Evidence map›Paper›PMID 38052815›Full record

ArticleNature communications2023

Environmental modulation of global epistasis in a drug resistance fitness landscape.

Juan Diaz-Colunga, Alvaro Sanchez, C Brandon Ogbunugafor

Open access · goldAbstract read
In one paragraph

Article in Nature communications, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed
7.5field-weighted citation impact, top 2% 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

14 citing papers in PubMed, 25 citations in OpenAlex.

  1. Review
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  5. Deconstructing empirical fitness seascapes across scales of granularity.bioRxiv : the preprint server for biology · 2026
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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 2 institutions in 2 countries.

Juan Diaz-ColungaDepartment of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA. juan.diazcolunga@yale.edu.ORCID 0000-0001-8995-4529
Alvaro SanchezDepartment of Microbial Biotechnology, Spanish National Center for Biotechnology CNB-CSIC, 28049, Madrid, Spain. alvaro.sanchez@usal.es.ORCID 0000-0002-2292-5608
C Brandon OgbunugaforDepartment of Ecology & Evolutionary Biology, Yale University, New Haven, CT, 06511, USA. brandon.ogbunu@yale.edu.ORCID 0000-0002-1581-8345
Universidad de Salamanca · ESSanta Fe Institute · US

Funding

National Science Foundation (NSF) 2142720
6 · The paper itself

Abstract

Interactions between mutations (epistasis) can add substantial complexity to genotype-phenotype maps, hampering our ability to predict evolution. Yet, recent studies have shown that the fitness effect of a mutation can often be predicted from the fitness of its genetic background using simple, linear relationships. This phenomenon, termed global epistasis, has been leveraged to reconstruct fitness landscapes and infer adaptive trajectories in a wide variety of contexts. However, little attention has been paid to how patterns of global epistasis may be affected by environmental variation, despite this variation frequently being a major driver of evolution. This is particularly relevant for the evolution of drug resistance, where antimicrobial drugs may change the environment faced by pathogens and shape their adaptive trajectories in ways that can be difficult to predict. By analyzing a fitness landscape of four mutations in a gene encoding an essential enzyme of P. falciparum (a parasite cause of malaria), here we show that patterns of global epistasis can be strongly modulated by the concentration of a drug in the environment. Expanding on previous theoretical results, we demonstrate that this modulation can be quantitatively explained by how specific gene-by-gene interactions are modified by drug dose. Importantly, our results highlight the need to incorporate potential environmental variation into the global epistasis framework in order to predict adaptation in dynamic environments.

Indexed as

Epistasis, GeneticGenetic FitnessDrug ResistanceEvolution, MolecularGenotypeModels, GeneticMutation

Identifiers

PMID38052815
PMCPMC10698197
OpenAlexW4389333260

What OpenQuestion holds

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LicenceCC BY
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.