Measuring proteomes with long strings: A new, unconstrained paradigm in mass spectrum interpretation

Abstract

12Thousands of protein post-translational modifications (PTMs) dynamically impact nearly all 13 cellular functions. Mass spectrometry is well suited to PTM identification, but proteome-scale 14 analyses are biased towards PTMs with existing enrichment methods. To measure the full 15 landscape of PTM regulation, software must overcome two fundamental challenges: intractably 16 large search spaces and difficulty distinguishing correct from incorrect identifications. Here, we 17 describe TagGraph, software that overcomes both challenges with a string-based search 18 method orders of magnitude faster than current approaches, and probabilistic validation model 19 optimized for PTM assignments. When applied to a human proteome map, TagGraph tripled 20 confident identifications while revealing thousands of modification types on nearly one million 21 sites spanning the proteome. We expand known sites by orders of magnitude for highly 22 abundant yet understudied PTMs such as proline hydroxylation, and derive tissue-specific 23 insight into these PTMs' roles. TagGraph expands our ability to survey the full landscape of 24 PTM function and regulation. 25Conventional sequence database search tools cannot identify modified peptides unless they are 44 first anticipated by the researcher [20][21][22] . Search parameters including the number, kind, and 45 frequency of PTMs are usually chosen to strike a difficult compromise: considering larger 46 numbers of PTMs and other sequence variants is necessary for their identification, but doing so 47 exponentially increases the time needed to interpret MS/MS datasets, and decreases the ability 48 to distinguish correct from incorrect assignments 23 . To partially address this compromise, 49 strategies have been proposed to constrain the number of proteins being searched, protease 50 specificity rules, or the allowable types and numbers of PTMs 17,18,[24][25][26] . In practice, these 51 approaches only marginally decrease search times without clearly distinguishing correct from 52 incorrect PTM assignments 27 . Therefore, most have not been demonstrated on large, proteome-53 scale datasets 23 54Here, we describe TagGraph, a powerful computational tool that addresses two principle 55 challenges of searching very large sequence spaces. First, TagGraph leverages accurate de 56 novo mass spectrum interpretations 28,29 to rapidly search millions of possible sequences for a 57 match with an FM-index 30 data structure. This highly efficient search method makes modern 58 next-generation genome sequencing possible 31 , but has not been adapted to proteomics. By 59 combining it with a graph-based string reconciliation algorithm, TagGraph rapidly searches 60 MS/MS datasets without restrictions on number of proteins, PTMs, or protease specificity. This 61 strategy achieves speeds orders of magnitude faster than prior algorithms because it considers 62 exponentially more sequence possibilities without having to explicitly test each one against input 63 spectra. Second, by replacing conventional "ta...

Fast Open Modification Spectral Library Searching through Approximate Nearest Neighbor Indexing

“…Caution has to be observed, however, because the actual FDR might be underestimated when too small groups are used . It is a standing research question whether alternative approaches are needed for the accurate FDR estimation of open searches. , …”

“…PIPI uses sequence tags of length 3 to perform a fuzzy tag-based filtering [68]. 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

“…Caution has to be observed though as the actual FDR might be underestimated when too small groups are used [27]. It is a standing research question whether alternative approaches are needed for the accurate FDR estimation of open searches [20,40].…”

“…PIPI uses sequence tags of length 3 to perform a fuzzy tag-based ltering [68]. 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].…”

BayesENproteomics: Bayesian elastic nets for quantification of proteoforms in complex samples

“…PALM provides a way of compressing information from many protein/proteoform fold changes into fewer annotated pathway fold changes, aiding interpretation of complex, multidimensional datasets. PALM can be used as a standalone pathway analysis tool; although it does assume protein fold changes are formatted according to the BayesENproteomics protein-level output format (see examples on https://github.com/VenkMallikarjun).With the improvement of MS technology, and the production of highly efficient unconstrained searching algorithms(Devabhaktuni et al, 2018; Kong et al, 2017), identification and quantification of increasingly rare PTM'd peptides, and thus their parent proteoforms, has become possible even without enrichment. Many quantification methods have discarded or otherwise diminished the influence of these potentially relevant peptides in bottom-up protein quantification.…”