Table S1; Table S2
Reason: The manuscript is in preparation. Data will be available in due course.
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year(s)9
month(s)7
day(s)until file(s) become available
Whole genome sequencing metadata of GAS isolates from Cape Town, South Africa, and comparison datasets.Group A Streptococcus. WGS Study Metadata 2024. [Supplementary dataset to Rampersadh Publication]
These datasets are supplementary to the doctoral thesis of Kimona Rampersadh. They contain the metadata from whole genome sequencing of 108 GAS isolates collected in Cape Town South Africa.
Abstract
Background
Streptococcus pyogenes (Group A streptococcus (GAS)) causes a variety of clinical presentations in humans, including the long-term sequela, rheumatic heart disease (RHD), which carries a large burden on the African continent. There have been numerous reports on the increase of antibiotic resistance in group A Streptococcus (GAS), particularly macrolide resistance. This study assessed the frequency and co-occurrence of virulence-related genes and antimicrobial resistance (AMR) determinants in GAS isolates from South Africa (SA), so as to contribute to the global understanding of GAS diseases.
Methods
GAS isolates (invasive, n=40; non-invasive, n=68) were subjected to whole genome sequencing (WGS). The WGS analysis investigated emm type, multi-locus sequence type (MLST), virulence-related genes and AMR. Results from Sensititre® STP6F assays were available for 95 GAS isolates (invasive, n=40; non-invasive, n=55) which allowed for correlation between the presence of resistance elements and phenotypic expression. Additionally, comparative analysis was conducted with GAS repository data from populations representing both high-income and low-income populations (HIP, LIP).
Results
The 25 included emm types showed high diversity. Capsule-associated genes (hasA, hasB, hasC) were uniformly high (>95%), as were fbaA, fbp54, prtf2 and sfbX. Superantigen genes speB and speG were present in all isolates, with smeZ (77.8%) and speJ (52.8%) also common. The DNase gene spd1 was present in all SA isolates, whereas spd2 and spd3 were present in less than 50%. Antimicrobial resistance genes (tetM, mefA, ermA and ThfT) were observed in less than 10% of SA isolates, with the exception of mefE (100%). Tetracycline resistance displayed the highest resistance, as correlated with phenotypic testing. The tetM gene was observed exclusively among emm76 isolates. Virulence and AMR gene distribution were proportionate between invasive and non-invasive isolates. Comparative analysis with HIP and LIP displayed similar frequencies of virulence factors. AMR gene occurrence was higher in HIPs compared to SA and LIPs.
Conclusion
This study sought to provide detailed information about the correlation of emm types with virulence, and antimicrobial resistance among South African isolates. Comparison to high-income (HIP) and low-income populations (LIP) isolate genomes supported the findings with regards to the prevalence of virulence factors. As expected, antimicrobial resistance was higher in HIPs compared to SA and LIPs. This study further supports the relationship of virulence with specific isolates rather than being broadly related to a particular serotype. The identification of molecular markers shared between high-income and low-income populations will provide insights into the pathogenicity and virulence factors of GAS across different socioeconomic contexts. Through comprehensive characterisation of more isolates from various infection types across diverse geographical regions and their correlation with host factors, we can achieve a deeper understanding of molecular mechanisms that govern tissue tropisms and virulence in GAS.
Description of dataset
The WGS metadata of GAS isolates from Cape Town includes the following: the collection site (hospitals/clinics in Cape Town), the collection date, the specimen isolation site, the clinical syndrome (invasive or non-invasive), details of the WGS such as the sequencing site, platform, library preparation kit, sequencing kit, and read size, the assembly statistics, typing information (emm type, emm cluster, multilocus sequence type (MLST)), the presence (indicated by 1) or absence (indicated by 0) of virulence and antimicrobial resistance genes, and the macrolide or tetracycline phenotypic outcome.
The global metadata of GAS isolates includes the following: the isolate identification number, country, the clinical syndrome (invasive or non-invasive), the population category (high-income or low-income), typing information (emm type, emm cluster, multilocus sequence type (MLST)), and the presence (indicated by 1) or absence (indicated by 0) of virulence and antimicrobial resistance genes.
Clarification on coding used for analysis of data: The coding and the sequencing reads will be uploaded onto Github for public access. The manuscript will also provide a summary of the bioinformatic analysis.
Period of data collection: 2016 - 2019
Location of data collection: Cape Town, South Africa. The precise location for each isolate is located in the metadata file.
