Bioinformatics, an interdisciplinary eld between information science and biol- ogy, provided new insights about living things by analyzing data. These methods are generally called "omics", and it specializes on various levels of biological data: genomics for DNA-level, transcriptomics for RNA-level, proteomics for protein- level, metabolomics for metabolite-level, and phenomics for phenotype-level. Recently, it has become possible and necessary to integrate different types of biological data and analyze their relationships along the enormous and detailed data spear headed by new experimental technologies, such as Next Generation Sequencers, high performance chromatographies. However, integrated analytical approaches called trans-omics analysis, are still maturing largely. In this study, we applied trans-omics analysis methods to examine micro- bial electron transfer chain (ETC). Phenotype of ETC was de ned by retrieving bio-energetically experimental measurements from literature. The quanti ed phe- notypes were integrated into the basic phylogenetic analysis of ETC proteins. We determined 17 clusters and 20 cluster pairs of ETC proteins to be statistically signi cant phenotypes. These clusters imply evolution under the constraints of the ETC. Moreover, from the viewpoint of proteomics, 3 clusters and 4 pairs were con rmed to have the apparent regions of mutation in their 3D structures. This study contributed much in the rising eld of trans-omics.