Stable-isotope-labeled histone peptide library for histone post-translational modification and variant quantification by mass spectrometry.

To facilitate accurate histone variant and post-translational modification (PTM) quantification via mass spectrometry, we present a library of 93 synthetic peptides using Protein-Aqua™ technology. The library contains 55 peptides representing different modified forms from histone H3 peptides, 23 peptides representing H4 peptides, 5 peptides representing canonical H2A peptides, 8 peptides representing H2A.Z peptides, and peptides for both macroH2A and H2A.X. The PTMs on these peptides include lysine mono- (me1), di- (me2), and tri-methylation (me3); lysine acetylation; arginine me1; serine/threonine phosphorylation; and N-terminal acetylation. The library was subjected to chemical derivatization with propionic anhydride, a widely employed protocol for histone peptide quantification. Subsequently, the detection efficiencies were quantified using mass spectrometry extracted ion chromatograms. The library yields a wide spectrum of detection efficiencies, with more than 1700-fold difference between the peptides with the lowest and highest efficiencies. In this paper, we describe the impact of different modifications on peptide detection efficiencies and provide a resource to correct for detection biases among the 93 histone peptides. In brief, there is no correlation between detection efficiency and molecular weight, hydrophobicity, basicity, or modification type. The same types of modifications may have very different effects on detection efficiencies depending on their positions within a peptide. We also observed antagonistic effects between modifications. In a study of mouse trophoblast stem cells, we utilized the detection efficiencies of the peptide library to correct for histone PTM/variant quantification. For most histone peptides examined, the corrected data did not change the biological conclusions but did alter the relative abundance of these peptides. For a low-abundant histone H2A variant, macroH2A, the corrected data led to a different conclusion than the uncorrected data. The peptide library and detection efficiencies presented here may serve as a resource to facilitate studies in the epigenetics and proteomics fields.

Drawbacks in the use of unconventional hydrophobic anhydrides for histone derivatization in bottom-up proteomics PTM analysis.

MS-based proteomics has become the most utilized tool to characterize histone PTMs. Since histones are highly enriched in lysine and arginine residues, lysine derivatization has been developed to prevent the generation of short peptides (<6 residues) during trypsin digestion. One of the most adopted protocols applies propionic anhydride for derivatization. However, the propionyl group is not sufficiently hydrophobic to fully retain the shortest histone peptides in RP LC, and such procedure also hampers the discovery of natural propionylation events. In this work we tested 12 commercially available anhydrides, selected based on their safety and hydrophobicity. Performance was evaluated in terms of yield of the reaction, MS/MS fragmentation efficiency, and drift in retention time using the following samples: (i) a synthetic unmodified histone H3 tail, (ii) synthetic modified histone peptides, and (iii) a histone extract from cell lysate. Results highlighted that seven of the selected anhydrides increased peptide retention time as compared to propionic, and several anhydrides such as benzoic and valeric led to high MS/MS spectra quality. However, propionic anhydride derivatization still resulted, in our opinion, as the best protocol to achieve high MS sensitivity and even ionization efficiency among the analyzed peptides.

Improvements in the Protein Identifier Cross-Reference service.

The Protein Identifier Cross-Reference (PICR) service is a tool that allows users to map protein identifiers, protein sequences and gene identifiers across over 100 different source databases. PICR takes input through an interactive website as well as Representational State Transfer (REST) and Simple Object Access Protocol (SOAP) services. It returns the results as HTML pages, XLS and CSV files. It has been in production since 2007 and has been recently enhanced to add new functionality and increase the number of databases it covers. Protein subsequences can be Basic Local Alignment Search Tool (BLAST) against the UniProt Knowledgebase (UniProtKB) to provide an entry point to the standard PICR mapping algorithm. In addition, gene identifiers from UniProtKB and Ensembl can now be submitted as input or mapped to as output from PICR. We have also implemented a 'best-guess' mapping algorithm for UniProt. In this article, we describe the usefulness of PICR, how these changes have been implemented, and the corresponding additions to the web services. Finally, we explain that the number of source databases covered by PICR has increased from the initial 73 to the current 102. New resources include several new species-specific Ensembl databases as well as the Ensembl Genome ones. PICR can be accessed at http://www.ebi.ac.uk/Tools/picr/.

Analysis of RNA Sequences and Modifications Using NASE.

Mass spectrometry is an ideal method for the discovery and characterization of modified RNAs. Unlike other traditional sequencing methods, mass spectrometry can identify and localize multiple types of modifications in tandem. One of the traditional hurdles to using this powerful technique has been a paucity of software to interpret the complicated data produced by these experiments. Here I describe how to use the NucleicAcidSearchEngine (NASE), a component of OpenMS as well as best practices for acquiring RNA data, and potential pitfalls in the analysis process.

A computational platform for high-throughput analysis of RNA sequences and modifications by mass spectrometry.

The field of epitranscriptomics continues to reveal how post-transcriptional modification of RNA affects a wide variety of biological phenomena. A pivotal challenge in this area is the identification of modified RNA residues within their sequence contexts. Mass spectrometry (MS) offers a comprehensive solution by using analogous approaches to shotgun proteomics. However, software support for the analysis of RNA MS data is inadequate at present and does not allow high-throughput processing. Existing software solutions lack the raw performance and statistical grounding to efficiently handle the numerous modifications found on RNA. We present a free and open-source database search engine for RNA MS data, called NucleicAcidSearchEngine (NASE), that addresses these shortcomings. We demonstrate the capability of NASE to reliably identify a wide range of modified RNA sequences in four original datasets of varying complexity. In human tRNA, we characterize over 20 different modification types simultaneously and find many cases of incomplete modification.