Niklaas Colaert

N α -terminal acetylation is one of the most common protein modifications in eukaryotes. The COmbined FRActional DIagonal Chromatography (COFRADIC) proteomics technology that can be specifically used to isolate N-terminal peptides was used to determine the N-terminal acetylation status of 742 human and 379 yeast protein N termini, representing the largest eukaryotic dataset of N-terminal acetylation. The major N-terminal acetyltransferase (NAT), NatA, acts on subclasses of proteins with Ser-, Ala-, Thr-, Gly-, Cys- and Val- N termini. NatA is composed of subunits encoded by y ARD1 and y NAT1 in yeast and h ARD1 and h NAT1 in humans. A yeast ard1 -Δ nat1 -Δ strain was phenotypically complemented by h ARD1 h NAT1 , suggesting that yNatA and hNatA are similar. However, heterologous combinations, h ARD1 y NAT1 and y ARD1 h NAT1 , were not functional in yeast, suggesting significant structural subunit differences between the species. Proteomics of a yeast ard1 -Δ nat1 -Δ strain expressing hNatA demonstrated that hNatA acts on nearly the same set of yeast proteins as yNatA, further revealing that NatA from humans and yeast have identical or nearly identical specificities. Nevertheless, all NatA substrates in yeast were only partially N-acetylated, whereas the corresponding NatA substrates in HeLa cells were mainly completely N-acetylated. Overall, we observed a higher proportion of N-terminally acetylated proteins in humans (84%) as compared with yeast (57%). N-acetylation occurred on approximately one-half of the human proteins with Met-Lys- termini, but did not occur on yeast proteins with such termini. Thus, although we revealed different N-acetylation patterns in yeast and humans, the major NAT, NatA, acetylates the same substrates in both species.

We here present a new method to measure the degree of protein-bound methionine sulfoxide formation at a proteome-wide scale. In human Jurkat cells that were stressed with hydrogen peroxide, over 2000 oxidation-sensitive methionines in more than 1600 different proteins were mapped and their extent of oxidation was quantified. Meta-analysis of the sequences surrounding the oxidized methionine residues revealed a high preference for neighboring polar residues. Using synthetic methionine sulfoxide containing peptides designed according to the observed sequence preferences in the oxidized Jurkat proteome, we discovered that the substrate specificity of the cellular methionine sulfoxide reductases is a major determinant for the steady-state of methionine oxidation. This was supported by a structural modeling of the MsrA catalytic center. Finally, we applied our method onto a serum proteome from a mouse sepsis model and identified 35 in vivo methionine oxidation events in 27 different proteins.

BACKGROUND: The growing interest in the field of proteomics has increased the demand for software tools and applications that process and analyze the resulting data. And even though the purpose of these tools can vary significantly, they usually share a basic set of features, including the handling of protein and peptide sequences, the visualization of (and interaction with) spectra and chromatograms, and the parsing of results from various proteomics search engines. Developers typically spend considerable time and effort implementing these support structures, which detracts from working on the novel aspects of their tool. RESULTS: In order to simplify the development of proteomics tools, we have implemented an open-source support library for computational proteomics, called compomics-utilities. The library contains a broad set of features required for reading, parsing, and analyzing proteomics data. compomics-utilities is already used by a long list of existing software, ensuring library stability and continued support and development. CONCLUSIONS: As a user-friendly, well-documented and open-source library, compomics-utilities greatly simplifies the implementation of the basic features needed in most proteomics tools. Implemented in 100% Java, compomics-utilities is fully portable across platforms and architectures. Our library thus allows the developers to focus on the novel aspects of their tools, rather than on the basic functions, which can contribute substantially to faster development, and better tools for proteomics.