Genomic characterization and quantification of

virulence factor activities in Streptococcus

pyogenes isolated from human infections

Mariana Isabel Pinto Ferreira

Thesis to obtain the Master of Science Degree in

Microbiology

Supervisors: Prof./Dr. Ana Isabel Aquino Friães

Prof./Dr. Isabel Maria De Sá Correia Leite de Almeida

Examination Committee

Chairperson: Prof./Dr. Jorge Humberto Gomes Leitão

Supervisor: Prof./Dr. Ana Isabel Aquino Friães

Member of the Committee: Dr. Sílvia Andreia Bento da Silva Sousa

Barbosa

October of 2018

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ACKNOWLEDGMENTS

Foremost, I would like to acknowledge my thesis supervisor, Professora Ana Friães, for

providing me with the opportunity to develop this work and further my experience in the medical

microbiology field. I will always value your guidance, support and shared knowledge throughout the

research time and writing of this dissertation. A very special gratitude goes to Professor Melo Cristino

and Professor Mário Ramirez for the given opportunity to integrate their work team and the latter also

for the scientific suggestions given. I extend my gratitude to Professora Isabel Sá Correia, my internal

supervisor, for accepting me into the Microbiology Master of Science Degree of the Instituto Superior

Técnico of University of Lisbon.

I would also like to thank my colleagues at Instituto de Medicina Molecular João Lobo Antunes

and Mário Ramirez Lab with whom I had the pleasure to work. I thank Miguel Machado and Mickael

Silva for their instrumental contributions regarding the bioinformatic analysis. A special acknowledgment

to my labmates Joana Costa, Lúcia Prados, Joana Silva, Elísia Lopes and Soraia Guerreiro for helping

me during the development of the research work and for the companionship.

I am most grateful to my mother who provided me with the tools to successfully progress in my

academic career and life in general. Your encouragement to take risks and move forward without any

hesitations is the fundamental basis of my success. I am also grateful to my brother whose intelligence

and achievements always inspired me to be my better self. I also wish to thank my other family members,

particularly my aunt and uncle, for the constant moral support. My profound gratitude goes to Miguel for

providing me with unfailing love, support and motivation and my friend Marta Mota for the invaluable

friendship.

Finally, I would like to dedicate this thesis to my father that despite not being able to follow the

progression of my academic path will always be the main inspiration behind my achievements. I will be

forever grateful for everyone involved in this process without whom this accomplishment would not have

been possible.

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ABSTRACT

Keywords: Streptococcus pyogenes, high throughput sequencing, genetic diversity, streptolysin O,

streptokinase

Streptococcus pyogenes (Lancefield group A Streptococcus, GAS) is an important human

pathogen and the causative agent of pharyngitis, superficial skin and soft tissue infections (SSTI) and

severe invasive disease.

High throughput sequencing of 320 GAS isolates belonging to six clones of interest and

recovered from pharyngitis, SSTI and invasive infection was performed. The minimum spanning tree

obtained by gene-by-gene analysis presented a clustering of isolates according to emm type, with emm1

isolates sharing a close genetic relationship. Within emm89, three major clades were identified, and the

isolates of the recently emerged clade 3 displayed the lowest intra-clade genetic distances. An overall

clustering of emm4 isolates according to macrolide resistance was observed, indicating that some

genetic characteristics may be responsible for the phenotypic differences between the lineages. The

genomic diversity observed within the clones analyzed was used to select isolates from each clone for

subsequent phenotypic studies, including the quantification of the in vitro extracellular activity of

streptolysin O (SLO) and streptokinase.

The optimization of the SLO activity assay was finished within the time scope of this thesis.

Some steps of the protocol for the streptokinase activity assay were not completely optimized, and

further work includes the determination of the optimal plasminogen concentration and the definition of a

standard curve to determine the streptokinase activity.

This work sets the ground for future research studies aimed at identifying genotypic and

phenotypic characteristics that may contribute to the preferential association of certain clones with

different types of infection.

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RESUMO

Palavras-chave: Streptococcus pyogenes, sequenciação de alto débito, diversidade genética,

estreptolisina O, estreptoquinase

Streptococcus pyogenes (Streptococcus do grupo A de Lancefield, GAS) é um importante

agente patogénico do ser humano, podendo causar faringite, infeções superficiais da pele e tecidos

moles e infeções invasivas.

Foi efetuada a sequenciação de alto débito de 320 estirpes de GAS pertencentes a seis clones

de interesse e isoladas de faringite, infeções da pele e tecidos moles e infeção invasiva. A árvore obtida

por métodos “gene-by-gene” demonstrou uma distribuição das estirpes de acordo com o tipo emm-, e

as estirpes emm1 revelaram-se geneticamente próximas. No clone emm89 observaram-se três clades

e as estirpes do clade 3, que surgiu recentemente, apresentaram as menores distâncias genéticas.

Observou-se uma boa separação dos clones emm4-, suscetível e resistente a macrólidos, o que sugere

a existência de característica(s) genética(s) responsável(eis) pelas diferenças fenotípicas observadas

entre as linhagens. A diversidade genética observada dentro de cada clone permitiu a seleção de um

grupo de estirpes para serem incluídas em estudos fenotípicos subsequentes, nomeadamente a

quantificação in vitro da atividade extracelular de estreptolisina O (SLO) e estreptoquinase.

A otimização do ensaio de atividade da SLO foi terminada dentro do tempo estabelecido para

esta tese. Alguns passos do protocolo da estreptoquinase não foram completamente otimizados e o

trabalho futuro inclui a determinação da concentração ótima de plasminogénio e a definição da curva

de calibração para determinação da atividade de estreptoquinase.

Este trabalho representa assim um ponto de partida para a identificação de características

genotípicas e fenotípicas responsáveis pela associação preferencial de alguns clones com

determinados tipos de infeção.

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TABLE OF CONTENTS

ABBREVIATIONS 11

FIGURES AND TABLES 13

GENERAL INTRODUCTION 15

General Features and Identification of Streptococcus pyogenes 15

Main Infections Caused by Streptococcus pyogenes 16

Suppurative infections 16

Nonsuppurative sequelea 19

Antimicrobial Therapy 20

Mechanisms of Pathogenesis and Virulence Factors 21

Adherence to cells 21

Internalization and dissemination 22

Resistance to host defenses 24

Toxicity 25

Typing Methods for Streptococcus pyogenes 26

Phenotypic methods 26

M serotyping 26

T serotyping 27

Molecular methods 28

emm typing 28

Multilocus sequence typing 28

Superantigen gene profiling 29

Pulsed-field gel electrophoresis (PFGE) macrorestriction profiling 30

High throughput sequencing 30

Molecular Epidemiology of Strains of Streptococcus pyogenes Isolated from Human Infections in

Portugal 31

Streptococcus pyogenes Genomics 33

AIM OF THE STUDY 35

MATERIALS AND METHODS 37

Bacterial strains and culture conditions 37

High throughput sequencing 37

Gene-by-gene analysis and genetic relationships between isolates 38

Optimization of streptolysin O activity determination assay 39

Optimization of streptokinase activity determination assay 40

Bacterial growth curves 39

RESULTS AND DISCUSSION 43

Genetic relationships between isolates 43

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Selection of isolates representative of the genetic diversity within each clone 49

Optimization of SLO activity determination assay 52

Optimization of streptokinase activity determination assay 55

CONCLUSIONS AND FUTURE PERSPECTIVES 63

REFERENCES 65

SUPPLEMENTARY DATA 79

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ABBREVIATIONS

A - Absorbance

APSGN - Acute post-streptococcal glomerulonephritis

ARF - Acute rheumatic fever

C4BP - C4-binding protein

CC - Clonal complex

CDC - Centers for Disease Control and Prevention

cgMLST - Core genome MLST

DLV - Double-locus variant

DTT – Dithiothreitol

emm1-EryS - emm1, erythromycin-susceptible clone

emm4-EryS - emm4, erythromycin-susceptible clone

emm4-EryR - emm4 erythromycin-resistant clone

FCT - fibronectin- and collagen-binding proteins and T antigen-encoding loci

FgR - Fibrinogen-binding receptors

GAPDH - Glyceraldehyde 3-phosphate dehydrogenase

GAS - Group A Streptococcus

HGT - Horizontal genetic transfer

HTS - High throughput sequencing

HVR - Hypervariable region

LTA - Lipoteichoic acid

M - Phenotype M of macrolide resistance (erythromycin resistance and clindamycin susceptibility)

MAC - Membrane attack complex

MALDI-TOF - Matrix-assisted laser desorption ionization time-of-flight

MGE - Mobile genetic element

MHC - Major histocompatibility complex

MLSB - Macrolides, lincosamides and streptogramin B (resistance phenotype)

cMLSB - constitutive MLSB resistance phenotype

iMLSB – Inducible MLSB resistance phenotype

MLST - Multilocus sequence typing

MS - Mass spectrometry

MSCRAMMs - Microbial surface components recognizing adhesive matrix molecules

MST - Minimum spanning tree

NADase - NAD-glycohydrolase

NAPlr - Nephritis associated plasmin receptor

NET - Neutrophil extracellular trap

OD - Optical density

PAM - Plasminogen-binding group A Streptococcal M-like protein

PBS - Phosphate-buffered saline

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PCR - polymerase chain reaction

PFGE - Pulsed-field gel electrophoresis

PLRs - Plasmin receptors

PYR - Pyrrolidonylarylamidase

RADT - Rapid antigen detection tests

RT - Room temperature

SAg - Superantigen

SDSE - S. dysgalactiae subsp. equisimilis

SDSD - S. dysgalactiae subsp. dysgalactiae

SIC - Streptococcal inhibitor of complement

SLO - Streptolysin O

SLS - Streptolysin S

SLVs - Single-locus variants

SMEZ - Streptococcal mitogenic exotoxin

SNPs - Single-nucleotide polymorphisms

Spe - streptococcal pyrogenic exotoxins

SpeB - Streptococcal cysteine protease

SRA - Sequence Read Archive

SSA - Streptococcal superantigen

SSTI - Skin and soft infections

ST - sequence type

STSS - Streptococcal toxic shock syndrome

THB - Todd Hewitt Broth

TSA - Tryptone Soya Agar

wgMLST - Whole genome MLST

zSPEB - Zymogen precursor of streptococcal pyrogenic exotoxin B

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FIGURES AND TABLES

Figure 1. GAS β-hemolytic colonies grown on blood agar .................................................................... 15

Figure 2. Visual presentation of streptococcal pharyngitis .................................................................... 17

Figure 3. Representation of GAS superficial and deep tissue skin and soft tissue infections in association

with the anatomical sites of the skin structure ....................................................................................... 19

Figure 4. Virulence factors involved in the different stages of GAS pathogenesis ................................ 24

Figure 5. The hypervariable region used for emm typing and the repeat regions (A, B, C and D repeats)

with a variable size and amino acid composition ................................................................................... 27

Figure 6. Molecular events leading to the emergence of the highly successful M1T1 clone and the

recently emerged emm89 clade 3 .......................................................................................................... 34

Figure 7. MST generated by the goeBURST full MST algorithm for the 319 GAS cgMLST dataset .... 44

Figure 8. MST generated by the goeBURST full MST algorithm at a tree cut off of 1052 that allows a

separation of strains according to emm type. Isolates are colored by ST within each emm type ......... 45

Figure 9. Clonal complexes defined by goeBURST and visualized on PHYLOViZ 2.0. ....................... 46

Figure 10. MST generated by the goeBURST full MST algorithm for isolates of emm89 and analysis of

the presence according to the hasABC locus and the nga promoter variant ........................................ 47

Figure 11. MST for the emm4 isolates (susceptible and resistant to erythromycin) .............................. 49

Figure 12. Isolate selection within the emm1-EryS and emm3 clones for subsequent phenotypic analysis

................................................................................................................................................................ 50

Figure 13. Isolate selection within the emm89 groups (hasABC+ and hasABC-) and the emm4 groups

(EryS and EryR) for subsequent phenotypic analysis ........................................................................... 51

Figure 14. Summary of the steps of the laboratory assay for the in vitro quantification of the extracellular

activity of SLO ........................................................................................................................................ 52

Figure 15. Summary of the steps of the laboratory assay for the in vitro quantification of the extracellular

activity of streptokinase. ......................................................................................................................... 56

Figure 16. Graphic representation of the absorbance plotted against time from the streptokinase

determination assay performed with glu-plasminogen 500 nM, with glu-plasminogen 220 nM or without

plasminogen, for culture supernatants of strain MGAS5005 grown at late-exponential phase ............. 57

Figure 17. Graphic representation of the absorbance plotted against time from the streptokinase

determination assay performed with plasminogen pre-incubated with fibrinogen or with plasminogen

alone, for culture supernatants of the GAS strains 2003V0731P or MGAS5005 grown at mid-exponential

phase ...................................................................................................................................................... 57

Figure 18. Graphic representation of the absorbance plotted against time from the streptokinase

determination assay performed for culture supernatants of GAS strain SF370 grown to mid-exponential

phase, late-exponential phase and stationary phase; and for GAS strain MGAS5005 grown to late-

exponential phase .................................................................................................................................. 59

Figure 19. Standard curves of commercial streptokinase performed during the optimization process . 61

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Table 1. Relevant genotypic (emm type) and phenotypic (NADase activity) characteristics of the strains

used for optimization of the SLO and streptokinase activity assays...................................................... 37

Table 2. Concentration of trypan blue and preincubation conditions tested to achieve a complete

inhibition of the SLS activity ................................................................................................................... 53

Table 3. Concentrations of DTT tested to stabilize SLO ........................................................................ 53

Table 4. SLO activity values obtained for the control strains and the other two strains with high activity.

................................................................................................................................................................ 55

Table 5. Summary of the conditions defined for the SLO activity determination assay after the

optimization process............................................................................................................................... 55

Table 6. Summary of the conditions defined for the streptokinase activity determination assay .......... 62

Figure S1. A: Distance matrix visualization between nodes within each emm type .............................. 87

Figure S2. MST for the 319 GAS cgMLST dataset at a tree cut off of 1052 and association with type of

infection .................................................................................................................................................. 88

Figure S3. MST for the emm1, emm3 and emm89 isolates and association with year of isolation ...... 89

Figure S4. Distance matrix visualization between nodes within emm89 clades 2 and 3 ...................... 89

Figure S5. Distance matrix visualization of erythromycin-susceptible and -resistant emm4 isolates ... 90

Figure S6. Growth curves of the 10 strains used in the optimization of the SLO and streptokinase activity

determination assays ............................................................................................................................. 90

Table S1. Strain selection was performed so as to include half of the isolates representative of six clones

of interest and associated with each type of infection in a minimum of 10 isolates .............................. 79

Table S2. List of the 320 isolates selected for genomic characterization as well as known characteristics

such as emm type, type of infection, year of isolation, ST, SAg genes profile, macrolide resistance

phenotype and hasABC locus ................................................................................................................ 79

Table S3. The isolates selected within each of the six clones of interest are listed, as well as the

respective year of isolation, type of infection, ST and SAg profile ......................................................... 86

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GENERAL INTRODUCTION

General Features and Identification of Streptococcus pyogenes

Streptococcus pyogenes, also known as group A Streptococcus (GAS), is a gram-positive

bacterium that exclusively colonizes the human host, primarily the throat or skin. The colonization may

lead to asymptomatic carriage or the development of disease. GAS is an important human pathogen

that causes a wide range of infections including relatively uncomplicated conditions such as pharyngitis

and superficial skin and soft tissue infections (SSTI), as well as life-threatening invasive diseases such

as necrotizing fasciitis and streptococcal toxic shock syndrome (STSS). Additionally, these bacteria are

also responsible for two nonsuppurative sequelae: acute poststreptococcal glomerulonephritis (APSGN)

and acute rheumatic fever (ARF) (1).

S. pyogenes usually appears as β-hemolytic colonies on 5% sheep blood agar with trypticase

soy base after 18-48 hours of incubation at 35-37°C under aerobic conditions (Figure 1).

Morphologically, GAS colonies are generally of white-greyish color with a diameter of > 0.5 mm, ranging

from highly mucoid to non-mucoid. The colonies are also catalase negative and under the microscope

GAS appears as gram-positive cocci arranged in chains. After culture of the organism on blood agar, β-

hemolytic and catalase negative colonies are further tested for species identification (1, 2).

Figure 1. GAS β-hemolytic colonies grown on blood agar. Adapted from (2).

The Lancefield classification scheme is a serological method developed by Rebecca Lancefield

(3) for identification of streptococci based on the presence of the group-specific cell wall polysaccharides

(groups A, B, C, F and G) or lipoteichoic acids (LTAs) (group D) antigens. This technique is

conventionally performed using commercial agglutination test kits where a rapid antigen extraction by

an enzymatic substrate is followed by agglutination with sera containing specific group antibodies. S.

pyogenes harbors on its surface the group A carbohydrate antigen that is composed of N-acetyl-β-D-

glucosamine linked to a rhamnose polymer backbone. Although all S. pyogenes strains, except for

strains containing rare mutations, possess the Lancefield group A antigen on their cell walls, other

streptococci such as Streptococcus anginosus group and Streptococcus dysgalactiae subsp. equisimilis

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can also harbor the group A antigen. However, group A strains belonging to these species are not

commonly associated with human infections, so the designation “GAS” usually refers to S. pyogenes

(1, 2).

The β-hemolytic group A streptococci can be distinguished from other β-hemolytic streptococci

and presumptively identified as S. pyogenes after performing the pyrrolidonylarylamidase (PYR) and

bacitracin susceptibility tests. These tests should be performed on pure cultures for a more reliable

result. The PYR test is a rapid colorimetric method that detects the activity of the pyrrolidonyl

aminopeptidase, an enzyme that hydrolyses the L-pyrrolidonyl-β-naphthylamide substrate producing β-

naphthylamine. S. pyogenes and the β-hemolytic mainly animal-associated species Streptococcus iniae

and Streptococcus porcinus are PYR positive (2, 4). Bacitracin is an antibiotic that interferes with the

cell wall and peptidoglycan synthesis of gram-positive bacteria (5). S. pyogenes is susceptible to

bacitracin and therefore the bacitracin susceptibility test allows its differentiation from other β-hemolytic

streptococci, which are resistant (2). However, S. pyogenes strains resistant to bacitracin have already

been identified in several countries (6, 7), compromising the reliability of this test for GAS identification.

For a less time-consuming GAS identification, automated bacterial identification systems such

as the matrix-assisted laser desorption ionization time-of-flight (MALDI-TOF) mass spectrometry (MS)

represents a reliable alternative to the conventional methods. This technique analyses the protein profile

detected, in general, from whole bacterial cells and produces a characteristic spectrum that is used for

species identification. Despite its limitation in identifying certain streptococcal species, MALDI-TOF MS

has emerged as a simple and fast tool for identification and diagnosis of many bacteria, including S.

pyogenes (8, 9).

Main Infections Caused by Streptococcus pyogenes

Suppurative infections

Pharyngitis, the most common GAS infection, is an upper respiratory tract infection with a viral or

bacterial etiology characterized by an inflammation of the pharynx (10). S. pyogenes is the main

causative agent of bacterial pharyngitis, being responsible for approximately 15-30% of acute

pharyngitis in school-age children between 5 and 15 years of age and 5-10% of cases in adult patients.

This acute infection is, therefore, mainly associated with pediatric patients with higher incidence during

winter and early spring. However, pharyngeal carriage of group A streptococci occurs in 3%-26% of

healthy children without presentation of clinical symptoms of disease (11). Other non-group A

streptococci, namely group C and G, can also be etiological agents of pharyngitis (12). Infection occurs

mostly by person-to-person transmission through respiratory droplets, although outbreaks of foodborne

cases have also been reported (11, 13). The most frequent clinical manifestations of streptococcal

pharyngitis include a sudden onset of sore throat and fever and physical examination findings such as

tender and enlarged anterior cervical nodes and tonsillopharyngeal erythema, often accompanied by

painful swallowing and white-yellowish exudate patches (Figure 2) (14, 15).

Although indicative of GAS pharyngitis, a diagnosis based solely on the symptoms and

physiological signs has proven to be insufficient due to the overlapping clinical features of streptococcal

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and nonstreptococcal pharyngitis. Since GAS pharyngitis is the only common form of the disease for

which antimicrobial therapy is prescribed, further microbiological tests are required for an accurate

diagnosis of the infection (14). The laboratory diagnosis of acute pharyngitis involves a throat culture,

the reference method for the diagnosis of this disease, and subsequent detection of the presence of

group A β-hemolytic colonies, or rapid antigen detection tests (RADT) for identification of GAS directly

from throat swabs. It is important to have in consideration that streptococcal pharyngitis is generally a

self-limited disease and treatment may not be required for improvement of clinical symptoms and signs

(10). Still, a rapid diagnosis and treatment of streptococcal pharyngitis aims not only at a rapid resolution

of the signs and symptoms, but also at the prevention of ARF and suppurative complications, and at a

decrease in the transmission of the organism, especially in susceptible environments such as the

household and schools (14).

Following a streptococcal pharyngitis episode, suppurative local and distant complications such

as peritonsillar or retropharyngeal abscesses and bacteremia can occur due to direct extension of the

infection to involving structures or by lymphatic and hematogenous dissemination of bacteria to distant

sites. Scarlet fever is a systemic manifestation of a S. pyogenes infection, generally streptococcal throat

infection. The clinical manifestations include a rash that spreads from the neck and upper trunk to the

limbs as a punctate erythema, the presence of flushed cheeks, a pale area around the mouth and a

coated tongue commonly known as “strawberry tongue”. This disease is commonly associated with the

production of the exotoxins SpeA and SpeC. The incidence of scarlet fever diminished in the twentieth

century, but several outbreaks have been recently reported (11, 15).

Figure 2. Visual presentation of streptococcal pharyngitis. Adapted from (16).

S. pyogenes can also cause a variety of SSTI, which can be superficial, such as impetigo, or

involve deeper tissues, like erysipelas, cellulitis or necrotizing fasciitis (10). Impetigo is a localized

purulent infection of the skin manifested as two types, bullous and nonbullous impetigo, that are globally

designated as pyoderma. While bullous impetigo is typically caused by Staphylococcus aureus,

nonbullous impetigo can be caused by S. pyogenes, S. aureus or both, with GAS infections being

predominant in developing countries while S. aureus infections are associated with industrialized

countries. GAS impetigo is a highly contagious disease that has a high prevalence in some parts of the

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world such as in Aboriginal Australians and generally affects children aged 2 to 5 years (17).

Streptococcal impetigo begins with an initial colonization of the unbroken skin followed by the

development of lesions, possibly due to an intradermal inoculation of the organism through skin

abrasions, small traumas or insect bites. The presence of deep ulcers that extend into the epidermis is

known as ecthyma. The treatment depends on numerous factors, including the concomitant presence

of S. pyogenes and S. aureus and prevents further spreading of this highly contagious disease (10, 17).

Some GAS strains responsible for skin infections are associated with the development of APSGN and

this nonssupurative sequelea is not prevented by the treatment of GAS impetigo (1, 10).

Erysipelas and cellulitis can occur due to entry of the organism through damaged skin sites and

subsequent penetration of the epidermidis. Erysipelas is an acute cutaneous infection, generally

confined to the dermis, that also involves the superficial lymphatic vessels (Figure 3). The disease

presents as raised lesions, generally on the legs and feet, with a well-defined delimitation from the

adjacent healthy tissue accompanied by fever and other systemic symptoms. Other possible causative

agents include groups B, C or G streptococci and rarely S. aureus. Cellulitis, much like erysipelas, is an

acute inflammation of the skin associated with systemic manifestations but with contrasting

presentations such as extension of infection to the lower dermal area and subcutaneous tissues, and

absence of a distinct boundary between the lesion and normal tissue (Figure 3). The clinical

manifestations of GAS cellulitis include edema, redness, warmth and erythema occurring in any part of

the body, usually associated with burns, wounds, surgical incisions or dermatological conditions.

Common causative agents of cellulitis are group A streptococci and S. aureus, with groups B, C or G

streptococci occurring less frequently (10, 18).

Necrotizing fasciitis caused by S. pyogenes, commonly designated as flesh-eating disease, is

a life-threatening infection that involves the muscle fascia, subcutaneous fat and epidermis, resulting in

a rapidly extending necrosis of the tissue and systemic toxicity (Figure 3). The infection often affects the

limbs and begins at a site of seemingly trivial cutaneous trauma or at a defined portal of entry such as

a surgical incision, burn, insect bite or varicella lesion. The signs and symptoms develop rapidly and

include fever and severe local pain, sometimes accompanied by discoloration of the skin and swelling.

The clinical manifestations later progress to pronounced inflammation of the skin, which then becomes

darkish and purplish, and development of skin bullae with yellow or hemorrhagic fluid and blistering.

Necrotizing fasciitis is often associated with GAS bacteremia and a successful management of the

disease requires an early diagnosis and subsequent treatment that involves not only antibiotic therapy,

but also surgical debridement of non-viable tissue to avoid spreading of the infection to adjacent sites

(19, 20). High mortality rates have been reported for necrotizing fasciitis, especially when it occurs in

association with either STSS or myositis (21, 22).

STSS is a streptococcal infection, first described in mid to late 1980s, associated with an abrupt

onset of shock and organ failure. The disease can affect people of all ages, with or without predisposing

medical conditions such as diabetes mellitus and chronic cardiac or pulmonary diseases. A variety of

GAS superantigens, including SSA (streptococcal superantigen) and SMEZ (streptococcal mitogenic

exotoxin), seem to be involved in the pathogenesis of STSS by eliciting a strong immunostimulatory

response which potentiates acute shock and systemic vascular leakage. STSS has been described in

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patients also presenting with necrotizing fasciitis and the clinical presentations include hypotension,

fever, a generalized erythematous macular rash that may desquamate, shock and multiple organ failure.

Empiric treatment should be provided since patients with STSS require aggressive supportive care such

as massive fluid resuscitation and monitoring of vital functions (10, 17, 19).

Myositis is an inflammation of the muscle, with bacterial myositis being characterized as a local

muscle infection that, contrary to necrotizing fasciitis, does not involve a primary infection of the

subcutaneous tissue or skin (22). In myositis, much like in STSS, the portal of entry is often not identified

and some cases are associated with an initial sore throat, indicating that pharyngitis may be responsible

for a bacteremia that may lead to invasive infection. Streptococcal myositis is associated with mortality

rates that range from 80% to 100% (23, 24).

Other invasive infections associated with GAS bacteremia, that are less frequently found since

the introduction of antibiotics, include pneumonia, meningitis, puerperal sepsis and endocarditis (19).

Figure 3. Representation of GAS superficial and deep tissue skin and soft tissue infections in association with the

anatomical sites of the skin structure. Adapted from (25).

Nonsuppurative sequelea

GAS infections can be followed by nonsuppurative complications, such APSGN. APSGN is

usually preceded by a pharyngeal or skin infection with GAS, affecting children aged 5 to 12, young

adults and elderly people. The latent period between streptococcal infection and the development of

APSGN signs and symptoms is 1-3 weeks for pharyngitis and 3-6 weeks for skin infections (17, 26).

The incidence of APSGN has been decreasing, and is currently a rare disease in industrialized

countries, limited to elderly people with debilitating conditions. However, post-streptococcal

glomerulonephritis remains a health problem in communities with low socioeconomic status (27).

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APSGN is an immune complex-mediated disease associated with certain streptococcal

nephritogenic strains. The proposed mechanisms of pathogenesis involve immune complex deposition

with complement activation and molecular mimicry. In the first mechanism, nephritogenic immune

complexes are formed in circulation and subsequently deposit in the glomeruli or, alternatively, the

glomerular immune complexes are formed in situ. This leads to the activation of the complement,

predominantly the alternative pathway, followed by an inflammatory response and induction of

glomerulonephritis. The second possible mechanism involves an autoimmune response due to shared

epitopes between streptococcal and renal antigens (molecular mimicry), with several antibodies against

laminin, collagen and other macromolecules present in the glomerular membrane being found in the

sera of patients with APSGN (26, 28).

The development of APSGN can be prevented with early antibiotic treatment for those with a

streptococcal infection and for individuals at risk such as family members with positive cultures. In

children, a good long-term prognosis for APSGN is expected, although abnormal urinary findings have

been reported. Regarding elderly patients, however, mortality rates can be as high as 25% (27).

ARF is a delayed nonsuppurative complication generally preceded by a pharyngeal infection

caused by group A streptococci. The disease affects mainly children, adolescents and young adults,

being the main cause of acquired heart disease in children worldwide. In industrialized countries, the

incidence of ARF decreased due to the introduction of antimicrobial therapy but in developing countries

and tropical regions it remains an important cause of heart disease. The latent period between

streptococcal infection, which is often asymptomatic, and the development of ARF symptoms is 2-3

weeks (10, 29). The major clinical findings include polyarthritis - the earliest and most common

manifestation of ARF -, carditis, a central nervous system presentation designated as chorea, a distinct

red circinate rash known as erythema marginatum and subcutaneous nodules (29).

ARF is characterized by an autoimmune response due to a molecular mimicry mechanism

where GAS M protein antigen and the immunodominant epitope of group A carbohydrate antigen, N-

acetyl-glucosamine, share epitopes with the host antigens in cardiac myosin, synovial tissue or neural

tissue. This leads to an antibody and/or T cells cross-reaction against human proteins and subsequent

tissue destruction, resulting in the characteristic clinical features (29, 30).

The management of the disease begins with a primary prevention, through an accurate

diagnosis and treatment of GAS pharyngitis, in order to prevent an ARF attack. When the patients

develop ARF, a secondary prevention is applied to prevent recurrent episodes of the disease and further

damage to the heart valves (1, 31).

Antimicrobial Therapy

The first-line antimicrobial agent recommended for uncomplicated GAS infections is penicillin.

S. pyogenes is uniformly susceptible to this antimicrobial, which has the further advantages of having a

narrow antimicrobial spectrum, low production costs and reduced side effects. Other beta lactams such

as amoxicillin and cephalosporins can be used as therapeutic alternatives. For patients allergic to

penicillin, erythromycin is the drug of choice but the local resistance rates to macrolide antibiotics should

21

be taken into consideration before prescription of these antimicrobial (32). For the treatment of severe

infections other options are considered, such as the administration of penicillin in association with

clindamycin due to the reported ability of the latter to suppress the expression of some exotoxins and

modulate cytokine production (33-35).

Variable resistance rates to macrolides have been reported worldwide and resistance to

clindamycin is often associated with resistance to macrolides in isolates presenting the MLSB

phenotype. In S. pyogenes, the two main mechanisms of resistance to macrolide antibiotics include the

post-transcriptional methylation of the 23S rRNA by methylases encoded by erm genes, generally

erm(B) or erm(TR), or the active efflux of the antibiotics by efflux pumps encoded by mef genes,

generally mef(A). The first mechanism leads to the resistance phenotype MLSB (macrolides,

lincosamides and streptogramin B) – constitutive (cMLSB) or inducible resistance to lincosamides and

streptogramin B (iMLSB). The second mechanism leads to resistance to 14- and 15-membered lactone

ring macrolides, but not to 16-member macrolides nor to lincosamides or streptogramins B (M

phenotype). The concomitant presence of erm and mef(A) in GAS isolates has been found, generally

accompanied by the expression of the MLSB phenotype. Both erm and mef resistance determinants are

usually encoded by mobile genetic elements (MGEs) (36). Tetracycline is not a therapeutic option for

the treatment of GAS infections, but the tet(M) gene, a tetracycline resistance determinant, often occurs

together with erm(B) in the same MGE (37, 38). Additionally, tet(O) gene has also been found in

association with macrolide resistance genes in GAS (39). Both genes code for ribosomal protection

proteins that allosterically interfere with the binding of tetracycline molecules to the ribosome (40).

Mechanisms of Pathogenesis and Virulence Factors

Adherence to cells

The first step in the pathogenesis of GAS is the adherence of the organism to the epithelial cells

of the two main sites of infection: oropharynx or skin. The adherence is an essential first step for

colonization and is described as a two-step model that starts with a weak interaction with the mucosa,

where the electrostatic repulsion between bacterial and host cell surface is overcome, that then

progresses to a firm, tissue specific adherence (1).

Several cell-surface components are thought to mediate these interactions with host molecules,

such as the LTA, the hyaluronic acid capsule, some M proteins, several fibronectin- and collagen-

binding proteins, and pili (Figure 4) (1, 41-43). The LTA, a hydrophobic component of the cell surface of

Gram-positive microorganisms, promotes adhesion through interactions of its lipid moiety with fatty acid-

binding domains on fibronectin and epithelial cells (1). The hyaluronic acid capsule seems to have a

variable importance in this process since GAS hyaluronic acid binds to cell-surface protein CD44 but,

at the same time, this component may mask other bacterial adhesins thereby impairing the attachment

mechanism. Therefore, it seems that a controlled regulation of the capsule is needed for colonization

and other adhesins are needed for this process (43, 44). Additionally, the production of GAS capsule

does not seem to be mandatory for virulence since human disease isolates lacking the hasABC locus

(encoding the hyaluronic acid capsule) have been reported, some of which in association with epidemic

22

disease (45, 46). Regarding the M protein, its importance in this process is dependent on the M protein

serotype and the target tissue, throat or skin. (1, 47). Fibronectin and collagen are molecules located in

the host extracellular matrix that allow adherence of GAS through microbial surface components

recognizing adhesive matrix molecules (MSCRAMMs), such as the fibronectin- and collagen-binding

proteins, namely F1/SfbI and Cpa, respectively. However, most of those MSCRAMMs are not present

in all GAS serotypes. (41). Pili are appendage-like molecules identified as important components in the

adhesion mechanism to squamous epithelial cells from the pharynx and skin (48-50). Therefore, in the

two-step model of adherence, the LTA, as an amphipathic molecule, mediates the first-step of adhesion

whereas other adhesins, such as M protein and fibronectin-binding proteins, are involved in the second-

step adhesion (42).

For a successful attachment and colonization, the organism has to overcome certain constraints

associated with the oropharynx or skin environments, such as the components of the innate and

acquired immune system present in the saliva, the low levels of nutrients, namely glucose, in the

oropharynx, and the exfoliation of the skin epithelium (1, 51). To circumvent the low levels of glucose in

the saliva, S. pyogenes developed a mechanism that allows its survival for long periods in the saliva,

possibly by resorting to alternative carbon sources digested by the human salivary α-amylase for

acquisition of nutrients and survival in this hostile environment (52). Regarding the dermal barrier, the

organism may, for instance, use a skin infringement or a wounded site as a portal of entry, thereby

overcoming this efficient barrier (1). For a prolonged colonization after attachment, the organism may

assemble into cell aggregates, which leads to microcolony formation and subsequent differentiation into

a mature biofilm. The biofilm structure protects bacteria from host defense mechanisms and

antimicrobials (53). Many GAS components seem to be involved in biofilm formation such as the M

protein, pili and the AgI/II family adhesin AspA, making it a complex multifactorial process (50, 54, 55).

Internalization and dissemination

Despite being described as an extracellular pathogen, S. pyogenes is also able to penetrate

human epithelial cells due to interactions between host integrins and GAS adhesins and cytoskeletal

rearrangements, a process that seems to play an important role in pathogenesis. The GAS M protein,

namely the M1 protein, and fibronectin-binding protein SfbI are involved in this intracellular invasion and

the internalization mechanism may differ according to the surface protein involved (56). Additionally, the

hyaluronic acid interacts with the cell-surface protein CD44, facilitating the paracellular translocation of

the bacterium into deeper tissues through disruption of intercellular junctions (32, 44).

The transition from localized to invasive disease in GAS is associated with differences at the

transcriptome level, which evidences the importance of differential gene expression regulation for the

pathogenesis of the organism. The switch to an invasive transcriptome profile is thought to involve the

CovRS two-component regulatory system that directly or indirectly influences approximately 15% of the

GAS transcriptome (57). This two-component gene regulatory system is composed by a membrane-

bound extracellular sensor protein (CovS) that responds to environmental stimuli such as temperature,

pH and osmolarity, leading to phosphorylation or desphosphorylation of the CovR protein, a response

regulator that modulates the transcription of multiple GAS genes (58). It has been described that

23

mutations leading to ablation of this regulatory system result in the upregulation of genes encoding

several virulence factors associated with invasive disease like the hasABC operon (the capsule

synthesis operon), slo (streptolysin O), ska (streptokinase) and sagA (streptolysin S), and in the

downregulation of speB (57, 59). Additionally, the regulation of speB is dependent on the transcriptional

regulator RopB and mutations in this regulator lead to the abrogation of SpeB expression (60, 61). The

highly conserved gene speB, carried by most S. pyogenes strains, encodes a cysteine protease known

as SpeB, and there seems to be a correlation between its differential expression and the transition from

local to systemic infection. SpeB not only degrades host molecules but also inactivates many group A

streptococci virulence factors including the M protein, C5a peptidase and streptokinase. In the initial

adherence stage, speB seems to be downregulated enabling the adherence process by GAS virulence

factors involved in the host-pathogen interactions. In response to environmental stimuli, SpeB levels are

increased in several strains which seems to help the transition from local site of infection to the blood

and the dissemination of the organism by degradation of host cell components. Once in blood, speB is

again downregulated sparing other virulence factors such as M protein and the DNase Sda1 (62-64).

Nevertheless, other mechanisms must be involved in the transition from localized to invasive disease in

GAS since the absence of SpeB activity alone is not associated with invasiveness (61). However,

previous studies have demonstrated that SpeB is a key virulence factor required for the pathogenesis

of the bacteria in necrotizing fasciitis and other infections (65, 66). Although inactivating mutations of

the CovRS operon have been statistically associated with isolates recovered from invasive disease, the

acquisition of such mutations does not seem to be exclusive of highly invasive lineages (59, 61).

Additionally, the occurrence of inactivating CovRS mutations is an uncommon event in the GAS

population (61).

Another virulence factor involved in bacterial dissemination is the streptokinase, a secreted

protein known for its non-enzymatic ability to activate human plasminogen, the zymogen form of the

serine protease plasmin. Streptokinase can bind plasminogen to form an activator complex, or bind both

plasminogen and fibrinogen producing a trimolecular plasmin activator complex. Streptokinase can,

therefore, activate plasminogen and the cell-surface bound plasmin is then responsible for the

fibrinolysis, resulting in degradation of fibrin networks, components of the extracellular matrix and

antimicrobial components, promoting the bacterial spread to surrounding sites (67, 68). Additionally, the

acquisition of plasminogen through GAS cell-surface receptors, even without streptokinase, seems to

confer enhanced virulence possibly via host plasmin activators (67, 69). The streptokinase gene (ska)

exhibits sequence variability, with the ska alleles being grouped into two sequence clusters, cluster type-

1 and cluster type-2, which is further sub-clustered into type-2a and type-2b (70-72). It has been shown

that allelic variants of streptokinase are associated with different plasminogen activation mechanisms.

Strains harboring a cluster 1 ska allele readily combine with plasminogen, producing a complex with

plasmin activity that binds the bacterial cell surface through plasmin receptors (PLRs), such as the α-

enolase and glyceraldehyde 3-phosphate dehydrogenase (GAPDH), or by interaction with fibrinogen

and fibrinogen-binding receptors (FgR). On the other hand, strains producing streptokinase encoded by

cluster 2 alleles combine with plasminogen and fibrinogen, producing a trimolecular complex with

plasmin activity. While the trimolecular complexes produced by cluster 2a streptokinase bind the cell

24

surface through FgR, cluster 2b streptokinase trimolecular complexes are bound through interactions

with plasminogen-binding group A streptococcal M-like protein (PAM) (71). An association between

PAM and tissue tropism for the skin has been previously suggested, with the gene encoding for PAM

being present in many strains that are generally associated with impetigo (73, 74).

Figure 4. Virulence factors involved in the different stages of GAS pathogenesis. Adapted from (75).

Resistance to host defenses

After invasion, S. pyogenes employs several mechanisms to evade the host innate immune

system and, therefore, improve its survival and persistence within the host. In response to infection, the

host complement system is activated via specific antibody, or through the alternative or lectin pathways,

which results in opsonisation of the organism and phagocytosis. The M protein and the hyaluronic acid

capsule are thought to be involved in resistance to phagocytosis in GAS (Figure 4). The presence of

peptidoglycan cell wall and also, in some strains, a hyaluronic acid capsule makes GAS naturally

resistant to complement lysis. One possible mechanism for M protein-mediated resistance to

opsonophagocytosis is binding of factor H, an inhibitor of the complement that limits the deposition of

opsonin C3b on the cell surface of the organism (29). However, it has been reported that binding of

factor H to S. pyogenes is neither a sufficient nor a necessary mechanism for phagocytosis resistance

25

(76). Other proposed mechanisms include the binding of M protein to host fibrinogen and the binding of

the human C4-binding protein (C4BP) to the hypervariable region (HVR) of the M protein. Fibrinogen

binding to the surface of GAS also reduces the deposition of C3b on the microbial surface thus

preventing phagocytosis (29), although this mechanism seems also insufficient for phagocytosis

resistance (77). C4BP is an inhibitor of the lectin pathway of the complement system and its binding

property to the many HVRs seems to promote phagocytosis resistance (77).

Several other virulence factors have been implicated in the resistance to host defenses and these

include the streptococcal inhibitor of complement (SIC), the C5a peptidase, DNases, streptolysin O

(SLO), SpeB and streptokinase (Figure 4). The SIC is an extracellular protein responsible for inhibiting

the membrane attack complex (MAC) and complement mediated lysis of the organism (78). The C5a

peptidase specifically cleaves and inactivates the C5a complement component and consequently

abolishes the accumulation of immune cells at sites of infection (79, 80). The DNases, namely SdaD2

(also designated as Sda1), protect GAS from neutrophil-mediated killing by degrading the neutrophil

extracellular traps (NETs), which are assemblies of chromatin fibers and antimicrobial peptides

responsible for immobilizing and killing bacteria (81). SLO is a secreted, oxygen-labile, thiol activated

toxin responsible for inhibiting the production of ROS by neutrophils and impairing other ROS-dependent

functions such as degranulation and formation of DNA-based NETs (82, 83). In S. pyogenes the slo

gene is in an operon also comprising the nga gene (NAD-glycohydrolase, NADase) and the ifs gene

(NADase intracellular inhibitor). Acquisition of a specific variant of the nga, ifs and slo promoter region

leading to increased NADase and SLO production has been implicated in the emergence of virulent

clones (46, 84). The synergistic action of SLO and its co-toxin NADase is essential for evasion to

macrophage-mediated killing and other immune mechanisms (85, 86). SpeB can suppress the host

immune response by cleaving the immunity modulators (66). S. pyogenes can also circumvent killing

by bactericidal histones through bacterial plasminogen binding and degradation by plasmin, or secreted

complexes of streptokinase-plasmin(ogen) (87).

Toxicity

SLO and streptolysin S (SLS) are potent toxins responsible for the formation of large

transmembrane pores on the host membranes, thereby exerting a cytotoxic effect on immune cells (82,

85, 88). Additionally, the coordinated action of SLO and NADase lead to macrophage intoxication. In

this process, impairment of the acidification of the phagolysosome by SLO is followed by SLO-mediated

translocation of NADase into the macrophage cytosol and subsequent depletion of the cellular energy

storages, inhibiting the cellular repair of the damaged membrane (85).

S. pyogenes produces several superantigens (SAgs) which are responsible for modulating the

host immune response. The SAgs interact with the host major histocompatibility complex (MHC) class

II molecules and the variable region of the T-cell receptor β-chain without previous processing by

antigen-presenting cells. This leads to the non-specific activation of large numbers of T cells and

subsequent production of inflammatory cytokines and interleukins, which potentiates the acute shock

and systemic vascular leakage observed in STSS (89, 90).

26

SpeB also seems to play a role in invasive disease by generating biologically active peptides such

as interleukin-1, kinins and histamine, thereby inducing inflammation. Additionally, an

immunostimulatory response may also be elicited by other virulence factors such as the M protein, SLO,

LTA and C5a peptidase (Figure 4) (56, 66).

Typing Methods for Streptococcus pyogenes

S. pyogenes infections have a wide range of clinical manifestations and represent a major burden

for public health worldwide, with an increase in the incidence of invasive disease associated with high

morbidity and mortality being reported (91). Epidemiological surveillance is of utmost importance to

identify changes in the clonal structure and genomic diversity of GAS isolates in different populations,

which may underlie the upsurge of severe infections or antimicrobial resistance. The most commonly

used epidemiological tools include phenotypic, molecular and sequence-based typing methods that,

based on phenotypic and genotypic characteristics, provide valuable information regarding the clonal

composition of GAS isolates and their relationships (92, 93). The increased availability, decreased costs

and high reproducibility of the molecular sequence-based typing methods such as emm typing and

multilocus sequence typing (MLST) lead to the replacement of the classical serological methods T and

M typing, which are restricted to the variety of typing sera available (94, 95).

Although a variety of methods have been proposed for GAS typing, the most widely used have

been M and T serotyping, emm typing, pulsed-field gel electrophoresis, MLST and SAg gene profiling.

Recently, high throughput sequencing (HTS) has been emerging as an epidemiological tool that also

allows the identification of the molecular events leading to changes in the clonal structure in different

populations (94, 96-99).

Phenotypic methods

M serotyping

Historically, epidemiological typing of S. pyogenes was based on the antigenic variability of the

streptococcal M protein, a serological method known as M typing. The M protein is a major virulence

factor of GAS that is anchored to the cell membrane and extends from the cell surface as a fibrillar

coiled-coil dimer. This surface protein, encoded by the emm gene, acts as a virulence factor by

promoting adhesion to the host cell and by providing resistance against multiple host immune

mechanisms (1, 100). The M protein structure includes a signal peptide, a hypervariable amino terminus,

a less variable central domain, and a highly conserved C-terminus domain. The hypervariable region is

followed by a number of repeat regions (A, B, C and D repeats) with variable size and amino acid

composition (Figure 5) (101).

The serological typing of the surface M protein developed by Rebecca Lancefield was based

on the antigenic diversity arising from the heterogeneity of its surface-exposed amino N-terminal. This

phenotypic method required type-specific antisera, which was difficult to produce and was not readily

27

available, and extraction of the M protein from the surface of group A streptococci. Additionally, some

isolates could not be typed due to limitations of the type-specific antisera available (102, 103).

Figure 5. The hypervariable region used for emm typing and the repeat regions (A, B, C and D repeats) with a

variable size and amino acid composition. The three emm pattern groups correlated with different tissue tropisms

are represented by a three M protein model (M5, M80 and M77). Adapted from (104).

T serotyping

Conventionally, serological typing methods based on GAS surface proteins such as the T and

M proteins were widely used in epidemiological studies. The phenotypic typing method known as T

serotyping is based on the trypsin-resistant T protein antigens, with the T protein being produced by

most strains of GAS. The first tee gene reported encoded the antigen recognized by T6 sera, but its

function remained unclear. Later, the T protein was found to be part of the pilus structures encoded by

a variable pathogenicity island designated as FCT region (fibronectin- and collagen-binding proteins

and T antigen-encoding loci) (48). The backbone (bp) variant within GAS pili was found to be strongly

associated with T antigens, providing the possibility to replace the serological typing method with a

molecular method based on a polymerase chain reaction (PCR) gene profiling using primers specific for

each bp gene to discriminate the tee types (105).

Many S. pyogenes strains have multiple T types, leading to recognized T agglutination patterns

such as 5/27/44. The occurrence of T patterns different from the ones known to be associated with each

emm type may be indicative of a clonal change, thereby providing information regarding strain diversity

within an emm type (106). However, it has also been reported that the combination of T typing and emm

typing does not significantly improve the discrimination power when compared with emm typing alone

(93).

28

Molecular methods

emm typing

The limitations associated with the serological methods led to the development of a molecular

typing method based on the sequencing of emm-specific PCR products that is independent of emm

gene expression and is able to type isolates difficult to type by serologic methods (102). The emm gene,

which encodes the S. pyogenes M protein, includes a hypervariable 5’ region. Therefore, the

amplification of the 5’-terminal portion of the emm gene by a specific primer pair and subsequent

sequencing of this region is the basis of the emm typing scheme (95). The Centers for Disease Control

and Prevention (CDC) provides the protocols and recommendations for emm typing and a standardized

reference database for assignment to a validated M protein gene sequence

(https://www.cdc.gov/streplab/groupa-strep/index.html). Over 240 emm types have been identified and

a good correlation between emm type and M serotype has been reported (106).

The emm gene has been found in all GAS strains and belongs to the emm gene superfamily

comprising genes for immunoglobulin-binding proteins, M-related proteins, and M proteins. In addition

to the emm gene, some GAS strains also present emm-like genes immediately upstream (mrp) and

downstream (enn). These genes are located near the multiple gene regulator of GAS (mga), a

transcriptional regulator that positively controls the expression of several GAS proteins including the M

protein (107, 108). The chromosomal arrangement and presence of the emm and emm-like genes gave

rise to another typing method designated as emm pattern typing that includes five distinct emm patterns

(patterns A-C, D and E) (Figure 5) (104, 109). An association between the emm pattern group and tissue

tropism has been identified, whereby GAS strains of the emm pattern A–C genotype are mostly found

in pharyngitis (throat specialists), emm pattern D isolates are generally associated with impetigo (skin

specialists) and emm pattern E strains are equally found in both tissues (“generalists”) (110, 111).

Additionally, a correlation between emm type and emm pattern has been observed, and the size and

structure of the M protein seems to be associated with the emm pattern (104, 112).

More recently, a new tool for molecular typing of GAS strains based on the sequenced portion of

emm genes encoding the entire surface-exposed region of M proteins has been proposed. The

implementation of this method, designated as emm cluster typing, as a complement to emm typing

provides a possible functional classification of proteins within the same emm cluster based on binding

and structural properties. Therefore, within each emm cluster, the M protein types share a high

sequence similarity and functional properties (113).

The emm typing method is widely used and became the gold-standard for S. pyogenes typing.

However, limitations to this method have been reported, so that it should be complemented with

additional typing methods for an improved identification of GAS clones (93).

Multilocus sequence typing

MLST is a sequence-based typing method based on the determination of the nucleotide

sequences of internal fragments of housekeeping genes amplified by PCR. This method identifies

variations within the multiple housekeeping loci and compares the obtained sequences with a MLST

database with known alleles, thereby generating an allelic profile, which is a series of seven integers

29

corresponding to the alleles at the seven house-keeping loci. Each different profile is assigned with a

number which defines the sequence type (ST) of each isolate. MLST provides portable and

unambiguous data that can be easily validated and compared between different laboratories. The

housekeeping genes encode proteins with essential functions and are, therefore, present in every

organism. Since these genes are evolutionarily slow, this method can be used for evolutionary studies.

Therefore, isolates that are descendants of a recent common ancestor share alleles within the multiple

housekeeping loci and are designated as clones or clonal complexes (94, 114, 115).

The eBURST is an algorithm that identifies the genetic similarity between isolates, allowing the

inference and reconstruction of evolutionary events based on differences between the allelic profile

generated from MLST. This model defines clonal complexes (CCs) composed by isolates sharing 100%

genetic identity at six or seven MLST housekeeping loci with at least one other member of the group.

Within each CC, there is a founding genotype (ST) that increases in frequency in the population and by

gradual diversification, starting with variants in one allele – single-locus variants (SLVs) - and then

progressing to double-locus variants (DLVs), leads to the emergence of clonal complexes. The

hypothetical patterns of descent and the genetic relationships of isolates and STs within each CC are

displayed graphically (115, 116). However, the eBURST is not globally optimized leading to relationships

between STs that may go against the rules implemented by the algorithm itself. Therefore, for a globally

optimized implementation of eBURST, the goeBURST algorithm was developed and the evolutionary

relationships between isolates can be visualized in the PHYLOViZ platform in association with other

relevant data for epidemiological and population studies (117, 118).

In S. pyogenes, the seven housekeeping genes used for MLST are gki (glucose kinase), gtr

(glutamine transporter protein), murI (glutamate racemase), mutS (DNA mismatch repair protein), recP

(transketolase), xpt (xanthine phosphoribosyl transferase) and yqiL acetyl coenzyme A (acetyl-CoA)

acetyltransferase. MLST can further discriminate isolates sharing the same emm type, identifying

clones or clonal complexes more consistently than emm typing alone, and should complement the latter

for an improved discrimination of strains (93, 114).

Superantigen gene profiling

The SAgs are virulence factors intimately involved in the pathogenesis of invasive GAS

infections such as STSS (90). In S. pyogenes, 11 different SAgs have been identified, namely the

streptococcal pyrogenic exotoxins (Spe) A, C, G, H, I, J, K, L and M, the SSA and the SmeZ, with the

majority being phage-encoded except for speG, speJ and smeZ. The chromosomally encoded speG

and smeZ are found in most GAS isolates. The speJ gene, although thought to be part of the bacterial

core chromosome, is located in a region with evidence of recombinatorial events mediated by MGEs

(119-121) and is absent in multiple GAS lineages (122). The identification of prophages and other MGEs

as the major contributors for the variation in gene content observed among GAS isolates highlights the

importance of SAg gene profiling as a typing method and as a marker for the horizontal transfer of

prophages that may carry other virulence genes (84, 123, 124).

SAg gene profiling is a molecular typing method for GAS based on the SAg genes repertoire,

which varies between strains. The detection of the SAg genes is commonly based on a PCR, but

30

discrepancies in the results between different studies may arise from the use of primers that do not

cover all the allelic variants that exist within some SAgs genes (122). SAg gene profiling is used as a

complementary method for the more conventional methods such as emm typing, and a strong

association between SAg profile and emm type has been demonstrated (121, 122). Variations of SAg

profiles within emm types indicates a faster diversification of SAg profiles in comparison with emm type,

highlighting the relevance of this typing method for a better discrimination of GAS clones in

epidemiological studies (99, 122).

Pulsed-field gel electrophoresis (PFGE) macrorestriction profiling

PFGE macrorestriction profiling has long been used as a typing technique for S. pyogenes and

other bacterial species, being especially relevant in outbreak investigations (125-127). The main

advantages of this typing method include high concordance with epidemiological relatedness, excellent

typeability and intra-laboratory reproducibility. However, due to large expenditure of labor and time

required, alternative approaches have been emerging, including HTS-based methods (127, 128).

This method involves the digestion of the chromosomal DNA, using a rare-cutting restriction

endonuclease, which generates macrorestriction fragments. The digested DNA is subjected to gel

electrophoresis with periodical changes in the direction of the electric field, promoting the resolution of

the large restriction fragments. The PFGE profiles obtained for each isolate can be compared using

digital software, and the relatedness between strains is determined based on the number of differences

observed between the profiles (127, 129). The rare-cutting restriction endonuclease generally used to

obtain the DNA restriction patterns for GAS is SmaI, but for macrolide-resistant isolates expressing the

M phenotype and whose DNA is resistant to digestion with SmaI, the use of the isoschizomer Cfr9I is

recommended (130).

PFGE seems to have some advantages for typing of GAS strains since horizontal gene transfer

(HGT) events and phage-mediated diversity, often associated with virulence, play a key role in the

genome diversification of this organism and prophage loss and acquisition leads to increased PFGE

pattern diversity. The relevance of PFGE for further discrimination of GAS clones identified by emm

typing is well documented (93, 124, 131).

High throughput sequencing

In recent years, there have been major improvements in HTS methods accompanied by a

reduction in the respective costs. HTS of bacterial genomes coupled with appropriate bioinformatic tools

to analyze the genomic data has become an accessible technology to reference microbiology, and

comparative genomics has been proposed as a typing method for GAS. The value of HTS as an

epidemiological tool is due to its potential in predicting typing information conventionally obtained from

molecular typing schemes (emm type and ST), but also the possibility to identify the molecular events

leading to changes in the clonal structure in different populations. Therefore, this method can potentially

replace the other typing techniques for epidemiological surveillance and investigation due to the

unambiguous data produced, its high resolution, reduced turnaround times and excellent predictive

value (96, 97, 132).

31

HTS has already been successfully applied in several contexts such as disease surveillance,

outbreak investigations and tracing of the evolutionary and molecular events leading to the emergence

of certain clones (98, 133). In Switzerland, a suspected outbreak of severe S. pyogenes disease was

studied using HTS, which produced fast results that allowed the exclusion of the occurrence of a clonal

outbreak (134). In Canada, 601 emm59 GAS strains genomes were sequenced in order to identify the

geographic dissemination patterns of an emergent and hypervirulent emm59 clone, genetically distinct

from other emm59 GAS strains. This study identified the spread of this distinct emm59 Canadian

epidemic clone into the United States (135). Additionally, HTS has been used for a comprehensive

analysis of the evolutionary events responsible for the emergence of the M1T1 clone and the new

emergent emm89 clade (98, 132). More recently, HTS was used to identify an outbreak of nosocomial

infections in France caused by the epidemic emm89 clade (136).

Taking all together, HTS seems to be an increasingly feasible typing method for bacterial

strains, providing further insight regarding the pathogenicity and evolution of the pathogen. However,

high-quality and well-curated databases are of paramount importance for an accurate and broad use of

the data provided from the genome sequences. Additionally, the development of bioinformatic pipelines

is essential in order to correctly handle the large amount of data generated through these methods (96).

Molecular Epidemiology of Strains of Streptococcus pyogenes Isolated from Human Infections

in Portugal

S. pyogenes infections are a public health concern worldwide, with the burden of GAS-related

morbidity and mortality being far superior in low-income countries than in developed nations (137).

However, the lack of surveillance systems, especially in developing countries, leads to an increased

difficulty in accurately measuring the global burden of GAS infections (92). Taking all into consideration,

it is clear that global surveillance of this pathogen is essential and the recent improvements in HTS

provide the means to accurately and effectively detect changes in the disease pattern within different

populations and further understand the evolution and emergence of strains (96, 132).

In developed countries, pharyngitis and invasive disease are the most relevant GAS clinical

manifestations. Similarities in emm type distribution are observed in these countries, with emm1

appearing as the dominant emm type in most high-income countries (92, 99, 138, 139). Furthermore, a

correlation between emm type and disease manifestation has been reported, with emm types 1, 3, 28

and 89 being commonly associated with invasive disease (99, 131, 138-146), and emm types 4 and 12

being reportedly associated with pharyngitis (131, 138, 147, 148). The available literature regarding

SSTI presents considerable variations in the distribution of emm types, with emm types 1, 12, 28, 77

and 89 being reported in studies concerning different types of SSTI and time periods (146, 149-153). In

the mid-1980s, a resurgence of invasive infections caused by GAS was reported and this occurrence

was associated with the emergence of a highly successful M1T1 clone (91, 154). In contrast, in

developing and tropical countries, a greater diversity of emm types without the predominance of one in

particular is observed. Additionally, the emm types profile is distinct from the one observed in the

developed world, presenting M types not commonly found in high-income countries (92).

32

The epidemiological study regarding GAS isolates associated with either invasive or pharyngeal

disease during 2000-2005 in Portugal found a high genetic diversity among the population analyzed,

with the majority on the isolates belonging to clones equally distributed between both disease

manifestations. The most prevalent clone, with a frequency of 18%, was a macrolide-susceptible emm1-

T1-ST28 clone, carrying the SAg genes speA, speG, speJ and smeZ. This clone along with an emm64-

ST161 clone that did not carry any phage-encoded SAg, was overrepresented among isolates

associated with invasive disease in comparison with pharyngeal isolates. In contrast, the emm4-T4-

ST39 clone was associated with pharyngitis and emm4, emm75 as well as SAg genes speC, ssa and

speL/M were identified as markers for pharyngeal disease (131).

The epidemiological surveillance of GAS isolates associated with invasive disease in Portugal

during the time period of 2006 to 2009 identified, once again, the emm1-T1-ST28 clone as the dominant

lineage and emerging as the second most prevalent clone was the emm89-TB3264-ST101 clone. In

contrast, the emm64-ST161, which was previously identified as being significantly associated with

invasive disease, had a low frequency among GAS isolates in the time period of 2006-2009. A lower

diversity of emm and PFGE types accompanied by a contrasting diversification of SAg profiles, with

statistical significance, for emm1 - the dominant emm type - and the emm types 28 and 44 was reported.

This intra-emm type SAg profile diversification was associated with the acquisition and loss of phage or

chromosomally encoded SAg genes, supporting the importance of horizontal gene transfer events as a

driving force behind the genomic diversification of S. pyogenes, which may lead to the emergence and

persistence of highly successful clones (99, 123). The epidemiological study concerning isolates

recovered from SSTI in Portugal identified emm89 as the most prevalent emm type, with only emm89

isolates lacking the hasABC locus being significantly associated with SSTI relative to invasive infections

between 2005 and 2009. In this study, both emm1 and emm3 were overrepresented among invasive

isolates when compared with SSTI isolates (146).

The rates of macrolide resistance display large asymmetries worldwide. The major resistant

clones circulating in Europe and frequently associated with the M phenotype are the emm12-ST36,

emm4-ST39 and emm1-ST28, while the lineages typically associated with the MLSB phenotype are

emm22-ST46, emm11-ST403, emm28-ST52 and emm77-ST63 (130, 131, 155-158). In Portugal, two

PFGE clusters, associated with macrolide susceptibility or resistance, were found in emm4-ST39 and

emm1-ST28. These lineages and their association with macrolide susceptibility/resistance were not

distinguished by MLST and emm typing data, which suggests that other genetic characteristics may

account for the differences observed (159). The association between high macrolide consumption and

antibiotic resistance has been observed (160). In Europe, however, a declining trend in resistance rates

has been reported and, in some countries, this was not accompanied by a decrease in macrolide

consumption (36). In Portugal, a continuous decline in macrolide resistance due to a decrease in the

clones that comprised for the majority of the resistant isolates, without a significant change in the pattern

of macrolide consumption, was described (156, 161). These results indicated that, besides macrolide

consumption, fluctuations in clonal composition within a population may also account for the changes

in the prevalence of resistant isolates (159).

33

Streptococcus pyogenes Genomics

The first complete GAS genome, belonging to an M1 strain, was reported in 2001 (162). To

date, 116 complete genome sequences and over 300 projects of whole-genome sequencing are publicly

available (https://www.ncbi.nlm.nih.gov/genome/genomes/175, accessed on September 23rd 2018).

The mean G+C content is 38.5% and the size of the complete genomes ranges between 1.70 Mb and

1.95 Mb. The recent advances in HTS provided the tools for the recent, large-scale, comparative

genome studies, such as the one involving 3 615 genomes of serotype M1 strains (98). The Sequence

Read Archive (SRA) on NCBI is a repository of raw sequencing data and alignment information retrieved

from HTS methods. The raw sequencing data of 24 891 strains of S. pyogenes is currently available on

SRA (https://www.ncbi.nlm.nih.gov/sra/?term=streptococcus+pyogenes, accessed on September 23rd

2018).

MGEs, namely prophages, contribute to the genomic variability of GAS, with around 10% of the

gene content being encoded on exogenous genetic elements that constitute a portion of the accessory

genome of several strains (163, 164). Recombination events involving MGEs have been identified as

the basis for the emergence of clones with enhanced virulence, since these elements are often

associated with resistance determinants (e.g. erm and mef genes), exotoxins such as most SAgs, and

enzymes (e.g. DNases). The dynamics and distribution of emm types can undergo some remodeling

over time and space, with the emergence and dissemination of clones or clades being reported (98,

132, 154). The global persistence of the M1T1 clone encouraged the development of several studies to

understand the underlying molecular events leading to the rise and persistence of this clone. These

studies demonstrated that the evolutionary pathway of the pandemic M1T1 clone included the

sequential acquisition of prophages encoding DNase SdaD2 and SAg SpeA2 variant (Figure 6) (84, 98).

Besides its role as superantigen, the variant SpeA2 allele possibly allowed this strain to overcome herd

immunity since the host lacked SpeA2-neutralizing antibodies (165). Following the phage-acquisition

events, a horizontal gene transfer event occurred involving a homologous recombination of a 36 Kb

chromosomal region comprising an nga-ifs-slo promotor variant with two single-nucleotide

polymorphisms (SNPs) acquired from an M12 strain (Figure 6). This led to an enhanced production of

both NADase and SLO (84, 98, 132). This recombination event was also responsible for the reversion

of a nonsynonymous SNP in the nga gene, allowing for the production of an enzymatically active form

of the NADase toxin (132).

During the decade of 2000, the emergence and dissemination of a successful clade within

emm89 (designated as clade 3), which rapidly displaced previously circulating emm89 clades (known

as clade 1 and 2), has been reported in different countries, including Portugal. The emergence of the

successful clade 3 seems to have occurred in the early 2000s and rapidly disseminated in at least two

continents around 2007-2009 (46, 132, 166-168). The emergent clade-associated strains suffered a

genomic remodeling characterized by the loss of the hasABC locus and acquisition, possibly from emm1

or emm12, of a variant nga-ifs-slo locus, leading to the phenotypic traits of absence of hyaluronic acid

capsule and increased production of NADase and SLO, respectively. The three clades identified within

emm89 are associated with variants of the nga promoter sequence (132). The loss of the hasABC locus

in clade 3 does not seem to be determinant for a significant decrease in capsule production, since clade

34

2 strains were reported to have already weak transcription levels of this locus (168). The acquisition by

homologous recombination of an nga-ifs-slo locus variant was similar to that observed for the pandemic

M1T1 clone leading, in both cases, to an increased NADase and SLO production in comparison to their

ancestors (Figure 6) (46, 132, 166, 167). The acquisition of this nga-ifs-slo locus variant is therefore

currently considered as a major molecular event triggering the virulence and/or transmissibility of GAS

clones (132).

Figure 6. Molecular events leading to the emergence of the highly successful M1T1 clone and the recently emerged

emm89 clade 3. The pandemic M1 clone acquired the phage encoded NADase sdaA2 and SAg SpeA. Additionally,

both the M1 clone and the new M89 clade horizontally acquired a variant nga-ifs-slo locus that lead to an increased

expression of NADase and SLO. The emergent emm89 clade also lost of the hasABC locus encoding the capsule

biosynthesis genes. Adapted from (43).

35

AIM OF THE STUDY

The dynamics of GAS populations is complex, presenting considerable geographic and

temporal variations, with several reports on the emergence and dissemination of virulent or successful

clones being found in the literature (46, 135, 154). It is of utmost importance to understand the

mechanisms responsible for the clonal changes in different populations and the particular association

of certain clones with different types of infection.

In the mid to late 1980s, an increase in the incidence of invasive disease caused by GAS was

reported in North America and in Europe, that was frequently linked to a specific M1T1 clone (91, 98,

154). In Portugal, previous epidemiological studies demonstrated a diverse population of GAS, with

some clones being significantly associated with specific types of infection. The macrolide-susceptible

emm1 clone (emm1-EryS) was overrepresented in invasive disease when compared with both

pharyngitis (131) and SSTI (146), and emm3 was significantly associated with invasive infections

relative to SSTI in Portugal (146). The association between the emm1 and emm3 clones and invasive

disease has been previously reported in different countries (131, 139, 143, 145). The macrolide-

susceptible emm4 clone (emm4-EryS) was found to be associated with pharyngitis and may display a

reduced ability to cause invasive disease, while the macrolide-resistant clone (emm4-EryR) was equally

prevalent in pharyngitis and invasive infection. The distinction between the emm4 clones (susceptible

and resistant to erythromycin) was only achieved through PFGE, with other methods such as MLST and

emm typing failing to do so, indicating that some genetic characteristics may account for the phenotypic

differences observed between the two lineages (131). The emm89 clone became the second most

prevalent clone associated with invasive infection in Portugal during the time period of 2006 to 2009

(99). The emergence of a successful clade within emm89 (clade 3, lacking the hasABC locus - emm89-

hasABC-) that replaced the previously circulating clades 1 and 2, both harboring the hasABC locus

(emm89-hasABC+), was reported in several countries such as the USA, Finland, United Kingdom, and

Portugal, and has been linked to the increase in the proportion of emm89 in infection (46, 132, 166-

168). In Portugal, this clade was significantly associated with SSTI when compared to invasive disease

(146).

Having in consideration these six clones identified in the GAS population in Portugal (emm1-

EryS, emm3, emm4-EryS, emm4-EryR, emm89-hasABC+ and emm89-hasABC-), it is now of interest

to identify genotypic and phenotypic characteristics, including the extracellular activity level of several

GAS virulence factors, that may contribute to the preferential association of the clones with different

types of infection. This is the aim of the research that integrates the present thesis, which has the

following goals:

• Isolation and purification of genomic DNA from 320 isolates of S. pyogenes, belonging to the

six clones of interest previously identified, using a commercial DNA extraction kit;

• Production of draft genomes through de novo assembly methods;

• Comparative analyses of the draft genomes using gene-by-gene methods;

• Construction and visualization of a minimum spanning tree (MST) using a cgMLST (core

genome MLST) schema;

36

• Genomic analysis of the GAS population and selection of isolates representative of the genetic

diversity within each clone to be included in future phenotypic studies.

• Optimization of laboratory assays for in vitro quantification of the extracellular activity of SLO

and streptokinase, so as to include these key GAS virulence factors in subsequent phenotypic

studies.

37

MATERIALS AND METHODS

Bacterial strains and culture conditions

For genomic characterization, the 320 GAS isolates were selected from a larger collection of

607 isolates recovered from human infections in Portugal, belonging to six clones of interest. The

selection was performed in order to include half of the isolates from each clone, in a minimum of 10 per

clone, and to represent the diversity of genotypes and phenotypes within each lineage according to

previously obtained data (99, 131, 146, 167, 169) (Tables S1 and S2).

Strains used for optimization of the SLO and streptokinase activity assays are listed in table 1

and were chosen so as to include strains with different emm types and NADase activities, as previously

determined. These strains correspond to isolates recovered from human infections in Portugal that were

included in previous epidemiological studies (61, 99, 131, 146, 167, 169). Strains SF370, obtained from

Colección Española de Cultivos Tipo (CECT 5109) and MGAS5005, obtained from American Type

Culture Collection (BAA-947), were used as controls. The strains were first cultured on Tryptone Soya

Agar (TSA) (Oxoid, Basingstoke, UK) supplemented with 5% defibrinated sheep blood (Probiológica,

Lisbon, Portugal) and then one colony of each strain was cultured in 5 mL of Todd Hewitt Broth (THB)

(BD, Sparks, MD, USA), and grown at 37ºC for 24 hours without shaking.

Table 1. Relevant genotypic (emm type) and phenotypic (NADase activity) characteristics of the strains used for

optimization of the SLO and streptokinase activity assays.

High throughput sequencing

Genomic DNA extraction of the 320 GAS isolates for HTS was performed using Invitrogen

Purelink Genomic DNA extraction kit (Thermo Fisher Scientific Inc., Waltham, MA, USA) according to

manufacturer’s instructions with small modifications. These modifications include the addition of 75 U of

mutanolysin (Sigma-Aldrich, St. Louis, MO, USA) and 86 μg of hyaluronidase (Sigma-Aldrich, St. Louis,

MO, USA) to the lysozyme digestion buffer, and the addition of 400 μg of RNAse (kit) with an incubation

at room temperature (RT) for 2 minutes after proteinase K treatment. Nucleic acid purity was assessed

by the 260/280 nm and 260/230 nm absorbance ratios, measured on a NanoDrop 2000

Spectrophotometer (Thermo Fisher Scientific Inc., Waltham, MA, USA). The DNA integrity was

evaluated by gel electrophoresis and the nucleic acid concentration was determined using the Invitrogen

QubitTM dsDNA HS assay kit (Thermo Fisher Scientific Inc., Waltham, MA, USA).

Strain Genotypic and phenotypic characteristics

1 SF370 pre-epidemic emm1; NADase ≤3

2 MGAS5005 contemporary, epidemic emm1; NADase=192

3 2004V1257P emm89-hasABC-; NADase ≤3

4 2003V0731P emm89-hasABC+; NADase=12

5 2003V1300P emm89-hasABC+; NADase ≤3

6 2001V1236P emm1; NADase=192

7 2005V1791P emm3; NADase=96

8 SH1066A emm44; NADase=48

9 SH0759A emm89-hasABC+; NADase=12

10 2001V0953P emm1; NADase=24

38

HTS libraries were prepared using paired-end Nextera® XT DNA Library Prep Kit, Index Kit v2

(Illumina©, San Diego, CA, USA) and sequenced on Illumina NextSeq® 500 system (Illumina©) using

NextSeq® 500/550 Mid-Output v2 Kit (300 cycles) at Instituto Gulbenkian de Ciência, Gene Express

Unit (Oeiras, Portugal). From the 320 isolates whose DNA was extracted and submitted for sequencing,

raw sequencing data was received for 319 samples. The quality of paired-end reads obtained was

assessed with the INNUca pipeline (https://github.com/B-UMMI/INNUca), which was also used for de

novo assembly and curation of the bacterial genomes. INNUca v3.1 was run using Docker image

“ummidock/innuca:3.1” (https://hub.docker.com/r/ummidock/innuca/) providing Nextera XT adapter

sequences for adapter removal using --adapters option and a predicted genome size of 2 Mb. Briefly,

read quality was checked with FastQC (https://www.bioinformatics.babraham.ac.uk/projects/fastqc/)

and cleaned using Trimmomatic (170). De novo assembly was performed using SPAdes (171) and

subsequently polished using Pilon (172). To determine the ST, the Innuca pipeline uses the mlst

software (Seemann T, mlst Github https://github.com/tseemann/mlst) developed by Keith Jolley (173)

and sited at the University of Oxford (the development of PubMLST website was funded by the

Wellcome Trust), which uses the PubMLST database (https://pubmlst.org/).

The obtained draft genomes were annotated with Prokka pipeline v1.12 (174) using Docker

image “ummidock/prokka:1.12” (https://hub.docker.com/r/ummidock/prokka/). SignalP v4.1 (175), used

to find signal peptide features in CDS, and RNAmmer v1.2 (176), used to find ribosomal RNA features,

were externally provided to the Docker container. Prokka was run using a genus database created with

S. pyogenes complete genomes available through NCBI at 24/10/2017, using the following parameters:

--addgenes --usegenus --rfam --rnammer --gram pos --increment 10 --mincontiglen 1 --gcode 11 --

kingdom Bacteria --genus Streptococcus --species pyogenes.

The nga gene promoter variant was determined using an assembly-based analysis with a

BLAST search approach. The spyogenes_nga_promoter_variant.py script was used for this purpose

with the reference spyogenes_nga_promoter_variant.CP000017_nga_promoter.fasta sequence that

can be found at https://github.com/miguelpmachado/randomScripts/. The bioinformatic analysis was

performed by the bioinformatics group of MRamirez lab.

Gene-by-gene analysis and genetic relationships between isolates

The gene-by-gene analysis of the draft genomes of the 319 GAS isolates was performed using

ChewBBACA (177). Firstly, a whole genome MLST (wgMLST) schema was created with the complete

genomes of S. pyogenes, S. dysgalactiae subsp. equisimilis (SDSE) and S. dysgalactiae subsp.

dysgalactiae (SDSD) available on NCBI (64 GAS, 5 SDSE and 1 SDSD). Allele calling was performed

with the wgMLST schema (3533 loci) followed by a second allele calling on the 319 draft genomes of

the GAS isolates. In the next step, paralog detection identified 89 paralogs and these loci were removed.

The number of loci found in all draft genomes was 1193 and these represent the cgMLST schema for

the selected strains. The gene-by-gene analysis was performed by the bioinformatics group of

MRamirez lab. The cgMLST schema was used to generate an allelic profile for each of the 319 GAS

draft genomes for further analysis. To evaluate the genetic relationships between strains, a network-

based approach using an extension of the goeBURST (goeBURST full MST algorithm) that generates

39

an MST implemented in PHYLOVIZ online (118, 178) was used. These results were integrated with

other relevant data for epidemiological studies, such as year of isolation, disease manifestation, emm

type, ST, macrolide resistance phenotype, presence of the has locus and nga promoter variant.

Bacterial growth curves

For determination of the growth curves of the tested strains, these were grown in 5 mL of THB

for 24h at 37ºC without shaking and then 0.5 mL of each culture was diluted in 4.5 mL of fresh THB

(1:10) for an initial OD6000.10. Cultures were grown in a 37ºC water bath and the OD600 was measured

every 15 min until stationary phase. For each strain, internal duplicates and three independent assays

were performed. The OD600 values were plotted against time. The strains for which the growth curves

were performed are listed in table 1 and the resulting curves are presented in supplementary figure 6.

The obtained results were used to determine the OD values representative of the mid-exponential phase

(OD600=0.80) and of the late-exponential phase (OD600=1.10).

Optimization of streptolysin O activity determination assay

The assay for determination of SLO activity was performed using an endpoint titer method

based on a previously optimized assay for SLS (61) with adaptations previously described for SLO

activity assay (83, 179). The assay was performed in both stationary and late-exponential growth phase.

For the stationary phase assays, the 24h cultures were diluted 1:10 in fresh THB and incubated for 18h

at 37ºC. For late-exponential phase assays, the 24h cultures were diluted 1:10 in fresh THB and

incubated in a 37ºC water bath until late-exponential phase of growth (OD600=1.10) was reached. Two

control wells were incubated with sterile THB. The cultures were then centrifuged at 3220xg for 10 min

and the bacteria-free supernatants or sterile THB (blank) were preincubated with 4 g/mL or 40 g/mL

(the final concentration chosen was 40 g/mL) of trypan blue (Sigma-Aldrich, St. Louis, MO, USA) to

inhibit SLS activity, and 4, 10, 20 or 50 mM (the final concentration chosen was 10 mM) of dithiothreitol

(DTT) (Sigma-Aldrich, St. Louis, MO, USA) to stabilize SLO, at 37ºC for 30 min or at RT for 10 min (the

final preincubation condition chosen was 37ºC for 30 min). The supernatants were serially diluted in

phosphate-buffered saline (PBS) and three dilution series were tested: 1/2, 1/4, 1/8, 1/16, 1/32, 1/64,

1/128; 1/3, 1/6, 1/12, 1/24, 1/48, 1/96, 1/192; and 1/3, 1/4, 1/6, 1/8, 1/12, 1/16, 1/24. The supernatants

or the blank solution (negative control - 0% hemolysis) were incubated with an equal volume of a 2.5%

(v/v) suspension of sheep erythrocytes for 30 or 60 min at 37ºC (the final incubation time chosen was

30 min). The suspension of sheep erythrocytes was prepared by centrifuging 10 mL of fresh defibrinated

sheep blood (Probiológica, Lisbon, Portugal) at 650xg for 10 min at 4ºC. The pelleted cells were washed

twice with sterile PBS and finally resuspended in PBS for a final concentration of 2.5% (v/v). Two

hemolysis positive controls 1% TritonTM X-100 (Sigma-Aldrich, St. Louis, MO, USA) and two

corresponding blanks with PBS were included. The microplate was then centrifuged at 3000xg for 5 min

to pellet the erythrocytes and the absorbance at 570 nm of the supernatants was measured in a

microplate reader Infinite® M200 (TECAN, Switzerland). Additionally, the SLO assays were performed

in the presence of 25 or 50 μg/mL water-soluble cholesterol (Sigma-Aldrich, St. Louis, MO, USA) to

confirm that SLS, as expected, does not contribute to the hemolytic activity observed in the assays

40

performed under these conditions (the final concentration chosen was 50 μg/mL). The SLO activity was

determined according to the hemolysis observed in each well. For each dilution, the percentage of

hemolysis relative to the positive control was calculated using formula (1), where the absorbance of the

corresponding blank solution, the positive control and the PBS blank are calculated as the mean of the

absorbance of the two wells corresponding to each of these conditions:

Abs570sample − Abs570blank corresponding dilution

Abs570positive control − Abs570PBS blank× 100

(1)

The SLO activity was defined as the inverse of the highest dilution before the percentage of

hemolysis decreased to half or less. The detection limit was either 2 or 3, depending on the dilution

series, and when a two-fold decrease was not observed the streptolysin activity for the corresponding

strain was considered 2 or 3, respectively. For each strain, three independent assays and intra-

assay duplicates were performed to control for intra- and inter-assay variability. The majority rule was

used to determine the final streptolysin activity value. The protocol can be found in the supplementary

data.

Optimization of streptokinase activity determination assay

The assay for determination of streptokinase activity was performed using an indirect

plasminogen activation assay with a plasmin-specific chromogenic substrate S-2251TM (Chromogenix,

Instrumentation Laboratory Company, USA), as previously described (71, 180, 181). Briefly, 24h

cultures were diluted 1:10 in fresh THB and grown to late-exponential (OD600=1.10) or mid-exponential

phase (OD600=0.80) in a 37ºC water bath. For stationary phase assays, 24h cultures grown in a 96-well

microplate were diluted 1:10 in fresh THB and incubated for 18h at 37ºC. Negative controls with sterile

THB were included. The cultures were centrifuged at 3220xg for 10 min and the bacteria-free

supernatants or sterile THB (blank) were added to Tris 50 mM, pH 7.5. Glu-plasminogen (Merck

Millipore, Burlington, MA, USA) preincubated at 37ºC for 15 min with human fibrinogen (Merck Millipore,

Burlington, MA, USA) in a 1:1 stoichiometric ratio was then added to the mixture to a final concentration

of 220 or 500 nM (an assay without fibrinogen was also performed), followed by the chromogenic

substrate S-2251TM, to a final concentration of 500 M. The addition of the chromogenic substrate was

performed with the plate on ice. The plate with the reaction mixture was incubated at 37ºC in a microplate

reader Infinite® M200, and the plasmin activity was monitored by measuring the absorbance at 405 nm

every minute, for 120 min. Three independent assays were performed for each strain as well as intra-

assay duplicates to control for intra- and inter-assay variability. Additionally, two internal positive controls

of a known concentration of commercial group C streptokinase (Sigma-Aldrich, St. Louis, MO, USA)

were used to control the variability between assays and standard curve. The assays were

simultaneously performed in the absence of plasminogen to control for unspecific hydrolysis. The

streptokinase activity rates of each strain were determined from the slope of the linear portion of the

curve obtained from plotting absorbance against time. A standard curve of group C streptokinase was

performed under the same assay conditions of the activity determination assays using serial dilutions of

41

commercial streptokinase from 1000 units/mL to 0.49 units/mL. The standard curve is used to convert

the slope values obtained for each strain into streptokinase activity (units/mL). The protocol can be

found in the supplementary data.

42

43

RESULTS AND DISCUSSION

Genetic relationships between isolates

The genomic analysis was performed for only 319 of the 320 isolates whose raw sequencing

data was available within the time scope of the study. The genetic relationships between the isolates

were visualized in the online PHYLOViZ platform (118, 178) using the allelic profiles generated from the

gene-by-gene analysis of the draft genomes. For this analysis, a cgMLST schema was established

based on the 1193 loci identified in all 319 isolates. This represents a limitation of this method, since it

excludes information derived from prophages and other MGEs that represent a significant part of the S.

pyogenes genome. The importance of MGEs in GAS arise from their association with resistance

determinants (e.g. erm and mef genes), exotoxins such as most SAgs, and enzymes (e.g. DNases) that

play key roles in the biology of the pathogen (107).

The initial analysis of the 319 isolates of S. pyogenes under study produced an MST generated

by the goeBURST full MST algorithm with a maximum link distance of 1075 (Figure 7A). It was possible

to observe a clustering of the isolates according to emm type, with nodes belonging to the same emm

type being grouped together. The exceptions were two emm4 isolates, SH7089A and SH1749A, that

were linked to emm1 nodes displaying, however, a high genetic distance to these nodes (1072 and

1052, respectively). These distances were comparable to those observed between nodes of different

emm types. The maxium distance observed between isolates belonging to the same emm group was

aproximately 56 for emm1 group, 115 for emm3 group, 176 for emm4 group (excluding the two emm4

nodes previously mentioned) and 241 for emm89 group. Therefore, as previously reported, the genetic

distance between strains sharing an emm type is, in general, relatively low in comparision to that of

isolates of any two different emm types (107). When the links between nodes with profiles with 1052 or

more differences were deleted, it was possible to observe four different groups separated according to

emm type and the two emm4 isolates previously linked to emm1 nodes became isolated (Figure 7B).

The computation of the distance matrix for each group (plotting all vs all distances between nodes) gives

a general view of the genetic distance between isolates of the same emm type (excluding the two emm4

isolates that failed to be grouped with the other emm4 isolates) (Figure S1). The emm1 isolates share

a close genetic relationship, in agreement with the low genomic diversity within emm1 observed in a

previous study using core chromosomal SNPs (98). For the other emm types, there was one isolate

presenting a higher genetic distance in comparison with the overall scenario (Figure S1A). For emm4,

this isolate (SH0264A) was a macrolide-resistant isolate genetically distant from the other nodes

belonging to the emm4 erythromycin-resistant group. The emm89 distant node (2002V1366P)

corresponds to the single emm89 isolate harboring the nga promoter variant 1, as discussed below. By

excluding these isolates that introduce increased genetic distance within each emm group, it was

possible to observe that emm4 and emm89 present the highest genetic distances (maximum distance

of 96 and 92, respectively) (Figure S1B). For emm89, extensive genomic diversity has been reported

elsewhere (168). However, within emm89, there is a group of isolates that appear to be more closely

related. These isolates lack the hasABC locus, corresponding to clade 3 and will be further analyzed.

44

Figure 7. MST generated by the goeBURST full MST algorithm for the 319 GAS cgMLST dataset. A: The maximum

link distance of the tree is 1075 and the colors represent the emm types: emm1 (blue); emm89 (red); emm3 (green);

emm4 (yellow). The size of the nodes is proportional to the number of isolates included in each node and the link

distances between groups (from a total of 1193 compared loci) are shown. In general, the nodes corresponding to

the same emm type are grouped together. The exceptions are two emm4 strains (SH7089A and SH1749A) that

are linked to emm1 nodes but with a high distance (comparable to the one between groups) of 1072 and 1052,

respectively. B: The links between nodes with profiles with 1052 or more differences (tree cut-off) are deleted and

four groups are created that are in agreement with emm type. The two strains from emm4 previously linked to emm1

became isolated.

In the analyzed dataset, 15 different STs were identified, with no single ST being associated

with more than one emm type (Figure 8). The emm1 isolates presented three different STs, namely

ST28 (accounting for 95% of the emm1 isolates;), and ST643 (3%) and ST830 (2%), which are both

SLVs of ST28 (Figure 8A). The results obtained for emm1 are congruent with previous reports indicating

ST28 as the lineage globally associated with this emm type (92, 99, 138, 139). The emm3 isolates were

associated with three STs, namely ST15 (55%), ST406 (30%) and ST315 (15%) (Figure 8B). These

STs are SLVs of each other and are commonly reported for emm3 (182). Regarding emm4 isolates,

four distint STs were present: ST39 (the predominant lineage; 93%), ST823 (2%), ST38 (2%) and ST771

(2%), with one isolate being associated with an undefined ST characterized by a new MLST allelic profile

gki(138)-gtr(2)-murI(3)-mutS(5)-recP(51)-xpt(3)-yqiL(1) (Figure 8C). The ST39 is frequently

associated with emm4 (143, 159) and STs 823 and 38 are SLVs of ST39. The two emm4 strains that

failed to be grouped within the isolates sharing the same emm type could represent the result of an

emm type switching event or a diversification within the emm4 lineage. The identification of emm type

switching has been previously reported (143), and HGT of the emm4 gene to a new genetic background

may be responsible for the genetic distance observed between these two isolates and the rest of the

emm4 nodes. However, both of these strains may have also resulted from a gradual long-term

diversification of an emm4 strain. One of these isolates (SH1749A) is associated with ST771, which was

previously reported in association with emm4 in the S. pyogenes MLST database

A

Tree cut-off: 1052

B

1069

1052

1072

1068

1075

SH7089A

SH1749A

emm type

1

89

3

4

emm1 emm3

emm89 emm4

Maximum link distance: 1075

45

(https://pubmlst.org/spyogenes/), in agreement with our data. The visualization on PHYLOViZ 2.0 of the

publicly available MLST data shows that ST771 integrates a heterogenous CC that includes STs of

strains associated with emm102 (ST376 and ST895, which are SLV and DLV of ST771, respectively)

and with emm114 (ST220 and ST401, both DLVs of ST771) (Figure 9A). The other isolate (SH7089A)

is, as mentioned above, associated with an undefined ST characterized by a new MLST allelic profile.

The addition of this new allelic profile to the available MLST dataset and subsequent analysis

demonstrated that this ST is a singleton at the SLV level and ST89 is its only DLV. ST89 is mostly

associated with emm94 but has also been reported in association with emm12 and emm13 strains.

Figure 8. MST generated by the goeBURST full MST algorithm at a tree cut off of 1052 that allows a separation of

strains according to emm type. Isolates are colored by ST within each emm type. The size of the nodes is

proportional to the number of isolates included in each node. A: emm1 isolates – ST28 (dark blue); ST643

(intermediate blue); ST830 (light blue). B: emm3 isolates – ST15 (dark green); ST406 (intermediate green); ST315

(light green). C: emm4 isolates – ST39 (brown); ST38 (dark yellow); ST771 (light yellow); ST823 (orange); - (gray)

– ST not defined; the black rectangles group erythromycin-susceptible and -resistant isolates; D: emm89 isolates –

ST101 (dark red); ST408 (red); ST824 (dark pink); ST568 (light pink); ST407 (purple); - (gray) – ST not defined; the

black rectangles group the isolates harboring the hasABC locus (hasABC+) and lacking the hasABC locus

(hasABC-). An undefined ST represents a ST with alleles or an allelic profile that are not yet described: emm4 strain

SH7089A has a new allelic profile; emm89 strain SH6140A has a new gki allele and the other two strains, SH9212A

and SH11927A, have a new recP allele that is the same for both.

28

643

830

101

408

824

15

406

315

39

38

771

823

-

emm1 emm3

emm89emm4

A B

C D hasABC+

hasABC-

Erythromycin-susceptible

Erythromycin-resistant

568

407

-

new recP allele

new gkiallele

new allelic profile

ST ST

ST

ST

46

For emm89 isolates, five different STs were identified: ST101 (58%), ST408 (24%), ST824

(11%), ST568 (2%), and ST407 (1%). In this group there were three isolates with an undefined ST -

SH6140A, SH9212A, and SH11927A. Isolate SH6140A has a new gki allele, while the other two isolates,

which are linked in the tree, have a new recP allele that is the same for both (Figure 8D). Therefore, for

emm89, two new STs have been identified. The addition of these STs to the publicly available MLST

data and visualization on PHYLOViZ 2.0 (118) shows that both STs integrate the ST101 CC. The ST

with a new gki allele is an SLV of ST824 and a DLV of ST101, while the other ST, harboring the new

recP allele, is an SLV of ST101 (Figure 9B).

Figure 9. Clonal complexes defined by goeBURST and visualized on PHYLOViZ 2.0. A: ST771 (associated with

emm4 isolate SH1749A genetically distant from the other emm4 isolates) is associated with emm type 4 (yellow) in

the S. pyogenes MLST database and integrates a CC that includes STs of strains associated with emm102 (green)

and with emm114 (blue). B: Addition the two STs associated with three emm89 hasABC- isolates into the public

MLST data available. The ST with a new gki allele (STY) - associated with isolate SH6140A - is an SLV of ST824

and a DLV of ST101. The ST harboring the new recP allele (STZ) - associated with isolates SH9212A and

SH11927A - is an SLV of ST101.

It is of interest to evaluate the distribution landscape of the isolates in the MST of the cgMLST

dataset so as to understand if any grouping according to type of infection occurs within each emm type.

For emm4, no particular pattern is observed, while for emm1, emm3 and emm89, isolates recovered

from pharyngitis seem to be underrepresented in some of the tree branches (Figure S2). However, this

pattern is most likely a result of the temporal distribution rather than the type of infection, since in this

dataset there are no pharyngitis isolates recovered after 2005 (Figure S3). This suggests that the overall

genomic characteristics within the core genome do not allow to differentiate strains based on the type

of infection from which they were recovered. The selection of strains for genomic analysis was

performed so as to maximize the diversity within the six clones of interest previously mentioned and

associated with each type of infection and was therefore not geared for this type of comparison. Further

771

emm type

4

102

114

A B

376

895220

401

: new ST with new recP allele STZ

: new ST with new gki allele STY

47

studies are required to understand if any particular phenotypic or genotypic characteristics are

responsible for the association of certain clones with disease manifestation.

In recent years, the emergence of an emm89 clade that quickly outcompeted previously

circulating emm89 clades was reported in the United States, Finland, Portugal, and the United Kingdom

(46, 166, 167, 183). Three distinct phylogenetic groups within emm89 have been reported, namely clade

1, 2 and 3, with the latter being associated with an increase in the prevalence of emm89 in infection (46,

166). The emergence of this clade resulted from a recombination event involving the acquisition of an

nga-ifs-slo locus variant, similar to that observed for the pandemic M1T1 clone in the mid 1980s, which

highlights the possible importance of this molecular event in the emergence of successful GAS clones

within a population (132). In this study, the genetic relationships and population structure of emm89

isolates, including isolates carrying the hasABC locus and isolates lacking the hasABC locus, as

previously determined (167), was analyzed. The MST of the cgMLST dataset obtained presented a

clustering of the isolates according to the presence or absence of the hasABC locus (Figure 10A). Three

major clades are observed (clades 1, 2 and 3), each associated with an nga promoter variant (1, 2 and

3, respectively), as reported elsewhere (132, 183, 184). Clade 3 seems to have emerged from clade 2

and all strains harboring the variant 3 promoter lacked the hasABC locus, in agreement with previous

findings (Figure 10B) (46, 132, 166-168). Only one isolate harboring variant 1 was found (2002V1366P)

and this isolate presents the highest genetic distance within the emm89 group (Figure 10B and Figure

S1). In addition, this was the only isolate presenting ST407 (Figure 8D). ST407 (as well as ST803) was

previously identified as the predominant lineage in the USA before the emergence of the new clade,

being less frequently found in European countries. Therefore, the herein obtained results are congruent

with previous findings (167, 184).

Figure 10. MST generated by the goeBURST full MST algorithm for isolates of emm89 and analysis of the presence

according to the hasABC locus and the nga promoter variant. The size of the nodes is proportional to the number

of isolates included in each node and the link distances between clades (from a total of 1193 compared loci) are

shown. A: Dataset colored by presence (+; light blue) or absence (-; dark blue) of the has locus (encoding the

capsule biosynthesis genes). B: Dataset colored according to the variant of the nga promoter - 1 (red); 2 (blue); 3

A B nga promoter variant

1

2

3

2002V1366P

222

58

Clade 2

Clade 1

Clade 3

hasABC locus

-

+

222

58

hasABC+ hasABC-

48

(green); The emm89 isolates are divided into three major clades, with clade 1 isolates harboring the variant 1

promoter region, clade 2 isolates the variant 2 and clade 3 isolates the variant 3. Clade 1 and 2 isolates also harbor

the hasABC locus that is absent in clade 3 isolates. In this dataset, only one isolate belonging to clade 1 was found

(2002V1366P).

The results obtained within this dataset are consistent with increased genetic distance between

clades, especially between clade 1 and the other two clades (Figure 10 and S1), in agreement with a

previous report using core chromosomal SNPs (168). The genetic distance between isolates within

clade 2 is high in comparison with that of isolates in clade 3, which are more closely related (Figure S4).

The recent emerge of clade 3 may explain the more limited diversification when compared with clade 2,

at least in Portugal. Two different lineages, ST101 and ST824, were associated with variant 3 strains,

with ST101 appearing as the predominant lineage, as previously reported (167, 184). ST824, an SLV

of ST101, was exclusively associated with strains of this clade in this dataset (Figure 8D). As mentioned

above, two new STs were identified for three emm89 isolates, one being an SLV and the other a DLV

of ST101 (Figure 9B). Hence, this data adds to the diversification of emm89 clade 3 previously reported

(167).

Macrolide resistance rates have been shown to be variable within GAS populations worldwide,

with declining resistance rates being reported in Portugal (36, 156). Previously, the distinction between

the emm4 macrolide-susceptible and -resistant clones was only achieved with PFGE (131) and only the

macrolide-susceptible clone was significantly associated pharyngitis, while the macrolide-resistant clone

was equally prevalent in pharyngitis and invasive disease (99, 131). The analysis of the MST for the

emm4 isolates showed that, in general, there is a clustering of the isolates according to macrolide

resistance or susceptibility (Figure 11A). However, within the resistant isolates there are two that fail to

be grouped with the other resistant isolates. One of these isolates (SH0264A) exhibits a higher genetic

distance from the other nodes of the erythromycin-resistant group and the emm4 clone in general

(Figure 11A). Interestingly, this isolate presents ST38 that is an SLV of ST39, associated with all other

resistant emm4 isolates (Figure 8C), supporting the divergence of this isolate relative to the remaining

resistant isolates. It is possible to observe that the majority of the resistant isolates were recovered

before 2006 (Figure 11B), in agreement with the declining trend in macrolide resistance previously

mentioned (156).

The genetic distance within the susceptible and resistant emm4 groups was compared,

excluding the two susceptible isolates that were not included in the emm4 group at tree cut-off of 1052

and the above mentioned isolate SH0264A. The macrolide-susceptible isolates were, in general,

genetically more distant in comparison with the macrolide-resistant isolates (Figure S5). Moreover, in

the susceptible clone, four different STs were identified (Figure 8C), despite three of those being

associated with only one isolate. Taken together, these results indicate that a lower diversification

occurred within the macrolide-resistant isolates in comparison to that observed for the susceptible

group. Further studies are required in order to conclude which genetic determinants are responsible for

the differences between the erythromycin-susceptible and resistant groups, but the overall clustering

according to antimicrobial susceptibility is in agreement with previous reports that suggest that some

49

underlaying genetic characteristics besides that observed from MLST and emm typing data are

responsible for the differences between lineages (99, 131).

Figure 11. MST for the emm4 isolates (susceptible and resistant to erythromycin). The macrolide resistance

phenotype and year of isolation are presented. The size of the nodes is proportional to the number of isolates

included in each node. A: Nodes colored according to macrolide resistance - resistant (M phenotype, pink);

susceptible (gray). B: Dataset colored by year of isolation – 2001 to 2005 (blue gradient, from lighter to darker

colors); 2006 to 2009 (green gradient, from lighter to darker colors); 2010-2012 (red/pink gradient, from lighter to

darker colors). The pink circle highlights the strains presenting the macrolide resistance phenotype M.

Selection of isolates representative of the genetic diversity within each clone

The evaluation of the genetic relationships between the 319 isolates based on the MST

generated by the cgMLST data provided insights about the genetic diversity within the six GAS clones

included in this study. Between 8 and 15 isolates representative of the diversity within each clone were

selected, in a total of 68 isolates, to be included in future phenotypic studies. For this selection, since

the range of genetic distances among different emm types varied considerably, different tree cut off

values were applied to the tree obtained for each emm type, in order to determine the groups that are

formed and their agreement with MLST data. Following this step, strains representative of the diversity

within each group were chosen having in consideration previously determined characteristics such as

SAg profiles, STs and type of infection. This selection thus maximizes the diversity within the group of

isolates chosen from each clone, so as to better cover the potential diversity of phenotypes in the

subsequent phenotypic studies.

Regarding the emm1-EryS clone, at a tree cut off value of 24, five different groups and 3

singletons were observed (Figure 12A). The selection was performed so as to include the three isolates

that appeared isolated, one isolate from the two small groups formed, two isolates from the intermediate

Susceptible

M

Macrolide resistance

phenotype

A

SH0264A

emm4

Year of

isolation

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

Macrolide resistance

phenotype M

B

emm4

151

50

groups and six isolates from the major group. For the emm3 clone, at a tree cut off value of 20, the

isolates were well separated according to ST. At this value, six different groups were formed, as well as

four singletons (Figure 12B). The selected isolates included the four singletons, one isolate from the

small groups, two isolates from the intermediate groups and three isolates from the large group. A total

of 15 isolates were selected from each of these two clones.

Figure 12. Isolate selection within the emm1-EryS and emm3 clones for subsequent phenotypic analysis. The size

of the nodes is proportional to the number of isolates included in each node and isolates are colored by ST. A:

Isolates belonging to emm1-EryS clone. Strain selection performed at a tree cut off value of 24 where five different

groups as well as 3 singletons were observed. B: Isolates belonging to emm3. Strain selection performed at a tree

cut off value of 20 where six different groups and four singletons were observed. The isolates selected from each

clone are identified.

For emm89-hasABC+, since higher genetic distances among isolates are observed in

comparison with the majority of the other groups under study, a higher tree cut off value was used to

choose the isolates representative of the diversity. At a tree cut off of 28, five groups are formed, and

three isolates appear as singletons (Figure 13A). The singletons were chosen, as well as one isolate

from each of the four small groups and three isolates from the larger group, in a total of ten isolates.

The isolates belonging to emm89-hasABC- are, on the other hand, closely related. Therefore, a tree cut

off value of 15 was chosen for the analysis where one major clade, as well as one small group with two

isolates and one singleton were observed (Figure 13B). The strain selection was made so as to include

the singleton, one isolate from the small group and six isolates from the larger group, in a total of eight

isolates.

The emm4-EryS group, much like the emm89-hasABC+, displays higher genetic distances

among isolates and, therefore, a higher tree cut off value was chosen for this analysis. At a tree cut off

of 31, four groups are observed, with five isolates being isolated (Figure 13C). The selected isolates

include the five singletons, one isolate from the smaller group and two isolates from the three larger

groups, in a total of 12 isolates. As previously mentioned, two of the singletons (SH7089A and SH1749A)

have increased genetic distances, comparable to the distances shared between isolates from different

emm types (Figure 7A). The selection of these isolates is of particular interest for further studies due to

the high genetic distance shared between these isolates and the rest of the emm4 group. The emm4-

emm1-EryS emm3A

Tree cut off: 24

B

28

643

830

ST

15

406

315

ST

Tree cut off: 20

SH8254A

SH0203A

SH1131A

SH3123A

SH4859A

2004V0014A

SH0011A

2003V1477PSH0253A

SH0915A

SH1102A

SH3845A

SH6186A

SH3210A

SH3077A

2001V0846P

SH5586A

SH2438A

SH2510A

SH0274A

2005V1950P

SH6223A

2002V0356P

2005V0404P

SH1097A

2002V1364P

SH2228A

SH4138A

SH6647A

2005V1832P

51

EryR group has a low number of isolates that are closely related in the cgMLST tree. Therefore, a low

tree cut off value (15) was chosen for the selection. At this value, one major group is formed as well as

one smaller one and three singletons (Figure 13D). One of these isolates (SH0264A) presents a higher

genetic distance to the other isolates of the same clone, as mentioned above (Figure S1). In accordance

with the selection performed for the other clones, besides the three singletons, one isolate from the

small group and four isolates from the large group were chosen, in a total of eight isolates. The isolates

selected from each clone of interest and the associated characteristics, such as year of isolation, type

of infection, ST and SAg profiles are listed in table S3.

Figure 13. Isolate selection within the emm89 groups (hasABC+ and hasABC-) and the emm4 groups (EryS and

EryR) for subsequent phenotypic analysis. The size of the nodes is proportional to the number of isolates included

in each node and isolates are colored by ST. A: Isolates belonging to emm89 hasABC+. Strain selection performed

at a tree cut off value of 28 where four small groups, one major group and 3 singletons were observed. B: Isolates

belonging to emm89 hasABC-. Strain selection performed at a tree cut off value of 15 where one major group, one

small group and one singleton were observed. C: Isolates belonging to emm4-EryS clone. Strain selection

performed at a tree cut off value of 31 where four different groups and five singletons were observed. D: Isolates

belonging to emm4-EryR clone. Strain selection performed at a tree cut off value of 15 where one large group, one

small group and three singletons were observed. The isolates selected from each clone are identified.

Tree cut off: 28

A emm89-hasABC+

Tree cut off: 15

B emm89-hasABC-

101

408

568

407

ST

101

824

-

ST

C Demm4-EryS emm4-EryR

39

771

ST

39

38

ST

Tree cut off: 15Tree cut off: 31

823

-

2002V1366P

2001V0807P

SH0201A

551PT

SH1037A

SH4950A

SH1712A2004V1019P

SH6560A

SH4701A

SH4612A

SH11927A2005V0414P

SH4345A

SH2920A

SH4067A

SH3904A

SH6140A

SH0264A2005V1272A

SH4490A 2003V0512P

2003V1352P 2004V1227P2003V0742P

SH2211A

SH1749A

SH7089A

2002V1221P

2003V0692P

2005V1572PSH5409A

SH2289A

SH2476A

2005V2258P

SH4073A

2005V1440P

SH2423A

52

Optimization of SLO activity determination assay

SLO plays a critical role in the pathogenesis of GAS, namely in the evasion to host defenses

and toxicity (82, 83, 85, 88). Previous studies suggested that increased production of both SLO and

NADase are responsible for an enhanced fitness of the pathogen in the upper respiratory tract;

increased tissue damage; and evasion to immune mechanisms (132). In order to include this key

virulence factor in the subsequent phenotypic studies of the 68 isolates selected in the previous section,

an assay for in vitro quantification of SLO extracellular activity was optimized.

Strains SF370, representative of the pre-epidemic M1 lineage, and MGAS5005, representative of

the contemporary, epidemic M1 lineage, were used as controls of the assay. GAS SF370 is expected

to present a low SLO activity, much like what was reported for the NADase activity. On the contrary, the

SLO activity of the MGAS5005 is expected to be high, in agreement with the high NADase activity

reported (61, 84). The selection of the strains used for the optimization process was made so as to

include isolates with relevant genotypic and phenotypic characteristics that may lead to differences in

their SLO activity (Table 1). Therefore, strains with different emm types and different levels of NADase

activity (61) were selected and since the NADase and SLO genes belong to the same operon, different

levels of SLO activities are expected.

The SLO activity was determined using an endpoint titer method based on the hemolytic titers

of GAS supernatants incubated with sheep erythrocytes (83, 179). The rationale of the assay is that

SLO, a pore-forming toxin (88), lysis the erythrocytes releasing hemoglobin which leads to an increase

in the absorbance at 570 nm. The summary of the steps of the assay for the for the in vitro quantification

of the extracellular activity of SLO is presented in Figure 14.

Figure 14. Summary of the steps of the laboratory assay for the in vitro quantification of the extracellular activity of

SLO. *Cholesterol was used to confirm that the hemolytic activity measured was due to SLO and will not be required

in further assays.

The first step of the optimization process included the definition of the concentration and

preincubation conditions with trypan blue. Trypan blue is a specific inhibitor of SLS (another pore-

forming toxin secreted by S. pyogenes) (185) and is used to guarantee that the hemolysis observed

under the assay conditions is only due to SLO activity. Firstly, the assay was performed only in the

presence of trypan blue in order to determine the concentration and the preincubation conditions needed

to inhibit the SLS activity. Two concentrations of trypan blue, 4 g/mL (83) and 40 µg/mL (61), as well

as preincubation at RT for 10 min (83) and at 37ºC for 30 min, were tested. With a preincubation of 10

Preparation of the culture

supernatants

- 1) Culture in blood agar

- 2) Culture one colony in THB for 24h

(pre-inocula)

- 3) Dilute pre-inocula in fresh THB

(1:10) and grow to late exponential

or stationary phase

- 4) Pellet bacterial cells

Pre-treatment of

the supernatants

• Trypan blue

• DTT

• Cholesterol*

Serial dilutions of

the supernatants

• PBS

Incubation with

erythrocytes

• Suspension of sheep

erythrocytes 2.5% (v/v)

Determination of SLO

activity

• Pellet the erythrocytes

• Measure A570 of supernatants

• Calculate % of hemolysis in

each well

53

min at RT, none of the trypan blue concentrations tested produced a complete inhibition of the SLS

activity (Table 2). When preincubation was at 37ºC for 30 min, the first trypan blue concentration tested,

4 g/mL, did not inhibit the hemolytic activity produced by SLS, while the concentration of 40 µg/mL lead

to a complete inhibition of the SLS activity. This optimization step was performed with an incubation with

erythrocytes at 37ºC for 60 min. Therefore, in order to properly inhibit the SLS hemolytic activity, a

concentration of trypan blue of 40 µg/mL coupled with a preincubation at 37ºC for 30 min are required.

Table 2. Concentration of trypan blue and preincubation conditions tested to achieve a complete inhibition of the

SLS activity. Strain SF370 was used as negative control and the set of dilutions used was 1/3 up to 1/192. Intra-

assay duplicates are presented.

In the second step of the optimization process, the concentration of DTT required for the SLO

activity determination assay was defined. The DTT is a reducing agent that stabilizes SLO, an oxygen

labile toxin, and is used simultaneously with the trypan blue in this assay. Different DTT concentrations

were tested: 4 mM (83), 10 mM (186), 20 mM and 50 mM. Comparing the results using 4 mM and 10

mM, an improvement in the SLO hemolytic activity was observed (Table 3). However, concentrations

above 10 mM did not produce improvements in the hemolysis observed. Hence, the DTT concentration

to be used in the hemolysis assay is 10 mM.

Table 3. Concentrations of DTT tested to stabilize SLO. Strain SF370 was used as negative control and the set of

dilutions used was 1/2 up to 1/128. Intra-assay duplicates are presented.

In order to confirm that the hemolytic activity measured under these conditions was due to SLO

activity, some assays were also performed in the presence of cholesterol, a known inhibitor of SLO (83).

Therefore, the third step of the optimization of the SLO activity assay comprised the definition of the

cholesterol concentration needed to completely inhibit the SLO activity in the bacterial supernatants.

Two different concentrations of cholesterol - 25 µg/mL and 50 µg/mL - were tested under the assay

conditions previously determined. The concentration of 25 µg/mL did not completely inhibit the

hemolysis produced by SLO while the concentration of 50 µg/mL lead to a complete inhibition. Following

this step, two different conditions for the incubation with erythrocytes were tested, both at 37ºC but one

for 30 min (83) and the other for 60 min (61). An incubation with erythrocytes for 60 min with cholesterol

Strain RT for 10 min 37ºC for 30 min

Trypan blue 4 𝜇g/mL Trypan blue 40 𝜇g/mL Trypan blue 4 𝜇g/mL Trypan blue 40 𝜇g/mL

1 SF370 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3

2 MGAS5005 12 12 6 6 6 6 ≤3 ≤3

6 2001V1236P 12 12 6 6 12 12 ≤3 ≤3

7 2005V1791P 12 12 6 6 6 6 ≤3 ≤3

Strain DTT 4 mM DTT 10 mM DTT 20 mM DTT 50 mM

assay1 assay2 assay1 assay2 assay1 assay2 assay1 assay2

1 SF370 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2

2 MGAS5005 4 4 4 4 8 4 8 8 4 4 4 4 4 4 4 4

6 2001V1236P 4 4 4 4 8 8 8 8 4 4 4 4 4 4 4 4

7 2005V1791P 4 4 4 4 4 8 8 8 4 4 4 4 4 4 4 4

54

lead to some detectable hemolysis in the first dilution while a 30 min incubation with erythrocytes lead

to a complete inhibition of the hemolytic activity. These results indicate that, for an incubation of 60 min,

the SLO activity could not be completely inhibited by cholesterol. Therefore, an incubation with

erythrocytes at 37ºC for 30 min produces the desirable results and the cholesterol concentration

indicated for the assay is 50 µg/mL.

The growth phase of GAS culture supernatants and the serial dilutions of the supernatants to

be used in the SLO hemolysis assay were defined in the final step of the optimization process. The

assay was performed with culture supernatants at late-exponential (OD=1.10) and stationary phase

(18h cultures), and different serial dilutions were tested: 1/2, 1/4, 1/8, 1/16, 1/32, 1/64, 1/128; 1/3, 1/6,

1/12, 1/24, 1/48, 1/96, 1/192; and 1/3, 1/4, 1/6, 1/8, 1/12, 1/16, 1/24. (Table 4). The growth curves of the

strains used in the optimization were performed beforehand, with internal duplicates and three

independent assays for each strain, in order to determine an OD value corresponding to late-exponential

phase of growth (Figure S6). The late-exponential phase supernatants coupled with the set of dilutions

of 1/2 up to 1/128 allowed to better discriminate between strains in comparison with stationary phase

and the set of dilutions of 1/3 up to 1/192 (Table 4). The dilution set 1/3, 1/4, 1/6, 1/8, 1/12, 1/16, 1/24

was performed in an attempt to better discriminate the upper range of dilutions, where the SLO activity

of the tested strains was situated (between the values of 2 and 16 or 3 and 12, according to the set of

serial dilutions used). This refinement, however, did not provide further discrimination of the SLO

activities of the strains tested and affected the reproducibility of the results. Taking these results into

consideration, the exponential phase was chosen for the hemolysis assay for determination of SLO

activity and the set of serial dilutions that produced the most effective results under this condition was

1/2; 1/4; 1/8; 1/16; 1/32; 1/64; 1/128. The conditions defined for the SLO activity determination assay

after the optimization process are summarized in table 5 and the final protocol can be found in the

supplementary data.

In addition to these findings, the results obtained throughout the different steps of the

optimization process also demonstrated that intra-assay duplicates are not required since the intra-

assay variability observed is not significant. However, for some strains, some inter-assay variation was

observed and at least three independent assays should be performed using different samples of fresh

sheep blood, since the batch of the blood used greatly influences the results. Finally, regarding the SLO

activity observed in the strains used for the optimization process, strain SF370 presented, as expected,

a low SLO activity throughout the different assays while strain MGAS5005 presented high activity. Only

two other strains, 2001V1236P and 2005V1791P, were found to have high SLO activity (Table 4). These

two strains were also previously associated with a high NADase activity (61) (Table 1). Since the

NADase and SLO genes belong to the same operon, their expression is expected to be positively

correlated. Therefore, the results obtained for these strains support the expected correlation between

the expression of NADase and SLO. However, under the assay conditions used, it was not possible to

detect SLO activity for strains presenting a NADase activity in the range of 12-48 (SH1066A, SH0759A,

2003V0731P and 2001V0953P).

55

Table 4. SLO activity values obtained for the control strains and the other two strains with high activity. The

remaining strains presented minimum activity (≤2 or ≤3, according to the set of dilutions tested). The results for the

late-exponential and stationary phase bacterial supernatants tested with different sets of dilutions are presented,

with three independent assays and intra-assay duplicates.

Table 5. Summary of the conditions defined for the SLO activity determination assay after the optimization process.

The preincubation conditions such as temperature, time and concentrations of trypan blue, DTT and cholesterol;

condition of the incubation with erythrocytes; and serial dilutions are presented.

Preincubation conditions Incubation with

erythrocytes

Serial dilutions

1/2

Concentration of the reagents

Temperature and time Temperature and time

1/4

1/8

Trypan blue DTT Cholesterol* 1/16

1/32

40 µg/mL 10 mM 50 µg/mL 37ºC for 30 min 37ºC for 30 min 1/64

1/128

*Assays performed in the presence of cholesterol are only required for a few strains under testing. Cholesterol was

used to confirm that the hemolytic activity measured was due to SLO and will not be required in further assays.

Optimization of streptokinase activity determination assay

Streptokinase is an important GAS virulence factor responsible for the non-enzymatic activation

of human plasminogen, generating plasmin activity, that leads to the degradation of fibrin networks,

components of the extracellular matrix and antimicrobial components. This action promotes bacterial

spread to surrounding sites thereby enhancing the pathogenic ability of the bacteria (67, 68). In order to

include this key virulence factor in the subsequent phenotypic studies of the previously 68 isolates

selected, an assay for in vitro quantification of streptokinase extracellular activity was optimized. The

streptokinase activity was determined using an indirect plasminogen activation assay with a plasmin-

specific chromogenic substrate. Streptokinase converts plasminogen into plasmin in solution, leading to

the hydrolysis of the plasmin-specific chromogenic substrate (180, 181), which causes changes in the

absorbance at 405 nm. The strains used for the optimization process of the streptokinase activity

Strain Late-exponential phase Stationary phase

assay1 assay2 assay3 assay1 assay2 assay3

Dilutions tested: 1/2; 1/4; 1/8; 1/16; 1/32; 1/64; 1/128

1 SF370 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2 ≤2

2 MGAS5005 8 8 8 16 8 8 4 4 4 4 4 4

6 2001V1236P 8 8 8 16 8 8 4 4 4 4 4 4

7 2005V1791P 4 4 8 4 4 4 4 4 4 4 4 4

Dilutions tested: 1/3; 1/6; 1/12; 1/24; 1/48; 1/96; 1/192

1 SF370 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3

2 MGAS5005 6 6 12 6 6 6 6 6 6 6 6 6

6 2001V1236P 6 6 6 6 6 6 6 6 6 6 6 6

7 2005V1791P 6 6 ≤3 6 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3

Dilutions tested: 1/3; 1/4; 1/6; 1/8; 1/12; 1/16; 1/24

1 SF370 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3 ≤3

2 MGAS5005 8 12 16 8 24 24 6 4 6 6 8 12

6 2001V1236P 16 16 12 8 16 24 6 6 6 6 16 16

7 2005V1791P 8 8 6 6 16 16 6 6 8 6 16 16

56

determination assay were the same used for the optimization of the SLO hemolysis assay (Table 1).

Strains SF370 and MGAS5005, expected to present a low and a high activity, respectively, were used

as controls of the assay. The summary of the steps of the assay for the in vitro quantification of the

extracellular activity of SLO is presented in figure 15.

Figure 15. Summary of the steps of the laboratory assay for the in vitro quantification of the extracellular activity of

streptokinase.

In the first part of the optimization process, the reagents required for the assay and their

respective concentrations were defined. In order to determine the streptokinase activity of different GAS

supernatants, the presence of the unprocessed form of plasminogen (known as glu-plasminogen) is

required, with the plasmin activity being monitored by measuring the absorbance at 405 nm for 120 min,

at 37ºC (71, 180). The absorbance is plotted against time and the streptokinase activity rates of each

strain are determined from the slope of the linear portion of the curve obtained. The plasminogen is the

target for the streptokinase and, therefore, should be present in excess. Two different concentrations of

glu-plasminogen – 220 nM (71) and 500 nM (180) – were tested. The slopes observed for each strain

were superior using 500 nM of plasminogen, as presented in figure 16 for strain MGAS5005. Therefore,

the concentration of 500 nM was chosen for further assays. Additionally, the assays were

simultaneously performed in the absence of plasminogen to confirm that the proteolytic activity observed

is a result of the plasminogen activation.

Some GAS strains, namely isolates harboring cluster 2b ska alleles, require the presence of

fibrinogen to produce streptokinase activity (71). The importance of the use of fibrinogen as a reagent

for this assay was tested, by performing the assay with plasminogen alone or with plasminogen pre-

incubated with fibrinogen at 37ºC for 15 min, in a 1:1 stoichiometric ratio (71). This test was performed

in four strains (2003V0731P, SH1066A and the two control strains) and for one of these (2003V0731P),

the streptokinase activity curve was not completed within the 120 min of the assay without fibrinogen

despite a complete curve being observed in the assay performed with both plasminogen and fibrinogen

(Figure 17). This result highlights the importance of using fibrinogen in the streptokinase activity

determination assay, in order to detect the streptokinase activity of all strains tested.

Preparation of the

culture supernatants

- 1) Culture in blood agar

- 2) Culture one colony in

THB for 24h (pre-inocula)

- 3) Dilute pre-inocula in fresh

THB (1:10) and grow to late

exponential or stationary

phase

- 4) Pellet bacterial cells

Pre-incubation

of plasminogen

with fibrinogen

(1:1)

Add supernatants to

50 mM Tris, pH 7.5

• Two negative controls

(THB)

• Two positive controls

(commercial

streptokinase)

Add plasminogen

preincubated with

fibrinogen

• Perform simultaneously

one assay under the

same conditions but

without plasminogen

Add chromogenic

agent S-2251

• Addition with the plate

on ice

Measurement of

absorbance at 405 nm

• For 90-120 min, every minute

• Plot absorbance against time

and determine slope

• Use standard curve to

determine streptokinase

activity

57

Figure 16. Graphic representation of the absorbance plotted against time from the streptokinase determination

assay performed with glu-plasminogen 500 nM (green triangles), with glu-plasminogen 220 nM (blue circles) or

without plasminogen (orange crosses), for culture supernatants of strain MGAS5005 grown at late-exponential

phase. The assays were performed under the same conditions, except for the concentration of glu-plasminogen.

Similar results regarding the effect of the concentration of glu-plasminogen on streptokinase activity were obtained

for the other tested strains.

Figure 17. Graphic representation of the absorbance plotted against time from the streptokinase determination

assay performed with plasminogen pre-incubated with fibrinogen (green triangles) or with plasminogen alone (blue

circles), for culture supernatants of the GAS strains 2003V0731P (A) or MGAS5005 (B) grown at mid-exponential

phase. The assays were performed under the same conditions with the exception of the presence/absence of

fibrinogen.

In this assay, the change in absorbance at 405 nm is due to the hydrolysis of S-2251, a

chromogenic substrate for plasmin and streptokinase-activated plasminogen. This reagent was used at

a final concentration of 500 µM (180), producing results congruent with the available literature (180,

181). However, in order to measure the initial stages of the reactions, we concluded that the addition of

the S-2251 should be performed with the plate on ice, with the reaction starting only when the plate was

incubated at 37ºC in the plate reader. Additionally, the change in absorbance at 405 nm was measured

0.15

0.35

0.55

0.75

0.95

1.15

1.35

0 10 20 30 40 50 60 70 80 90

A4

05

Time (min)

MGAS5005

glu-plasminogen 500 nM glu-plasminogen 220 nM Assay without plasminogen

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0 20 40 60 80 100 120

A4

05

Time (min)

2003V0731P

Plasminogen pre-incubated with fibrinogen Plasminogen alone

A

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0 20 40 60 80 100 120

A4

05

Time (min)

MGAS5005

Plasminogen pre-incubated with fibrinogen Plasminogen alone

B

58

every minute instead of every 3 min, as previously reported (71), so as to allow for a more precise

definition of the slopes of the curves produced by GAS strains with high streptokinase activity. The

reaction was monitored for a total time of 120 min instead of 60 min (71), to ensure that the complete

curves of the GAS strains with low streptokinase activity were registered. According to the results

obtained for the limited number of strains used in the optimization of the assay, a total time of 90 min is

predicted to be adequate, although this needs further confirmation by testing a larger number of isolates.

Different growth phases of GAS cultures were tested in the optimization of the assay, namely

mid-exponential (OD600=0.80), late-exponential (OD600=1.10) and stationary phase (18h cultures). The

absorbance values for mid-exponential and late-exponential phase were determined based on the

growth curves performed for the tested strains (Figure S6). For the limited number of strains tested

(Table 1), differences in the slopes of the absorbance versus time curves were observed for the GAS

supernatants grown to different phases, with the highest values obtained at late-exponential phase of

growth. Furthermore, for some strains, such as SF370, the streptokinase activity was only measurable

at late-exponential, since for the mid-exponential phase the slope could not be precisely measured

because the activity curve was not completed within the 120 min of the assay. Regarding stationary

phase, no curve was observed within the 60 min during which the changes in absorbance were

measured (Figure 18). The assay with culture supernatants at stationary phase was performed first, so

the changes in absorbance were only measured for 60 min versus the 120 min performed for the assays

at exponential phases of growth. However, when comparing the assays performed at the different

growth phases, after 60 min it was already possible to see some increase in the absorbance values with

the culture supernatants at mid-exponential and an increase to near maximum values of absorbance

with culture supernatants at late-exponential. Despite the measurable streptokinase activity of strain

SF370 at exponential phase, no apparent activity in stationary phase was observed. This could be

explained by the accumulation of SpeB, a cysteine protease with maximal expression in the transition

from exponential to stationary phase, which is known to degrade many GAS virulence factors such as

streptokinase (66). The degradation of streptokinase by SpeB in stationary phase culture supernatants

coupled with high streptokinase presence in late-exponential and reduced, but detectable streptokinase

in mid-exponential phase of growth cultures have been previously described and are in agreement with

the results obtained herein (73). These data indicate that the streptokinase activity is more effectively

measured at late-exponential phase, and, therefore, this was the growth phase chosen for the activity

determination assay.

59

Figure 18. Graphic representation of the absorbance plotted against time from the streptokinase determination

assay performed for culture supernatants of GAS strain SF370 grown to mid-exponential phase (A), late-

exponential phase (B) and stationary phase (C); and for GAS strain MGAS5005 grown to late-exponential phase

(D). Intra-assay duplicates as well as two independent assays were performed. For strain SF370, the streptokinase

activity was only measurable at late-exponential growth phase, where the slope of the linear portion of the curve

could be effectively measured. For the mid-exponential assay, it was possible to observe part of the curve, but the

slope could not be measured. Regarding stationary phase, no curve was observed. The assays were performed

under the same conditions, except for the total assay time, which for the stationary phase assay was 60 min instead

of 120 min.

In order to convert the rate of S-2251 degradation to streptokinase activity in units/mL, a

standard curve must be defined using known concentrations of streptokinase. Standard curves were

performed under the same assay conditions of the activity determination assays and using serial

dilutions of commercial group C streptokinase, from 1000 units/mL to 0.49 units/mL, based on a previous

report (187). For each concentration, the changes in absorbance as a result of the streptokinase activity

were measured and plotted against time and the standard curve was constructed by plotting the slopes

of the linear portion of the resulting curves of each dilution against the corresponding concentration

(Figure 19). Since the standard curve will be used to determine the streptokinase activity from the plots

obtained for each strain in the different assays, the variability between assays and the standard curve

should be controlled so as to guarantee that the results are not greatly affected by variations. To do so,

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0 20 40 60 80 100 120

A4

05

Time (min)

SF370 - Mid-exponential phase

Assay1-1 Assay1-2 Assay2-1 Assay2-2

A

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0 20 40 60 80 100 120

A4

05

Time (min)

SF370 - Late-exponential phase

Assay1-1 Assay1-2 Assay2-1 Assay2-2

B

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0 10 20 30 40 50 60

A4

05

Time (min)

SF370 - Stationary phase

Assay1-1 Assay1-2 Assay2-1 Assay2-2

C

0.15

0.20

0.25

0.30

0.35

0.40

0.45

0.50

0.55

0.60

0 20 40 60 80 100 120

A4

05

Time (min)

MGAS5005 - Late-exponential phase

Assay1-1 Assay1-2 Assay2-1 Assay2-2

D

60

several standard curves are performed, and for each streptokinase concentration a range of slopes is

obtained. The final standard curve to be used plots the mean values with respective 95% confidence

intervals against the commercial streptokinase concentrations. For each assay, two internal positive

controls with a known concentration included in the standard curve range should be performed, and the

slopes obtained should fall within the confidence intervals previously determined, otherwise the assay

should be dismissed and repeated. For this work, the goal was to perform ten standard curves using

different stocks of reagents or freshly prepared solutions within what is feasible in a research laboratory

setting (order time, shipping of material, project time and available budget). By doing so, variations

associated with preparation of solutions, changes in the stocks of reagents and performance of different

assays are contemplated in the error. Regarding the commercial streptokinase, the fibrinogen and the

buffer solution, the same stock was used, but for each assay a fresh working solution was prepared.

The chromogenic substrate S-2251 was freshly prepared for each assay from the same solid stock

reagent. For glu-plasminogen, two different stock solutions were used and for each assay a newly

working solution was prepared. The concentrations of the plasminogen stock solutions were certified by

the manufacturer to contain 2.43 mg/mL (stock 1) and 2.8 mg/mL (stock 2). The volume available of the

stock 1 of plasminogen was only enough to perform one standard curve and after performing six curves,

one using stock 1 and five with stock 2, significant discrepancies were found. For the five curves

performed with the stock 2 of glu-plasminogen, some expected variation was observed but within an

acceptable range. However, the standard curve obtained using stock 1 was considerably different from

the other standard curves (Figure 19). The stock 1 of glu-plasminogen was previously used in the

positive controls in the optimization of the determination assay and the results obtained were in

agreement with the ones for the standard curve using the same plasminogen stock. The concentration

of the positive control used in the assays was 3.90 units/mL and the range of slopes obtained was

between 4.51 and 5.18. The slope obtained for this concentration in the standard curve using stock 1

was 4.52, while the range of slopes using stock 2 was between 2.3 and 3.0. Therefore, despite only one

curve being performed using stock 1, the variability observed does not appear to be the result of an

error while performing the assay. Taking all these results into consideration, one can speculate that the

variability observed was most likely due to the different plasminogen stocks, since the independent

preparation of the other reagents did not result in significant variations within the five curves in which

plasminogen stock 2 was used. Therefore, two possible factors may have accounted for the observed

discrepancies: the concentrations of the plasminogen stock solutions certified by the manufacturer were

inaccurate and/or the plasminogen concentration used was below the saturation point under the assay

conditions used. Hence, the standard curve must be repeated with increasing plasminogen

concentrations in order to determine the saturation concentration under the assay conditions used. The

use of a plasminogen concentration slightly above that saturation point in future experiments will allow

for a more effective quantification of all streptokinase activity in the culture supernatants, since

plasminogen is the target for streptokinase. Furthermore, it will make the assay less sensitive to possible

variations in the plasminogen concentration certified by the manufacturer.

61

Figure 19. Standard curves of commercial streptokinase performed during the optimization process. The assay

conditions were the same defined for the activity determination assays with serial dilutions of commercial

streptokinase from 1000 units/mL to 0.49 units/mL used. One standard curve was performed using stock 1 of glu-

plasminogen while the stock 2 of glu-plasminogen was used for the other five standard curves. Significant

differences were observed when different stocks of glu-plasminogen were used which is indicative that the

concentration of the stocks defined by the manufacturer are inaccurate or the saturation point of the plasminogen

in the assay performed under these conditions is yet to be reached.

In order to retrieve the streptokinase activity of each strain from the standard curve, an equation

has to be defined. A previous report defined the standard curve for group C streptokinase as a linear

regression (187), which does not seem to be adequate to the standard curves obtained under the assay

conditions used herein. However, the best fit for the curve can only be determined after the curves have

been performed with the optimal plasminogen concentration.

Throughout the different steps of the optimization process some intra- and inter-assay variability

was observed for the strains tested. These results demonstrate that for an affective measurement of the

streptokinase activity, intra-assay duplicates as well as three independent assays should be performed

in order to account for this variability. Regarding the streptokinase activity observed for the strains used

in the optimization process, strain SF370 presented, as expected, a low streptokinase activity while

strain MGAS5005 presented high activity (Figure 18). The conditions optimized for the streptokinase

activity determination assay and the standard curve are summarized in table 6. The protocol can be

found in the supplementary data.

0.00

2.00

4.00

6.00

8.00

10.00

12.00

14.00

0 100 200 300 400 500 600 700 800 900 1000

Slo

pe

x 1

0^

2

Streptokinase (units/mL)

Standard curve

Glu-plasminogen Stock1

Glu-plasminogen Stock2

62

Table 6. Summary of the conditions defined for the streptokinase activity determination assay. The concentrations

of tris pH 7.5, plasminogen, fibrinogen and chromogenic agent S-2251, the temperature and time for the

preincubation and incubation, and the concentrations of commercial streptokinase used in the standard curve are

presented.

Activity determination assay and standard curve Standard curve

Tris pH 7.5

Preincubated at 37ºC for 15 min Chromogenic substrate

S-2251

Serial dilution of commercial streptokinase (units/mL)

1000.00

Plasminogen Fibrinogen 500.00

250.00

50 mM 500 nM

1:1 stoichiometric

ratio with plasminogen

500 µM

125.00

62.50

31.25

15.63

7.81

3.91

1.95

0.98

0.49

Incubation in a microplate reader at 37ºC for 120 min with measures of absorbance at every minute

63

CONCLUSIONS AND FUTURE PERSPECTIVES

S. pyogenes is an important human pathogen responsible for a wide range of clinical

manifestations such as pharyngitis, SSTI and life-threatening invasive diseases associated with high

morbidity and mortality. The global burden of GAS infections in association with the observed increase

in the incidence of invasive disease reinforces the importance of the worldwide implementation of

epidemiological surveillance systems. Moreover, a deeper knowledge of the mechanisms and

characteristics responsible for the changes in the clonal structure of different GAS populations and for

the particular association of certain clones with different types of infection may provide the tools to better

deal with this pathogen (1, 91).

With the aim of evaluating the genetic diversity within six GAS clones of interest, HTS was

performed for 320 strains belonging to these clones. The MST of the cgMLST schema showed a

clustering of isolates according to emm type, with the exception of two isolates that failed to be grouped

with the other emm4 isolates. An overall close genetic relationship among emm1 isolates was observed,

while for the other emm types, namely emm3, emm4 and emm89, there was at least one isolate with

increased genetic distance. The distribution of isolates within the MST indicates that the cgMLST profile

does not discriminate isolates according to type of infection.

The MST of the emm89 isolates presented a clustering of isolates according to the presence or

absence of the hasABC locus, with three major clades being observed in association with nga promoter

variants 1, 2 and 3. Only one isolate harboring the variant 1 was found in this dataset, in agreement with

previous reports indicating the predominance of this lineage in the USA in comparison with European

countries (167, 184). The clades are genetically distant from each other, with a particular high genetic

distance observed between clade 1 and the other two clades. In Portugal, a low diversification within

the recently emerged clade 3 was observed. However, previously unidentified STs that are SLVs and

DLVs of the major lineage of this clade were identified, suggesting that limited diversification is occurring,

as reported elsewhere (167). For emm4 isolates, the overall clustering of isolates according to the

macrolide resistance in the MST is congruent with the available literature that indicates that some

genetic characteristics are responsible for the phenotypic differences observed between the macrolide-

resistant and -susceptible lineages (131). Further studies are, however, required in order to identify

these genetic determinants. The isolates within the macrolide susceptible clone are, in general,

genetically more distant in comparison with those in the macrolide resistant group, suggesting a

restricted diversification within latter.

The SLO and streptokinase are key virulence factors involved in the pathogenesis of S.

pyogenes infections (68, 82, 88). Therefore, different activity levels of SLO and streptokinase may

contribute to the preferential association of certain GAS clones with specific types of infection. In the

optimization of the laboratory assays for quantification of their extracellular activities, strains SF370 and

MGAS5005 were used as controls and presented, as expected, low and high activities, respectively.

Strain MGAS5005 harbors an nga-ifs-slo promotor variant associated with enhanced SLO production

(84), and a covS mutation that is often associated with the upregulation of several virulence factors such

as SLO and streptokinase (57, 60, 61). The other two strains found to have high SLO activities were

64

also previously associated with a high NADase activity (61), in agreement with the expected correlation

between the expression of NADase and SLO.

The in vitro assay for quantification of the extracellular activity of SLO was successfully

optimized within the time scope of this thesis. Regarding the protocol for the quantification of

streptokinase activity, it was possible to optimize the concentrations of several reagents as well as the

incubation times. However, the plasminogen concentration requires further adjustments so as to

improve the robustness of the assay.

The gene-by-gene analysis performed with the draft genomes of 319 GAS isolates provided the

data to select between 8 and 15 isolates representative of the genetic diversity observed within six

clones of interest previously identified in Portugal, in a total of 68 isolates. The genetic characteristics

of these isolates will be further analyzed, and phenotypic studies will be performed, including the

quantification of the SLO and streptokinase activities, whose assays were optimized during this work.

Phenotypic traits can be associated with genotypic characteristics, such as allelic variants of the genes

encoding virulence factors or transcriptional regulators. Therefore, the work developed in this thesis

provides important genomic data and tools for future research studies aiming at identifying correlations

between genotypic and phenotypic characteristics and at better understanding the molecular

mechanisms underlying the association of some GAS clones with specific types of infection.

65

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79

SUPPLEMENTARY DATA

Table S1. Strain selection was performed so as to include half of the isolates representative of six clones of interest

and associated with each type of infection in a minimum of 10 isolates. The yellow columns correspond to the

number of strains selected for genomic analysis. SSTI: skin and soft tissue infection; EryS: erythromycin-

susceptible; EryR: erythromycin-resistant; 89-hasABC+: emm89 isolates harboring the hasABC locus enconding

the capsule biosynthesis genes; 89-hasABC-: emm89 isolates lacking the hasABC locus.

Clone Pharyngitis SSTI Invasive Total

emm1-EryS 20 10 52 26 159 80 231 116

emm3 37 19 13 10 68 34 118 63

emm4-EryS 32 16 14 10 26 13 72 39

emm4-EryR 19 10 3 3a 8 8 30 21

emm89-hasABC+ 22 11 26 13 23 12 71 36

emm89-hasABC- 4 4 36 18 45 23 85 45

Total 134 70 144 80 329 170 607 320

a One isolate from the emm4-EryR clone isolated from SSTI was not included in the genomic analysis due to the

lack of raw sequencing data at the time of the study (isolate ID: SH2621A).

Table S2. List of the 320 isolates selected for genomic characterization as well as known characteristics such as

emm type, type of infection, year of isolation, ST, SAg genes profile, macrolide resistance phenotype and hasABC

locus. SSTI: skin and soft tissue infection.

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH0011A 1 SSTI 2003 28 61 Susceptible ND

SH0049A 1 Invasive 2003 28 10 Susceptible ND

SH0130A 1 SSTI 2003 28 10 Susceptible ND

SH0203A 1 Invasive 2004 28 10 Susceptible ND

SH0253A 1 SSTI 2003 28 3 Susceptible ND

SH0263A 1 SSTI 2003 28 3 Susceptible ND

SH0526A 1 Invasive 2004 28 10 Susceptible ND

SH0756A 1 SSTI 2005 28 10 Susceptible ND

SH0841A 1 SSTI 2005 28 10 Susceptible ND

SH0915A 1 Invasive 2005 28 10 Susceptible ND

SH0917A 1 Invasive 2005 28 10 Susceptible ND

SH0943A 1 Invasive 2005 28 10 Susceptible ND

SH1025A 1 Invasive 2005 28 10 Susceptible ND

SH1068A 1 Invasive 2005 28 10 Susceptible ND

SH1069A 1 Invasive 2005 28 10 Susceptible ND

SH1102A 1 Invasive 2005 643 10 Susceptible ND

SH1122A 1 Invasive 2005 643 10 Susceptible ND

SH1131A 1 Invasive 2005 28 10 Susceptible ND

SH1300A 1 Invasive 2005 28 10 Susceptible ND

SH1328A 1 Invasive 2006 28 10 Susceptible ND

SH1361A 1 SSTI 2006 28 10 Susceptible ND

SH1515A 1 SSTI 2006 643 10 Susceptible ND

SH1531A 1 Invasive 2005 28 10 Susceptible ND

SH1533A 1 SSTI 2005 28 10 Susceptible ND

SH1699A 1 Invasive 2006 28 10 Susceptible ND

SH1709A 1 SSTI 2006 28 3 Susceptible ND

SH2000A 1 SSTI 2006 28 3 Susceptible ND

80

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH2222A 1 Invasive 2007 643 10 Susceptible ND

SH2353A 1 Invasive 2007 28 10 Susceptible ND

SH2486A 1 SSTI 2007 28 10 Susceptible ND

SH2541A 1 SSTI 2007 28 10 Susceptible ND

SH2872A 1 Invasive 2007 28 10 Susceptible ND

SH2883A 1 Invasive 2007 28 10 Susceptible ND

SH2902A 1 SSTI 2007 28 10 Susceptible ND

SH3058A 1 SSTI 2007 28 10 Susceptible ND

SH3077A 1 Invasive 2007 28 44 Susceptible ND

SH3094A 1 SSTI 2007 28 10 Susceptible ND

SH3123A 1 SSTI 2007 28 10 Susceptible ND

SH3190A 1 Invasive 2007 28 10 Susceptible ND

SH3207A 1 Invasive 2008 28 3 Susceptible ND

SH3210A 1 SSTI 2008 28 3 Susceptible ND

SH3249A 1 Invasive 2007 28 3 Susceptible ND

SH3289A 1 Invasive 2008 28 3 Susceptible ND

SH3295A 1 Invasive 2008 28 10 Susceptible ND

SH3543A 1 SSTI 2008 28 3 Susceptible ND

SH3742A 1 SSTI 2008 28 10 Susceptible ND

SH3750A 1 Invasive 2008 28 3 Susceptible ND

SH3757A 1 Invasive 2008 28 10 Susceptible ND

SH3778A 1 Invasive 2008 28 10 Susceptible ND

SH3813A 1 SSTI 2008 28 10 Susceptible ND

SH3825A 1 SSTI 2008 28 10 Susceptible ND

SH3845A 1 SSTI 2008 830 10 Susceptible ND

SH3846A 1 SSTI 2008 830 10 Susceptible ND

SH3937A 1 Invasive 2009 28 10 Susceptible ND

SH3948A 1 Invasive 2008 28 44 Susceptible ND

SH3956A 1 Invasive 2008 28 3 Susceptible ND

SH4050A 1 Invasive 2009 28 10 Susceptible ND

SH4069A 1 Invasive 2008 28 10 Susceptible ND

SH4140A 1 Invasive 2009 28 10 Susceptible ND

SH4353A 1 SSTI 2009 28 10 Susceptible ND

SH4620A 1 Invasive 2008 28 10 Susceptible ND

SH4859A 1 Invasive 2009 28 10 Susceptible ND

SH4869A 1 Invasive 2009 28 10 Susceptible ND

SH4947A 1 Invasive 2009 28 10 Susceptible ND

SH4949A 1 SSTI 2009 28 10 Susceptible ND

SH4974A 1 Invasive 2010 28 3 Susceptible ND

SH5069A 1 Invasive 2010 28 10 Susceptible ND

SH5829A 1 Invasive 2011 28 10 Susceptible ND

SH6186A 1 Invasive 2011 28 10 Susceptible ND

SH6214A 1 Invasive 2011 28 3 Susceptible ND

SH6244A 1 Invasive 2011 28 3 Susceptible ND

SH6308A 1 Invasive 2011 28 10 Susceptible ND

SH6444A 1 Invasive 2011 28 10 Susceptible ND

SH6523A 1 Invasive 2011 28 10 Susceptible ND

SH6618A 1 Invasive 2012 28 10 Susceptible ND

SH6681A 1 Invasive 2011 28 10 Susceptible ND

SH6765A 1 Invasive 2012 28 10 Susceptible ND

SH6740A 1 Invasive 2012 28 10 Susceptible ND

SH6871A 1 Invasive 2012 28 10 Susceptible ND

SH7140A 1 Invasive 2012 28 10 Susceptible ND

SH7156A 1 Invasive 2012 28 10 Susceptible ND

SH7448A 1 Invasive 2012 28 10 Susceptible ND

81

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH7567A 1 Invasive 2012 28 10 Susceptible ND

SH8114A 1 Invasive 2013 28 10 Susceptible ND

SH8254A 1 Invasive 2013 28 10 Susceptible ND

SH8387A 1 Invasive 2013 28 10 Susceptible ND

SH8391A 1 Invasive 2013 28 10 Susceptible ND

SH8565A 1 Invasive 2014 28 10 Susceptible ND

SH8572A 1 Invasive 2014 28 10 Susceptible ND

SH8638A 1 Invasive 2014 28 10 Susceptible ND

SH10138A 1 Invasive 2014 28 10 Susceptible ND

SH11549A 1 Invasive 2011 28 10 Susceptible ND

2001V0647P 1 Invasive 2001 28 10 Susceptible ND

2001V0953P 1 Invasive 2001 28 10 Susceptible ND

2002V1396P 1 Invasive 2002 28 10 Susceptible ND

2002V1422P 1 Invasive 2002 28 10 Susceptible ND

2002V1491P 1 Invasive 2002 28 3 Susceptible ND

2003V0699P 1 Invasive 2003 28 10 Susceptible ND

2003V0729P 1 Invasive 2003 28 10 Susceptible ND

2003V1351P 1 Invasive 2003 28 10 Susceptible ND

2003V1477P 1 Pharyngitis 2003 28 10 Susceptible ND

2004V0014P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V0347P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V0582P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V0585P 1 Invasive 2004 28 10 Susceptible ND

2004V0695P 1 Invasive 2004 28 10 Susceptible ND

2004V0959P 1 Invasive 2004 28 10 Susceptible ND

2004V0977P 1 Invasive 2004 28 10 Susceptible ND

2004V1249P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V1259P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V1287P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V1816P 1 Invasive 2004 28 10 Susceptible ND

2004V1857P 1 Pharyngitis 2004 28 10 Susceptible ND

2004V1887P 1 Invasive 2004 28 10 Susceptible ND

2005V1116P 1 Pharyngitis 2005 28 10 Susceptible ND

2005V1838P 1 Pharyngitis 2005 28 10 Susceptible ND

491PT 3 Pharyngitis 2001 15 8 Susceptible ND

SH0125A 3 Invasive 2003 406 8 Susceptible ND

SH0274A 3 Invasive 2004 15 8 Susceptible ND

SH0877A 3 Invasive 2005 406 8 Susceptible ND

SH0957A 3 Invasive 2005 15 8 Susceptible ND

SH0958A 3 Invasive 2005 15 8 Susceptible ND

SH1034A 3 Invasive 2005 15 8 Susceptible ND

SH1097A 3 Invasive 2005 406 8 Susceptible ND

SH1108A 3 Invasive 2005 406 8 Susceptible ND

SH1347A 3 SSTI 2006 315 8 Susceptible ND

SH1527A 3 Invasive 2005 15 8 Susceptible ND

SH1669A 3 Invasive 2006 15 8 Susceptible ND

SH1702A 3 SSTI 2006 15 8 Susceptible ND

SH1999A 3 Invasive 2006 315 8 Susceptible ND

SH2228A 3 SSTI 2006 315 8 Susceptible ND

SH2283A 3 Invasive 2006 15 8 Susceptible ND

SH2285A 3 SSTI 2006 315 8 Susceptible ND

SH2334A 3 Invasive 2007 15 8 Susceptible ND

SH2339A 3 SSTI 2007 15 8 Susceptible ND

SH2351A 3 Invasive 2007 315 8 Susceptible ND

SH2424A 3 Invasive 2007 406 8 Susceptible ND

82

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH2438A 3 Invasive 2007 15 53 Susceptible ND

SH2510A 3 Invasive 2007 15 8 Susceptible ND

SH2518A 3 SSTI 2007 15 8 Susceptible ND

SH2522A 3 SSTI 2007 15 53 Susceptible ND

SH3061A 3 Invasive 2007 15 8 Susceptible ND

SH3264A 3 Invasive 2008 15 8 Susceptible ND

SH3626A 3 SSTI 2008 315 8 Susceptible ND

SH4005A 3 Invasive 2009 15 8 Susceptible ND

SH4019A 3 SSTI 2009 15 8 Susceptible ND

SH4138A 3 SSTI 2009 15 8 Susceptible ND

SH5586A 3 Invasive 2010 15 9 Susceptible ND

SH5633A 3 Invasive 2010 15 8 Susceptible ND

SH8595A 3 Invasive 2013 15 8 Susceptible ND

SH6223A 3 Invasive 2011 406 8 Susceptible ND

SH6647A 3 Invasive 2012 15 9 Susceptible ND

SH6692A 3 Invasive 2012 15 8 Susceptible ND

SH6759A 3 Invasive 2012 315 9 Susceptible ND

SH6507A 3 Invasive 2011 315 53 Susceptible ND

2001V0262P 3 Invasive 2001 15 8 Susceptible ND

2001V0648P 3 Invasive 2001 15 8 Susceptible ND

2001V0846P 3 Pharyngitis 2001 15 8 Susceptible ND

2001V0848P 3 Invasive 2001 406 8 Susceptible ND

2002V0356P 3 Pharyngitis 2002 406 8 Susceptible ND

2002V0596P 3 Invasive 2002 406 8 Susceptible ND

2002V0810P 3 Pharyngitis 2002 406 8 Susceptible ND

2002V0813P 3 Pharyngitis 2002 315 37 Susceptible ND

2002V1041P 3 Pharyngitis 2002 15 8 Susceptible ND

2002V1364P 3 Pharyngitis 2002 315 37 Susceptible ND

2002V1405P 3 Invasive 2002 406 8 Susceptible ND

2002V1490P 3 Invasive 2002 406 8 Susceptible ND

2003V0745P 3 Pharyngitis 2003 406 8 Susceptible ND

2005V0082P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V0404P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V0996P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V1395P 3 Pharyngitis 2005 15 2 Susceptible ND

2005V1511P 3 Pharyngitis 2005 15 8 Susceptible ND

2005V1513P 3 Pharyngitis 2005 15 8 Susceptible ND

2005V1791P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V1832P 3 Pharyngitis 2005 15 8 Susceptible ND

2005V1930P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V1935P 3 Pharyngitis 2005 406 8 Susceptible ND

2005V1949P 3 Pharyngitis 2005 15 2 Susceptible ND

2005V1950P 3 Pharyngitis 2005 15 1 Susceptible ND

SH0264A 4 SSTI 2003 38 23 M ND

SH0520A 4 Invasive 2004 39 23 M ND

SH0807A 4 SSTI 2005 39 23 M ND

SH1749A 4 Invasive 2006 771 44 Susceptible ND

SH1997A 4 SSTI 2006 39 23 Susceptible ND

SH2211A 4 SSTI 2006 39 23 M ND

SH2280A 4 SSTI 2007 39 23 Susceptible ND

SH2289A 4 Invasive 2006 39 1 Susceptible ND

SH2423A 4 SSTI 2007 39 23 Susceptible ND

SH2476A 4 Invasive 2007 823 23 Susceptible ND

SH2621Ab 4 SSTI 2007 38 41 M ND

SH2634A 4 Invasive 2007 39 23 M ND

83

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH2704A 4 Invasive 2007 39 23 Susceptible ND

SH3096A 4 SSTI 2007 39 23 Susceptible ND

SH3782A 4 Invasive 2008 39 23 Susceptible ND

SH4073A 4 SSTI 2009 39 23 Susceptible ND

SH4267A 4 SSTI 2009 39 23 Susceptible ND

SH4343A 4 Invasive 2009 39 23 Susceptible ND

SH4445A 4 SSTI 2009 39 23 Susceptible ND

SH4490A 4 Invasive 2009 39 23 M ND

SH4577A 4 SSTI 2009 39 23 Susceptible ND

SH4691A 4 SSTI 2009 39 23 Susceptible ND

SH5409A 4 Invasive 2010 39 94 Susceptible ND

SH5655A 4 Invasive 2010 39 23 Susceptible ND

SH5852A 4 Invasive 2011 39 23 Susceptible ND

SH7089A 4 Invasive 2012 - 44 Susceptible ND

2001V0960P 4 Invasive 2001 39 23 Susceptible ND

2002V1221P 4 Pharyngitis 2002 39 23 Susceptible ND

2003V0483P 4 Invasive 2003 39 23 M ND

2003V0512P 4 Invasive 2003 39 23 M ND

2003V0692P 4 Pharyngitis 2003 39 22 Susceptible ND

2003V0735P 4 Pharyngitis 2003 39 23 M ND

2003V0742P 4 Pharyngitis 2003 39 41 M ND

2003V0739P 4 Invasive 2003 39 23 Susceptible ND

2003V0853P 4 Pharyngitis 2003 39 23 Susceptible ND

2003V1116P 4 Invasive 2003 39 23 Susceptible ND

2003V1320P 4 Pharyngitis 2003 39 23 Susceptible ND

2003V1332P 4 Pharyngitis 2003 39 23 M ND

2003V1350P 4 Invasive 2003 39 23 M ND

2003V1352P 4 Pharyngitis 2003 39 40 M ND

2004V0444P 4 Invasive 2004 39 23 M ND

2004V1028P 4 Pharyngitis 2004 39 23 Susceptible ND

2004V1227P 4 Pharyngitis 2004 39 30 M ND

2004V1228P 4 Pharyngitis 2004 39 23 M ND

2004V1233P 4 Pharyngitis 2004 39 30 M ND

2004V1235P 4 Pharyngitis 2004 39 23 Susceptible ND

2004V1400P 4 Pharyngitis 2004 39 23 Susceptible ND

2004V1802P 4 Pharyngitis 2004 39 23 M ND

2004V1879P 4 Invasive 2004 39 23 M ND

2005V0167P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V0398P 4 Pharyngitis 2005 39 23 M ND

2005V0417P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V1272P 4 Pharyngitis 2005 39 23 M ND

2005V1440P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V1449P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V1572P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V1783P 4 Pharyngitis 2005 39 22 Susceptible ND

2005V1797P 4 Pharyngitis 2005 39 23 Susceptible ND

2005V2258P 4 Pharyngitis 2005 39 23 Susceptible ND

551PT 89 Pharyngitis 2001 568 43 Susceptible +

SH0036A 89 Invasive 2003 408 27 Susceptible +

SH0201A 89 SSTI 2004 101 27 Susceptible +

SH0424A 89 Invasive 2004 408 27 Susceptible +

SH0456A 89 Invasive 2004 408 27 Susceptible +

SH0496A 89 Invasive 2004 408 27 Susceptible +

SH0759A 89 Invasive 2005 408 27 Susceptible +

SH0865A 89 Invasive 2005 101 27 Susceptible +

84

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH0992A 89 SSTI 2005 101 27 Susceptible +

SH1037A 89 SSTI 2005 101 46 Susceptible +

SH1118A 89 SSTI 2005 408 27 Susceptible +

SH1401A 89 SSTI 2006 101 29 Susceptible -

SH1712A 89 SSTI 2006 101 46 Susceptible +

SH2212A 89 Invasive 2006 408 29 Susceptible +

SH2431A 89 SSTI 2007 101 46 Susceptible +

SH2449A 89 SSTI 2007 408 27 Susceptible +

SH2827A 89 SSTI 2007 408 27 Susceptible +

SH2841A 89 Invasive 2007 824 29 Susceptible -

SH2914A 89 SSTI 2007 101 29 Susceptible -

SH2920A 89 SSTI 2007 824 29 Susceptible -

SH3097A 89 SSTI 2008 101 26 Susceptible -

SH3222A 89 Invasive 2008 101 29 Susceptible -

SH3260A 89 SSTI 2008 408 27 Susceptible +

SH3281A 89 Invasive 2008 101 29 Susceptible -

SH3298A 89 SSTI 2008 824 29 Susceptible -

SH3350A 89 SSTI 2008 824 29 Susceptible -

SH3439A 89 Invasive 2008 824 29 Susceptible -

SH3523A 89 SSTI 2008 101 29 Susceptible -

SH3602A 89 Invasive 2008 101 29 Susceptible -

SH3603A 89 Invasive 2008 101 46 Susceptible +

SH3630A 89 SSTI 2008 824 29 Susceptible -

SH3638A 89 SSTI 2008 101 29 Susceptible -

SH3641A 89 SSTI 2008 824 29 Susceptible -

SH3755A 89 SSTI 2008 408 27 Susceptible +

SH3904A 89 SSTI 2008 101 29 Susceptible -

SH3905A 89 SSTI 2008 101 29 Susceptible -

SH3907A 89 SSTI 2008 101 29 Susceptible -

SH3954A 89 SSTI 2008 101 29 Susceptible -

SH4017A 89 SSTI 2008 101 29 Susceptible -

SH4067A 89 Invasive 2008 101 46 Susceptible -

SH4102A 89 Invasive 2009 101 29 Susceptible -

SH4345A 89 SSTI 2009 824 29 Susceptible -

SH4357A 89 Invasive 2009 101 29 Susceptible -

SH4377A 89 SSTI 2009 101 46 Susceptible -

SH4612A 89 Invasive 2009 101 29 Susceptible -

SH4701A 89 SSTI 2009 408 29 Susceptible +

SH4846A 89 SSTI 2009 824 29 Susceptible -

SH4950A 89 SSTI 2009 101 46 Susceptible +

SH4951A 89 SSTI 2009 101 46 Susceptible +

SH5354A 89 Invasive 2010 101 29 Susceptible -

SH5723A 89 Invasive 2010 101 29 cMLSB -

SH6103A 89 Invasive 2011 101 29 Susceptible -

SH6140A 89 Invasive 2011 - 29 Susceptible -

SH6560A 89 Invasive 2011 408 29 Susceptible +

SH6617A 89 Invasive 2012 101 29 Susceptible -

SH6969A 89 Invasive 2012 101 26 Susceptible -

SH7051A 89 Invasive 2012 101 29 Susceptible -

SH7052A 89 Invasive 2012 101 29 Susceptible -

SH7388A 89 Invasive 2012 101 29 Susceptible -

SH7840A 89 Invasive 2013 101 29 Susceptible -

SH8554A 89 Invasive 2013 101 29 Susceptible -

SH9147A 89 Invasive 2014 101 29 cMLSB -

SH9212A 89 Invasive 2014 - 29 Susceptible -

85

Isolates ID emm type Type of

infection Year of

isolation ST

SAg

profilea

Macrolide resistance phenotype

hasABC locus

SH11927A 89 Invasive 2014 - 46 Susceptible -

2001V0807P 89 Pharyngitis 2001 101 40 Susceptible +

2002V1138P 89 Invasive 2002 101 27 Susceptible +

2002V1366P 89 Invasive 2002 407 46 Susceptible +

2003V0714P 89 Pharyngitis 2003 408 27 Susceptible +

2003V0731P 89 Invasive 2003 408 27 Susceptible +

2003V0836P 89 Pharyngitis 2003 408 27 Susceptible +

2003V1300P 89 Pharyngitis 2003 568 43 Susceptible +

2004V0754P 89 Pharyngitis 2004 101 46 Susceptible +

2004V1002P 89 Pharyngitis 2004 101 46 Susceptible +

2004V1019P 89 Pharyngitis 2004 101 27 Susceptible +

2004V1245P 89 Pharyngitis 2004 408 29 Susceptible +

2004V1248P 89 Pharyngitis 2004 408 29 Susceptible +

2004V1251P 89 Pharyngitis 2004 408 27 Susceptible +

2004V1257P 89 Pharyngitis 2004 101 29 Susceptible -

2005V0414P 89 Pharyngitis 2005 101 29 Susceptible -

2005V1903P 89 Pharyngitis 2005 101 29 Susceptible -

2005V1909P 89 Pharyngitis 2005 101 29 Susceptible -

a The SAg profiles numbering follows the one adopted previously (99, 131).

b Isolate SH2621A (belonging to clone emm4-EryR and isolated from SSTI) was not included in the genomic

analysis due to the lack of raw sequencing data at the time of the study.

86

Table S3. The isolates selected within each of the six clones of interest are listed, as well as the respective year of

isolation, type of infection, ST and SAg profile. SSTI: skin and soft tissue infection. A total of 68 strains were

selected: 15 from each emm1 and emm3 clones, 12 from emm4-EryS group, 10 from emm89-hasABC+ group and

8 from each emm89-hasABC- and emm4-EryR groups.

emm1-EryS (n=15) emm3 (n=15)

Isolates ID Year of isolation

Type of infection

ST SAg

profile Isolates ID

Year of isolation

Type of infection

ST SAg

profile

SH0011A 2003 SSTI 28 61 SH0274A 2004 Invasive 15 8

SH0203A 2004 Invasive 28 10 SH1097A 2005 Invasive 406 8

SH0253A 2003 SSTI 28 3 SH2285A 2006 SSTI 315 8

SH0915A 2005 Invasive 28 10 SH2438A 2007 Invasive 15 53

SH1102A 2005 Invasive 643 10 SH2510A 2007 Invasive 15 8

SH1131A 2005 Invasive 28 10 SH4138A 2009 SSTI 15 8

SH3077A 2007 Invasive 28 44 SH5586A 2010 Invasive 15 9

SH3123A 2007 SSTI 28 10 SH6223A 2011 Invasive 406 8

SH3210A 2008 SSTI 28 3 SH6647A 2012 Invasive 15 9

SH3845A 2008 SSTI 830 10 2001V0846P 2001 Pharyngitis 15 8

SH4859A 2009 Invasive 28 10 2002V0356P 2002 Pharyngitis 406 8

SH6186A 2011 Invasive 28 10 2002V1364P 2002 Pharyngitis 315 37

SH8254A 2013 Invasive 28 10 2005V0404P 2005 Pharyngitis 406 8

2003V1477P 2003 Pharyngitis 28 10 2005V1832P 2005 Pharyngitis 15 8

2004V0014P 2004 Pharyngitis 28 10 2005V1950P 2005 Pharyngitis 15 1

emm89-hasABC+ (n=10) emm89-hasABC- (n=8)

Isolates ID Year of isolation

Type of infection

ST SAg

profile Isolates ID

Year of isolation

Type of infection

ST SAg

profile

551PT 2001 Pharyngitis 568 43 SH2920A 2007 SSTI 824 29

SH0201A 2004 SSTI 101 27 SH3904A 2008 SSTI 101 29

SH1037A 2005 SSTI 101 46 SH4067A 2008 Invasive 101 46

SH1712A 2006 SSTI 101 46 SH4345A 2009 SSTI 824 29

SH4701A 2009 SSTI 408 29 SH4612A 2009 Invasive 101 29

SH4950A 2009 SSTI 101 46 SH6140A 2011 Invasive - 29

SH6560A 2011 Invasive 408 29 SH11927A 2014 Invasive - 46

2001V0807P 2001 Pharyngitis 101 40 2005V0414P 2005 Pharyngitis 101 29

2002V1366P 2002 Invasive 407 46 2004V1019P 2004 Pharyngitis 101 27

emm4-EryS (n=12) emm4-EryR (n=8)

Isolates ID Year of isolation

Type of infection

ST SAg

profile Isolates ID

Year of isolation

Type of infection

ST SAg

profile

SH1749A 2006 Invasive 771 44 SH0264A 2003 SSTI 38 23

SH2289A 2006 Invasive 39 1 SH2211A 2006 SSTI 39 23

SH2423A 2007 SSTI 39 23 SH4490A 2009 Invasive 39 23

SH2476A 2007 Invasive 823 23 2003V0512P 2003 Invasive 39 23

SH4073A 2009 SSTI 39 23 2003V0742P 2003 Pharyngitis 39 41

SH5409A 2010 Invasive 39 94 2003V1352P 2003 Pharyngitis 39 40

SH7089A 2012 Invasive - 44 2004V1227P 2004 Pharyngitis 39 30

2002V1221P 2002 Pharyngitis 39 23 2005V1272P 2005 Pharyngitis 39 23

2003V0692P 2003 Pharyngitis 39 22 2005V1440P 2005 Pharyngitis 39 23 2005V1572P 2005 Pharyngitis 39 23 2005V2258P 2005 Pharyngitis 39 23

87

Figure S1. A: Distance matrix visualization between nodes within each emm type. For emm4, the two strains that

failed to group with the other emm4 isolates (SH7089A and SH1749A) were excluded from the distance matrix.

Within emm types 3, 4 and 89 groups there is one isolate presenting a higher genetic distance in comparison with

the overall scenario (red rows and columns). B: Distance matrix visualization between nodes within emm types 3,

4 and 89 after excluding the strains displaying higher genetic distance values.

Distance Matrix

SH0264A vs all 2002V1366P vs all

emm1 emm3

emm89emm4

A

B emm3 emm4 emm89

03/09 /2018, 21*45

Page 1 of 2about :blank

Order name

0.00 - 3.29

3.29 - 6.59

6.59 - 9.88

9.88 - 13.18

13.18 - 16.47

16.47 - 19.76

19.76 - 23.06

23.06 - 26.35

26.35 - 29.65

29.65 - 32.94

32.94 - 36.24

03/09/2018, 21*56

Page 1 of 2about :b lank

Order name

0.00 - 6.76

6.76 - 13.53

13.53 - 20.29

20.29 - 27.06

27.06 - 33.82

33.82 - 40.59

40.59 - 47.35

47.35 - 54.12

54.12 - 60.88

60.88 - 67.65

67.65 - 74.41S

H243

8A

vs a

ll

SH2438A vs all

20

02V

1366

P v

s a

ll

SH

0264

A v

s a

ll

88

Figure S2. MST for the 319 GAS cgMLST dataset at a tree cut off of 1052 and association with type of infection.

The size of the nodes is proportional to the number of isolates included in each node. Dataset colored by type of

infection – invasive infections (blue); SSTI (green); pharyngitis (orange). The clones of interest within emm4,

erythromycin-susceptible and -resistant, are highlighted in gray and pink, respectively. The clones of interest within

emm89, hasABC+ and hasABC-, are highlighted in black and blue, respectively.

Invasive

SSTI

Pharyngitis

Type of infection

emm1 emm3

emm89emm4

Erythromycin-resistant

Erythromycin-susceptible

hasABC-

hasABC+

89

Figure S3. MST for the emm1, emm3 and emm89 isolates and association with year of isolation. The size of the

nodes is proportional to the number of isolates included in each node. Dataset colored by year of isolation – 2001

to 2005 (blue gradient, from lighter to darker colors); 2006 to 2009 (green gradient, from lighter to darker colors);

2010-2014 (red/pink gradient, from lighter to darker colors).

Figure S4. Distance matrix visualization between nodes within emm89 clades 2 and 3. Clade 2 isolates harbor the

hasABC locus and the nga promoter variant 2. Clade 3 isolates lack the hasABC locus and carry the nga promoter

variant 3.

Year of

isolation

2001

2002

2003

2004

2005

2006

2007

2008

2009

2010

2011

2012

2013

2014

emm3

emm1

emm89hasABC-

hasABC+

Clade 2

Distance Matrix – emm89Clade 3

90

Figure S5. Distance matrix visualization of erythromycin-susceptible and -resistant emm4 isolates. Two susceptible

isolates and one resistant isolate that presented a much higher genetic distance to the respective groups were

excluded from this analysis.

Figure S6. Growth curves of the 10 strains used in the optimization of the SLO and streptokinase activity

determination assays, with internal duplicates and three independent assays performed for each strain. For each

strain, one growth curve with the mean values of OD for each time is represented, with error bars corresponding to

95% confidence intervals. The OD value chosen to determine the activity of the GAS culture supernatants at mid-

exponential phase was OD600=0.80 and for late-exponential phase a value of OD600=1.10 was considered.

Erythromycin-susceptible

Distance Matrix – emm4

Erythromycin-resistant

0.00

0.20

0.40

0.60

0.80

1.00

1.20

1.40

1.60

0 50 100 150 200 250 300

OD

600

Time (min)

Growth Curves

SF370 MGAS5005 2001V1236P 2005V1791P 2001V0953P 2004V1257P 2003V0731P 2003V1300P SH1066A SH0759A

Late-exponential

Mid-exponential

91

Protocol – Streptolysin O activity determination assay

1st Day

Culture the strains in TSA supplemented with 5% defibrinated sheep blood at 37ºC, for approximately

24h.

2nd Day – Pre-inocula

Culture one colony of each strain in 5 mL of THB. Perform duplicates for each strain and two negative

controls without inoculum (only THB). Incubate at 37ºC, for 24h.

3rd Day– Inocula

1. Transfer 0.5 mL of each bacterial suspension to 4.5 mL of fresh THB.

2. Incubate in a water bath at 37ºC until the optical density of 1.10 is reached (late-exponential phase

of growth).

3. Centrifuge the bacterial suspensions at 3220xg at 4ºC, for 10 min.

4. Transfer 1 mL of the supernatants to a new tube and preserve on ice.

3rd Day – Activity assay

1. Centrifuge 10 mL of fresh sheep blood at 650xg at 4ºC, for 10 min without brake.

2. Discard the supernatant using a pipette and complete the volume up to 10 mL with PBS1x. Mix

carefully and centrifuge again with the same parameters.

3. Repeat step 2.

4. After the last centrifugation, transfer 1.25 mL of the pellet of erythrocytes to 48.75 mL of PBS 1x,

obtaining a suspension of defibrinated sheep erythrocytes 2.5% (v/v). Mix carefully and preserve on

ice.

5. Transfer 200 L of the supernatant of the inocula to a new line of the 96-well microplate.

6. Perform a pre-incubation of the supernatants with 40 g/mL trypan blue and 10 mM DTT for 30 min,

at 37ºC.

7. Prepare the 96-well microplate as follows:

Dilutions: 1/2; 1/4; 1/8; 1/16; 1/32; 1/64; 1/128

Lines A-G: 150 L PBS 1x

92

Wells H11 and H12 (PBS blank): 150 L PBS 1x

Wells H9 and H10 (hemolysis positive control): 50 L PBS 1x + 100 L Triton X-100 3% diluted in water.

8. Transfer 150 L of the pre-incubated supernatants to the first line of the 96-well microplate

previously prepared. Resuspend 3 times with the pipette.

9. Using new tips, transfer 150 L from the first to the second line, resuspending 3 times with the

pipette.

10. Repeat step 9 from the second to the third line and from there consecutively until line G, discarding

150 L from this line.

11. Add 150 L of the suspension of sheep erythrocytes 2.5% (v/v) to every well. Incubate at 37ºC, for

30 min.

12. Centrifuge the plate at 3000xg for 5min, at 4ºC.

13. Transfer 150 L of each well to a new 96-well microplate.

14. Measure the absorbance at 570 nm in a microplate reader.

15. For each dilution, the percentage of hemolysis relative to the positive control is calculated using

formula (1), where the absorbance of the corresponding blank solution, the positive control and the

PBS blank are calculated as the mean of the absorbance of the two wells corresponding to each of

these conditions:

Abs570sample − Abs570blank corresponding dilution

Abs570positive control − Abs570PBS blank× 100

(1)

The SLO activity is defined as the inverse of the highest dilution before the percentage of hemolysis

decreases to half or less. When a two-fold decrease is not observed, the streptolysin activity for the

corresponding strain is considered 3. For each strain, three independent assays are performed to

control inter-assay variability. The majority rule is used to determine the final streptolysin activity value.

Additional information:

1) Intra-assay duplicates are not necessary but three independent assays should be performed to

control inter-assay variability (replicas performed in different days, with different THB and different

blood batches).

93

Plate scheme:

1 2 3 4 5 6 7 8 9 10 11 12

A a1/2 b1/2 c1/2 d1/2 e1/2 f1/2 g1/2 h1/2 i1/2 j1/2 NC1/2 NC1/2

B a1/4 b1/4 c1/4 d1/4 e1/4 f1/4 g1/4 h1/4 i1/4 j1/4 NC1/4 NC1/4

C a1/8 b1/8 c1/8 d1/8 e1/8 f1/8 g1/8 h1/8 i1/8 j1/8 NC1/8 NC1/8

D a1/16 b1/16 c1/16 d1/16 e1/16 f1/16 g1/16 h1/16 i1/16 j1/16 NC1/16 NC1/16

E a1/32 b1/32 c1/32 d1/32 e1/32 f1/32 g1/32 h1/32 i1/32 j1/32 NC1/32 NC1/32

F a1/64 b1/64 c1/64 d1/64 e1/64 f1/64 g1/64 h1/64 i1/64 j1/64 NC1/64 NC1/64

G a1/128 b1/128 c1/128 d1/128 e1/128 f1/128 g1/128 h1/128 i1/128 j1/128 NC1/128 NC1/128

H 100%

hemolysis 100%

hemolysis PBS PBS

a-j: strains tested

NC: negative control

94

Protocol – Standard curve of group C streptokinase

Dilutions used in the standard curve: 1000/ 500/ 250/ 125/ 62.5/ 31.25/ 15.63/ 7.81/ 3.91/ 1.95/ 0.98/

0.49 units/mL

1. Add 50 L of Tris pH 7.5 to each well of the first line of a 96-well microplate to a final concentration

of 50 mM.

2. Add 50 L of commercial SK to the first well for a final concentration of 1000 units/mL. Resuspend

5 times with the pipette.

3. Using a new tip, transfer 50 L from the first to the second well, resuspending 5 times with the

pipette.

4. Repeat step 3 from the third to the fourth well and from there consecutively until the last well,

discarding 50 L from this well.

5. Pre-incubate 230 L of glu-plasminogen with 230 L of fibrinogen (1:1 proportion) at 37 ºC, for 15

min. Final concentrations of glu-plasminogen and fibrinogen in the pre-incubation of 1430 nM.

6. Add 35 L of the pre-incubated solution of glu-plasminogen and fibrinogen to each well of the first

line to a final concentration of glu-plasminogen and fibrinogen of 500 nM.

7. With the plate on ice, add 15 L of the chromogenic agent S-2251 to each well of the two lines for

a final concentration of 500 M.

8. Measure the absorbance at 405 nm every minute for 120 min, at 37ºC.

95

Protocol – Streptokinase activity determination assay

1st Day

Culture the strains in TSA supplemented with 5% defibrinated sheep blood at 37ºC, for approximately

24h.

2nd Day – Pre-inocula

Culture one colony of each strain in 5 mL of THB. Perform duplicates for each strain and two negative

controls without inoculum (only THB). Incubate at 37ºC, for 24h.

3rd Day– Inocula

1. Transfer 0.5 mL of each bacterial suspension to 4.5 mL of fresh THB.

2. Incubate in a water bath at 37ºC until the optical density of 1.10 is reached (late-exponential phase

of growth).

3. Centrifuge the bacterial suspensions at 3220xg at 4ºC, for 10 min.

4. Transfer 1 mL of the supernatants to a new tube and preserve on ice.

3rd Day – Activity assay

1. Pre-incubate 230 L of glu-plasminogen with 230 L of fibrinogen (1:1 proportion) at 37 ºC, for 15

min. Final concentrations of glu-plasminogen and fibrinogen in the pre-incubation of 1430 nM.

2. Add 30 L of Tris pH 7.5 to each well of the first line of a 96-well microplate (assay with plasminogen)

to a final concentration of 50 mM.

3. Add 65 L of Tris pH 7.5 to each well of the second line of the 96-well microplate (assay without

plasminogen) to a final concentration of 50 mM.

4. Add 20 L of commercial SK to the last two wells of each line to a final concentration of 3.90

units/mL. Resuspend 5 times with the pipette.

5. Transfer 20 L of the supernatants to the wells of the two lines except for the last wells in which

commercial SK was previously added.

6. Add 35 L of the pre-incubated solution of glu-plasminogen and fibrinogen to each well of the first

line to a final concentration of glu-plasminogen and fibrinogen of 500 nM.

96

7. With the plate on ice, add 15 L of the chromogenic agent S-2251 to each well of the two lines for

a final concentration of 500 M.

8. Measure the absorbance at 405 nm every minute for 90 min, at 37ºC.

Additional information:

Plate scheme:

1 2 3 4 5 6 7 8 9 10 11 12

A a1 a2 b1 b2 c1 c2 d1 d2 NC1 NC2 SK1 SK2

B a1 a2 b1 b2 c1 c2 d1 d2 NC1 NC2 SK1 SK2

C

D

E

F

G

H

a-d: strains tested

NC: negative control

SK: assay with commercial SK