Takabayashi Atsushi, Takabayashi Saeka, Takahashi Kaori, Watanabe Mai, Uchida Hiroko, Murakami Akio, Fujita Tomomichi, Ikeuchi Masahiko, Tanaka Ayumi
Institute of Low Temperature Science, Hokkaido University, Kita-ku, Sapporo, Japan.
CREST, JST, Kita-ku, Sapporo, Japan.
Plant Cell Physiol. 2017 Jan 1;58(1):e10. doi: 10.1093/pcp/pcw219.
The identification of protein complexes is important for the understanding of protein structure and function and the regulation of cellular processes. We used blue-native PAGE and tandem mass spectrometry to identify protein complexes systematically, and built a web database, the protein co-migration database (PCoM-DB, http://pcomdb.lowtem.hokudai.ac.jp/proteins/top), to provide prediction tools for protein complexes. PCoM-DB provides migration profiles for any given protein of interest, and allows users to compare them with migration profiles of other proteins, showing the oligomeric states of proteins and thus identifying potential interaction partners. The initial version of PCoM-DB (launched in January 2013) included protein complex data for Synechocystis whole cells and Arabidopsis thaliana thylakoid membranes. Here we report PCoM-DB version 2.0, which includes new data sets and analytical tools. Additional data are included from whole cells of the pelagic marine picocyanobacterium Prochlorococcus marinus, the thermophilic cyanobacterium Thermosynechococcus elongatus, the unicellular green alga Chlamydomonas reinhardtii and the bryophyte Physcomitrella patens. The Arabidopsis protein data now include data for intact mitochondria, intact chloroplasts, chloroplast stroma and chloroplast envelopes. The new tools comprise a multiple-protein search form and a heat map viewer for protein migration profiles. Users can compare migration profiles of a protein of interest among different organelles or compare migration profiles among different proteins within the same sample. For Arabidopsis proteins, users can compare migration profiles of a protein of interest with putative homologous proteins from non-Arabidopsis organisms. The updated PCoM-DB will help researchers find novel protein complexes and estimate their evolutionary changes in the green lineage.
蛋白质复合物的鉴定对于理解蛋白质结构与功能以及细胞过程的调控至关重要。我们使用蓝色非变性聚丙烯酰胺凝胶电泳和串联质谱系统地鉴定蛋白质复合物，并构建了一个网络数据库——蛋白质共迁移数据库（PCoM-DB，http://pcomdb.lowtem.hokudai.ac.jp/proteins/top），以提供蛋白质复合物的预测工具。PCoM-DB提供任何给定感兴趣蛋白质的迁移图谱，并允许用户将其与其他蛋白质的迁移图谱进行比较，显示蛋白质的寡聚状态，从而识别潜在的相互作用伙伴。PCoM-DB的初始版本（于2013年1月推出）包括集胞藻全细胞和拟南芥类囊体膜的蛋白质复合物数据。在此，我们报告PCoM-DB 2.0版本，它包括新的数据集和分析工具。额外的数据来自海洋浮游蓝细菌聚球藻、嗜热蓝细菌嗜热栖热菌、单细胞绿藻莱茵衣藻和苔藓植物小立碗藓的全细胞。拟南芥蛋白质数据现在包括完整线粒体、完整叶绿体、叶绿体基质和叶绿体被膜的数据。新工具包括一个多蛋白搜索表单和一个用于蛋白质迁移图谱的热图查看器。用户可以比较感兴趣蛋白质在不同细胞器之间的迁移图谱，或比较同一样本中不同蛋白质之间的迁移图谱。对于拟南芥蛋白质，用户可以将感兴趣蛋白质的迁移图谱与来自非拟南芥生物的假定同源蛋白质进行比较。更新后的PCoM-DB将帮助研究人员发现新的蛋白质复合物，并估计它们在绿色谱系中的进化变化。
