Shotgun Protein Sequencing with Meta-contig Assembly

Abstract

Full-length de novo sequencing from tandem mass (MS/ MS) spectra of unknown proteins such as antibodies or proteins from organisms with unsequenced genomes remains a challenging open problem. Conventional algorithms designed to individually sequence each MS/MS spectrum are limited by incomplete peptide fragmentation or low signal to noise ratios and tend to result in short de novo sequences at low sequencing accuracy. Our shotgun protein sequencing (SPS) approach was developed to ameliorate these limitations by first finding groups of unidentified spectra from the same peptides (contigs) and then deriving a consensus de novo sequence for each assembled set of spectra (contig sequences). But whereas SPS enables much more accurate reconstruction of de novo sequences longer than can be recovered from individual MS/MS spectra, it still requires error-tolerant matching to homologous proteins to group smaller contig sequences into full-length protein sequences, thus limiting its effectiveness on sequences from poorly annotated proteins. Using low and high resolution CID and high resolution HCD MS/MS spectra, we address this limitation with a Meta-SPS algorithm designed to overlap and further assemble SPS contigs into Meta-SPS de novo contig sequences extending as long as 100 amino acids at over 97% accuracy without requiring any knowledge of homologous protein sequences. We demonstrate Meta-SPS using distinct MS/MS data sets obtained with separate enzymatic digestions and discuss how the remaining de novo sequencing limitations relate to MS/MS acquisition settings. Molecular & Cellular Proteomics 11: 10.1074/mcp.M111.015768, 1084-1096, 2012.Database search tools, such as Sequest (3), Mascot (4), and InsPecT (5), are the most frequently used methods for reliable protein identification in tandem mass (MS/MS) spectrometry based proteomics. These operate by separately matching each MS/MS spectrum to peptide sequences from reference protein databases where all proteins of interest are presumably contained. But this assumption often does not hold true as many important proteins, such as monoclonal antibodies, are not contained in any database because mechanisms of antibody variation (including genetic recombination and somatic hypermutation (6)) constantly create new proteins with novel unique sequences. These mechanisms of variation are the foundation of adaptive immune systems and have enabled highly successful antibody-based therapeutic strategies (7,8). Nevertheless, such variation also means that antibody MS/MS spectra are typically impossible to identify via standard database search techniques whenever the corresponding sequences are not known in advance. An inherent drawback of database search strategies is that they are only as good as the database(s) being searched and incomplete databases often result in proteins being misidentified or left unidentified (9).Despite the importance of novel protein identification, few high-throughput methods have been developed for de novo sequencing of unknown proteins. Low-through...

Ecological venomics: How genomics, transcriptomics and proteomics can shed new light on the ecology and evolution of venom

“…These methods may well be effective for simple spectra, derived from short peptides, yet they are still inadequate for the analysis of spectra derived from larger peptides and proteins. This is not to say that de-novo sequencing has no future in Top-Down proteomics; though still in development, multiple publications have presented some promise for Top-Down proteomics, either through a combination of Bottom-Up and Top-Down data[147,148] or through a constrained approach [149] that requires a sequence "anchor" from which the de-novo algorithm works.Despite its limitations Top-Down proteomics, either in its more "primitive form" or the modern one, provided an immensely important finding about venom biology: the understanding that venom production and secretion is not monolithic and uniform, but rather a complex mixture whose composition is susceptible to biochemical and behavioral modulation.Studies have hinted of this phenomenon in scorpions [17, 103], snake [150] and cone snails [16, 123, 151]. It is still…”

Neutron-encoded Signatures Enable Product Ion Annotation From Tandem Mass Spectra

“…Remaining peaks not predicted to be y-ions were converted to charge one by a previously described MS/MS deconvolution tool (38). Deconvoluted DTA spectra that originated from identified MS/MS scans were then paired with the MSGF ϩ peptide IDs and passed to PepNovo ϩ for training.…”

The Generating Function Approach for Peptide Identification in Spectral Networks

“…Yet, recent advances in de novo sequencing have demonstrated 97-99% sequencing accuracy (percent of amino acids in matched peptides that are correct) at nearly the same level of coverage (percent of amino acids in target peptides that were matched) as that of database search for small mixtures of target proteins (Guthals et al, 2012a(Guthals et al, , 2013. At the heart of this approach is the pairing of spectra from overlapping peptides (i.e., peptides that have overlapping sequences) to construct spectral networks (Bandeira et al, 2004;Guthals et al, 2012b) where a node represents an individual spectrum [or a consensus spectrum from a clustered set of spectra from the same precursor (Frank et al, 2008)] and edges denote pairs of spectra from peptides with overlapping sequences.…”

“…At the heart of this approach is the pairing of spectra from overlapping peptides (i.e., peptides that have overlapping sequences) to construct spectral networks (Bandeira et al, 2004;Guthals et al, 2012b) where a node represents an individual spectrum [or a consensus spectrum from a clustered set of spectra from the same precursor (Frank et al, 2008)] and edges denote pairs of spectra from peptides with overlapping sequences. It is then shown that de novo sequences assembled by simultaneous interpretation of multiple spectra from overlapping peptides are much more accurate than individual per-spectrum interpretations (Guthals et al, 2012a(Guthals et al, , 2013. Use of multiple enzyme digestions and strong cation exchange (SCX) (Edelmann, 2011) fractionation is becoming more common in MS/MS protocols to generate broader coverage of protein sequences and yield wider distributions of overlapping peptides, but current statistical methods still ignore the peptide sequence overlaps and separately compute the significance of individual peptides matched to individual spectra (Swaney et al, 2010).…”