GSE117303
Reframing gene essentiality in terms of adaptive flexibility
Essentiality assays are commonly practiced as important tools for the discovery of gene functions. Growth/no growth screens of single gene knockout strain collections are often utilized to test the predictive power of genome-scale models. False positive predictions occur when computational analysis predicts a gene to be non-essential, however experimental screens deem the gene to be essential. One explanation for this inconsistency is that the model contains the wrong information, possibly an incorrectly annotated alternative pathway or isozyme reaction. Inconsistencies could also be attributed to experimental limitations, such as growth tests with arbitrary time cut-offs. The focus of this study was to resolve such inconsistencies to better understand isozyme activities and gene essentiality. Gene-deletion strains associated with false positive predictions of gene essentiality on defined minimal medium for Escherichia coli were targeted for extended growth tests followed by population sequencing. Overall design: RNAseq was performed on various Keio collection gene-deletion populations and clones adapted for growth on D-glucose. The genes that were knocked out of these strains were thrA, ptsI, and serB. Differentially expressed genes were examined comparing gene-deletion strains to the wild type strain.