Microglia are major immune cells in the central nervous system. A characterization of microglia proteome would facilitate on the study of microglial functions in association with various neurodegenerative diseases. To build a reference proteome, we established a BV-2 microglial proteome to a depth of 5494 unique protein groups using a novel strategy that combined FASP, StageTip-based high pH fractionation, and high-resolution MS quickly and cost efficiently. By bioinformatics analysis, the BV-2 proteome is a valuable resource for studies of microglial function, such as in the immune response, inflammatory response, and phagocytosis. All MS data have been deposited in the ProteomeXchange with identifier PXD000168.

Type 2 diabetes results from aberrant regulation of the phosphorylation cascade in beta-cells. Phosphorylation in pancreatic beta-cells has not been examined extensively, except with regard to subcellular phosphoproteomes using mitochondria. Thus, robust, comprehensive analytical strategies are needed to characterize the many phosphorylated proteins that exist, because of their low abundance, the low stoichiometry of phosphorylation, and the dynamic regulation of phosphoproteins. In this study, we attempted to generate data on a large-scale phosphoproteome from the INS-1 rat pancreatic beta-cell line using linear ion trap MS/MS. To profile the phosphoproteome in-depth, we used comprehensive phosphoproteomic strategies, including detergent-based protein extraction (SDS and SDC), differential sample preparation (in-gel, in-solution digestion, and FASP), TiO2 enrichment, and MS replicate analyses (MS2-only and multiple-stage activation). All spectra were processed and validated by stringent multiple filtering using target and decoy databases. We identified 2467 distinct phosphorylation sites on 1419 phosphoproteins using 4 mg of INS-1 cell lysate in 24 LC-MS/MS runs, of which 683 (27.7%) were considered novel phosphorylation sites that have not been characterized in human, mouse, or rat homologues. Our informatics data constitute a rich bioinformatics resource for investigating the function of reversible phosphorylation in pancreatic beta-cells. In particular, novel phosphorylation sites on proteins that mediate the pathology of type 2 diabetes, such as Pdx-1, Nkx.2, and Srebf1, will be valuable targets in ongoing phosphoproteomics studies.

Diabetic nephropathy (DN) is a long-term complication of diabetes mellitus that leads to end-stage renal disease. Microalbuminuria is used for the early detection of diabetic renal damage, but such levels do not reflect the state of incipient DN precisely in type 2 diabetic patients because microalbuminuria develops in other diseases, necessitating more accurate biomarkers that detect incipient DN. Isobaric tags for relative and absolute quantification (iTRAQ) were used to identify urinary proteins that were differentially excreted in normoalbuminuric and microalbuminuric patients with type 2 diabetes where 710 and 196 proteins were identified and quantified, respectively. Some candidates were confirmed by 2-DE analysis, or validated by Western blot and multiple reaction monitoring (MRM). Specifically, some differentially expressed proteins were verified by MRM in urine from normoalbuminuric and microalbuminuric patients with type 2 diabetes, wherein alpha-1-antitrypsin, alpha-1-acid glycoprotein 1, and prostate stem cell antigen had excellent AUC values (0.849, 0.873, and 0.825, resp.). Moreover, we performed a multiplex assay using these biomarker candidates, resulting in a merged AUC value of 0.921. Although the differentially expressed proteins in this iTRAQ study require further validation in larger and categorized sample groups, they constitute baseline data on preliminary biomarker candidates that can be used to discover novel biomarkers for incipient DN.

Pancreatic cancer is one of the most fatal cancers and is associated with limited diagnostic and therapeutic modalities. Currently, gemcitabine is the only effective drug and represents the preferred first-line treatment for chemotherapy. However, a high level of intrinsic or acquired resistance of pancreatic cancer to gemcitabine can contribute to the failure of gemcitabine treatment. To investigate the underlying molecular mechanisms for gemcitabine resistance in pancreatic cancer, we performed label-free quantification of protein expression in intrinsic gemcitabine-resistant and - sensitive human pancreatic adenocarcinoma cell lines using our improved proteomic strategy, combined with filter-aided sample preparation, single-shot liquid chromatography-mass spectrometry, enhanced spectral counting, and a statistical method based on a power law global error model. We identified 1931 proteins and quantified 787 differentially expressed proteins in the BxPC3, PANC-1, and HPDE cell lines. Bioinformatics analysis identified 15 epithelial to mesenchymal transition (EMT) markers and 13 EMT-related proteins that were closely associated with drug resistance were differentially expressed. Interestingly, 8 of these proteins were involved in glutathione and cysteine/methionine metabolism. These results suggest that proteins related to the EMT and glutathione metabolism play important roles in the development of intrinsic gemcitabine resistance by pancreatic cancer cell lines.

The heterotrimeric enzyme AMP-activated protein kinase (AMPK) is a major metabolic factor that regulates the homeostasis of cellular energy. In particular, AMPK mediates the insulin resistance that is associated with type 2 diabetes. Generally, cellular processes require tight regulation of protein kinases, which is effected through their formation of complex with other proteins and substrates. Despite their critical function in regulation and pathogenesis, there are limited data on the interaction of protein kinases. To identify proteins that interact with AMPK, we performed large-scale affinity purification (AP)-mass spectrometry (MS) of the AMPK-α1 and -β1 subunits. Through a comprehensive analysis, using a combination of immunoprecipitaion and ion trap mass spectrometry, we identified 381 unique proteins in the AMPKα/β interactomes: 325 partners of AMPK-α1 and 243 for AMPK-β1. Further, we identified 196 novel protein-protein interactions with AMPK-α1 and AMPK-β1. Notably, in our bioinformatics analysis, the novel interaction partners mediated functions that are related to the regulation of actin organization. Specifically, several such proteins were linked to pancreatic beta-cell functions, including glucose-stimulated insulin secretion, beta-cell development, beta-cell differentiation, and cell-cell communication.