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Record W3098349959 · doi:10.1101/864983

Non-clonal emergence of colistin resistance associated with mutations in the BasRS two-component system in <i>Escherichia coli</i> bloodstream isolates

2019· preprint· en· W3098349959 on OpenAlexfundno aff
Axel B. Janssen, Toby Leigh Bartholomew, Natalia P. Marciszewska, Marc J. M. Bonten, Rob J. L. Willems, José A. Bengoechea, Willem van Schaik

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2019
Typepreprint
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicAntibiotic Resistance in Bacteria
Canadian institutionsnot available
FundersBiotechnology and Biological Sciences Research CouncilDirectorate for Biological SciencesDepartment for Employment and Learning, Northern IrelandQueen's UniversityNederlandse Organisatie voor Wetenschappelijk OnderzoekQueen's University Belfast
KeywordsColistinEscherichia coliLipid ABiologyMicrobiologyPlasmidPolymyxinMCR-1MutantGeneEnterobacteriaceaeBacteriaGeneticsAntimicrobialAntibiotics

Abstract

fetched live from OpenAlex

Abstract Infections by multidrug-resistant Gram-negative bacteria are increasingly common, prompting the renewed interest in the use of colistin. Colistin specifically targets Gram-negative bacteria by interacting with the anionic lipid A moieties of lipopolysaccharides, leading to membrane destabilization and cell death. Here, we aimed to uncover the mechanisms of colistin resistance in nine colistin-resistant Escherichia coli strains and one E. albertii strain. These were the only colistin-resistant strains out of 1140 bloodstream Escherichia isolates collected in a tertiary hospital over a ten-year period (2006 - 2015). Core genome phylogenetic analysis showed that each patient was colonised by a unique strain, suggesting that colistin resistance was acquired independently in each strain. All colistin-resistant strains had lipid A that was modified with phosphoethanolamine. In addition, two E. coli strains had hepta-acylated lipid A species, containing an additional palmitate compared to the canonical hexa-acylated E. coli lipid A. One E. coli strain carried the mobile colistin resistance (mcr) gene mcr-1.1 on an IncX4-type plasmid. Through construction of chromosomal transgene integration mutants, we experimentally determined that mutations in basRS , encoding a two-component signal transduction system, contributed to colistin resistance in four strains. We confirmed these observations by reversing the mutations in basRS to the sequences found in reference strains, resulting in loss of colistin resistance. While the mcr -genes have become a widely studied mechanism of colistin resistance in E. coli , sequence variation in basRS is another, potentially more prevalent but relatively underexplored, cause of colistin resistance in this important nosocomial pathogen. Importance Multidrug resistance among Gram-negative bacteria has led to the use of colistin as a last-resort drug. The cationic colistin kills Gram-negative bacteria through electrostatic interaction with the anionic lipid A moiety of lipopolysaccharides. Due to increased use in clinical and agricultural settings, colistin resistance has recently started to emerge. In this study, we used a combination of whole genome sequence analysis and experimental validation to characterise the mechanisms through which E. coli strains from bloodstream infections can develop colistin resistance. We found no evidence of direct transfer of colistin-resistant isolates between patients. The lipid A of all isolates was modified by the addition of phosphoethanolamine. In four isolates, colistin resistance was experimentally verified to be caused by mutations in the basRS genes, encoding a two-component regulatory system. Our data show that chromosomal mutations are an important cause of colistin resistance among clinical E. coli isolates.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.215
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations2
Published2019
Admission routes1
Has abstractyes

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