Your browser doesn't support javascript.
loading
Optimized conditions for Listeria, Salmonella and Escherichia whole genome sequencing using the Illumina iSeq100 platform with point-and-click bioinformatic analysis.
Alvarez Narvaez, Sonsiray; Shen, Zhenyu; Yan, Lifang; Stenger, Brianna L S; Goodman, Laura B; Lim, Ailam; Nissly, Ruth H; Nair, Meera Surendran; Zhang, Shuping; Sanchez, Susan.
Afiliação
  • Alvarez Narvaez S; Department of Population Health, College of Veterinary Medicine, The University of Georgia, Athens, Georgia, United States of America.
  • Shen Z; Department of Veterinary Pathology, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States of America.
  • Yan L; Department of Pathobiology and Population Medicine, College of Veterinary Medicine, Mississippi State University, Starkville, Mississippi, United States of America.
  • Stenger BLS; Veterinary Diagnostic Laboratory, North Dakota Agricultural Experiment Station, North Dakota State University, Fargo, North Dakota, United States of America.
  • Goodman LB; Department of Public & Ecosystem Health, College of Veterinary Medicine, Cornell University, Ithaca, New York, United States of America.
  • Lim A; Wisconsin Veterinary Diagnostic Laboratory, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
  • Nissly RH; Department of Veterinary and Biomedical Sciences, College of Agricultural Sciences, PennState University, State College, Pennsylvania, United States of America.
  • Nair MS; Department of Veterinary and Biomedical Sciences, College of Agricultural Sciences, PennState University, State College, Pennsylvania, United States of America.
  • Zhang S; Department of Veterinary Pathobiology, Veterinary Medical Diagnostic Laboratory, College of Veterinary Medicine, University of Missouri, Columbia, Missouri, United States of America.
  • Sanchez S; Department of Infectious Disease, College of Veterinary Medicine, The University of Georgia, Athens, Georgia, United States of America.
PLoS One ; 17(11): e0277659, 2022.
Article em En | MEDLINE | ID: mdl-36449522
ABSTRACT
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.
Assuntos

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Listeria Tipo de estudo: Guideline Idioma: En Ano de publicação: 2022 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Listeria Tipo de estudo: Guideline Idioma: En Ano de publicação: 2022 Tipo de documento: Article