Rapid bacterial genome sequencing: methods and applications in clinical microbiology
Clinical Microbiology and Infection·
- DOI
- 10.1111/1469-0691.12217
- PMID
- 23601179
- PMCID
- —
- OpenAlex
- W1927124817
- Study type
- Genomic study
- Publisher
- Elsevier BV
- Article type
- journal-article
- Integrity
- current
Why this research matters now
The authors suggest that high-throughput sequencing is positioned to influence diagnostics, epidemiology, risk management, and patient care as costs decrease and turnaround times shorten.
Structured evidence summary
Research question
The review addresses how high-throughput sequencing can be applied within clinical microbiology, focusing on diagnostic development, epidemiological typing, and characterization of strain properties.
Study design
The article is a narrative review summarizing methods and applications of rapid bacterial genome sequencing in clinical microbiology.
Population and setting
The review is framed around clinical microbiology laboratories and the broader context of pathogen surveillance and diagnostics, without a defined study population.
Main findings
The review describes high-throughput sequencing as a transformative tool for clinical microbiology, with applications in diagnostic assay development, precise strain typing for outbreak monitoring, and characterization of resistance and virulence features. It also highlights emerging areas such as comparative metagenomics and single-cell sequencing for studying microbial communities and host-pathogen interactions.
Public-health relevance
The authors suggest that high-throughput sequencing is positioned to influence diagnostics, epidemiology, risk management, and patient care as costs decrease and turnaround times shorten.
Important limitations
This summary is limited to the supplied single-article abstract and metadata; the original paper is required for decision-grade interpretation.
GIDS interpretation
The article is indexed under topics including diagnostics, antimicrobial resistance, and genomic epidemiology, with tuberculosis listed as a relevant disease tag, providing context for discoverability rather than confirming any active surveillance signal.
Related GIDS surveillance
Literature context does not validate, explain, or change a surveillance signal. Exact and contextual relationships are shown separately.
Evidence relationships
This article has 8 auditable classifier relationships to diseases, places, topics, and study design.