A standardized framing for reporting protein identifications in mzIdentML 1.2.

Inferring which protein species have been detected in bottom-up proteomics experiments has been a challenging problem for which solutions have been maturing over the past decade. While many inference approaches now function well in isolation, comparing and reconciling the results generated across different tools remains difficult. It presently stands as one of the greatest barriers in collaborative efforts such as the Human Proteome Project and public repositories such as the PRoteomics IDEntifications (PRIDE) database. Here we present a framework for reporting protein identifications that seeks to improve capabilities for comparing results generated by different inference tools. This framework standardizes the terminology for describing protein identification results, associated with the HUPO-Proteomics Standards Initiative (PSI) mzIdentML standard, while still allowing for differing methodologies to reach that final state. It is proposed that developers of software for reporting identification results will adopt this terminology in their outputs. While the new terminology does not require any changes to the core mzIdentML model, it represents a significant change in practice, and, as such, the rules will be released via a new version of the mzIdentML specification (version 1.2) so that consumers of files are able to determine whether the new guidelines have been adopted by export software.

Proteome informatics research group (iPRG)_2012: a study on detecting modified peptides in a complex mixture.

The proteome informatics research group of the Association of Biomolecular Resource Facilities conducted a study to assess the community's ability to detect and characterize peptides bearing a range of biologically occurring post-translational modifications when present in a complex peptide background. A data set derived from a mixture of synthetic peptides with biologically occurring modifications combined with a yeast whole cell lysate as background was distributed to a large group of researchers and their results were collectively analyzed. The results from the twenty-four participants, who represented a broad spectrum of experience levels with this type of data analysis, produced several important observations. First, there is significantly more variability in the ability to assess whether a results is significant than there is to determine the correct answer. Second, labile post-translational modifications, particularly tyrosine sulfation, present a challenge for most researchers. Finally, for modification site localization there are many tools being employed, but researchers are currently unsure of the reliability of the results these programs are producing.

Response to: the problem with peptide presumption and low Mascot scoring.

A letter published in January 2011, "The Problem with Peptide Presumption and Low Mascot Scoring", raised concerns about the reporting of peptide identifications based on mass spectrometry data with high precursor mass accuracy. We explain why we believe these concerns are unfounded.

Protein identification using MS/MS data.

The subject of this tutorial is protein identification and characterisation by database searching of MS/MS Data. Peptide Mass Fingerprinting is excluded because it is covered in a separate tutorial. Practical aspects of database searching are emphasised, such as choice of sequence database, effect of mass tolerance, and how to identify post-translational modifications. The relationship between sensitivity and specificity is discussed, as is the challenge of using peptide match information to infer which proteins were present in the sample. Since these tutorials are introductory in nature, most references are to reviews, rather than primary research papers. Some familiarity with mass spectrometry and protein chemistry is assumed. There is an accompanying slide presentation, including speaker notes, and a collection of web-based, practical exercises, designed to reinforce key points. This Tutorial is part of the International Proteomics Tutorial Programme (IPTP 6).

Hierarchical clustering of shotgun proteomics data.

A new result report for Mascot search results is described. A greedy set cover algorithm is used to create a minimal set of proteins, which is then grouped into families on the basis of shared peptide matches. Protein families with multiple members are represented by dendrograms, generated by hierarchical clustering using the score of the nonshared peptide matches as a distance metric. The peptide matches to the proteins in a family can be compared side by side to assess the experimental evidence for each protein. If the evidence for a particular family member is considered inadequate, the dendrogram can be cut to reduce the number of distinct family members.

Biomolecular characterization and protein sequences of the Campanian hadrosaur B. canadensis.

Molecular preservation in non-avian dinosaurs is controversial. We present multiple lines of evidence that endogenous proteinaceous material is preserved in bone fragments and soft tissues from an 80-million-year-old Campanian hadrosaur, Brachylophosaurus canadensis [Museum of the Rockies (MOR) 2598]. Microstructural and immunological data are consistent with preservation of multiple bone matrix and vessel proteins, and phylogenetic analyses of Brachylophosaurus collagen sequenced by mass spectrometry robustly support the bird-dinosaur clade, consistent with an endogenous source for these collagen peptides. These data complement earlier results from Tyrannosaurus rex (MOR 1125) and confirm that molecular preservation in Cretaceous dinosaurs is not a unique event.

Unimod: Protein modifications for mass spectrometry.

Unimod is a database of protein modifications for use in mass spectrometry applications, especially protein identification and de novo sequencing. It contains accurate and verifiable values, derived from elemental compositions, for the mass differences introduced by both natural and artificial modifications.

Error tolerant searching of uninterpreted tandem mass spectrometry data.

An error tolerant mode for database matching of uninterpreted tandem mass spectrometry data is described. Selected database entries are searched without enzyme specificity, using a comprehensive list of chemical and post-translational modifications, together with a residue substitution matrix. The modifications are tested serially, to avoid the catastrophic loss of discrimination that would occur if all the permutations of large numbers of modifications in combination were possible. The new mode has been coded as an extension to the Mascot search engine, and tested against a number of Liquid chromatography-tandem mass spectrometry datasets. The results show a number of additional peptide matches, but require careful interpretation. The most significant limitation of this approach is that it can only reveal new matches to proteins that already have at least one significant peptide match.