Domain-based Comparative Analysis of Bacterial Proteomes: Uniqueness, Interactions, and the Dark Matter

Background: Proteins may have none, single, double, or multiple domains, while a single domain may appear in multiple proteins. Their distribution patterns may have impacts on bacterial physiology and lifestyle. Objective: This study aims to understand how domains are distributed and duplicated in bacterial proteomes, in order to better understand bacterial physiology and lifestyles. Methods: In this study, we used 16712 Hidden Markov Models to screen 944 bacterial reference proteomes versus a threshold E-value<0.001. The number of non-redundant domains and duplication rates of redundant domains for each species were calculated. The unique domains, if any, were also identified for each species. In addition, the properties of no-domain proteins were investigated in terms of physicochemical properties. Results: The increasing number of non-redundant domains for a bacterial proteome follows the trend of an asymptotic function. The domain duplication rate is positively correlated with proteome size and increases more rapidly. The high percentage of single-domain proteins is more associated with small proteome size. For each proteome, unique domains were also obtained. Moreover, no-domain proteins show differences with the other three groups for several physicochemical properties analysed in this study. Conclusion: The study confirmed that a low domain duplication rate and a high percentage of singledomain proteins are more likely to be associated with bacterial host-dependent or restricted nicheadapted lifestyle. In addition, the unique lifestyle and physiology were revealed based on the analysis of species-specific domains and core domain interactions or co-occurrences.