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Record W3010209973 · doi:10.1186/s12866-019-1668-3

In vitro synergy between sodium deoxycholate and furazolidone against enterobacteria

2020· article· en· W3010209973 on OpenAlexfundno aff
Vuong Van Hung Le, Catrina Olivera, Julian Spagnuolo, Ieuan G. Davies, Jasna Rakonjac

Bibliographic record

VenueBMC Microbiology · 2020
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicBacterial Genetics and Biotechnology
Canadian institutionsnot available
FundersMinistry of Business, Innovation and EmploymentKeio UniversityInstitute of GeneticsNew Zealand Vice-Chancellors' CommitteeMassey UniversityCallaghan Innovation
KeywordsFurazolidoneEscherichia coliBiologyNitrofuranEffluxSalmonella entericaMicrobiologyKlebsiella pneumoniaeEnterobacteriaceaeColistinAntimicrobialSalmonellaBacteriaBiochemistryAntibioticsGene

Abstract

fetched live from OpenAlex

BACKGROUND: Antimicrobial combinations have been proven as a promising approach in the confrontation with multi-drug resistant bacterial pathogens. In the present study, we identify and characterize a synergistic interaction of broad-spectrum nitroreductase-activated prodrugs 5-nitrofurans, with a secondary bile salt, Sodium Deoxycholate (DOC) in growth inhibition and killing of enterobacteria. RESULTS: Using checkerboard assay, we show that combination of nitrofuran furazolidone (FZ) and DOC generates a profound synergistic effect on growth inhibition in several enterobacterial species including Escherichia coli, Salmonella enterica, Citrobacter gillenii and Klebsiella pneumoniae. The Fractional Inhibitory Concentration Index (FICI) for DOC-FZ synergy ranges from 0.125 to 0.35 that remains unchanged in an ampicillin-resistant E. coli strain containing a β-lactamase-producing plasmid. Findings from the time-kill assay further highlight the synergy with respect to bacterial killing in E. coli and Salmonella. We further characterize the mechanism of synergy in E. coli K12, showing that disruption of the tolC or acrA genes that encode components of multidrug efflux pumps causes, respectively, a complete or partial loss, of the DOC-FZ synergy. This finding indicates the key role of TolC-associated efflux pumps in the DOC-FZ synergy. Overexpression of Nitric Oxide-detoxifying enzyme Hmp results in a three-fold increase in FICI for DOC-FZ interaction, suggesting a role of nitric oxide in the synergy. We further demonstrate that DOC-FZ synergy is largely independent of NfsA and NfsB, the two major activation enzymes of the nitrofuran prodrugs. CONCLUSIONS: This study is to our knowledge the first report of nitrofuran-deoxycholate synergy against Gram-negative bacteria, offering potential applications in antimicrobial therapeutics. The mechanism of DOC-FZ synergy involves FZ-mediated inhibition of TolC-associated efflux pumps that normally remove DOC from bacterial cells. One possible route contributing to that effect is via FZ-mediated nitric oxide production.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.881

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.011
GPT teacher head0.216
Teacher spread0.205 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
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

Citations21
Published2020
Admission routes1
Has abstractyes

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