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This content will become publicly available on June 29, 2027

Title: Systematic design of auxotrophic strains and media conditions to probe metabolic functions in E. coli
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 theEscherichia coligenome-scale metabolic modeliML1515, 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 theE. coliGSM 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.  more » « less
Award ID(s):
2319732
PAR ID:
10706235
Author(s) / Creator(s):
; ; ; ;
Editor(s):
Cannon, William R
Publisher / Repository:
PLoS Computational Biology
Date Published:
Journal Name:
PLOS Computational Biology
Volume:
22
Issue:
6
ISSN:
1553-7358
Page Range / eLocation ID:
e1014469
Format(s):
Medium: X
Sponsoring Org:
National Science Foundation
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