Evidence map›Paper›PMID 28813680›Full record

ArticleCell reports2017

Antibiotics Disrupt Coordination between Transcriptional and Phenotypic Stress Responses in Pathogenic Bacteria.

Paul A Jensen, Zeyu Zhu, Tim van Opijnen

Open access · goldAbstract read
In one paragraph

Article in Cell reports, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing papers in PubMed
4.0field-weighted citation impact, top 5% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

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.

2 · The registry

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.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

48 citing papers in PubMed, 91 citations in OpenAlex.

  1. Article
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  4. Synergistic inhibition ofFrontiers in microbiology · 2026
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  10. Matrine AttenuatesMicroorganisms · 2025
    Article
  11. Article
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  14. Article
  15. Review
  16. Proteomic survey of the DNA damage response inJournal of bacteriology · 2023
    Article
  17. Dual ICA to extract interacting sets of genes and conditions from transcriptomic data.ACM-BCB ... ... : the ... ACM Conference on Bioinformatics, Computational Biology and Biomedicine. ACM Conference on Bioinformatics, Computational Biology and Biomedicine · 2023
    Article
  18. Review
  19. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 1 institution in 1 country.

Paul A JensenBiology Department, Boston College, Chestnut Hill, MA, USA. Electronic address: pjens@illinois.edu.
Zeyu ZhuBiology Department, Boston College, Chestnut Hill, MA, USA. Electronic address: zhuzd@bc.edu.
Tim van OpijnenBiology Department, Boston College, Chestnut Hill, MA, USA. Electronic address: vanopijn@bc.edu.
Boston College · US

Funding

Predicting the emergence of antibiotic resistance through multi-omics approaches and Immune System-surveillanU01AI124302 · NIAID · BOSTON COLLEGE · PI BENTO, JOSE, COOPER, VAUGHN · 2016 to 2020
$10.2M
The bacterial response to antibiotics and the evolution of antibiotic resistanceR01AI110724 · NIAID · BOSTON COLLEGE · PI VAN OPIJNEN, TIM · 2015 to 2019
$2.0M
NIAID NIH HHS R01 AI110724NIAID NIH HHS U01 AI124302
6 · The paper itself

Abstract

Bacterial genes that change in expression upon environmental disturbance have commonly been seen as those that must also phenotypically matter. However, several studies suggest that differentially expressed genes are rarely phenotypically important. We demonstrate, for Gram-positive and Gram-negative bacteria, that these seemingly uncoordinated gene sets are involved in responses that can be linked through topological network analysis. However, the level of coordination is stress dependent. While a well-coordinated response is triggered in response to nutrient stress, antibiotics trigger an uncoordinated response in which transcriptionally and phenotypically important genes are neither linked spatially nor in their magnitude. Moreover, a gene expression meta-analysis reveals that genes with large fitness changes during stress have low transcriptional variation across hundreds of other conditions, and vice versa. Our work suggests that cellular responses can be understood through network models that incorporate regulatory and genetic relationships, which could aid drug target predictions and genetic network engineering.

Indexed as

Gene Expression Regulation, BacterialGene Regulatory NetworksGenes, BacterialAnti-Bacterial AgentsCulture MediaGene Expression ProfilingGenetic FitnessPhenotypePseudomonas aeruginosaStreptococcus pneumoniaeStress, PhysiologicalTranscription, GeneticAnti-Bacterial AgentsCulture Mediadata integrationmetabolic modelingPseudomonasRNA-seqStreptococcusstress responsesystems biologyTn-seq

Identifiers

PMID28813680
PMCPMC5584877
OpenAlexW2748973356

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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.