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Poster Presentations
Day 3, June 24（Tue.）
Room P (Maesato East, Foyer, Ocean Wing)
- 3P-AM-36
Evaluation of Analytical Software Suitable for Metaproteome Analysis
(Kitasato Univ.)
oRyota Fukumoto, Yoshio Kodera, Shin Kawano
Metaproteome analysis helps understand microbial communities by identifying proteins from environmental samples using mass spectrometry. This approach reveals species composition, functions, and metabolic pathways in the community. However, data complexity and interpretation difficulties due to similar proteins require improving processing methods. In this study, we analyzed metaproteome data (PXD010754) from the Japanese intestinal microbiota using MGnify as a reference database. Analyses with MetaLab MAG and MaxQuant mainly focused on protein identification rates. The MetaLab MAG analysis revealed the species distribution and functional distribution. The presence of Prevotella and Blautia, which are key intestinal bacteria, suggests accurate identification of intestinal bacteria. Functional classification of proteins using COG identified many proteins related to carbohydrate and energy metabolism, aligning with intestinal bacterial functions. Currently, we are analyzing data with MaxQuant. By comparing species distribution, protein identification rates, and functional classifications, we will evaluate both software performances for metaproteome analysis.