Evidence map›Paper›PMID 36168291›Full record

ArticleBiophysical journal2022

Optimal transcriptional regulation of dynamic bacterial responses to sudden drug exposures.

Daniel Schultz, Mirjana Stevanovic, Lev S Tsimring

Open access · greenAbstract read
In one paragraph

Article in Biophysical journal, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
0.7field-weighted citation impact, top 25% 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

3 citing papers in PubMed, 4 citations in OpenAlex.

  1. Direct Quantification of Protein-Protein Interactions in Living Bacterial Cells.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025
    Article
  2. Article
  3. Article
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 2 institutions in 1 country.

Daniel SchultzDepartment of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire. Electronic address: daniel.schultz@dartmouth.edu.
Mirjana StevanovicDepartment of Microbiology and Immunology, Geisel School of Medicine at Dartmouth, Hanover, New Hampshire.
Lev S TsimringSynthetic Biology Institute, University of California, San Diego, La Jolla, California.
Dartmouth College · USUniversity of California, San Diego · US

Funding

Zhao - Proj 2P20GM130454 · NIGMS · DARTMOUTH COLLEGE · PI Li Song · 2019 to 2026
$27.2M
Engineered Gene Circuits for Basic Science and BiotechnologyR01GM069811 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI HASTY, JEFF M, TSIMRING, LEV S · 2004 to 2025
$13.6M
NIGMS NIH HHS P20 GM130454NIGMS NIH HHS R01 GM069811
6 · The paper itself

Abstract

Cellular responses to the presence of toxic compounds in their environment require prompt expression of the correct levels of the appropriate enzymes, which are typically regulated by transcription factors that control gene expression for the duration of the response. The characteristics of each response dictate the choice of regulatory parameters such as the affinity of the transcription factor to its binding sites and the strength of the promoters it regulates. Although much is known about the dynamics of cellular responses, we still lack a framework to understand how different regulatory strategies evolved in natural systems relate to the selective pressures acting in each particular case. Here, we analyze a dynamical model of a typical antibiotic response in bacteria, where a transcriptionally repressed enzyme is induced by a sudden exposure to the drug that it processes. We identify strategies of gene regulation that optimize this response for different types of selective pressures, which we define as a set of costs associated with the drug, enzyme, and repressor concentrations during the response. We find that regulation happens in a limited region of the regulatory parameter space. While responses to more costly (toxic) drugs favor the usage of strongly self-regulated repressors, responses where expression of enzyme is more costly favor the usage of constitutively expressed repressors. Only a very narrow range of selective pressures favor weakly self-regulated repressors. We use this framework to determine which costs and benefits are most critical for the evolution of a variety of natural cellular responses that satisfy the approximations in our model and to analyze how regulation is optimized in new environments with different demands.

Indexed as

Gene Expression RegulationTranscription FactorsBacteriaBinding SitesGene Expression Regulation, BacterialPromoter Regions, GeneticTranscription Factors

Identifiers

PMID36168291
PMCPMC9675034
OpenAlexW4297141455

What OpenQuestion holds

Textmetadata
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.