Multi-species Identification of Polymorphic Peptide Variants via Propagation in Spectral Networks.
Peptide and protein identification remains challenging in organisms with poorly annotated or rapidly evolving genomes, as are commonly encountered in environmental or biofuels research. Such limitations render tandem mass spectrometry (MS/MS) database search algorithms ineffective as they lack corresponding sequences required for peptide-spectrum matching. We address this challenge with the spectral networks approach to (1) match spectra of orthologous peptides across multiple related species and then (2) propagate peptide annotations from identified to unidentified spectra. We here present algorithms to assess the statistical significance of spectral alignments (Align-GF), reduce the impurity in spectral networks, and accurately estimate the error rate in propagated identifications. Analyzing three related Cyanothece species, a model organism for biohydrogen production, spectral networks identified peptides from highly divergent sequences from networks with dozens of variant peptides, including thousands of peptides in species lacking a sequenced genome. Our analysis further detected the presence of many novel putative peptides even in genomically characterized species, thus suggesting the possibility of gaps in our understanding of their proteomic and genomic expression. A web-based pipeline for spectral networks analysis is available at http://proteomics.ucsd.edu/software.
From the ‡Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, California, 92093.|§Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, California, 92093.
Seungjin
0000-0002-5159-2048
S
Na
¶Pacific Northwest National Laboratory, Richland, Washington 99354.
Samuel H
0000-0002-8351-1994
SH
Payne
From the ‡Dept. of Computer Science and Engineering, University of California, San Diego, La Jolla, California, 92093; bandeira@ucsd.edu.|§Center for Computational Mass Spectrometry, University of California, San Diego, La Jolla, California, 92093.|‖Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California, San Diego, La Jolla, California, 92093.
Nuno
N
Bandeira
D000465:Algorithms; D001426:Bacterial Proteins / Q000378:metabolism; D016000:Cluster Analysis; D046889:Cyanothece / Q000145:classification / Q000378:metabolism*; D030562:Databases, Protein; D016680:Genome, Bacterial; D010455:Peptides / Q000032:analysis*; D040901:Proteomics / Q000379:methods*; D020539:Sequence Analysis, Protein; D012984:Software; D053719:Tandem Mass Spectrometry / Q000379:methods
D001426:Bacterial Proteins; D010455:Peptides