Search PubMed⌕ Search

Biomedical subjects

Toshiaki Isobe

Publications and source records attributed to Toshiaki Isobe.

38 records · Page 3Linked to original sources

Large-scale identification of Caenorhabditis elegans proteins by multidimensional liquid chromatography-tandem mass spectrometry.

A proteome of a model organism, Caenorhabditis elegans, was analyzed by an integrated liquid chromatography (LC)-based protein identification system, which was constructed by microscale two-dimensional liquid chromatography (2DLC) coupled with electrospray ionization (ESI) tandem mass spectrometry (MS/MS) on a high-resolution hybrid mass spectrometer with an automated data analysis system. Soluble and insoluble protein fractions were prepared from a mixed growth phase culture of the worm C. elegans, digested with trypsin, and fractionated separately on the 2DLC system. The separated peptides were directly analyzed by on-line ESI-MS/MS in a data-dependent mode, and the resultant spectral data were automatically processed to search a genome sequence database, wormpep 66, for protein identification. The total number of proteins of the composite proteome identified in this method was 1,616, including 110 secreted/targeted proteins and 242 transmembrane proteins. The codon adaptation indices of the identified proteins suggested that the system could identify proteins of relatively low abundance, which are difficult to identify by conventional 2D-gel electrophoresis (GE) followed by an offline mass spectrometric analysis such as peptide mass fingerprinting. Among the approximately 5,400 peptides assigned in this study, many peptides with post-translational modifications, such as N-terminal acetylation and phosphorylation, were detected. This expression profile of C. elegans, containing 571 hypothetical gene products, will serve as the basic data of a major proteome set expressed in the worm.

Animals↗

STEM: a software tool for large-scale proteomic data analyses.

We describe the software, STEM (STrategic Extractor for Mascot's results), which efficiently processes large-scale mass spectrometry-based proteomics data. V (View)-mode evaluates the Mascot peptide identification dataset, removes unreliable candidates and redundant assignments, and integrates the results with key information in the experiment. C (Comparison)-mode compares peptide coverage among multiple datasets and displays proteins commonly/specifically found therein, and processes data for quantitative studies that utilize conventional isotope tags or tags having a smaller mass difference. STEM significantly improves throughput of proteomics study.

Algorithms↗