Biology subjects

Allard, M. W.

Publications and source records attributed to Allard, M. W..

5 recordsLinked to original sources

bioRxiv2022

A schema for digitized surface swab site metadata in open-source DNA sequence databases

Large, open-source DNA sequence databases have been generated, in part, through the collection of microbial pathogens from swabbing surfaces in built environments. Analyzing these data in aggregate through public health surveillance requires digitization of the complex, domain-specific metadata associated with swab site locations. However, the swab site location information is currently collected in a single, free-text "isolation source" field promoting generation of poorly detailed descriptions with varying word order, granularity, and linguistic errors, making automation difficult and reducing machine-actionability. We assessed 1,498 free-text swab site descriptions generated during routine foodborne pathogen surveillance. The lexicon of free-text metadata was evaluated to determine the informational facets and quantity of unique terms used by data collectors. Open Biological Ontologies (OBO) foundry libraries were used to develop hierarchical vocabularies connected with logical relationships to describe swab site locations. Five informational facets described by 338 unique terms were identified via content analysis. Term hierarchy facets were developed as were statements (called axioms) about how entities within these five domains were related. The schema developed through this study has been integrated into a publicly available pathogen metadata standard, facilitating ongoing surveillance and investigations. The One Health Enteric Package is available at NCBI BioSample beginning in 2022. Collective use of metadata standards increases the interoperability of DNA sequence databases, enabling large-scale approaches to data sharing, artificial intelligence, and big-data solutions to food safety. IMPORTANCERegular analysis of whole genome sequence data in collections such as NCBIs Pathogen Detection Database is used by many public health organizations to detect outbreaks of infectious disease. However, isolate metadata in these databases are often incomplete and poor quality. These complex raw metadata must often be re-organized and manually formatted for use in aggregate analysis. These processes are inefficient and time-consuming, increasing the interpretative labor needed by public health groups to extract actionable information. Future use of open genomic epidemiology networks will be supported through the development of an internationally applicable vocabulary system to describe swab site locations.

genomics↗

bioRxiv2020

Genomic surveillance of antimicrobial resistance shows cattle are a moderate source of multi-drug resistant non-typhoidal Salmonella in Mexico

Multi-drug resistant (MDR) non-typhoidal Salmonella (NTS) is a major public health concern globally. This study reports antibiotic susceptibility testing and genotypic antimicrobial resistance (AMR) profiles of NTS isolates from bovine lymph nodes (n=48) and ground beef (n=29). Furthermore, we compared genotypic AMR data of our isolates with those of publicly available NTS genomes from Mexico (n=1637). The probability of finding MDR isolates was higher in ground beef as compared to lymph nodes: {chi}2=12.0, P=0.0005. The most common resistant phenotypes involved tetracycline (40.3%), carbenicillin (26.0%), amoxicillin-clavulanic acid (20.8%), chloramphenicol (19.5%) and trimethoprim-sulfamethoxazole (16.9%), while over 55% of the isolates showed decreased susceptibility to ciprofloxacin and 26% were MDR. Occurrence of MDR isolates was strongly associated with NTS serovar ({chi}2=24.5, P<0.0001), with Typhimurium accounting for 40% of MDR strains. Most of these (9/10), carried Salmonella genomic island 1, which harbors multiple AMR genes (aadA2, blaCARB-2, floR, sul1, tetG) that confer a penta-resistant phenotype. Moreover, 100% of MDR isolates had mutations in the ramR gene. Among public NTS isolates from foods and clinical cases in Mexico to date, those from cattle had the highest proportion of MDR genotypes. Our results suggest attaining significant improvements in AMR meat safety may require the identification and removal (or treatment) of product harboring MDR NTS, instead of screening for Salmonella spp. or for isolates showing resistance to individual antibiotics. In that sense, massive integration of whole genome sequencing (WGS) technologies in AMR surveillance provides the shortest path to accomplish these goals.

genomics↗

bioRxiv2020

Precision long-read metagenomics sequencing for food safety by detection and assembly of Shiga toxin-producing Escherichia coli in irrigation water

Shiga toxin-producing Escherichia coli (STEC) contamination of agricultural water might be an important factor to recent foodborne illness and outbreaks involving leafy greens. Whole genome sequencing generation of closed bacterial genomes plays an important role in source tracking. We aimed to determine the limits of detection and classification of STECs by qPCR and nanopore sequencing using enriched irrigation water artificially contaminated with E. coli O157:H7 (EDL933). We determined the limit of STEC detection by qPCR to be 30 CFU/reaction, which is equivalent to 105 CFU/ml in the enrichment. By using Oxford Nanopores EPI2ME WIMP workflow and de novo assembly with Flye followed by taxon classification with a k-mer analysis software (Kraken), E. coli O157:H7 could be detected at 103 CFU/ml (68 reads) and a complete fragmented E. coli O157:H7 metagenome-assembled genome (MAG) was obtained at 105-108 CFU/ml. Using a custom script to extract the E. coli reads, a completely closed MAG was obtained at 107-108 CFU/ml and a complete, fragmented MAG was obtained at 105-106 CFU/ml. In silico virulence detection for E. coli MAGs for 105-108 CFU/ml showed that the virulotype was indistinguishable from the spiked E. coli O157:H7 strain. We further identified the bacterial species in the un-spiked enrichment, including antimicrobial resistance genes, which could have important implications to food safety. We propose this workflow could be used for detection and complete genomic characterization of STEC from a complex microbial sample and could be applied to determine the limit of detection and assembly of other foodborne bacterial pathogens. IMPORTANCEFoodborne illness caused by Shiga toxin-producing E. coli (STEC) ranges in severity from diarrhea to hemolytic uremic syndrome and produce-related incidence is increasing. The pervasive nature of E. coli requires not only detection, but also a complete genome to determine potential pathogenicity based on stx and eae genes, serotype, and other virulence factors. We have developed a pipeline to determine the limits of nanopore sequencing for STECs in a metagenomic sample. By utilizing the current qPCR in the FDA Bacteriological Analytical Manual (BAM) Chapter 4A, we can quantify the amount of STEC in the enrichment and then sequence and classify the STEC in less than half the time as current protocols that require a single isolate. These methods have wide implications for food safety, including decreased time to STEC identification during outbreaks, characterization of the microbial community, and the potential to use these methods to determine the limits for other foodborne pathogens.

genomics↗

bioRxiv2019

Nanopore sequencing for fast determination of plasmids, phages, virulence markers, and antimicrobial resistance genes in Shiga toxin-producing Escherichia coli

Whole genome sequencing can provide essential public health information. However, it is now known that widely used short-read methods have the potential to miss some randomly-distributed segments of genomes. This can prevent phages, plasmids, and virulence factors from being detected or properly identified. Here, we compared assemblies of three complete STEC O26:H11 genomes from two different sequence types (ST21 and 29), each acquired using the MiSeq-Nextera XT, MinION nanopore-based sequencing, and Pacific Biosciences (PacBio) sequencing. Each closed genome consisted of a single chromosome, approximately 5.7 Mb for CFSAN027343, 5.6 Mb for CFSAN027346, and 5.4 MB for CFSAN027350. However, short-read WGS using MiSeq-Nextera failed to identify some virulence genes in plasmids and on the chromosome, both of which were detected using the long-read platforms. Results from long-read MinION and PacBio allowed us to identify differences in plasmid content: a single 88 kb plasmid in CFSAN027343; a 157kb plasmid in CFSAN027350; and two plasmids in CFSAN027346 (one 95 Kb, one 72 Kb). These data enabled rapid characterization of the virulome, detection of antimicrobial genes, and composition/location of Stx phages. Taken together, positive correlations between the two long-read methods for determining plasmids, virulome, antimicrobial resistance genes, and phage composition support MinION sequencing as one accurate and economical option for closing STEC genomes and identifying specific virulence markers.

genomics↗

bioRxiv2018

Whole genome sequence analysis of 91 Salmonella Enteritidis isolates from mice caught on poultry farms in the mid 1990s

Salmonella enterica serovar Enteritidis (SE), the most commonly reported serovar of human salmonellosis, has been frequently associated with poultry farms, eggs and egg products. Mice are known vectors of SE contamination in these facilities. The objective of this study was to use whole-genome sequencing (WGS) to analyze SE from mice obtained at poultry farms in Pennsylvania. Documenting pathogen diversity can identify reliable biomarkers for rapid detection and speed up outbreak investigations. We sequenced 91 SE isolates from 83 mice (62 spleen isolates, 29 intestinal isolates) caught at 15 poultry farms between 1995-1998 using an Illumina NextSeq 500. We identified 742 single nucleotide polymorphisms (SNPs) capable of distinguishing each isolate from one another. Isolates were divided into two major clades: there were more SNPs differences within Clade B than counterparts in Clade A. All isolates containing antimicrobial resistance genes belong to Subgroup B2. Clade-defining SNPs provided biomarkers distinguishing isolates from 12 individual subgroups, which were separated by farm location or year of collection. Nonsynonymous changes from the clade-defining SNPs proffered a better understanding of possible genetic variations among these isolates. For a broader view of SE diversity, we included data from NCBI Pathogen Detection Isolates Browser, in which subgroups in Clade B formed new SNP Clusters.\n\nImportanceWGS and SNPs analyses are excellent and powerful tools for investigating SE phylogenies. Identifying the evolutionary relationships among SE isolates from mouse, poultry, environmental, and clinical isolates, along with patterns of genetic diversity, advances understanding of SE and the role mice may play in SE contamination and spread among poultry population. Our data was able to identify SE isolates from different farms or years of collection. Moreover, the annotations of clade-defining SNPs provided information about possible protein functions among these SE isolates from each subgroup. Clade-defining or farm-unique biomarkers were useful for rapid detection and outbreak investigations.

genomics↗