Evidence map›Paper›PMID 42685135›Full record

ArticlePLoS computational biology2026

Synergies and trade-offs in the heat shock response mechanism.

Rupal Chauhan, Biswajit Das, Ajeet K Sharma

Abstract read
In one paragraph

Article in PLoS computational biology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
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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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Rupal ChauhanDepartment of Physics, Indian Institute of Technology Jammu, Jammu, India.
Biswajit DasAmrita School of Artificial Intelligence, Amrita Vishwa Vidyapeetham, Coimbatore, India.
Ajeet K SharmaDepartment of Physics, Indian Institute of Technology Jammu, Jammu, India.ORCID 0000-0002-2819-1668

Funding

Ministry of Education, Government of India
6 · The paper itself

Abstract

E. coli relies on the heat shock response (HSR) to preserve protein homeostasis under stress, through three feedback modules: feedforward translational control, chaperone-mediated sequestration and targeted degradation. Although previous studies have highlighted how this layered architecture ensures rapid and robust protection compared to simpler designs, not much attention is paid to how these modules interact. Moreover, how do interactions among the three modules balance performance trade-offs, where gains in one module may come at the expense of another, yet together yield an optimal overall response? We address this using a mathematical model that integrates protein folding with σ32 regulation. We show that the feedback modules both cooperate and compete, giving rise to nonmonotonic dynamics that govern HSR performance. Specifically, increasing feedforward strength does accelerate response, but beyond a threshold, despite increasing chaperone levels, it paradoxically slows recovery. Similarly, while sequestration enhances relative chaperone production and per-chaperone efficiency, when excessive, it traps σ32 in inactive complexes, prolonging recovery and delaying shutdown. Mapping the parameter space reveals regimes of synergy as well as trade-offs between speed and efficiency, with wild-type parameters lying near the optimal region. These results reveal design principles that produces a robust and efficient heat shock response.

Indexed as

Escherichia coliHeat-Shock ResponseModels, BiologicalComputational BiologyEscherichia coli ProteinsFeedback, PhysiologicalHeat-Shock ProteinsMolecular ChaperonesProtein FoldingSigma FactorEscherichia coli ProteinsHeat-Shock Proteinsheat-shock sigma factor 32Molecular ChaperonesSigma Factor

Identifiers

PMID42685135
PMCPMC13577541

What OpenQuestion holds

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Registered trials

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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.