Project description:Using recent developments in sample preparation strategies and improvements in mass spectrometry (MS), an optimized procedure was developed to characterize the proteome of Methylocystis sp. strain SC2, a type II methanotroph. It represents one of the ecologically important groups of methane-oxidizing bacteria. The major challenge for developing an efficient analytical proteomics workflow for methanotrophic bacteria is the high amount of membrane-associated proteins that need to be efficiently solubilized and digested for downstream analysis. Therefore, each step of the workflow, including cell lysis, protein solubilization and digestion, and MS peptide quantification, was assessed and optimized. Our novel crude-lysate-MS approach proved to increase protein quantification accuracy and the proteome coverage of strain SC2. It captured 62% of predicted SC2 proteome, with 10-fold increase in membrane-associated proteins relative to less effective conditions. Use of crude cell lysate for downstream analysis showed not only to be highly efficient for strain SC2 but also for other members of the Methylocystaceae family. To validate the efficiency of our newly developed workflow, we analyzed the SC2 proteome under two contrasting nitrogen conditions, with a focus on the differential expression of proteins involved in methane and nitrogen metabolisms.
Project description:The objective of this study was to assess whether Methylocystis sp. strain SC2, as a representative for Methylocystis spp., can utilize hydrogen to optimize the biomass yield by mixed utilization of CH4 and H2, rather than CH4 as the sole source of energy. Thus, we aimed to show that, in the presence of H2, CH4 will primarily be used for synthesis of cell carbon and increased biomass/protein yield. In particular, we intended to explore those CH4/O2 ratios, which maximize the effect of hydrogen addition on the biomass yield and proteome reconstruction of strain SC2. To achieve our goals, we combined hydrogen-based growth experiments with our recently optimized proteomics workflow.
