Nucleoside antibiotics are a large class of pharmaceutically relevant chemical entities, which exhibit a broad spectrum of biological activities. Most nucleosides belong to the canonical N-nucleoside family, where the heterocyclic unit is connected to the carbohydrate through a carbon-nitrogen bond. However, atypical C-nucleosides were isolated from Streptomyces bacteria over 50 years ago, but the molecular basis for formation of these metabolites has been unknown. Here, we have sequenced the genome of S. showdoensis ATCC 15227 and identified the gene cluster responsible for showdomycin production. Key to the detection was the presence of sdmA, encoding an enzyme of the pseudouridine monophosphate glycosidase family, which could catalyze formation of the C-glycosidic bond. Sequence analysis revealed an unusual combination of biosynthetic genes, while inactivation and subsequent complementation of sdmA confirmed the involvement of the locus in showdomycin formation. The study provides the first steps toward generation of novel C-nucleosides by pathway engineering.

Pseudouridine is a noncanonical C–nucleoside commonly present in RNA, which is not metabolized in mammals, but can be recycled by the unique enzyme family of bacterial pseudouridine glycosidases such as YeiN from Escherichia coli. Here, we present rigorous bioinformatic and biochemical analyses of the protein family in order to find sequences that might code for nonpseudouridine glycosidase activities. To date, the only other function reported for the enzyme family occurs during the biosynthesis of the antibiotic alnumycin A in Streptomyces species, where AlnA functions as an unusual C–glycosynthase. Bioinformatics analysis of 755 protein sequences identified one group of sequences that were unlikely to harbour pseudouridine glycosidase activities. This observation was confirmed in vitro with one representative protein, IdgA from Streptomyces albus, which was unable to synthesize pseudouridine monophosphate, but was able to attach d–ribose‐5‐phosphate to juglone. Furthermore, our analyses provide evidence for horizontal gene transfer of pseudouridine glycosidases that may have occurred in Streptomyces and Doria species. Inspection of the genomic loci in the vicinity of pseudouridine glycosidases revealed that in 77% of the strains a kinase gene putatively involved in the phosphorylation of pseudouridine was found nearby, whereas the sequences encoding nonpseudouridine glycosidases coexisted with a phosphatase of the haloacid dehalogenase enzyme family. The investigation suggested that these unknown sequences might be involved in the biosynthesis of soluble blue pigments because of the presence of genes homologous to nonribosomal peptide synthetases.

Angucyclines are tetracyclic polyketides produced by Streptomyces bacteria that exhibit notable biological activities. The great diversity of angucyclinones is generated in tailoring reactions, which modify the common benz[a]anthraquinone carbon skeleton. In particular, the opposite stereochemistry of landomycins and urdamycins/gaudimycins at C-6 is generated by the short-chain alcohol dehydrogenases/reductases LanV and UrdMred/CabV, respectively. Here we present crystal structures of LanV and UrdMred in complex with NADP(+) and the product analog rabelomycin, which enabled us to identify four regions associated with the functional differentiation. The structural analysis was confirmed in chimeragenesis experiments focusing on these regions adjacent to the active site cavity, which led to reversal of the activities of LanV and CabV. The results surprisingly indicated that the conformation of the substrate and the stereochemical outcome of 6-ketoreduction appear to be intimately linked.

Melanocortin receptor 1 (MC1-R) is expressed in leukocytes, where it mediates anti-inflammatory actions. We have previously observed that global deficiency of MC1-R signaling perturbs cholesterol homeostasis, increases arterial leukocyte accumulation and accelerates atherosclerosis in apolipoprotein E knockout (Apoe-/-) mice. Since various cell types besides leukocytes express MC1-R, we aimed at investigating the specific contribution of leukocyte MC1-R to the development of atherosclerosis. For this purpose, male Apoe-/- mice were irradiated, received bone marrow from either female Apoe-/- mice or MC1-R deficient Apoe-/- mice (Apoe-/- Mc1re/e) and were analyzed for tissue leukocyte profiles and atherosclerotic plaque phenotype. Hematopoietic MC1-R deficiency significantly elevated total leukocyte counts in the blood, bone marrow and spleen, an effect that was amplified by feeding mice a cholesterol-rich diet. The increased leukocyte counts were largely attributable to expanded lymphocyte populations, particularly CD4+ T cells. Furthermore, the number of monocytes was elevated in Apoe-/- Mc1re/e chimeric mice and it paralleled an increase in hematopoietic stem cell count in the bone marrow. Despite robust leukocytosis, atherosclerotic plaque size and composition as well as arterial leukocyte counts were unaffected by MC1-R deficiency. To address this discrepancy, we performed an in vivo homing assay and found that MC1-R deficient CD4+ T cells and monocytes were preferentially entering the spleen rather than homing in peri-aortic lymph nodes. This was mechanistically associated with compromised chemokine receptor 5 (CCR5)-dependent migration of CD4+ T cells and a defect in the recycling capacity of CCR5. Finally, our data demonstrate for the first time that CD4+ T cells also express MC1-R. In conclusion, MC1-R regulates hematopoietic stem cell proliferation and tissue leukocyte counts but its deficiency in leukocytes impairs cell migration via a CCR5-dependent mechanism.

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Melanocortin 1 receptor (MC1-R) is widely expressed in melanocytes and leukocytes, and is thus strongly implicated in the regulation of skin pigmentation and inflammation. MC1-R mRNA has also been found in the rat and human liver, but its functional role has remained elusive. We hypothesized that MC1-R is functionally active in the liver and involved in the regulation of cholesterol and bile acid metabolism. We generated hepatocyte-specific MC1-R knock-out (L-Mc1r-/-) mice and phenotyped the mouse model for lipid profiles, liver histology and bile acid levels. L-Mc1r-/- mice had significantly increased liver weight, which was accompanied by elevated levels of total cholesterol and triglycerides in the liver as well as in the plasma. These mice demonstrated also enhanced liver fibrosis and a disturbance in bile acid metabolism as evidenced by markedly reduced bile acid levels in the plasma and feces. Mechanistically, using HepG2 cells as an in vitro model, we found that selective activation of MC1-R in HepG2 cells reduced cellular cholesterol content and enhanced uptake of low- and high-density lipoprotein particles via a cAMP-independent mechanism. In conclusion, the present results demonstrate that MC1-R signaling in hepatocytes regulates cholesterol and bile acid metabolism and its deficiency leads to hypercholesterolemia and enhanced lipid accumulation and fibrosis in the liver. Key words: Melanocortin 1 receptor; Cholesterol; Triglyceride; Bile acid; Steatosis; Fibrosis

For decades, molecular biologists have been uncovering the mechanics of biological systems. Efforts to bring their findings together have led to the development of multiple databases and information systems that capture and present pathway information in a computable network format. Concurrently, the advent of modern omics technologies has empowered researchers to systematically profile cellular processes across different modalities. Numerous algorithms, methodologies, and tools have been developed to use prior knowledge networks in the analysis of omics datasets. Interestingly, it has been repeatedly demonstrated that the source of prior knowledge can greatly impact the results of a given analysis. For these methods to be successful it is paramount that their selection of prior knowledge networks is amenable to the data type and the computational task they aim to accomplish. Here we present a five-level framework that broadly describes network models in terms of their scope, level of detail, and ability to inform causal predictions. To contextualize this framework, we review a handful of network-based omics analysis methods at each level, while also describing the computational tasks they aim to accomplish.

Interactions among tumor, immune and vascular niches play major roles in driving glioblastoma (GBM) malignancy and treatment responses. The composition, heterogeneity, and localization of extracellular core matrix proteins (CMPs) that mediate such interactions, however, are not well understood. Here, we characterize functional and clinical relevance of genes encoding CMPs in GBM at bulk, single cell, and spatial anatomical resolution. We identify a matrix code for genes encoding CMPs whose expression levels categorize GBM tumors into matrisome-high and matrisome-low groups that correlate with worse and better survival, respectively, of patients. The matrisome enrichment is associated with specific driver oncogenic alterations, mesenchymal state, infiltration of pro-tumor immune cells and immune checkpoint gene expression. Anatomical and single cell transcriptome analyses indicate that matrisome gene expression is enriched in vascular and leading edge/infiltrative anatomic structures that are known to harbor glioma stem cells driving GBM progression. Finally, we identified a 17-gene matrisome signature that retains and further refines the prognostic value of genes encoding CMPs and, importantly, potentially predicts responses to PD1 blockade in clinical trials for GBM. The matrisome gene expression profiles may provide biomarkers of functionally relevant GBM niches that contribute to mesenchymal-immune cross talk and patient stratification to optimize treatment responses.