Evidence map›Paper›PMID 42371986›Full record

ArticlePLoS computational biology2026

Systematic design of auxotrophic strains and media conditions to probe metabolic functions in E. coli.

Roghaye Mohammadbeygi, Patrick F Suthers, Fang-Yu Chung, Brian F Pfleger, Costas D Maranas

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.

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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

5 authors.

Roghaye MohammadbeygiDepartment of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
Patrick F SuthersDepartment of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.
Fang-Yu ChungDepartment of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Brian F PflegerDepartment of Chemical and Biological Engineering, University of Wisconsin-Madison, Madison, Wisconsin, United States of America.
Costas D MaranasDepartment of Chemical Engineering, The Pennsylvania State University, University Park, Pennsylvania, United States of America.ORCID https://orcid.org/0000-0002-1508-1398

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Despite progress in automated gene annotation, many deficiencies and knowledge gaps remain, even for well-studied organisms. Of particular concern is the accuracy and detail of annotations for transporters of various organic substrates and products of metabolism and for enzymes that do not share sequence homology with well-characterized strains. Unfortunately, annotation errors present in earlier genome-scale metabolic (GSM) models propagate to newer models with few opportunities for later correction. Here, we introduce a systematic computational procedure that applies the Escherichia coli genome-scale metabolic model iML1515, extended with transcriptional regulatory rules, to design auxotrophs that can grow on glucose but fail to grow on different carbon substrate(s) unless rescued with the addition of an ORF encoding a complementation metabolic function (transport and enzymatic reactions). Using the E. coli GSM model supplemented with regulatory rules that quantify growth/no growth outcomes on different organic substrates, we identified 258 distinct auxotrophic designs (97 single-gene, 142 double-gene, and 19 triple-gene knockouts) for which specific single functions can uniquely complement them. Experimental validation of 61 single-knockout strains demonstrated 59% confirmed auxotrophy and 28% partial auxotrophy. We envision that this collection of auxotrophic strains can be used to disambiguate the metabolic role of unannotated or poorly annotated genes.

Indexed as

Escherichia coliModels, BiologicalComputational BiologyCulture MediaEscherichia coli ProteinsGene Knockout TechniquesGenome, BacterialGlucoseMetabolic Networks and PathwaysCulture MediaEscherichia coli ProteinsGlucose

Identifiers

PMID42371986
PMCPMC13345470

What Socratic holds

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LicenceCC BY
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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.