Shotgun-metagenomics based prediction of antibiotic resistance and virulence determinants in Staphylococcus aureus from periprosthetic tissue on blood culture bottles
| العنوان: | Shotgun-metagenomics based prediction of antibiotic resistance and virulence determinants in Staphylococcus aureus from periprosthetic tissue on blood culture bottles |
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| المؤلفون: | Jessin Janice, Adriana Sanabria, Gunnar Skov Simonsen, Erik Hjerde, Anne-Merethe Hanssen |
| المصدر: | Scientific Reports Scientific Reports, Vol 11, Iss 1, Pp 1-13 (2021) |
| سنة النشر: | 2021 |
| مصطلحات موضوعية: | Staphylococcus aureus, Virulence Factors, Science, Periprosthetic, Virulence, Diseases, Computational biology, Biology, medicine.disease_cause, Genome, Microbiology, Article, Antibiotic resistance, Drug Resistance, Bacterial, medicine, Humans, Typing, Gene, Pathogen, Multidisciplinary, VDP::Medisinske Fag: 700::Basale medisinske, odontologiske og veterinærmedisinske fag: 710, Staphylococcal Infections, VDP::Medical disciplines: 700::Basic medical, dental and veterinary science disciplines: 710, Anti-Bacterial Agents, Computational biology and bioinformatics, Blood Culture, Genes, Bacterial, Medicine, Metagenomics |
| الوصف: | Shotgun-metagenomics may give valuable clinical information beyond the detection of potential pathogen(s). Identification of antimicrobial resistance (AMR), virulence genes and typing directly from clinical samples has been limited due to challenges arising from incomplete genome coverage. We assessed the performance of shotgun-metagenomics on positive blood culture bottles (n = 19) with periprosthetic tissue for typing and prediction of AMR and virulence profiles in Staphylococcus aureus. We used different approaches to determine if sequence data from reads provides more information than from assembled contigs. Only 0.18% of total reads was derived from human DNA. Shotgun-metagenomics results and conventional method results were consistent in detecting S. aureus in all samples. AMR and known periprosthetic joint infection virulence genes were predicted from S. aureus. Mean coverage depth, when predicting AMR genes was 209 ×. Resistance phenotypes could be explained by genes predicted in the sample in most of the cases. The choice of bioinformatic data analysis approach clearly influenced the results, i.e. read-based analysis was more accurate for pathogen identification, while contigs seemed better for AMR profiling. Our study demonstrates high genome coverage and potential for typing and prediction of AMR and virulence profiles in S. aureus from shotgun-metagenomics data. |
| وصف الملف: | application/pdf |
| تدمد: | 2045-2322 |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::0b5d8978a9e817ecd66adb3c324cec95 https://pubmed.ncbi.nlm.nih.gov/34675288 |
| Rights: | OPEN |
| رقم الانضمام: | edsair.doi.dedup.....0b5d8978a9e817ecd66adb3c324cec95 |
| قاعدة البيانات: | OpenAIRE |
| تدمد: | 20452322 |
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