interactions of cationic antimicrobial peptides with ... · from the sequence...

Interactions of Cationic Antimicrobial Peptides with Bacterial Membranes and Biofilms

by

Lois Menglu Yin

A thesis submitted in conformity with the requirements for the degree of Master of Science

Department of Biochemistry University of Toronto

© Copyright by Lois Menglu Yin 2012

ii

Interactions of Cationic Antimicrobial Peptides with Bacterial

Membranes and Biofilms

Lois Menglu Yin

Master of Science

Department of Biochemistry

University of Toronto

2012

Abstract

Cationic antimicrobial peptides (CAPs) offer a viable alternative to conventional antibiotics as

they physically disrupt the bacterial membranes, leading to cell lysis and death. However,

colonized bacteria often form “biofilms” – characterized by the overproduction of

exopolysaccharides - that restrict the penetration of antibiotics; successful antimicrobial agents

must evade this exopolysaccharide ‘matrix’ to reach the bacterial membrane. Since the

Pseudomonas aeruginosa biofilm alginate traps CAPs by forming peptide-alginate complexes,

the aim of this thesis is to better understand the mechanisms of interaction of CAPs with

bacterial membranes and biofilm alginate. Using a series of CAPs designed in our lab derived

from the sequence KKKKKK-AAFAAWAAFAA-NH2, we found that hydrophobicity, charge

distribution, and amino acid composition of CAPs play important roles in their membrane

disruptive power, bioactivities, alginate-binding and alginate-diffusion abilities. These findings

suggest routes to an optimal balance of factors in CAP design to allow both biofilm penetration

and bacterial membrane destruction.

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Table of Contents

Abstract .......................................................................................................................................... ii

Table of Contents ......................................................................................................................... iii

List of Figures .............................................................................................................................. vii

List of Tables ................................................................................................................................ xi

List of Appendices ....................................................................................................................... xii

List of Abbreviations ................................................................................................................. xiii

Chapter 1 Introduction..................................................................................................................1

1.1 BIOFILMS ...........................................................................................................................2

1.1.1 Formation of biofilms ..............................................................................................2

1.1.2 Environmental and medical problems caused by biofilms ......................................4

1.1.3 Pseudomonas aeruginosa ........................................................................................5

1.1.4 Biofilm exopolysaccharides .....................................................................................6

1.1.5 Alginate ....................................................................................................................7

1.1.6 Mechanisms of biofilm resistance to antimicrobial agents ......................................9

1.1.7 Conventional antibiotics and current treatments for P. aeruginosa infections ......11

1.2 ANTIMICROBIAL PEPTIDES ........................................................................................13

1.2.1 Natural Antimicrobial Peptides..............................................................................13

1.2.2 Mechanisms of Action ...........................................................................................15

1.2.3 De novo Design of Novel CAPs ............................................................................17

1.3 PEPTIDE-MEMBRANE INTERACTIONS .....................................................................22

1.3.1 Composition of Bacterial vs. Mammalian Membranes .........................................22

iv

1.3.2 Basis for selectivity of CAPs .................................................................................22

1.3.3 Toxicity Threshold of CAPs ..................................................................................24

1.3.4 Effect of Cholesterol in CAP Selectivity ...............................................................26

1.4 PEPTIDE-ALGINATE INTERACTIONS ........................................................................26

1.4.1 Helical Induction of CAPs in Alginate ..................................................................26

1.4.2 Factors that influence peptide-alginate interactions. .............................................28

1.4.2.1 Peptide Concentration .............................................................................28

1.4.2.2 M- vs. G-blocks of Alginate .....................................................................29

1.4.2.3 O-Acetylation of Alginate ........................................................................30

1.4.2.4 Length of Glycan Chain ...........................................................................31

1.5 OVERALL GOALS OF THE THESIS .............................................................................32

Chapter 2 Antimicrobial Activity of Designed Novel CAPs ....................................................34

2.1 INTRODUCTION .............................................................................................................35

2.2 MATERIAL AND METHODS .........................................................................................36

2.2.1 Peptide Synthesis and Purification.........................................................................36

2.2.2 Circular Dichroism.................................................................................................37

2.2.3 Minimal Inhibitory Concentration (MIC) Assay ...................................................38

2.2.4 Time Course Study of Killing ................................................................................38

2.2.5 Purification of Alginate..........................................................................................39

2.2.6 Minimal Inhibitory Concentration in the Presence of Alginate .............................39

2.2.7 Statistical Analysis .................................................................................................39

2.3 RESULTS AND DISCUSSION ........................................................................................40

2.3.1 Secondary Structure of CAPs ................................................................................40

2.3.2 Antimicrobial Activity of Novel CAPs against Various Bacterial Strains ............42

2.3.3 Time Course of Bacteria Killing ............................................................................44

v

2.3.4 Alginate Reduces the Activity of CAPs.................................................................46

2.4 SUMMARY .......................................................................................................................47

Chapter 3 Peptide-Membrane Interactions...............................................................................48

3.1 INTRODUCTION .............................................................................................................49


3.2.1 Peptide Synthesis ...................................................................................................50


3.2.3 SDS-PAGE ............................................................................................................51

3.2.4 Computational Modeling of CAPs.........................................................................51

3.2.5 Liposome Preparation ............................................................................................51

3.2.6 Atomic Force Microscopy (AFM) .........................................................................52

3.2.7 Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-

FTIR)......................................................................................................................53

3.2.8 Antibacterial Activity.............................................................................................54

3.2.9 Hemolytic Activity.................................................................................................55


3.3.1 Helix Induction of CAPs in SDS Micelles ............................................................56

3.3.2 CAPs Run as Dimers on SDS-PAGE ....................................................................57

3.3.3 CAP Interactions with Model Bacterial Membranes .............................................59

3.3.4 Positive Charges on Both CAP Termini Minimize Aggregation in Bacterial

Membrane-Mimetic Models ..................................................................................62

3.3.5 Antimicrobial Activity ...........................................................................................64

3.3.6 Interaction of Peptides and Mammalian Membrane Lipids ...................................65

3.3.7 Hemolytic Activity.................................................................................................68

3.4 SUMMARY .......................................................................................................................71

Chapter 4 Peptide-Alginate Interactions ...................................................................................72

vi

4.1 INTRODUCTION .............................................................................................................73


4.2.1 Peptide Synthesis ...................................................................................................74

4.2.2 Purification of Alginate..........................................................................................74


4.2.4 Tryptophan Fluorescence .......................................................................................75

4.2.5 Alginate-Peptide Binding Affinity Assay ..............................................................75

4.2.6 Fluorophore Labeling.............................................................................................76

4.2.7 Antimicrobial Activity Assay – Minimal Inhibitory Concentration ......................77

4.2.8 Statistical Analysis .................................................................................................77

4.2.9 Penetration of Peptides into Alginate Beads – Laser Scanning Confocal

Microscopy ............................................................................................................77


4.3.1 Titration of Peptides with Alginate ........................................................................78

4.3.2 Tryptophan Fluorescence Blue-Shifts of CAPs in Alginate ..................................80

4.3.3 Alginate-Binding Affinity Assay ...........................................................................85

4.3.4 Diffusion of Peptides into Alginate Beads.............................................................88

4.4 SUMMARY .......................................................................................................................91

Chapter 5 Conclusions and Implications ...................................................................................92

References .....................................................................................................................................98

Appendix .....................................................................................................................................125

Copyright Acknowledgements ..................................................................................................137

vii

List of Figures

Figure 1-1. Schematic diagram of mushroom-like P. aeruginosa biofilm maturation. .................. 3

Figure 1-2. Formation of a flat P. aeruginosa biofilm. .................................................................. 4

Figure 1-3. Composition and structure of alginate. ........................................................................ 8

Figure 1-4. Mechanisms of biofilm resistance to antimicrobial agents. ....................................... 10

Figure 1-5. Classes of antimicrobial peptides. ............................................................................. 14

Figure 1-6. Mechanisms proposed for cationic antimicrobial peptides (CAP) activity at the site of

the bacterial membrane. ................................................................................................................ 17

Figure 1-7. Schematic representation of natural vs. de novo designed CAPs. ............................ 18

Figure 1-8. Blue shifts (nm) in wavelength maxima emission (Δλmax) of Trp fluorescence upon

exposure of selected peptides to large unilamellar vesicles (LUVs) parepared from bacterial lipid

mixtures (LUV-bact) or mammalian red blood cell mixtures (LUV-RBC (outer)). .................... 24

Figure 1-9. Blue shifts (nm), given as Δλmax = Δλmax(aqueous) – Δλmax(LUV), of selected

CAPs to freshly prepared anionic and zwitterionic large unilamellar vesicles (LUV) ................. 25

Figure 1-10. Helical induction of secondary structures in peptides by alginate studied by CD

spectroscopy. ................................................................................................................................. 27

Figure 1-11. Circular dichroism spectra of the X = Phe peptide at 30 µM (dashed line) or 90 µM

(solid line) in 0.2 mg/mL alginate solution in Tris-HCl buffer at pH 7.0. .................................... 29

Figure 1-12. CD spectra of CAP KK-AAAFAAAAAFAAWAAFAAA-KKKK in alginate and in

oligo-D-mannuronate (AlgM-M) and oligo-L-guluronate (AlgG-G). ............................................... 30

viii

Figure 1-13. % ANS fluorescence emission at increasing concentrations of non-O-acetylated

kelp alginate (- O-acetyl), O-acetylated P. aeruginosa alginate (+ O-acetyl) and the CAP (X =

Phe). .............................................................................................................................................. 31

Figure 1-14. Helical content of CAP KK-AAAFAAAAAFAAWAAFAAA-KKKK at 222 nm of

molar ellipticity as a function of increasing alginate degree of polymerization. .......................... 32

Figure 2-1. Circular dichroism spectra of designed CAPs in aqueous and SDS micelle

environments. ................................................................................................................................ 41

Figure 2-2. Killing potential of designed antimicrobial peptides. ............................................... 43

Figure 2-3. Time course study of antimicrobial activity of peptides against P. aeruginosa (PAO1

strain). ........................................................................................................................................... 45

Figure 2-4. Killing potential of designed antimicrobial peptides in the presence of alginate. ..... 47

Figure 3-1. A photograph of the FTIR set-up. .............................................................................. 54

Figure 3-2. Circular dichroism spectra of CAPs in aqueous solution and SDS micelles. ........... 57

Figure 3-3. (A) SDS -PAGE (silver stain) analysis and (B) representative structural models of

CAP antiparallel dimers. ............................................................................................................... 59

Figure 3-4. AFM topography images of 6k-f17 (a-c) and 6K-F17-4L8,11,13,16 (d-f) at various

concentrations in bacterial membrane lipid mimics. .................................................................... 60

Figure 3-5. Effects of synthetic CAPs on topography images obtained from AFM experiments

performed in tandem with ATR-FTIR measurements in a bacterial model lipid bilayer (3:1

POPE/DOPG). .............................................................................................................................. 62

Figure 3-6. Effects of CAPs on topography images obtained from AFM experiments performed

in tandem with ATR-FTIR measurements in a bacterial model lipid bilayer (3:1 POPE/DOPG).

....................................................................................................................................................... 64

ix


performed in tandem with ATR-FTIR measurements in a mammalian model lipid bilayer (1:1:1

DOPC/DSPC/cholesterol). ............................................................................................................ 67


performed in tandem with ATR-FTIR measurements in a mammalian model lipid bilayer (1:1:1

DOPC/DSPC/cholesterol). ............................................................................................................ 68

Figure 3-9. A typical hemolysis assay. ......................................................................................... 69

Figure 3-10. Hemolytic Activities of the designed CAPs............................................................. 70

Figure 4-1. Schematic illustration of the alginate affinity binding assay. ................................... 76

Figure 4-2. Schematic illustration of the assay to measure the penetration of peptides into

alginate beads. ............................................................................................................................... 78

Figure 4-3. Circular dichroism spectra of the representative peptide 6K-F17-4L8,11,13,16 (20 μM)

titrated with increments in alginate concentration (0 to 0.6 mg/mL). .......................................... 79

Figure 4-4. Normalized Trp fluorescence emission maxima of the peptides (Table 4-1) in

aqueous solution (solid lines) and in alginate (dotted lines). ........................................................ 81

Figure 4-5. The correlation between the alginate-induced blue shift (nm) and the core segment

hydrophobicity of the peptides (Table 4-1). ................................................................................. 84

Figure 4-6. Structural model of the peptide 6K-F17-2L11,13 in a β-strand conformation. ........... 85

Figure 4-7. The BCA analysis of the percentage of peptides bound to alginate separated from the

free peptides 6K-F17-3L11,13,16 (red) and 6K-F17-2L8,16 (black) as a function of alginate

concentration. ................................................................................................................................ 86

Figure 4-8. The distribution of the dissociation constant, Kd, of each of the CAPs (listed in Table

2-1) binding to alginate. ................................................................................................................ 87

Figure 4-9. Schematic illustration of two peptides with high Kd values. ..................................... 87

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Figure 4-10. Helicity detected by CD (A) and the bacterial inhibition curves measured by the

MIC assay (B) of peptide 6k-a17-f9 (blue) and its TAMRA-labelled analog TAMRA-6k-a17-f9

(red). .............................................................................................................................................. 89

Figure 4-11. Confocal laser scanning micrographs obtained of the interactions and extent of

diffusive penetration of TAMRA-labelled CAPs into alginate beads. ......................................... 90

Figure 5-1. Proposed mechanisms of action of CAPs in bacterial membranes vs. mammalian

membranes. ................................................................................................................................... 96

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List of Tables

Table 1-1. Core segment hydrophobicity values and antimicrobial activities (MICs) of designed

25-residue KKAAAXAAAAAXAAWAAXAAAKKKK-NH2 peptides. .................................... 20

Table 1-2. Sequences, core segment hydrophobicity values and antimicrobial activities of

designed 17-residue CAPs. ........................................................................................................... 21

Table 2-1. Sequences and hydrophobicity values of the non-amphipathic core segments for

peptides used in this study. ........................................................................................................... 37

Table 2-2. Antimicrobial activities of CAPs tested against various bacterial strains. .................. 44

Table 3-1. Sequences, molecular weights (MW), and hydrophobicity values of CAPs used in this

study. ............................................................................................................................................. 50

Table 3-2. Antimicrobial activities of designed peptides. ............................................................ 65

Table 4-1. Core segment hydrophobicity of the peptides and alginate-induced blue-shifts in

tryptophan fluorescence emission maxima (Δλ, nm). ................................................................... 82

xii

List of Appendices

Figure A 1. A representative HPLC spectrum of the peptide 6K-F17. ....................................... 125

Table A 1. Expected molecular weights (MWs) and mass spectrometry (MS) analysis of

synthesized peptides.................................................................................................................... 126

xiii

List of Abbreviations

AFM Atomic force microscopy

Ala Alanine (A)

ANOVA Analysis of variation

ANS 8-Anilino-1-naphthalene sulfonic acid

ATR Attenuated total reflection

BCA Bicinchroninic acid

BSA Bovine serum albumin

CAMHB Cation-adjusted Mueller Hinton broth

CAP Cationic antimicrobial peptide

CD Circular dichroism

CF Cystic fibrosis

CFU Colony forming unit

Da Dalton

DDW Double-distilled water

DIEA N,N-diisopropylethylamine

DMF N,N-dimethylformamide

DOPC 1,2-Dioleoyl-sn-glycero-3-phosphocholine

DOPG 1,2-Dioleoyl-sn-glycero-3-phospho-(1'-rac-glycerol)

DSPC 1,2-Distearoyl-sn-glycero-3-phosphocholine

E. coli Escherichia coli

EDTA Ethylenediamine tetraacetic acid

EPS Extracellular polymeric substance

xiv

ESI Electron spray ionization

Fmoc Fluorenylmethoxyl carbonyl

FSD Fourier self deconvolution

FTIR Fourier transform infrared spectroscopy

FWHH Full width at half height

G α-(1-4)-L-guluronate

Glu Glutamate (E)

HATU 2-(7-azabenzotriazol-1-yl)-1,1,3,3-tetramethyluronium

hexafluorophosphate

HEPES 4-(2-Hydroxyethyl)-1-piperazineethanesulfonic acid

HPLC High performance liquid chromatography

IRE Internal reflectance element

Kd Dissociation constant

Leu Leucine (L)

LSM Laser scanning microscopy

LUV Large unilamellar vesicle

Lys Lysine (K)

M β-(1-4)-D-mannuronate

MALDI Matrix-assisted laser desorption/ionization

MES 2-(N-morpholino) ethanesulfonic acid

MHB Mueller Hinton broth

MIC Minimal inhibitory concentration

MS Mass spectroscopy

MW Molecular weight

MWCO Molecular weight cut-off

xv

OD Optical density

P. aeruginosa Pseudomonas aeruginosa

PAGE Polyacrylamide gel electrophoresis

PAL-PEG-PS [5-(4-Fmoc-aminomethyl-3,5-dimethoxyphenoxy) valeric acid]-

polyethylene glycol-polystyrene

PBS Phosphate buffered saline

PC Phosphatidylcholine

PE Phosphatidylethanolamine

PG Phosphatidylglycerol

Phe Phenolalanine (F)

POPC 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphocholine

POPE 1-Palmitoyl-2-oleoyl-sn-glycero-3-phosphoethanolamine

POPG 1-Palmitoyl-2-oleoyl-sn-glycero-3-[phosphor-rac-(1-glycerol)]

RBCs Red blood cells

SDS Sodium dodecyl sulfate

Ser Serine (S)

TAMRA 5-(and-6-)-carboxytetramethylrhodamine

TFA TrifluTriisopropylsilane

Trp Tryptophan (W)

1

Chapter 1 Introduction

1

2

1.1 BIOFILMS

The evolution of microbes in both nature and diseases is becoming one of the most important

topics in biomedical research. It is known that the majority of bacteria exist in matrix-enclosed

biofilms adherent to surfaces (Costerton et al. 1978). In nature, since the first discovery of

biofilm formation in billions-year-old fossils (Rasmussen 2000), biofilms have been found in

hydrothermal environments such as hot springs (Reysenbach et al. 2001), deep-sea vents (Taylor

et al. 1999), and freshwater rivers (Hall-Stoodley et al. 2004). Biofilms confer a degree of

stability to the structure of bacterial microcolonies, and provide protection to the cells from a

wide range of environmental challenges, including UV exposure (Espeland et al. 2001), acid

stresses (McNeill et al. 2003), metal toxicity (Teitzel et al. 2003), dehydration and salinity (Le

Magrex-Debar et al. 2000), macrophage killing (Leid et al. 2005), and many antimicrobial

agents (Mah et al. 2001; Davies 2003). Due to this survival strategy for bacteria, persistent

biofilm microbial infections have been an increasing challenge in health-related problems

(Chopp et al. 2003; Marsh 2006).

1.1.1 Formation of biofilms

Bacterial biofilms are initiated when free-swimming (planktonic) bacteria attach irreversibly to a

surface by overproducing extracellular polymeric substances (EPSs) (Stoodley et al. 2002b).

There are generally five stages involved in the typical Pseudomonas aeruginosa biofilm

formation (Fig. 1-1). Initially, bacteria cells loosely and reversibly associate with the surface,

followed by robust attachment. After the initial adhesion, these bacteria begin to aggregate into

microcolonies, in which genes involved in the production of EPS are up-regulated (Davies et al.

1995; Gacesa 1998). The secretion of large amounts of EPS provides mechanical strength for

the cells to subsequently grow and mature into a three-dimensional biofilm matrix (Stoodley et

al. 1999; Stoodley et al. 2001; Stoodley et al. 2002b). The shape of the biofilm structure highly

depends on the nutrient source. A mushroom-shaped P. aeruginosa biofilm (Fig. 1-1) forms

3

when the cells subsequently rearrange into microcolonies through type IV pili twitching motility

on surfaces via extension and retraction (Semmler et al. 1999; Skerker et al. 2001). Flagellum-

motility also promotes the initial cell-to-surface interactions in P. aeruginosa PA14 strain

(O'Toole et al. 1998). However, Klausen et al. [2003] proposed that under different nutritional

and environmental conditions (i.e. flow chamber irrigated with citrate minimal media), flagella

and type IV pili play no role in attachment or biofilm development; rather, initial microcolony

formation occurs by clonal growth, followed by twitching motility-mediated spreading over the

substratum, and eventually results in a dynamic flat mature biofilm (Fig. 1-2) (Klausen et al.

2003). The mature biofilm may contain physiological heterogeneity, such as metabolic and

oxygen gradients (Xu et al. 1998), that causes microbial colonies to alter their physiological

processes in response to the local conditions (Stoodley et al. 2002a). At the final stage of a

biofilm cycle, bacteria get dispersed from the biofilms to the surroundings due to perturbation or

other unfavourable environmental cues (Adams et al. 2002). The free bacteria revert to their

planktonic form, and then start a biofilm cycle at other locations (Sauer et al. 2002).

Figure 1-1. Schematic diagram of mushroom-like P. aeruginosa biofilm maturation. Biofilm development involves five stages: (1) initial reversible attachment of bacteria (red rods)

to a surface; (2) permanent colonization by the secretion of exopolysaccharides; (3) development

of the three-dimensional biofilm matrix; (4) maturation; and (5) dispersal of non-mucoid cells

from the biofilm – which can eventually develop into further colonies. The formation of

biofilms emphasizes that antibiotics targeted to bacteria in biofilms must penetrate the

exopolysaccharide layer in order to reach – and act upon – the bacterial membrane. Adapted

from (Stoodley et al. 2002b).

4

Figure 1-2. Formation of a flat P. aeruginosa biofilm. (A) Bacterial attachment occurs

independently of flagella and type IV pili; (B) microcolonization occurs by clonal growth; (C)

bacteria spread on the surface, mediated by twitching motility; and (D) the mature flat biofilm

forms. Adapted from (Klausen et al. 2003).

1.1.2 Environmental and medical problems caused by biofilms

Biofilms can be present everywhere in nature, including hydrothermal hot springs, freshwater

rivers, water pipes, shower heads, drinking water filters, heating devices and building walls,

variously causing contamination of agricultural crops, blockage of pipelines, and corrosion of

ship hulls and heating systems (Flemming 2002; Kilb et al. 2003; Hall-Stoodley et al. 2004). In

clinical settings, the formation of biofilms on biomaterial surfaces is the main determinant in

many diseases, including infective endocarditis (Mohamed et al. 2004), and various dental and

medical device-related infections (Hall-Stoodley et al. 2009), such as those related to the use of

central venous catheters (Passerini et al. 1992), urinary catheters (Morris et al. 1999), prosthetic

heart valves (Hyde et al. 1998), and orthopaedic devices (Gristina et al. 1994). Pneumonia,

5

periodontitis and chronic lung infection in cystic fibrosis patients are also diseases associated

with biofilms (Lyczak et al. 2002; Ricucci et al. 2010; Lee et al. 2011; Wilson et al. 2012).

Biofilms of polymicrobial communities also occur on the mucosal surface of human adenoids in

patients with chronic and/or otitis media (Kania et al. 2008).

1.1.3 Pseudomonas aeruginosa

Among the organisms used to study biofilm formation, Pseudomonas aeruginosa is a ubiquitous

bacterium and a common Gram-negative nosocomial opportunistic pathogen. In addition to

causing acute pneumonia in emphysema patients and bacteremia in burn and cancer patients, this

bacterium is also the primary cause of lung disease and mortality in cystic fibrosis (CF) patients

(Govan et al. 1996; Jones et al. 2001; Merlo et al. 2007). Non-mucoid P. aeruginosa strains

initially colonize on the CF airway surface, but then convert to the mucoid alginate-producing

form, which leads to biofilm formation and the resulting increased resistance to antibiotic attack.

Mucoid conversion is caused by mutations in the gene encoding the σ-factor AlgU negative

regulator (MucA) (Martin et al. 1993). The mucoid derivative strain PDO300, which is

constructed from the P. aeruginosa wild-type strain PAO1 by deregulation of the mucA σ-22

activity, causes 300x alginate hyperproduction (Malhotra et al. 2000).

P. aeruginosa has developed a highly intrinsic resistance to a variety of antibacterial agents due

to the relatively low permeability of its outer membrane to antibiotics, the formation of biofilms,

the presence of β-lactamases, and its multi-drug efflux system (Hancock 1997; Li et al. 2000;

Mah et al. 2003). The up-regulation of multidrug efflux systems, such as MexAB-OprM,

MexEF-OprN and MexXY-OprM, has been shown to confer resistance to fluoroquinolones,

aminoglycosides, and some β-lactams (Masuda et al. 2000; Poole 2001; Fraud et al. 2011;

Llanes et al. 2011).

6

1.1.4 Biofilm exopolysaccharides

Production of exopolysaccharides is a feature shared by most bacterial species in biofilm

formation that mainly provides mechanical stability to the matrix (Sutherland 2001; Whitchurch

et al. 2002; Ma et al. 2009). Bacterial exopolysaccharides are long chains of sugars that are

exported from the cell and which remain either tightly (capsules) or loosely (slime) associated

with the cell surface. Exopolysaccharide typically constitutes >90% of the mass of the biofilm

matrix and it is this polysaccharide ‘coating’ that is proposed to shield the bacteria from

conventional antibiotics (Vu et al. 2009). Once established, biofilms are extremely difficult to

eliminate, as the bacteria are protected from the natural defense mechanisms of the host

organism and at this stage have become tolerant of antibiotics and disinfectants – likely because

the exopolysaccharide ‘layer’ reduces susceptibility to external agents by acting as a diffusion

barrier (Mah et al. 2001).

Biofilm exopolysccharides can be homopolysaccharides, such as the sucrose-derived glucans and

fructans produced by the streptococci in oral biofilms, and cellulose formed by

Gluconacetobacter xylinus, Agrobacterium tumefaciens, Rhizobium spp., Enterobacteriaceae

and Pseudomonadaceae families (Wingender et al. 2001; Zogaj et al. 2001). Yet most

exopolysaccharides are heteropolysaccharides that consist of a mixture of charged and neutral

sugar residues. Many known exopolysaccharides containing uronic acids, including alginate

(Davies et al. 1995), xanthan (Jansson et al. 1975) and colonic acid (Prigent-Combaret et al.

1999), are polyanionic. An example of polycationic exopolysaccharides is intercellular adhesion

– composed of β-(1,6)-linked N-acetylglucosamine with partly deacetylated residues – which is

produced by biofilm-forming Staphylococcus epidermidis and Staphylococcus aureus (Heilmann

et al. 1996; Cramton et al. 1999). Acetyl groups are common substituents of

exopolysaccharides, and they increase the adhesive and cohesive properties of EPS and alter

biofilm architecture (Tielen et al. 2005).

7

P. aeruginosa, a well studied biofilm-forming bacterial model, produces at least three distinct

exopolysaccharides that contribute to biofilm development and architecture. One of the most

extensively characterized exopolysaccharides from P. aeruginosa mucoid strains is alginate,

which results in a highly viscous appearance of the bacterial colonies on agar (Ramsey et al.

2005). Although alginate is not essential for biofilm formation in non-mucoid P. aeruginosa

strains such as PAO1 and PA14 (Wozniak et al. 2003), it has notable effects on mucoid biofilm

architecture when it is present (Ryder et al. 2007). The other two biofilm exopolysaccharides,

Pel and Psl, contribute to biofilm establishment in both mucoid and non-mucoid strains of P.

aeruginosa (Colvin et al. 2011; Ma et al. 2012). Pel, a glucose-rich polysaccharide, is essential

for the formation of pellicles at the air-liquid interface of biofilms (Friedman et al. 2004). Psl,

which consists of a repeating pentasaccharide containing D-mannose, D-glucose and L-

rhamnose, is involved in the adherence to abiotic and biotic surfaces and in the maintenance of

biofilm architecture (Byrd et al. 2009).

1.1.5 Alginate

Alginate is an anionic heteropolymer of β-(1-4) linked D-mannuronate (M) and α-(1-4) linked L-

guluronate (G) monosaccharides (Fig. 1-3); these sugars are carboxylate-containing forms of the

corresponding common hexoses: mannose and gulose. Alginate biosynthesis genes are clustered

in a 12-gene operon to regulate and stabilize the alginate machinery in a mucoid strain (Stover et

al. 2000; Hay et al. 2012). Individual M residues within the polymer can be either epimerized to

G by the polymer-level epimerase AlgG (Chitnis et al. 1990; Franklin et al. 1994) or acetylated

at the second and third position of hydroxyl groups (Franklin et al. 1993; Franklin et al. 1996).

Acetylation protects the bacteria from host defense mechanisms by preventing activation of the

alternative complement pathway, while epimerization protects against the action of endogenous

lyase (Gimmestad et al. 2003; Jain et al. 2003). The modification of alginate with acetyl groups

strongly influences the aggregation of bacteria into microcolonies and determines the

architecture of mature biofilms (Franklin et al. 1993; Tielen et al. 2005). The molecular weights

of alginate range between 50 – 100,000 kDa depending on the preparation methods (Augst et al.

8

2006). Sequences of poly-β-(1-4)-D-mannuronate (M-block), poly-α-(1-4)-L-guluronate (G-

block), and alternating sequences of D-mannuronate and L-guluronate are determined by the

mode of their glycosidic linkages, and the relative amount of each block depends on the origin of

the alginate (Smidsrod et al. 1990); for example, P. aeruginosa alginate only consists of M-

blocks and MG-blocks (Gacesa 1998).

Figure 1-3. Composition and structure of alginate. (A) The monomers of alginate, D-

mannuronate (M) and its C-5 epimer L-guluronate (G), linked with a β 1-4 glycosidic linkage.

O-acetyl groups (Ac) are attached to the O2’ and/or O3’ hydroxyls of M residues. (B) In P.

aeruginosa alginate, monomers combine to form a polymer composed of M blocks and M-G

blocks. Pseudomonas alginates are devoid of the G-blocks found in other organisms. Glycosidic

bonds between M residues result in ribbon-like structures. G residues introduce a bend in the

linear chain, which modulates its physical properties. Anionic carboxylic acid substituents on

each M and G monomer are the primary electrostatic binding sites when cationic antibiotics

interact with alginate. Adapted from (Franklin et al. 2011). (C) Space-filling models of M- and

G-chains. G-block rings (left) adopt a stacked conformation; M-block rings (right) adopt a

‘ribbon’ conformation. Adapted from (Kuo et al. 2007).

Alginate has the ability to form hydrogels in the presence of divalent cations such as calcium – a

property that has been exploited in a wealth of applications ranging from the preparation of

9

biocompatible microcapsules to tissue engineering (Lim et al. 1980; Donati et al. 2005;

Stojkovska et al. 2010). Calcium ions can create a bridge between polyanionic alginate

molecules, stimulating the development of thick and compact biofilms with increased

mechanical stability (Korstgens et al. 2001).

1.1.6 Mechanisms of biofilm resistance to antimicrobial agents

Biofilms are commonly viewed as being resistant to killing by a broad range of antimicrobial

agents. Biofilm-formed bacteria can become 10 to 1,000 times more resistant to conventional

antibiotics than their planktonic counterparts (Hoyle et al. 1991). Depending on the type of

antibiotics, biofilm resistance can be due to the failure of the antimicrobial agent to penetrate the

biofilm matrix, an altered physiological state of the biofilm microbes, and/or the emergence of

slow growing, antibiotic-resistant persister cells within the biofilm (Fig. 1-4) (Lewis 2001;

Stewart et al. 2001; Stewart 2002; del Pozo et al. 2007).

The slime matrix of biofilm acts as a physical barrier, which limits the penetration of reactive,

charged, or large antibiotics, such as superoxides, metals, aminoglycosides, β-lactams and

immunoglobulins (Anderl et al. 2000; Al-Fattani et al. 2004; Hall-Stoodley et al. 2004; Singh et

al. 2010), and consequently reduces the drugs to sublethal concentrations before they reach the

bacterial cells. At the same time, slow rate of penetration also extends the time for bacterial

enzymes (i.e. β-lactamase) to inactivate or modify the antibiotics (Dibdin et al. 1996).

The increased bacterial density within biofilm microcolonies results in waste accumulation and

an altered microenvironment, including pH, oxygen, carbon dioxide, osmolarity, temperature,

and low divalent cation and pyrimidine concentration (del Pozo et al. 2007), which leads to an

adaptive physiological state of biofilm organisms. For example, even though ciprofloxacin is

able to penetrate the P. aeruginosa biofilm matrix, its activity is limited due to low oxygen

10

environment and low bacteria metabolic activity within the biofilms (Walters et al. 2003). The

absence of oxygen also reduces the antimicrobial activity of aminoglycosides (Tack et al. 1985).

Environmental conditions may induce the up-regulation of stress-response genes in bactiera,

such as the overexpression of β-lactamases and multidrug resistance efflux pumps (Brooun et al.

2000; Bagge et al. 2004). The gene expressed in biofilm P. aeruginosa, ndvB, is responsible for

the synthesis of periplasmic glucans, which in turn interact with tobramycin to prevent it from

reaching the site of action (Mah et al. 2003).

The fact that bacteria can develop reduced susceptibility even in very thin biofilms can be due to

the existence of ‘persisters’. Persisters are subpopulations of cells with highly resistant

phenotypes, and may be present in much higher numbers in biofilm than planktonic communities

(Spoering et al. 2001; Stewart 2002; Suci et al. 2003). These cells can be slow growing or non-

growing (at stationary-phase); therefore they respond to antimicrobial agents in a different way

(Eng et al. 1991). Once a small fraction of persister cells survive the assault and reconstitute the

biofilm, the specific antimicrobial treatment is no longer effective.

Figure 1-4. Mechanisms of biofilm resistance to antimicrobial agents. (1) Failure of

antimicrobial agents to penetrate the biofilm matrix; (2) Up-regulation of antibiotic chelator

enzymes due to the stress response in the altered microenvironment; and (3) existence of

antibiotic-resistant persister cells within the biofilm (i.e. non-growing cells).

11

1.1.7 Conventional antibiotics and current treatments for P. aeruginosa infections

The opportunistic bacterial pathogen Pseudomonas aeruginosa is the most prevalent pathogen

and leads to most of the morbidity and mortality in CF patients (Govan et al. 1996). A number

of therapeutic strategies have been developed to combat P. aeruginosa infections, including

antibiotic therapy, protease-inhibitors, anti-inflammatory agents, and vaccines developed against

P. aeruginosa attachment to biofilm formation (Cryz et al. 1991; Cryz et al. 1994; Kobayashi et

al. 2009). Among these, appropriate antibiotic treatment is the major therapeutic option in

managing CF lung diseases (Gibson et al. 2003).

β-lactam based drugs, including carbenicillin, ampicillin, penicillin, and ceftazidime, inhibit

bacterial cell wall biosynthesis (Waxman et al. 1983). However, P. aeruginosa strains possess a

chromosomal AmpC β-lactamase that can be derepressed by mutation, which protects the

bacteria from β-lactams (Livermore et al. 1997; Masuda et al. 1999). Additionally, biofilm cells

that are primarily slow growing are resistant to killing by many β-lactam antibiotics, such as

carbenicillin (Spoering et al. 2001).

Aminoglycosides, such as tobramycin, gentamycin, and kanamycin, have a high therapeutic

index against Gram-negative bacteria (Burns et al. 1999; Ramsey et al. 1999). They function by

binding irreversibly to a site on the bacterial 30S ribosome subunits, preventing formation of the

70S complex, inhibiting bacterial protein synthesis, and consequently leading to altered cell

membrane permeability and eventual cell death (Davis 1987). However, the primary mechanism

of P. aeruginosa resistance to aminoglycosides is caused by the overexpression of the MexXY

efflux system (Westbrock-Wadman et al. 1999; MacLeod et al. 2000). Aminoglycosides also

tend to bind to the biofilm exopolysaccharide, and become difficult to kill biofilm-state bacteria

(Hentzer et al. 2001; Sadovskaya et al. 2010). Combinational therapy involving tobramycin in

12

conjunction with other antibiotics such as meropenem has been reported to have an improved

efficacy (Dales et al. 2009).

Fluoroquinolones can readily penetrate biofilms of P. aeruginosa and kill non-growing bacteria

(Vrany et al. 1997). Ciprofloxacin, the most commonly used quinolone in antipseudomonal

treatment, inhibits bacterial DNA gyrase, which in turn stops synthesis of DNA and of proteins

(Campoli-Richards et al. 1988). However, prolonged treatment with ciprofloxacin imposes

bacterial resistance due to mutations of the quinolone target protein, GyrA subunit of DNA

gyrase (Hancock et al. 2000).

Macrolides have excellent biofilm penetration and intracellular accumulation in P. aeruginosa

(Tateda et al. 1996). Macrolides with 14- or 15-membered rings, such as erythromycin,

azithromycin and clarithromycin, are especially effective antibiotics for patients with P.

aeruginosa infections (Kobayashi et al. 2009). They inhibit activity in the final stage of the

alginate synthesis pathway, resulting in the inhibition of alginate production (Nagino et al. 1997;

Mitsuya et al. 2000), and inhibit the autoinducers that increase the expression of las I and rhlI in

P. aeruginosa, that are responsible for the development of the mushroom-like biofilm structure

(Tateda et al. 2001).

Furanone compounds contribute to the prevention of long-term colonization with P. aeruginosa.

P. aeruginosa in CF sputum have been shown to generate quorum-sensing signals to coordinate

biofilm formation (Davies et al. 1998; Singh et al. 2000). Furanones penetrate the P. aeruginosa

biofilm matrix, specifically block quorum-sensing signalling gene expression, and consequently

render bacteria less virulent and more sensitive to biocide treatment; nevertheless, they have no

effect on bacterial attachment to solid surfaces, bacterial protein synthesis, or bacterial growth

(Givskov et al. 1996; Hentzer et al. 2002; Hentzer et al. 2003).

13

1.2 ANTIMICROBIAL PEPTIDES

Conventional small molecule antibiotics target a wide range of microbial biochemical functions

including translation, and cell wall construction (Franklin et al. 1998), and often they require at

least some degree of cellular activity to be effective. Bacterial resistance to these antibiotics is

on the rise as the bacteria can evolve the enzymes and components involved in their life cycle.

As a consequence, novel approaches to the treatment of microbial infections are urgent.

1.2.1 Natural Antimicrobial Peptides

Antimicrobial peptides, which occur naturally as important innate immunity agents in a wide

spectrum of living organisms ranging from plants to insects to mammals including humans

(Zasloff 2002; Wang et al. 2004), have become increasingly recognized in current research as

templates for prospective antibiotic agents. Databases currently report more than 1000 natural

antimicrobial peptides that are mature and active (Wang et al. 2009). Several classes of natural

antimicrobial peptides have emerged (Fig. 1-5), including (1) amphipathic linear peptides free of

cysteines (i.e., human cathelicidin LL-37); (2) peptides with disulfide bonds that can produce a

flat dimeric β-sheet structure (i.e., HBD-2); (3) loop peptides with one disulfide bridge (i.e.,

thanatin); and (4) peptides with a high frequency of amino acids such as Gly, Pro, Trp, Arg

and/or His (i.e., indolicidin) (Mandard et al. 1998; Rozek et al. 2000; Sawai et al. 2001; Hancock

et al. 2006; Wang 2008). Many of the antimicrobial peptides are highly positively-charged,

ranging from +2 to +9 (Hancock et al. 1998), and hence known as cationic antimicrobial

peptides (CAPs).

14

Figure 1-5. Classes of antimicrobial peptides. (A) amphipathic linear peptides free of Cys

(human LL-37); (B) β-sheet structured peptides with disulfide bonds (human β-defensin 2); (C)

loop peptides with one disulfide bridge (thanatin); and (D) peptides rich in Gly, Pro, Trp, Arg

and/or His (indolicidin).

While they differ widely in sequence and structure, natural CAPs generally consist of 12-50

residues, approximately 50% of which are hydrophobic (Hancock 2001), and exist

predominantly as monomers with random coil structures in solution (Oren et al. 1998) but have

the potential to form an amphipathic α-helical structure when bound to membranes .

Antimicrobial peptides provide a viable alternative to small molecular antibiotics, as (1) CAPs

consist of naturally-occurring amino acids; (2) they are highly selective against the negatively

charged bacteria membrane vs. the zwitterionic mammalian membranes of a human host; and (3)

there is no specificity in targeting, so that bacteria have little recourse against CAP membrane

disruptive properties, and therefore CAPs are unlikely to evoke bacterial resistance (Hancock

2001). CAPs are active in the nanomolar to micromolar concentration range and show little L-

vs. D-residue specificity, although their D-enantiomers often exhibit better activity than their L-

15

counterparts due to the lack of proteolysis, reinforcing the fact that they interact with achiral

components of the cell membrane (Bessalle et al. 1990; Lee et al. 1994).

More recent studies have shown that some natural CAPs are effective against biofilms; for

example, the human cathelicidin LL-37 at low concentrations inhibited the formation of bacterial

biofilms in vitro (Overhage et al. 2008); indolicidin and Bac7(1-35) significantly reduced

biofilm formation by Stenotrophomonas maltophilia and P. aeruginosa strains (Pompilio et al.

2011); and pleurocidin showed a favourable killing effect against BioFlux flow biofilms (Tao et

al. 2011). However, many natural cationic peptides do display some host toxicity, as measured

by their tendency to induce lysis of erythrocytes (red blood cells) at higher concentrations, such

as gramicidin S (50% hemolysis at 12 μM) (Wadhwani et al. 2006), pardaxin (50% at 40 μg/mL)

(Hsu et al. 2011), mellitins (100% at only 7 μM) (Pandey et al. 2010), protegrin I (50% at 25

μg/mL) (Jacobsen et al. 2007), and several cathelicidins (Travis et al. 2000; Xiao et al. 2006).

Some antimicrobial peptides that are relatively non-toxic are mammalian defensins (Johnstone et

al. 2000); dermaseptins (Oren et al. 1996); spinegirin (no hemolysis at 100 μM) (Lee et al.

2003); and magainin (hemolysis only at the relatively high concentration of 100 μg/mL) (Porter

et al. 2002).

1.2.2 Mechanisms of Action

Understanding the mechanism of membrane disruption by a variety of peptides in many different

types of membranes is necessary to elucidate the various factors determining the activity of a

peptide and to subsequently design therapeutic peptides with the desired potency and selectivity

(Shai 2002; Yeaman et al. 2003; Sato et al. 2006). In prevailing views of CAP mechanisms,

peptides interact with the membrane, inducing relocation of the peptide into a position parallel to

the membrane at the interface of the hydrophilic head groups and hydrophobic fatty acid chains

of the membrane phospholipids. During this step, which reduces the dielectric constant of the

peptide’s surrounding media, the peptide folds into a membrane-bound structure. Following this

16

parallel membrane orientation, outcomes have been proposed on the basis of model membrane

studies, which include the “barrel-stave” mechanism, the “carpet-like” mechanism, and the

“toroidal pore” mechanism. In the barrel-stave model (Fig. 1-6A), peptide reorientation occurs

to a position perpendicular to the cytoplasmic membrane to form channels with regular structure

(“barrel-stave”; typified by alamethicin (He et al. 1996)). Peptides bound in this manner to the

bacterial membrane recognize each other and oligomerize, and the resulting oligomer inserts into

the hydrophobic core of the membrane, forming a transmembrane pore. In the “carpet”

mechanism (Fig. 1-6B), peptide-mediated packing defects are introduced into the membrane

phospholipids by very dense aggregation of parallel-oriented peptides, wherein membrane

permeation is eventually induced at sites where local peptide concentration ultimately exceeds

threshold values (i.e. cecropin P1 (Gazit et al. 1995)). In the “toroidal pore” model (Fig. 1-6C),

the peptides similarly bind and interact with lipid head groups, imposing a positive curvature

strain on membranes while the CAPs reorient to form micelle-like aggregates that induce

informal channels for the movement of ions across the membrane (i.e. magainin (Matsuzaki et

al. 1995) and melittin (Yang et al. 2001)). Some authors combine the “carpet” and the “toroidal

pore” mechanisms as one – “carpet” – characterized in general by three main steps: (a)

interfacial partitioning with accumulation of monomers on the target membrane (rate-limiting

step); (b) peptide structural changes (conformation, aggregation, and orientation) induced by

interactions with the lipid bilayer (as already shown with liposomes and erythrocytes); (c)

plasma membrane permeabilization maintained above a critical threshold. However, unlike the

“carpet” mechanism, CAPs following the “toroidal pore” model are usually too small (~16Å)

(Toniolo et al. 1994) to span an unperturbed phospholipid bilayer (32-38 Å) (Zhang et al. 1995)

in its α-helical conformation.

17

Figure 1-6. Mechanisms proposed for cationic antimicrobial peptides (CAP) activity at the

site of the bacterial membrane. (A) Barrel-stave mechanism, in which CAP α-helices bind and

assemble in a transmembrane manner perpendicularly to form channels. (B) Carpet mechanism,

where CAPs bind, accumulate and penetrate the bacterial membrane, eventually causing

membrane lysis. (C) Toroidal pore mechanism, where CAPs bind and induce the localized

formation of micelle-like toroidal pores. Adapted and modified from (Sato et al. 2006).

1.2.3 De novo Design of Novel CAPs

Several series’ of hydrophobic peptides were originally designed in our lab as model

transmembrane segments, such as a series of 25-residue membrane-active peptides of prototypic

sequence KKAAAXAAAAAXAAWAAXAAAKKKK-NH2, where X is each of the 20

commonly-occurring amino acids, as produced by solid phase peptide synthesis (Liu et al.

1998b). The specific rationales of the design (Fig. 1-7) are as follows:

18

1. Lys tags are included at the N and/or C termini to enhance peptide solubility in aqueous

media (Liu et al. 1998b; Melnyk et al. 2001), rendering them much easier than purely

hydrophobic peptides to isolate, purify, and characterize.

2. The hydrophobic segment includes 19 amino acids that sufficiently spans the lipid

bilayer when folded into an α-helical conformation.

3. Three X guest residues are distributed along the helix such that the symmetry is

preserved and amphipathicity reduced

4. Ala was chosen as the background residue due to its midrange hydrophobicity and

frequent occurrence in membrane domains.

5. A Trp residue was included in the hydrophobic core as an environment sensitive

fluorescent probe.

Figure 1-7. Schematic representation of natural vs. de novo designed CAPs. (A) Natural

CAP: The amphipathic peptide magainin of the sequence GIGKFLHAAKKFAKAFVAEIMNS-

NH2 in an α-helical conformation. The positively-charged residues (blue) are located at one face

of helix whereas the hydrophobic residues (green) are at the other face. (B) Designed CAP: A

CAP originally designed in our lab with core hydrophobic sequence KK-

AAAXAAAAAXAAWAAXAAA-KKKK-NH2, where X = a given amino acid (i.e. X = Val, as

indicated in orange), in an α-helical conformation; and (C) the corresponding helical wheel

representation of the peptide in (B), in which the three X residues are symmetrically distributed

on each helical face. Solid (green) spheres represent methyl groups of Ala residues. Lys

residues at both N- and C-termini are represented by blue ‘tails’. The Trp indole ring,

incorporated for fluorescence measurements, is shown in outline form. Adapted from (Liu et al.

1998a).

19

Although these peptides are all water-soluble, when the average hydrophobicity of a given

peptide core segment is above an experimentally determined ‘threshold’ value, we observed that

it spontaneously inserts into lipid micelles with accompanying formation of α-helical structures

(Liu et al. 1998a; Deber et al. 2001). While these peptides had originally been designed as

model transmembrane segments to systematize the contributions of hydrophobicity and helicity

to peptide membrane interactions (Liu et al. 1998a), we noticed that their sequences and positive

charges broadly resembled a variety of naturally-occurring CAPs. However, unlike the

amphipathic natural CAPs (i.e. magainin) that have positively charged and hydrophobic groups

segregated onto opposite faces of a helix (Fig. 1-7A), the key features of the designed peptides

are the consecutive non-amphipathic hydrophobic core of 19 residues, and the multi-positively

charged Lys/Arg in either segregated (all basic residues at the N- or C-terminus), or separated

forms (basic residues at both termini) (Fig. 1-7B,C).

The need for development of new ways to combat bacterial infection led us initially to examine

the antimicrobial potency of the 25-mer series of designed peptides. We found that peptides in

this series with core hydrophobic sequences above the ‘threshold’ (such as when X = Phe in

Table 1-1) display antimicrobial activity at µM concentrations (Table 1-1) against both free-

swimming Gram-positive and Gram-negative bacteria and yeast, and are non-hemolytic to

mammalian cells even at relatively high doses (325 µM = 650 µg/ml) (Stark et al. 2002; Burrows

et al. 2006). In contrast, peptides of average core segment hydrophobicity below the threshold

(such as when X = Ser in Table 1-1) are biologically inactive, indicating that membrane insertion

is the operative killing factor.

20

Table 1-1. Core segment hydrophobicity values and antimicrobial activities (MICs) of

designed 25-residue KKAAAXAAAAAXAAWAAXAAAKKKK-NH2 peptides.

Peptide X-Residuea Core Segment Hydrophobicity

b

MICc (μM)

Gram-negative Gram-positive

E.coli DC2 C. xerosis C875

F 1.12 4 <0.25

W 1.11 8 <0.25

L 1.09 16 <0.25

I 1.05 16 <0.25

M 0.86 32 0.5

V 0.83 >32 0.5

C 0.75 8 1

Y 0.68 16 <0.25

A 0.42 >64 2

T 0.21 n/d n/d

E 0.15 n/d n/d

D 0.01 n/d n/d

Q -0.03 n/d n/d

R -0.04 32 8

S -0.05 >64 >64

G -0.12 n/d n/d

N -0.19 n/d n/d

H -0.32 64 32

P -0.36 n/d n/d

K -0.37 64 16

a Peptides have the sequence KKAAAXAAAAAXAAWAAXAAAKKKK-NH2, where X is

each of the 20 commonly occurring amino acids.

b Average hydrophobicity of the core 19-residue segment based on X-residue relative

hydrophobicity values on the Liu-Deber hydrophobicity scale (Liu et al. 1996). Peptides with

average core hydrophobicity above 0.42 (X = Ala) are above the ‘hydrophobicity threshold’ for

membrane insertion (Deber et al. 2001).

c Minimal inhibitory concentration (MIC) values are representative of results from three or more

separate experiments. Values reported in (Stark et al. 2002).

n/d = not determined.

21

Once alerted to the antimicrobial activity of these peptides, we sought to minimize the length of

the peptides, and subsequently designed a second category of CAPs that has the 17-residue

prototypic sequence KKKKKKAAXAAWAAXAA-NH2 (X = any of the 20 commonly

occurring amino acids), wherein the Lys charges are grouped at the N-terminus, and the

hydrophobic core has been reduced to 11 residues. Several of the 17-mers displayed

significantly increased antimicrobial activity (Table 1-2) compared to the original 25-mers

(Table 1-1) (Stark et al. 2002; Glukhov et al. 2008).

Table 1-2. Sequences, core segment hydrophobicity values and antimicrobial activities of

designed 17-residue CAPs.

Peptide Sequence Core Segment

Hydrophobicitya

MICb (μM)

P. aeruginosa

PAO1

6k-f17 kkkkkk-aafaawaafaa-NH2 1.48 2

6K-F17-1L11 KKKKKK-AAFALWAAFAA-NH2 1.89 16

6K-F17-2L11,13 KKKKKK-AAFALWLAFAA-NH2 2.31 16

6K-F17-2L10,14 KKKKKK-AAFLAWALFAA-NH2 2.31 8

6k-f17-2l16,17 kkkkkk-aafaawaafll-NH2 2.31 8

6K-F17-2L8,16 KKKKKK-ALFAAWAAFLA-NH2 2.31 64

6K-F17-2L7,8 KKKKKK-LLFAAWAAFAA-NH2 2.31 8

6K-F17-3L8,11,13 KKKKKK-ALFALWLAFAA-NH2 2.73 32

6K-F17-3L11,13,16 KKKKKK-AAFALWLAFLA-NH2 2.73 16

6K-F17-4L8,11,13,16 KKKKKK-ALFALWLFLA-NH2 3.14 64

Amino acids in lower case are D-enantiomers.

a Average hydrophobicity value of the core 11-residue segment is calculated from the Liu-Deber

hydrophobicity scale (Liu et al. 1998a); Lys residues are not included.

b Minimal inhibitory concentration (MIC) values measured against P. aeruginosa PAO1 strains

are representative of results from three or more separate experiments. Table MIC values reported

in (Glukhov et al. 2008).

22

1.3 PEPTIDE-MEMBRANE INTERACTIONS

1.3.1 Composition of Bacterial vs. Mammalian Membranes

Membrane-active antibiotics must exclusively target the invaders (bacteria) while being harmless

to the mammalian host cells. For this purpose, CAPs can take advantage of the significant

differences in the lipid compositions of these two systems. E. coli membranes, for example,

contain about 75% phosphatidylethanolamine (PE), 20% phosphatidylglycerol (PG), and 5% of

other components, including cardiolipin (Zhang et al. 2008). In particular, the anionic head

groups of PG and cardiolipin render this membrane susceptible electrostatically for association

with positively charged species such as natural and synthetic CAPs. In contrast, erythrocyte

lipids consist exclusively of zwitterionic (neutral) head groups, viz., the mammalian erythrocyte

membrane (outer leaflet) typically contains 33% phosphatidylcholine (PC), 18% sphingomyelin,

9% PE, along with 25% cholesterol (Spector et al. 1985). Two key differences of mammalian

vs. bacterial membranes are the facts that the erythrocyte lipids consist exclusively of

zwitterionic (neutral) head groups, and contain substantial amounts of cholesterol; bacterial

membranes are highly anionic and devoid of cholesterol.

1.3.2 Basis for selectivity of CAPs

Our laboratory has investigated the evidence of peptide selectivity for bacterial vs. mammalian

cell membranes by exposing the peptides to anionic and zwitterionic unilamellar lipid vesicles

(Fig. 1-8) (Glukhov et al. 2005). In these experiments, lipid/peptide (L/P) ratios were

maintained high enough (250 and above) at low peptide concentration (4 μM, below the lowest

MIC values) in order to mimic the initial steps of peptide-mediated membrane disruption.

Measurements of fluorescence emission intensity and blue shifts (or lack thereof) in the λmax of

the Trp probe incorporated into the hydrophobic core of peptides in the library were particularly

23

diagnostic for analysis of peptide insertion into a given membrane. Results have indicated that

CAPs with average core hydropathy above the 'threshold hydrophobicity' readily inserted into

bacterial lipid mixtures at depths of 2.4 to 7.9 Å (λmax values of 17-23 nm), while no insertion

was usually detected in model "mammalian" membranes. Peptide antimicrobial activity in

general was found to be increased with increasing depth of peptide insertion (Glukhov et al.

2005).

Structural studies of our designed peptides further revealed that they generally run as dimers on

SDS-PAGE gel (Glukhov et al. 2005), likely due to the fact that the sequences contain the

AxxxA (“small-xxx-small”) sequence motif, which is well-known to promote peptide

dimerization in membranes (Lear et al. 2004; Schneider et al. 2004). Such ability may be the

key determinant of the high antimicrobial activity, because oligomerization within the membrane

surface region is expected to create substantially larger disturbances in the bilayer once insertion

occurs. Based on the evidence of the depths of insertion in membrane and the dimerization

properties of the CAPs, results suggest a ‘grip and dip’ process, where in an initial electrostatic

interaction step, the anionic bacterial membrane lipids attract and bind peptide dimers onto the

bacterial surface, followed by the “sinking” of the hydrophobic core segment to a peptide into

the membrane (Glukhov et al. 2005).

24

Figure 1-8. Blue shifts (nm) in wavelength maxima emission (Δλmax) of Trp fluorescence

upon exposure of selected peptides to large unilamellar vesicles (LUVs) parepared from

bacterial lipid mixtures (LUV-bact) or mammalian red blood cell mixtures (LUV-RBC

(outer)). The large blue shifts confirm the insertion of the peptide Trp moiety into the

membrane. Peptides are: F17 = KKKAAAFAAWAAFAKKK-NH2; 6R-F17 =

RRRRRRAAFAAWAAFAA-NH2; 6K-F17, see Table 1-2; all-D 6K-W17-4L =

kkkkkkalwalwlawla-NH2. Purple bars: LUV-Zwit [0% anionic lipids, 100% zwitterionic lipids,

no cholesterol]. Only the relatively hydrophobic 6K-F17-4L inserts, and only in the absence of

cholesterol. Adapted from (Glukhov et al. 2005).

1.3.3 Toxicity Threshold of CAPs

To examine whether there exists a second “hydrophobicity threshold ” for peptide insertion into

zwitterionic membranes (at which point hemolytic activity may occur in mammalian cells), our

laboratory has designed a series of CAPs with various hydrophobicities based on the highly

active 6K-F17 CAP (Table 2) (Glukhov et al. 2008). It was found that as the core segment

hydrophobicity of the CAPs is increased, as in the case where the sequence contains two or more

Ala-to-Leu substitutions, we observed partial/shallow Trp insertion into the zwitterionic bilayer

moiety with blue shifts of 5-15 nm (Fig. 1-9). This is explained by the fact that the peptides start

25

to leave the bulk water for attachment/insertion into mammalian bilayers when their

hydrophobicity begins to approach sufficiently high levels, whereas relatively low core

hydrophobicity prohibits direct peptide attachment to the membrane via hydrophobic

interactions. The results indicate that a second hydrophobicity threshold for peptide insertion

into mammalian membranes occurs between hydrophobicity values of 1.9-2.3 among the sets of

6K-F17 analogues.

Figure 1-9. Blue shifts (nm), given as Δλmax = Δλmax(aqueous) – Δλmax(LUV), of selected

CAPs to freshly prepared anionic and zwitterionic large unilamellar vesicles (LUV), which

correlate with their hemolytic interactions (Song et al. 2005). Peptide sequences are given in

Table 1-2. Orange bars: anionic LUVs comprised of 25% anionic lipids (POPG) and 75%

zwitterionic lipids (POPC), similar to the composition of bacterial membranes. Blue bars:

zwitterionic-LUVs comprised of 100% zwitterionic lipids (POPC), similar to the outer leaflet of

erythrocyte cell membranes. Adapted from (Glukhov et al. 2008).

26

1.3.4 Effect of Cholesterol in CAP Selectivity

Our group has previously found that the combination of a highly hydrophobic novel CAP (with

four Leu residues replacing Ala) and the lack of cholesterol (LUV-Zwit. in Fig. 1-8) results in

significant membrane insertion (Glukhov et al. 2005), while normal level of 25% of cholesterol

in mammalian membranes slightly hinder the ability of CAPs to insert into the membrane

(Glukhov et al. 2008). Studies on natural CAPs such as pea defensin (Goncalves et al. 2012) and

gramicidin S (Prenner et al. 2001) also support the notion that cholesterol protects host cell

membranes from the disruptive effects of CAPs. This is likely because that the presence of

cholesterol in the membrane increases the packing density of the lipids and prevents the peptide

from forming a stable association with the membrane, and consequently prevents local

concentration of the peptide at the bilayer interface and hence inhibits activity in mammalian

membrane (Dennison et al. 2011).

1.4 PEPTIDE-ALGINATE INTERACTIONS

The exopolysaccharide alginate that produced by P. aeruginosa biofilms in the lungs of CF

patients protects the bacteria (Ramsey et al. 2005; Ryder et al. 2007). Understanding the

mechanism(s) by which alginate confers heightened antibiotic resistance, and developing

strategies to circumvent it, is an important focus.

1.4.1 Helical Induction of CAPs in Alginate

Knowledge of those designed peptides that insert successfully into bacterial membranes

prompted us to examine the mechanism of CAP tolerance in biofilm bacteria, and in the course

27

of the research, to discover a novel function of alginate. Our laboratory investigated the

interaction of several of our synthetic transmembrane model peptides with alginate, and noted

that an α-helical conformation induction in peptides by alginate occurred only for antimicrobially

active peptides – those that are above the hydrophobicity threshold (Liu et al. 1998a) (Fig. 1-10).

Consistent with these findings, blue shifts in Trp fluorescence maxima in hydrophobic peptides

above the "threshold hydrophobicity" similarly correlate with helix induction. Peptides in this

series that exhibit no helix induction and no blue shifts are biologically inactive. The fact that

helical induction of membrane-active peptides (above the hydrophobicity threshold) is typically

observed upon peptide association with micelles or membrane bilayers (Wieprecht et al. 1996;

Gesell et al. 1997; Liu et al. 1998a) leads us to suggest that alginate acts as an 'auxiliary bacterial

membrane', triggering the synthetic CAPs to undergo premature conformational changes of the

type normally associated with their insertion into a membrane environment, and "trap" only

those peptides that would be lethal to bacteria if they reached the bacterial membranes (Chan et

al. 2004).

Figure 1-10. Helical induction of secondary structures in peptides by alginate studied by

CD spectroscopy. Model peptides in the sequence KKAAAFAAAAAFAAWAAFAAAKKKK-

NH2 that are above the hydrophobicity threshold (X = Phe) adopted an α-helical conformation,

while the peptides below the hydrophobic threshold (X = Glu) remained as randomly coiled.

Adapted from (Chan et al. 2004).

28

1.4.2 Factors that influence peptide-alginate interactions.

It was proposed that the peptide-alginate binding and interaction are mediated by hydrophobic

microdomains comprised of pyranosyl C-H groups that are inducible upon formation of peptide-

alginate complexes due to charge neutralization (Chan et al. 2004). Our lab has investigated the

molecular origin of the hydrophobic interface in alginate by examining the effects of alginate

composition, including the M- and G-block sequences, O-acetylation of alginate, glycan chain

length, and the general peptide-alginate binding ratios, on the secondary structure and

fluorescence emission of designed CAPs having the sequence of KK-

AAAXAAAAAXAAWAAXAAA-KKKK (where X = Phe, Trp or Leu) (Chan et al. 2005; Kuo

et al. 2007). The findings are described below.

1.4.2.1 Peptide Concentration

Chan et al. [2005] explored the effect of the peptide concentration on CD spectra in a fixed

amount of alginate using the 25-mer novel peptides. At a peptide:alginate ratio of 30 μM/0.2

mg/mL, the peptide with X= Phe adopts an α-helical conformation, whereas in a higher ratio of

90 μM/0.2 mg/mL, peptide aggregates in alginate and results in a loss of helicity in the CD

spectrum (Fig. 1-11). Upon binding to the anionic carboxylate groups of alginate, all peptides

with Lys positive charges present would be effectively ‘neutralized’ at a relatively high peptide-

to-alginate w/w ratio, and the complex eventually reaches its solubility limit in aqueous solution.

29

Figure 1-11. Circular dichroism spectra of the X = Phe peptide at 30 µM (dashed line) or 90

µM (solid line) in 0.2 mg/mL alginate solution in Tris-HCl buffer at pH 7.0. Adapted from

(Chan et al. 2005).

1.4.2.2 M- vs. G-blocks of Alginate

Alginate is a heteropolysaccharide consisting of β-(1-4)-D-mannuronate (M) and α-(1-4)-L-

guluronate (G), where M residues constitute about 75% of residues in P. aeruginosa alginate

(Gacesa 1998). To investigate whether the compartments composed of four oriented C-H

protons on M residues are a major source of alginate-mediated helix induction in hydrophobic

peptides (Chan et al. 2004; Chan et al. 2005), our laboratory has quantitated the relative extents

of CAP helical induction as a function of M- and G-contents that are prepared from

enzymatically-cleaved alginate. It was observed that M-block and G-block induced similar α-

helical conformations (Fig. 1-12) and tryptophan fluorescence blue shifts, suggesting that both of

these structural units of alginate exhibit a considerable degree of significant non-polar surfaces to

interact with the hydrophobic core of the CAPs upon charge neutralization. However, their

molar ellipticities are significantly lower than that of the starting alginate, which may be

30

explained by the fact that the undigested alginate with a higher molecular weight and a longer

chain length may accommodate additional CAP binding (Kuo et al. 2007).

Figure 1-12. CD spectra of CAP KK-AAAFAAAAAFAAWAAFAAA-KKKK in alginate

and in oligo-D-mannuronate (AlgM-M) and oligo-L-guluronate (AlgG-G). Peptide

concentrations are 5 μM. AlgG-G and AlgM-M are alginate sequences enriched in repeating α-L-

guluronate (G-block) and β-D-mannuronate (M-block), respectively. Adapted from (Kuo et al.

2007).

1.4.2.3 O-Acetylation of Alginate

While tryptophan fluorescence data have suggested that alginate may process hydrophobic

components (Chan et al. 2004), the percent emission intensity of 8-anilino-1-naphthalene

sulfonic acid (ANS), a hydrophobic fluorescent probe commonly used in the detection of non-

polar surfaces in protein aggregates and supramolecular assemblies (De Campos Vidal 1978;

Salemi et al. 2006), was measured to determine whether hydrophobic surfaces exist in alginate in

the absence of CAPs (Fig. 1-13). The emission intensity of ANS showed no significant increase

above basal fluorescence in water with increasing alginate or alginate concentration, which

suggests that both alginate and peptides intrinsically do not have hydrophobic domains

31

conducive for ANS binding alone. In addition, O-acetylated alginate of P. aeruginosa origin had

little effect on ANS fluorescence, although the intensity was overall higher than non-acetylated

alginate, suggesting that O-acetylation in P. aeruginosa alginate only slightly increases the

hydrophobicity of the polymer, but is likely not a significant factor in driving the hydrophobic

interaction with CAPs after charge neutralization (Kuo et al. 2007).

Figure 1-13. % ANS fluorescence emission at increasing concentrations of non-O-

acetylated kelp alginate (- O-acetyl), O-acetylated P. aeruginosa alginate (+ O-acetyl) and

the CAP (X = Phe). Adapted from (Kuo et al. 2007).

1.4.2.4 Length of Glycan Chain

Kuo et al. [2007] have studied the effect of alginate glycan chain length on the alginate-peptide

interaction, and found that the CAP conformation is sensitive to the mixing ratio of peptides to

oligo-uronates of ca. 7-12 degree of polymerization (Fig. 1-14), which appear to be in a delicate

equilibrium between aggregation and partial α-helix formation. At a 1:1 ratio of negatively

charged carboxylate of the alginate to positively charged Lys groups of the CAPs, visible

aggregates are observed in the mixtures. This effect is not exclusive to the binding of CAPs, but

true for the interaction of alginate with other poly-positively charged polymers (i.e. cationic

32

aminoglycoside antibiotics), and depending on the concentration ratio, result in a spectrum of

phase transitions from gels to aggregates (Hoffman 2001).

Figure 1-14. Helical content of CAP KK-AAAFAAAAAFAAWAAFAAA-KKKK at 222 nm

of molar ellipticity as a function of increasing alginate degree of polymerization. The solid

line represents the oligo-D-mannuronate, and the dotted line represents the oligo-L-guluronate.

Adapted from (Kuo et al. 2007).

1.5 OVERALL GOALS OF THE THESIS

The intrinsic antimicrobial tolerance of P. aeruginosa biofilms and its propensity to develop

resistance against conventional antibiotics are major therapeutic challenges at the present time.

Antimicrobial agents not only need to effectively kill the planktonic bacteria, but also need to be

capable of efficiently penetrating the biofilm matrix once the bacteria have become embedded

and colonized. For this purpose, our laboratory has carried out ongoing development of novel

membrane-active cationic antimicrobial peptides. To optimize the antimicrobial activity of these

peptides and to examine their potential applications to biofilms, it is now essential to expand our

understanding of the basis of the interactions involved between the CAPs and the bacterial

membrane bilayers, as well as important biofilm exopolysaccharides such as alginate. The aims

33

of the thesis are thus to elucidate the chemical and structural factors primarily responsible for the

mechanism of action of CAPs as they become embedded in bacterial polysaccharides and

membranes. The general hypothesis is that a combination of factors, such as peptide core

segment hydrophobicity level and length, overall positive charges and their distribution, and

amino acid composition and chirality, act as key determinants in peptide-membrane and peptide-

polysaccharide interactions that contribute to CAP antimicrobial efficacy combined with biofilm

diffusion. In this context, the specific goals of this thesis are:

1. To determine the antimicrobial efficacy of the designed cationic peptides (17-mers)

against multiple strains of P. aeruginosa (Chapter 2);

2. To visualize the membrane disruptive ability of CAPs and correlate the results with the

structural conformations of CAPs using a combination of atomic force microscopy and

FTIR spectroscopy (Chapter 3);

3. To explore the roles of peptide core hydrophobicity level and positive charge distribution

in CAP design, and their influences on the bioactivity of the CAPs (Chapter 3);

4. To determine the effects of amino acid composition, peptide hydrophobicity and charge

distribution on the structural basis of CAP-alginate interactions (Chapter 4); and

5. To correlate the alginate binding affinity of the CAPs with their permeation ability into

the alginate matrix (Chapter 4).

34

Chapter 2 Antimicrobial Activity of Designed Novel CAPs

2

35

2.1 INTRODUCTION

Pseudomonas aeruginosa is one of the leading Gram-negative pathogens that is associated with

various nosocomial infections, including the chronic respiratory infection in cystic fibrosis

patients (Kerem et al. 1990; Henry et al. 1992). Antibiotic treatment of P. aeruginosa infections

in CF patients often takes prolonged periods, and may encourage antibiotic resistance (Ashish et

al. 2011). This resistance has been be attributed to low permeability of bacterial outer membrane

to antibiotics (Nikaido 1994), multidrug resistance efflux pumps (Bhardwaj et al. 2012), and/or

the formation of biofilms (del Pozo et al. 2007). Biofilms are characterized by bacteria

producing exopolysaccharides; for instance, the overproduction of alginate is an important

phenotype in the mucoid strains of P. aeruginosa (Terry et al. 1991). The increase in resistance

to antibiotics of biofilm-forming bacteria can be due to overexpression of multidrug efflux

pumps, slow bacterial growth, and restricted penetration problems (Stewart et al. 2001; del Pozo

et al. 2007). Therefore, the development of effective therapeutic alternatives is urgently required.

Our lab has developed a new category of non-amphipathic hydrophobic membrane-active

peptides that have antimicrobial activity against Gram-positive, Gram-negative bacteria, and

yeast (Stark et al. 2002; Burrows et al. 2006). These peptides have been shown to adopt an α-

helical structure in SDS micelles, and spontaneously insert into membranes when the average

core segment hydrophobicity is above an experimentally determined threshold value (0.4) based

on the Liu-Deber hydrophobicity scale (Liu et al. 1998a). Among these novel CAPs, the peptide

D-6k-f17 (D-enantiomer of 6K-F17) in the sequence of KKKKKKAAFAAWAAFAA-NH2 was

shown to have an MIC (minimal inhibition concentration) of 2 μM against P. aeruginosa PAO1

strain (Glukhov et al. 2008), a value ca. 100 times more effective than a variety of other

antibacterial peptides. A series of derivatives varying in hydrophobicity levels were designed

based on this peptide 6K-F17, as listed in Table 2-1. A higher hydrophobicity was obtained by

replacing Ala residues by Leu at various positions of the core segment, whereas a lower

hydrophobicity was obtained by replacing Phe by Ala at positions 8 and/or 13.

36

In the present work, to establish a general relationship of the hydrophobicity level of CAPs to

their antimicrobial activity, we measured the antimicrobial efficacy of these designed CAPs

against multiple mucoid and non-mucoid strains of P. aeruginosa, and a typical lab strain of

Escherichia coli, and determined the time-course kinetics of peptide killing. For comparison, the

effect of alginate alone on the bacterial resistance to CAPs was also investigated.

2.2 MATERIAL AND METHODS

2.2.1 Peptide Synthesis and Purification

The amino acid sequences of the peptides studied are listed in Table 2-1. The peptides were

synthesized by the continuous flow Fmoc solid-phase method on a PS3 Protein Technologies

Inc. peptide synthesizer using the standard cycle (Liu et al. 1997). FMOC-PAL-PEG-PS resin

(Applied Biosystems) was used to produce an amidated C-terminus. 2-(7-azabenzotriazol-1-yl)-

1,1,3,3-tetramethyluronium hexafluorophosphate (HATU) and N,N-diisopropylethylamine

(DIEA) were used as the activation pair with amino acids at four-fold excess. N-terminal Fmoc

groups were removed at the last step of the synthesis. Deprotection and cleavage of peptides

were performed in a mixture of 88% trifluoroacetic acid (TFA), 5% phenol, 5% water, and 2%

triisopropylsilane (TIPS) for 2 hr at room temperature.

The crude peptides were precipitated in cold ether for > 30 min, and purified on a reverse-phase

C4 preparative high performance liquid chromatography (HPLC) using a linear gradient of

acetonitrile in 0.1% TFA. The purities of the peptides were confirmed by their molecular masses

using MALDI or ESI mass spectrometry. The concentrations of the peptides were determined

using the micro-bicinchoninic acid (BCA) protein assay.

37

Table 2-1. Sequences and hydrophobicity values of the non-amphipathic core segments for

peptides used in this study.

Amino acids in lower case are D-enantiomers. The top 11 peptides have been reported (Glukhov

et al. 2005; Glukhov et al. 2008), and were re-synthesized for study in the present work. The

bottom two peptides are two newly designed peptides that have lower segment hydrophobicity

than 6k-f17.

CSH, core segment hydrophobicity.

2.2.2 Circular Dichroism

Circular dichroism (CD) spectra were recorded on a Jasco-810 spectropolarimeter using a 1-mm

path-length quartz cell at 25oC. 20 μM of each peptide in 1.0 mM MES buffer at pH 5.5 with or

without 10μM of SDS was measured on an average of 3 scans with buffer background

subtracted.

38

2.2.3 Minimal Inhibitory Concentration (MIC) Assay

The antimicrobial activity of each peptide was tested in sterile 96-well microtiter plates against

ampicillin-resistant Escherichia coli BL21 strain, P. aeruginosa PAO1, PA14, PAK, FRD1, and

PDO300 strains (kind gifts from Dr. Lynne Howell, Hospital for Sick Children) by following

standard microtiter dilution protocols in Mueller Hinton Broth (MHB) (Wiegand et al. 2008).

The bacterial strains were grown in MHB (with ampicilin) at 37oC overnight, and diluted to a

final concentration of ~5 x 105 to 10

6 colony forming units as determined by UV

spectrophotometry at optical density (OD) 600 nm. 11 L of peptides of two-fold serial

dilutions were added to 100 μL of diluted bacterial suspension in 0.2% bovine serum albumin

(BSA) and 0.01% acetic acid buffer, which helped to prevent high concentrations of peptides

from aggregating in the broth or attaching to the wells (Wu et al. 1999). Plates were incubated at

37oC overnight for 20 h, and the minimum inhibitory concentration (MIC) was taken as the

concentration at which the bacterial growth was fully inhibited, detected at OD600 using a

Genesys 5 microplate autoreader Spectrophotometer.

2.2.4 Time Course Study of Killing

MHB was incubated at 37oC for 2 hours prior to the experiments. Inocula of ~10

6 cfu/mL

bacterial cells were suspended in MHB in 5 mL polypropylene tubes, where 2x the concentration

of the MIC of the antimicrobial peptides were added. The cell mixtures were incubated at 37oC,

and aliquots were taken from the tube at different time points and visible plate counts were

performed (Burrows et al. 2006).

39

2.2.5 Purification of Alginate

Alginate (Sigma) was purified using a procedure adapted from previously described method (De

Vos et al. 1997). Briefly, 1% alginate in 1 mM EDTA was precipitated by dropwise addition of

2 M HCl on ice until pH reached 2.5, and washed with 0.01 M HCl containing 20 mM NaCl to

remove the soluble impurities. The precipitated alginate was re-dissolved by bringing the pH up

to 7.0 with the dropwise addition of 0.5 M NaOH. Alginate was extracted twice in a

chloroform/butanol mixture (4:1 v/v) to remove potential lipids and polyphenols (Dusseault et al.

2006). The aqueous layer containing alginate was precipitated with 100% ethanol, washed with

diethyl ether, and lyophilyzed overnight.

2.2.6 Minimal Inhibitory Concentration in the Presence of Alginate

The MIC test was performed as described above in 2.2.3, in the presence of purified alginate

ranging from 0 to 2.0 mg/mL in MHB.

2.2.7 Statistical Analysis

One-way ANOVA (analysis of variance) test was performed using program GraphPad Prism to

compare the MIC curves in the presence of alginate.

40

2.3 RESULTS AND DISCUSSION

2.3.1 Secondary Structure of CAPs

The CAPs dissolved in an aqueous environment display largely random coiled structure (Fig. 2-

1A). In the membrane-mimetic environment of SDS micelles, all peptides induced an α-helical

conformation as their hydrophobic core regions become inserted into phospholipid micelles (Liu

et al. 1998a), indicated by the two extrema at 208 nm and 222 nm in the CD spectra (Fig. 2-1B).

This indicates that these peptides would in theory insert into the bacterial membranes. The

mirror image helical CD spectra of all-D-residue peptides insert into SDS micelles in the same

manner.

41

Figure 2-1. Circular dichroism spectra of designed CAPs in aqueous and SDS micelle

environments. The peptide sequences are given in Table 1. The spectra were measured for 20

μM of each CAP in 20 mM Tris buffered at pH 7.0 with (B) or without (A) 10μM of SDS. The

spectra are based on triplicate measurements with buffer background subtracted.

42

2.3.2 Antimicrobial Activity of Novel CAPs against Various Bacterial Strains

The antimicrobial activities of the designed peptides were measured against multiple bacterial

strains, including E. coli BL21, P. aeruginosa non-mucoid strains PAO1, PA14 and PAK, and

mucoid strains FRD1 and PDO300. Among all the tested CAPs, the peptide D-6k-f17 displayed

the most effective antimicrobial activities (Table 2-2). In agreement with our previous findings,

the peptides with D-amino acids are 2 to 8-fold more active than corresponding L-residue analogs

(Glukhov et al. 2008), suggesting that D-enantiomers of the peptides are less susceptible to

proteases secreted by P. aeruginosa - and also supporting the notion that CAPs act by physical

disruption of membranes rather than by association with any chiral components. The peptide 6k-

a17-f9 with a hydrophobicity value of 1.04 displayed good-to-modest MIC values (2-16 μM

depending on the strains) (Table 2-2). The 6k-a17 peptide with the lowest hydrophobicity (a

value of 0.4 based on the Liu-Deber scale (Liu et al. 1998a)) has MICs much greater than 64 μM

(Fig. 2-2; representative inhibition curves tested against E. coli BL21). The results indicate that

even though 6k-a17 was designed to be suitable for membrane insertion as its core segment

hydrophobicity is above the Liu-Deber hydrophobicity threshold, it is a much less effective

antimicrobial peptide than the rest of the 17-residue novel CAPs. The antibacterial activities

become generally decreased as the hydrophobicity of the CAPs is increased, suggesting that the

increased segmental hydrophobicity of peptides eventually lead to an increased potential to self-

association/oligomerization in the aqueous phase, thus limiting the concentration of peptide

actually impacting on the bacterial membrane (see Chapter 3 for a further discussion). We noted

that the MIC values of the mucoid strains are comparable to the ones of the non-mucoid strains,

likely because bacteria have not yet developed biofilms at this stage. Some CAPs display better

antimicrobial activities against certain strains over others, possibly due to the differences in

membrane thickness and cell viability among the strains.

43

Figure 2-2. Inhibitory potential of designed antimicrobial peptides. Shown are the OD600

measurements of the peptides 6k-a17 (blue) and 6k-a17-f9 (orange) when the E.coli cells were

incubated with increasing concentrations of peptides. 100 μL of ~5 x 105 colony forming units

of E.coli cells in MHB were mixed with 11 μL of varying concentrations of peptides in 96-well

sterile plates, and OD600 was taken after 20 hrs incubation at 37oC. The results shown represent

averages of three experiments for each peptide; standard deviations are indicated in error bars.

44

Table 2-2. Antimicrobial activities of CAPs tested against various bacterial strains.

MICb (µM)

Peptidea E. coli BL21 P.a PAO1 P.a PA14 P.a PAK P.a FRD1 P.a PDO300

D-6k-f17 4 2 0.5 2 1 0.5

6K-F17 n/d 4 n/d n/d 4 2

6K-F17-1L11 4 4 2 4 4 4

6K-F17-2L11,13 8 16 4 16 8 4

6K-F17-2L10,14 8 8 4 8 4 1

D-6k-f17-2l16,17 2 4 1 4 2 2

6K-F17-2L8,16 8 4 0.5 8 2 4

6K-F17-2L7,8 8 16 0.5 8 4 16

6K-F17-3L8,11,13 16 16 8 16 16 8

6K-F17-3L11,13,16 16 16 8 16 8 8

6K-F17-4L8,11,13,16 16 16 16 8 16 16

D-6k-a17 >>64 >>64 n/d n/d n/d n/d

D-6k-a17-f9 8 16 n/d n/d n/d 2

a Sequences of peptides are shown in Table 2-1. Amino acids in lower case are D-enantiomers.

The bottom two peptides are the newly designed peptides that have lower segment

hydrophobicity than 6k-f17.

b MIC, minimal inhibitory concentration, is the lowest concentration required to fully inhibit the

bacterial growth.

P.a = P. aeruginosa; n/d = not determined.

2.3.3 Time Course of Bacteria Killing

One of the important advantages of CAPs over conventional antibiotics is their ability to cause

rapid killing via physical mechanisms (Zhang et al. 2001), and precludes the development of

resistance. While we know that most of our designed novel CAPs are effective against different

strains of bacteria, it is worth obtaining a better understanding on the kinetics of the CAPs at

killing microbes by measuring the time course of bacterial inhibition. The most active peptide,

D-6k-f17, the modestly active peptide 6K-F17-4L, and a peptide with 3 Lys each distributed at

45

either N- or C- termini and a same hydrophobic core as 6K-F17-4L, termed 3K-F17-4L-3K (see

Table 3-1 in Chapter 3), were chosen as representatives for this study. P. aeruginosa (PAO1

strain) cells were treated with selected CAPs at final concentrations of twice the determined

MICs to ensure full bacterial inhibition. The antimicrobial peptides were able to completely kill

the planktonic bacteria in 20-40 min (Fig. 2-3; selected CAPs were tested), suggesting that these

peptides could be valuable drug candidates since the planktonic bacterial cells are killed before

they can develop resistance against the antimicrobial peptides. It is interesting to note that the

3K-F17-4L-3K peptide induced bacterial cell death more rapidly than the 6K-F17-4L, suggesting

that it may undergo a slightly different mechanism of action (see Chapter 3 for a further

discussion).

Figure 2-3. Time course study of antimicrobial activity of peptides against P. aeruginosa

(PAO1 strain). Sequences of the peptides 6K-F17-4L and 6k-f17 are shown in Table 2-1, and

the sequence of 3K-F17-4L-3K is shown in Table 3-1 (see Chapter 3). The viable bacterial cells

(log cfu/mL) were measured as a function of time after peptides at 2X their MIC concentrations

were added to ~106-10

7 cfu/mL bacterial suspensions.

46

2.3.4 Alginate Reduces the Activity of CAPs

Prior to incubating the CAPs in experiments designed to mimic the mucoid environment, the

antimicrobial activities were measured with the addition of alginate in the growth media

containing E. coli BL21, a bacterial strain that does not produce alginate. As shown in Fig. 2-4,

the addition of merely 0.25 mg/ml alginate increased the MIC value of the peptide 6K-F17-

3L11,13,16 by more than 4-fold (16 to >64 µM), which is likely caused by CAP binding to the

anionic alginate through both electrostatic and hydrophobic interactions (Chan et al. 2005).

However, the peptide 6K-F17 showed no significant difference in the MIC curves as the addition

of alginate was increased up to 1.0 mg/mL (p >> 0.05), and only a slight increase was observed

from 4 µM to 8 µM in the presence of 2.0 mg/mL alginate. This result suggests that some

peptides (such as 6K-F17) have relatively lower interference getting through alginate, possibly

due to a weaker alginate-binding ability (see Chapter 4 for a further discussion). Nevertheless, in

general the mucoid alginate matrix provides protection against the host immune system by acting

as a diffusion barrier to positively-charged antimicrobial peptides.

47

Figure 2-4. Killing potential of designed antimicrobial peptides in the presence of alginate.

Shown are the OD600 measurements of the peptides 6K-F17-3L11,13,16 (left) and 6k-f17 (right)

when the E.coli cells were incubated with peptides in the presence of alginate ranging from 0 to

2.0 mg/mL. Varying concentrations of alginate were mixed with the MHB media prior to cell

dilution. 100 μL of 3 to 5 x 105 colony forming units of E.coli cells in each alginate containing

broth media were mixed with 11 μL of different concentrations of peptides in 96-well sterile

plates, and OD600 values are taken after 20 hrs incubation at 37oC. The results shown represent

averages of three experiments for each peptide; standard deviations are indicated in error bars.

2.4 SUMMARY

CAPs require an optimal hydrophobicity to remain active against bacterial membranes. Even

though in principle CAPs with a hydrophobicity value of 0.4 or above (Liu-Deber scale) should

insert into membrane-mimetic SDS micelles (Liu et al. 1998b), they become actually

antimicrobial at a hydrophobicity level above 1.0 in vivo. Then, as peptide hydrophobicity

increases beyond a certain threshold, the antimicrobial activity of CAPs generally decreases from

maximum values. In favor to our interests, regardless of their MIC values, these designed novel

CAPs are able to kill bacteria within 20-40 min before bacteria start to develop resistance.

However, in the case of a mimetic bacteria mucoid environment, the presence of alginate reduces

the activity of the CAPs, albeit the interference caused by alginate is less severe with some

CAPs.

48

Chapter 3 Peptide-Membrane Interactions

Exploring the Roles of Peptide Hydrophobicity and Charge Distribution in CAP Design

3

The contents of this chapter have been published, in part, by

1. Yin, L.M., Lee, S., Edwards, M.A., Yip, C.M., and Deber, C.M. (2011). Proceedings of the

22nd

American Peptide Symposium, San Diego, CA, June 25-30, 2011, pp. 252-253,

©American Peptide Society, San Diego, CA.

2. Yin, L.M., Edwards, M.A., Li, J., Yip, C.M., and Deber, C.M. (2012). J. Biol. Chem.

287(10): 7738-7745. © the American Society for Biochemistry and Molecular Biology.

Author contributions:

1. LMY and CMD designed the research. LMY synthesized and purified the peptides. MAE

performed the AFM experiments. LMY and CMD wrote the paper with input from CMY

and SL.

2. LMY and CMD designed the research. LMY performed the experiments and analyzed the

data for circular dichroism, SDS-PAGE, antimicrobial activity assays and hemolytic assays.

MAE and CMY conducted the AFM experiments and analysis. JL optimized the set-up for

the FTIR experiments. LMY and JL performed the FTIR experiments and analysis. CMD

provided guidance in computational modeling. LMY and CMD wrote the paper.

49

3.1 INTRODUCTION

It is known that peptide hydrophobicity plays an important role in membrane selectivity and

insertion, and for antimicrobial activity (Wieprecht et al. 1997; Chen et al. 2007). As discussed

in Chapter 1, based on the highly active CAP 6K-F17, our laboratory has designed a series of

CAPs with a range of hydrophobicity values, and observed a “threshold hydrophobicity” for

selective bacterial membrane insertion (Liu et al. 1996; Liu et al. 1998b; Glukhov et al. 2005) –

viz., any peptide with hydrophobicity below this level (minimum value of 0.4 calculated from the

Liu-Deber scale (Liu et al. 1998b)) becomes no longer membrane-active. Yet for being effective

at bacterial killing in vivo, CAPs require a slightly higher hydrophobicity (value of ~1.0

calculated from the Liu-Deber scale; see Chapter 2). However, once the core segment

hydrophobicity of the CAPs is beyond an upper threshold – as in the case where the sequence

contains two or more Ala-to-Leu substitutions – the CAPs generally have reduced antimicrobial

activity, and display increased toxicity to mammalian membranes (Glukhov et al. 2008). In

addition to hydrophobicity, the net positive charge of a given CAP also plays an important role

in peptide-membrane interactions, particularly in attracting the CAP efficiently to the anionic

surface of bacterial membranes (De Kroon et al. 1990; Dathe et al. 2001; Leptihn et al. 2010).

Yet the critical interplay of CAPs with varying hydrophobicity levels vs. varying distributions of

positive residues along the CAP sequence as a determinant of bioactivity remains to be clarified.

In this study, we examined four such bioactive peptides (Table 3-1), selected to highlight the

extremes of the two properties: core segment hydrophobicity (four Ala residues substituted with

four Leu residues) and positive charge distribution (six Lys residues on the N terminus versus

three Lys residues on each of the N and C termini). By relating the microbiological studies of

these designed peptides to the biophysical characteristics of peptide-membrane interactions, we

can increase our understanding as to (1) why increasing hydrophobicity leads to poorer

antimicrobial activity and greater hemolytic toxicity; (2) whether altered charge distribution

would improve the activity of CAP with the same hydrophobicity level; and (3) which factor

50

(hydrophobicity and charge distribution) is ultimately the more important contributor to effective

CAP design and bioactivity.


3.2.1 Peptide Synthesis

The amino acid sequences of the peptides studied in this Chapter are listed in Table 3-1. Peptide

synthesis and purification were performed as described in Chapter 2.

Table 3-1. Sequences, molecular weights (MW), and hydrophobicity values of CAPs used in

this study.

Peptide Amino Acid Sequence MW (Da) Hydrophobicitya

6K-F17 KKKKKK-AAFAAWAAFAA-NH2 1836 1.48

6K-F17-4L KKKKKK-ALFALWLAFLA-NH2 2005 3.14

3K-F17-3K KKK-AAFAAWAAFAA-KKK-NH2 1836 1.48

3K-F17-4L-3K KKK-ALFALWLAFLA-KKK-NH2 2005 3.14

a Hydrophobicity is the mean residue hydrophobicity of the peptide core segment, calculated

from the Liu-Deber scale (Liu et al. 1998a); Lys residues are not included.


CD spectra were recorded on a Jasco-810 spectropolarimeter using a 1-mm path-length quartz

cell at 25oC. 20 µM of each peptide in 20 mM Tris buffer and 10mM NaCl, with and without

51

10mM of SDS at pH 7.0 was measured on an average of 3 scans with buffer background

subtracted.

3.2.3 SDS-PAGE

50 ng portions of each peptide were prepared in sample buffer (Novex) and incubated at room

temperature for >30 min prior to being loaded onto NuPAGE Novex 12% Bis-Tris precast gels

(1.0 mm thickness, 10 wells) in MES buffer according to the manufacturer’s protocols. Silver

stain was performed using the SilverXpress silver staining kit (Invitrogen) to visualize peptides

on gels. Apparent molecular weights were estimated from the migration of Novex Sharp

Unstained Protein Standard (Invitrogen). The gel was analyzed using the ImageJ (NIH)

program, and MWexp/MWtheor values were calculated from the ratios of the experimental to

theoretical molecular weights of the CAPs.

3.2.4 Computational Modeling of CAPs

Energy-minimized models of the interaction between two identical -helices of CAP sequence

were generated using the global conformation search program CHI, as described (Adams et al.

1996). These CAP homodimer models with energetically favourable packing interfaces were

analyzed, and visualized using PyMOL (DeLano Scientific).

3.2.5 Liposome Preparation

To mimic bacterial and mammalian membranes, desired ratios of lipid solutions in chloroform

were mixed and dried by rotary evaporation for a minimum of 1 hr. 10 mM HEPES buffer

52

containing 150 mM NaCl and 1 M CaCl2 at pH 7.4 was added to rehydrate the lipid mixture to a

final concentration of 1 µM, followed by sonication at a temperature higher than the melting

temperatures of all the lipids for 40 min prior to atomic force microscopy (AFM) measurements.

For the FTIR experiments, the lipids were rehydrated in CaCl2-free deuterated HEPES buffer to

a final concentration of 2 µM, and used immediately.

3.2.6 Atomic Force Microscopy (AFM)

AFM images were acquired in fluid tapping mode using a Digital Instrument MultiMode

scanning probe microscope comprising a Nanoscope IIIA controller equipped with either a “J”

scanner (maximum scan area: 116 µm x 116 µm), or an “E” scanner (maximum lateral scan

area:14.6 µm by 14.6 µm). All images were acquired using a SNL-10 short, thin tip (Veeco

Probes, Camarillo, CA) fitted to a combined tapping mode/contact mode glass fluid cell fitted

with inlet and outlet ports. Images were collected at a resolution of 512 x 512 pixels using a scan

angle of 0o and scan rate of 1 Hz. The tip drive frequency was generally set between 7 and 10

kHz with a drive amplitude set point of 0.2-0.6 V. The flow-through glass fluid cell was sealed

against freshly cleaved mica with a silicone O-ring to create a 200 µL sample compartment. To

facilitate liposome fusion and bilayer formation, the freshly cleaved mica sealed in the fluid cell

was incubated for ~ 10 minutes with HEPES buffer (10 mM HEPES, 150 mM NaCl, pH 7.4, 1

M CaCl2) prior to the introduction of ~ 500 µL of hydrated liposomes heated to ~70 oC. After ~

30 minutes of incubation at room temperature to allow for bilayer formation, the fluid cell was

flushed with liposome-free buffer. Reference AFM images of the bilayers were then acquired

prior to the addition of ~ 300 µL aliquot of CAP of interest at 8 µM in HEPES buffer to the fluid

cell. All AFM images were acquired at room temperature. Image analysis was performed using

the Nanoscope software (ver. 5.30r1, Digital Instruments) on images that had been subjected to

zero-order flatten and second-order plane fit filters. Relative height differences were determined

using a horizontal section line along the slow scan axis.

53

3.2.7 Attenuated Total Reflection-Fourier Transform Infrared Spectroscopy (ATR-FTIR)

The FTIR spectra were collected using a Nexus 670 FTIR spectrometer equipped with an

EverGlo mid-IRsource, a liquid-N2-cooled MCT/A detector, a KBr beamsplitter, a SmartOrbit

single-bounce ATR accessory fitted with a diamond internal reflectance element (IRE), and a

custom flow-through sealed fluid cell at a resolution of 2 cm-1

using an average of 128 scans

over a scan range of 4000-700 cm-1

, referenced against the spectra of a clean diamond IRE (Fig.

3-1). 500 µL of freshly sonicated liposomes in 10 mM deuterated HEPES and 150 mM NaCl

(pH 7.4) were injected into the custom fluid flow cell (as above) covering the diamond IRE, and

flushed with buffer after the lipids fused onto the surface, as confirmed with IR scans. Each

tested peptide (8 µM) in HEPES buffer was added to the fused lipids, and scans were taken over

time. All spectra were analyzed using the Omnic software (version 5.2a, Nicolet Instrument

Inc.), with lipid spectra subtracted, H2O- and baseline-corrected. Fourier self deconvolution

(FSD) was performed on the amide peak from 1700 to 1600 cm-1

using a full width at half height

(FWHH) of 13 cm-1

(typically 12 to 20 cm-1

(Goormaghtigh et al. 1999)) and an enhancement

factor, K, of 2.4 (typically 2-3 (Tamm et al. 1997)).

54

Figure 3-1. A photograph of the FTIR set-up. A custom-made fluid flow cell with a 300 μL

compartment volume placed on top of the diamond internal reflection element (IRE).

3.2.8 Antibacterial Activity

The antimicrobial activity of each peptide was tested in sterile 96-well plates by a modified

standard microtiter dilution protocols in cation-adjusted MHB (Wu et al. 1999). P. aeruginosa

PAO1 strain (kind gift from Dr. Lynne Howell, Hospital for Sick Children) was grown in cation-

adjusted MHB at 37oC overnight, and diluted to a final concentration of 5 × 10

4 to 1 × 10

5

colony-forming units/mL. 11 L of peptides of two-fold serial dilutions were added to 100 L

of diluted bacterial suspension. Plates were incubated at 37oC overnight for 20 h, and the

minimum inhibitory concentration (MIC) was taken as the concentration at which the bacterial

growth was fully inhibited, as detected at A600 using a Genesys 5 microplate autoreader

Spectrophotometer.

55

3.2.9 Hemolytic Activity

The hemolytic toxicities of the designed CAPs were measured in human red blood cells (RBCs)

as previously described (Glukhov et al. 2008). Freshly collected venous human blood with

heparin was centrifuged at 1000 × g for 5 min at 11oC to remove the buffy coat, and the RBCs

obtained were washed three times with PBS (8.0 g NaCl, 1.44 g Na2HPO4 × H2O, 0.612 g

KH2PO4 and 0.2 g KCl per litre DDW, pH 7.4). Peptides were diluted in PBS to 100 µL and

mixed with 100 µL of 4% v/v RBCs suspension to final concentrations ranging from 320 to 5

µM in 96-well polystyrene microtiter plates (Nunc). PBS and 0.1 % Triton X-100 were used as

negative and positive lysis controls, respectively. The plate was incubated at 37 oC for 1 h, and

unlysed RBCs were removed by centrifugation at 1000 × g on a Beckman Model TJ-6

microplate centrifuge for 5 min. 100 µL of the supernatant aliquots were transferred to new

microplates, and the release of hemoglobin was monitored at A540 on a Genesys 5 microplate

autoreader Spectrophotometer. The percent hemolysis at each peptide concentration was

measured in duplicate according to the following equation:

where Aexp is the experimental A540 measurement, APBS is the negative control where only PBS

buffer was added to the RBCs, and A100% is the positive control where 0.1% Triton X-100 was

used to cause lysis of 100% RBCs present. The experiments were performed in triplicates.

56


3.3.1 Helix Induction of CAPs in SDS Micelles

The TM Finder program (Deber et al. 2001) predicts that the hydrophobic core segments of the

peptides should adopt an -helical secondary structure in membrane mimetic environments.

Both the 6K- peptides and their derived 3K-3K partners displayed ‘random coil’ structures in

aqueous buffer (Fig. 3-2, dashed lines). In the membrane-mimetic environment of SDS micelles,

the CAPs all underwent an α-helical conformational transition, signified by the minima of their

CD spectra at 208 nm and 222 nm (Fig. 3-2, solid lines). This indicates that all four peptides in

principle insert into the bacterial membranes and adopt an α-helical secondary structure. There

was no significant difference between the induced helicity of the 6K- peptides vs. their 3K-3K

analogs (Fig. 3-2 A and B).

57

Figure 3-2. Circular dichroism spectra of CAPs in aqueous solution and SDS micelles. The

spectra were measured for 20 μM of each CAP in 10 mM Tris-HCl, 10 mM NaCl, pH 7.0, in the

presence (solid lines) and absence (dashed lines) of 10 mM SDS. The curves are based on

triplicate measurements with buffer background subtracted. Adapted from (Yin et al. 2012).

3.3.2 CAPs Run as Dimers on SDS-PAGE

The sequences of the designed peptides containing at least one pair of “small” residues separated

by three residues (AxxxA motifs) are known to promote helix-helix dimerization in

transmembrane segments (Lear et al. 2004; Schneider et al. 2004). The peptide core sequence

F17 contains three AxxxA motifs (two AAFAA sequences and a central AAWAA sequence),

and the F17-4L sequence retains the central motif (ALWLA). Consistent with our previous

findings (Glukhov et al. 2005; Glukhov et al. 2008), the MWexp/MWtheor values for both 6K-F17

and 6K-F17-4L are 2.4 (Fig. 3-3A), indicating that these two CAPs form SDS-resistant dimers

on SDS-PAGE gels, even at the low loading levels used in silver stain analysis. The peptides

58

3K-F17-3K and 3K-F17-4L-3K migrate with MWexp/MWtheor ratios of 2.0 and 2.1, respectively,

also indicative of dimer formation. In addition, peptides with a greater hydrophobicity are

known to run slower on SDS-PAGE due to increased detergent binding (Rath et al. 2009); thus,

the 6K-F17-4L peptide should be migrating significantly more slowly than the 6K-F17 peptide

regardless of its greater molecular weight, yet its band position is virtually identical. Given that

all four peptides are dimeric (Fig. 3-3A), this finding may be explicable by the fact that the Leu

residues in 6K-F17-4L largely line the peptide-peptide dimeric interface, thus exposing mainly

Ala rather than Leu residues to detergent – as would be the case for the 6K-F17 peptide as well.

The same analysis holds for the 3K-F17-3K vs. 3K-F17-4L-3K – which also display comparable

migration positions. These findings allow us to choose possible representative CAP dimer

space-filling models from CHI clusters, as shown in Fig. 3-3B. In CAPs where Ala is not

replaced by Leu (e.g. 6K-F17 and 3K-F17-3K), the ‘AxxxA’ motif is expected to be primarily

involved in the helix-helix packing pocket of the CAP dimer pairs (Glukhov et al. 2005). In the

F17-4L CAPs, Leu residues become participants in the van der Waals interface that stabilizes the

peptide dimer. This effect may be further driven by the hydrophobic effect when the peptides are

first solubilized in aqueous media. Dimers of 6K-F17 and 3K-F17-3K show discernibly more

‘space’ between molecules, further suggesting that the Leu residues can effectively ‘fill’ the van

der Waals packing interface.

59

Figure 3-3. (A) SDS -PAGE (silver stain) analysis and (B) representative structural models

of CAP antiparallel dimers. (A) MWexp/MWtheor is the ratio of experimentally determined to

actual molecular weight of each CAP, where a value of ~2 corresponds to dimer. (B) Lys

residues are rendered in blue; core hydrophobic residues are shown in green. The packing

interfaces of 6K-F17 and 3K-F17-3K are highlighted by two Ala residues in the motif

‘AAWAA’ (rendered in gold), whereas 3K-F17-4L-3K and 6K-F17-4L have several Leu

residues embedded in the hydrophobic binding pocket (rendered in orange). Adapted from (Yin

et al. 2012).

3.3.3 CAP Interactions with Model Bacterial Membranes

The core segment hydrophobicity of CAPs is a key factor that affects bacterial membrane

insertion ability and antimicrobial activity (Glukhov et al. 2005; Glukhov et al. 2008). To better

understand how peptide hydrophobicity influences their membrane-disruptive ability, we have

compared the interactions of the two CAPs with the same positive charges but contrasting core

hydrophobicities – 6K-F17 with a ‘low’ core segment hydrophobicity (1.48) and 6K-F17-4L

with a ‘high’ core hydrophobicity (3.14) (Table 3-1) – in a bacterial membrane model using a

combination of atomic force microscopy (AFM) and attenuated total reflection-Fourier transform

infrared spectroscopy (ATR-FTIR) techniques (Yin et al. 2011). In situ AFM allows us to

directly image the impact of peptide-membrane interactions on membrane stability and structure,

while FTIR detects the accompanying structural changes of peptides (Van Mau et al. 1999;

60

Verity et al. 2009). The bacterial lipid bilayer model mixture is comprised of 3:1 POPE/DOPG,

which resembles the PE/PG ratio found in the inner membrane of Gram-positive and Gram-

negative bacteria (van der Does et al. 2000; Oreopoulos et al. 2009). The addition of the CAPs

to the membrane bilayers led to an immediate remodeling or restructuring of the surfaces. When

each peptide at concentrations lower than or equal to their reported MIC values was added to

bacterial membrane lipid bilayers comprised of 3:1 POPE/DOPG, there was a 1-2 nm difference

in topological heights (Fig. 3-4 b,e), indicating that the peptides are binding to the membrane

surface initially. As more peptide was added, there were concave regions greater in number and

size appearing on the membrane (Fig. 3-4 c,f), indicating peptide-induced defects in the

membrane.

Figure 3-4. AFM topography images of 6k-f17 (a-c) and 6K-F17-4L8,11,13,16 (d-f) at various

concentrations in bacterial membrane lipid mimics. The color indicates the height of the

sample, ranging from 0 (lightest brown) to 20nm (darkest brown). White stars represent the

same point of the membrane across the scans. Red and green arrows indicate the difference in

heights, as shown on the spectra below the images. Adapted from (Yin et al. 2011).

61

It is important to note that such CAP-induced membrane disruption is not only affected by the

concentration of CAP added, but also can be time-dependent. As AFM reveals the nature of the

membrane destabilization, FTIR spectra are continuously acquired to detect any secondary

structural changes of the CAPs in bacterial membrane models over time (Yin et al. 2012). 6K-

F17 adopted largely -helical structure (indicated by the amide I band at ~1650 cm-1

) over the

corresponding time course (Fig. 3-5 B), and the overall spectral intensity increases over time as

additional amounts of CAPs penetrate the lipids. 6K-F17-4L, on the other hand, initially induced

an -helical conformation in the bacterial membrane lipids, and eventually exhibited a time-

dependent increase of -stranded aggregation (indicated by the band at ~1625 cm-1

) with

concomitant relatively increased ratio to -helical conformation (70-min curve in Fig. 3-5 D).

This phenomenon is likely caused by the charge neutralization effect as the peptides bind to the

membranes, and the resulting dehydrated environment facilitates the formation of β-strand

aggregates of CAPs with a high hydrophobicity (Dzwolak et al. 2004; Mukherjee et al. 2007).

The result indicates that high core segmental hydrophobicity can lead to an increased potential to

peptide aggregation at the membrane surface, thus limiting the concentration of peptide actually

impacting on the bacterial membrane, and consequently reducing antimicrobial activity (see

Section 3.3.5).

62

Figure 3-5. Effects of synthetic CAPs on topography images obtained from AFM

experiments performed in tandem with ATR-FTIR measurements in a bacterial model

lipid bilayer (3:1 POPE/DOPG). (A, B) 6K-F17; (C, D) 6K-F17-4L. AFM scale bar is 3 µm,

and the corresponding section analysis for each CAP is labeled below the images; height

differences are indicated between the red or green pairs of arrows. ATR-FTIR spectra for the

amide I peaks at ~1650 nm-1

and 1625 nm-1

represent α-helical (Vie et al. 2000), and β-strand

conformations (Verity et al. 2009), respectively. The overall spectral intensity increases over

time as additional amounts of CAPs penetrate the lipids. Adapted from (Yin et al. 2012).

3.3.4 Positive Charges on Both CAP Termini Minimize Aggregation in Bacterial Membrane-Mimetic Models

The peptide 6K-F17-4L discussed above is likely self-oligomerized and aggregated in an

antiparallel manner, because the grouping of the six Lys positive charges at the N-terminus

mitigates against parallel association. Therefore, placement of three positive charges on each of

the N- and C-termini – while an identical core sequence is maintained – might be expected to

produce a mix of parallel and antiparallel dimers, but likely with reduced higher-level

63

aggregation in membranes due to charge repulsion. To address this hypothesis, we designed

CAPs 3K-F17-3K and 3K-F17-4L-3K as derivatives of the parent peptides 6K-F17 and 6K-F17-

4L, respectively (Table 3-1). Each 3K-3K peptide now has 3 Lys residues each at the N- and C-

termini, with an identical core segment as the 6K peptides. In contrast to 6K-F17-4L, the

interactions of 3K-F17-3K and 3K-F17-4L-3K with the bacterial membrane mimic were less

well-defined, appearing to result in a reduction in the lateral stability of the membrane itself,

rather than outright restructuring (Fig. 3-6 A, C). This was seen in the emergence of sunken

regions and the ability of the AFM tip to induce localized distortions (Fig. 3-6 C). Remarkably,

association of these two CAPs with the bacterial membrane did not result in an aggregated -

type structure, as indicated by the predominant -helical (~1650 cm-1

) (Vie et al. 2000) and the

absence of -strand (~1625 cm-1

) (Verity et al. 2009) bands in amide I region of their FTIR

spectra in bacterial membranes (Fig. 3-6 B, D).

64

Figure 3-6. Effects of CAPs on topography images obtained from AFM experiments

performed in tandem with ATR-FTIR measurements in a bacterial model lipid bilayer (3:1

POPE/DOPG). (A, B) 3K-F17-3K; (C, D) 3K-F17-4L-3K. The AFM scale bar is 3 µm, and

the corresponding section analysis for each CAP is labeled below the images; height differences

are indicated between the red or green pairs of arrows. The amide I peak at ~1650 nm-1

represents α-helical conformation (Vie et al. 2000). The spectral intensity increases over time as

additional amounts of CAPs penetrate the lipids. Adapted from (Yin et al. 2012).

3.3.5 Antimicrobial Activity

The antimicrobial activities of the four novel CAPs in terms of MIC (minimium inhibitory

concentration) values were measured against Pseudomonas aeruginosa PAO1 strain (Table 3-2),

from which it was determined that all four CAPs displayed significant antimicrobial activity. 3K-

F17-4L-3K showed an improved antimicrobial efficacy (8 µM) versus 6K-F17-4L (16 µM),

while 3K-F17-3K (32 µM) displayed reduced activity versus 6K-F17 (4 µM). It appears that

65

charge distribution does not dominate the impact on activity, since it only improves the

antimicrobial activity for the CAP with high hydrophobicity (3K-F17-4L-3K), and reduces the

MIC of 3K-F17-3K vs. 6K-F17. This situation can be explained by the fact that CAPs still need

to self-dimerize to function upon binding to the bacterial membrane, yet separated charges are

seen to mitigate against the parallel or antiparallel aggregation of the 3K-3K peptides, ostensibly

via repulsions of the positive changes at the peptide termini.

Table 3-2. Antimicrobial activities of designed peptides.

Peptide MICa (µM)

3K-F17-3K 32

6K-F17 4

3K-F17-4L-3K 8

6K-F17-4L 16

a MIC values obtained here are tested against P. aeruginosa PAO1 strain using a modified assay

prototol (Yin et al. 2012); hence, the values are not identical to those previously published

(Glukhov et al. 2008).

3.3.6 Interaction of Peptides and Mammalian Membrane Lipids

While interactions with bacterial membranes are of primary interest, it is essential to establish

whether a given CAP interacts with a zwitterionic (neutral) mammalian-type membrane,

particularly because peptide-mediated hemolysis of host cells cannot be tolerated for a useful

therapeutic. To examine the effects of the present CAPs on mammalian membranes, we

performed in tandem AFM and ATR-FTIR experiments on the four designed peptides with a

mammalian membrane model (1:1:1 DOPC/DSPC/cholesterol) that mimicks the outer leaflet of

eukaryotic cell membranes (Florin-Christensen et al. 2001; Oreopoulos et al. 2009). Before

peptide addition, fusion of this lipid mixture to mica resulted in DSPC/cholesterol-rich lipid-

66

ordered domains surrounded by a DOPC-rich liquid-disordered phase, distinguishable by an ~ 2

nm height difference (Figs. 3-7 A, C and Fig. 3-8 A, C, left panels). We ascribe the ~ 15-20 nm

taller features seen as blobs in the control image to unfused liposomes bound with the bilayer

surface. 6K-F17 simply does not interact with mammalian membranes at 8 µM – as noted by the

absence of membrane defects (Fig. 3-7 A) and the absence of an FTIR signal (Fig. 3-7 B),

indicating no membrane penetration. In contrast, 6K-F17-4L is apparently of sufficient core

hydrophobicity to use this property (rather than electrostatic binding) as a route to partition into –

and produce defects in – mammalian membranes (Fig. 3-7 C), where it produces a mixture of α-

helical and β-strand peaks in FTIR spectra (Fig. 3-7 D). 3K-F17-3K and 3K-F17-4L-3K also

showed comparable effects in mammalian membranes: 3K-F17-3K produced no significant

membrane destabilization (Fig. 3-8 A) and very minimal structures in the zwitterionic

mammalian membrane model (Fig. 3-8 B), whereas 3K-F17-4L-3K adopted significant helical

structure detected by FTIR (Fig. 3-8 D), and induced multiple small 'holes' ~3.6 nm deep in the

bilayer (Fig. 3-8 C). These results revealed that only CAPs 6K-F17-4L and 3K-F17-4L-3K

destabilized mammalian membrane bilayers upon addition, which suggests that CAPs with a

sufficiently high level of hydrophobicity would likely partition from the bulk water phase for

insertion into zwitterionic bilayers via hydrophobic solvation, supporting our previous findings

(Glukhov et al. 2008). It is interesting to note that 3K-F17-4L-3K induced tiny "holes" rather

than larger defects (as in the case of 6K-F17-4L) in zwitterionic bilayers (Fig. 3-8 C), suggesting

that altering charge distribution of the CAPs likely results in a different mechanism of interaction

with the mammalian membranes and a lower level of hemolysis (see Section 3.3.7).

67


experiments performed in tandem with ATR-FTIR measurements in a mammalian model

lipid bilayer (1:1:1 DOPC/DSPC/cholesterol). (A, B) 6K-F17; and (C, D) 6K-F17-4L. The

concentrations of each CAP addition in both AFM and IR experiments were 8 µM.

Corresponding section analysis for each CAP is labeled below the AFM images; height

differences are indicated between the arrows. The peptide 6K-F17 induces no membrane defects

(A) and displays virtually no entry into the bilayer (B), while 6K-F17-4L promotes significant

interaction with the mammalian membrane (C) and penetrates the membrane to produce a

mixture of α-helical and β-strand FTIR signals (~1650 cm-1

and ~1620 cm-1

, respectively) (D).

The spectral intensity increases over time as additional amounts of CAPs penetrate the lipids.

The 6K-F17 tested here is the D-isomer; the L-enantiomer gives comparable results (data not

shown). Adapted from (Yin et al. 2012).

68


experiments performed in tandem with ATR-FTIR measurements in a mammalian model

lipid bilayer (1:1:1 DOPC/DSPC/cholesterol). (A, B) 3K-F17-3K; and (C, D) 3K-F17-4L-3K.

The concentrations of each CAP addition in both AFM and IR experiments were 8 µM.

Corresponding section analysis for each CAP is labeled below the AFM images; height

differences are indicated between the arrows. 3K-F17-3K display very minimal FTIR signal into

the bilayer (B); and 3K-F17-4L-3K significantly induces helical (~1650 cm-1

) conformation (D).

The spectral intensity increases over time as additional amounts of CAPs penetrate the lipids.

Adapted from (Yin et al. 2012).

3.3.7 Hemolytic Activity

The CAP toxicity to mammalian cells is frequently expressed as hemolytic activity (Fig. 3-9).

The hemolytic activities of the designed CAPs were measured against human RBCs at

concentrations ranging from 320 to 10 µM (Fig. 3-10). Peptides with ‘low’ hydrophobicity,

namely 3K-F17-3K and 6K-F17, displayed no hemolysis even at high concentrations (320 µM

69

and 160 µM, respectively). In striking contrast, peptides with ‘high’ hydrophobicity (3K-F17-

4L-3K and 6K-F17-4L) showed hemolytic activities at every concentration tested. These results

support the notion that CAPs with a greater hydrophobicity are prone to inducing hemolysis

against human erythrocytes (Glukhov et al. 2008). It is interesting to note that the 6K-F17

peptide did display a detectable level of hemolysis at the highest concentration tested (2.7 ±

1.2% at 320 M), while 3K-F17-3K displayed no hemolysis up to 320 M. The CAP 3K-F17-

4L-3K also induced less hemolysis than the 6K-F17-4L peptides, yet only at low concentrations.

This may be because positive residues evenly distributed at both ends of the peptides leading to

charge repulsion, which outcompetes with the packing tendency due to hydrophobic effect, and

consequently prevents the peptides from self-aggregating and inserting into the zwitterionic

mammalian membranes. However, as the peptide concentration increases, the hemolysis

percentages induced in RBCs by the 4L peptides (Fig. 3-10) level off near 40% for the 6K-F17-

4L peptide, and near 80% for the 3K-F17-4L-3K peptides. This indicates that in each case, the

limiting aqueous solubility of the peptide has been reached, and that any further additions of

peptide result in precipitation such that no further activity will ensue.

Figure 3-9. A typical hemolysis assay. CAPs (labelled at the left) ranging from 320 to 5 μM

(labelled at the top) were tested with 4% v/v human RBCs. PBS and 0.1 % Triton X-100 were

used as negative (-) and positive (+) lysis controls, respectively. Red colour indicates hemolysis

of RBCs.

70

Figure 3-10. Hemolytic Activities of the designed CAPs. The % hemolysis (± error) was

tested at peptide concentrations ranging from 320 to 5 µM with 4% v/v RBCs. Values averaged

from at least three separate experiments are listed below the bar graph. Adapted from (Yin et al.

2012).

71

3.4 SUMMARY

The data suggest that in the bacterial membrane model, peptides with higher core hydrophobicity

have stronger self-association and aggregation tendency than those with lower hydrophobicity.

On the other hand, when positive charge is distributed equally at both termini, peptide

aggregation is eliminated. The results further indicate that the separated charge distribution of

CAPs - which otherwise retain identical hydrophobic cores with AxxxA motif(s) - does not

disrupt their helix-forming and dimerization ability in hydrophobic environments – which may

be the crucial properties for bioactivity in the 6K-F17 series of novel CAPs (Glukhov et al. 2005;

Glukhov et al. 2008) – and accordingly, that primary sequence motifs remain a determinant of

oligomeric status. Nevertheless, once dimers are established, the inherent charge repulsion

extant at both termini vs. the 6-Lys N-terminus, mitigates against further oligomerization. The

findings also reveal that a CAP with increased hydrophobicity enters zwitterionic membranes

and causes hemolytic effects. Separate distribution of positive charges reduces the hemotoxicity

of peptides with the same core hydrophobicity at low concentration, but does not have

favourable effect at higher concentrations.

Given that effective antimicrobial activity and minimal hemotoxicity of CAPs do not involve

only one factor, but rather require a good balance among (i) peptide helicity, (ii) optimal

hydrophobicity of the core segment, (iii) positive charges and their distribution, (iv) dimerization

and/or oligomerization ability in the membrane, and (v) freedom from aggregation, the overall

findings clarify preferable routes to optimization of sequences most likely to be of value toward

devising therapeutic strategies.

72

Chapter 4 Peptide-Alginate Interactions

Effects of Amino Acid Composition, Peptide Hydrophobicity, and Charge Distribution on

the Interactions of Designed CAPs and Alginate

4

73

4.1 INTRODUCTION

The designed novel CAPs described in this Thesis have displayed significant antimicrobial

activities against the planktonic forms of bacteria, including the CF lung infectious pathogen

Pseudomonas aeruginosa (Chapters 2 and 3). Yet despite the highly favourable properties of the

CAPs, once the bacteria attach and colonize onto the body tissue, they often form biofilms that

are characterized by the overproduction of exopolysaccharides. The prototypic anionic

polysaccharide alginate is a major and extensively studied type of exopolysaccharide found in

mucoid strains of P. aeruginosa. Alginate, consisting of two monosaccharide building blocks:

the α-L-guluronate and the β-D-mannuronate (Gacesa 1998), reduces bacterial killing by

conferring tolerance to conventional antibiotics by diffusion limitation and through binding of

positively charged drugs via its negatively-charged components (Costerton et al. 1999; Gilbert et

al. 2002). However, electrostatic attraction is not the only force involved in peptide-alginate

interactions. Our group has previously shown that once biofilm alginate binds to the membrane-

active CAPs upon charge neutralization, hydrophobic interactions occur between the π-electrons

of aromatic side chains of the peptides and the hypothesized C-H hydrophobic domains present

in hexopyranoses of alginate (Chan et al. 2004). Studies further indicate that alginate acts as

what we have termed an ‘auxiliary membrane’ that competes with the anionic bacterial

membrane, and traps the peptides by promoting peptide-peptide oligomerization or forming

peptide-alginate complexes (Chan et al. 2005; Kuo et al. 2007).

It is thus crucial to design CAPs that maintain a high antimicrobial efficacy at the bacterial

membrane, but also are able to efficiently penetrate the biofilm exopolysaccharide barrier. In

order to gain further insights into how peptide design can be employed to elicit the properties

required to evade binding by alginate in bacterial biofilms, we have investigated the interactions

between the newly designed 17-mer novel CAPs (Table 2-1) – varying in core segment

hydrophobicity and amino acid compositions – and alginate, using various biophysical

approaches. In this Chapter, specific questions have been addressed: (1) what is the structural

74

basis of the peptide-alginate interaction? (2) What factors in peptide design play a role in

alginate-binding? (3) Does the alginate-binding ability affect how CAPs diffuse into the alginate

matrix?


4.2.1 Peptide Synthesis

Peptide synthesis and purification were performed as described in Chapter 2. Amino acid

sequences are listed in Table 2-1 and Table 3-1.

4.2.2 Purification of Alginate

Alginate purification was performed as described in Chapter 2.


Circular dichroism (CD) spectra were recorded on a Jasco-810 spectropolarimeter using a 1-mm

path-length quartz cell at 25oC. 20 μM of each peptide in the presence of alginate ranging from 0

mg/mL to 0.6 mg/mL, and in 10 μM of SDS in 1.0 mM MES buffer at pH 5.5 was measured on

an average of 3 scans with buffer background subtracted.

75

4.2.4 Tryptophan Fluorescence

Tryptophan fluorescence emission spectra of the peptides were recorded on a Hitachi F-400

fluorescence spectrophotometer at an excitation wavelength of 280 nm and emission

wavelengths ranging from 300 to 400 nm. Fluorescence measurements were performed with 4

μM of peptides in 20 mM Tris buffer at pH 7.0 with or without 0.02 mg/mL of alginate.

4.2.5 Alginate-Peptide Binding Affinity Assay

This assay (as illustrated in Fig. 4-1) is modified to quantitate the binding affinity of the model

CAPs with alginate (Chan et al. 2005). Various concentrations of alginate were allowed to

incubate with 30 μg of peptides in 20 mM Tris-HCl at pH 7.4 overnight to reach equilibrium for

binding affinity. The solutions were each centrifuged through a filter (100 kDa MWCO) to

separate the free peptides (PF) from the alginate-bound peptides (PB). The unbound peptide

solutions were lyophilized and quantified using micro-BCA protein assay. A control containing

the same amount of peptide with no alginate present was used to measure the total amount of

peptide (PT). The percentage bound, calculated from PB/PT, is plotted against the concentration

of alginate ([Ao]), and the binding curves were analyzed using the following equation:

where Kd is the dissociation constant, representing the amount of alginate that is required to bind

50% of the total amount of peptide present. [Ao], the alginate concentration, was varied between

0 and 0.06 mg/mL. All binding assays were repeated at least three times and plotted using the

Igor Pro graph program.

76

Figure 4-1. Schematic illustration of the alginate affinity binding assay. (1) Varying

concentrations of alginate (green) were incubated in peptide solutions (red) overnight. (2) Each

sample of the unbound peptides was separated from the bound peptides by centrifugation, (3)

lyophilyzed, and (4) quantified using micro-BCA protein assay and analyzed according to the

equation given in section 4.2.5.

4.2.6 Fluorophore Labeling

Fluorophore labeling of peptides was performed by reacting 5-(and-6-)-

carboxytetramethylrhodamine(5(6)-TAMRA) succinimidyl ester mixed isomers with peptide

resins in 1 mL DMF overnight before cleavage and purification. The concentration of the

TAMRA-labelled peptides was determined by UV absorbance (TAMRA, ε555 = 65,000 M-1

cm-1

)

(Reshetnyak et al. 2007).

77

4.2.7 Antimicrobial Activity Assay – Minimal Inhibitory Concentration

The minimal inhibitory concentration assay was performed as described in Chapter 2 to compare

the antimicrobial activities between the TAMRA-labelled peptides and the unlabelled peptides.

The A600 readings of bacteria growth treated with TAMRA-labelled peptides were each

subtracted from controls containing the same amount of TAMRA-labelled peptides to avoid the

overlapping of absorbance obtained from the TAMRA-tags.

4.2.8 Statistical Analysis

95% confidence interval for the correlation between peptide hydrophobicity and their blue-shifts

in alginate was predicted using program GraphPad Prism. Two-sample t-test was performed to

compare the CD spectra and MIC curves between TAMRA-labelled and unlabelled peptides.

4.2.9 Penetration of Peptides into Alginate Beads – Laser Scanning Confocal Microscopy

As illustrated in Fig. 4-2, alginate beads (0.5 mm in diameter) were made by the “dripping

method” (Fundueanu et al. 1999) where droplets of a 10 mg/ml solution of purified alginate were

added into a solution containing 1 M CaCl2 through a 25 1/2 G needle. Following dialysis

performed to remove excess CaCl2, 20 μL of 8 μM of TAMRA-labeled peptides were allowed to

incubate with the alginate beads for 5 min, 1 hr, 2 hr, 3 hr, 4 hr, 5 hr, 6 hr, 18 hr, and 24 hr.

Unbound peptides were removed by washing with H2O. Examination of the interaction of

TAMRA-labeled peptides with alginate beads was performed using a LSM 510 confocal laser

scanning microscopy (Zeiss). The images were recorded with an excitation wavelength of 543

78

nm and an emission wavelength of 635 nm for TAMRA-labeled peptides at the mid-cross-

section of the beads using the LSM 510 positioning software.

Figure 4-2. Schematic illustration of the assay to measure the penetration of peptides into

alginate beads. Alginate beads were formed by dripping alginate into a solution containing 1 M

CaCl2, and incubated in 8 µM TAMRA-peptide solution for various periods of time, then

visualized using laser scanning confocal microscopy.


4.3.1 Titration of Peptides with Alginate

The peptides initially displayed with a randomly coiled structure (blue line in Fig. 4-3) in

aqueous buffer. α-Helical conformations were induced when they were mixed with 0.075

mg/mL of alginate, as indicated by the two minima at 208 nm and 222 nm in the CD spectra

(black line in Fig. 4-3). As more alginate was titrated into the peptide solution, visible

precipitates formed, accompanied by the appearance of a β-sheet like CD spectra (minimum at

79

215 nm) (orange line in Fig. 4-3), that is presumably due to severe peptide aggregation

(Arutyunyan et al. 2001). The results suggest that there is a strong interaction between the CAPs

and alginate that leads to the formation of insoluble peptide-alginate complexes, and also initially

indicate that the peptide would remain α-helical only when the right proportion of alginate is

added, which, in turn, may be strongly impacted by the opposite charge ratio of the electrostatic

attraction between the cationic peptide and the anionic alginate.

Figure 4-3. Circular dichroism spectra of the representative peptide 6K-F17-4L8,11,13,16 (20

μM) titrated with increments in alginate concentration (0 to 0.6 mg/mL). The solutions are

buffered at pH 5.5 in 1 mM MES. The spectra are based on triplicate measurements with buffer

background subtracted.

In any case, the structural transition of any of the designed peptides we tested from α-helical to

aggregated β-sheet conformation in the presence of alginate occurred within 30 min of

incubation (data not shown), regardless of the concentrations of alginate used. This observation

suggests that the equilibrium of peptide-alginate binding is always favorable towards the

formation of insoluble peptide-alginate complexes, and that the α-helical conformation of

peptides might only be an intermediate state.

80

4.3.2 Tryptophan Fluorescence Blue-Shifts of CAPs in Alginate

In the design of the antimicrobial peptides, a Trp residue was included in the hydrophobic core,

which allowed us to probe for changes in the local environment of the peptides through

examining the blue shifts in Trp fluorescence emission maxima. The Trp fluorescence emission

maxima for peptides in aqueous buffer were all approximately 350 nm, as previously reported

for a Trp residue in an aqueous environment (Burstein et al. 1973). When 0.02 mg/mL of

alginate was added to each of the peptide solutions, alginate-induced blue shifts were observed

(Fig. 4-4). This effect arises when the indole ring of the tryptophan residues in the peptide

interact with the pyranosol ring of the alginate; water molecules are excluded from this

hydrophobic interaction, and as a result, blue shifts occur in the emission maxima towards the

lower wavelength end (Vazquez-Ibar et al. 2003). This observation indicates that the peptides

are able to hydrophobically interact with the hydrophobic compartment of alginate upon charge

neutralization, supporting our previous findings (Chan et al. 2004). It should be expected that

there would be increases in the fluorescence intensity corresponding to the blue shifts due to the

Trp exposure to a less hydrophilic environment; but instead, the fluorescence intensities of the

alginate-induced blue-shifts decreased. This result is due to the precipitation that occurred from

the formation of peptide-alginate complexes, which leads to the loss of solubilized peptides and

accordingly decreased peak intensities.

81

Figure 4-4. Normalized Trp fluorescence emission maxima of the peptides (Table 4-1) in

aqueous solution (solid lines) and in alginate (dotted lines). The peptide sequences are listed

in Table 1. The peptide concentration is 4 μM in 20 mM Tris-HCl at pH 7.0, and the alginate

concentration is 0.02 mg/mL. The curves are based on triplicate measurements each on an

average of three scans with buffer background subtracted.

82

Table 4-1. Core segment hydrophobicity of the peptides and alginate-induced blue-shifts in

tryptophan fluorescence emission maxima (Δλ, nm).

Peptidesa Core Segment Hydrophobicity

b

Alg-induced blue shiftc

(Δλ, nm)

D-6k-a17 0.6 5

D-6k-a17-f9 1.04 8

D-6k-f17 1.48 9

6K-F17-1L11 1.89 13

6K-F17-2L11,13 2.31 10

6K-F17-2L10,14 2.31 17

D-6k-f17-2l16,17 2.31 14

6K-F17-2L8,16 2.31 17

6K-F17-2L7,8 2.31 15

6K-F17-3L8,11,13 2.73 9

6K-F17-3L11,13,16 2.73 11

6K-F17-4L8,11,13,16 3.14 23

a Peptide sequences are listed in Table 2-1 (Chapter 2).

b Core segment hydrophobicity of each peptide is calculated according to the Liu-Deber scale

(Liu et al. 1998a).

c The blue-shift is the shift in Trp emission maximum of a given peptide upon addition of

alginate, given as Δλmax = λmax (aqueous) – λmax (alginate).

83

The alginate-induced blue-shifts of the CAPs (Table 4-1) were correlated with their core segment

hydrophobicities (Fig. 4-5 A). However, the correlation had an R2 of 0.496, which did not

represent a strong fit. The bottom three data points (6K-F17-L11,13, 6K-F17-3L8,11,13, and 6K-

F17-3L11,13,16) lie outside of the 99% confidence intervals of the fit (Fig. 4-5, dashed lines),

indicating that they might be ‘outliers’. After excluding these three points (Fig. 4-5 B), a much

stronger positive linear correlation was obtained (R2 = 0.952), which suggests that the overall

core segment hydrophobicity of the peptides strongly affects their hydrophobic interaction and

binding with alginate. We observed that the three ‘outlier’ peptides, which have smaller

alginate-induced blue-shifts than predicted, all contain Leu residues at positions 11 and 13,

adjacent to both sides the Trp residue in their sequences. While the peptides exhibit an overall β-

strand conformation when tightly binding to alginate (as shown in the CD spectra, Fig. 4-3), the

two Leu residues create a local hydrophobic compartment that lie opposite to the Trp residue

along the peptide backbone (Fig. 4-6). This double-Leu compartment may be more favourable at

interacting with the hypothesized sugar C-H bonds compartment of alginate hydrophobically,

and likely competes with the stacking between alginate and the Trp aromatic ring.

Consequently, the Trp residues were more exposed to the aqueous environment, hence resulting

in reduced blue-shifts. It was interesting to note that even though 6K-F17-4L8,11,13,16 also has

Leu residues at positions 11 and 13, its blue-shift was not reduced as the other three peptides.

This may be because that the Trp residue of 6K-F17-4L is involved in some peptide-peptide

antiparallel packing (see section 4.3.4 for a further discussion), and as a result, Trp still ended up

being buried in a hydrophobic environment.

84

Figure 4-5. The correlation between the alginate-induced blue shift (nm) and the core

segment hydrophobicity of the peptides (Table 4-1). The R2 value of the line of best fit (solid

line) is shown. The dashed lines represent the 99% confidence interval. (A) the correlation of

all the data points; and (B) the correlation excluding the bottom three points (circled in red).

85

Figure 4-6. Structural model of the peptide 6K-F17-2L11,13 in a β-strand conformation. The

two Leu residues at positions 11 and 13 are rendered in green, the Trp residue (position 12) is

shown in orange, and the remainder of the residues in blue.

4.3.3 Alginate-Binding Affinity Assay

While CD spectra and Trp fluorescence data reveal that the strong interaction between our

designed CAPs and alginate leads to the formation of insoluble peptide-alginate complexes, it

may be suggested that the binding of CAPs to alginate is the fundamental cause of the reduced

efficacy of the CAPs against mucoid forms of bacteria. We have quantified and compared the

alginate binding abilities of designed CAPs either with different hydrophobicities or the same

hydrophobicity but different compositions (Table 2-1) using a binding affinity assay (Chan et al.

2005). This method allows us to determine whether there exist any motifs of the peptides that

specifically favour interaction with alginate, and aids in identifying the properties/features of

CAP design crucial for alginate binding and effective penetration. The results of the assay have

shown that the alginate-binding patterns vary for different peptides; for example, 6K-F17-2L8,16

peptide has a lower alginate-binding ability than the 6K-F17-3L11,13,16, which results in a greater

Kd value (Fig. 4-7). As hydrophobicity of the peptide increases, no obvious trend of Kd’s is

observed (Fig. 4-8). This suggests that the binding ability of the peptides is affected not only by

the hydrophobicity, but also influenced by its residue-based composition and distribution.

Interestingly, among all the CAPs studied, two peptides exhibited relatively largest Kd’s,

86

meaning that their structures allowed them to have the lowest binding affinities to alginate (Fig.

4-8): peptide 6K-F17-2L8,16 has a much larger Kd than the peptides with the same hydrophobicity

(all with 2 Leu-to-Ala substitutions); in addition, peptide 6K-F17-4L8,11,13,16 would be predicted

to bind tighter with alginate due to its greatest hydrophobic interactions with alginate, but it

actually has the least alginate-binding ability. These effects may be explained by the fact that

these peptides have a binding pocket with a large(Leu)-small(Ala)-large(Trp)-small(Ala)-

large(Leu) residue pattern that leads to tight antiparallel self-oligomerization/aggregation, which

competes with the heterogeneous alginate binding (Fig. 4-9).

Figure 4-7. The BCA analysis of the percentage of peptides bound to alginate separated

from the free peptides 6K-F17-3L11,13,16 (red) and 6K-F17-2L8,16 (black) as a function of

alginate concentration. Total peptide used before incubating with alginate varying from 0 to

0.06 mg/mL was 30 μg, buffered at pH 7.0 in 20 mM Tris-HCl. The percentage bound is

calculated from alginate bound peptide (subtracting free peptide determined from total peptide)

over total peptide. The points are based on triplicate measurements.

87

Figure 4-8. The distribution of the dissociation constant, Kd, of each of the CAPs (listed in

Table 2-1) binding to alginate. The peptides are displayed in the order of increasing core

segment hydrophobicity (left to right).

Figure 4-9. Schematic illustration of two peptides with high Kd values. 6K-F17-2L8,16 and

6K-F17-4L8,11,13,16, form antiparallel β-stranded self-oligomers/aggregates at their binding pocket

with a large(L)-small(A)-large(W)-small(A)-large(L) residue pattern, versus a peptide, 6K-F17,

that does not contain this binding pocket.

88

4.3.4 Diffusion of Peptides into Alginate Beads

To correlate the alginate-binding affinities (see Fig. 4-8) of the peptides to their actual abilities

to permeate the alginate matrix, the time-dependent localization and diffusion of fluorescently

(TAMRA-) labelled CAPs with varying alginate binding affinities into alginate beads were

investigated using confocal laser scanning microscopy. Diffusion into the beads may signal the

ability of a given peptide to evade the ‘alginate trap’ and diffuse toward the bacterial membrane.

Controls examining the secondary structures in a membrane-mimetic environment and MIC

values of TAMRA-tagged peptides have confirmed that their structural behaviour and

antimicrobial activity are both comparable to their untagged counterparts (Fig. 4-10). As shown

in Fig. 4-11, the peptides with an intermediate alginate-binding ability, such as 6k-a17-f9, and

with a great alginate-binding ability, such as 6K-F17-3L11,13,16, all gradually diffuse into the

alginate beads, and eventually manifest as largely red-coloured beads (24 hrs), whereas the

peptides with high Kd values, meaning low alginate-binding abilities, such as 6K-F17-2L8,16 and

6K-F17-4L8,11,13,16, do not diffuse into the alginate beads over time, as indicated by the outer

‘ring’ formed around the surface of the bead over the full time of incubation. This reveals that

the peptides that have low alginate-binding abilities do not diffuse into the alginate barrier easily,

and further supports the notion that these peptides may be self-oligomerizing/aggregating rather

than penetrating the beads effectively. To address this hypothesis, a peptide 3K-F17-4L-3K,

with the same hydrophobic core as the peptide 6K-F17-4L but a different charge distribution (3

Lys each at the N- and C-termini), which is supposed to be resistant to self-aggregation due to

charge repulsion (see Chapter 3), is shown to be able to diffuse into the alginate beads over time.

This indicates that peptide self-aggregation is an important factor that limits the diffusion of

peptides.

89

Figure 4-10. Helicity detected by CD (A) and the bacterial inhibition curves measured by

the MIC assay (B) of peptide 6k-a17-f9 (blue) and its TAMRA-labelled analog TAMRA-6k-

a17-f9 (red). There is no significant difference between the secondary structures and the

antimicrobial abilities of 6k-a17f9 and TAMRA-6k-a17f9.

90

Figure 4-11. Confocal laser scanning micrographs obtained of the interactions and extent

of diffusive penetration of TAMRA-labelled CAPs into alginate beads. Alginate beads are

incubated with TAMRA-labeled peptide solutions for varying time periods, and washed before

the images are taken (excitation wavelength at 543 nm, emission at 635 nm) at the mid-cross-

section of the alginate beads using LSM 510 imaging software. The results shown are

representative images of at least 3 individual beads at each time point with each peptide.

91

4.4 SUMMARY

The 6K series of CAPs form insoluble complexes in alginate, which appears in CD spectra as a

β-sheet like secondary conformation. After the initial electrostatic binding of the cationic

peptides to the anionic alginate, van der Waals packing forces further contribute to the peptide-

alginate interaction. Such hydrophobic interaction is linearly proportional to the overall core

segment hydrophobicity of the peptides, yet certain sequence patterns (Leu on each side of the

Trp residue) possibly compete with the stacking of Trp π-electrons with the alginate

hexopyranosol compartment. However, the actual alginate-binding affinities of the CAPs are not

only affected by the peptide hydrophobicity level, but also by the amino acid composition.

When the β-strand dimer interface contains the pattern of large-small-large-small-large residues,

the peptides are more likely to be involved in self-aggregation rather than binding to alginate,

which results in an overall apparent low alginate-binding ability. Due to this effect, these

peptides with competing alginate-binding abilities do not diffuse into alginate beads over time,

while peptides with intermediate and great binding abilities both diffuse into the beads. This

latter result suggests that peptide self-aggregation that is promoted after the charge neutralization

effect in alginate is the principal origin of the limited diffusion into the biofilm alginate matrix.

When peptide aggregation is reduced by having positive charges distributed on both termini of

the peptides, diffusion of the peptides becomes more efficient.

92

Chapter 5 Conclusions and Implications

5

93

Microbial biofilms have become one of the most challenging problems in nature and in human

infectious diseases. For example, the chronicity of P. aeruginosa infections in CF – due to the

propensity of the organism to develop resistance via growth as biofilms during prolonged

antimicrobial therapy – has presented major therapeutic issues to CF patients. While we are

running out of therapeutic options to effectively combat biofilm-forming bacterial infections, in

the last decade, CAPs have been developed as potential alternative antibiotics. Clearly, an ideal

candidate for a CAP must rapidly diffuse into the biofilm matrix and pass through it, before it

can reach the bacterial membrane, and remain active towards bacteria without causing toxicity to

the mammalian host cells. The focus of the research in this thesis not only has thus been on the

elucidation of the interactions of CAPs with both bacterial and mammalian membranes, but also

on the molecular mechanism(s) by which the alginate polysaccharide matrix specifically

functions to confer antibiotic resistance to biofilm-embedded bacteria.

In the present work, we have established the sequence dependence of antimicrobial selectivity

and activity of de novo designed CAPs, along with their peptide-membrane, and peptide-alginate

interactions, by mainly focusing on three major contributing features of peptides:

hydrophobicity, charge distribution, and amino acid composition. Our principal findings are as

follows.

(i) CAP bioactivities

Our designed novel CAPs display great killing efficacies against multiple strains of P.

aeruginosa by quickly binding to and then physically disrupting the bacterial membranes. CAPs

require an optimal range of core hydrophobicity levels to remain active against bacterial

membranes. When the core hydrophobicity is too low, it prevents peptide insertion into the

membrane (Chapter 2), whereas when the hydrophobicity is too high, CAPs begin to cause

hemolysis in human erythrocytes (Chapter 3).

94

(ii) The balance between peptide hydrophobicity and charge distribution

For CAPs with all positive charges distributed at the N-terminus (the 6K-series) and a high core

hydrophobicity (i.e. 6K-F17-4L), as the grouped positive charges become neutralized in bacterial

membranes, the hydrophobic core of the peptides begins to partition from the water phase and

facilitates the formation of antiparallel self-oligomerization and β-strand aggregates (Chapter 3).

This observation explains why the 6K-peptides with a greater core segmental hydrophobicity can

lead to an increased potential to peptide aggregation at the membrane surface. As well, this

phenomenon limits the concentration of peptide actually impacting on the bacterial membrane,

and consequently reduces antimicrobial activity. When positive charge is distributed equally at

both termini, as in the case of the CAP 3K-F17-4L-3K, the inherent charge repulsion extant at

both termini vs. the 6-Lys N-terminus, mitigates against further oligomerization, and hence

revives the antimicrobial activity that is suffered from loss of population of active peptide

species due to aggregation. However, charge distribution does not dominate the impact on

activity, since it only improves the antimicrobial activity for the CAP with high hydrophobicity

(3K-F17-4L-3K), and reduces the MIC of the CAP with low hydrophobicity (3K-F17-3K vs. 6K-

F17). In the latter case, even though separated positive charges mitigate against peptide

aggregation, they likely interfere with the favourable self-dimerization ability of CAPs with low

core hydrophobicity via charge-charge repulsion. Therefore, it is apparent that in future peptide

design, one must balance the roles of hydrophobicity and charge distribution in CAP design to

allow the highest efficacy.

(iii) Mechanisms of action of CAPs in bacterial vs. mammalian membranes

In bacterial membranes, the positively-charged peptides adopt an α-helical conformation upon

binding to the anionic bacterial membrane via electrostatic interactions. Whether the positive

95

charges of the peptide are distributed all at the N-terminus or equally at the N- and C-termini,

and independent of the numbers of Leu residues in the sequence, the mechanisms of action

following the initial binding are similar, that is, once the amount of CAPs exceeds a

concentration threshold on the surface of the membrane, their hydrophobic core ‘sinks and dips’

into the lipid bilayers, leading to membrane destabilization and disruption (Fig. 5-1, left).

In a mammalian system, peptide hydrophobicity dominates the selectivity for insertion. CAPs

with an increased hydrophobicity begin to partition from the water phase for insertion into the

zwitterionic mammalian membranes via hydrophobic interactions, and cause hemolytic effects

(Fig. 5-1, right). Separate distribution of positive charges (3K-3K) likely prevents peptide from

higher self-oligomerization and tight packing, though only slightly reduces the hemotoxicity of

peptides with the same core hydrophobicity at low concentrations (Chapter 3).

96

Figure 5-1. Proposed mechanisms of action of CAPs in bacterial membranes vs.

mammalian membranes. CAPs (6K or 3K-3K peptides) initially exist as random coils in

water, where the hydrophobic sequences coil and interact with each other to minimize contact

with water, while Lys positive charges aid the overall solubility. Left, CAPs become α-helical

antiparallel dimers as their positive charges grip onto the anionic surface of the bacterial

membrane, upon which their hydrophobic core dips into the lipid bilayer and causes membrane

disruption. Right, when the hydrophobicity of the CAPs becomes too high, as with our 4L

CAPs, the hydrophobic core of the CAPs can partition, at least partially, from the water phase for

insertion into the zwitterionic mammalian membrane via hydrophobic interactions. However,

the hydrophobic core of the CAPs may not insert too deeply into the mammalian lipid bilayers,

since the positive charges likely still remain in the water phase, preventing further sinking of the

peptides.

97

(iv) Alginate-binding and diffusion ability of the CAPs

With respect to peptide-alginate interactions, while the 25-mer CAPs are able to adopt an α-

helical conformation in the ‘auxiliary membrane’ – alginate (Chan et al. 2004), the 17-mer CAPs

largely form insoluble complexes in alginate (Chapter 4). This indicates that the length of

peptide core directly affects their binding to alginate. The 17-mer CAPs contain only 11 residues

in the hydrophobic core segment, which may be too short for them (vs. the 19-residue core of the

25-mers) to properly fold into α-helical structures within the matrix of the alginate glycan chains

upon charge neutralization. While all the 6K-series of 17-mer CAPs do strongly bind to alginate,

the binding affinity is sequence-dependent. A pattern of large-small-large residues on one face

of the peptides possibly creates a tight binding pocket for peptide self-association and

aggregation, which competes with the heterogeneous affinity for alginate. This self-

oligomerization and/or aggregation behaviour limits peptide penetration into alginate matrix.

However, when peptide aggregation is reduced by having positive charges distributed on both

termini of the peptides (Chapter 3), diffusion of the peptides becomes much more efficient

(Chapter 4).

Overall, the findings support the idea that peptide hydrophobicity, charge distribution, and amino

acid residue composition each play important roles in the interactions of CAPs with membranes

and biofilm alginate, yet their relative roles in effective antimicrobial activity and minimal

hemotoxicity of CAPs – while having an efficient alginate penetration – need an optimal

balance. The results of the thesis clarify preferable routes to optimization of sequences most

likely to be of value toward devising therapeutic strategies. Thus, an excellent CAP requires

peptide helicity induction, insertion and dimerization ability in the bacterial membrane, and

freedom from aggregation, without interference from binding to, and becoming trapped in the

biofilm alginate matrix. As CAP sequences become optimized in future research, the most active

CAPs may find principal roles as participants in ‘combination therapy’ with conventional small-

molecule antibiotics to achieve a higher efficacy against bacterial infections.

98

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Appendix

Figure A 1. A representative HPLC spectrum of the peptide 6K-F17. The synthesized

peptides were purified on a reverse-phase C4 preparative high performance liquid

chromatography (HPLC) using a linear gradient of acetonitrile in 0.1% TFA. The circled peak

shown indicates the pure peptide, confirmed by mass spectrometry analysis (see Table A 1

below).

126

Table A 1. Expected molecular weights (MWs) and mass spectrometry (MS) analysis of

synthesized peptides. The synthesized peptide sequences are listed in Table 2-1 and Table 3-1.

D-enantiomers of the peptides are denoted in lower case letters. MS analysis was performed by

either the Sickkids MS facility or U of T chemistry department MS center. The ionization

method used was either ESI or MALDI.

Peptides MW

(Da)

MS Analysis

6K-F17 1836

127

6k-f17 1836

6K-F17-1L11 1878

128

6K-F17-2L11,13 1920

6K-F17-2L10,14 1920

129

6k-f17-2l16,17 1920

6K-F17-2L8,16 1920

130

6K-F17-2L7,8 1920

6K-F17-

3L8,11,13

1962

131

6K-F17-

3L11,13,16

1962

6K-F17-4L 2005

132

3K-F17-3K 1836

3K-F17-4L-3K 2005

133

6k-a17 1684

6k-a17-f9 1761

134

TAMRA-6KF17 2250

TAMRA-

6KF172L8,16

2334

135

TAMRA-

6KF173L11,13,16

2377

TAMRA-

6KF174L

2418

136

TAMRA-3K-

F174L-3K

2418

137

Copyright Acknowledgements

Figure 1-8 was originally published in the Journal of Biological Chemistry. Glukhov, E., M.

Stark, L. L. Burrows and C. M. Deber. Basis for selectivity of cationic antimicrobial peptides for

bacterial versus mammalian membranes. J Biol Chem. 2005; 280: 33960-33967. © the American

Society for Biochemistry and Molecular Biology.

Figure 1-10 was originally published in the Journal of Biological Chemistry. Chan, C., L. L.

Burrows and C. M. Deber. Helix induction in antimicrobial peptides by alginate in biofilms. J

Biol Chem. 2004; 279: 38749-38754. © the American Society for Biochemistry and Molecular

Biology.

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