Danjun Ma

let-7 microRNAs induce tamoxifen sensitivity by downregulation of estrogen receptor α signaling in breast cancer.

MicroRNAs (miRNAs) play an important regulatory role in breast tumorigenesis. Previously, we found that let-7 miRNAs were downregulated significantly in formalin-fixed paraffin-embedded (FFPE) breast cancer tissues. In this study, we further found that endogenous levels of let-7b and let-7i miRNAs are inversely correlated with levels of estrogen receptor (ER)-a36, a new variant of ER-α66, in the FFPE tissue set. Bioinformatic analysis suggested that ER-α36 may be another target of let-7 miRNAs. To test this hypothesis, cotransfection of let-7 mimics or inhibitors together with full-length or a fragment of ER-α36 3′UTR luciferase construct was performed, and we found that let-7b and let-7i mimics suppressed the activity of reporter gene significantly, which was enhanced remarkably by let-7b and let-7i inhibitors. Both mRNA and protein expression of ER-α36 were inhibited by let-7 mimics and enhanced by let-7 inhibitors. Furthermore, ER-α36 mediated nongenomic MAPK and Akt pathways were weakened by let-7b and let-7i mimics in triple negative breast cancer cell line MDA-MB-231. The reverse correlation between let-7 miRNAs and ER-α36 also exists in Tamoxifen (Tam)-resistant MCF7 cell line. Transfection of let-7 mimics to Tam-resistant MCF7 cells downregulated ER-α36 expression and enhanced the sensitivity of MCF7 cells to Tam in estrogen-free medium, which could be restored by overexpression of ER-α36 constructs without 3′UTR. Our results suggested a novel regulatory mechanism of let-7 miRNAs on ER-α36 mediated nongenomic estrogen signal pathways and Tam resistance.

SEC24A deficiency lowers plasma cholesterol through reduced PCSK9 secretion

The secretory pathway of eukaryotic cells packages cargo proteins into COPII-coated vesicles for transport from the endoplasmic reticulum (ER) to the Golgi. We now report that complete genetic deficiency for the COPII component SEC24A is compatible with normal survival and development in the mouse, despite the fundamental role of SEC24 in COPII vesicle formation and cargo recruitment. However, these animals exhibit markedly reduced plasma cholesterol, with mutations in Apoe and Ldlr epistatic to Sec24a, suggesting a receptor-mediated lipoprotein clearance mechanism. Consistent with these data, hepatic LDLR levels are up-regulated in SEC24A-deficient cells as a consequence of specific dependence of PCSK9, a negative regulator of LDLR, on SEC24A for efficient exit from the ER. Our findings also identify partial overlap in cargo selectivity between SEC24A and SEC24B, suggesting a previously unappreciated heterogeneity in the recruitment of secretory proteins to the COPII vesicles that extends to soluble as well as trans-membrane cargoes. DOI: http://dx.doi.org/10.7554/eLife.00444.001

Increased Interaction with Insulin Receptor Substrate-1, a Novel Abnormality in Insulin Resistance and Type 2 Diabetes

Insulin receptor substrate 1 (IRS1) is a key mediator of insulin signal transduction. Perturbations involving IRS1 complexes may lead to the development of insulin resistance and type 2 diabetes (T2D). Surprisingly little is known about the proteins that interact with IRS1 in humans under health and disease conditions. We used a proteomic approach to assess IRS1 interaction partners in skeletal muscle from lean healthy control subjects (LCs), obese insulin-resistant nondiabetic control subjects (OCs), and participants with T2D before and after insulin infusion. We identified 113 novel endogenous IRS1 interaction partners, which represents the largest IRS1 interactome in humans and provides new targets for studies of IRS1 complexes in various diseases. Furthermore, we generated the first global picture of IRS1 interaction partners in LCs, and how they differ in OCs and T2D patients. Interestingly, dozens of proteins in OCs and/or T2D patients exhibited increased associations with IRS1 compared with LCs under the basal and/or insulin-stimulated conditions, revealing multiple new dysfunctional IRS1 pathways in OCs and T2D patients. This novel abnormality, increased interaction of multiple proteins with IRS1 in obesity and T2D in humans, provides new insights into the molecular mechanism of insulin resistance and identifies new targets for T2D drug development.

Quantitative phosphoproteomics reveals novel phosphorylation events in insulin signaling regulated by protein phosphatase 1 regulatory subunit 12A.

UNLABELLED Serine/threonine protein phosphatase 1 regulatory subunit 12A (PPP1R12A) modulates the activity and specificity of the catalytic subunit of protein phosphatase 1, regulating various cellular processes via dephosphorylation. Nonetheless, little is known about phosphorylation events controlled by PPP1R12A in skeletal muscle insulin signaling. Here, we used quantitative phosphoproteomics to generate a global picture of phosphorylation events regulated by PPP1R12A in a L6 skeletal muscle cell line, which were engineered for inducible PPP1R12A knockdown. Phosphoproteomics revealed 3876 phosphorylation sites (620 were novel) in these cells. Furthermore, PPP1R12A knockdown resulted in increased overall phosphorylation in L6 cells at the basal condition, and changed phosphorylation levels for 698 sites (assigned to 295 phosphoproteins) at the basal and/or insulin-stimulated conditions. Pathway analysis on the 295 phosphoproteins revealed multiple significantly enriched pathways related to insulin signaling, such as mTOR signaling and RhoA signaling. Moreover, phosphorylation levels for numerous regulatory sites in these pathways were significantly changed due to PPP1R12A knockdown. These results indicate that PPP1R12A indeed plays a role in skeletal muscle insulin signaling, providing novel insights into the biology of insulin action. This new information may facilitate the design of experiments to better understand mechanisms underlying skeletal muscle insulin resistance and type 2 diabetes. BIOLOGICAL SIGNIFICANCE These results identify a large number of potential new substrates of serine/threonine protein phosphatase 1 and suggest that serine/threonine protein phosphatase 1 regulatory subunit 12A indeed plays a regulatory role in multiple pathways related to insulin action, providing novel insights into the biology of skeletal muscle insulin signaling. This information may facilitate the design of experiments to better understand the molecular mechanism responsible for skeletal muscle insulin resistance and associated diseases, such as type 2 diabetes and cardiovascular diseases.

Inhibition of glycogen phosphorylation induces changes in cellular proteome and signaling pathways in MIA pancreatic cancer cells

Objectives Novel quantitative proteomic approaches were used to study the effects of inhibition of glycogen phosphorylase on proteome and signaling pathways in MIA PaCa-2 pancreatic cancer cells. Methods We performed quantitative proteomic analysis in MIA PaCa-2 cancer cells treated with a stratified dose of CP-320626 (5-chloro-1H-indole-2-carboxylic acid [1-(4-fuorobenzyl)-2-(4-hydroxypiperidin-1-yl)-2 oxoethyl] amide) (25, 50, and 100 &mgr;M). The effect of metabolic inhibition on cellular protein turnover dynamics was also studied using the modified SILAC (stable isotope labeling with amino acids in cell culture) method. Results A total of 22 protein spots and 4 phosphoprotein spots were quantitatively analyzed. We found that dynamic expression of total proteins and phosphoproteins was significantly changed in MIA PaCa-2 cells treated with an incremental dose of CP-320626. Functional analyses suggested that most of the proteins differentially expressed were in the pathways of mitogen-activated protein kinase/extracellular signal–regulated kinase and tumor necrosis factor &agr;/nuclear factor &kgr;B. Conclusions Signaling pathways and metabolic pathways share many common cofactors and substrates forming an extended metabolic network. The restriction of substrate through 1 pathway such as inhibition of glycogen phosphorylation induces pervasive metabolomic and proteomic changes manifested in protein synthesis, breakdown, and posttranslational modification of signaling molecules. Our results suggest that quantitative proteomic is an important approach to understand the interaction between metabolism and signaling pathways. Abbreviations MALDI - matrix-assisted laser desorption ionization, TOF/TOF MS - time-of-flight/time-of-flight mass spectrometry, 2-DE - 2-dimensional electrophoresis, PMF - peptide mass fingerprinting, CP-320626 - 5-chloro-1H-indole-2-carboxylic acid [1-(4-fuorobenzyl)-2-(4-hydroxypiperidin-1-yl)-2 oxoethyl]amide

Site-Specific Phosphorylation of Protein Phosphatase 1 Regulatory Subunit 12A Stimulated or Suppressed by Insulin

Protein phosphatase 1 (PP1) is one of the major phosphatases responsible for protein dephosphorylation in eukaryotes. So far, only few specific phosphorylation sites of PP1 regulatory subunit 12A (PPP1R12A) have been shown to regulate the PP1 activity. The effect of insulin on PPP1R12A phosphorylation is largely unknown. Utilizing a mass spectrometry based phosphorylation identification and quantification approach, we identified 21 PPP1R12A phosphorylation sites (7 novel sites, including Ser20, Thr22, Thr453, Ser478, Thr671, Ser678, and Ser680) and quantified 16 of them under basal and insulin stimulated conditions in hamster ovary cells overexpressing the insulin receptor (CHO/IR), an insulin sensitive cell model. Insulin stimulated the phosphorylation of PPP1R12A significantly at Ser477, Ser478, Ser507, Ser668, and Ser695, while simultaneously suppressing the phosphorylation of PPP1R12A at Ser509 (more than 2-fold increase or decrease compared to basal). Our data demonstrate that PPP1R12A undergoes insulin stimulated/suppressed phosphorylation, suggesting that PPP1R12A phosphorylation may play a role in insulin signal transduction. The novel PPP1R12A phosphorylation sites as well as the new insulin-responsive phosphorylation sites of PPP1R12A in CHO/IR cells provide targets for investigation of the regulation of PPP1R12A and the PPP1R12A-PP1cδ complex in insulin action and other signaling pathways in other cell models, animal models, and humans.

Smoke-Induced Signal Molecules in Bone Marrow Cells from Altered Low-Density Lipoprotein Receptor-Related Protein 5 Mice

Mechanism underlying smoke-induced loss of bone mass is unknown. In this study, we hypothesized that protein signals induced by smoking in bone marrow may be associated with the loss of bone mass. Using a proteomics approach, we identified 38 proteins differentially expressed in bone marrow cells from low-density lipoprotein receptor-related protein 5 (Lrp5) mice exposed to cigarette smoking. Smoking effects on protein expression in bone marrow among three genotypes (Lrp5(+/+), Lrp5(G171V), and Lrp5(-/-)) varied. On the basis of the ratio of protein expression induced by smoking versus nonsmoking, smoke induced protein expression significantly in wild-type mice compared to the other two genotypes (Lrp5(G171V) and Lrp5(-/-)). These proteins include inhibitors of β-catenin and proteins associated with differentiation of osteoclasts. We observed that S100A8 and S100A9 were overexpressed in human smokers compared to nonsmokers, which confirmed the effect of smoking on the expression of two proteins in Lrp5 mice, suggesting the role of these proteins in bone remodeling. Smoke induced expression of S100A8 and S100A9 in a time-dependent fashion, which was opposite of the changes in the ratio of OPG/RANKL in bone marrow cells, suggesting that the high levels of S100A8 and S100A9 may be associated with smoke-induced bone loss by increasing bone resorption.

Optimization of Search Engines and Postprocessing Approaches to Maximize Peptide and Protein Identification for High-Resolution Mass Data

The two key steps for analyzing proteomic data generated by high-resolution MS are database searching and postprocessing. While the two steps are interrelated, studies on their combinatory effects and the optimization of these procedures have not been adequately conducted. Here, we investigated the performance of three popular search engines (SEQUEST, Mascot, and MS Amanda) in conjunction with five filtering approaches, including respective score-based filtering, a group-based approach, local false discovery rate (LFDR), PeptideProphet, and Percolator. A total of eight data sets from various proteomes (e.g., E. coli, yeast, and human) produced by various instruments with high-accuracy survey scan (MS1) and high- or low-accuracy fragment ion scan (MS2) (LTQ-Orbitrap, Orbitrap-Velos, Orbitrap-Elite, Q-Exactive, Orbitrap-Fusion, and Q-TOF) were analyzed. It was found combinations involving Percolator achieved markedly more peptide and protein identifications at the same FDR level than the other 12 combinations for all data sets. Among these, combinations of SEQUEST-Percolator and MS Amanda-Percolator provided slightly better performances for data sets with low-accuracy MS2 (ion trap or IT) and high accuracy MS2 (Orbitrap or TOF), respectively, than did other methods. For approaches without Percolator, SEQUEST-group performs the best for data sets with MS2 produced by collision-induced dissociation (CID) and IT analysis; Mascot-LFDR gives more identifications for data sets generated by higher-energy collisional dissociation (HCD) and analyzed in Orbitrap (HCD-OT) and in Orbitrap Fusion (HCD-IT); MS Amanda-Group excels for the Q-TOF data set and the Orbitrap Velos HCD-OT data set. Therefore, if Percolator was not used, a specific combination should be applied for each type of data set. Moreover, a higher percentage of multiple-peptide proteins and lower variation of protein spectral counts were observed when analyzing technical replicates using Percolator-associated combinations; therefore, Percolator enhanced the reliability for both identification and quantification. The analyses were performed using the specific programs embedded in Proteome Discoverer, Scaffold, and an in-house algorithm (BuildSummary). These results provide valuable guidelines for the optimal interpretation of proteomic results and the development of fit-for-purpose protocols under different situations.

Proteomics analyses of subcutaneous adipocytes reveal novel abnormalities in human insulin resistance

To provide a more global view of adipocyte changes in human insulin resistance by proteomics analyses.

Quantitative proteomics reveals novel protein interaction partners of PP2A catalytic subunit in pancreatic β-cells.

Protein phosphatase 2A (PP2A) is one of the major serine/threonine phosphatases. We hypothesize that PP2A regulates signaling cascades in pancreatic β-cells in the context of glucose-stimulated insulin secretion (GSIS). Using co-immunoprecipitation (co-IP) and tandem mass spectrometry, we globally identified the protein interaction partners of the PP2A catalytic subunit (PP2Ac) in insulin-secreting pancreatic β-cells. Among the 514 identified PP2Ac interaction partners, 476 were novel. This represents the first global view of PP2Ac protein-protein interactions caused by hyperglycemic conditions. Additionally, numerous PP2Ac partners were found involved in a variety of signaling pathways in the β-cell function, such as insulin secretion. Our data suggest that PP2A interacts with various signaling proteins necessary for physiological insulin secretion as well as signaling proteins known to regulate cell dysfunction and apoptosis in the pancreatic β-cells.