Evidence map›Paper›PMID 34536379›Full record

ArticleCell systems2021

High-throughput characterization of mutations in genes that drive clonal evolution using multiplex adaptome capture sequencing.

Daniel E Deatherage, Jeffrey E Barrick

Open access · greenAbstract read
In one paragraph

Article in Cell systems, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.9field-weighted citation impact, top 13% 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

7 citing papers in PubMed, 12 citations in OpenAlex.

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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

2 authors at 1 institution in 1 country.

Daniel E DeatherageDepartment of Molecular Biosciences, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA.
Jeffrey E BarrickDepartment of Molecular Biosciences, Center for Systems and Synthetic Biology, The University of Texas at Austin, Austin, TX 78712, USA. Electronic address: jbarrick@cm.utexas.edu.
The University of Texas at Austin · US

Funding

The biophysical basis of translational selectionR01GM088344 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI BARRICK, JEFFREY EVAN, WILKE, CLAUS O · 2009 to 2023
$3.5M
Identifying Mutations that Promote Microbial EvolvabilityR00GM087550 · NIGMS · UNIVERSITY OF TEXAS AT AUSTIN · PI BARRICK, JEFFREY EVAN · 2011 to 2013
$724k
NIGMS NIH HHS R00 GM087550NIGMS NIH HHS R01 GM088344
6 · The paper itself

Abstract

Understanding how cells are likely to evolve can guide medical interventions and bioengineering efforts that must contend with unwanted mutations. The adaptome of a cell-the neighborhood of genetic changes that are most likely to drive adaptation in a given environment-can be mapped by tracking rare beneficial variants during the early stages of clonal evolution. We used multiplex adaptome capture sequencing (mAdCap-seq), a procedure that combines unique molecular identifiers and hybridization-based enrichment, to characterize mutations in eight Escherichia coli genes known to be under selection in a laboratory environment. We tracked 301 mutations at frequencies as low as 0.01% and inferred the fitness effects of 240 of these mutations. There were distinct molecular signatures of selection on protein structure and function for the three genes with the most beneficial mutations. Our results demonstrate how mAdCap-seq can be used to deeply profile a targeted portion of a cell's adaptome.

Indexed as

Escherichia coliEscherichia coli ProteinsAdaptation, PhysiologicalClonal EvolutionMutationEscherichia coli Proteinsclonal interferencedistribution of fitness effectsDNA topoisomerase Ilong-term evolution experiment with E. coliLTEENadRPykFpyruvate kinaseTopA

Identifiers

PMID34536379
PMCPMC8678185
OpenAlexW3199973217

What OpenQuestion holds

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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.