Shotgun protein sequencing: assembly of peptide tandem mass spectra from mixtures of modified proteins.
Despite significant advances in the identification of known proteins, the analysis of unknown proteins by MS/MS still remains a challenging open problem. Although Klaus Biemann recognized the potential of MS/MS for sequencing of unknown proteins in the 1980s, low throughput Edman degradation followed by cloning still remains the main method to sequence unknown proteins. The automated interpretation of MS/MS spectra has been limited by a focus on individual spectra and has not capitalized on the information contained in spectra of overlapping peptides. Indeed the powerful shotgun DNA sequencing strategies have not been extended to automated protein sequencing. We demonstrate, for the first time, the feasibility of automated shotgun protein sequencing of protein mixtures by utilizing MS/MS spectra of overlapping and possibly modified peptides generated via multiple proteases of different specificities. We validate this approach by generating highly accurate de novo reconstructions of multiple regions of various proteins in western diamondback rattlesnake venom. We further argue that shotgun protein sequencing has the potential to overcome the limitations of current protein sequencing approaches and thus catalyze the otherwise impractical applications of proteomics methodologies in studies of unknown proteins.
Bandeira
Nuno
N
Department of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA. bandeira@cs.ucsd.edu
Clauser
Karl R
KR
Pevzner
Pavel A
PA
D000465:Algorithms; D000595:Amino Acid Sequence; D000818:Animals; D003435:Crotalid Venoms / Q000032:analysis*; D017839:Crotalus / Q000378:metabolism; D008969:Molecular Sequence Data; D010455:Peptides / Q000032:analysis*; D020543:Proteome / Q000378:metabolism*; D020539:Sequence Analysis, Protein / Q000379:methods*; D053719:Tandem Mass Spectrometry / Q000379:methods
D003435:Crotalid Venoms; D010455:Peptides; D020543:Proteome