Complex interplay between gene deletions and the environment uncovers cellular roles for genes of unknown function in Escherichia coli

Abstract

Phenotypic outcomes can be heavily affected by environmental factors. In this study, we exploited the previously observed nutrient-dependency of cell biological phenotypic features, captured by a cross-condition image-based profiling assay of Escherichia coli deletion strains, to examine this in more detail. We identified several general principles, including the existence of a spectrum of deviating phenotypes across nutrient conditions (i.e., from nutrient- or feature-specific to pleiotropic phenotypic deviations), limited conservation of phenotypic deviations across nutrient conditions (i.e., limited phenotypic robustness), and a subset of nutrient-independent phenotypic deviations (indicative of consistent genetic determinants of specific phenotypic features). In a subsequent step, we used this cross-condition dataset to identify five genes of unknown function of which the deletion displayed either nutrient-independent phenotypic deviations or phenotypic similarities to genes of known function: yibN, yaaY, yfaQ, ybiJ, and yijD. These genes showed different levels of phylogenetic conservation, ranging from conserved across the tree of life (yibN) to only present in some genera of the Enterobacterales (yaaY). Analysis of the structural properties of the proteins encoded by these y-genes, identification of structural similarities to other proteins, and the examination of their subcellular localization yielded new insights into their contribution to E. coli cell morphogenesis, cell cycle progression and cell growth. Together, our approach showcases how bacterial image-based profiling assays and datasets can serve as a gateway to reveal the function of uncharacterized proteins. ImportanceDespite unprecedented access to genomic information, predicting phenotypes based on genotypes remains notoriously difficult. One major confounding factor is the environment and its ability to modulate phenotypic outcomes. Another is the fact that a large fraction of protein-coding genes in bacterial genomes remains uncharacterized and have no known function. In this work, we use a large-scale cross-condition image-based profiling dataset to characterize nutrient-dependent phenotypic variability of E. coli deletion strains and exploit it to provide insight into the cellular role of genes of unknown function. Through our analysis, we identified five genes of unknown function that we subsequently further characterized by examining their phylogenetic conservation, predicted structural properties and similarities, and their intracellular localization. Combined, this approach highlights the potential of cross-condition image-based profiling, which extracts many cell biological phenotypic readouts across multiple conditions, to better understand nutrient-dependent phenotypic variability and uncover protein function.