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
10
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
11
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
15
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).
20
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