Homology-Driven Proteomics of Dinoflagellates with Unsequenced Genomes UsingMALDI-TOF/TOF and Automated De NovoSequencing
This study developed a multilayered, gel-based, and underivatized strategy for de novo protein sequence analysis of unsequenced dinoflagellates using a MALDI-TOF/TOF mass spectrometer with the assistance of DeNovo Explorer software. MASCOT was applied as the first layer screen to identify either known or unknown proteins sharing identical peptides presented in a database. Once the confident identifications were removed after searching against the NCBInr database, the remainder was searched against the dinoflagellate expressed sequence tag database. In the last layer, those borderline and nonconfident hits were further subjected to de novo interpretation using DeNovo Explorer software. The de novo sequences passing a reliability filter were subsequently submitted to nonredundant MS-BLAST search. Using this layer identificationmethod, 216 protein spots representing 158 unique proteins out of 220 selected protein spots from Alexandrium tamarense, a dinoflagellate with unsequenced genome, were confidently or tentatively identified by database searching. These proteins were involved in various intracellular physiological activities. This study is the first e.ort to develop a completely automated approach to identify proteins from unsequenced dinoflagellate databases and establishes a preliminary protein database for various physiological studies of dinoflagellates in the future.
Da-ZhiWang Cheng Li Zhang-Xian Xie Hong-Po Dong Lin Lin Hua-Sheng Hong
State Key Laboratory of Marine Environmental Science/Environmental Science Research Center, Xiamen University, Xiamen 361005, China
国际会议
青岛
英文
1-16
2010-10-09（万方平台首次上网日期，不代表论文的发表时间）