Identification of Immune-Responsive Gene 1 (IRG1) as a Target of A20.

A20 is a negative regulator of NF-κB signaling; it controls inflammatory responses and ensures tissue homeostasis. A20 is thought to restrict NF-κB activation both by its ubiquitin-editing activity as well as by its nonenzymatic activities. Besides its role in NF-κB signaling, A20 also acts as a protective factor inhibiting apoptosis and necroptosis. Because of the ability of A20 to both ubiquitinate and deubiquitinate substrates, and its involvement in many cellular processes, we hypothesized that deletion of A20 might generally impact on protein levels, thereby disrupting cellular signaling. We performed a differential proteomics study on bone marrow-derived macrophages (BMDMs) from control and myeloid-specific A20 knockout mice, both in untreated conditions and after LPS or TNF treatment, and demonstrated A20-dependent changes in protein expression. Several inflammatory proteins were found up-regulated in the absence of A20, even without an inflammatory stimulus, but, depending on the treatment and the treatment time, more proteins were found regulated. Together these protein changes may affect normal signaling events, which may disturb tissue homeostasis and induce (autoimmune) inflammation, in agreement with A20s proposed identity as a susceptibility gene for inflammatory disease. We further verify that immune-responsive gene 1 (IRG1) is up-regulated in the absence of A20 and that its levels are transcriptionally regulated.

Intelligent Mixing of Proteomes for Elimination of False Positives in Affinity Purification-Mass Spectrometry.

Protein complexes are essential in all organizational and functional aspects of the cell. Different strategies currently exist for analyzing such protein complexes by mass spectrometry, including affinity purification (AP-MS) and proximal labeling-based strategies. However, the high sensitivity of current mass spectrometers typically results in extensive protein lists mainly consisting of nonspecifically copurified proteins. Finding the true positive interactors in these lists remains highly challenging. Here, we report a powerful design based on differential labeling with stable isotopes combined with nonequal mixing of control and experimental samples to discover bona fide interaction partners in AP-MS experiments. We apply this intelligent mixing of proteomes (iMixPro) concept to overexpression experiments for RAF1, RNF41, and TANK and also to engineered cell lines expressing epitope-tagged endogenous PTPN14, JIP3, and IQGAP1. For all baits, we confirmed known interactions and found a number of novel interactions. The results for RNF41 and TANK were compared to a classical affinity purification experiment, which demonstrated the efficiency and specificity of the iMixPro approach.

Fast profiling of protease specificity reveals similar substrate specificities for cathepsins K, L and S.

Proteases are important effectors of numerous physiological and pathological processes. Reliable determination of a protease's specificity is crucial to understand protease function and to develop activity-based probes and inhibitors. During the last decade, various proteomic approaches for profiling protease substrate specificities were reported. Although most of these approaches can identify up to thousands of substrate cleavage events in a single experiment, they are often time consuming and methodologically challenging as some of these approaches require rather complex sample preparation procedures. For such reasons their application is often limited to those labs that initially introduced them. Here, we report on a fast and simple approach for proteomic profiling of protease specificities (fast profiling of protease specificity (FPPS)), which can be applied to complex protein mixtures. FPPS is based on trideutero-acetylation of novel N-termini generated by the action of proteases and subsequent peptide fractionation on Stage Tips containing ion-exchange and reverse phase chromatographic resins. FPPS can be performed in 2 days and does not require extensive fractionation steps. Using this approach, we have determined the specificity profiles of the cysteine cathepsins K, L and S. We further validated our method by comparing the results with the specificity profiles obtained by the N-terminal combined fractional diagonal chromatography method. This comparison pointed to almost identical substrate specificities for all three cathepsins and confirmed the reliability of the FPPS approach. All MS data have been deposited in the ProteomeXchange with identifiers PXD001536 and PXD001553 (http://proteomecentral.proteomexchange.org/dataset/PXD001536; http://proteomecentral.proteomexchange.org/dataset/PXD001553).

Proteomic data and structure analysis combined reveal interplay of structural rigidity and flexibility on selectivity of cysteine cathepsins.

Addressing the elusive specificity of cysteine cathepsins, which in contrast to caspases and trypsin-like proteases lack strict specificity determining P1 pocket, calls for innovative approaches. Proteomic analysis of cell lysates with human cathepsins K, V, B, L, S, and F identified 30,000 cleavage sites, which we analyzed by software platform SAPS-ESI (Statistical Approach to Peptidyl Substrate-Enzyme Specific Interactions). SAPS-ESI is used to generate clusters and training sets for support vector machine learning. Cleavage site predictions on the SARS-CoV-2 S protein, confirmed experimentally, expose the most probable first cut under physiological conditions and suggested furin-like behavior of cathepsins. Crystal structure analysis of representative peptides in complex with cathepsin V reveals rigid and flexible sites consistent with analysis of proteomics data by SAPS-ESI that correspond to positions with heterogeneous and homogeneous distribution of residues. Thereby support for design of selective cleavable linkers of drug conjugates and drug discovery studies is provided.

A protein-protein interaction map of the TNF-induced NF-κB signal transduction pathway.

Tumor Necrosis Factor (TNF) has a crucial role in inflammation, cell proliferation and cell death. Dysregulation of TNF receptor 1 (TNFR1)-induced Nuclear Factor-kappa B (NF-κB) signaling leads to chronic inflammation and is associated with several human inflammatory pathologies. Hence, TNF neutralization suppresses inflammation and attenuates inflammatory pathology. However, despite its beneficial effects, anti-TNF therapy suffers from efficacy issues and severe immune side effects. There is thus an urging need to identify novel targets for pharmaceutical intervention in the NF-κB signaling pathway. Here, we present a protein-protein interaction dataset of the TNFR1-induced signaling pathway. For this, we used Virotrap, a novel method for studying protein complexes without disrupting the cellular integrity, on 12 central proteins controlling NF-κB and cell death signaling, both under resting conditions as well as upon TNF stimulation. Our dataset reveals dynamic interactions in TNFR1-induced NF-κB signaling and identifies both known as well as novel interactors that may help to further unravel the molecular mechanisms steering TNF-induced inflammatory signaling and pathology.

Analyzing trapped protein complexes by Virotrap and SFINX.

The analysis of protein interaction networks is one of the key challenges in the study of biology. It connects genotypes to phenotypes, and disruption of such networks is associated with many pathologies. Virtually all the approaches to the study of protein complexes require cell lysis, a dramatic step that obliterates cellular integrity and profoundly affects protein interactions. This protocol starts with Virotrap, a novel approach that avoids the need for cell homogenization by fusing the protein of interest to the HIV-1 Gag protein, trapping protein complexes in virus-like particles. By using the straightforward filtering index (SFINX), which is a powerful and intuitive online tool (http://sfinx.ugent.be) that enables contaminant removal from candidate lists resulting from mass-spectrometry-based analysis, we provide a complete workflow for researchers interested in mammalian protein complexes. Given direct access to mass spectrometers, researchers can process up to 24 samples in 7 d.

Trapping mammalian protein complexes in viral particles.

Cell lysis is an inevitable step in classical mass spectrometry-based strategies to analyse protein complexes. Complementary lysis conditions, in situ cross-linking strategies and proximal labelling techniques are currently used to reduce lysis effects on the protein complex. We have developed Virotrap, a viral particle sorting approach that obviates the need for cell homogenization and preserves the protein complexes during purification. By fusing a bait protein to the HIV-1 GAG protein, we show that interaction partners become trapped within virus-like particles (VLPs) that bud from mammalian cells. Using an efficient VLP enrichment protocol, Virotrap allows the detection of known binary interactions and MS-based identification of novel protein partners as well. In addition, we show the identification of stimulus-dependent interactions and demonstrate trapping of protein partners for small molecules. Virotrap constitutes an elegant complementary approach to the arsenal of methods to study protein complexes.