Undefined
Ontology highlight
ABSTRACT:
PROVIDER: PRJEB64404 | ENA |
REPOSITORIES: ENA
Dataset's files
| Action | DRS | |||
|---|---|---|---|---|
| ERR11862305_1.fastq.gz | Fastqsanger.gz | |||
| ERR11862305_2.fastq.gz | Fastqsanger.gz | |||
| ERR11862306_1.fastq.gz | Fastqsanger.gz | |||
| ERR11862306_2.fastq.gz | Fastqsanger.gz | |||
| ERR11862307_1.fastq.gz | Fastqsanger.gz |
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Project description:Streptococcus dysgalactiae subspecies equisimilis (SDSE) is a Gram-positive bacterial pathogen that infects humans and is closely related to group A streptococcus (GAS). Compared to GAS, far less is known about SDSE pathobiology. Increased rates of invasive SDSE infections have recently been reported in many countries. One SDSE emm type, stG62647, is known to cause severe diseases, including necrotizing soft-tissue infections, endocarditis, and osteoarticular infections. To increase our understanding of the molecular pathogenesis of stG62647 SDSE isolates causing human infections, we sequenced to closure the genomes of 120 stG62647 SDSE isolates. The genomes varied in size from 2.1 to 2.24 megabase pairs. Consistent with previous data, the great majority of stG62647 isolates had IS1548 integrated into the silB gene, thereby inactivating it. Regions of difference in gene content, including putative mobile genetic elements, were the largest source of genomic diversity. All 120 stG62647 isolates were assayed for virulence using a well-established mouse model of necrotizing myositis. An unexpectedly wide range of virulence was identified (20% to 95%), as assessed by near-mortality data. To explore the molecular mechanisms underlying virulence differences, we analyzed RNAseq transcriptome profiles for 38 stG62647 isolates (comprising the 19 least and most virulent) grown in vitro. Genetic polymorphisms were identified from whole-genome sequence data. Collectively, the results suggest that these SDSE isolates use multiple genetic pathways to achieve an altered virulence phenotype. Our study integrates genomic, mouse virulence, and RNAseq data to advance our understanding of SDSE pathobiology and its molecular pathogenesis.
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