A turn-key approach for large-scale identification of complex posttranslational modifications

Detecting diagnostic features in MS/MS spectra of post-translationally modified peptides

Post-translational modifications are an area of great interest in mass spectrometry-based proteomics, with a surge in methods to detect them in recent years. However, post-translational modifications can introduce complexity into proteomics searches by fragmenting in unexpected ways, ultimately hindering the detection of modified peptides. To address these deficiencies, we present a fully automated method to find diagnostic spectral features for any modification. The features can be incorporated into proteomics search engines to improve modified peptide recovery and localization. We show the utility of this approach by interrogating fragmentation patterns for a cysteine-reactive chemoproteomic probe, RNA-crosslinked peptides, sialic acid-containing glycopeptides, and ADP-ribosylated peptides. We also analyze the interactions between a diagnostic ion's intensity and its statistical properties. This method has been incorporated into the open-search annotation tool PTM-Shepherd and the FragPipe computational platform.

Irreversible oxidative post-translational modifications in heart disease

Introduction: Development of specific biomarkers aiding early diagnosis of heart failure is an ongoing challenge. Biomarkers commonly used in clinical routine usually act as readouts of an already existing acute condition rather than disease initiation. Functional decline of cardiac muscle is greatly aggravated by increased oxidative stress and damage of proteins. Oxidative post-translational modifications occur already at early stages of tissue damage and are thus regarded as potential up-coming disease markers. Areas covered: Clinical practice regarding commonly used biomarkers for heart disease is briefly summarized. The types of oxidative post-translational modification in cardiac pathologies are discussed with a special focus on available quantitative techniques and characteristics of individual modifications with regard to their stability and analytical accessibility. As irreversible oxidative modifications trigger protein degradation pathways or cause protein aggregation, both influencing biomarker abundance, a chapter is dedicated to their regulation in the heart.

Clinically Relevant Post-Translational Modification Analyses-Maturing Workflows and Bioinformatics Tools

Post-translational modifications (PTMs) can occur soon after translation or at any stage in the lifecycle of a given protein, and they may help regulate protein folding, stability, cellular localisation, activity, or the interactions proteins have with other proteins or biomolecular species. PTMs are crucial to our functional understanding of biology, and new quantitative mass spectrometry (MS) and bioinformatics workflows are maturing both in labelled multiplexed and label-free techniques, offering increasing coverage and new opportunities to study human health and disease. Techniques such as Data Independent Acquisition (DIA) are emerging as promising approaches due to their re-mining capability. Many bioinformatics tools have been developed to support the analysis of PTMs by mass spectrometry, from prediction and identifying PTM site assignment, open searches enabling better mining of unassigned mass spectra-many of which likely harbour PTMs-through to understanding PTM associations and interactions. The remaining challenge lies in extracting functional information from clinically relevant PTM studies. This review focuses on canvassing the options and progress of PTM analysis for large quantitative studies, from choosing the platform, through to data analysis, with an emphasis on clinically relevant samples such as plasma and other body fluids, and well-established tools and options for data interpretation.

The kinase TPL2 activates ERK and p38 signaling to promote neutrophilic inflammation

Tumor progression locus 2 (TPL2; also known as MAP3K8) is a mitogen-activated protein kinase (MAPK) kinase kinase (MAP3K) that phosphorylates the MAPK kinases MEK1 and MEK2 (MEK1/2), which, in turn, activate the MAPKs extracellular signal-regulated kinase 1 (ERK1) and ERK2 (ERK1/2) in macrophages stimulated through the interleukin-1 receptor (IL-1R), Toll-like receptors (TLRs), or the tumor necrosis factor receptor (TNFR). We describe a conserved and critical role for TPL2 in mediating the effector functions of neutrophils through the activation of the p38 MAPK signaling pathway. Gene expression profiling and functional studies of neutrophils and monocytes revealed a MEK1/2-independent branch point downstream of TPL2 in neutrophils. Biochemical analyses identified the MAPK kinases MEK3 and MEK6 and the MAPKs p38α and p38δ as downstream effectors of TPL2 in these cells. Genetic ablation of the catalytic activity of TPL2 or therapeutic intervention with a TPL2-specific inhibitor reduced the production of inflammatory mediators by neutrophils in response to stimulation with the TLR4 agonist lipopolysaccharide (LPS) in vitro, as well as in rodent models of inflammatory disease. Together, these data suggest that TPL2 is a drug target that activates not only MEK1/2-dependent but also MEK3/6-dependent signaling to promote inflammatory responses.

Combinatorial approach for large-scale identification of linked peptides from tandem mass spectrometry spectra

The combination of chemical cross-linking and mass spectrometry has recently been shown to constitute a powerful tool for studying protein-protein interactions and elucidating the structure of large protein complexes. However, computational methods for interpreting the complex MS/MS spectra from linked peptides are still in their infancy, making the high-throughput application of this approach largely impractical. Because of the lack of large annotated datasets, most current approaches do not capture the specific fragmentation patterns of linked peptides and therefore are not optimal for the identification of cross-linked peptides. Here we propose a generic approach to address this problem and demonstrate it using disulfide-bridged peptide libraries to (i) efficiently generate large mass spectral reference data for linked peptides at a low cost and (ii) automatically train an algorithm that can efficiently and accurately identify linked peptides from MS/MS spectra. We show that using this approach we were able to identify thousands of MS/MS spectra from disulfide-bridged peptides through comparison with proteome-scale sequence databases and significantly improve the sensitivity of cross-linked peptide identification. This allowed us to identify 60% more direct pairwise interactions between the protein subunits in the 20S proteasome complex than existing tools on cross-linking studies of the proteasome complexes. The basic framework of this approach and the MS/MS reference dataset generated should be valuable resources for the future development of new tools for the identification of linked peptides.