Biology subjects

Folster, J. P.

Publications and source records attributed to Folster, J. P..

4 recordsLinked to original sources

bioRxiv2023

Harnessing the pangenome for genomic surveillance: Salmonella enterica serotype Typhi as a paradigm

Public health genomic surveillance systems typically measure genome relatedness and infer molecular epidemiological relationships using chromosomal loci alone - an approximation of vertical evolution, or homology-by-descent. The accessory genome, composed of plasmids and other mobile genetic elements, reflects horizontal gene transfer and serves as an important mechanism of bacterial evolution, enabling rapid adaptation. Measuring homology in the accessory genome - homology-by-admixture - could offer important molecular epidemiological information for public health application. We applied Jaccard Index and a novel genome length distance metric to compute pangenome relatedness for the globally-important pathogen Salmonella enterica serotype Typhi (Typhi), and graphically express both homology-by-descent and homology-by-admixture in a reticulate network. Jaccard Index Network Analysis revealed structure in the Typhi pangenome that can be harnessed to enhance discriminatory power for surveillance, track antimicrobial resistance, and refine our understanding of homology for outbreak management and prevention. This offers a more intricate, multidimensional framework for understanding pathogen evolution. Significance StatementBacterial relatedness is often measured and visualized using chromosomal comparison and phylogenetic trees. While valuable, this approach captures only the vertical evolutionary dimension and excludes genetic material acquired or lost through horizontal gene transfer. We present an approach for measuring and visualizing bacterial relatedness using all core and accessory genetic material and discuss the interpretation of resulting reticulate networks of bacterial genomes. In application to Salmonella Typhi, Jaccard Index Network Analysis revealed structure in populations of this pathogen that may be harnessed for public health applications. This approach captures both vertical and horizontal evolutionary dimensions, offering an intricate genetic framework for exploring pathogen evolution.

genomics↗

bioRxiv2019

Emergence of a novel Salmonella enterica serotype Reading clone is linked to its expansion in commercial turkey production, resulting in unanticipated human illness in North America

Concurrent separate human outbreaks of Salmonella enterica serotype Reading occurred in 2017-2019 in the United States and Canada, which were both linked to the consumption of raw turkey products. In this study, a comprehensive genomic investigation was conducted to reconstruct the evolutionary history of S. Reading from turkeys, and to determine the genomic context of outbreaks involving this rarely isolated Salmonella serotype. A total of 988 isolates of U.S. origin were examined using whole genome-based approaches, including current and historical isolates from humans, meat, and live food animals. Broadly, isolates clustered into three major clades, with one apparently highly adapted turkey clade. Within the turkey clade isolates clustered into three subclades, including an "emergent" clade that only contained isolates dated 2016 or later, including many of the isolates from these outbreaks. Genomic differences were identified between emergent and other turkey subclades suggesting that the apparent success of currently circulating subclades clade is, in part, attributable to plasmid acquisitions conferring antimicrobial resistance, gain of phage-like sequences with cargo virulence factors, and mutations in systems that may be involved in beta-glucuronidase activity and resistance towards colicins. U.S. and Canadian outbreak isolates were found interspersed throughout the emergent subclade and the other circulating subclade. The emergence of a novel S. Reading turkey subclade, coinciding temporally with expansion in commercial turkey production and with U.S. and Canadian human outbreaks, indicates that emergent strains with higher potential for niche success were likely vertically transferred and rapidly disseminated from a common source. ImportanceIncreasingly, outbreak investigations involving foodborne pathogens are confounded by the inter-connectedness of food animal production and distribution, necessitating high-resolution genomic investigations to determine their basis. Fortunately, surveillance and whole genome sequencing, combined with the public availability of these data, enable comprehensive queries to determine underlying causes of such outbreaks. Utilizing this pipeline, it was determined that a novel clone of Salmonella Reading has emerged that coincides with increased abundance in raw turkey products and two outbreaks of human illness in North America. The rapid dissemination of this highly adapted and conserved clone indicates that it was likely obtained from a common source and rapidly disseminated across turkey production. Key genomic changes may have contributed to its apparent continued success in the barn environment, and ability to cause illness in humans.

microbiology↗

bioRxiv2019

Novel quinolone resistance determinant, qepA8, in Shigella flexneri isolated in the United States, 2016

A qepA8+ Shigella flexneri was cultured from the stool of a traveler returning from India and East Asia. This chromosomally encoded qepA variant, has a six-base insertion, and may have been mobilized as part of a complex IS1-mediated composite transposon including catA1, aadA1, and blaOXA-1. In laboratory E. coli, qepA8 alone only conferred decreased ciprofloxacin susceptibility; however, it may work in combination with additional mechanisms to confer clinical resistance.

microbiology↗

bioRxiv2019

Using the NCBI AMRFinder Tool to Determine Antimicrobial Resistance Genotype-Phenotype Correlations Within a Collection of NARMS Isolates

Antimicrobial resistance (AMR) is a major public health problem that requires publicly available tools for rapid analysis. To identify acquired AMR genes in whole genome sequences, the National Center for Biotechnology Information (NCBI) has produced a high-quality, curated, AMR gene reference database consisting of up-to-date protein and gene nomenclature, a set of hidden Markov models (HMMs), and a curated protein family hierarchy. Currently, the Bacterial Antimicrobial Resistance Reference Gene Database contains 4,579 antimicrobial resistance gene proteins and more than 560 HMMs. Here, we describe AMRFinder, a tool that uses this reference dataset to identify AMR genes. To assess the predictive ability of AMRFinder, we measured the consistency between predicted AMR genotypes from AMRFinder against resistance phenotypes of 6,242 isolates from the National Antimicrobial Resistance Monitoring System (NARMS). This included 5,425 Salmonella enterica, 770 Campylobacter spp., and 47 Escherichia coli phenotypically tested against various antimicrobial agents. Of 87,679 susceptibility tests performed, 98.4% were consistent with predictions. To assess the accuracy of AMRFinder, we compared its gene symbol output with that of a 2017 version of ResFinder, another publicly available resistance gene database. Most gene calls were identical, but there were 1,229 gene symbol differences between them, with differences due to both algorithmic differences and database composition. AMRFinder missed 16 loci that Resfinder found, while Resfinder missed 1,147 loci AMRFinder identified. Two missing drug classes from the 2017 version of ResFinder contributed 81% of missed loci. Based on these results, AMRFinder appears to be a highly accurate AMR gene detection system. ImportanceAntimicrobial resistance is a major public health problem. Traditionally, antimicrobial resistance has been identified using phenotypic assays. With the advent of genome sequencing, we now can identify resistance genes and deduce if an isolate could be resistant to antibiotics. We describe a database of 4,579 acquired antimicrobial resistance genes, the largest publicly available, and a software tool to identify genes in bacterial genomes, AMRFinder. Unlike other tools, AMRFinder uses a gene hierarchy to prevent overpredicting what the correct gene call should be, enabling more accurate assessment. To assess these resources, we determined the resistance gene content of over 6,200 bacterial isolates from the National Antimicrobial Resistance Monitoring System that have been assayed using traditional methods and that also have had their genomes sequenced. We also compared our gene assessments to those of a popularly used tool. We found that AMRFinder has a high overall consistency between genotypes and phenotypes.

microbiology↗