Abstract

Previous bioinformatics studies have linked gain or loss of energy reserves with host-pathogen interactions and bacterial virulence based on a comparatively small number of bacterial genomes or proteomes. Thus, understanding the theoretical distribution patterns of energy reserves across bacterial species could provide a shortcut route to look into bacterial lifestyle and physiology. So far, five major energy reserves have been identified in bacteria due to their capacity to support bacterial persistence under nutrient deprivation conditions. These include polyphosphate (polyP), glycogen, wax ester (WE), triacylglycerol (TAG), and polyhydroxyalkanoates (PHAs). Although the enzymes related with metabolism of energy reserves are well understood, there is a lack of systematic investigations into the distribution of bacterial energy reserves from an evolutionary point of view. In this study, we sourced 8282 manually reviewed bacterial reference proteomes and combined a set of hidden Markov sequence models (HMMs) to search homologs of key enzymes related with the metabolism of energy reserves. Our results revealed that specific pathways like trehalose-related glycogen metabolism and enzymes such as wax ester synthase/acyl-CoA:diacylglycerol acyltransferase (WS/DGAT) are mainly restricted within specific types of bacterial groups, which provides evolutionary insights into the understanding of their origins and functions. In addition, the study also confirms that loss of energy reserves like polyP metabolism absence in Mollicutes is correlated with bacterial genome reduction. Through this analysis, a clearer picture about the metabolism of energy reserves in bacteria is presented, which could serve as a guide for further theoretical and experimental analyses of bacterial energy metabolism.

Conclusions

Distribution patterns of key enzymes and their combined pathways in bacteria provided a comprehensive view of how energy reserves are incorporated and lost. In general, polyP, PHA, and glycogen are widely distributed across bacterial species as energy storage compounds. The other two neutral lipids investigated in this study are comparatively minor energy reserves in bacteria and mainly found in the super phylum Proteobacteria and phylum Actinobacteria. Within the group, more bacteria have the capacity to accumulate WE and TAG due to the abundance of WS/DGAT homolog. Comparatively, polyP acts as a transient energy reserve while neutral lipids are a more sustainable energy provider (Finkelstein et al. 2010; Wang and Wise 2011). Thus, neutral lipids could be major players for bacterial persistence under harsh conditions such terrestrial and aquatic environments. As for glycogen, its ability to enhance bacterial environmental viability is still controversial. Its widespread distribution in bacteria indicates that its metabolism is tightly linked with bacterial essential activities. In sum, through this study, we obtained a much clearer picture about how key enzymes responsible for the metabolism of energy reserves are distributed in bacteria. Further investigation via incorporating bacterial physiology and lifestyle could supply additional explanations to illustrate the distribution patterns, although experimental evidence is indispensable to confirm the computational analysis.