A prospective survey of Streptococcus pyogenes infections in French Brittany from 2009 to 2017: Comprehensive dynamic of new emergent emm genotypes

Streptococcus pyogenes or group A Streptococcus (GAS) causes diseases ranging from uncomplicated pharyngitis to life-threatening infections. It has complex epidemiology driven by the diversity, the temporal and geographical fluctuations of the circulating strains. Despite the global burden of GAS diseases, there is currently no available vaccination strategy against GAS infections. This study, based on a longitudinal population survey, aimed to understand the dynamic of GAS emm types and to give leads to better recognition of underlying mechanisms for the emergence of successful clones. From 2009 to 2017, we conducted a systematic culture-based diagnosis of GAS infections in a French Brittany population with a prospective recovery of clinical data. The epidemiological analysis was performed using emm typing combined with the structural and functional cluster-typing system for all the recovered strains. Risk factors for the invasiveness, identified by univariate analysis, were computed in a multiple logistic regression analysis, and the only independent risk factor remaining in the model was the age (OR for the entire range [CI95%] = 6.35 [3.63, 11.10]; p<0.0001). Among the 61 different emm types identified, the most prevalent were emm28 (16%), emm89 (15%), emm1 (14%), and emm4 (8%), which accounted for more than 50% of circulating strains. During the study period, five genotypes identified as emm44, 66, 75, 83, 87 emerged successively and belonged to clusters D4, E2, E3, and E6 that were different from those gathering “Prevalent” emm types (clusters A-C3 to 5, E1 and E4). We previously reported significant genetic modifications for emm44, 66, 83 and 75 types resulting possibly from a short adaptive evolution. Herein we additionally observed that the emergence of a new genotype could occur in a susceptible population having specific risk factors or probably lacking a naturally-acquired cluster-specific immune cross-protection. Among emergent emm types, emm75 and emm87 tend to become prevalent with a stable annual incidence and the risk of a clonal expansion have to be considered.

Introduction Streptococcus pyogenes or Group A Streptococcus (GAS) are Gram-positive cocci that usually colonize the human skin and throat and cause a wide variety of diseases ranging in severity from uncomplicated pharyngitis to severe and life-threatening infections [1]. On a global scale, GAS ranked as the fourth deadliest bacterium in the world, with more than 500,000 deaths per year [2].
Lancefield's pioneering work demonstrated that GAS infections elicit a robust immune response by producing opsonizing antibodies against the cell surface M protein encoded by the emm gene [3]. For GAS, M protein is a major immunological and virulence determinant able to bind several host factors (fibrinogen, plasminogen, immunoglobulins) [1]. For an epidemiological survey of GAS infections, emm genotyping based on the sequence of the 5' hypervariable end of the emm gene, is a worldwide-accepted marker [4]. More than 250 different genotypes have been identified and referenced by the Centers for Disease Control and Prevention (CDC), Atlanta. The M-protein-based vaccine appears to be the most promising strategy. Although many trials are in progress (CANVAS Group: Coalition to Accelerate New Vaccines Against Streptococcus) [5], there is currently no available vaccination against GAS infections. Its unavailability is mainly explained by the epidemiological complexity of circulating strains stressed by their geographical diversity and temporal variability [6][7][8][9][10].
The epidemiological studies performed on the different continents revealed remarkable differences between the industrialized and the low-income countries [7,8,[11][12][13]. In a thorough review of studies focussing on the distribution of emm types between global regions, Steer et al. reported that in high-and middle-income countries (Americas, Europe, Asia, and the Middle East), there is essentially a high prevalence of few genotypes (emm1, 12, 28, 3, 4, and 89). In contrast, in Africa and the Pacific Islands, the distribution of emm types is more diverse and does not show dominant emm types [9].
In addition to emm genotyping, and based on their tissue tropism, GAS emm types can also be grouped into patterns where the patterns A to C strains have a preferential pharyngeal tropism, the pattern D has a cutaneous tropism, and the pattern E which is said to be "generalist" having no specific pharyngeal or cutaneous tropism [14]. In tropical countries, the most frequently isolated emm types of GAS belong to emm-pattern D (skin tropism) or E (no specific tropism), as opposed to temperate regions where there are more strains of emm-pattern A-C (pharyngeal tropism) [15]. The reasons for this contrasting molecular epidemiology are not understood. However, to support the notion that skin emm types dominate the epidemiology in many tropical countries, it has been suggested that strains belonging to the pattern E elicit a weaker immune response than throat specialist strains (pattern A-C) [16]. Despite these significant differences in the distribution of emm genotypes, regional and temporal differences within industrialized countries remain poorly explained.
Consistent with emm typing and emm patterns, similar sequences of N terminal part of M proteins, predictable to share functional properties and elicit cross-protective antibodies, has recently been assigned to a specific emm-cluster [17]. Therefore, cluster-typing system proposes a new working hypothesis to analyse epidemiological data with a functional and immunological view. From a public health perspective, it could offer the opportunity to understand better the population's immune susceptibility and explain the emergence of new clones, or yet to anticipate a possible vaccination strategy.
Over nine years of the prospective survey, we first aimed to describe clinical and molecular epidemiology of GAS infections in a population of French Brittany. Secondly, hypothesizing that population immunity has to be considered as a risk for clonal emergence or emm type switching, we analysed the dynamic of "Prevalent" and "Emergent" emm types by combining emm genotyping and emm-cluster system.

Study design and case definition
We conducted a prospective study based on the culture-diagnosis of GAS infections from January 1 st 2009 to December 31 st 2017, at the University Hospital Centre (UHC) of Rennes-France. A case was defined as a patient in whom one or several GAS isolates were collected. For each case, clinical data were collected prospectively by a detailed questionnaire and comprised demographic data (age, sex, residence area. . .), anatomical site of isolates, clinical presentation (asymptomatic, local signs, fever and/or general signs, hemodynamic shock), clinical diagnosis (as reported in the final medical report for each case), the portal of entry (cutaneous, pharyngeal, anogenital or unknown), risk factors and underlying disease (concomitant surgery, pregnancy, diabetes mellitus, chronic lung and heart failure, intravenous drug abuse, homeless, daily alcohol intake, cirrhosis, steroids medication, solid or haematological malignancy. . .), and primary treatment management strategy (medical, surgical, requiring or not intensive care). Combined data were validated weekly to identify any inconsistencies and to recover missing data when possible. Cases were classified into three categories: 1. Carriage: when clinical symptoms were unrelated to GAS infection.
2. Non-invasive disease: when GAS was isolated from non-sterile sites in association with superficial mucosal or cutaneous infections.
3. Invasive disease, which is subcategorized in a) Probable invasive disease: when GAS was isolated from non-sterile sites but caused an acute illness that required surgery or hospital care, and b) Definite invasive disease, when at least one GAS isolate was obtained from a sterile site (e.g., blood, pleural, peritoneal. . .), or when associated with tissue necrosis or hemodynamic shock, either requiring fluid resuscitation or vasopressor drugs.
The results of the study were reported following the STROBE reporting guidelines for observational studies [18].

Gas isolates collection
All GAS isolates were collected in the hospital from clinical samples. Most of the isolates have been collected in the University Hospital Centre (UHC) of Rennes (87% of total), where they have been saved exhaustively for nine years, and regardless of infection site or invasiveness. When several isolates were recovered from the same infection case, only the first isolate was then considered to avoid redundancies. The collection was further enriched with GAS isolates sent from other hospital microbiological laboratories of French Brittany: Lorient, Pontivy, and Vannes (11,5% of total recovered isolates), Saint-Brieuc, and Dinan (1,5%). All GAS isolates were identified by Matrix-Assisted Laser Desorption Ionisation-Mass Spectrometry (MAL-DI-TOF MS, Bruker Daltonics GmbH, Germany). Each isolate was then stored at -80˚C, and sub-cultured at 37˚C with 5% CO 2 on Columbia blood agar plates containing 5% sheep blood (Biorad™, France) before performing any experimental procedure.

Molecular emm typing and emm-cluster typing system
Emm typing was performed by sequencing the 5' portion of the emm gene according to the CDC guidelines, and emm type was determined by submitting the sequence to CDC emm type database (https://www.cdc.gov/streplab/groupa-strep/index.html; last accessed on 23 th November 2020). The designation of each emm-cluster was then deduced as recently described [17].

Epidemiological definition
Depending on the strain occurrence observed during the survey period, each emm type was classified according to three different dynamic profiles assigned as "Prevalent", "Emergent", and "Sporadic" and defined as follows: 1. "Prevalent" emm types: the strains corresponding to genotypes that were isolated continuously, and apart from some fluctuations, their annual rates appeared relatively constant during the study period; 2. "Emergent" emm types: the strains corresponding to genotypes that exhibited a sudden change in their incidence, whether this occurred during a specific lag-time or continued over time; 3. "Sporadic" emm types: did not correspond to the precedent definitions, and each emm type was rarely observed with a prevalence <1% of total isolates.

Data analysis and statistics
The incidence of invasive infections was estimated using the population statistics of French Brittany regions collected from the National Institute of Statistics and Economic Studies (INSEE, https://www.insee.fr/fr/statistiques/2386251; last accessed on 23 th November 2020). Continuous data were expressed as means and standard deviations (SDs), and categorical data as absolute numbers and frequencies. Categorical data were compared by the Chi-square test or Fisher's exact test. The diversity of isolates was expressed by the Simpson's diversity index (SDI) with corresponding 95% confidence intervals (CI 95% ) calculated using online tools (http://www.comparingpartitions.info/; last accessed on 23 th November 2020). Logistic regression analyses were conducted to explore the associations of individual risk factors variables (age, sex, comorbidities, or lifestyle risk factors. . .) with invasiveness ("Invasive" versus "Noninvasive") and emm dynamic profiles ("Prevalent" versus "Sporadic" and "Prevalent" versus "Emergent"). Variables with a significance level of p � 0.20 in univariate analyses were included in a multivariate logistic regression model. The values of Odds ratios (OR) and CI95% were adjusted to sex and age. p-values < 0.05 were considered statistically significant. All statistical analyses were performed using JMP.V13 and SAS 1 V9.4 software (SAS Institute Inc., Cary, USA).

Ethical statement
Ethical approval, or patients' consent, was not required since the study included only microbiological samples and did not involve human subjects or material. Once validated, the database was completely anonymized.

GAS infections and clinical characteristics of the studied population
Between 1st January 2009 and 31st December 2017, GAS isolates were recovered from specimens collected from the skin (38%), oropharyngeal (20%), anogenital (16%), blood (12%), synovial fluid and bone (6%), pleuro-pulmonary (4%) or other (4%) locations. Several isolates could be collected for a single case, but only the first isolate was attached to each of the 942 recorded cases. The diagnosis of GAS infections was mainly performed within the UHC of Rennes, and explain that, over the 21 regions of French Brittany, the majority of GAS isolates was recovered from patients residing in Rennes and the neighbouring areas (S1 Fig). In the UHC of Rennes, the collection was exhaustive since all the isolated GAS were saved. During the surveillance period, and as previously described, we also observed seasonal variation of the rate of infections (invasive and non-invasive), peaking in autumn/winter (S2 Fig) [19].
As indicated in the final medical report, clinical diagnoses were available for almost all the recorded cases except four and were reported in Fig 1. Proportionally, skin and soft tissue infections were the most frequent (45%), followed by ENT-respiratory (23%), anogenital (15%), and bone and joint infections (10%). Isolated bacteraemia represented 2% of the whole population or 6% of all infections defined as invasive. Notably, in our studied population based on hospital diagnosis, ENT-Respiratory infections were more frequently invasive [non-invasive = 65/350 (19%) vs invasive = 154 / 539 (29%)] and were mainly related to the high proportion of pharyngeal infections that required hospital care or surgical treatment.
The portal of entry was identified for all infection cases except for 31 patients in whom it remained unknown (Table 1) and for whom the final diagnosis was septic arthritis (n = 14), isolated bacteraemia (n = 12), central nervous system infections (n = 2), primary peritonitis (n = 2), and pericarditis (n = 1). Overall the studied population, blood cultures were performed for 462 cases (49%). By focusing on the invasive infections, blood cultures had been performed for 69/172 (40%) of the probable invasive and 293/367 (80%) of definite invasive infections, suggesting that the rate of bacteraemia could be underestimated (Table 1).
Depending on their occurrence during the survey, each of the 61 identified emm types was assigned to one of the three dynamic profiles: "Prevalent", "Sporadic", or "Emergent" (see Materials and methods section for definition). Emm types categorized as "Prevalent" encompasses the majority of isolates (n = 686; 72,8%) and corresponded to 9 different emm types (emm 28, 89, 1, 4, 12, 3, 6, 77, and 2). They were isolated from the beginning of the survey with almost a constant occurrence despite little variations around an individual slope (Fig 2). In
Depending on the emm type identified, each case was assigned to one of the three groups of emm type dynamic profiles ("Prevalent", "Sporadic", and "Emergent") that were subsequently analyzed according to the demographic and clinical data, aiming to find specific risk factors that could be associated. As shown in Table 2, the age, the sex, general symptoms related to the infection, the invasiveness of the infection, and the rate of positive blood culture were similar for each of the emm type dynamic profiles. The rate of the cutaneous portal of entry was higher for patients infected with "Sporadic" and "Emergent" emm types, while ENT-respiratory and anogenital portal of entries were higher when infection occurred with "Prevalent" emm types. By performing univariate analysis, risk factors identified to be significantly associated with the group of patients infected with "Emergent" emm types were those related to people living in poor hygienic conditions (homeless, alcohol abuse, of IV drug user) ( Table 2). By computing the data in a logistic regression model and considering the "Prevalent" emm types as a reference category, homeless and alcohol abuse remained both in the model as independent risk factors for the category of patients infected with "Emergent" emm types (Table 3). Furthermore, by analyzing risk factors independently for each of the five "Emergent" emm types we found that infections with emm44 (invasive infections = 16/32; 50%), emm66 (7/13; 54%), and emm83 (10/20; 50%) were significantly linked to patients living in poor hygienic conditions (p<0.001) and associating with one or several risk factors such as homeless, alcoholism or IV drug user. In contrast, we did not find any explanatory clinical risk factors for patients infected with the emergent emm75 (invasive infection = 27/48; 56%) and emm87 (17/26; 65%) genotypes.

Dynamic of emm types and emm-clusters analysis
Protein M is the most immunogenic protein and can confer emm-specific immunity against GAS infections. Emm types and their distribution were organised according to the recently described cluster classification proposed by Sanderson-Smith [21], that, in addition to the structure and function of the M protein, also consider its capacity to induce an immune crossprotection against the other M proteins belonging to the same cluster. Hypothesizing that most frequent or prevalent emm types that circulate in a population may confer a collective immune cross-protection against the other emm types from the same cluster, we analysed the relationship of "Emergent" emm types to their cluster classification. As represented in Fig 3, the 942 emm-typed GAS isolates were assigned to 16 of the 48 described emm-clusters and ordered according to their dynamic profile shown by their densities during the survey period ( Fig 3A).

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a patient with a superficial skin infection that occurred during recent touristic travel in Africa (Senegal). In our study population, "Emergent" emm types (n = 140 GAS isolates; 15%) belonged exclusively to clusters D or E, and within which "Sporadic" emm types could also be classified. We thus observed sequentially the emergence of the genotypes emm44 (before 2009; cluster E3), emm83 (2011; cluster D4), emm75 (2013; cluster E6), emm66 (2013; cluster E2), and emm87 (2013; cluster E3). Consistently, after nine years of comprehensive and prospective surveillance in French Brittany, we did not observe any clonal emergence of a new emm type within the clusters A-C3, A-C4, A-C5, E1 and E4 that gather "Prevalent" genotypes. Therefore, our observation suggested a complementary hypothesis that "Prevalent" emm types would provide a certain degree of immune cross-protection for the population, reducing the probability of allowing the emergence of a new emm type within the same cluster. Of note, despite a high diversity of emm genotypes found within the cluster E4 (4 "Prevalent" and 7 "Sporadic" emmgenotypes), we did not observe the emergence of a new genotype during the study period in this cluster. Finally, emm types clustered as a single protein, and for which it has been proposed that their M protein could have different immunological, structural, and functional characteristics were grouped in the same row and encompassed "Prevalent" (emm6) and "Sporadic" (emm5, emm29, and emm105) emm types (Fig 3).

Discussion
We presented a comprehensive dynamic of GAS emm types over 9-years of prospective culture-based diagnosis in French Brittany. Among the 942 isolates that were clinically documented, 61 different emm types were identified. The most "Prevalent" emm types wereemm28, 89, 1, 4, 12, 3, 6, and 77, in agreement with those reported from other studies performed in developed countries [6,7]. Deciphering the temporal dynamics of the emm genotypes in our studied population, we observed that the five "Emergent" emm types never belonged to clusters within which "Prevalent" genotypes have been identified.

Clinical characteristics of the studied population
We initially analysed our population's clinical characteristics, aiming to compare our data with those of other surveys carried out in industrialized countries. Age distribution of GAS infections is generally described with a higher rate in the elderly, followed by infants under 10 years old. This bimodal distribution suggests possible protection by a natural-immunity acquired through multiple episodes of colonization or infection in early life, and that declines in the "Prevalent" emm type served as a reference category for logistic regression. Odds ratios (OR) and CI 95% for risk factors associated with "Sporadic" and "Emergent" emm types were estimated by performing two independent logistic regressions adjusted by age and sex. https://doi.org/10.1371/journal.pone.0244063.t003

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elderly [20,21]. As reported by Lamagni et al [22], we have also observed increased infection rate between 20 and 40 years. Regarding the UK population, it has been proposed that this reshaping of age distribution results from a high rate of intravenous drug users [22]. In the same way of evidence, we noticed for this age group category an excess of patients having one or several risk factors such as homeless, alcoholism, or intravenous drug use. Besides, we have also observed a high genital tract sepsis rate in women of childbearing age (between 30 and 40

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years old). The primary diagnoses were endometritis and postpartum puerperal sepsis that accounted for about 20% of all the invasive infections for this age category. It has been suggested that altered immune status during pregnancy and specific characteristics of the infecting GAS strain contribute to the risk for GAS infection and mortality in postpartum women [23]. For the overall population, risk factors for invasiveness identified by univariate analysis (age, diabetes, cardiac failure, and malignancy) are consistent with other studies performed in industrialized countries [6,7,19,24]. However, the rate of risk factors identified above increased with ageing, and when analysed with a multivariate logistic regression model, the age remained the unique independent risk factor in our studied population. Gender as a risk factor varies between studies, and this is possibly dependent on the age group distribution of each studied population [7,13,22,[25][26][27][28].
Skin and soft tissue infections were the most frequent clinical presentations, and the severity of the infections required hospitalization for the majority of them. Among cases diagnosed as erysipelas, although frequently described as restricted to the superficial skin and considered as a non-invasive infection, 48% of them have a positive blood culture and subsequently categorised as invasive infections. This may indicate that clinical differentiation of erysipelas is not precise enough, and streptococcal cellulitis could be underdiagnosed.

Dynamic of emm types
For several decades, it has been known that the most potent protective immunity against GAS infection is M specific [3], which produces opsonizing antibodies directed against the N terminus of the M protein. Molecular types sharing structural and functional homologies were inferred to a unique emm-cluster and could elicit cross-protective immunity of almost all emm types within a specific emm-cluster [32]. As in all the surveys performed in industrialized countries, the throat specialist genotypes emm1 (belonging to cluster A-C3), emm12 (A-C4), and emm3 (A-C5) are "Prevalent" [12,33,34], and they are characterized by their ability to have fibrinogen binding properties accounting for a high rate of invasive manifestations. Throughout the nine years of our surveillance, the genotypes emm1, 3 and 12, were dominant emm types without any other emm type competitors identified within their specific emmcluster. Their epidemiological dominance and persistence are not well understood and could be explained by the absence of other circulating emm types belonging to their specific emmclusters. An alternative explanation could be a complex antigenic structure or a specific dynamic for genetic evolution affecting immunogenic epitopes of many A-C emm types with throat tropism [35], preventing a stable and highly-specific long-lasting immunity.
The high prevalence and diversity of emm types encountered for the cluster E4 corroborate other studies [8,33], and may indicate a variable or insufficient cluster-specific natural immune cross-protection. Recent work investigating the cross-protection capabilities against the 17 emm types of the cluster E4 identified the potential requirement of five M peptides (emm2, 8, 22, 89, and 112) to induce a bactericidal cross activity against 15/17 E4 GAS, excepting emm77 and emm114 [32]. Notably, we never recorded any "Emergent" emm type for this cluster, but seven "Sporadic" emm-genotypes were identified.
"Emergent" emm types occurred as an epidemiological shift within the clusters D4, E2, E3 and E6 that were free of any "Prevalent" emm types during all the study period. Mechanisms that can contribute to the emergence of one or more genotypes in a population are not well understood. However, risk factors and genetic modifications of the strain, including the acquisition of new virulence factors, may play variable roles depending on the emm type. Although more challenging to assess, another complementary factor is the lack of protective immunity of the population against GAS, which can thus facilitate the emergence of a specific emm type. Most of emm44, 83 and 66 strains were isolated from patients with specific risk factors such as living in poor conditions and big cities. As we reported previously, the whole genome analysis of some of emergent strains in French Brittany identified a genetic acquisition of new transposons for emm44, and emm83, and mutations resulting in a null allele of a stand-alone RopB regulator for emm66 [36][37][38][39]. The role of these genetic modifications as an explanatory mechanism for clonal emergence remained unknown, and the increase in infection incidence was recorded for only 2 to 3 years. These observations are consistent with studies reporting that short adaptive evolution driven by habitat adaptation (skin or generalist rather than throat specialist strains) underwent horizontal gene transfer events that could offer selective advantages in a susceptible population, either lacking immune protection or having a specific risk factor [35] as we observed in our population.
The European survey published in 2009 indicated that infections with emm75 strains were found only in few countries (Finland, Greece, Germany, and Romania), but remained marginal among the "Prevalent" emm types [6]. As we previously reported [40], the sharp increase of emm75 infection rate observed in 2013 was most likely related to the emergence of a new clone that acquired two new prophages encoding virulence factors (SpeC and SpeK superantigens). Herein, we failed to identify any specific risk factor (clinical or behavioural) that could explain the emergence of the genotype emm75 in a susceptible population. However, the genotype emm75 tended to become prevalent in the French Brittany population where it represents 4 to 6% of strains isolated annually. We do not know if the sustained rise of the emm75 genotype will continue, or if we will observe upsurges or epidemic waves in French Brittany as in other geographic regions. In our opinion, the emergence of genotype emm75 needs careful consideration. First, an emm75 strain isolated from blood culture in 2015 in the UK and recently sequenced (Strain: NCTC13751, GeneBank accession: LS483437) exhibits the same genetic modifications that we have observed in strains isolated in French Brittany. Second, it has recently been reported in Portugal an increasing trend of invasive infections due to the genotype emm75 that also shares the superantigens genes speC and speK [41]. All these strains deserve to be analyzed more in-depth to decipher if this emergence corresponded to the same clonal spread. Our observation can be paralleled with the nationwide increase in invasive disease due to the genotype emm89. This genotype upsurges last decades and has recently been associated with the emergence of a new successful clade variant that has undergone several genetic modifications affecting known virulence factors [42].
Finally, the emergence of the emm87 genotype observed in 2013 is remarkable because it predominates in England while seldom isolated in the rest of Europe [6]. The spreading of the genotype emm87 may have occurred in French Brittany, given the geographical proximity and frequent exchanges between the two countries.
The monocentric design is the main limitation of our study, and other population-based investigations are required to confirm our findings. However, many strengths have to be considered, including the prospective and longitudinal collection of strains from invasive and non-invasive infections with their attached clinical data. Also, the geographic delimitation to a population-based recovery of GAS strain enabled us to observe a comprehensive dynamic of circulating emm types.
After nine years of GAS infection surveillance, we described a high diversity of circulating GAS emm types and characterized accurately epidemiological shifts and dynamic profiles of five successive "Emergent" emm types (emm44, 66, 75, 83 and 87). They occurred within emmclusters different from those gathering "Prevalent" emm types that could suggest a population susceptibility potentially due to a weak natural immune cluster-specific cross-protection. The emergence of the genotype emm75 occurred in 2013 is now marked by a sustained prevalence suggesting a potential expansion of a successful clone. Dynamic monitoring of GAS infections by combining at least molecular emm typing and cluster classification remains the keystone strategy for epidemiological surveillance.  Table. Emm types diversity "In Rennes" area and "Out Rennes" grouped areas. For each identified emm types, the total number of GAS isolates (n) and percentage of the total (%) were indicated in the corresponding column. For the most frequent genotypes (n > 10 isolates) we performed a categorical analysis (Fisher's exact test) to compare the rate of their occurrence "In Rennes" vs "Out Rennes" groups. Simpson's Indexes of Diversity (SDI) and their comparison were given at the bottom of the table. � Among the 942 emm-typed GAS isolates, 1 missed value for the residential area. (DOCX) S1 File. (XLSX)