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Record W4301372494 · doi:10.1101/2022.10.03.510743

MarR-Dependent Transcriptional Regulation of <i>mmpSL5</i> induces Ethionamide Resistance in <i>Mycobacterium abscessus</i>

2022· preprint· en· W4301372494 on OpenAlexfundno aff
Ronald Rodriguez, Jesus Gonzalez Camba, John C. Berude, Rachel Fetterman, Sarah A. Stanley

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2022
Typepreprint
Languageen
FieldMedicine
TopicMycobacterium research and diagnosis
Canadian institutionsnot available
FundersGenome Center, University of California, DavisUniversity of California, DavisUniversity of California BerkeleyNorthwestern UniversityYork UniversityNational Institutes of HealthNational Science Foundation
KeywordsMycobacterium abscessusEthionamideMycobacterium tuberculosisBiologyMicrobiologyTetRAntibioticsTransposon mutagenesisPathogenDrug resistanceMycobacteriumVirologyMutantGeneTuberculosisTransposable elementGeneticsBacteriaMedicineGene expressionEthambutolRifampicinRepressor

Abstract

fetched live from OpenAlex

Abstract Mycobacterium abscessus ( Mabs ) is an emerging non-tuberculosis mycobacterial (NTM) pathogen responsible for a wide variety of respiratory and cutaneous infections that are difficult to treat with standard antibacterial therapy. Mabs has a high degree of both innate and acquired antibiotic resistance to most clinically relevant drugs, including standard anti-mycobacterial agents. Ethionamide (ETH), an inhibitor of mycolic acid biosynthesis is currently utilized as a second-line agent for treating multidrug resistant tuberculosis (MDR-TB) infections. Here, we show that ETH has activity against clinical strains of Mabs in vitro at concentrations that are therapeutically achievable. Using transposon mutagenesis and whole genome sequencing of spontaneous drug-resistant mutants, we identified marR (MAB_2648c) as a genetic determinant of ETH sensitivity in Mabs . The gene marR encodes a transcriptional regulator of the TetR family of regulators. We show that MarR represses expression of MAB_2649 ( mmpS5 ) and MAB_2650 ( mmpL5 ). Further, we show that de-repression of these genes in marR mutants confers resistance to ETH, but not other antibiotics. To identify determinants of resistance that may be shared across antibiotics, we also performed Tn-Seq during treatment with amikacin and clarithromycin, drugs currently used clinically to treat Mabs . We found very little overlap in genes that modulate the sensitivity of Mabs to all three antibiotics, suggesting a high degree of specificity for resistance mechanisms in this emerging pathogen. Importance Antibiotic resistant infections caused by Mycobacterium abscessus ( Mabs ) have been increasing in prevalence and treatment is often unsuccessful. Success rates range from 30-50%, primarily due to the high intrinsic resistance of Mabs to most clinically useful antibiotics. New therapeutic strategies, including repurposing of existing antibiotics, are urgently needed to improve treatment success rates. Here, we show that the anti-TB antibiotic ethionamide (ETH) has repurposing potential against Mabs , displaying bacteriostatic activity and delaying emergence of drug resistance when combined with clinically relevant antibiotics currently used against Mabs in vitro . We identified genes that modulated susceptibility of Mabs to ETH. marR encodes a transcriptional regulator that when deleted, confers ETH resistance. Our collective findings can be used to further explore the function of other genes that contribute to ETH susceptibility and help design the next generation of antibacterial regimens against Mabs that may potentially include ETH.

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)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.020
GPT teacher head0.253
Teacher spread0.234 · 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 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

Citations0
Published2022
Admission routes1
Has abstractyes

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