Jérôme Ambroise, Bertrand Bearzatto, Jean-Francois Durant, Leonid M Irenge, Jean-Luc Gala
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引用次数: 0
Abstract
Objective: Multiple-Locus Variable Number of Tandem Repeats (VNTR) Analysis (MLVA) is widely used to subtype pathogens causing foodborne and waterborne disease outbreaks. The MLVAType shiny application was previously designed to extract MLVA profiles of Vibrio cholerae isolates from whole-genome sequencing (WGS) data, and provide backward compatibility with traditional MLVA typing methods. The previous development and validation work was conducted using short (pair-end 300 and 150 nt long) reads from Illumina MiSeq and Hiseq sequencing. In this study, the MLVAType application was validated using long reads generated by Oxford Nanopore Technologies (ONT) sequencing platforms. In silico MLVA profiles of V. cholerae isolates (n = 9) from the Democratic Republic of the Congo were generated using the MLVAType application on Nanopore WGS data. The WGS-derived in silico MLVA profiles were extracted from Canu (v.2.2) assemblies obtained through MinION and GridION sequencing by ONT. The results were compared to those obtained from SPAdes assemblies (v3.13.0; k-mer 175) generated from short-read (pair-end 300-bp) reference data obtained by MiSeq sequencing, Illumina.
Results: For each isolate, the in silico MLVA profiles were concordant across all three sequencing methods, demonstrating that the MLVAType application can accurately predict the MLVA profiles from assembled genomes generated by long-reads ONT sequencers.
BMC Research NotesBiochemistry, Genetics and Molecular Biology-Biochemistry, Genetics and Molecular Biology (all)
CiteScore
3.60
自引率
0.00%
发文量
363
审稿时长
15 weeks
期刊介绍:
BMC Research Notes publishes scientifically valid research outputs that cannot be considered as full research or methodology articles. We support the research community across all scientific and clinical disciplines by providing an open access forum for sharing data and useful information; this includes, but is not limited to, updates to previous work, additions to established methods, short publications, null results, research proposals and data management plans.