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Tillman, G.

Publications and source records attributed to Tillman, G..

2 recordsLinked to original sources
bioRxiv2019

Genomic Analysis of Emerging Florfenicol-Resistant Campylobacter coli Isolated from the Intestinal Cecal Contents of Cattle in the United States

ObjectiveGenomic analyses were performed on florfenicol resistant (FFNR) Campylobacter coli (C. coli) isolated from cattle and the cfr(C) gene-associated multi-drug resistance (MDR) plasmid was characterized.\n\nMethodsSixteen FFNR C. coli isolates recovered between 2013-2018 from beef cattle were sequenced using MiSeq. Genomes and plasmids were closed for three of the isolates using the PacBio(R) system. Single nucleotide polymorphisms (SNPs) across the genome and the structures of MDR plasmids were investigated. Conjugation experiments were performed to determine the transferability of cfr(C) associated MDR plasmids. The spectrum of resistance encoded by the cfr(C) gene was further investigated by agar dilution antimicrobial susceptibility testing.\n\nResultsAll 16 FFNR isolates were MDR and exhibited co-resistance to ciprofloxacin, nalidixic acid, clindamycin and tetracycline. All isolates shared the same resistance genotype, carrying aph(3)-III, hph, {triangleup}aadE (truncated), blaOXA-61, cfr(C), and tet(O) genes plus a mutation of GyrA T86I. The cfr(C), aph(3)-III, hph {triangleup}aadE, and tet(O) genes were co-located on transferable MDR plasmids with size 48-50 kb. These plasmids showed high sequence homology with the pTet plasmid, and carried several Campylobacter virulence genes, including virB2, virB4, virB5, VirB6, virB7, virB8, virb9, virB10, virB11 and virD4. The cfr(C) gene conferred resistance to florfenicol (8-32 {micro}g/ml), clindamycin (512-1,024 {micro}g/ml), linezolid (128-512 {micro}g/ml), and tiamulin (1,024 {micro}g/ml). Phylogenetic analysis showed SNP differences ranging from 11-2,248 among the 16 isolates.\n\nConclusionsThe results showed that the cfr(C) gene located in the conjugative pTet MDR/virulence plasmid is present in diverse strains, where it confers high levels of resistance to several antimicrobials, including linezolid, a critical drug for treating Gram positive bacterial infections in humans. This study highlights the power of genomic antimicrobial resistance surveillance to uncover the intricacies of transmissible co-resistance and provides information that is needed for accurate risk assessment and mitigation strategies.

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↗