Potential benefit of loss-of-function on bacterial fitness
Escherichia coli is a well-studied organism with extensive genomic and proteomic data. This study examines how gene loss reallocates cellular resources and impacts fitness. Genes were classified based on fitness measurements as essential, important, mean-effect, or fitness-enhancing. Using proteomic data, we analyzed the relationship between protein production cost and fitness, finding that genes with a high proteomic mass fraction are more likely to affect fitness, while fitness-enhancing deletions rarely improve fitness by reducing proteomic burden. We calculated the cumulative of proteome fractions encoded by genes classified as mean-effect and compared it with the results from the ME-model simulations. The mean-effect category constitutes 31-75% of the proteome, with the highest proportion LB, while enrichment analysis of core mean-effect genes highlighted transmembrane transport as the main functional category. Furthermore, we identified a subset of genes whose deletion increased fitness compared to the mean; they generally have low expression, and many have unknown functions. AI-assisted structural analyses identified domains and conserved features compatible with DNA-binding proteins, suggesting that some may represent putative transcriptional regulators requiring further validation. RpoS, stress sigma factor controlling up to 15% of the proteome is one of the transcriptional regulators in the fitness-enhancing category. Our findings suggest that the cost of being a generalist is linked to transcriptional regulation, while molecular transport represents a high burden for nutrient readiness. ImportanceThis study provides new insights into how gene loss benefits bacteria by identifying gene categories and their associated protein fractions whose disruption does not impose large fitness penalties. Additionally, it uncovers specific fitness-enhancing genes and generates hypotheses based on structural analyses for previously uncharacterized ones. Our findings suggest that several of these genes may encode putative transcriptional regulators, highlighting a potential role for regulatory complexity in cellular efficiency. By revealing how certain gene deletions enhance fitness and which gene categories are nonessential, this work advances our understanding of bacterial adaptation and genome streamlining. These insights have broad implications for evolutionary biology, metabolic engineering, and biotechnology, offering strategies to optimize microbial function by selectively reducing genetic and regulatory burden.