Towards an automated approach for protein identification in proteome projects

The development of automated, high throughput technologies for the rapid identification of proteins is essential for large‐scale proteome projects. While a degree of automation already exists in some stages of the protein identification process, such as automated acquisition of matrix assisted laser...

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Veröffentlicht in:Electrophoresis 1998-08, Vol.19 (11), p.1941-1949
Hauptverfasser: Traini, Mathew, Gooley, Andrew A., Ou, Keli, Wilkins, Marc R., Tonella, Luisa, Sanchez, Jean-Charles, Hochstrasser, Denis F., Williams, Keith L.
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Sprache:eng
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Zusammenfassung:The development of automated, high throughput technologies for the rapid identification of proteins is essential for large‐scale proteome projects. While a degree of automation already exists in some stages of the protein identification process, such as automated acquisition of matrix assisted laser desorption ionisation — time of flight (MALDI‐TOF) mass spectra, efficient interfaces between different stages are still lacking. We report the development of a highly automated, integrated system for large scale identification of proteins separated by two‐dimensional gel electrophoresis (2‐DE), based on peptide mass fingerprinting. A prototype robotic system was used to image and excise 288 protein spots from an amido black stained polyvinylidene difluoride (PVDF) blot. Protein samples were enzymatically digested with a commercial automated liquid handling system. MALDI‐TOF mass spectrometry was used to acquire mass spectra automatically, and the data analysed with novel automated peptide mass fingerprinting database interrogation software. Using this highly automated system, we were able to identify 95 proteins on the basis of peptide mass fingerprinting, isoelectric point and molecular weight, in a period of less than ten working days. Advantages, problems, and future developments in robotic excision systems, liquid handling, and automated database interrogation software are discussed.
ISSN:0173-0835
1522-2683
DOI:10.1002/elps.1150191112