Molecular Epidemiology of Noninvasive and Invasive Group A Streptococcal Infections in Cape Town.

Group A streptococcus (GAS) is responsible for a wide range of noninvasive group A streptococcal (non-iGAS) and invasive group A streptococcal (iGAS) infections. Information about the emm type variants of the M protein causing GAS disease is important to assess potential vaccine coverage of a 30-valent vaccine under development, particularly with respect to how they compare and contrast with non-iGAS isolates, especially in regions with a high burden of GAS. We conducted a prospective passive surveillance study of samples from patients attending public health facilities in Cape Town, South Africa. We documented demographic data and clinical presentation. emm typing was conducted using CDC protocols. GAS was commonly isolated from pus swabs, blood, deep tissue, and aspirates. Clinical presentations included wound infections (20%), bacteremia (15%), abscesses (9%), and septic arthritis (8%). Forty-six different emm types were identified, including M76 (16%), M81 (10%), M80 (6%), M43 (6%), and M183 (6%), and the emm types were almost evenly distributed between non-iGAS and iGAS isolates. There was a statistically significant association with M80 in patients presenting with noninvasive abscesses. Compared to the 30-valent vaccine under development, the levels of potential vaccine coverage for non-iGAS and iGAS infection were 60% and 58%, respectively, notably lower than the coverage in developed countries; five of the most prevalent emm types, M76, M81, M80, M43, and M183, were not included. The emm types from GAS isolated from patients with invasive disease did not differ significantly from those from noninvasive disease cases. There is low coverage of the multivalent M protein vaccine in our setting, emphasizing the need to reformulate the vaccine to improve coverage in areas where the burden of disease is high.IMPORTANCE The development of a vaccine for group A streptococcus (GAS) is of paramount importance given that GAS infections cause more than 500,000 deaths annually across the world. This prospective passive surveillance laboratory study evaluated the potential coverage of the M protein-based vaccine currently under development. While a number of GAS strains isolated from this sub-Sahara African study were included in the current vaccine formulation, we nevertheless report that potential vaccine coverage for GAS infection in our setting was approximately 60%, with four of the most prevalent strains not included. This research emphasizes the need to reformulate the vaccine to improve coverage in areas where the burden of disease is high.

INTRODUCTION

The World Health Organization (WHO) ranked group A β-hemolytic streptococcus (GAS) (also known as Streptococcus pyogenes) the ninth leading single-organism cause of human mortality due to infectious diseases, with the majority of deaths attributable to invasive group A streptococcal (iGAS) diseases and rheumatic heart disease (1). The majority of cases occur in developing countries (2). It is believed that >600,000 cases of iGAS infection occur annually, with >160,000 deaths. Despite these alarming numbers, data on iGAS infection in developing countries are scant (2).

GAS is responsible for a wide range of noninvasive (non-iGAS) and iGAS diseases (3, 4). These diseases range from mild infections such as impetigo and pharyngitis to serious diseases such as streptococcal toxic shock syndrome and necrotizing fasciitis. Moreover, GAS may trigger autoimmune diseases, such as acute rheumatic fever (ARF) and rheumatic heart disease (RHD) and acute poststreptococcal glomerulonephritis (APSGN) (2), following repeated episodes of infection.

Primary prevention of GAS has been focused on the development of a vaccine; the most advanced being a 30-valent vaccine formulation (5). The GAS M protein, encoded by the emm gene, consists of four structural repeat blocks that have been intensively explored in epidemiological studies of GAS (6). The M serotypes in the current vaccine formulation were included on the basis of data from the developed world, with cross-coverage of certain emm types being observed. Information about the emm types causing iGAS disease is crucially important to assess potential vaccine coverage, especially in regions such as sub-Saharan Africa, where the burden of iGAS disease is among the highest (2).

There is a dearth of emm type data in sub-Saharan Africa; three studies (7–9) have reported the molecular typing of non-iGAS, and a single study (10) reported on the molecular epidemiology of iGAS. The African GAS infection registry (the AFROStrep Study) was established to collect epidemiological data on GAS in Africa, where surveillance information is largely lacking (11). Launched in 2016 with a pilot project in South Africa, AFROStrep aimed to provide an understanding of GAS disease in Africa.

By means of a prospective surveillance laboratory study, under the auspices of AFROStrep, we sought to determine the extent of GAS infections and the molecular characteristics of the GAS isolates that cause disease among inpatients and outpatients attending Groote Schuur Hospital (GSH) in Cape Town, so as to inform the development of M protein-based vaccines. Additionally, we investigated how iGAS isolates compare and contrast with non-iGAS isolates with respect to their respective molecular characteristics.

RESULTS

From February 2016 to March 2017, 488 laboratory-confirmed GAS cases were identified at the National Health Laboratory Service (NHLS) based at GSH in Cape Town. Characteristics of patients with non-iGAS and iGAS infection are listed in Table 1. The median age was 31 years (interquartile range [IQR], 21 to 45 years). GAS was more commonly isolated from males (63%). iGAS accounted for 46% of GAS cases. Patients with iGAS infection were older, with a median age of 36 years (IQR, 22 to 53 years), than patients who had non-iGAS infection, with a median age of 29 years (IQR, 20 to 40 years). The proportion of patients with iGAS infections was higher for newborns and patients ≥65 years old than for the other patients.

TABLE 1

Gender and age distribution of cases with noninvasive and invasive GAS infection in Cape Town

Parameter	No. (%) of cases
	Non-iGAS (n = 262)	iGAS (n = 226)	Total (n = 488)
Sex
Female	100 (38)	76 (34)	176 (36)
Male	162 (62)	143 (63)	305 (63)
NS		7 (3)	7 (1)
Age
≤12 mo	4 (2)	10 (4)	14 (3)
>1–5 yrs	20 (8)	12 (5)	32 (7)
>5–12 yrs	25 (10)	11 (5)	36 (7)
>12–18 yrs	12 (5)	6 (3)	18 (4)
>18–64 yrs	192 (72)	140 (62)	332 (68)
≥65 yrs	9 (3)	26 (12)	45 (9)
Unknown		21 (9)	21 (2)

Non-iGAS, noninvasive group A streptococcus; iGAS, invasive group A streptococcus; NS, not stated.

Clinical information was available for 460 (94%) isolates (Table 2). Among non-iGAS cases, the most common clinical manifestations were wound infections (34%), abscesses (11%), and hand sepsis (11%). For iGAS infections, the most common clinical presentations were bacteremia (33%), septic arthritis (18%), and abscesses (7%). emm 80 was significantly associated with patients presenting with non-iGAS abscesses (P = 0.007).

TABLE 2

Clinical manifestations of noninvasive and invasive GAS infection by age category

Parameter	No. of patients with clinical manifestations by age category						Total no. (%)
	≤12 mo	1–5 yrs	6–12 yrs	13–18 yrs	19–64 yrs	≥65 yrs
Noninvasive GAS infection (n = 262)
Wound infection	1	6	11	5	63	3	89 (34)
Abscess	1	4	2	2	19	1	29 (11)
Hand sepsisb	0	2	4	2	20	0	28 (11)
Hand infection	0	0	1	1	15	0	18 (6)
Lower limb infection	0	1	0	0	15	2	18 (7)
Otherc	2	6	6	0	42	2	58 (26)
NS							2222 (8)
Invasive GAS infection (n = 226)
Bacteremia	7	5	2	1	41	18	74 (33)
Septic arthritis	0	3	3	1	29	5	41 (18)
Abscess	2	0	1	0	13	0	16 (7)
Necrotizing fasciitis	0	0	0	1	10	1	12 (5)
Wound infection	0	0	0	0	7	1	8 (4)
Cellulitis	0	1	0	0	4	0	5 (2)
Osteomyelitis	0	0	1	0	4	0	5 (2)
Erysipelas	0	0	1	0	3	0	4 (2)
Otherc	1	2	3	2	25	1	34 (15)
NS							6 (3)
Missing age data							21 (9)

GAS, group A streptococcus; NS, not stated; N, number of cases with clinical manifestations.

Hand sepsis is considered noninvasive because infection was inoculated through the skin.

Other, symptoms of another disease(s) occurring in <5 patients, including osteitis, osteomyelitis, empyema, and meningitis, among others.

Information on the site of sampling was available for 475 isolates (97%); data were recorded as detailed on the laboratory requisition form. In addition to those listed in Table 3, bone, nasal swabs and tissue samples were included under “other.” Thirteen isolates had no site of isolation information; however, classifications into non-iGAS and iGAS infections were based on clinical data and additional information recorded in the notes section of the case report form (CRF).

TABLE 3

Sample sources of cases with noninvasive and invasive GAS infection in Cape Town

Sample source	No. (%) of cases
Pus swab	258 (53)
Blood	90 (18)
Deep tissue	47 (10)
Abscess	36 (7)
Aspirate	31 (6)
CSF	5 (1)
Other	8 (2)
NS	13 (3)
Total	488 (100)

CSF, cerebrospinal fluid; NS, not stated.

Distribution of M types.

Molecular evaluation was conducted on 238 isolates; reasons for lack of typing included contaminated agar plates (following subculture of GAS isolates), failed PCRs, and isolates awaiting sequencing. Forty-six emm types were identified in 233 non-iGAS and iGAS isolates (Fig. 1). The 10 most prevalent emm types accounted for >67% of the isolates; these were, in descending order, M76 (16%), M81 (10%), M80 (6%), M43.7 (6%), M183.2 (6%), M44 (5%), M53 (5%), M92 (5%), M184 (4%), and M116 (3.0%). Twenty different emm types accounted for 86% of GAS isolates. Twenty emm types were represented only once, including STG1750.0, previously thought to be group G streptococcus (12). Analyses of five isolates failed to identify emm types, with results classified as “no hits found.”

FIG 1

Distribution of emm types identified by analysis of noninvasive and invasive GAS isolates. non-igas, noninvasive group A streptococcus; igas, invasive group A streptococcus.

Vaccine coverage.

We assessed the proportion of emm types that were included in the 30-valent GAS vaccine currently being developed (5). Fifteen emm types among our cohort are included in the vaccine and were represented by 54 GAS isolates (23%) (Fig. 2). Fifteen nonvaccine emm types representing 100 isolates (43%) have shown cross-protection, demonstrating >50% bactericidal killing in the presence of rabbit antisera generated after vaccination with the 30-valent vaccine (5). The emm type (M76) most commonly identified by us is not included in the 30-valent vaccine but is among the emm types that evoked bactericidal antibodies. Of 233 GAS isolates, 54 were vaccine types (VT) and 100 were non-vaccine types, indicating cross coverage (identified in the figures as “NVT-K” [non-vaccine type—killed]). No information regarding potential vaccine coverage was available for 40 (17%) isolates (“No killing data”). This vaccine could cover 65% of emm types, corresponding to 66% of GAS cases in our setting.

FIG 2

Frequency of noninvasive and invasive emm types observed. VT, vaccine type; NVT-K; non-vaccine type—killed; NVT-NK, non-vaccine type—not killed.

Non-iGAS.

A total of 32 emm types were identified in 126 non-iGAS isolates (Fig. 3). Of these, the most prevalent emm types, with a frequency of >3% in the population, were M76 (15%), M81 (12%), M80 (8%), M43.7 (6%), M184 (6%), M183.2 (6%), M44 (5%), M53 (5%), M92 (5%), and M49 (3%). The 10 most prevalent emm types accounted for 71% of the isolates; 20 different emm types accounted for 90% of non-iGAS isolates. No new emm types were observed. Twelve emm types were presented only once.

FIG 3

Frequency of emm types recovered from noninvasive GAS isolates. VT, vaccine type; NVT-K; non-vaccine type—killed; NVT-NK, non-vaccine type—not killed.

A total of 29 (23%) non-iGAS emm types are included in the 30-valent vaccine, representing 11 different emm types. An additional 47 non-iGAS isolates (37%), representing 7 emm types, were included among the cross-protection isolates. The most commonly isolated emm type for non-iGAS infection, M76, was not included in the 30-valent vaccine. The potential coverage for non-iGAS infection in our setting is 60%. No information regarding potential vaccine coverage (“No killing data”) was available for 28 (22%) isolates.

iGAS.

Thirty-five emm types were identified in 107 iGAS isolates (Fig. 4). Among these isolates, the most prevalent emm types, i.e., those with a frequency of >3% in the population, were M76 (17%), M81 (8%), M183.2 (7%), M43.7 (6%), M44 (6%), M53 (6%), M92 (6%), M80 (5%), M116.1 (4%), M33 (4%), and M8 (3%). The 10 most prevalent emm types accounted for 66% of the isolates; 20 different emm types accounted for 84% of the GAS cases isolated. STG1750.0 was identified in 1 isolate. Seventeen emm types were represented only once.

FIG 4

Frequency of invasive emm types observed. VT, vaccine type; NVT-K; non-vaccine type—killed; NVT-NK, non-vaccine type—not killed.

A total of 24 (22%) iGAS emm types are included in the 30-valent vaccine, representing 11 different emm types. An additional 39 iGAS isolates (36%) representing 9 more emm types were included among the cross-protection isolates. The most commonly isolated emm type for iGAS infection (M76) was not included in the 30-valent vaccine. The potential coverage for iGAS infection in our setting is 58%. No information regarding potential vaccine coverage was available for 27 (25%) isolates (“No killing data”).

Clusters.

Among the 233 GAS isolates, we were able to assign an emm cluster designation (from the CDC website) to 231 isolates (Table 4) according to the cluster classification method (13). Ten emm type clusters were observed among the GAS isolates (Table 4). Five emm clusters, namely, D4, E2, E3, E6, and E4, comprised 90% of the emm types.

TABLE 4

Frequency of emm clusters among GAS isolates from cases of noninvasive and invasive GAS infection in Cape Town

Cluster	Frequency	% of total
D4	59	25.54
E2	54	23.37
E3	41	17.74
E6	34	14.71
E4	20	8.65
NS	9	3.89
stG6.6	9	3.89
Clade Y	2	0.86
D2	1	0.43
E1	1	0.43
Formerly st3211.0	1	0.43
Total	231	100.00

NS, not stated.

Seasonal variation.

There was an association between the type of GAS infection and the season of the year; however, the data did not reach statistical significance (chi-square test for trend, P = 0.06). Non-iGAS infections showed a peak in the winter months. iGAS infections reached a trough in the winter months and peaked in the summer months (Fig. 5). Furthermore, a higher proportion of iGAS infections than of non-iGAS infections was observed during the winter months, and this difference was statistically significant (Z test, P = <0.001).

FIG 5

Seasonal distribution of GAS recovered from noninvasive and invasive GAS infection. non-iGAS, noninvasive group A streptococcus; iGAS, invasive group A streptococcus.

DISCUSSION

This is the first report of a prospective study describing the molecular types of both noninvasive and invasive GAS infections in South Africa. The most prevalent emm types were almost evenly distributed between non-iGAS and iGAS isolates; a small number of emm types accounted for the majority of non-iGAS (90%) and iGAS (84%) cases. The proportion of iGAS cases was remarkably high, accounting for almost half (46%) of GAS infections in our surveillance study.

Compared with the 30-valent vaccine, only one-third of the 46 emm types in our study (15/46), were included, translating to levels of vaccine coverage (vaccine type and non-vaccine type killing) for non-iGAS and iGAS infection of 60% and 58%, respectively. Notably, the strains identified by us as the most prevalent, in both the non-iGAS and iGAS groups, were not included in the 30-valent vaccine. Interestingly, one emm type, STG1750.0, was obtained from one patient presenting with bacteremia.

We found a lower diversity of emm types, a result similar to others found in high-income countries (14). In our study, 20 emm types represented 86% of GAS isolates, which is lower than the proportion found in other studies conducted in Africa, which reported 25 emm types representing 70% of 70 emm types (8), 26 emm types representing 63% of 91 emm types for GAS pharyngitis (14), and 48 emm types representing 62% of 78 emm types for GAS skin and pharyngeal infections (9). Another study of iGAS isolates, conducted in Kenya, reported 88 different emm types (10); 74% of our strains were also found in their study. Of interest, our study findings were similar to those reported from a surveillance study conducted in Tunisia (33). Their 20 most prevalent emm types represented 82% of the total emm types, and the proportion of iGAS cases was 46% compared with the 49% proportion in our surveillance study. Furthermore, the emm types most commonly isolated in high-income countries (M1, M12, M28, M3, and M4) were not represented in our study.

Epidemiological studies have shown significant associations between emm type and GAS disease manifestations. emm types 1, 3, 5, 6, 12, 14, 17, 44, and 61 have been reported previously to be associated with superficial GAS disease (15–17), and emm types 1, 3, and 28 have been reported previously to be associated with iGAS diseases (18). In addition, emm types have been found to be associated with clinical manifestations, including APSGN (emm types 1, 4, 12, 49, 55, 57, and 60) (19) and ARF (emm types 1, 3, 5, 6, 11, 12, 14, 17, 18, 19, 24, 27, 29, 30, 32, and 41) (19, 20). Our study included emm types that have been previously shown to be associated with pharyngitis, impetigo, ARF, and PSGN.

Seasonal variations in the frequency of GAS cases have been observed in studies conducted in the United States. GAS infections have been shown to peak in the winter and early spring months and to reach a trough in the summer and autumn months (21). Similar seasonal variations have been observed in Europe (22, 23). The data regarding non-iGAS infections in our study are in keeping with this observation; however, for iGAS infection, a higher number of cases were observed in the summer months.

A new emm cluster typing system classifies >200 emm types into 48 emm clusters containing closely related M proteins that share structural and binding properties (24). This system predicts the M protein vaccine antigen content and serves as a framework to investigate the cross-protection phenomenon and to provide complementary hypotheses for the many variants from low-to-middle-income countries (24). Five emm clusters were responsible for 90% of the disease burden. It is thus conceivable that the emm cluster typing system could be an important typing tool to identify vaccine antigen candidates that may prove to be effective at preventing a larger proportion of GAS infections, especially in South Africa (24).

Our study had a number of limitations. (i) We were unable to assess the variation in the distribution of emm types over time, as reported in other studies (21, 25), since our data were collected over a one-year period. (ii) This was a hospital-based study; therefore, we could not calculate population-based incidence rates over the study period. (iii) GSH is mainly an adult hospital; hence, the number of cases in young patients was low. Therefore, caution must be applied when generalizing these findings to the lower age category. (iv) emm data were not available for all GAS isolated over the study period. We compared the isolates that were typed with those not typed and found no significant difference with regard to gender (chi-square test, P = 0.92) and non-iGAS and iGAS groups (chi-square test, P = 0.87). We also considered age group analysis and found no differences among patients between the ages of 13 to 18 (Z test for proportions, P = 0.84) and 19 to 64 years (Z test, P = 0.79) and those older than 64 years (Z test, P = 0.90). There was a difference in the younger population, among the newborns (Z test, P = 0.02) and those 6 to 12 years of age (Z test, P = 0.02). This difference could have been due to the small sample size in these age categories.

Our results have implications for current vaccine development initiatives. The current 30-valent vaccine formulation is informed by high-income countries, accounting for 90% of strains causing disease in those regions. By comparison, vaccine coverage in our study was considerably lower than the coverage in high-income countries. Even though the five most prevalent emm types (M76, M81, M80, M43 and M183) identified by us, accounting for 45% of our cases, are not included in the current 30-valent vaccine formulation, there is evidence of cross-protection based on detection of bactericidal antibodies that recognize shared epitopes in the N-terminal region of the emm types (5, 26). A small number of emm types are responsible for the majority of GAS cases in our setting; thus, an effective vaccine will not require diverse emm serotypes. Furthermore, an important finding in our study is that bactericidal activity against 33% of the non-vaccine emm types in our study could translate to a 43% increase in protective coverage.

The same emm types caused both iGAS and non-iGAS infections in our study, thus suggesting that host immune factors have a role to play in determining the severity and outcome of GAS infections in different individuals (27). Patients with serious GAS infections who present with severe clinical manifestations tend to produce elevated levels of proinflammatory cytokines in response to GAS products (28).

Although we were unable to calculate incidence rates, the proportion of iGAS infection at GSH was high; however, this was to be expected given that GSH is a tertiary-level hospital to which patients with severe disease are referred for care. In contrast, at a community health center, we would expect to see fewer iGAS infections and more non-iGAS infections, e.g., GAS pharyngitis.

iGAS infection is responsible for a substantial burden of disease, and its clinical manifestations are associated with important causes of premature mortality and morbidity. Following the first comprehensive review, published more than a decade ago, there remains a challenge in quantifying the burden of GAS disease around the world. Although more data are slowly becoming available, more work needs to be done, especially in resource-limited areas such as sub-Saharan Africa. Understanding the epidemiology and true burden of GAS diseases will help target efforts and settings in which the vaccine and other trials could be conducted. While vaccine development efforts targeting areas other than emm protein are under way, it must be noted that the emm protein vaccine is currently at the most advanced stage of development, thus warranting documentation of the corresponding variations in distributions of emm types. Furthermore, the reporting of iGAS through passive surveillance provides a platform to evaluate trends and identify new strains causing disease and, in so doing, inform the development of vaccine efforts.

MATERIALS AND METHODS

Study design and participants.

We conducted a prospective passive surveillance laboratory study among samples submitted from February 2016 to March 2017 to the National Health Laboratory Service (NHLS) from inpatients and outpatients attending Groote Schuur Hospital (GSH) in Cape Town. GSH is a tertiary-level hospital serving a catchment population of approximately one and a half million people (6) and forms part of a network of clinics and hospitals that are affiliated with the University of Cape Town. GSH (Groote Schuur Hospital [including state hospitals Cape Town and Western Cape, South Africa, and Groote Schuur Hospital]) provides care to more than 560,000 referrals and inpatient admissions every year, including adults (>12 years) and neonates; the NHLS also receives specimens from external primary health care clinics. We documented demographic data and clinical presentation and laboratory data from non-iGAS and iGAS infections. The study was approved by the Human Research Ethics Committee at the University of Cape Town (HREC/REF: R006/2015).

Clinical surveillance and case definitions.

At the time of a laboratory-confirmed GAS diagnosis, a standardized case report form was completed by a study microbiologist. Clinical information was obtained by accessing the patient’s medical record. A total of 122 isolates were collected and stored at −80°C until transfer to the AFROStrep laboratory.

iGAS was defined as GAS isolated from a sterile source such as blood, cerebrospinal fluid, or pleural fluid (29) or from a wound culture with a clinical diagnosis of necrotizing fasciitis or streptococcal toxic shock syndrome (21). GAS cultures from deep tissue (e.g., abscess) or from a biopsy sample following surgery were also considered to represent invasive infection (14). GAS isolated from a nonsterile site such as the skin or the throat was considered to be noninvasive (30).

Molecular assays.

GAS isolates were stored in the AFROStrep laboratory at −80°C in cryopreservative microbeads until DNA extraction. emm typing was performed as described previously (34). Briefly, isolates were subcultured on 5% sheep’s blood agar media by isolation and streaking and the plate was incubated for 24 to 48 h at 37°C in presence of 5% CO2. DNA was extracted using a Wizard genomic DNA purification kit per the manufacturer’s instructions, and the DNA quality and quantity were determined using a NanoDrop 1000 spectrophotometer (Thermo Scientific, Wilmington, DE, USA).

Sequencing of purified DNA was done using an ABI Prism BigDye Terminator cycle sequencing kit (Applied Biosystems, USA) at Stellenbosch University, South Africa. The sequences generated were analyzed using BioEdit v7.0.9 (Ibis Biosciences, USA). The sequences were submitted electronically to the S. pyogenes emm sequence database center at the CDC, which assigned all the emm types and subtypes (31).

Statistics.

We evaluated the association between emm type and clinical symptoms using the chi-square test or Fisher’s exact test. A P value of <0.05 was considered to be statistically significant. All statistical analyses were performed using Stata (version 13.1; StataCorp, College Station, TX). The sample size was calculated using a prevalence of 21% for GAS pharyngitis as reported in a previous study conducted in Cape Town (32). The minimum reliable sample size was n = 255 to detect possible differences between non-iGAS and iGAS infection groups (95% confidence level; margin of error = 5%).