Evidence map›Paper›PMID 42732001›Full record

ArticleEMBO reports2026

Selection favors cost-ordered adaptive mutational paths in a stress-magnitude-dependent manner.

Anjali V Patil, Jiao Zhao, Snehal V Khairnar, Sonali Srivastava, Laurence Yang, Amitesh Anand

Abstract read
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In one paragraph

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

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0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

6 authors.

Anjali V PatilDepartment of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, India.ORCID http://orcid.org/0009-0009-4373-2619
Jiao ZhaoDepartment of Chemical Engineering, Queen's University, Kingston, Ontario, Canada.
Snehal V KhairnarDepartment of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, India.
Sonali SrivastavaBRIC-National Institute of Immunology, Delhi, India.
Laurence YangDepartment of Chemical Engineering, Queen's University, Kingston, Ontario, Canada.ORCID http://orcid.org/0000-0001-6663-7643
Amitesh AnandDepartment of Biological Sciences, Tata Institute of Fundamental Research, Mumbai, India. amitesh.anand@tifr.res.in.ORCID http://orcid.org/0000-0002-3720-4301

Funding

Department of Atomic Energy, Government of India (DAE) RTI4015Department of Biotechnology, Ministry of Science and Technology, India (DBT) BT/RLF/Re-entry/70/2020Government of Canada (GC) Genome Canada and Ontario 904 Genomics (OGI-207),and Genome Quebec
6 · The paper itself

Abstract

Chronic exposure to stress requires adaptive strategies beyond canonical regulatory mechanisms. Stress varies, both qualitatively and quantitatively, across physiological niches and exerts distinct selection pressures on colonizing bacteria. Bacteria employ diverse defense strategies to withstand various stressful conditions, yet how they tailor their responses to different magnitudes of the same stressor remains poorly understood. We used multiple adaptive laboratory evolution experiments of Escherichia coli across varying paraquat concentrations and genetic backgrounds to dissect adaptive strategies at different levels of stress. Integrating multi-omic analyses with a tailored genome-scale metabolic model-based parametrized cost calculations, we identify two fundamentally distinct tolerance mechanisms. Under low-paraquat stress, blocking the polyamine transporter that is reported to be hijacked for paraquat influx suffices to maintain optimal growth. In contrast, higher stress levels activate an energetically demanding program involving enhanced detoxification and efflux. The transport flux regulation establishes a primary defense layer, upon which metabolic repair systems provide additional fitness advantages. The stress magnitude-dependent differential engagement of previously reported paraquat tolerance approaches offers insights into the principles governing dynamic bacterial adaptation.

Identifiers

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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 Socratic graph.