The y-ome defines the 35% of Escherichia coli genes that lack experimental evidence of function

Experimental studies of Escherichia coli K-12 MG1655 often implicate poorly annotated genes in cellular phenotypes. However, we lack a systematic understanding of these genes. How many are there? What information is available for them? And what features do they share that could explain the gap in our understanding? Efforts to build predictive, whole-cell models of E. coli inevitably face this knowledge gap. We approached these questions systematically by assembling annotations from the knowledge bases EcoCyc, EcoGene, UniProt and RegulonDB. We identified the genes that lack experimental evidence of function (the 'y-ome') which include 1600 of 4623 unique genes (34.6%), of which 111 have absolutely no evidence of function. An additional 220 genes (4.7%) are pseudogenes or phantom genes. y-ome genes tend to have lower expression levels and are enriched in the termination region of the E. coli chromosome. Where evidence is available for y-ome genes, it most often points to them being membrane proteins and transporters. We resolve the misconception that a gene in E. coli whose primary name starts with 'y' is unannotated, and we discuss the value of the y-ome for systematic improvement of E. coli knowledge bases and its extension to other organisms

Additional file 1: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

Sheet 1: Reactions in iEK1011 and details of reactions. Sheet 2: Metabolites in iEK1011 and details of metabolites. Sheet 3: Genes present in previous models but not accounted for in iEK1011. Sheet 4: Gene Essentiality Predictions with the Griffin et al. dataset. Sheet 5: Gene Essentiality Predictions with the deJesus dataset. Sheet 6: Description of media conditions used in study. Sheet 7: Maximum FVA values for AMR genes across different objectives on in vivo media. Sheet 8: Maximum FVA values for AMR genes across different objectives on in vitro media. Sheet 9: “Shared” Essentiality Predictions with the Griffin et al. dataset. Sheet 10: “Shared” Essentiality Predictions with the deJesus et al. dataset. Sheet 11: List of blocked reactions in iEK1011. Sheet 12: “All models incorrect” - List of genes that were incorrectly predicted across all models and their corresponding iEK1011 subsystems. Sheet 13: “iEK Wrong and sMtb Correct” - List of incorrect iEK1011 predictions that were correctly predicted by sMtb. Sheet 13: “iEK Correct and sMtb Wrong” - List of correct iEK1011 predictions that were incorrectly predicted by sMtb. (XLSX 258 kb

Additional file 3: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

iEK1011 models: Genome-scale models of iEK1011 in json format initialized with different media conditions. iEK1011_griffinEssen_media.json - Used for essentiality testing on Griffin et al. dataset. iEK1011_deJesusEssen_media.json - Used for essentiality testing on deJesus et al. dataset. iEK1011_m7H10_media.json - iEK1011 initialized with Middlebrook 7H10 media. iEK1011_drugTesting_media.json - Used for simulating on Lowenstein-Jensen media. iEK1011_inVivo_media.json - Used for simulating on approximated physiological media. (ZIP 310 kb

Additional file 2: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

A conversion of the sMtb model to BiGGs identifiers (JSON 476 kb

Additional file 4: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

Escher Maps: Contains four escher maps of M. tuberculosis metabolic subsystems. Central_carbon.json. Arabinogalactan_peptidoglycan_complex.json. Nitrogen.json. Sulfur_and_folate.json (ZIP 236 kb

Additional file 6: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

An ipython notebook that runs the simulations described in this study. (IPYNB 637 kb

Additional file 5: of Updated and standardized genome-scale reconstruction of Mycobacterium tuberculosis H37Rv, iEK1011, simulates flux states indicative of physiological conditions

Table S1. Table describing changes in gene essentiality predictions according to changes in GAM and NGAM values that were utilized across different genome-scale reconstructions of M. tuberculosis .Table S2. List of reactions in iEK1011 that violate the law of mass conservation. Table S3. Examples of false negatives computed by iEK1011 on the DeJesus et al. gene essentiality dataset that are not within the iSM810 model, and reasoning for its inclusion [54, 55]. Table S4. Gene essentiality predictions using the shared set of 472 genes. (DOCX 17 kb