Mining for Distinct Amino Acid Sequences of Archaea Regarding Methane Production by Genome Comparison - sun jin yin (Asia University, 2008)
Methanogenic archaea is the only methane-producing microorganisms on earth. They can use hydrogen and carbon compound to obtain energy through the metabolic character of anaerobic respiration and then generate methane. Methane itself is an efficient fuel, can be used to make battery and generate electricity. Especially, methane hydrate (gas hydrate) is considered as the substitutes of petroleum energy in the future. In order to explore the specific metabolic character of methanogenic archaea, we excavate the coding sequence (CDS) of amino acid of protein which exclusively exists in methanogenic archaea by comparing the genome of them. We also examine their function and character. Hopefully these can provide biologist as a reference for further research. In this study we apply three steps, they are: (1) CDS clustering, (2) Mining of representative and specific CDS cluster, (3) investigation of function and character of the representative CDS cluster. First we retrieve information of whole sequence of CDS of 45 archaea strains (19 strains are methane-producing , 26 non-methaneproducing ) from NCBI to establish databases of the CDS sequence (totally 98716 band ), then use Blastp (Parameter Identity=30%;Evalue 5e-30)to conduct alignment and clustering of similarity of CDS sequence. Next we apply the difference method of set theory to identify CDS cluster which only exist in some strains, then calculate and assess the coverage of CDS cluster. Finally we excavate 21 clusters of CDS clustering which are representatively and exclusively associated with methane metabolism. Through the investigation of protein’s function maker of these clusters in NCIB, we found that among 12 clusters are enzymatic clusters which participate the catalysis in the process of methanation and nitrogen fixation and other 9 clusters are hypothetical protein. Further excavation of the 9 clusters of hypothetical protein by the Blastp’s one by one alignment method, we identify among 4 clusters with potential function and character.