Ultrahigh-Resolution Mass Spectrometry-Based Platform for Plasma Metabolomics Applied to Type 2 Diabetes Research

Metabolomics-the endpoint of the omics cascade-is increasingly recognized as a preferred method for understanding the ultimate responses of biological systems to stress. Flow injection electrospray (FIE) mass spectrometry (MS) has advantages for untargeted metabolic fingerprinting due to its simplicity and capability for high-throughput screening but requires a high-resolution mass spectrometer to resolve metabolite features. In this study, we developed and validated a high-throughput and highly reproducible metabolomics platform integrating FIE with ultrahigh-resolution Fourier transform ion cyclotron resonance (FTICR) MS for analysis of both polar and nonpolar metabolite features from plasma samples. FIE-FTICR MS enables high-throughput detection of hundreds of metabolite features in a single mass spectrum without a front-end separation step. Using plasma samples from genetically identical obese mice with or without type 2 diabetes (T2D), we validated the intra and intersample reproducibility of our method and its robustness for simultaneously detecting alterations in both polar and nonpolar metabolite features. Only 5 min is needed to acquire an ultra-high resolution mass spectrum in either a positive or negative ionization mode. Approximately 1000 metabolic features were reproducibly detected and annotated in each mouse plasma group. For significantly altered and highly abundant metabolite features, targeted tandem MS (MS/MS) analyses can be applied to confirm their identity. With this integrated platform, we successfully detected over 300 statistically significant metabolic features in T2D mouse plasma as compared to controls and identified new T2D biomarker candidates. This FIE-FTICR MS-based method is of high throughput and highly reproducible with great promise for metabolomics studies toward a better understanding and diagnosis of human diseases.

A gene expression network analysis of the pancreatic islets from lean and obese mice identifies complement 1q like-3 secreted protein as a regulator of β-cell function

Secreted proteins are important metabolic regulators. Identifying and characterizing the role of secreted proteins from small tissue depots such as islets of Langerhans, which are required for the proper control of whole-body energy metabolism, remains challenging. Our objective was to identify islet-derived secreted proteins that affect islet function in obesity. Lean and obese mouse islet expression data were analyzed by weighted gene co-expression network analysis (WGCNA) to identify trait-associated modules. Subsequently, genes within these modules were filtered for transcripts that encode for secreted proteins based on intramodular connectivity, module membership, and differential expression. Complement 1q like-3 (C1ql3) secreted protein was identified as a hub gene affecting islet function in obesity. Co-expression network, hierarchal clustering, and gene-ontology based approaches identified a putative role for C1ql3 in regulating β-cell insulin secretion. Biological validation shows that C1ql3 is expressed in β-cells, it inhibits insulin secretion and key genes that are involved in β-cell function. Moreover, the increased expression of C1ql3 is correlated with the reduced insulin secretion in islets of obese mice. Herein, we demonstrate a streamlined approach to effectively screen and determine the function of secreted proteins in islets, and identified C1ql3 as a putative contributor to reduced insulin secretion in obesity, linking C1ql3 to an increased susceptibility to type 2 diabetes.

SAT-168 A Secreted Protein Complement 1q Like-3 Protein Inhibits Insulin Secretion by an Adhesion G-Protein Coupled Receptor, BAI3 in Pancreatic β-Cells

Secreted proteins are important metabolic regulators in both healthy and disease states. By using Bioinformatics approaches, we identified complement-1q-like-3 secreted protein that expressed in α-cells affects β-cell function in the pancreatic islets. Our objective was to investigate the mechanism by which C1ql3 regulates insulin secretion from pancreatic β-cells. Our data suggest that C1ql3 predominantly inhibits exendin-4 and cAMP-stimulated insulin secretion from mouse and human islets. Moreover, C1ql3 also attenuated insulin secretion stimulated by high KCl, a sulphonyl urea tolbutamide (potassium channel blocker) and high glucose to a lesser extent. Interestingly, C1ql3 failed to affect insulin secretion caused by fatty acids, amino acids, or mitochondrial metabolites, either at low or submaximal glucose concentrations. Furthermore, C1ql3 decreased islet-cAMP levels stimulated by high glucose, and insulin secretion caused by Epac2 (exchange protein directly activated by cAMP-2) and protein kinase A. Our data suggest that C1ql3 inhibits insulin secretion primarily by regulating cAMP signaling pathway. The cell adhesion G protein-coupled receptor, brain angiogenesis inhibitor-3 (BAI3), is a receptor for C1ql3. Knockdown of BAI3 by siRNA in INS1(832/13) cells increased glucose-stimulated insulin secretion in a dose dependent manner. In addition, incubating the mouse islets with soluble C1ql3-binding fragment of the BAI3 protein completely blocked the inhibitory effects of C1ql3 on insulin secretion in response to cAMP. These findings suggest that inhibitory effects of C1ql3 on insulin secretion from pancreatic β-cells is mediated by Bai3. Additionally, C1ql3 and BAI3 expression increases with obesity suggesting that novel C1ql3/BAI3 signaling, which causes an impairment of insulin secretion from β-cells, possibly contributing to the progression of type 2 diabetes in obesity.