Next-Generation Sequencing in Melioidosis: Enhancing Diagnosis, Epidemiology and Antimicrobial Resistance Surveillance
Diagnostics·
- DOI
- 10.3390/diagnostics16162613
- PMID
- —
- PMCID
- —
- OpenAlex
- W7203690435
- Study type
- Journal article
- Publisher
- MDPI AG
- Article type
- journal-article
- Integrity
- current
Why this research matters now
Incorporating these genomic methodologies into standard care pathways may strengthen disease control efforts and optimize therapeutic decision-making, particularly in underserved regions.
Structured evidence summary
Research question
The review evaluates how next-generation sequencing platforms can improve diagnostic turnaround times, epidemiological tracking, and resistance monitoring for melioidosis infections.
Study design
The manuscript is explicitly classified as a narrative review that consolidates published literature rather than presenting original experimental data.
Population and setting
The analysis centers on clinical specimens, cultured bacterial isolates, and environmental reservoirs, with specific attention to healthcare environments that operate under resource constraints.
Main findings
Metagenomic approaches enable direct pathogen identification without prior cultivation, while whole-genome methods support transmission mapping and source identification. Additional applications involve identifying genetic markers linked to drug resistance to inform treatment strategies, alongside emerging techniques for extracting microbial DNA from environmental matrices.
Public-health relevance
Incorporating these genomic methodologies into standard care pathways may strengthen disease control efforts and optimize therapeutic decision-making, particularly in underserved regions.
Important limitations
Implementation is currently hindered by substantial financial requirements and inconsistent procedural standards across laboratories. Furthermore, the work functions as a descriptive synthesis rather than an original empirical investigation.
GIDS interpretation
This manuscript situates advanced genomic methodologies within established diagnostic frameworks, emphasizing their theoretical capacity to refine pathogen tracking and therapeutic alignment without asserting validated operational deployment or real-time monitoring validation.
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 11 auditable classifier relationships to diseases, places, topics, and study design.