Project description:Heterotrimeric G proteins were originally discovered through efforts to understand the effects of hormones, such as glucagon and epinephrine, on glucose metabolism. On the other hand, many cellular metabolites, including glucose, serve as ligands for G protein-coupled receptors. Here we investigate the consequences of glucose-mediated receptor signaling, and in particular the role of a Gα subunit Gpa2 and a non-canonical Gβ subunit, known as Asc1 in yeast and RACK1 in animals. Asc1/RACK1 is of particular interest because it has multiple, seemingly unrelated, functions in the cell. The existence of such "moonlighting" operations has complicated the determination of phenotype from genotype. Through a comparative analysis of individual gene deletion mutants, and by integrating transcriptomics and metabolomics measurements, we have determined the relative contributions of the Gα and Gβ protein subunits to glucose-initiated processes in yeast. We determined that Gpa2 is primarily involved in regulating carbohydrate metabolism while Asc1 is primarily involved in amino acid metabolism. Both proteins are involved in regulating purine metabolism. Of the two subunits, Gpa2 regulates a greater number of gene transcripts and was particularly important in determining the amplitude of response to glucose addition. We conclude that the two G protein subunits regulate distinct but complementary processes downstream of the glucose-sensing receptor, as well as processes that lead ultimately to changes in cell growth and metabolism.
Project description:BackgroundMicroRNAs (miRNAs) play a key role in mediating the action of insulin on cell growth and the development of diabetes. However, few studies have been conducted to provide a comprehensive overview of the miRNA-mediated signaling network in response to glucose in pancreatic beta cells. In our study, we established a computational framework integrating multi-omics profiles analyses, including RNA sequencing (RNA-seq) and small RNA sequencing (sRNA-seq) data analysis, inverse expression pattern analysis, public data integration, and miRNA targets prediction to illustrate the miRNA-mediated regulatory network at different glucose concentrations in INS-1 pancreatic beta cells (INS-1), which display important characteristics of the pancreatic beta cells.ResultsWe applied our computational framework to the expression profiles of miRNA/mRNA of INS-1, at different glucose concentrations. A total of 1437 differentially expressed genes (DEGs) and 153 differentially expressed miRNAs (DEmiRs) were identified from multi-omics profiles. In particular, 121 DEmiRs putatively regulated a total of 237 DEGs involved in glucose metabolism, fatty acid oxidation, ion channels, exocytosis, homeostasis, and insulin gene regulation. Moreover, Argonaute 2 immunoprecipitation sequencing, qRT-PCR, and luciferase assay identified Crem, Fn1, and Stc1 are direct targets of miR-146b and elucidated that miR-146b acted as a potential regulator and promising target to understand the insulin signaling network.ConclusionsIn this study, the integration of experimentally verified data with system biology framework extracts the miRNA network for exploring potential insulin-associated miRNA and their target genes. The findings offer a potentially significant effect on the understanding of miRNA-mediated insulin signaling network in the development and progression of pancreatic diabetes.
Project description:The yeast Saccharomyces cerevisiae has long been used to produce alcohol from glucose and other sugars. While much is known about glucose metabolism, relatively little is known about the receptors and signaling pathways that indicate glucose availability. Here, we compare the two glucose receptor systems in S. cerevisiae. The first is a heterodimer of transporter-like proteins (transceptors), while the second is a seven-transmembrane receptor coupled to a large G protein (Gpa2) that acts in coordination with two small G proteins (Ras1 and Ras2). Through comprehensive measurements of glucose-dependent transcription and metabolism, we demonstrate that the two receptor systems have distinct roles in glucose signaling: the G-protein-coupled receptor directs carbohydrate and energy metabolism, while the transceptors regulate ancillary processes such as ribosome, amino acids, cofactor and vitamin metabolism. The large G-protein transmits the signal from its cognate receptor, while the small G-protein Ras2 (but not Ras1) integrates responses from both receptor pathways. Collectively, our analysis reveals the molecular basis for glucose detection and the earliest events of glucose-dependent signal transduction in yeast.
Project description:BackgroundPhosphorylation of proteins is a key step in the regulation of many cellular processes including activation of enzymes and signaling cascades. The abundance of a phosphorylated peptide (phosphopeptide) is determined by the abundance of its parent protein and the proportion of target sites that are phosphorylated.ResultsWe quantified phosphopeptides, proteins, and transcripts in heart, liver, and kidney tissue samples of mice from 58 strains of the Collaborative Cross strain panel. We mapped ~700 phosphorylation quantitative trait loci (phQTL) across the three tissues and applied genetic mediation analysis to identify causal drivers of phosphorylation. We identified kinases, phosphatases, cytokines, and other factors, including both known and potentially novel interactions between target proteins and genes that regulate site-specific phosphorylation. Our analysis highlights multiple targets of pyruvate dehydrogenase kinase 1 (PDK1), a regulator of mitochondrial function that shows reduced activity in the NZO/HILtJ mouse, a polygenic model of obesity and type 2 diabetes.ConclusionsTogether, this integrative multi-omics analysis in genetically diverse CC strains provides a powerful tool to identify regulators of protein phosphorylation. The data generated in this study provides a resource for further exploration.
Project description:Proteogenomic studies of cancer samples have shown that copy-number variation can be attenuated at the protein level for a large fraction of the proteome, likely due to the degradation of unassembled protein complex subunits. Such interaction-mediated control of protein abundance remains poorly characterized. To study this, we compiled genomic, (phospho)proteomic and structural data for hundreds of cancer samples and find that up to 42% of 8,124 analyzed proteins show signs of post-transcriptional control. We find evidence of interaction-dependent control of protein abundance, correlated with interface size, for 516 protein pairs, with some interactions further controlled by phosphorylation. Finally, these findings in cancer were reflected in variation in protein levels in normal tissues. Importantly, expression differences due to natural genetic variation were increasingly buffered from phenotype differences for highly attenuated proteins. Altogether, this study further highlights the importance of posttranscriptional control of protein abundance in cancer and healthy cells.
Project description:BackgroundGlucose metabolism in breast cancer has a potential effect on tumor progression and is related to the immune microenvironment. Thus, this study aimed to develop a glucose metabolism-tumor microenvironment score to provide new perspectives on breast cancer treatment.MethodData were acquired from the Gene Expression Omnibus and UCSC Xena databases, and glucose-metabolism-related genes were acquired from the Gene Set Enrichment Analysis database. Genes with significant prognostic value were identified, and immune infiltration analysis was conducted, and a prognostic model was constructed based on the results of these analyses. The results were validated by in vitro experiments with MCF-7 and MCF-10A cell lines, including expression validation, functional experiments, and bulk sequencing. Single-cell analysis was also conducted to explore the role of specific cell clusters in breast cancer, and Bayes deconvolution was used to further investigate the associations between cell clusters and tumor phenotypes of breast cancer.ResultsFour significant prognostic genes (PMAIP1, PGK1, SIRT7, and SORBS1) were identified, and, through immune infiltration analysis, a combined prognostic model based on glucose metabolism and immune infiltration was established. The model was used to classify clinical subtypes of breast cancer, and PMAIP1 was identified as a potential critical gene related to glucose metabolism in breast cancer. Single-cell analysis and Bayes deconvolution jointly confirmed the protective role of the PMAIP1+ luminal cell cluster.
Project description:The sirtuins and histone deacetylases are the best characterized members of the lysine deacetylase (KDAC) enzyme family. Recently, we annotated the "orphan" enzyme ABHD14B (α/β-hydrolase domain containing protein # 14B) as a novel KDAC and showed this enzyme's ability to transfer an acetyl-group from protein lysine residue(s) to coenzyme-A to yield acetyl-coenzyme-A, thereby, expanding the repertoire of this enzyme family. However, the role of ABHD14B in metabolic processes is not fully elucidated. Here, we investigated the role of this enzyme using mammalian cell knockdowns in a combined transcriptomics and metabolomics analysis. We found from these complementary experiments in vivo that the loss of ABHD14B results in significantly altered glucose metabolism, specifically the decreased flux of glucose through glycolysis and the citric acid cycle. Further, we show that depleting hepatic ABHD14B in mice also results in defective systemic glucose metabolism, particularly during fasting. Taken together, our findings illuminate the important metabolic functions that the KDAC ABHD14B plays in mammalian physiology and poses new questions regarding the role of this hitherto cryptic metabolism-regulating enzyme.
Project description:Au@Pt nanozyme, a bimetallic core-shell structure Au and Pt nanoparticle, has attracted significant attention due to its excellent catalytic activity and stability. Here, we propose that Au@Pt improves glucose tolerance and reduces TG after four weeks administration. The transcriptomic analysis of mouse liver tissues treated with Au@Pt nanozyme showed changes in genes related to glucose and lipid metabolism signaling pathways, including glycolysis/gluconeogenesis, pyruvate metabolism, PPAR signaling, and insulin signaling. Moreover, analysis of fecal samples from mice treated with Au@Pt nanozyme showed significant changes in the abundance of beneficial gut microbiota such as Dubosiella, Parvibacter, Enterorhabdus, Monoglobus, Lachnospiraceae_UCG-008, Lachnospiraceae_UCG-006, Lachnospiraceae_UCG-001, and Christensenellaceae_R-7_group. Combined multi-omics correlation analyses revealed that the modulation of glucose and lipid metabolism by Au@Pt was strongly correlated with changes in hepatic gene expression profiles as well as changes in gut microbial profiles. Overall, our integrated multi-omics analysis demonstrated that Au@Pt nanozyme could modulate glucose and lipid metabolism by regulating the expression of key genes in the liver and altering the composition of gut microbiota, providing new insights into the potential applications of Au@Pt nanozyme in the treatment of metabolic disorder.
Project description:Hek293 cells are the predominant hosts for transient expression of recombinant proteins and are used for stable expression of proteins where post-translational modifications performed by CHO cells are inadequate. Nevertheless, there is little information available on the key cellular features underpinning recombinant protein production in Hek293 cells. To improve our understanding of recombinant protein production in Hek293 cells and identify targets for the engineering of an improved host cell line, we have compared a stable, recombinant protein producing Hek293 cell line and its parental cell line using a combination of transcriptomics, metabolomics and fluxomics. Producer cultures consumed less glucose than non-producer cultures while achieving the same growth rate, despite the additional burden of recombinant protein production. Surprisingly, there was no indication that producer cultures compensated for the reduction in glycolytic energy by increasing the efficiency of glucose utilization or increasing glutamine consumption. In contrast, glutamine consumption was lower and the majority of genes involved in oxidative phosphorylation were downregulated in producer cultures. We observed an overall downregulation of a large number of genes associated with broad cellular functions (e.g., cell growth and proliferation) in producer cultures, and therefore speculate that a broad adaptation of the cellular network freed up resources for recombinant protein production while maintaining the same growth rate. Increased abundance of genes associated with endoplasmic reticulum stress indicated a possible bottleneck at the point of protein folding and assembly.
Project description:BackgroundGlucose metabolic reprogramming (GMR) is a cardinal feature of carcinogenesis and metastasis. However, the underlying mechanisms have not been fully elucidated. The aim of this study was to profile the metabolic signature of primary tumor and circulating tumor cells from metastatic colorectal cancer (mCRC) patients using integrated omics analysis.MethodsPET-CT imaging, serum metabolomics, genomics and proteomics data of 325 high 18F-fluorinated deoxyglucose (FDGhigh) mCRC patients were analyzed. The para-tumor, primary tumor and liver metastatic tissues of mCRC patients were used for proteomics analysis.ResultsThe glucose uptake in tumor tissues as per the PET/CT images was correlated to serum levels of glutamic-pyruvic transaminase (ALT), total bilirubin (TBIL), creatinine (CRE). Proteomics analysis indicated that several differentially expressed proteins were enriched in both GMR and epithelial-mesenchymal transition (EMT)-related pathways. Using a tissue-optimized proteomic workflow, we identified novel proteomic markers (e.g. CCND1, EPCAM, RPS6), a novel PCK1-CDK6-INSR protein axis, and a potential role for FOLR (FR) in GMR/EMT of CRC cells. Finally, CEA/blood glucose (CSR) was defined as a new index, which can be used to jointly diagnose liver metastasis of colorectal cancer.ConclusionsGMR in CRC cells is closely associated with the EMT pathway, and this network is a promising source of potential therapeutic targets.