scholarly journals Retrospective whole-genome sequencing analysis distinguished PFGE and drug-resistance-matched retail meat and clinical Salmonella isolates

Microbiology ◽  
2019 ◽  
Vol 165 (3) ◽  
pp. 270-286 ◽  
Author(s):  
Andrea B. Keefer ◽  
Lingzi Xiaoli ◽  
Nkuchia M. M’ikanatha ◽  
Kuan Yao ◽  
Maria Hoffmann ◽  
...  
Keyword(s):  
Drug Resistance ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Retail Meat

scholarly journals Retrospective whole-genome sequencing analysis distinguished PFGE and drug resistance matched retail meat and clinical Salmonella isolates

2018 ◽  
Author(s):  
Andrea B. Keefer ◽  
Lingzi Xiaoli ◽  
Nkuchia M. M’ikanatha ◽  
Kuan Yao ◽  
Maria Hoffmann ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Genetic Relatedness ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Foodborne Illnesses ◽  
Multiple Sources ◽  
Genetic Characteristics ◽  
Retail Meats ◽  
Retail Meat

AbstractNon-typhoidal Salmonella are a leading cause of outbreak and sporadic-associated foodborne illnesses in the U.S. These infections have been associated with a range of foods, including retail meats. Traditionally, pulsed-field gel electrophoresis (PFGE) and antibiotic susceptibility testing (AST) have been used to facilitate public health investigations of Salmonella infections. However, whole-genome sequencing (WGS) has emerged as an alternative tool that can be routinely implemented. To assess its potential in enhancing integrated surveillance in Pennsylvania, WGS was used to directly compare the genetic characteristics of 7 retail meat and 43 clinical historic Salmonella isolates, subdivided into three subsets based on PFGE and AST results, to retrospectively resolve their genetic relatedness and identify antimicrobial resistance (AMR) determinants. Single nucleotide polymorphism (SNP) analyses revealed the retail meat isolates within S. Heidelberg, S. Typhimurium var. O5- subset 1, and S. Typhimurium var. O5- subset 2 were separated from each primary PFGE pattern-matched clinical isolate by 6-12, 41-96, and 21-81 SNPs, respectively. Fifteen resistance genes were identified across all isolates, including fosA7, a gene only recently found in a limited number of Salmonella and a ≥ 95% phenotype to genotype correlation was observed for all tested antimicrobials. Moreover, AMR was primarily plasmid-mediated in S. Heidelberg and S. Typhimurium var. O5- subset 2; whereas, AMR was chromosomally-carried in S. Typhimurium var. O5- subset 1. Similar plasmids were identified in both the retail meat and clinical isolates. Collectively, these data highlight the utility of WGS in retrospective analyses and enhancing integrated surveillance of Salmonella from multiple sources.

scholarly journals Sarek: A portable workflow for whole-genome sequencing analysis of germline and somatic variants

2018 ◽  
Author(s):  
Maxime Garcia ◽  
Szilveszter Juhos ◽  
Malin Larsson ◽  
Pall I. Olason ◽  
Marcel Martin ◽  
...  
Keyword(s):  
Whole Genome Sequencing ◽  
Open Source ◽  
Genome Sequencing ◽  
Development Project ◽  
Whole Genome ◽  
Sequencing Analysis ◽  
Single Nucleotide Variants ◽  
Single Nucleotide ◽  
Insertion And Deletion ◽  
Sample Heterogeneity

AbstractSummaryWhole-genome sequencing (WGS) is a cornerstone of precision medicine, but portable and reproducible open-source workflows for WGS analyses of germline and somatic variants are lacking. We present Sarek, a modular, comprehensive, and easy-to-install workflow, combining a range of software for the identification and annotation of single-nucleotide variants (SNVs), insertion and deletion variants (indels), structural variants, tumor sample heterogeneity, and karyotyping from germline or paired tumor/normal samples. Sarek is implemented in a bioinformatics workflow language (Nextflow) with Docker and Singularity compatible containers, ensuring easy deployment and full reproducibility at any Linux based compute cluster or cloud computing environment. Sarek supports the human reference genomes GRCh37 and GRCh38, and can readily be used both as a core production workflow at sequencing facilities and as a powerful stand-alone tool for individual research groups.AvailabilitySource code and instructions for local installation are available at GitHub (https://github.com/SciLifeLab/Sarek) under the MIT open-source license, and we invite the research community to contribute additional functionality as a collaborative open-source development project.

scholarly journals Comprehensive Whole-Genome Sequencing and Reporting of Drug Resistance Profiles on Clinical Cases of Mycobacterium tuberculosis in New York State

2017 ◽  
Vol 55 (6) ◽  
pp. 1871-1882 ◽  
Author(s):  
Joseph Shea ◽  
Tanya A. Halse ◽  
Pascal Lapierre ◽  
Matthew Shudt ◽  
Donna Kohlerschmidt ◽  
...  
Keyword(s):  
New York ◽  
Drug Resistance ◽  
Mycobacterium Tuberculosis ◽  
Whole Genome Sequencing ◽  
Genome Sequencing ◽  
Predictive Value ◽  
New York State ◽  
Whole Genome ◽  
Content Type ◽  
York State

ABSTRACTWhole-genome sequencing (WGS) is a newer alternative for tuberculosis (TB) diagnostics and is capable of providing rapid drug resistance profiles while performing species identification and capturing the data necessary for genotyping. Our laboratory developed and validated a comprehensive and sensitive WGS assay to characterizeMycobacterium tuberculosisand otherM. tuberculosiscomplex (MTBC) strains, composed of a novel DNA extraction, optimized library preparation, paired-end WGS, and an in-house-developed bioinformatics pipeline. This new assay was assessed using 608 MTBC isolates, with 146 isolates during the validation portion of this study and 462 samples received prospectively. In February 2016, this assay was implemented to test all clinical cases of MTBC in New York State, including isolates and early positive Bactec mycobacterial growth indicator tube (MGIT) 960 cultures from primary specimens. Since the inception of the assay, we have assessed the accuracy of identification of MTBC strains to the species level, concordance with culture-based drug susceptibility testing (DST), and turnaround time. Species identification by WGS was determined to be 99% accurate. Concordance between drug resistance profiles generated by WGS and culture-based DST methods was 96% for eight drugs, with an average resistance-predictive value of 93% and susceptible-predictive value of 96%. This single comprehensive WGS assay has replaced seven molecular assays and has resulted in resistance profiles being reported to physicians an average of 9 days sooner than with culture-based DST for first-line drugs and 32 days sooner for second-line drugs.

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