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The stimulation of Toll-like receptors (TLRs) on macrophages by pathogen-associated molecular patterns (PAMPs) results in the activation of intracellular signaling pathways that are required for initiating a host immune response. Both phosphatidylinositol 3-kinase (PI3K)–Akt and p38 mitogen-activated protein kinase (MAPK) signaling pathways are activated rapidly in response to TLR activation and are required to coordinate effective host responses to pathogen invasion. In this study, we analyzed the role of the p38-dependent kinases MK2/3 in the activation of Akt and show that lipopolysaccharide (LPS)-induced phosphorylation of Akt on Thr308 and Ser473 requires p38α and MK2/3. In cells treated with p38 inhibitors or an MK2/3 inhibitor, phosphorylation of Akt on Ser473 and Thr308 is reduced and Akt activity is inhibited. Furthermore, BMDMs deficient in MK2/3 display greatly reduced phosphorylation of Ser473 and Thr308 following TLR stimulation. However, MK2/3 do not directly phosphorylate Akt in macrophages but act upstream of PDK1 and mTORC2 to regulate Akt phosphorylation. Akt is recruited to phosphatidylinositol 3,4,5-trisphosphate (PIP3) in the membrane, where it is activated by PDK1 and mTORC2. Analysis of lipid levels in MK2/3-deficient bone marrow-derived macrophages (BMDMs) revealed a role for MK2/3 in regulating Akt activity by affecting availability of PIP3 at the membrane. These data describe a novel role for p38α-MK2/3 in regulating TLR-induced Akt activation in macrophages.

Protein–protein interactions are essential for almost all cellular processes, hence understanding these processes mainly depends on the identification and characterization of the relevant protein–protein interactions. In the present paper, we introduce the concept of TRS ( trans -SUMOylation), a new method developed to identify and verify protein–protein interactions in mammalian cells in vivo . TRS utilizes Ubc9-fusion proteins that trans -SUMOylate co-expressed interacting proteins. Using TRS, we analysed interactions of 65 protein pairs co-expressed in HEK (human embryonic kidney)-293 cells. We identified seven new and confirmed 16 known protein interactions, which were determined via endogenous SUMOylation sites of the binding partners or by using SUMOylation-site tags respectively. Four of the new protein interactions were confirmed by GST (glutathione transferase) pull-down and the p38α–Edr2 interaction was verified by co-localization analysis. Functionally, this p38α–Edr2 interaction could possibly be involved in the recruitment of p38α to the polycomb chromatin-remodelling complex to phosphorylate Bmi1. We also used TRS to characterize protein-interaction domains of the protein kinase pairs p38α–MK2 [MK is MAPK (mitogen-activated protein kinase)-activated protein kinase] and ERK3 (extracellular-signal-regulated kinase 3)–MK5 and of the p38α–p53 complex. The ability of TRS to monitor protein interactions in mammalian cells in vivo at levels similar to endogenous expression makes it an excellent new tool that can help in defining the protein interactome of mammalian cells. Abbreviations: BIFC, bimolecular complementation of a fluorescence signal; BRET, bioluminescence resonance energy transfer; CDC37, cell division cycle 37; CDK4, cyclin-dependent kinase 4; CRSP9, cofactor required for Sp1 transcriptional activation, subunit 9; CSNK2B, casein kinase 2, β polypeptide; DMEM, Dulbecco's modified Eagle's medium; ERK, extracellular-signal-regulated kinase; FKBP, FK506-binding protein; FRET, fluorescence resonance energy transfer; GFP, green fluorescent protein; EGFP, enhanced GFP; GST, glutathione transferase; HA, haemagglutinin; HDGF, hepatoma-derived growth factor; HEK, human embryonic kidney; HRP, horseradish peroxidase; HSF2BP, heat-shock factor 2-binding protein; Hsp, heat-shock protein; JNK, c-Jun N-terminal kinase; MAPK, mitogen-activated protein kinase; MAPPIT, Mammalian Protein–Protein Interaction Trap; MEK, MAPK/ERK kinase; MEKK1ca, constitutively active MEK kinase 1; MK, MAPK-activated protein kinase; PcG, polycomb group complex; PSMC3, proteasome 26S ATPase subunit 3-interacting protein; RFP, red fluorescent protein; ST, SUMOylation-site tag; STAT1, signal transducer and activator of transcription 1; SUMO, small ubiquitin-related modifier; TBP, TATA-box-binding protein; TAF10, TBP-associated factor 10; TEV, tobacco etch virus; TRS, trans-SUMOylation; UC, uncleavable; UFDS, Ubc9 fusion-directed SUMOylation; Y2H, yeast two-hybrid

Downstream of mitogen-activated protein kinases (MAPKs), three structurally related MAPK-activated protein kinases (MAPKAPKs or MKs) - MK2, MK3 and MK5 - signal to diverse cellular targets. Although there is no known common function for all three MKs, MK2 and MK3 are mainly involved in regulation of gene expression at the post-transcriptional level and are implicated in inflammation and cancer. MK2 and MK3 are phosphorylated and activated by p38(MAPKα,β) and, in turn phosphorylate various substrates involved in diverse cellular processes. In addition to forwarding of the p38-signal by MK2/3, protein complex formation between MK2/3 and p38 mutually stabilizes these enzymes and affects p38(MAPK) signaling in general. Among the substrates of MK2/3, there are mRNA-AU-rich-element (ARE)-binding proteins, such as tristetraprolin (TTP) and hnRNP A0, which regulate mRNA stability and translation in a phosphorylation-dependent manner. Phosphorylation by MK2 stabilizes TTP, releases ARE-containing mRNAs, such as TNF-mRNA, from default translational repression and inhibits their nucleolytic degradation. Here we demonstrate that MK2/3 also contribute to the de novo synthesis of TTP. Whether this contribution proceeds via transcription factors directly targeted by MK2/3 or via chromatin remodeling by the reported binding of MK2/3 to the polycomb repressive complex is still open. A model is proposed, which demonstrates how this new function of transcriptional activation of TTP by MK2/3 cooperates with the role of MK2/3 in post-transcriptional gene expression to limit the inflammatory response.

The scratch wound healing assay is a sensitive method to characterize cell proliferation and migration, but it is difficult to be quantitatively evaluated. Therefore, we developed an infrared fluorescence detection-based real-time assay for sensitive and accurate quantification of cell migration in vitro. The method offers sensitivity, simplicity, and the potential for integration into automated large-scale screening studies. A live cell staining lipophilic tracer-1,1'-dioctadecyl-3,3,3',3'-tetramethyl indotricarbocyanine iodide (DiR)-is used for accurate imaging of wound closure in a simple 96-well scratch assay. Scratches are made on prestained confluent cell monolayers using a pipette tip and scanned at different time intervals using a fluorescent scanner. Images are analyzed using Image J software and the migration index is calculated. Effect of cell number, time after scratch and software settings are analyzed. The method is validated by showing concentration- and time-dependent effects of cytochalasin-D on fibroblast migration. Using this assay, we quantitatively evaluate the role of the MAPK-activated protein kinases MK2 and MK3 in fibroblast migration. First, the migratory phenotype of MK2-deficient MEFs is analyzed in a retroviral rescue model. In addition, migration of MK2/3-double-deficient cells is determined and the ability of MK3 to rescue cell migration in MK2/3-double-deficient fibroblasts is demonstrated.

The structurally related MAPK-activated protein kinases (MAPKAPKs or MKs) MK2, MK3 and MK5 are involved in multiple cellular functions, including cell-cycle control and cellular differentiation. Here, we show that after deregulation of cell-cycle progression, haematopoietic stem cells (HSCs) in MK2-deficient mice are reduced in number and show an impaired ability for competitive repopulation in vivo. To understand the underlying molecular mechanism, we dissected the role of MK2 in association with the polycomb group complex (PcG) and generated a MK2 mutant, which is no longer able to bind to PcG. The reduced ability for repopulation is rescued by re-introduction of MK2, but not by the Edr2-non-binding mutant of MK2. Thus, MK2 emerges as a regulator of HSC homeostasis, which could act through chromatin remodelling by the PcG complex.

The MAPK-activated protein kinases (MAPKAP kinases) MK2 and MK3 are directly activated via p38 MAPK phosphorylation, stabilize p38 by complex formation, and contribute to the stress response. The list of substrates of MK2/3 is increasing steadily. We applied a phosphoproteomics approach to compare protein phosphorylation in MK2/3-deficient cells rescued or not by ectopic expression of MK2. In addition to differences in phosphorylation of the known substrates of MK2, HSPB1 and Bag-2, we identified strong differences in phosphorylation of keratin 8 (K8). The phosphorylation of K8-Ser(73) is catalyzed directly by p38, which in turn shows MK2-dependent expression. Notably, analysis of small molecule p38 inhibitors on K8-Ser(73) phosphorylation also demonstrated reduced phosphorylations of keratins K18-Ser(52) and K20-Ser(13) but not of K8-Ser(431) or K18-Ser(33). Interestingly, K18-Ser(52) and K20-Ser(13) are not directly phosphorylated by p38 in vitro, but by MK2. Furthermore, anisomycin-stimulated phosphorylations of K20-Ser(13) and K18-Ser(52) are inhibited by small molecule inhibitors of both p38 and MK2. MK2 knockdown in HT29 cells leads to reduced K20-Ser(13) phosphorylation, which further supports the notion that MK2 is responsible for K20 phosphorylation in vivo. Physiologic relevance of these findings was confirmed by differences of K20-Ser(13) phosphorylation between the ileum of wild-type and MK2/3-deficient mice and by demonstrating p38- and MK2-dependent mucin secretion of HT29 cells. Therefore, MK2 and p38 MAPK function in concert to phosphorylate K8, K18, and K20 in intestinal epithelia.

Background SLE is a chronic multisystem autoimmune disease with yet unknown etiology. One hallmark of SLE is the B cell activation and the production of various autoantibodies. Differential diagnosis involves ANA screening which may yield also positive results in many connective tissue disorders and other autoimmune diseases, and may occur in normal individuals. More specific subtypes of antinuclear antibodies include anti-Smith and anti-double stranded DNA (dsDNA) antibodies. However, anti-dsDNA antibodies are present in just 70% SLE patients leaving a certain gap in diagnosis. Objectives In this study we characterized the autoimmune signatures of SLE patients and healthy blood donors in order to identify established plus novel autoantibodies with differential abundance in serum samples of SLE patients. Methods We used 5800 human proteins to investigate the autoantibodies present in more than 110 serum samples of SLE patients as well as healthy blood donors applying bead-based arrays (Luminex). Biostatistical analysis was performed using univariate as well as multivariate statistical algorithms. Results In addition to the well-established clinical markers Ro52/SS-A (TRIM21), ribosomal P0, ribosomal P1, ribosomal P2, SS-A/Ro60 (TROVE2), SSB and SmB/B´ new biomarkers were identified showing high discriminatory p-values and promising sensitivity and specificity. Consequently, a small protein antigen panel consisting of four new markers plus six well-established clinical markers (Ro52/SS-A, Ro60/SS-A, ribosomal P0, ribosomal P1, ribosomal P2, and SmB/B´protein) has been defined. This panel results in an improved AUC when compared to the classification performance of the established markers alone. Conclusions With novel biomarkers a large proportion of dsDNA AB-negative SLE patients can be addressed. The benefit of the identified marker panel for SLE diagnosis is currently evaluated in comparative analysis of other patient cohorts of ankylosing spondylitis, progressive systemic sclerosis, and rheumatoid arthritis. Disclosure of Interest None Declared

Background Rheumatoid arthritis (RA) is an autoimmune disease typically characterized by chronic inflammation, accumulation of self-reactive B-cells and production of autoantibodies of which anti–cyclic citrullinated peptide (anti-CCP) antibodies and rheumatoid factor (RF) have diagnostic utility. Despite these two well established markers up to 30% of RA patients remain sero-negative making an early diagnosis of RA more difficult. Although progress has been made to characterize risk factors for anti-CCP negative RA, studies on autoantibody profiles in CCP-negative RA are so far lacking. Objectives To improve the current diagnosis of RA, we aimed to determine whether the group of anti-CCP negative RA patients can be identified based on specific autoantibody profiles. Our major goal is to develop a novel autoantibody-based diagnostic test that allows to correctly diagnosing CCP- and RF-negative early RA patients. Methods In order to identify novel autoantigens characteristic for CCP-negative RA patients we performed a large-scale screen of 5800 proteins in a total of 150 serum samples of patients with stable RA and healthy volunteers. The major technology platform employed in this study is an automated bead-based Luminex xMAP technology which enables to measure the reactivity of autoantibodies to up to 500 different antigens in one single serum sample. All proteins are produced from E. coli , are highly purified by affinity capturing, sequenced by mass spectrometry, and each protein is coupled in optimised concentration to individual colour coded Luminex beads. Results Using both univariate and multivariate statistical algorithms we identified 144 novel antigens in RA patients. Furthermore, our data indicated heterogeneity in the autoantibody profile of RA patients and some overlap between the group of CCP-positive and CCP-negative patients. To address this complexity and heterogeneity we developed biomarker panels comprising five to ten antigens to identify CCP-negative RA patients. Notably, one panel with six antigens showed high specificity comparable to CCP. Another panel was able to detect about 60% of CCP-negative patients for whom currently no diagnostic marker is available. Conclusions CCP sero-negative RA patients can be identified based on specific set of autoantibodies. Further studies are currently conducted to validate the biomarker panels in early RA patients. Disclosure of Interest None Declared