Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates
Summary: Analyzing whole-genome sequencing (WGS) data from bacterial isolates is pivotal for understanding virulence and predicting clinical outcomes through association studies. Herein, we present a computational protocol for the detailed analysis of WGS data from Staphylococcus aureus clinical iso...
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| Language: | English |
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Elsevier
2025-03-01
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| Series: | STAR Protocols |
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| Online Access: | http://www.sciencedirect.com/science/article/pii/S266616672500019X |
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| author | Miquel Sánchez-Osuna Ivan Erill Oriol Gasch Oscar Q. Pich |
| author_facet | Miquel Sánchez-Osuna Ivan Erill Oriol Gasch Oscar Q. Pich |
| author_sort | Miquel Sánchez-Osuna |
| collection | DOAJ |
| description | Summary: Analyzing whole-genome sequencing (WGS) data from bacterial isolates is pivotal for understanding virulence and predicting clinical outcomes through association studies. Herein, we present a computational protocol for the detailed analysis of WGS data from Staphylococcus aureus clinical isolates generated with Illumina sequencing. We describe steps for de novo assembly, functional annotation, and genetic characterization of chromosomal and extrachromosomal elements. This approach paves the way for an improved understanding of the interplay between virulence factors, resistome, strain type, and disease severity.For complete details on the use and execution of this protocol, please refer to Sánchez-Osuna et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics. |
| format | Article |
| id | doaj-art-5fef8866f77f4a40a3b3baa8c809abf2 |
| institution | Kabale University |
| issn | 2666-1667 |
| language | English |
| publishDate | 2025-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | STAR Protocols |
| spelling | doaj-art-5fef8866f77f4a40a3b3baa8c809abf22025-02-02T05:29:21ZengElsevierSTAR Protocols2666-16672025-03-0161103613Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolatesMiquel Sánchez-Osuna0Ivan Erill1Oriol Gasch2Oscar Q. Pich3Laboratori de Recerca en Microbiologia i Malalties Infeccioses, Hospital Universitari Parc Taulí, Institut d’Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, 08208 Sabadell, Barcelona, Spain; Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, Spain; Corresponding authorDepartment of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD 21250, USA; Departament d’Enginyeria de la Informació i de les Comunicacions, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, SpainServei de Malalties Infeccioses, Hospital Universitari Parc Taulí, Institut d’Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, 08208 Sabadell, Barcelona, SpainLaboratori de Recerca en Microbiologia i Malalties Infeccioses, Hospital Universitari Parc Taulí, Institut d’Investigació i Innovació Parc Taulí (I3PT-CERCA), Universitat Autònoma de Barcelona, 08208 Sabadell, Barcelona, Spain; Institut de Biotecnologia i Biomedicina, Universitat Autònoma de Barcelona, 08193 Cerdanyola del Vallès, Barcelona, SpainSummary: Analyzing whole-genome sequencing (WGS) data from bacterial isolates is pivotal for understanding virulence and predicting clinical outcomes through association studies. Herein, we present a computational protocol for the detailed analysis of WGS data from Staphylococcus aureus clinical isolates generated with Illumina sequencing. We describe steps for de novo assembly, functional annotation, and genetic characterization of chromosomal and extrachromosomal elements. This approach paves the way for an improved understanding of the interplay between virulence factors, resistome, strain type, and disease severity.For complete details on the use and execution of this protocol, please refer to Sánchez-Osuna et al.1 : Publisher’s note: Undertaking any experimental protocol requires adherence to local institutional guidelines for laboratory safety and ethics.http://www.sciencedirect.com/science/article/pii/S266616672500019Xbioinformaticssequence analysishealth sciencesgenomicssequencingmicrobiology |
| spellingShingle | Miquel Sánchez-Osuna Ivan Erill Oriol Gasch Oscar Q. Pich Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates STAR Protocols bioinformatics sequence analysis health sciences genomics sequencing microbiology |
| title | Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates |
| title_full | Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates |
| title_fullStr | Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates |
| title_full_unstemmed | Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates |
| title_short | Computational protocol for analyzing whole-genome sequencing data from Staphylococcus aureus clinical isolates |
| title_sort | computational protocol for analyzing whole genome sequencing data from staphylococcus aureus clinical isolates |
| topic | bioinformatics sequence analysis health sciences genomics sequencing microbiology |
| url | http://www.sciencedirect.com/science/article/pii/S266616672500019X |
| work_keys_str_mv | AT miquelsanchezosuna computationalprotocolforanalyzingwholegenomesequencingdatafromstaphylococcusaureusclinicalisolates AT ivanerill computationalprotocolforanalyzingwholegenomesequencingdatafromstaphylococcusaureusclinicalisolates AT oriolgasch computationalprotocolforanalyzingwholegenomesequencingdatafromstaphylococcusaureusclinicalisolates AT oscarqpich computationalprotocolforanalyzingwholegenomesequencingdatafromstaphylococcusaureusclinicalisolates |