Identity
Escherichia coli is a bacterial reference organism included in the cross-organism annotation-gap analysis. 1
Known aliases include E. coli and E. coli Keio (Keio). 1
A stable external identifier was not reported in this document. 1
Findings in annotation-gap discovery
E. coli Keio was one of 14 organisms selected for analysis using carbon-source Fitness Browser data and random-barcode transposon sequencing (RB-TnSeq), a method that measures genome-wide mutant fitness with barcoded transposon libraries. 1
For E. coli Keio, 7 gapfilled reaction-organism pairs were evaluated and 4 were resolved, giving a reported resolution rate of 57.1%. 1
The E. coli Keio result contributed to the study’s cross-organism integration of metabolic-model gapfilling, fitness phenotypes, pangenome annotations, GapMind pathway evidence, and BLAST homology. 1
The analysis used draft metabolic models based on ModelSEED and RAST annotations and evaluated them with flux-balance analysis (FBA), a constraint-based method for predicting metabolic flux and growth. 1
Pangenome and GapMind coverage
The essential-metabolome analysis found 0 GapMind predictions for the E. coli K-12 Keio genome, GCF_000005845.2, in the KBase pangenome collection. 2 This missing coverage was attributed to E. coli’s exclusion from GTDB pangenome construction because it had too many genomes for species-level analysis, contributing to reduction of the intended 45-organism analysis to a 7-organism pilot. 2
The conservation-versus-fitness analysis refines that context: although the main Escherichia coli clade was absent because it contained too many genomes, E. coli BW25113/Keio mapped to the small s__Escherichia_coli_E clade at only 26.1% coverage. 3 This supports interpreting the missing GapMind and limited pangenome evidence as coverage and clade-construction constraints rather than evidence that E. coli lacks conserved genes. 3
Fitness Browser and Web of Microbes integration
The Web of Microbes (WoM) analysis supports E. coli Keio’s role as a reference strain by matching E. coli BW25113 to the Fitness Browser’s Keio record, with 4,610 genes and 168 experiments. 4 This refines the broader carbon-source fitness evidence: the WoM BW25113 record contained only 12 observations focused on sulfur metabolism in ZMMG medium, despite the richer Keio Fitness Browser resource. 4
Functional dark-matter prioritization
The functional-dark-matter analysis supports E. coli Keio’s role as an experimentally useful reference by ranking E. coli Keio 14796 among its highest-priority essential dark-gene candidates, with score 0.875 and a YbeY domain prediction. 5 Because essential genes lack viable RB-TnSeq mutants, the report recommends CRISPRi (CRISPR interference, transcriptional knockdown) followed by growth measurements under standard and stress conditions; this refines the earlier fitness-based characterization with a direct strategy for testing essential, uncharacterized genes. 5
Literature coverage
PaperBLAST further supports E. coli’s status as a heavily studied bacterial reference: E. coli K-12 had 8,860 papers, second among the three leading bacterial organisms in the collection after Mycobacterium tuberculosis H37Rv (9,079) and ahead of Pseudomonas aeruginosa PAO1 (5,928). 6 This literature concentration refines the experimental-reference picture with a resource-level measure of research attention, while PaperBLAST’s text-mining and open-access limitations mean paper counts do not establish complete functional characterization. 6
IBD pathobiont and phage-targeting evidence
The IBD analysis extends E. coli’s reference-organism evidence into disease-associated ecology: E. coli was one of six actionable Tier-A pathobionts, with total score 3.6, and was among five donor-2708-engraftment pathobionts that passed the confound-free CD-up test, with CLR-Δ = +1.43. 7
The analysis supports an E. coli-centered iron and genotoxin mechanism: E. coli correlated with heme biosynthesis at ρ = 0.640, had mean ρ = +0.45 with 15 iron pathways, and alone among the six actionable core species carried the iron-plus-genotoxin MIBiG signature, including 19 Yersiniabactin, 16 Enterobactin, 8 Colibactin, and 15 Microcin B17 BGCs. 7
The paired metabolomics analysis further associated E. coli with cadaverine at ρ = +0.45, and with choline and tryptophan at +0.25 for each; these findings refine the earlier multi-omics characterization but do not establish causality. 7
E. coli had direct phage evidence in PhageFoundry: the five-phage cocktail DIJ07_P2, LF73_P1, AL505_Ev3, 55989_P2, and LF110_P2 covered 94.7 % of 188 tested E. coli strains, although the dataset did not establish in-vivo efficacy or distinguish AIEC from commensal strains. 7
Related pages
- Annotation-Gap Discovery via Phenotype-Fitness-Pangenome-Gapfilling Integration — source summary for the cross-organism annotation-gap study. 1
- Conservation vs Fitness — Linking FB Genes to Pangenome Clusters — source summary for linking Fitness Browser essentiality to pangenome conservation. 3
- Essential Metabolome: GapMind Pathway Analysis Across Essential-Gene Organisms — source summary for the GapMind essential-metabolome pilot. 2
- Functional Dark Matter — Experimentally Prioritized Novel Genetic Systems — source summary for essential dark-gene prioritization. 5
- Metagenome-Prioritized Phage Cocktails for Crohn’s Disease and IBD — source summary for IBD pathobiont prioritization and phage-cocktail design. 7
- PaperBLAST Data Explorer — Literature Coverage Bias in Protein Sequence Space — source summary for PaperBLAST literature-coverage and protein-family analysis. 6
- Web of Microbes Data Explorer — source summary for Web of Microbes cross-collection integration. 4
- metabolic-model-gapfilling — the study resolved 4 of 7 E. coli Keio gapfilled pairs. 1
- gene-essentiality — E. coli Keio 14796 was prioritized as an essential dark-gene candidate for CRISPRi testing. 5
- condition-specific-fitness — E. coli Keio was analyzed using carbon-source fitness measurements. 1
- pangenome-integration — pangenome evidence was part of the candidate-gene assignment pipeline, while conservation-versus-fitness analysis exposed limited E. coli clade coverage. 1,3
- multi-omics-integration — the studies combined fitness, annotation, pathway, homology, and metabolic-model evidence; the IBD analysis adds taxonomy–metabolomics and BGC evidence. 1,7
- kescience-fitnessbrowser — source of the organism’s carbon-source fitness data. 1
- tnseq — method family underlying the RB-TnSeq measurements. 1
- modelseed — source of metabolic-model annotations and gapfilling reactions. 1
- gapmind — pathway-completeness method whose collection lacked predictions for the Keio genome. 2
- gtdb — pangenome construction context associated with the missing GapMind coverage. 2