Template Proteogenomics: Sequencing Whole Proteins Using an Imperfect Database
peer-reviewed · Molecular & Cellular Proteomics · 2010
| Date | 2010-06-01 |
| Type | peer-reviewed |
| Venue | Molecular & Cellular Proteomics |
| Publisher | Elsevier BV |
| Contribution | adjacent |
| DOI | 10.1074/mcp.m900504-mcp200 |
| Citations (OpenAlex) | 49 |
| Venue 2-year citedness | 4.69 |
Abstract
Database search algorithms are the primary workhorses for the identification of tandem mass spectra. However, these methods are limited to the identification of spectra for which peptides are present in the database, preventing the identification of peptides from mutated or alternatively spliced sequences. A variety of methods has been developed to search a spectrum against a sequence allowing for variations. Some tools determine the sequence of the homologous protein in the related species but do not report the peptide in the target organism. Other tools consider variations, including modifications and mutations, in reconstructing the target sequence. However, these tools will not work if the template (homologous peptide) is missing in the database, and they do not attempt to reconstruct the entire protein target sequence. De novo identification of peptide sequences is another possibility, because it does not require a protein database. However, the lack of database reduces the accuracy. We present a novel proteogenomic approach, GenoMS, that draws on the strengths of database and de novo peptide identification methods. Protein sequence templates (i.e. proteins or genomic sequences that are similar to the target protein) are identified using the database search tool InsPecT. The templates are then used to recruit, align, and de novo sequence regions of the target protein that have diverged from the database or are missing. We used GenoMS to reconstruct the full sequence of an antibody by using spectra acquired from multiple digests using different proteases. Antibodies are a prime example of proteins that confound standard database identification techniques. The mature antibody genes result from large-scale genome rearrangements with flexible fusion boundaries and somatic hypermutation. Using GenoMS we automatically reconstruct the complete sequences of two immunoglobulin chains with accuracy greater than 98% using a diverged protein database. Using the genome as the template, we achieve accuracy exceeding 97%.
Methods and tools
- Template proteogenomics: Reconstructs full target protein sequences, including mutations, from MS/MS spectra by using a homologous protein as a template where the database is imperfect.
Cites (10)
- Automated protein (re)sequencing with MS/MS and a homologous database yields almost full coverage and accuracy (2009) both
- Automated de novo protein sequencing of monoclonal antibodies (2008) both
- Shotgun Protein Sequencing: Assembly of Peptide Tandem Mass Spectra from Mixtures of Modified Proteins (2007) both
- InsPecT: Identification of Posttranslationally Modified Peptides from Tandem Mass Spectra (2005) both
- SPIDER: software for protein identification from sequence tags with de novo sequencing error (2005) crossref
- Identification of Protein Modifications Using MS/MS de Novo Sequencing and the OpenSea Alignment Algorithm (2005) both
- PepNovo: de novo peptide sequencing via probabilistic network modeling (2005) both
- PEAKS: powerful software for peptide de novo sequencing by tandem mass spectrometry (2003) crossref
- Charting the Proteomes of Organisms with Unsequenced Genomes by MALDI-Quadrupole Time-of-Flight Mass Spectrometry and BLAST Homology Searching (2001) both
- De novo peptide sequencing via tandem mass spectrometry (1999) both
Cited by (18)
- De Novo Sequencing of Peptides from Tandem Mass Spectra and Applications in Proteogenomics (2024) crossref
- A perspective toward mass spectrometry-based de novo sequencing of endogenous antibodies (2022) both
- Template-Assisted De Novo Sequencing of SARS-CoV-2 and Influenza Monoclonal Antibodies by Mass Spectrometry (2022) crossref
- Protein de novo sequencing by top-down and middle-down MS/MS: Limitations imposed by mass measurement accuracy and gaps in sequence coverage (2018) crossref
- De Novo Sequencing of Proteins and Peptides: Algorithms, Applications, Perspectives (2018) crossref
- Automated Antibody De Novo Sequencing and Its Utility in Biopharmaceutical Discovery (2017) both
- De Novo Sequencing of Top-Down Tandem Mass Spectra: A Next Step towards Retrieving a Complete Protein Sequence (2017) both
- Ultrahigh‐resolution Fourier transform ion cyclotron resonance mass spectrometry and tandem mass spectrometry for peptide de novo amino acid sequencing for a seven‐protein mixture by paired single‐residue transposed Lys‐N and Lys‐C digestion (2017) crossref
- De Novo MS/MS Sequencing of Native Human Antibodies (2017) both
- Tandem Mass Spectrum Sequencing: An Alternative to Database Search Engines in Shotgun Proteomics (2016) crossref
- Top-down analysis of protein samples by de novo sequencing techniques (2016) crossref
- Complete De Novo Assembly of Monoclonal Antibody Sequences (2016) both
- Combining phage display with de novo protein sequencing for reverse engineering of monoclonal antibodies (2016) both
- De Novo Sequencing of Peptides from Top-Down Tandem Mass Spectra (2015) crossref
- Sequencing-Grade De novo Analysis of MS/MS Triplets (CID/HCD/ETD) From Overlapping Peptides (2013) both
- Shotgun Protein Sequencing with Meta-contig Assembly (2012) both
- The spectral networks paradigm in high throughput mass spectrometry (2012) both
- Resurrection of a clinical antibody: Template proteogenomic de novo proteomic sequencing and reverse engineering of an anti‐lymphotoxin‐α antibody (2011) both