of 4.08 minutes

which was identified as Thymol by comparing it with NIST 02 spectral librar. d) Mass

spectral analysis of peak with retention time of 4.151 minutes which was identified as

4 Hydroxy, 3 methyl acetophenone by comparing it with NIST 02 spectral library.

Chapter 3 Results

115

3.5.5 Characterization of Plant Extract Loaded Alginate Coated Chitosan

Nanoparticles

Thymol, one of the constituent of T. ammi hexane fraction, has been reported earlier as

a strong antibacterial agent. But due its hydrophobic nature it is difficult to administer

orally in poultry for control of C. jejuni, and furthermore its activity is reduced in

chicken gut as it is degraded at acidic pH of chicken gizzard. To overcome this problem,

alginate coated chitosan nanoparticles were successfully prepared for intestinal delivery

of plant extract (hexane fraction) and results of their morphological characterization

(scanning electron microscopy and atomic force microscopy), composition (fourier

transform infrared spectroscopy), release profile, encapsulation efficiency and

cytotoxicity are as follows.

3.5.5.1 Scanning Electron Microscopy

Scanning electron microscopy (SEM) analysis was done to study the morphology and

size of the nanoparticles. Our results showed that all the prepared nanoparticle i.e.,

empty chitosan nanoparticles (CNP), alginate coated chitosan nanoparticles (CANP),

plant extract loaded chitosan alginate nanoparticles (PE-CANP) were less than 100 nm

in size (Fig. 3.37).

Both empty chitosan nanoparticles (CNP) and alginate coated chitosan nanoparticles

(CANP) were homogenous as compared to plant extract loaded chitosan alginate

nanoparticles (PE-CANP) in which some aggregates as visible. With encapsulation of

plant extract the average size of alginate coated chitosan nanoparticle increase from

54.68nm to 68.78nm.

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a)

b)

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117

c)

Fig. 3.37 Scanning Electron Microscopy (SEM) images of a) empty chitosan

nanoparticles (CNP) b) alginate coated chitosan nanoparticles (CANP) c) plant extract

loaded chitosan alginate nanoparticles (PE-CANP) showing that the size of the

nanoparticles was below 100nm and nanoparticles were evenly distributed

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118

3.5.6.2 Atomic Force Microscopy

The 3D imaging of empty chitosan nanoparticles (CNP), alginate coated chitosan

nanoparticles (CANP), plant extract loaded chitosan alginate nanoparticles (PE-CANP)

by Atomic Force Microscopy (AFM) revealed that all nanoparticles were

homogenously distributed. The maximum height of chitosan nanoparticle (47nm)

increased with alginate coating (57nm) and encapsulation of plant extract (73nm), thus

verifying the similar trend observed in SEM results (Fig. 3.38 a-c).

3.5.6.3 Encapsulation Efficiency

The encapsulation efficiency (EE) of PE-CANP nanoparticles was estimated to be 85%

% which showed that a very high amount of plant extract was loaded in the alginate

coated chitosan nanoparticles.


To assess the cytotoxicity of CNP, CANP and PE-CANP nanoparticles towards SH-

SY5Y cells, MTT [3-(4, 5-Dimethylthiazol-2yl)-2, 5-Diphenyltetrazolium Bromide]

assay was used. Results showed that all the tested nanoparticles reduced the cell

viability to some extent, but it was not significant (Fig. 3.39).

3.5.6.5 pH Dependent Release Profile

The release of plant extract at acidic pH (3.0) and neutral pH (7.0) by PE-CANP was

study for the period of 24 h. to determine its behavior at physiological pH of chicken

crop and colon respectively. At pH 7.0, PE-CANP released plant extract at a very fast

rate in the first 4h (i.e. 40% of plant extract was released) after which it become steady

reaching a maximum of 55% after 24h showing control release. However, insignificant

amount of plant extract (10%) was releases at acidic pH of 3.0 (Fig. 3.40).

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119

a)

b)

c)

Fig. 3.38 Atomic force microscopic images showing surface topography and 3-

Dimensional (3D) structures of a) Chitosan nanoparticle (CNP) b) Alginate coated

chitosan nanoparticles (CANP) c) Alginate coated chitosan nanoparticle loaded with

plant extract (PE-CANP). All nanoparticles were homogenously distributed.

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120

Fig. 3.39 Cytotoxicity assay of plant extract (PE), empty alginate coated chitosan

nanoparticles (CANP) and plant extract loaded chitosan alginate nanoparticles (PE-

CANP) using Human neuroblastoma cells (SH-SY5Y). Untreated cells were used as

negative controls.

Fig. 3.40 pH dependent release profile showing percentage release of plant extract

from Alginate coated chitosan nanoparticles (PE-CANP) at acidic (3.0) and neutral

(7.0) pH. At neutral pH plant extract at a very fast rate in the first 4h, however

insignificant amount of plant extract was released at acidic pH.

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121

3.5.6.6 Fourier-Transform Infrared Spectroscopy Analysis (FTIR)

In the FTIR spectra of plant extract (PE), empty alginate coated chitosan nanoparticles

(CANP) and plant extract encapsulated chitosan alginate nanoparticles (PE-CANP) are

shown in Fig. 3.42 (a-c). Plant extract (PE) spectra showed medium grade peaks at

2917 and 2856 corresponding to C-H stretching of alkane. Two strong peaks

representing C=C stretching of aromatic ring were observed at 1566 and 1599 cm-1.

Peaks at 1382, 1150 and 795 cm-1 correspond to C-H stretching of alkane, C-O

stretching (alcohol or phenol) C-H bending of alkene respectively (Fig. 3.41 a).

In the FTIR spectra of Alginate coated chitosan nanoparticles (CANP) following peaks

were observed i.e., 3444, 2927, 2858, 1654, 1388, 1021, and 700 cm-1 that correspond

to O-H stretching (representing alcohol or phenol), CH stretching of alkanes, -C=C-

stretch of alkynes, C=N stretching, alkyl amine, CH bending of alkene respectively

(Fig. 3.41 b).

The FTIR spectra plant extract encapsulated chitosan alginate nanoparticles (PE-

CANP) showed peaks observed in both CANP and PE spectra. Peaks at 3418 (O-H

stretching), 2919 (CH stretching of alkanes), 2855 (CH stretching of alkanes), 1645 (-

C=C- stretch of alkynes), 1379 (C=N stretching), 1083 (C-O stretching of alcohol or

phenol) and 541 (CH stretching of alkene) were similar to those observed in CANP

representing the same functional groups. The peaks in PE-CANP spectrum at 1547

(C=C stretching of aromatic ring), 1154(C-O stretching of alcohol or phenol), 799 cm-

1 (C-H bending of alkene) were also observed in plant extract (PE) with a slight shifting

in their spectral position (Fig. 3.41 c). The results indicated that plant extract is

completely encapsulated in alginate coated chitosan nanoparticle (CANP).

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122

a)

b)

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123

c)

Fig. 3.41 Fourier-transform infrared spectroscopy analysis showing spectra of a)

Plant extract (PE) b) Alginate coated chitosan nanoparticles (CANP) c) Alginate coated

chitosan nanoparticle loaded with plant extract (PE-CANP).

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124

3.5.7 In-vivo Trial in Chicken

In-vivo trial in chicken was done to test the effectiveness of the prepared plant extract

loaded alginate coated chitosan nanoparticles. Significant reduction in CFU count of C.

jejuni in fecal sample at, 7th day of infection, was observed among all treated groups

i.e., 1.5 log reduction in CANP group (empty alginate coated nanoparticles as feed

additive) (student’s t-test; P<0.01),4 log in PE group (Plant extract as feed additive)

(student’s t-test; P <0.005), 2 log reduction in PE-CANP (Plant extract encapsulated

alginate coated chitosan nanoparticles as feed additive) (student’s t-test; P<0.01) as

compared to control group (with no feed additive). After 14-day post infection the CFU

count/g in fecal sample remained the same in CANP group, whereas it increased by 1.5

logs (of CFU count/g in fecal sample) in case of PE-CANP group and by 3 logs in PE

group (Fig. 3.42). No significant change in feed to gain ratio (FCR) was observed

among all group at both 7 and 14th day of sampling (Fig. 3.43).

At day 21st post infection the chickens were euthanized, and caecum samples were

collected. The CFU counts per gram of caecal content was recorded in each group

which showed that the CFU count/g reduced by 4 log in CANP group (student’s t-test;

P<0.01), 1.5 log in PE group (student’s t-test; P<0.05,) and maximum reduction was

observed in PE-CANP group i.e., by 6 log (student’s t-test; P<0.005) (Fig. 3.44). No

significant change in feed to gain ratio (FCR) was observed among all group at 21st day

of sampling (student’s t-test; P>0.05) (Fig. 3.45).

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125

Fig. 3.42 Log reduction in C. jejuni CFU/g of chicken fecal samples at day 7 and

14 post infection in CANP (empty alginate coated chitosan nanoparticles), PE group

(Plant extract as feed additive), PE-CANP (Plant extract encapsulated alginate coated

chitosan nanoparticles as feed additive). Significant reduction at 7 and 14-day post in

CFU count/g in fecal sample was observed as compared to untreated control group.

(student’s t-test; ***P<0.005, **P<0.01).




chitosan nanoparticles as feed additive). No significant change in feed to gain ratio

(FCR) was observed at both 7 and 14th day of sampling.

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126

Fig. 3.44 Log reduction in C. jejuni CFU/g of chicken caecum at day 21st post

infection in CANP (empty alginate coated chitosan nanoparticles), PE group (Plant


nanoparticles as feed additive), and Control group (with no feed additive) (student’s t-

test;*P<0.05, **P<0.01, ***P<0.005).




chitosan nanoparticles as feed additive), Control group (with no feed additive). No

significant change in feed to gain ratio (FCR) was observed (student’s t-test; P>0.05)

(Fig. 3.45).

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127

3.6 Metallic Nanoparticle as Control of C. jejuni Biofilms

C. jejuni persist in harsh environment i.e. food processing plant and water, for relatively

longer periods due to its ability of surface attachment and biofilms formation (Buswell

et al., 1998; Kalmokoff et al., 2006). In the present study the anti-campylobacter and

anti-biofilm activity of three different metal oxide nanoparticles was evaluated i.e.,

TiO2 based, Ferrite based and Zinc Oxide for their potential application as coating

material in food processing units.

3.6.1 TiO2-Ag-Graphene Nanocomposites

3.6.1.1 Minimal Inhibitory Concentration

Doping of both silver (Ag-TiO2) and Silver-Graphene (Ag-Graphene-TiO2) composites

increased the anti-campylobacter activity of TiO2 nanoparticles as indicated by a

decrease in MIC from 1 µg/ml to 0.1 and 0.01 µg/ml respectively. Silver-Graphene-

TiO2 composites were found to be most effective against C. jejuni as indicated by the

lowest MIC value i.e., 0.01 µg/ml.

3.6.1.2 Cell Survival

Cell survival assay of C. jejuni in response to exposure to TiO2, Ag-TiO2, Graphene-

TiO2 and Silver-Graphene-TiO2 composites showed that viable cell count (CFU)

decreased in response to exposure to all these nanoparticles (Fig. 3.46). TiO2

nanoparticles exposure resulted in 1 log reduction in viable bacterial colonies compared

to that of 1.5 log reduction in response to Silver/TiO2 and TiO2/Graphene

nanocomposites exposure. Silver-Graphene-TiO2 composites were most lethal of all the

nanoparticles, indicated by a 2-log reduction in CFU count of C. jejuni.

3.6.1.3 Hydrophobicity and Auto-aggregation

Auto aggregation of C. jejuni decreased significantly when exposed to sub lethal doses

of Silver doped TiO2 (Ag-TiO2) (student’s t-test; P<0.01) and Silver-Graphene-TiO2

composites (student’s t-test; P<0.005), whereas TiO2, and Graphene-TiO2 had no effect

on auto aggregation (Fig. 3.47). A significant decrease in hydrophobicity of bacterial

cell was observed after silver-Graphene-TiO2 composites exposure.

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128

Fig. 3.46 Influence of TiO2, TiO2-graphene (TiO2/GR), Ag-TiO2 (TiO2/AG) and

Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on the growth of C. jejuni. Untreated

bacterial cells were used as control.


Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on hydrophobicity and aggregation of

C. jejuni. Untreated bacterial cells were used as control. Silver doped TiO2 (Ag-TiO2)

and Silver-Graphene-TiO2 composites caused significant reduction in hydrophobicity

and aggregation (student’s t-test; **P<0.01, ***P<0.005).

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129


Exposure to all the TiO2 based nanoparticles lead to decrease in bacterial motility. More

than 60% reduction in motility was observed in the presence of Silver doped TiO2 (Ag-

TiO2) (student’s t-test; P<0.005) and Silver-Graphene-TiO2 composites (student’s t-

test; P<0.005) compared to strong migration in control (Fig. 3.48).

3.6.1.5 DNA and Protein Leakage

To study the mechanism of action of Silver-Graphene-TiO2 composites cytoplasmic

leakage assay was done. The results showed that both DNA and proteins were released

from C. jejuni cells in response to exposure of lethal dose of Silver-Graphene-TiO2

composites as shown in Fig. 3.49.

3.6.1.6 Anti-biofilm Activity

Biofilm formation was significantly decreased in response to all TiO2 based

nanoparticles. Silver-Graphene-TiO2 composites (student’s t-test; P<0.005) resulted in

a 4-fold reduction in biofilm formation (Fig. 3.50).


Cytotoxicity of all TiO2 based nanoparticles was studied against Human neuroblastoma

cell line (SH-SY5Y). Although slight variation in cell viability was observed between

the different type of nanoparticles and no significant cytotoxicity was observed as the

percentage viability for all the samples were well above 70% (Fig. 3.51).

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130


Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles on C. jejuni motility. Untreated

bacterial cells were used as control. All nanoparticles significantly reduced the

motility of C. jejuni (student’s t-test; *P<0.05, **P<0.01, ***P<0.005).

Fig. 3.49 Inhibition of biofilm activity of C. jejuni by TiO2, TiO2-graphene

(TiO2/GR), Ag-TiO2 (TiO2/AG) and Ag/TiO2-graphene (TiO2/GR/AG nanoparticles.

All nanoparticles significantly reduced biofilm formation in C. jejuni (student’s t-test;

**P<0.01, ***P<0.005).

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131

Fig. 3.50 Leakage of DNA and protein in response to 2 and 4 h exposure of


leakage index. Untreated bacterial cells were used as control. Both DNA and proteins

were released from C. jejuni cells in response to exposure of lethal dose of Silver-

Graphene-TiO2 composites.

Fig. 3.51 Cytotoxicity of TiO2, TiO2-graphene (TiO2/GR), Ag-TiO2 (TiO2/AG)

and Ag/TiO2-graphene (TiO2/GR/AG) nanoparticles towards Human neuroblastoma

cells (SH-SY5Y). Untreated cells were used as control. No significant cytotoxicity was

observed

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132

3.6.2 Erbium doped Lithium Nickel Ferrite Nanoparticles


The broad spectrum antibacterial activity of different size erbium doped Li-Ni ferrite

nanoparticles was evaluated against clinical multidrug resistant strains of V. cholerae,

enteropathogenic E. coli, S. aureus, and C. jejuni. Minimum inhibitory concentration

of nanoparticles increased with increase in size of nanoparticles (R≥0.83) against all

test bacteria (Fig. 3.52). The effect of size dependency was most pronounced against C.

jejuni (R=0.997). The MIC of the smallest size erbium doped Li-Ni ferrite nanoparticles

i.e., 24 nm was measured to be 0.0162, 0.0162, 0.0625 and 0.0312 mg/ml for C. jejuni,

V. cholera, EPEC and S. aureus respectively.


To further investigate the effect of erbium doped Li-Ni ferrite nanoparticles (24 nm) on

cell viability survival assay was done which showed that viable cell count (CFU) of C.

jejuni decreased in response to exposure of nanoparticles by 2.5 log reduction in CFU

(Fig. 3.53) (student’s t-test; P<0.01)

3.6.2.3 DNA and Protein Leakage

To study the mechanism of action of erbium doped Li-Ni ferrite nanoparticles

cytoplasmic leakage assay was done. The results showed that both DNA and proteins

were released from C. jejuni cells in response to exposure of lethal dose of erbium

doped Li-Ni ferrite as shown in Fig. 3.54.


Exposure to erbium doped Li-Ni ferrite nanoparticles didn’t affected the motility of C.

jejuni cells as no difference in zone of motility was observed.

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133

Fig. 3.52 Size dependent antibacterial activity of Erbium doped Li-Ni ferrite

nanoparticles shown in terms of Minimum inhibitory concentration (MIC).

Fig. 3.53 Influence of Erbium doped Li-Ni ferrite nanoparticles on the growth of

C. jejuni. Untreated bacterial cells were used as control. C. jejuni growth (CFU /ml)

was significantly decreased in response to exposure of nanoparticles (student’s t-test;

P<0.01).

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134

Fig. 3.54 Leakage of DNA and protein in response to 2 and 4 h exposure of


leakage index. Untreated bacterial cells were used as control. Both DNA and proteins

were released from C. jejuni cells in response to exposure of lethal dose of erbium

doped Li-Ni ferrite.

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135


Anti-biofilm activity of erbium doped Li-Nickel ferrite was evaluated using micro titer

well plate method which showed that biofilm formation of C. jejuni was greatly reduced

by more the 3 folds as indicated in Fig. 3.55 (student’s t-test; P<0.005).


Cytotoxicity assay of different sized erbium doped Li-Nickel ferrite nanoparticles

against Human neuroblastoma cell line (SH-SY5Y) showed that no significant

cytotoxicity was observed as the percentage viability of cells exposed to all the different

sized Erbium doped Lithium Nickel ferrite nanoparticle (3.56).

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136

Fig. 3.55 Inhibition of biofilm activity of C. jejuni by erbium doped Li-Ni ferrite

nanoparticles. Untreated bacterial cells were used as control. Biofilm formation of C.

jejuni was greatly reduced in response to erbium doped Li-Ni ferrite nanoparticles

treatment (student’s t-test; P<0.005).

Fig. 3.56 Cytotoxicity of different sized erbium doped Li-Ni ferrite nanoparticles

towards Human neuroblastoma cells (SH-SY5Y). Untreated cells were used as control.

No significant cytotoxicity was observed.

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137

3.6.3 Zinc Oxide Nanoparticles


ZnO nanoparticles were tested for its broad spectrum antibacterial activity against three

gram-negative bacteria (Enteropathogenic E. coli, C. jejuni and V. cholera), and a

gram-positive bacterium (methicillin resistant Staphylococcus aureus). The results

showed that NPs were effective against all tested microorganism (3.57). However, the

ZnO nanoparticles were most effective against C. jejuni as shown by lowest MIC of

0.156mM as compared to other bacteria i.e., Enteropathogenic E. coli (0.156mM), V.

cholerae (MIC = 0.312mM) and S. aureus (0.625mM).


To investigate the effect of ZnO nanoparticles on cell viability survival assay was done.

Results showed that viable cell count (CFU) of C. jejuni decreased by 2 logs in response

to exposure of 4h to ZnO nanoparticle (Fig. 3.58) (student’s t-test; P<0.01).


Anti-biofilm activity of ZnO nanoparticles was evaluated using micro titer well plate

method which showed that biofilm formation of C. jejuni was greatly reduced by 4

folds as indicated in Fig. 3.59 (student’s t-test; P<0.005).


Cytotoxicity of ZnO nanoparticles was studied against Human neuroblastoma cell line

(SH-SY5Y). No significant cytotoxicity was observed as the percentage viability of

cells exposed to all tested nanoparticle (Fig. 3.60).

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138

Fig. 3.57 Determination of Minimum Inhibitory Concentration of ZnO

nanoparticles using tetrazolium chloride based micro-dilution method. The

nanoparticles were most effective against C. jejuni as shown by lowest MIC of

0.156mM.

Fig. 3.58 Influence of ZnO nanoparticles on the growth of C. jejuni. Untreated

bacterial cells were used as control. C. jejuni growth (CFU /ml) was significantly

decreased in response to exposure of nanoparticles (student’s t-test; P<0.01).

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139

Fig. 3.59 Inhibition of biofilm activity of C. jejuni by ZnO nanoparticles.

Untreated bacterial cells were used as control. Biofilm formation of C. jejuni was

greatly reduced in response to ZnO nanoparticles treatment (student’s t-test; P<0.005).

Fig. 3.60 Cytotoxicity of ZnO nanoparticles towards Human neuroblastoma cells

(SH-SY5Y). Untreated cells were used as control. No significant cytotoxicity was

observed.

Chapter 4 Discussion

140

Chapter 4

Discussion


141

Globally, diarrhoea is considered as the second leading cause of death among children

less than five years of age. Diarrhoea alone is responsible for death of 2,195 children

per day which is far more compared to that caused by AIDS, malaria, and measles

combined (Wardlaw et al., 2010). Approximately 80% of the child mortalities due to

diarrhoeal illness occur in South Asia and Africa (Wardlaw et al., 2010). In Pakistan

the annual mortality due to diarrhoea has been estimated to be 55,500 among children

(GDB, 2017). Campylobacter jejuni is one of the four main global causes of diarrhoeal

diseases and is recognized as the most common cause of bacterial associated acute

diarrhoea (WHO, 2012; Platts-Mills et al., 2015).

C. jejuni has been classified by ‘WHO’ as “High priority pathogens” due to emergence

of multidrug resistance, thus making surveillance necessary for the control of disease

(WHO, 2017b). The prevalence of multidrug resistance isolates of C. jejuni has been

under reported in developing countries like Pakistan, as compared to developed

countries, due to lack of proper surveillance program. The first aim of the present study

was to determine the prevalence of C. jejuni, its antimicrobial resistance profiling and

trace the potential sources of transmission of C. jejuni isolated from human clinical

cases in Pakistan. In our study C. jejuni was found to be present in 82 samples (n=150)

indicating a relative very high isolation rate of 54.6% compared to previously reported

rates in Pakistan of 11.3-29.5% during the period of 1993-2013 (Khalil et al., 1993; Ali

et al., 2003; Ibrahim et al., 2004; Siddiqui et al., 2015a). Overall 75% of isolates were

resistant to more than eight of the antibiotics. This increase in prevalence of C. jejuni

could be attributed to many reasons including the increase in antibiotic resistant strains

in the population in the past few years. To validate this hypothesis, we compared the

antibiotic resistance profile of C. jejuni to that of previously reported isolates from our

laboratory in year 2011-2012 (Siddiqui et al., 2015a). The results indicated an increased

rate of resistance to all the tested antibiotics. The percentage of resistant isolates to

ampicillin increased from 40% to 96%, streptomycin from 53% to 91%, ciprofloxacin

20% to 69%, erythromycin 27% to 96%, tetracycline 27% to 87%, sulphomethoxazole

+ trimethoprin 40% to 87%, gentamycin from 7% to 79%, chloramphenicol 20% to

36% and nalidixic acid 13% to 79% (Siddiqui et al., 2015a). Poultry related C. jejuni

isolates have earlier been reported to show higher resistance to antibiotics due to their

indiscriminate use as a growth promoter used in livestock feed (Thomas et al., 1998;


142

Luangtongkum et al., 2009). The high resistance profile observed in this study is

relatively similar to those reported in poultry isolates, as compared to earlier reported

clinical isolates, suggesting the possible transmission of such isolates from poultry to

humans (Wardak et al., 2007; Siddiqui et al., 2015b; Nguyen et al., 2016; Nisar et al.,

2017).

Antibiotics belonging to β-Lactams class have been used as preferable therapy due to

their high efficacy and low toxicity to humans (Wang et al., 2017). The choice of β-

Lactams is reduced to carbapenem when infections are caused by extended-spectrum

β-Lactamase (ESBL) producing organisms (Paterson et al., 2004; Vardakas et al.,

2012). Such extended-spectrum β-Lactamase (ESBL) producing isolates have also been

reported in C. jejuni but studies so far none have reported to be resistant to carbapenem

(Siddiqui et al., 2015a). In the present study 7.3% C. jejuni were found to show

resistance to Imipenem (member of carbapenem family) by combined disk method and

PCR based methods. This is the first report on emergence of Imipenem resistant isolates

among C. jejuni in clinical samples and hence may affect the treatment and subsequent

recovery among patients.

Tracing the potential source of C. jejuni infection can help develop better and effective

preventive strategies for campylobacteriosis. Genotyping of C. jejuni isolates by MLST

has been commonly employed for the clonal clustering of strains based on potential

source; however, it does not take into account genetics adaptation to specific

environment/niche. A source predictive Multiplex PCR, based on adaptive genotypes

identified by microarray analysis, has been developed by Stabler et al. (2013) to cluster

C. jejuni isolates into livestock and non-livestock groups. One of the objectives of the

current was to employ this multiplex source predictive PCR to assign strain clusters to

all the C. jejuni isolates. Overall 57.3% of the isolates belonged to C1 to C6 which

have been previously described as livestock-associated cluster comparatively 42.8% of

isolates belonging to C7 to C9 were predicted to be of non-livestock /environmental in

origin (Champion et al., 2005; Stabler et al., 2013). The MAR index is a health risk

assessment tool, used to identify whether the isolates are linked to a source with high

or low antibiotic exposure. High values indicate ‘higher-risk’ source of isolate (Davis


143

and Brown, 2016). Interestingly, in the present study isolates belonging to livestock

cluster had high MAR index (p<0.001) as compared to non-livestock suggesting

presence of more multidrug resistance among livestock origin isolates. Livestock is a

major part of agriculture sector in Pakistan and contributes a total of 11% to the

country’s agricultural gross domestic product (AGDP). However, with current farming

practices i.e. use of antimicrobials to cure and prevent disease as well as promote

growth has been extensive leading to a rise in multi-drug resistance in associated

microbiota including C. jejuni (Siddiqui et al., 2015a; Rehman et al., 2017). The

association of more resistant C. jejuni to livestock clades in the present study depicts

the ability for such strains to persist and spread, through the food chain, from animals

to human. High prevalence of antibiotic resistance and linkage of isolates, with high

MAR index, to livestock clade observed in the present study provide evidence of

possible transmission of C. jejuni from animals to human, thus posing serious health

concern.

C. jejuni is considered as a fragile microorganism outside its favorable niche or host

and lacks the usual stress response machinery present in other gut pathogen (i.e.,

Salmonella or E. coli) (Ramos et al., 2001; Park, 2002). However, it is still able to

persistence in the harsh environment such as acidic pH (in host gut and poultry

processing plants), cold and heat shocks (in poultry processing plants and in natural

water reservoirs) oxidative and nitrosative stresses (in the environment) and starvation

(in host and in environment) and is eventually transmitted via food chain to humans.

The mechanism by which C. jejuni withstand theses stresses is still unknown. Secretion

systems in many pathogenic and non-pathogenic bacteria provide selective advantage

and help withstand environmental stresses. Among all secretion system the type six

secretion system (T6SS) has been linked to virulence, inter-bacterial communication,

symbiosis, biofilm formation, antipathogenesis and environmental stress response in

many Gram-negative bacteria (Jani and Cotter 2010; Lertpiriyapong et al., 2012). The

T6SS has been recently discovered in C. jejuni and is associated with bloody diarrhoeal

cases (Harrison et al., 2014). The T6SS in C. jejuni is unique from other T6SSs as it is

seemingly not essential for bacterial survival or growth, even though it is active.

Moreover, it lacks the T6 secretion ATPase, ClpV, which is thought to provide energy

to the T6SS machinery (Bonemann et al., 2009). Little is known about the functioning


144

of T6SS in C. jejuni and its role in stress adaptation. Therefore, the second aim of the

present study was to study the role of type six secretion system in stress adaptation in

general i) by comparing biofilm formation of T6SS positive and negative isolates in

response to stresses; more specifically ii) by determining the structure and function of

Hcp protein (Hall mark protein of T6SS).

The effect of sub lethal stresses of pH (4.5), temperature (55ºC), and oxidative stress

(8mM) on motility, hydrophobicity, auto aggregation and biofilm formation of T6SS

positive and negative isolates was evaluated. Oxidative stress plays a key role in

enhancement / stimulation of biofilm formation in various bacterial species. Under

normal environmental conditions such as water and air C. jejuni faces unavoidably

harsh oxygen stress. This oxidative stress has been previously reported to enhance

sessile cells and stimulate biofilm formation (Reurer et al., 2010; Turonova et al., 2015;

Oh et al., 2016). Our results are in accordance with these studies as marked increase in

auto aggregation and hydrophobicity was observed in response to oxidative stress,

which leads to enhancement of biofilm formation in T6SS positive groups. However,

the effect of oxidative stress on auto aggregation and hydrophobicity was less

pronounced in T6SS negative group which lead to insignificant change in biofilm

formation. C. jejuni grows optimally at body temperature of human and birds i.e., 37

ºC and 42 ºC respectively. However, occurrence of C. jejuni infection in human due to

ingestion of under cooked meat and vegetables suggests its survival under heat stress.

In the present study biofilm formation was significantly more enhanced in T6SS

positive isolates as compared to T6SS negative isolates under heat stress as was

observed in case of oxidative stress. This is in accordance with the previous studies

which have shown that oxidative stress response in C. jejuni is co-regulated with that

of temperature stress via enhancement of catalase activity (Hazeleger et al., 1998). C.

jejuni, like other food borne pathogens, encounter acid stress during food

processing/preservation and in host stomach. In C. jejuni oxidative stress genes (such

as dps, sodB, trxB, and ahpC) also help it to survive under acidic stress (Birk et al.,

2012). In our study the biofilm formation was enhanced in both T6SS positive and

negative isolates as under acidic pH (4.5) stress. However, this sub lethal stress doesn’t

seem to cause any differential effect on any of the studied properties among T6SS

positive and negative groups. T6SS has been known to be down regulated under acidic


145

pH which can be reason that no difference in biofilm formation under acidic pH was

observed among T6SS positive and negative strains (Siddiqui et al., 2015b). To test this

hypothesis the structure and function of hemolysin co-regulatory protein (Hcp) as

secretory effect and role in biofilm formation was evaluated along with its virulence

potential.

Of the 13 core T6SS proteins, the hemolysin coregulated protein (Hcp) is considered

the hallmark of a functional system. Hcp is essential for both T6SS assembly and

function, with roles as structural and effector proteins (Mougous et al., 2006; Hood et

al., 2010; Lim et al., 2015). Many gram-negative bacteria possess more than one type

of Hcp that encodes either a structural or an effector protein; however, C. jejuni has

only one Hcp protein proposed to play both functions (Zhou et al., 2012). Functional

studies have shown that Hcp in C. jejuni mediates in vivo colonization by enhancing

adhesion and invasion into the eukaryotic host cell and providing resistance to bile salts

and deoxycholic acids (Lertpiriyapong et al., 2012; Bleumink-Pluym et al., 2013).

Furthermore, it enhances contact-dependent hemolysis (Bleumink-Pluym et al., 2013).

Previous functional studies on Hcp in C. jejuni have used Hcp mutant strains to shut

down T6SS functioning. Therefore, it is difficult to analyze the potential effector role

of Hcp based on previous findings. Six crystal structures of Hcp have been determined

to date, sharing overall similar hexametric ring architecture but varying greatly in their

functional ability (Mougous et al., 2006; Osipiuk et al., 2011; Douzi et al., 2014; Lim

et al., 2015; Jobichen et al., 2015; Ruiz et al., 2015) In the present study crystal structure

of Hcp-Cj along with its role in virulence and biofilm formation was determined. Hcp-

Cj showed limited sequence identity with the six other structurally characterized Hcp

proteins. However, structural alignment of Hcp-Cj shows a common hexameric ring

structure, with RMSD values between 1.9 Å and 4.8 Å. The main differences in the

secondary structures are the number of β sheets, the presence/absence of a one-turn α

helix, and the presence of overhang loops L1, 2 and L2, 3 which vary greatly in length

and composition (Noreen et al., 2018). Most of the conserved amino acids are located

on the external side of the ring and are exposed, whereas the residues in the inner

side/channel of the ring are more varied. Diversity among the different Hcp sequences,

especially in the inner side of the ring, suggests that these bacteria secrete different

proteins with different effector functions likely in response to different signals (Osipiuk


146

et al., 2011).Through these structural analyses, we show that Hcp-Cj belongs to Hcp

protein subclass II, along with Hcp3 of Pseudomonas aeruginosa, and that the

remaining Hcps with resolved structures belong to subclass I (Osipiuk et al., 2011).

Hcp protein in some bacteria e.g. P. aeruginosa V. cholerae, A. hydrophila, and B.

pseudomallei has been associated with providing selective advantage to bacteria by

killing other competing bacteria. In this study; Hcp-Cj was found to have no cytotoxic

effect on prokaryotic cells which is in accordance with previous functional assays, with

no selective growth advantage noted for the C. jejuni 108 strain in the presence of a

functional T6SS system (Bleumink-Pluym et al., 2013). Hcp in different bacteria are

associated with eukaryotic cell lysis and death (Suarez et al., 2007; Hood et al., 2010;

Zhou et al., 2012). Therefore, we next examined the effect of secreted Hcp-Cj protein

on the viability of red blood cells (RBC) and our results showed that Hcp-Cj was unable

to induce hemolysis in sheep erythrocytes. Although previous reports showed that the

presence of Hcp enhances the hemolytic ability of T6SS harboring C. jejuni, this

activity was not shown using culture supernatant, and suggests perhaps a contact-

dependent structural role of Hcp (Bleumink-Pluym et al., 2013). However, in the

present study, exposure of recombinant Hcp-Cj to HepG2 cells caused a significant

reduction in cell viability, suggesting a cytotoxic function. Furthermore, a structure-

based, point mutation in Hcp-Cj at Arg30 (Arg30Ala) resulted in a significant increase

in cell viability (P<0.01) as compared to recombinant-type Hcp-Cj, indicating the

importance of the loop region in inducing cytotoxicity (Noreen et al., 2018). Previous

studies have shown that the T6SS-positive C. jejuni 108 strain was unable to cause cell

lysis of Caco-2 intestinal epithelial cells, with the bacteria remaining trapped in the

endo-lysosomal compartment (Bleumink-Pluym et al., 2013; Bouwman et al., 2013).

The cytotoxicity observed in the present study may reflect the function of secreted Hcp-

Cj; indeed, others have reported that secretory Hcp1 from the meningitis-causing E.

coli K1 strain (sequence identity >57% with Hcp-Cj) causes cytotoxicity in human

brain microvascular endothelial cells (Zhou et al., 2012). Therefore, it can be

hypothesized that secreted Hcp-Cj binds to the surface of HepG2 cells, thereby

triggering cell apoptosis as reported earlier (Suarez et al., 2007; Zhou et al., 2012). Hcp

plays a significant role in the motility of several bacteria; however, in this study no


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change in the motility of C. jejuni strains was observed in response to Hcp-Cj exposure

(Das et al., 2002; Sha et al., 2013).

The T6SS enhances environmental adaptation and the survival of gram-negative

bacteria (Ho et al., 2014). Biofilm formation helps bacteria contend with harsh

environmental stressors in natural, clinical and industrials setups (Nguyen et al., 2012;

Turonova et al., 2015). The T6SS has a diverse impact on biofilm formation in various

bacteria; in some bacteria, it enhances biofilm formation (Acinetobacter baumannii;

Avian-pathogenic Escherichia coli, Acidovorax citrulli, enteroaggregative Escherichia

coli); in others, it aids in biofilm maturation (Pseudomonas fluorescens) or has no effect

(Vibrio alginolyticus) (de Pace et al., 2011; Tian et al., 2015; Gallique et al., 2017; Kim

et al., 2017). The role of T6SS in C. jejuni biofilm formation had yet to be reported,

which led us to study the effect of secretory Hcp-Cj on biofilm formation in both T6SS-

positive and -negative strains. We found that the establishment of biofilm was

independent of the presence or absence of Hcp-Cj in both strains. However, the volume

of biofilm formation was significantly enhanced in all C. jejuni isolates (P < 0.01). The

effect of Hcp-Cj exposure and the reduction in biofilm formation was more pronounced

in T6SS-positive isolates as compared with T6SS-negative isolates (P < 0.05). This is

likely because all the T6SS-positive strains were weak biofilm formers in the absence

of Hcp as compared to T6SS-negative strains. A change in biofilm formation was

observed in HcpR30A and HcpY31A mutants as compared to recombinant-type Hcp-

Cj; however, this difference was not statistically significant. The T6SS in many bacteria

is known to be involved in biofilm formation but the mechanistic bases have not been

described yet. Hcp has been recently shown to be secreted and accumulation in sister

cells in a manner similar to auto-inducer accumulation in quorum sensing (Vettiger and

Basler, 2016; Gallique et al., 2017). Hcp-Cj may possibly act in the same way as auto-

inducers for biofilm formation, however; additional experiments are required to

validate this hypothesis (Noreen et al., 2018).

Infections caused by C. jejuni in humans are generally self-limiting and the

administration of antibiotics in required only in children and immune-compromised

patients. However, extensive use of antibiotics especially in poultry has led to

emergence of multidrug resistant C. jejuni among both chicken and clinical samples


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(Moore et al., 2006; Kittl et al., 2011; FoodNet, 2012). C. jejuni strains resistant to the

two-recommended drugs of choice i.e., erythromycin and ciprofloxacin have been

reported from various parts of the world (Sharma et al., 2003; Moore et al., 2006;

Feizabadi et al., 2007; Mattheus et al., 2012; Siddiqui et al., 2015a). Such resistant

strains not only delay the recovery process but also lead to increase in possibility of

sequels. Therefore the third aim of the present study was to develop control strategies

which can provide alternate solution at three different levels i.e., 1) in-silico drug target

identification for development of drug against MDR C. jejuni in future, 2) nano-carrier

based targeted delivery of natural anti-campylobacter products as an on-farm control

strategy to reduce load of C. jejuni among chicken and 3) metallic nanoparticles as a

coating material for control of C. jejuni biofilms.

New antibiotics/drugs development process is costly, laborious and eventually lead to

development of resistance in bacteria against them (Katz et al., 2006; Nicolle, 2006).

An alternate strategy is to identify novel and essential drug target which are important

for survival of pathogenic bacteria as such genes have high rate of evolutionary

conservation (Rocha and Danchin, 2003; Gustafson et al., 2006; Deng et al., 2011).

Computational analysis of the available genomics, proteomes, microarray, and

metabolomics data of the specific pathogen is done to identify and characterize unique

and essential protein targets sites (Zhang et al., 2005). The present study uses a

combination of subtractive proteomics and comparative metabolic pathway analysis

approach to identify potential drug targets in C. jejuni (11168) which may lead to

development of novel and highly specific drugs to control infections with least side

effects on host (Barh and Kumar, 2009; Rathi et al., 2009; Butt et al., 2012; Ahn et al.,

2014). Overall 10 proteins were shortlisted as the most potential drug targets which are

not only essential for the survival of C. jejuni but also share no homology to human and

chicken proteomes. Furthermore, with least homology to human gut flora these targets

will help to develop more specific and effective drug with minimum side effects on

human health (Raman et al., 2008; Shanmugham and Pan, 2013).

Human campylobacteriosis can mainly originate through consumption of undercooked

food (especially poultry meat), unpasteurized milk, contaminated water and contact

with either infected animal or person (Friedman, 2000; Domingues, 2012). Intake of


149

contaminated undercooked poultry has been considered as the major cause of

Campylobacteriosis in humans (Friedman et al., 2000). Quantitative risk assessment

has shown that 2-3 log reduction of C. jejuni load in the intestines/carcass of chickens

would lead to 90% decrease in campylobacteriosis case as it is the only amplifying

point of C. jejuni in the whole food chain (Rosenquist et al., 2003; EFSA, 2011).

Therefore, most of the approaches have been designed to control Campylobacteriosis

are targeted to reduce the load of C. jejuni in poultry, however till date, there is no safe,

effective, reliable, and practical intervention measure available to reduce C. jejuni

colonization in poultry (Lin, 2009; Ghareeb et al., 2013).

Over the past few decades there has been decreased acceptability among consumers of

administration of synthetic additives in food chain which has led to development and

use of natural antimicrobial compounds as animal feed additive (Verbeke et al., 2007;

Brenes and Roura, 2010; Navarro et al., 2015). Therefore, in the present study several

plant extracts, which are been reported to be used in traditional medicine, were screened

for their anti-campylobacter activity i.e., Berberis lycium (bark), Trachyspermum

annum (seeds), Nigella sativa (seeds), Camellia sinensis (leaves), Mentha longifolia

(leaves). Out of these plants Trachyspermum ammi showed excellent antibacterial

activity and its hexane fraction caused complete cell death of C. jejuni within 4h of

exposure. The hexane fraction was found to be composed of four major components by

GC-MS analysis i.e. Mitozolomide, 1-4 Cyclohexadiene, Thymol, and Hydroxy, 3

methyl acetophenone. Of all these compounds thymol (2-isopropyl-5-methylphenol),

which was found to be the most abundant content in hexane fraction, has been reported

earlier as a strong antimicrobial against different pathogenic bacteria as it binds to with

bacterial membrane proteins and causes cell lysis (Shah et al., 2012). Thymol is also

classified as ‘generally recognized as safe’ (GRAS) by the U.S. Food and Drug

Administration (FDA) and is also biodegradable. Therefore, thymol has wide

application in the medical, food and agricultural setups. Due to low water solubility

(hydrophobicity) it is difficult to administer orally in poultry, and furthermore the

thymol is hydrolyzed at acidic pH thereby making it impossible to reach chicken in its

100% activity form. To overcome the problem in this study, the hexane fraction of

Trachyspermum ammi was encapsulated in alginate coated chitosan nanoparticles.

Chitosan is a biodegradable polymer which has been recently used as nanocarrier


150

system due to its muco-adhesive, broad spectrum antibacterial and biocompatible

nature (Rampino et al., 2013; Chaubey and Mishra, 2014; Piras et al., 2015). Such

nanocarrier system improves the solubility, stability, metabolism, and clearance of the

encapsulated drug/moieties. Muco-adhesive property of chitosan help prolongs

residence time of drug in the intestine thus enhancing its antibacterial effect. However,

chitosan is soluble at acidic pH thus most of the drug is lost in stomach if administered

orally. Therefore, in the present study chitosan nanoparticles were coated with alginate

which is stable at acid pH. Our nanocarrier system i.e., alginate coated chitosan

nanoparticles were designed for targeted delivery of hexane fraction of T. ammi into

the chicken caecum without loss of its activity in gizzard. In the present study the plant

extract was encapsulated in chitosan nanoparticle which was then coated with alginate

and their size was confirmed using SEM and AFM. Previous studies in which alginate

coated chitosan nanoparticle have been reported to be of larger in size ranging from

213-404 nm, in contrast to this study both empty and plant extract encapsulated CANP

were less than 100 nm in diameter (Li et al., 2008; Barge et al., 2013; Wang et al.,

2017). However, the size of PE-CNP increased with the coating of alginate from

54.68nm to 68.78 nm which is in accordance with that reported by Barge et al., 2013.

FTIR spectroscopy was done to confirm the successful encapsulation of plant extract

and to study its interaction with the nanocarrier system. The FTIR spectrum for

Chitosan alginate nanoparticles (CANP) observed in the present study was in

accordance with previous studies (Körpe et al., 2014; Bhunchu et al., 2015). In case of

plant extract the spectrum resembled that of thymol as reported by Valderrama and

Rojas De (2017). The PE-CANP showed peaks corresponding to both CANP and plant

extract indicating successful encapsulation. As there was no additional peak observed

it was suggested that there was no interaction between plant extract and CANP. The

encapsulation efficiency of CANP was observed to be 85% indicating the chitosan

alginate complex as excellent encapsulation material for hydrophobic plant extract

(Natrajan et al., 2015). The in vitro release of plant extract from CANP at neutral pH

(7.0) was much faster than that at acidic pH (3.0) for the period of 24 h. At pH 7.0 initial

burst release of plant extract was observed up to 4 h (which accounts for 40% of the

total encapsulated amount) followed by a sustained release phase for the next 20 h. Less

than 12 % of the plant extract was released at acidic pH due to the fact that alginate


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forms a tight crosslinking network at low pH (Vandenberg and De La Noue 2001; Coppi

et al., 2002;). Moreover, the reduced porosity of alginate coated chitosan nanoparticles

protects the encapsulated drug/compound thus accounting for acid environment

protection and control release in gastrointestinal tract (Katuwavila et al., 2016).

In-vivo trial in chicken showed significant reduction in CFU count of C. jejuni in fecal

sample at both 7th and 14th day of infection among all treated groups. Plant extract

initially showed 4 logs reduction in CFU/g of fecal sample at day7 post infection which

was decreased to 3 logs after 14 days. However, in case of PE-CANP (Plant extract

encapsulated alginate coated chitosan nanoparticles as feed additive) initially showed 2

log reduction which was increased to 3.5 logs after 14 days. This sustained reduction

indicates control/sustained release of plant extract from PE-CANP nanoparticles after

14 days. The blank CANP group (empty alginate coated nanoparticles as feed additive)

caused decrease in CFU/g of fecal sample but the effect remains the same after 7- and

14-day post infection indicating the intrinsic antimicrobial activity of chitosan alginate

complex (Jamil et al., 2016). Similar trend was observed after 21 days post infection in

whereby 6 logs reduction in CFU/g of caecal content was observed in PE-CANP group

whereas the efficiency of plant extract was reduced to 1.5 logs in PE group. Similar

control release of antibacterial essential oil has been reported earlier in in vitro studies;

however, this is the first study on in-vivo trail of nano-encapsulated plant extract

showing significant reduction in C. jejuni load in Chicken (Hsieh et al., 2006; Hosseini

et al., 2013; Jamil et al., 2016; Sotelo-Boyás et al., 2017).

Although C. jejuni is fastidious in nature but it possesses the ability to persist on food

and in the environment for relatively longer periods due to its ability of surface

attachment and biofilms formation (Buswell et al., 1998; Kalmokoff et al., 2006). In

poultry farms, C. jejuni adhere to door handles, utensils and other abiotic surfaces and

help transmission of bacteria from an infected flock to the next flock resulting in spread

of contamination. Similarly, biofilm formation by C. jejuni in chicken meat processing

setup also contributes towards persistence of bacteria in human food chain (Balogu et

al., 2014; Brown et al., 2014). In the present study the anti-campylobacter and anti-


152

biofilm activity of three different metal oxide nanoparticles was evaluated i.e., TiO2

based, Ferrite based and Zinc Oxide.

As most of objects/surfaces in the environment/food processing plants on which C.

jejuni form biofilm are exposed to visible light sources therefore visible-light-induced

photo catalysts can be considered as a useful coating material for disinfection.

Therefore, in the present study visible light induced Silver-Graphene-TiO2

(TiO2/Ag/Gr) and its parent derivative were evaluated for their ability to control both

growth and biofilm formation of C. jejuni. All the TiO2 based nanocomposites (TIO2,

TiO2/Ag, TiO2/Gr and TiO2/Ag/Gr showed broad spectrum antibacterial activity

against C. jejuni, V. cholerae, E. coli, and S. aureus which is in accordance with

previous studies (Maness et al., 1999). The effect of TiO2 and its derived nanoparticles

on the cell survival, membrane integrity, and cellular motility was evaluated to get an

insight into the mechanism of action against C. jejuni. Cell survival assay was carried

out against C. jejuni which showed that viable cell count (CFUs) decreased in response

to exposure of all the synthesized nanoparticles. TiO2 nanoparticles exposure resulted

in 1 log reduction in viable bacterial colonies as compared 1.5 log reduction by

Silver/TiO2 and TiO2/Graphene nanocomposites indicating that addition of Silver and

Graphene enhance the killing potential of TiO2. The enhancement in antibacterial

activity of TiO2 by addition of Silver ions can be due to reasons that (i) Ag ions directly

interacts with thiol group of vital enzymes and deactivates them (ii) Ag ions extend the

light absorption of TiO2 from UV into the visible range, indirectly inducing

photocatalytic antibacterial activity of TiO2 under visible light (Feng et al., 2000;

Harikishorea et al., 2014). Similarly, higher antibacterial effect of TiO2/Graphene

compared to pure TiO2 nanoparticles could be due to the fact Graphene not only extends

light absorption range but can also be used as electron acceptor and transporter resulting

thus producing more oxides and hydroxyl ions involved in the antibacterial activity

(Cao et al., 2013). Silver-Graphene-TiO2 composites was most lethal of all the

nanoparticles as indicated by 2 log reduction which can be contributed towards the

synergistic antibacterial effect of silver, graphene and titanium oxide. Cytoplasmic

leakage assay showed that the exposure to Silver-TiO2 and Silver-Graphene-TiO2

nanoparticles resulted in release of significant higher amount of both DNA and RNA


153

from C. jejuni cells. Similar results have been reported by Singh et al., (2016) whereby

silver nanoparticle resulted in cytoplasmic leakage in S. dysentriae.

In the present study the effect of TiO2 based nanoparticles on virulence properties of C.

jejuni i.e., autoaggregation, hydrophobicity and motility, was also investigated.

Autoaggregation and hydrophobicity are physicochemical surface properties of

pathogenic bacteria which are considered as virulence markers in virulence in several

Gram-negative bacteria (Menozzi et al., 1994; Chiang et al., 1995). Auto aggregation

plays an important role in host cell invasion and helps establish infection. In this study

autoaggregation capability of C. jejuni strain decreased significantly when exposed to

sub-lethal concentration of Silver doped TiO2 (Ag-TiO2) (p<0.01) and Silver-

Graphene-TiO2 composites (p<0.005) whereas TiO2, and Graphene-TiO2 had not effect

on auto aggregation. Hydrophobicity is another important cell surface hydrophobicity

and is positively correlated with autoaggregation (Saran et al., 2012). Silver-Graphene-

TiO2 composites exposure resulted in significant decrease in hydrophobicity of

bacterial cell thus reducing their ability to bind to host cell as well as in environment

rendering it vulnerable to host immune system and harsh environmental conditions

respectively. Motility plays a critical role in colonization of C. jejuni by allowing it to

penetrate mucus lining of gut and eventual invasion of intestinal epithelial cells. High

motility also helps bacteria to evade bile salt and the antimicrobial effect of the human

serum which may be detrimental to C. jejuni (Wassenaar et al., 1993; Guerry et al.,

2000). In the present study Silver doped TiO2 (Ag-TiO2) (p<0.005) and Silver-

Graphene-TiO2 composites decreased the motility of C. jejuni up to 60% indicating its

effect on the overall virulence potential of bacteria. Biofilm formation was significantly

decreased in response to all the synthesized nanoparticles. Silver-Graphene-TiO2

composites (p<0.005) resulted in 4 times reduction in biofilm formation.

Autoaggregation has been reported to be correlated with strength of biofilm production

(Abdel-Nour et al., 2014), similarly in our study the decrease in biofilm formation was

seen when autoaggregation was negatively affected by the nanoparticles. The present

study suggests that Silver-Graphene-TiO2 composites can be used as a safe and self-

cleaning antibacterial and coating agent to control spread of C. jejuni.


154

Ferrite nanoparticles are gaining importance as a promising candidate for the

biomedical applications such as magnetic hyperthermia (for cancer treatment), targeted

drug delivery and as antibacterial agents (Liu et al., 2000; Kim et al., 2008). Ferrite due

to its excellent magnetic properties can adhere to metallic objects and are therefore

attractive choice as coating materials in medical and food processing setup. Doping of

various transitions and rare earth metal ions at different sub lattices of the spinel lattice

not only improve the electromagnetic properties but also enhance their antibacterial

activities. Therefore, in the present study the antibacterial and anti-biofilm activity of

erbium doped Li-Ni ferrite nanoparticles was evaluated against C. jejuni. Erbium doped

Li-Ni ferrite nanoparticles showed broad spectrum activity against clinical multidrug

resistant strains of V. cholerae, enteropathogenic E. coli, S. aureus and C. jejuni. This

antibacterial activity was found to be size dependent as the minimum inhibitory

concentration of nanoparticles increased with increase in the size of nanoparticles

against all test bacteria. This suggests that the antibacterial activity is also contact

dependent because increase in the volume to surface ratio enhances the antibacterial

potency. The effect of size dependency was most pronounced against C. jejuni

(R=0.997). To study the mechanism of action of erbium doped Li-Ni ferrite

nanoparticles survival assay, motility cytoplasmic leakage assay was done. The results

showed that 2-log reduction in CFU of C. jejuni. Both DNA and proteins were released

from C. jejuni cells in response to exposure of lethal dose of erbium doped Li-Ni ferrite.

Several mechanisms of action of ferrites have been proposed which include 1) the

release of reactive oxygen species such as hydroxyl ions, peroxides and super-oxides

from ferrites, which penetrate the bacterial cell wall and cause cell death, and 2) the

penetration and release of toxic metals from nanoparticles (Velho-Pereira et al., 2015).

Our study supports both mechanism of action of ferrite. As Li-Ni ferrites was effective

against both facultative aerobic and microaerophilic bacteria suggesting that oxidative

stress is not alone responsible for the observed activity, NP might have released toxic

metals into the cell. Erbium doped Lithium-Nickel ferrite showed excellent anti-biofilm

activity against C. jejuni. This is the first report on the anti-biofilm activity of any type

of ferrites and indicates that Li-Ni can act as a good coating agent to reduce the biofilm

formation in food processing setup (Noreen et al., 2017).


155

Zinc oxide (ZnO) is s “Generally Recognized as Safe” by FDA (Food and Drug

Administration, USA) and is commonly used in food as additive (as source of zinc) or

preservative. Zinc Oxide has an intrinsic antibacterial ability which is further enhanced

by reducing their size to nanometer (less than 100nm) (Xie et al., 2011). Zinc

nanoparticles have high surface to volume ratio which increases its interaction with

bacterial cells thereby enhancing it antibacterial potential. In the present study the ZnO

nanoparticles showed broad spectrum antibacterial activities against both Gram-

positive and Gram-negative bacteria which is in accordance with the previous studies

(Jones et al., 2008; Liu et al., 2009). However, the ZnO nanoparticles were

comparatively more effective against C. jejuni having a lower MIC values (i.e., 0.156

mM) than that reported earlier (MIC=0.30 mM) (Xie et al., 2011). ZnO nanoparticles

used in the present study shown no significant cytotoxicity towards human cell line

which is in accordance with the previous reports (Reddy et al., 2007). The bactericidal

effect of ZnO nanoparticle was confirmed by decrease the viable cell count (CFU) of

C. jejuni by 2 logs within 4 h of exposure. The ZnO nanoparticles showed excellent

anti-biofilm activity against C. jejuni (4 folds reduction) at a very low concentration

(i.e., 0.078mM) as compared to a similar reduction in biofilm reported at a higher

concentration of nanoparticle (i.e., 0.30mM) (Lu et al., 2012). Therefore, the ZnO

nanoparticles evaluated in the present study can serve as an efficient antibacterial and

anti-biofilm material for control of biofilm formation of C. jejuni which will, in turn,

prevent its transmission in food chain.

4.1 Conclusions

From the present study it is concluded that i) Multidrug resistant C. jejuni strains with

high MAR index were associated with livestock sources implying the strict regulation

for use of these antibiotics as growth promoters in food animals and the veterinary

industry; ii) Secretory Hcp play a role in cytotoxicity towards eukaryotic cells and

enhances biofilm formation in C. jejuni, thereby aiding the bacterium survival in the

harsh environments; iii) Ten essential non-homologous drug targets were identified

using in silico approach which can be used in future to developed safe and effective

drug; Nano encapsulated hexane fraction of T. ammi (PE-CANP) reduced C. jejuni load

to 6 logs in chicken trial and can therefore be used as a good alternative to conventional

antibiotics; Silver/Graphene/TiO2, Li-Ni Ferrites and ZnO nanoparticle showed


156

promising antibacterial and anti-biofilm activity, thus can be used as coating material

for control of C. jejuni.

4.2 Future Prospects

Monitoring and surveillance of C. jejuni at various stages of meat production from farm

to folk can be done to track the potential stage of contamination. Structure and function

of other T6SS effectors proteins can be studied in future. To control multidrug resistant

C. jejuni screening of different drugs against the in silico identified drug targets could

be done to identify new drugs for treatment. Furthermore, testing other natural plant-

based drugs for control of C. jejuni in chicken could be done in future.

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Chapter 5

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188

Annexure

189

Metadata of C. jejuni positive samples

Sample

ID

Date City Gender Age Fever

(C)

Diarrhoea/watery

diarrhoea/bloody

diarrhoea

Income

group

Dehydration Group

Predicted

MAR

index

BH1 Jan-15 Rawalpindi Male 9 Months 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

BH2 Jan-15 Rawalpindi Male 9 Months 37.5 Watery diarrhoea LIC Severe C9 0.71

BH3 Jan-15 Rawalpindi Male 3 Months 38 Watery diarrhoea LIC Severe C1/C2/C3 0.57

BH4 Jan-15 Rawalpindi Male 8 Months 37 Watery diarrhoea LIC Severe C7/C8 0.50

BH5 Jan-15 Rawalpindi Male 3 years 38 Diarrhoea LIC Some C7/C8 0.57

BH6 Jan-15 Rawalpindi Male 3 years 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

BH7 Jan-15 Rawalpindi Female 5 months 38 Watery diarrhoea LIC Severe C7/C8 0.43

BH11 Jan-15 Rawalpindi Female 3.5 Months 38 Watery diarrhoea LIC Severe C9 0.64

BH12 Jan-15 Rawalpindi Female 1 year 38 Watery diarrhoea LIC Severe C4/C6 0.79

BH14A Jan-15 Rawalpindi Female 10 months 37.5 Diarrhoea LIC Some C1/C2/C3 0.79

BH15 Jan-15 Rawalpindi Male 7 Months 38 Diarrhoea LIC Some C5 0.71

BH20 Jan-15 Rawalpindi Female 1.5 years 37.5 Diarrhoea LIC Some C4/C6 0.64

BH21 Jan-15 Rawalpindi Female 8 Months 37 Diarrhoea LIC Some C5 0.71

BH22 Jan-15 Rawalpindi Male 11 months 37 Diarrhoea LIC Some C4/C6 0.50

BH24 Jan-15 Rawalpindi Female 8 Months 37 diarrhoea LIC Some C7/C8 0.57

190

BH26 Jan-15 Rawalpindi Male 8 Months 38 Watery diarrhoea LIC Severe C9 0.43

BH28 Jan-15 Rawalpindi Male 10 months 38 Diarrhoea LIC Some C9 0.43

BH31 Jan-15 Rawalpindi Female 4 months 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

BH35 Jan-15 Rawalpindi Female 2 months 38 diarrhoea LIC Some C7/C8 0.43

BH37 Jan-15 Rawalpindi Male 9 Months 38 diarrhoea LIC Some C1/C2/C3 0.71

BH39 Jan-15 Rawalpindi Male 4 months 37.5 Watery diarrhoea LIC Severe C7/C8 0.57

BH44 Jan-15 Rawalpindi Male 7 Months 38 Watery diarrhoea LIC Severe C4/C6 0.79

RPH1 May-15 Islamabad Female 5 months 37.5 Diarrhoea MIC Some C4/C6 0.71

RPH2 May-15 Islamabad Female 2 years 37.5 Watery diarrhoea MIC Severe C1/C2/C3 0.71

RPH3 May-15 Islamabad Male 3month 37.5 Watery diarrhoea MIC Severe C9 0.50

LH1

(s1)

May-15 Lahore Male 5years 37.5 Watery diarrhoea MIC Severe C4/C6 0.79

LH3

(s2)

May-15 Lahore Male 3 years 37.5 Watery diarrhoea MIC Severe C4/C6 0.79

st Aug-15 Peshawar Female 1 year 38 Bloody Diarrhoea MIC Severe C9 0.64

SH6 May-15 Khairpur Female 10 months 37.5 Watery diarrhoea LIC Severe C1/C2/C3 0.64

SH8 May-15 Khairpur Female 4.5 years 37.5 Watery diarrhoea LIC Severe C4/C6 0.79

SH10 May-15 Khairpur Male 2.5 years 37 Watery diarrhoea LIC Severe C1/C2/C3 0.79

SH10J May-15 Khairpur Female 1 year 37.5 Watery diarrhoea LIC Severe C4/C6 0.71

191

SH11 May-15 Khairpur Female 3.5 years 37 Watery diarrhoea LIC Severe C5 0.71

SH17 May-15 Khairpur Male 10 months 37 Watery diarrhoea LIC Severe C7/C8 0.50

SH19 May-15 Khairpur Male 4 years 37.5 Watery diarrhoea LIC Severe C5 0.71

SH32 May-15 Khairpur Female 3 years 37.5 Watery diarrhoea LIC Severe C4/C6 0.64

SH56 May-15 Khairpur Female 11 months 37.5 Watery diarrhoea LIC Severe C1/C2/C3 0.71


SH60 May-15 Khairpur Male 5 years 37.5 Watery diarrhoea LIC Severe C4/C6 0.64


SH64 May-15 Khairpur Female 1 year 37 Watery diarrhoea LIC Severe C4/C6 0.71

PH2 Jul-15 Peshawar Male 2.5 years 37.5 Watery diarrhoea MIC Severe C5 0.71

PH7 Jul-15 Peshawar Male 3 years 37.5 Watery diarrhoea LIC Severe C4/C6 0.64

PH8 Jul-15 Peshawar Male 4 years 37 Watery diarrhoea MIC Severe C5 0.64

PH9 Jul-15 Peshawar Male 1.25 year 37.5 Watery diarrhoea LIC Severe C5 0.50

PH11 Jul-15 Peshawar Male 8 months 37.5 Watery diarrhoea MIC Severe C1/C2/C3 0.71

PH12 Jul-15 Peshawar Male 3 years 37.5 Watery diarrhoea LIC Severe C5 0.64

PH13 Jul-15 Peshawar Male 1.5 years 37.5 Diarrhoea LIC Some C4/C6 0.57

PH14 Jul-15 Mardan Male 1 year 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

PH15 Jul-15 Mardan Male 6 months 37.5 Watery diarrhoea LIC Severe C1/C2/C3 0.64

192

PH16 Jul-15 Mardan Male 2.5 years 37 Watery diarrhoea LIC Severe C5 0.71

PH17 Jul-15 Peshawar Male 2.5 years 37.5 Watery diarrhoea MIC Severe C4/C6 0.57

PH18 Jul-15 Peshawar Male 10 months 37.5 Watery diarrhoea LIC Severe C7/C8 0.50

PH19 Jul-15 Peshawar Male 3 years 37 Watery diarrhoea MIC Severe C4/C6 0.64

PH20 Jul-15 Peshawar Male 4.5 years 37.5 Watery diarrhoea MIC Severe C7/C8 0.50

PH21 Jul-15 Peshawar Male 1.5 years 37.5 Watery diarrhoea LIC Severe C1/C2/C3 0.64

PH22 Jul-15 Peshawar Male 11 months 37.5 Watery diarrhoea LIC Severe C5 0.71

PH25 Jul-15 Nowshera Male 5 years 37 Watery diarrhoea LIC Severe C4/C6 0.79

PH26 Jul-15 Nowshera Male 1.5 years 37.5 Watery diarrhoea LIC Severe C4/C6 0.64

PH28 Jul-15 Peshawar Male 1.5 years 37.5 Watery diarrhoea MIC Severe C5 0.71

PH29 Jul-15 Peshawar Male 2 years 37 Watery diarrhoea LIC Severe C4/C6 0.71

PH30 Jul-15 Peshawar Male 1.5 years 37 Watery diarrhoea LIC Severe C5 0.64

PH30A Jul-15 Peshawar Male 3 years 37.5 Watery diarrhoea MIC Severe C9 0.50

MC4 May-15 Nowshera Male 3 years 37.5 Watery diarrhoea LIC Severe C5 0.64

MC7 May-15 Nowshera Male 2.5 years 37.5 Watery diarrhoea LIC Severe C7/C8 0.57

MC8 May-15 Mardan Male 1.5 years 37.5 Watery diarrhoea LIC Severe C1/C2/C3 0.64

MC9 May-15 Mardan Male 4.5 years 37.5 Watery diarrhoea LIC Severe C7/C8 0.57

MC13 May-15 Mardan Male 3 years 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

193

AS3 Aug-15 Islamabad Male 2 months 37.5 Diarrhoea MIC Some C9 0.36

AS5 Aug-15 Islamabad Female 1 year 37 Diarrhoea LIC Some C1/C2/C3 0.57

AS8 Aug-15 Islamabad Male 11 months 37.5 Watery diarrhoea LIC Severe C9 0.43

AS10 Aug-15 Islamabad Male 4 months 37.5 Watery diarrhoea LIC Severe C7/C8 0.64

AS11 Aug-15 Islamabad Male 6 months 37.5 Watery diarrhoea MIC Severe C9 0.36

AS31 Aug-15 Islamabad Female 11 months 38 Diarrhoea LIC Some C9 0.36

AS38 Aug-15 Islamabad Female 10 months 37.5 Watery diarrhoea LIC Severe C4/C6 0.71

AS51 Aug-15 Islamabad Male 4 months 38 Watery diarrhoea LIC Severe C1/C2/C3 0.71

AS59 Aug-15 Islamabad Female 8 Months 37.5 Diarrhoea LIC Some C9 0.50

AS65 Aug-15 Islamabad Male 8 Months 37 Watery diarrhoea MIC Severe C7/C8 0.50

AS70 Aug-15 Islamabad Male 1 year 37 Diarrhoea LIC Some C4/C6 0.71

AS74 Aug-15 Islamabad Female 2 years 37.5 Diarrhoea LIC Some C9 0.36

AS85 Aug-15 Islamabad Female 11 months 37.5 Diarrhoea LIC Some C9 0.64

AS89 Aug-15 Islamabad Female 3.5 years 38 Watery diarrhoea LIC Severe C7/C8 0.43

LIC-low income group

MIC- middle income group

role of type vi secretion system in stress adaptations and

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