Modification of Collagen by 3-Deoxyglucosone Alters Wound Healing through Differential Regulation of p38 MAP Kinase

Background: Wound healing is a highly dynamic process that requires signaling from the extracellular matrix to the fibroblasts for migration and proliferation, and closure of the wound. This rate of wound closure is impaired in diabetes, which may be due to the increased levels of the precursor for advanced glycation end products, 3-deoxyglucosone (3DG). Previous studies suggest a differential role for p38 mitogen-activated kinase (MAPK) during wound healing; whereby, p38 MAPK acts as a growth kinase during normal wound healing, but acts as a stress kinase during diabetic wound repair. Therefore, we investigated the signaling cross-talk by which p38 MAPK mediates wound healing in fibroblasts cultured on native collagen and 3DG-collagen. Methodology/Principal Findings: Using human dermal fibroblasts cultured on 3DG-collagen as a model of diabetic wounds, we demonstrated that p38 MAPK can promote either cell growth or cell death, and this was dependent on the activation of AKT and ERK1/2. Wound closure on native collagen was dependent on p38 MAPK phosphorylation of AKT and ERK1/2. Furthermore, proliferation and collagen production in fibroblasts cultured on native collagen was dependent on p38 MAPK regulation of AKT and ERK1/2. In contrast, 3DG-collagen decreased fibroblast migration, proliferation, and collagen expression through ERK1/2 and AKT downregulation via p38 MAPK. Conclusions/Significance: Taken together, the present study shows that p38 MAPK is a key signaling molecule that plays

Protein kinase C-delta (PKC delta), a marker of inflammation and tuberculosis disease progression in humans, is important for optimal macrophage killing effector functions and survival in mice (vol 11, pg 496, 2018)

We previously demonstrated that protein kinase C-δ (PKCδ) is critical for immunity against Listeria monocytogenes, Leishmania major, and Candida albicans infection in mice. However, the functional relevance of PKCδ during Mycobacterium tuberculosis (Mtb) infection is unknown. PKCδ was significantly upregulated in whole blood of patients with active tuberculosis (TB) disease. Lung proteomics further revealed that PKCδ was highly abundant in the necrotic and cavitory regions of TB granulomas in multidrug-resistant human participants. In murine Mtb infection studies, PKCδ−/− mice were highly susceptible to tuberculosis with increased mortality, weight loss, exacerbated lung pathology, uncontrolled proinflammatory cytokine responses, and increased mycobacterial burdens. Moreover, these mice displayed a significant reduction in alveolar macrophages, dendritic cells, and decreased accumulation of lipid bodies (lungs and macrophages) and serum fatty acids. Furthermore, a peptide inhibitor of PKCδ in wild-type mice mirrored lung inflammation identical to infected PKCδ−/− mice. Mechanistically, increased bacterial growth in macrophages from PKCδ−/− mice was associated with a decline in killing effector functions independent of phagosome maturation and autophagy. Taken together, these data suggest that PKCδ is a marker of inflammation during active TB disease in humans and required for optimal macrophage killing effector functions and host protection during Mtb infection in mice

Genomics Meets Glycomics—The First GWAS Study of Human N-Glycome Identifies HNF1α as a Master Regulator of Plasma Protein Fucosylation

Over half of all proteins are glycosylated, and alterations in glycosylation have been observed in numerous physiological and pathological processes. Attached glycans significantly affect protein function; but, contrary to polypeptides, they are not directly encoded by genes, and the complex processes that regulate their assembly are poorly understood. A novel approach combining genome-wide association and high-throughput glycomics analysis of 2,705 individuals in three population cohorts showed that common variants in the Hepatocyte Nuclear Factor 1α (HNF1α) and fucosyltransferase genes FUT6 and FUT8 influence N-glycan levels in human plasma. We show that HNF1α and its downstream target HNF4α regulate the expression of key fucosyltransferase and fucose biosynthesis genes. Moreover, we show that HNF1α is both necessary and sufficient to drive the expression of these genes in hepatic cells. These results reveal a new role for HNF1α as a master transcriptional regulator of multiple stages in the fucosylation process. This mechanism has implications for the regulation of immunity, embryonic development, and protein folding, as well as for our understanding of the molecular mechanisms underlying cancer, coronary heart disease, and metabolic and inflammatory disorders

Meta-Analysis of 28,141 Individuals Identifies Common Variants within Five New Loci That Influence Uric Acid Concentrations

Elevated serum uric acid levels cause gout and are a risk factor for cardiovascular disease and diabetes. To investigate the polygenetic basis of serum uric acid levels, we conducted a meta-analysis of genome-wide association scans from 14 studies totalling 28,141 participants of European descent, resulting in identification of 954 SNPs distributed across nine loci that exceeded the threshold of genome-wide significance, five of which are novel. Overall, the common variants associated with serum uric acid levels fall in the following nine regions: SLC2A9 (p = 5.2×10−201), ABCG2 (p = 3.1×10−26), SLC17A1 (p = 3.0×10−14), SLC22A11 (p = 6.7×10−14), SLC22A12 (p = 2.0×10−9), SLC16A9 (p = 1.1×10−8), GCKR (p = 1.4×10−9), LRRC16A (p = 8.5×10−9), and near PDZK1 (p = 2.7×10−9). Identified variants were analyzed for gender differences. We found that the minor allele for rs734553 in SLC2A9 has greater influence in lowering uric acid levels in women and the minor allele of rs2231142 in ABCG2 elevates uric acid levels more strongly in men compared to women. To further characterize the identified variants, we analyzed their association with a panel of metabolites. rs12356193 within SLC16A9 was associated with DL-carnitine (p = 4.0×10−26) and propionyl-L-carnitine (p = 5.0×10−8) concentrations, which in turn were associated with serum UA levels (p = 1.4×10−57 and p = 8.1×10−54, respectively), forming a triangle between SNP, metabolites, and UA levels. Taken together, these associations highlight additional pathways that are important in the regulation of serum uric acid levels and point toward novel potential targets for pharmacological intervention to prevent or treat hyperuricemia. In addition, these findings strongly support the hypothesis that transport proteins are key in regulating serum uric acid levels

A Machine Learning Approach for Identifying Novel Cell Type–Specific Transcriptional Regulators of Myogenesis

Transcriptional enhancers integrate the contributions of multiple classes of transcription factors (TFs) to orchestrate the myriad spatio-temporal gene expression programs that occur during development. A molecular understanding of enhancers with similar activities requires the identification of both their unique and their shared sequence features. To address this problem, we combined phylogenetic profiling with a DNA–based enhancer sequence classifier that analyzes the TF binding sites (TFBSs) governing the transcription of a co-expressed gene set. We first assembled a small number of enhancers that are active in Drosophila melanogaster muscle founder cells (FCs) and other mesodermal cell types. Using phylogenetic profiling, we increased the number of enhancers by incorporating orthologous but divergent sequences from other Drosophila species. Functional assays revealed that the diverged enhancer orthologs were active in largely similar patterns as their D. melanogaster counterparts, although there was extensive evolutionary shuffling of known TFBSs. We then built and trained a classifier using this enhancer set and identified additional related enhancers based on the presence or absence of known and putative TFBSs. Predicted FC enhancers were over-represented in proximity to known FC genes; and many of the TFBSs learned by the classifier were found to be critical for enhancer activity, including POU homeodomain, Myb, Ets, Forkhead, and T-box motifs. Empirical testing also revealed that the T-box TF encoded by org-1 is a previously uncharacterized regulator of muscle cell identity. Finally, we found extensive diversity in the composition of TFBSs within known FC enhancers, suggesting that motif combinatorics plays an essential role in the cellular specificity exhibited by such enhancers. In summary, machine learning combined with evolutionary sequence analysis is useful for recognizing novel TFBSs and for facilitating the identification of cognate TFs that coordinate cell type–specific developmental gene expression patterns

A metabolomics approach exploring the function of the ESX-3 type VII secretion system of M. smegmatis.

Please help populate SUNScholar with the full text of SU research output. Also - should you need this item urgently, please send us the details and we will try to get hold of the full text as quick possible. E-mail to [email protected]. Thank you.Journal Articles (subsidised)Geneeskunde en GesondheidswetenskappeMolekul�re Biologie & Mensgenetik