Rescuing discarded spectra: Full comprehensive analysis of a minimal proteome

peer-reviewed · PROTEOMICS · 2016

peer-reviewed · PROTEOMICS · 2016. Maria Lluch‐Senar et al. A common problem encountered when performing large-scale MS proteome analysis is the loss of information due…
Date 2016-02-01
Type peer-reviewed
Venue PROTEOMICS
Publisher Wiley
Contribution downstream-application
DOI 10.1002/pmic.201500187
Citations (OpenAlex) 9

Abstract

A common problem encountered when performing large-scale MS proteome analysis is the loss of information due to the high percentage of unassigned spectra. To determine the causes behind this loss we have analyzed the proteome of one of the smallest living bacteria that can be grown axenically, Mycoplasma pneumoniae (729 ORFs). The proteome of M. pneumoniae cells, grown in defined media, was analyzed by MS. An initial search with both Mascot and a species-specific NCBInr database with common contaminants (NCBImpn), resulted in around 79% of the acquired spectra not having an assignment. The percentage of non-assigned spectra was reduced to 27% after re-analysis of the data with the PEAKS software, thereby increasing the proteome coverage of M. pneumoniae from the initial 60% to over 76%. Nonetheless, 33,413 spectra with assigned amino acid sequences could not be mapped to any NCBInr database protein sequence. Approximately, 1% of these unassigned peptides corresponded to PTMs and 4% to M. pneumoniae protein variants (deamidation and translation inaccuracies). The most abundant peptide sequence variants (Phe-Tyr and Ala-Ser) could be explained by alterations in the editing capacity of the corresponding tRNA synthases. About another 1% of the peptides not associated to any protein had repetitions of the same aromatic/hydrophobic amino acid at the N-terminus, or had Arg/Lys at the C-terminus. Thus, in a model system, we have maximized the number of assigned spectra to 73% (51,453 out of the 70,040 initial acquired spectra). All MS data have been deposited in the ProteomeXchange with identifier PXD002779 (http://proteomecentral.proteomexchange.org/dataset/PXD002779).

Authors

  1. Maria Lluch‐Senar · Centre for Genomic Regulation, European Molecular Biology Laboratory, Universitat Pompeu Fabra
  2. Francesco M. Mancuso · Centre for Genomic Regulation, Universitat Pompeu Fabra, Vall d’Hebron Institute of Oncology
  3. Héctor Climente‐González · Centre for Genomic Regulation, European Molecular Biology Laboratory, Universitat Pompeu Fabra
  4. Marcia I. Peña‐Paz · Centre for Genomic Regulation, Universitat Pompeu Fabra
  5. Eduard Sabidó · Barcelona Institute of Science and Technology, Centre for Genomic Regulation, Universitat Pompeu Fabra, University Pompeu Fabra
  6. Luis Serrano · Centre for Genomic Regulation, European Molecular Biology Laboratory, Institució Catalana de Recerca i Estudis Avançats, Universitat Pompeu Fabra

Methods and tools

Methods it uses

  • PEAKS: Commercial DP-based de novo
  • SPIDER: Protein identification from sequence tags while accounting for de novo sequencing error.

Data deposited

  • Rescuing discarded spectra: Full comprehensive analysis of a minimal proteome — as deposited · PXD002779

Cites (1)

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