Optimized conditions for Listeria, Salmonella and Escherichia whole genome sequencing using the Illumina iSeq100 platform with point-and-click bioinformatic analysis
Whole-genome sequencing (WGS) data have become an integral component of public health investigations and clinical diagnostics. Still, many veterinary diagnostic laboratories cannot afford to implement next generation sequencing (NGS) due to its high cost and the lack of bioinformatic knowledge of th...
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Published in: | PloS one Vol. 17; no. 11; p. e0277659 |
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Main Authors: | , , , , , , , , , |
Format: | Journal Article |
Language: | English |
Published: |
United States
Public Library of Science
30-11-2022
Public Library of Science (PLoS) |
Subjects: | |
Online Access: | Get full text |
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Summary: | Whole-genome sequencing (WGS) data have become an integral component of public health investigations and clinical diagnostics. Still, many veterinary diagnostic laboratories cannot afford to implement next generation sequencing (NGS) due to its high cost and the lack of bioinformatic knowledge of the personnel to analyze NGS data. Trying to overcome these problems, and make NGS accessible to every diagnostic laboratory, thirteen veterinary diagnostic laboratories across the United States (US) initiated the assessment of Illumina iSeq100 sequencing platform for whole genome sequencing of important zoonotic foodborne pathogens Escherichia coli, Listeria monocytogenes, and Salmonella enterica. The work presented in this manuscript is a continuation of this multi-laboratory effort. Here, seven AAVLD accredited diagnostic laboratories explored a further reduction in sequencing costs and the usage of user-friendly platforms for genomic data analysis. Our investigation showed that the same genomic library quality could be achieved by using a quarter of the recommended reagent volume and, therefore a fraction of the actual price, and confirmed that Illumina iSeq100 is the most affordable sequencing technology for laboratories with low WGS demand. Furthermore, we prepared step-by-step protocols for genomic data analysis in three popular user-friendly software (BaseSpace, Geneious, and GalaxyTrakr), and we compared the outcomes in terms of genome assembly quality, and species and antimicrobial resistance gene (AMR) identification. No significant differences were found in assembly quality, and the three analysis methods could identify the target bacteria species. However, antimicrobial resistance genes were only identified using BaseSpace and GalaxyTrakr; and GalaxyTrakr was the best tool for this task. |
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Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 23 Competing Interests: The authors have declared that no competing interests exist. |
ISSN: | 1932-6203 1932-6203 |
DOI: | 10.1371/journal.pone.0277659 |