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Fragmentation‐free LC‐MS can identify hundreds of proteins
Author(s) -
Bochet Pascal,
Rügheimer Frank,
Guina Tina,
Brooks Peter,
Goodlett David,
Clote Peter,
Schwikowski Benno
Publication year - 2010
Publication title -
proteomics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.26
H-Index - 167
eISSN - 1615-9861
pISSN - 1615-9853
DOI - 10.1002/pmic.200900765
Subject(s) - fragmentation (computing) , computational biology , computer science , biology , operating system
One of the most common approaches for large‐scale protein identification is LC, followed by MS. If more than a few proteins are to be identified, the additional fragmentation of individual peptides has so far been considered as indispensable, and thus, the associated costs, in terms of instrument time and infrastructure, as unavoidable. Here, we present evidence to the contrary. Using a combination of (i) highly accurate and precise mass measurements, (ii) modern retention time prediction, and (iii) a robust scoring algorithm, we were able to identify 257 proteins of Francisella tularensis from a single LC‐MS experiment in a fragmentation‐free approach (i.e. without experimental fragmentation spectra). This number amounts to 59% of the number of proteins identified in a standard fragmentation‐based approach, when executed with the same false discovery rate. Independent evidence supports at least 27 of a set of 31 proteins that were identified only in the fragmentation‐free approach. Our results suggest that additional developments in retention time prediction, measurement technology, and scoring algorithms may render fragmentation‐free approaches an interesting complement or an alternative to fragmentation‐based approaches.