Evidence map›Paper›PMID 22798278›Full record

ArticleMolecular & cellular proteomics : MCP2012

Shotgun protein sequencing with meta-contig assembly.

Adrian Guthals, Karl R Clauser, Nuno Bandeira

Open access · hybridAbstract read
In one paragraph

Article in Molecular & cellular proteomics : MCP, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing papers in PubMed
1.6field-weighted citation impact, top 18% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

18 citing papers in PubMed, 30 citations in OpenAlex.

  1. Review
  2. A Handle on Mass Coincidence Errors inJournal of proteome research · 2024
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Database-independent Protein Sequencing (DiPS) Enables Full-lengthMolecular & cellular proteomics : MCP · 2017
    Article
  8. Methods, Tools and Current Perspectives in Proteogenomics.Molecular & cellular proteomics : MCP · 2017
    Review
  9. De Novo MS/MS Sequencing of Native Human Antibodies.Journal of proteome research · 2017
    Article
  10. Article
  11. Article
  12. The generating function approach for Peptide identification in spectral networks.Journal of computational biology : a journal of computational molecular cell biology · 2015
    Article
  13. Review
  14. Article
  15. Article
  16. Article
  17. Review
  18. Review
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 2 institutions in 1 country.

Adrian GuthalsDepartment of Computer Science and Engineering, University of California San Diego, La Jolla, California 92093, USA. aguthals@cs.ucsd.edu
Karl R Clauser
Nuno Bandeira
University of California, San Diego · USMassachusetts Institute of Technology · US

Funding

Measuring Cancer Biomarker Candidates by Targeted MS and Ab EnrichmentU24CA126476 · NCI · MASSACHUSETTS INSTITUTE OF TECHNOLOGY · PI CARR, STEVEN A · 2006 to 2010
$14.6M
TrainingP41GM103484 · NIGMS · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2012 to 2018
$8.7M
CENTER FOR COMPUTATIONAL MASS-SPECTROMETRYP41RR024851 · NCRR · UNIVERSITY OF CALIFORNIA, SAN DIEGO · PI PEVZNER, PAVEL A · 2008 to 2011
$5.2M
NCI NIH HHS 1U24 CA126476-02NCI NIH HHS U24 CA126476NCRR NIH HHS 1-P41-RR024851NCRR NIH HHS P41 RR024851NIGMS NIH HHS P41 GM103484
6 · The paper itself

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.

Indexed as

AlgorithmsAmino Acid SequenceAnimalsArmoraciaCattleComputational BiologyEscherichia coliHorsesHumansMiceMolecular Sequence DataPeptide FragmentsProteinsReproducibility of ResultsSensitivity and SpecificitySequence Analysis, ProteinPeptide FragmentsProteins

Identifiers

PMID22798278
PMCPMC3494147
OpenAlexW2162443513

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.