Dataset Information

Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks.

ABSTRACT: Genomic surveillance that combines bacterial sequencing and epidemiological information will become the gold standard for outbreak detection, but its clinical translation is hampered by the lack of automated interpretation tools. We performed a prospective pilot study to evaluate the analysis of methicillin-resistant Staphylococcus aureus (MRSA) genomes using the Next Gen Diagnostics (NGD) automated bioinformatics system. Seventeen unselected MRSA-positive patients were identified in a clinical microbiology laboratory in England over a period of 2?weeks in 2018, and 1 MRSA isolate per case was sequenced on the Illumina MiniSeq instrument. The NGD system automatically activated after sequencing and processed fastq folders to determine species, multilocus sequence type, the presence of a mec gene, antibiotic susceptibility predictions, and genetic relatedness based on mapping to a reference MRSA genome and detection of pairwise core genome single-nucleotide polymorphisms. The NGD system required 90?s per sample to automatically analyze data from each run, the results of which were automatically displayed. The same data were independently analyzed using a research-based approach. There was full concordance between the two analysis methods regarding species (S. aureus), detection of mecA, sequence type assignment, and detection of genetic determinants of resistance. Both analysis methods identified two MRSA clusters based on relatedness, one of which contained 3 cases that were involved in an outbreak linked to a clinic and ward associated with diabetic patient care. We conclude that, in this pilot study, the NGD system provided rapid and accurate data that could support infection control practices.

SUBMITTER: Brown NM

PROVIDER: S-EPMC6813015 | biostudies-literature | 2019 Nov

REPOSITORIES: biostudies-literature

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Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks.

Brown Nicholas M NM Blane Beth B Raven Kathy E KE Kumar Narender N Leek Danielle D Bragin Eugene E Rhodes Paul A PA Enoch David A DA Thaxter Rachel R Parkhill Julian J Peacock Sharon J SJ

Journal of clinical microbiology 20191023 11

Genomic surveillance that combines bacterial sequencing and epidemiological information will become the gold standard for outbreak detection, but its clinical translation is hampered by the lack of automated interpretation tools. We performed a prospective pilot study to evaluate the analysis of methicillin-resistant <i>Staphylococcus aureus</i> (MRSA) genomes using the Next Gen Diagnostics (NGD) automated bioinformatics system. Seventeen unselected MRSA-positive patients were identified in a cl ...[more]

PMID: 31462548

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Project description:Methicillin resistant Staphylococcus aureus (MRSA) infection is becoming refractory to existing antibiotic therapy owing to the inherent ability of S. aureus to develop rapid resistance and is considered a major threat to public health. We found that a natural isolate of Bacillus pumilus from the Columbia River Estuary produces a strong anti-MRSA compound, amicoumacin A. As amicoumacin A has been reported to exhibit anti-microbial, anti-inflammatory, and anti-ulcer activities, we sought to uncover its mechanism of action. Genome-wide transcriptome analysis of S. aureus COL in response to amicoumacin A showed alteration in the expression of genes involved in several cellular processes including cell envelope turnover, cross-membrane transport, virulence, metabolism, and general stress response. The most highly induced gene was lrgA, encoding an antiholin-like product, which has been shown to be induced in response to a collapse of membrane potential. In order to gain further insight into the mechanism of action of amicoumacin A, a whole genome comparison of wild-type COL and amicoumacin A-resistant mutants isolated by serial passage method was carried out. Single point mutations resulting in codon substitutions were uncovered in several distinct genes: ksgA, RNA dimethyltranferase; fusA, elongation factor G; dnaG, primase, ; lacD, tagatose 1,6-bisphosphate aldolase, ; and SACOL0611, encoding a putative glycosyl transferase gene. Based on these results, a candidate approach was undertaken to recreate the same amino acid substitution individually in FusA and KsgA, each of which resulted in two-fold resistance towards amicoumacin A. The fusA gene is known as the site for fusidic acid- resistant mutations; however the codon substitutions in EF-G that cause amicoumacin A resistance and fusidic acid resistance occur in separate domains and do not bring about cross resistance. Taken together, these results suggest that amicoumacin A might cause perturbation of the cell membrane and lead to energy dissipation. Decreased rates of cellular metabolism including protein synthesis and DNA replication in resistant strains might allow cells to compensate for membrane dysfunction and thus increase cell survivability.

Dataset Information

Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks.

Publications

Pilot Evaluation of a Fully Automated Bioinformatics System for Analysis of Methicillin-Resistant Staphylococcus aureus Genomes and Detection of Outbreaks.

Similar Datasets

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