Literature DB >> 31068414

Whole-Genome Single-Nucleotide Polymorphism (SNP) Analysis Applied Directly to Stool for Genotyping Shiga Toxin-Producing Escherichia coli: an Advanced Molecular Detection Method for Foodborne Disease Surveillance and Outbreak Tracking.

Navjot Singh1, Pascal Lapierre1, Tammy M Quinlan1, Tanya A Halse1, Samantha Wirth1, Michelle C Dickinson1, Erica Lasek-Nesselquist1, Kimberlee A Musser2.   

Abstract

Whole-genome sequencing (WGS) of pathogens from pure culture provides unparalleled accuracy and comprehensive results at a cost that is advantageous compared with traditional diagnostic methods. Sequencing pathogens directly from a primary clinical specimen would help circumvent the need for culture and, in the process, substantially shorten the time to diagnosis and public health reporting. Unfortunately, this approach poses significant challenges because of the mixture of multiple sequences from a complex fecal biomass. The aim of this project was to develop a proof of concept protocol for the sequencing and genotyping of Shiga toxin-producing Escherichia coli (STEC) directly from stool specimens. We have developed an enrichment protocol that reliably achieves a substantially higher DNA yield belonging to E. coli, which provides adequate next-generation sequencing (NGS) data for downstream bioinformatics analysis. A custom bioinformatics pipeline was created to optimize and remove non-E. coli reads, assess the STEC versus commensal E. coli population in the samples, and build consensus sequences based on population allele frequency distributions. Side-by-side analysis of WGS from paired STEC isolates and matched primary stool specimens reveal that this method can reliably be implemented for many clinical specimens to directly genotype STEC and accurately identify clusters of disease outbreak when no STEC isolate is available for testing.
Copyright © 2019 American Society for Microbiology.

Entities:  

Keywords:  SNP analysis; STEC; outbreak; stool; surveillance studies; whole genome

Mesh:

Substances:

Year:  2019        PMID: 31068414      PMCID: PMC6595464          DOI: 10.1128/JCM.00307-19

Source DB:  PubMed          Journal:  J Clin Microbiol        ISSN: 0095-1137            Impact factor:   5.948


  19 in total

1.  Escherichia coli O157:H7 and O157:H(-) strains that do not produce Shiga toxin: phenotypic and genetic characterization of isolates associated with diarrhea and hemolytic-uremic syndrome.

Authors:  H Schmidt; J Scheef; H I Huppertz; M Frosch; H Karch
Journal:  J Clin Microbiol       Date:  1999-11       Impact factor: 5.948

2.  The emerging clinical importance of non-O157 Shiga toxin-producing Escherichia coli.

Authors:  Kristine E Johnson; Cheleste M Thorpe; Cynthia L Sears
Journal:  Clin Infect Dis       Date:  2006-11-09       Impact factor: 9.079

3.  Recommendations for diagnosis of shiga toxin--producing Escherichia coli infections by clinical laboratories.

Authors:  L Hannah Gould; Cheryl Bopp; Nancy Strockbine; Robyn Atkinson; Vickie Baselski; Barbara Body; Roberta Carey; Claudia Crandall; Sharon Hurd; Ray Kaplan; Marguerite Neill; Shari Shea; Patricia Somsel; Melissa Tobin-D'Angelo; Patricia M Griffin; Peter Gerner-Smidt
Journal:  MMWR Recomm Rep       Date:  2009-10-16

4.  The Sequence Alignment/Map format and SAMtools.

Authors:  Heng Li; Bob Handsaker; Alec Wysoker; Tim Fennell; Jue Ruan; Nils Homer; Gabor Marth; Goncalo Abecasis; Richard Durbin
Journal:  Bioinformatics       Date:  2009-06-08       Impact factor: 6.937

5.  Preliminary FoodNet Data on the incidence of infection with pathogens transmitted commonly through food--10 States, 2008.

Authors: 
Journal:  MMWR Morb Mortal Wkly Rep       Date:  2009-04-10       Impact factor: 17.586

6.  Enhanced identification and characterization of non-O157 Shiga toxin-producing Escherichia coli: a six-year study.

Authors:  Lisa A Mingle; Daniel L Garcia; Timothy P Root; Tanya A Halse; Tammy M Quinlan; Leanna R Armstrong; Amy K Chiefari; Dianna J Schoonmaker-Bopp; Nellie B Dumas; Ronald J Limberger; Kimberlee A Musser
Journal:  Foodborne Pathog Dis       Date:  2012-09-25       Impact factor: 3.171

7.  Interactive metagenomic visualization in a Web browser.

Authors:  Brian D Ondov; Nicholas H Bergman; Adam M Phillippy
Journal:  BMC Bioinformatics       Date:  2011-09-30       Impact factor: 3.307

8.  Hybrid selection for sequencing pathogen genomes from clinical samples.

Authors:  Alexandre Melnikov; Kevin Galinsky; Peter Rogov; Timothy Fennell; Daria Van Tyne; Carsten Russ; Rachel Daniels; Kayla G Barnes; James Bochicchio; Daouda Ndiaye; Papa D Sene; Dyann F Wirth; Chad Nusbaum; Sarah K Volkman; Bruce W Birren; Andreas Gnirke; Daniel E Neafsey
Journal:  Genome Biol       Date:  2011-08-11       Impact factor: 13.583

Review 9.  Food-related illness and death in the United States.

Authors:  P S Mead; L Slutsker; V Dietz; L F McCaig; J S Bresee; C Shapiro; P M Griffin; R V Tauxe
Journal:  Emerg Infect Dis       Date:  1999 Sep-Oct       Impact factor: 6.883

10.  FastTree: computing large minimum evolution trees with profiles instead of a distance matrix.

Authors:  Morgan N Price; Paramvir S Dehal; Adam P Arkin
Journal:  Mol Biol Evol       Date:  2009-04-17       Impact factor: 16.240

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  2 in total

1.  Metagenomic Approaches for Public Health Surveillance of Foodborne Infections: Opportunities and Challenges.

Authors:  Heather A Carleton; John Besser; Amanda J Williams-Newkirk; Andrew Huang; Eija Trees; Peter Gerner-Smidt
Journal:  Foodborne Pathog Dis       Date:  2019-06-06       Impact factor: 3.171

2.  Development of Single Nucleotide Polymorphism (SNP)-Based Triplex PCR Marker for Serotype-specific Escherichia coli Detection.

Authors:  Md-Mafizur Rahman; Sang-Jin Lim; Yung-Chul Park
Journal:  Pathogens       Date:  2022-01-19
  2 in total

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