ArticleAntimicrobial stewardship & healthcare epidemiology : ASHE2026
A comparative review of three cloud-based platforms for microbial whole genome sequencing analysis.
Article in Antimicrobial stewardship & healthcare epidemiology : ASHE, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Authors and funding
4 authors.
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Abstract
Objective: Whole genome sequencing (WGS) of microbes is a powerful tool for pathogen detection, antimicrobial resistance (AMR) genes, and outbreak analysis. However, WGS data analysis is a challenging process and a major limitation of adopting WGS in clinical use. In this manuscript, we performed in-depth review of three cloud-based sequencing data analysis platforms that are user-friendly and require minimal or no bioinformatics expertise. Methods: Total of 90 bacterial isolates collected from inpatient units of the Central Texas Veterans healthcare system were sequenced on Nextseq 550 system (Illumina). FASTQ files generated after the sequencing were uploaded to the sequence analysis platforms: BugSeq™, EPISEQ® CS, and Solu. Each platform' s usability, cost, output type, turnaround time from uploading files to results, and analysis output including number of identifiable pathogen species, AMR genes, and epidemiological clusters were assessed. Results: All platforms were easy to use and offered analysis features including pathogen identification, AMR gene and plasmid detection, and epidemiological analysis. Analysis results were generated within hours (BugSeq™ & EPISEQ® CS, 3 ∼ 4 hrs; Solu, 1 hr) after sequence file upload. All platforms identified most pathogen species correctly (BugSeq™, 89; EPISEQ® CS, 83; Solu, 87). Among 90 isolates, wide-ranging number of AMR genes were detected (BugSeq™, 83; EPISEQ® CS, 358; Solu, 137). Epidemiological clusters (closely related isolates) detection was also varied (BugSeq™, 9; EPISEQ® CS, 11; Solu, 12) because each platform used different methodologies. Conclusion: While users need to consider factors such as cost, IT infrastructure, and data security, cloud-based platforms may ease barriers for adopting WGS for clinical and infection prevention purposes.
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Registered trials
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