Assessing Protein Sequence Database Suitability Using De Novo Sequencing

The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is derived from multiple organisms poses two key questions. The first is whether the proteomic data obtained from an unusual sample type even contains peptide tandem mass spectra. The second question is whether an appropriate protein sequence database is available for proteomic searches. We describe the use of automated de novo sequencing for evaluating both the quality of a collection of tandem mass spectra and the suitability of a given protein sequence database for searching that data. Applications of this method include the proteome analysis of closely related species, metaproteomics, and proteomics of extinct organisms. The analysis of samples from unsequenced and/or understudied species as well as samples where the proteome is derived from multiple organisms poses two key questions. The first is whether the proteomic data obtained from an unusual sample type even contains peptide tandem mass spectra. The second question is whether an appropriate protein sequence database is available for proteomic searches. We describe the use of automated de novo sequencing for evaluating both the quality of a collection of tandem mass spectra and the suitability of a given protein sequence database for searching that data. Applications of this method include the proteome analysis of closely related species, metaproteomics, and proteomics of extinct organisms. Matching tandem mass spectra to database-derived sequences is routine, and a variety of software pipelines are available (1Eng J.K. Searle B.C. Clauser K.R. Tabb D.L. A face in the crowd: recognizing peptides through database search.Mol. Cell. Proteomics. 2011; 10: 1-9Abstract Full Text Full Text PDF Scopus (126) Google Scholar). However, atypical and new types of samples can be problematic. For example, it can be difficult to evaluate sample preparation methods using LCMS/MS data from fossils, soil, or glacial meltwaters, when such samples are new to the research community, DNA is unattainable, or there is no obvious protein database to search. If the genome of the organism under study is unknown, or if the sample comes from multiple unknown species (i.e. metaproteomics) the suitability of a chosen sequence database can be difficult to evaluate (2Timmins-Schiffman E. May D.H. Mikan M. Riffle M. Frazar C. Harvey H.R. Noble W.S. Nunn B.L. Critical decisions in metaproteomics: Achieving high confidence protein annotations in a sea of unknowns.ISME J. 2017; 11: 309-314Crossref PubMed Scopus (53) Google Scholar). In the case of species whose genomes are unsequenced, data analysis typically employs a protein sequence database from a taxonomically related species, where the hope is that the sequences are mostly identical (3Cilia M. Tamborindeguy C. Rolland M. Howe K. Thannhauser T.W. Gray S. Tangible benefits of the aphid Acyrthosiphon pisum genome sequencing for aphid proteomics: Enhancements in protein identification and data validation for homology-based proteomics.J. Insect Physiol. 2011; 57: 179-190Crossref PubMed Scopus (15) Google Scholar). For metaproteomics, the standard approach is to sequence the DNA in the sample, assemble a metagenome, and translate it into protein sequences as a FASTA formatted file (4Ruggles K.V. Krug K. Wang X. Clauser K.R. Wang J. Payne S.H. Fenyo D. Zhang B. Mani D.R. Methods, tools and current perspectives in proteogenomics.Mol. Cell. Proteomics. 2017; 16: 959-981Abstract Full Text Full Text PDF PubMed Scopus (88) Google Scholar). The hope is that there are no mistakes in assembly and translation to protein sequence, and that the translated metagenome accurately represents the metaproteome under study. Once a FASTA file is created, a database search is performed and the number of identifications is reported, yet it is not clear how many high-quality tandem mass spectra failed to make a match because the peptide sequence was not represented in the FASTA file. If there is more than one sequence database to choose from (e.g. because of different gene assembly methods), the one with the largest number of identifications over a range of false discovery rates is the optimal choice. Although this is a valid way to proceed, one cannot know if a low number of identifications is because of bad tandem mass spectrometry (MS/MS) 1The abbreviations used are:MS/MStandem mass spectrometryCIDcollision induced dissociationABCammonium bicarbonateDDAdata dependent acquisitionPSMpeptide-spectrum matchFDRfalse discovery rateTPtrue positiveFPfalse positiveFNfalse negativeTICtotal ion currentDIAdata independent acquisition. 1The abbreviations used are:MS/MStandem mass spectrometryCIDcollision induced dissociationABCammonium bicarbonateDDAdata dependent acquisitionPSMpeptide-spectrum matchFDRfalse discovery rateTPtrue positiveFPfalse positiveFNfalse negativeTICtotal ion currentDIAdata independent acquisition. data, an inappropriate or insufficient sequence database, or both. Here we propose and evaluate a simple solution that uses automated de novo sequencing to evaluate both tandem mass spectrum quality and sequence database suitability. tandem mass spectrometry collision induced dissociation ammonium bicarbonate data dependent acquisition peptide-spectrum match false discovery rate true positive false positive false negative total ion current data independent acquisition. tandem mass spectrometry collision induced dissociation ammonium bicarbonate data dependent acquisition peptide-spectrum match false discovery rate true positive false positive false negative total ion current data independent acquisition. De novo sequencing is the concept of deriving a peptide sequence from a tandem mass spectrum without use of a sequence database (5Ma B. Johnson R. De novo sequencing and homology searching.Mol. Cell. Proteomics. 2012; 11: 1-16Abstract Full Text Full Text PDF Scopus (129) Google Scholar). Before the existence of sequence databases (or ready access to powerful computers), de novo sequencing was the only approach to interpret tandem mass spectra of peptides. The degree to which one can successfully derive a sequence is dependent on spectral quality. Specifically, spectra that can be sequenced possess a contiguous series of sequencing ions of the same type (e.g. b- and y-type ions), which turns out to be the case for low energy collision induced dissociation (CID) of peptides. 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May D.H. Mikan M. Riffle M. Frazar C. Harvey H.R. Noble W.S. Nunn B.L. Critical decisions in metaproteomics: Achieving high confidence protein annotations in a sea of unknowns.ISME J. 2017; 11: 309-314Crossref PubMed Scopus (53) Google Scholar). typically are databases only of from or species (e.g. are not to be in one can DNA assemble the into a metagenome, and translate the metagenome sequences to a metaproteome (4Ruggles K.V. Krug K. Wang X. Clauser K.R. Wang J. Payne S.H. Fenyo D. Zhang B. Mani D.R. Methods, tools and current perspectives in proteogenomics.Mol. Cell. Proteomics. 2017; 16: 959-981Abstract Full Text Full Text PDF PubMed Scopus (88) Google Scholar). The assembly of a metagenome from DNA sequence and translation to metaproteome can May D.H. E. Mikan Harvey H.R. E. Nunn B.L. 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