ArticleNature communications2020
Entropy of a bacterial stress response is a generalizable predictor for fitness and antibiotic sensitivity.
Article in Nature communications, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
27 citing papers in PubMed, 47 citations in OpenAlex.
- Translation Inhibiting Antibiotics Induce an asRNA Regulating Purine Metabolism inbioRxiv : the preprint server for biology · 2026Article
- Dual membrane-spanning anti-sigma 2 controls OMV biogenesis and colonization fitness inJournal of bacteriology · 2026Article
- Revealing transcriptomic responses inmSystems · 2026Article
- Weighted Gene Networks Derived from Multi-Omics Reveal Core Cancer Genes in Lung Cancer.Biology · 2025Article
- Silver single atoms and nanoparticles on floatable monolithic photocatalysts for synergistic solar water disinfection.Nature communications · 2025Article
- Identification of determinants that allow maintenance of high-level fluoroquinolone resistance inmBio · 2025Article
- Diclofenac sensitizes multi-drug resistant Acinetobacter baumannii to colistin.PLoS pathogens · 2024Article
- Identification of Determinants that Allow Maintenance of High-Level Fluoroquinolone Resistance inbioRxiv : the preprint server for biology · 2024Article
- CRISPRi-TnSeq maps genome-wide interactions between essential and non-essential genes in bacteria.Nature microbiology · 2024Article
- Assessment of the Safety and Probiotic Properties ofMicroorganisms · 2024Article
- High-throughput transcriptomics of 409 bacteria-drug pairs reveals drivers of gut microbiota perturbation.Nature microbiology · 2024Article
- LptD depletion disrupts morphological homeostasis and upregulates carbohydrate metabolism inFEMS microbes · 2023Article
- Genome-wide association studies reveal distinct genetic correlates and increased heritability of antimicrobial resistance inMicrobial genomics · 2022Article
- A bacterial pan-genome makes gene essentiality strain-dependent and evolvable.Nature microbiology · 2022Article
- A flux-based machine learning model to simulate the impact of pathogen metabolic heterogeneity on drug interactions.PNAS nexus · 2022Article
- Extensively Drug-Resistant Klebsiella pneumoniae Counteracts Fitness and Virulence Costs That Accompanied Ceftazidime-Avibactam Resistance Acquisition.Microbiology spectrum · 2022Article
- Article
- A genome-wide atlas of antibiotic susceptibility targets and pathways to tolerance.Nature communications · 2022Article
- Gradients in gene essentiality reshape antibacterial research.FEMS microbiology reviews · 2022Review
- Combating Antimicrobial Resistance via Single-Cell Diagnostic Technologies Powered by Droplet Microfluidics.Accounts of chemical research · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
Current approaches explore bacterial genes that change transcriptionally upon stress exposure as diagnostics to predict antibiotic sensitivity. However, transcriptional changes are often specific to a species or antibiotic, limiting implementation to known settings only. While a generalizable approach, predicting bacterial fitness independent of strain, species or type of stress, would eliminate such limitations, it is unclear whether a stress-response can be universally captured. By generating a multi-stress and species RNA-Seq and experimental evolution dataset, we highlight the strengths and limitations of existing gene-panel based methods. Subsequently, we build a generalizable method around the observation that global transcriptional disorder seems to be a common, low-fitness, stress response. We quantify this disorder using entropy, which is a specific measure of randomness, and find that in low fitness cases increasing entropy and transcriptional disorder results from a loss of regulatory gene-dependencies. Using entropy as a single feature, we show that fitness and quantitative antibiotic sensitivity predictions can be made that generalize well beyond training data. Furthermore, we validate entropy-based predictions in 7 species under antibiotic and non-antibiotic conditions. By demonstrating the feasibility of universal predictions of bacterial fitness, this work establishes the fundamentals for potentially new approaches in infectious disease diagnostics.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.