Open-pFind enables precise, comprehensive and rapid peptide identification in shotgun proteomics

Abstract

Shotgun proteomics has grown rapidly in recent decades, but a large fraction of tandem mass spectrometry (MS/MS) data in shotgun proteomics are not successfully identified. We have developed a novel database search algorithm, Open-pFind, to efficiently identify peptides even in an ultra-large search space which takes into account unexpected modifications, amino acid mutations, semi-or non-specific digestion and co-eluting peptides. Tested on two metabolically labeled MS/MS datasets, Open-pFind reported 50.5-117.0% more peptide-spectrum matches (PSMs) than the seven other advanced algorithms. More importantly, the Open-pFind results were more credible judged by the verification experiments using stable isotopic labeling. Tested on four additional large-scale datasets, 70-85% of the spectra were confidently identified, and high-quality spectra were nearly completely interpreted by Open-pFind. Further, Open-pFind was over 40 times faster than the other three open search algorithms and 2-3 times faster than three restricted search algorithms. Re-analysis of an entire human proteome dataset consisting of ~25 million spectra using Open-pFind identified a total of 14,064 proteins encoded by 12,723 genes by requiring at least two uniquely identified peptides. In this search results, Open-pFind also excelled in an independent test for false positives based on the presence or absence of olfactory receptors. Thus, a practical use of the open search strategy has been realized by Open-pFind for the truly global-scale proteomics experiments of today and in the future.

SLM-Transform: A Method for Memory-Efficient Indexing of Spectra for Database Search in LC-MS/MS Proteomics

“…If the search has to be conducted with a number of PTMs and charge states incorporated, it must be done in multiple runs to avoid a crash [23], reported at: https://github.com/chhh/FragPipe/issues/63. A similar issue was also reported by [4] where MSFragger crashed when non-tryptic peptides were included in the search space. This demands for the need of novel methods that can index large number of peptides and corresponding theoretical spectra in a memory-efficient manner as well fast peptide identification.…”

“…Recently, it has been shown [5,15] that the peptide identification rate increases if speactra are searched against wide precursor mass tolerance windows of upto ±500Da (also known as open-search). However, widening the search window to such large tolerances incurs an enormous search time penalty [15,4].…”

“…A number of computational techniques have been developed to quickly reduce the search space by filteringin the peptide sequences that have high likelihood of being matched to a MS/MS spectrum and hence, accelerate the database search. A popular PSM filtering technique is based on sequence-tagging and is employed in [4,18,31,7,28] where a sequence-tag is extracted from the experimental spectra and its k-mers are constructed. The proteome database is filtered prior to digestion using the k-mer tags and the search is conducted only against the protein sequences containing one or more k-mer tags.…”

Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing

“…TagGraph uses an FM-index to filter candidates based on substrings of de novo derived sequences [20]. Finally, Open-pFind combines tag-based filtering to speed up open searches with a subsequent standard search including highly abundant variable modifications in a two-pass strategy [14].…”

Fast open modification spectral library searching through approximate nearest neighbor indexing

“…TagGraph uses an FM-index to lter candidates based on substrings of de novo derived sequences [20]. Finally, Open-pFind combines tag-based ltering to speed up open searches with a subsequent standard search including highly abundant variable modi cations in a two-pass strategy [14].…”