Small-protein Enrichment Assay Enables the Rapid, Unbiased Analysis of Over 100 Low Abundance Factors from Human Plasma.

Unbiased and sensitive quantification of low abundance small proteins in human plasma (e.g. hormones, immune factors, metabolic regulators) remains an unmet need. These small protein factors are typically analyzed individually and using antibodies that can lack specificity. Mass spectrometry (MS)-based proteomics has the potential to address these problems, however the analysis of plasma by MS is plagued by the extremely large dynamic range of this body fluid, with protein abundances spanning at least 13 orders of magnitude. Here we describe an enrichment assay (SPEA), that greatly simplifies the plasma dynamic range problem by enriching small-proteins of 2-10 kDa, enabling the rapid, specific and sensitive quantification of >100 small-protein factors in a single untargeted LC-MS/MS acquisition. Applying this method to perform deep-proteome profiling of human plasma we identify C5ORF46 as a previously uncharacterized human plasma protein. We further demonstrate the reproducibility of our workflow for low abundance protein analysis using a stable-isotope labeled protein standard of insulin spiked into human plasma. SPEA provides the ability to study numerous important hormones in a single rapid assay, which we applied to study the intermittent fasting response and observed several unexpected changes including decreased plasma abundance of the iron homeostasis regulator hepcidin.

Tankyrase modulates insulin sensitivity in skeletal muscle cells by regulating the stability of GLUT4 vesicle proteins.

Tankyrase 1 and 2, members of the poly(ADP-ribose) polymerase family, have previously been shown to play a role in insulin-mediated glucose uptake in adipocytes. However, their precise mechanism of action, and their role in insulin action in other cell types, such as myocytes, remains elusive. Treatment of differentiated L6 myotubes with the small molecule tankyrase inhibitor XAV939 resulted in insulin resistance as determined by impaired insulin-stimulated glucose uptake. Proteomic analysis of XAV939-treated myotubes identified down-regulation of several glucose transporter GLUT4 storage vesicle (GSV) proteins including RAB10, VAMP8, SORT1, and GLUT4. A similar effect was observed following knockdown of tankyrase 1 in L6 myotubes. Inhibition of the proteasome using MG132 rescued GSV protein levels as well as insulin-stimulated glucose uptake in XAV939-treated L6 myotubes. These studies reveal an important role for tankyrase in maintaining the stability of key GLUT4 regulatory proteins that in turn plays a role in regulating cellular insulin sensitivity.

Preprocessing significantly improves the peptide/protein identification sensitivity of high-resolution isobarically labeled tandem mass spectrometry data.

Isobaric labeling techniques coupled with high-resolution mass spectrometry have been widely employed in proteomic workflows requiring relative quantification. For each high-resolution tandem mass spectrum (MS/MS), isobaric labeling techniques can be used not only to quantify the peptide from different samples by reporter ions, but also to identify the peptide it is derived from. Because the ions related to isobaric labeling may act as noise in database searching, the MS/MS spectrum should be preprocessed before peptide or protein identification. In this article, we demonstrate that there are a lot of high-frequency, high-abundance isobaric related ions in the MS/MS spectrum, and removing isobaric related ions combined with deisotoping and deconvolution in MS/MS preprocessing procedures significantly improves the peptide/protein identification sensitivity. The user-friendly software package TurboRaw2MGF (v2.0) has been implemented for converting raw TIC data files to mascot generic format files and can be downloaded for free from https://github.com/shengqh/RCPA.Tools/releases as part of the software suite ProteomicsTools. The data have been deposited to the ProteomeXchange with identifier PXD000994.

PGC1α Controls Sucrose Taste Sensitization in Drosophila.

Perceived palatability of food controls caloric intake. Sweet taste is the primary means of detecting the carbohydrate content of food. Surprisingly, sweet taste sensitivity is responsive to extrinsic factors like diet, and this occurs by unknown mechanisms. Here, we describe an unbiased proteomic investigation into sweet taste sensitivity in the fruit fly. We identify a dopamine/cyclic AMP (cAMP)/CREB axis acting within sweet taste neurons that controls taste perception but is largely dispensable for acute taste transduction. This pathway modulates sweet taste perception in response to both sensory- and nutrient-restricted diets and converges on PGC1α, a critical regulator of metabolic health and lifespan. By electrophysiology, we found that enhanced sucrose taste sensitivity was the result of heightened sweet taste intensity and that PGC1α was both necessary and sufficient for this effect. Together, we provide the first molecular insight into how diet-induced taste perception is regulated within the sweet taste neuron.

Type 2 diabetes-associated single nucleotide polymorphism in Sorcs1 gene results in alternative processing of the Sorcs1 protein in INS1 ß-cells.

A threonine-to-Isoleucine (Thr52Ile) mutation within the pro-domain of the Sorcs1 gene was positionally cloned as the gene underlying a quantitative trait locus that affects fasting insulin levels in mice. In humans, genome-wide association studies and linkage studies have shown that SORCS1 is associated with diabetes and all of diabetes complications. We have recently shown that deletion of Sorcs1 in mice made obese with the leptinob mutation results in diabetes and an insulin granule stability defect. This present study investigates the functional consequence of the Sorcs1 Thr52Ile mutation in the rat INS1 ß-cell line expressing either the wildtype or mutant Sorcs1 allele. We find that Sorcs1 Thr52Ile mutation is associated with increased basal insulin secretion, reduced glucose-stimulated insulin secretion and decreased insulin content in INS1 cells. Moreover, expression of Thr52Ile causes differential processing of the Sorcs1 protein resulting in the formation of an additional 90 kDa mutant form of the protein. The mutant form of the protein is localised to the ER, retains its pro-domain, and concurrently reduces expression of the functional mature 130 kDa Sorcs1 protein. These findings provide a mechanistic clue to why this specific allelic variation in Sorcs1 was associated with reduced insulin levels and type 2 diabetes.

Global redox proteome and phosphoproteome analysis reveals redox switch in Akt.

Protein oxidation sits at the intersection of multiple signalling pathways, yet the magnitude and extent of crosstalk between oxidation and other post-translational modifications remains unclear. Here, we delineate global changes in adipocyte signalling networks following acute oxidative stress and reveal considerable crosstalk between cysteine oxidation and phosphorylation-based signalling. Oxidation of key regulatory kinases, including Akt, mTOR and AMPK influences the fidelity rather than their absolute activation state, highlighting an unappreciated interplay between these modifications. Mechanistic analysis of the redox regulation of Akt identified two cysteine residues in the pleckstrin homology domain (C60 and C77) to be reversibly oxidized. Oxidation at these sites affected Akt recruitment to the plasma membrane by stabilizing the PIP3 binding pocket. Our data provide insights into the interplay between oxidative stress-derived redox signalling and protein phosphorylation networks and serve as a resource for understanding the contribution of cellular oxidation to a range of diseases.

The transcriptional response to oxidative stress is part of, but not sufficient for, insulin resistance in adipocytes.

Insulin resistance is a major risk factor for metabolic diseases such as Type 2 diabetes. Although the underlying mechanisms of insulin resistance remain elusive, oxidative stress is a unifying driver by which numerous extrinsic signals and cellular stresses trigger insulin resistance. Consequently, we sought to understand the cellular response to oxidative stress and its role in insulin resistance. Using cultured 3T3-L1 adipocytes, we established a model of physiologically-derived oxidative stress by inhibiting the cycling of glutathione and thioredoxin, which induced insulin resistance as measured by impaired insulin-stimulated 2-deoxyglucose uptake. Using time-resolved transcriptomics, we found > 2000 genes differentially-expressed over 24 hours, with specific metabolic and signalling pathways enriched at different times. We explored this coordination using a knowledge-based hierarchical-clustering approach to generate a temporal transcriptional cascade and identify key transcription factors responding to oxidative stress. This response shared many similarities with changes observed in distinct insulin resistance models. However, an anti-oxidant reversed insulin resistance phenotypically but not transcriptionally, implying that the transcriptional response to oxidative stress is insufficient for insulin resistance. This suggests that the primary site by which oxidative stress impairs insulin action occurs post-transcriptionally, warranting a multi-level 'trans-omic' approach when studying time-resolved responses to cellular perturbations.

Systems Signatures Reveal Unique Remission-path of Type 2 Diabetes Following Roux-en-Y Gastric Bypass Surgery.

Roux-en-Y Gastric bypass surgery (RYGB) is emerging as a powerful tool for treatment of obesity and may also cause remission of type 2 diabetes. However, the molecular mechanism of RYGB leading to diabetes remission independent of weight loss remains elusive. In this study, we profiled plasma metabolites and proteins of 10 normal glucose-tolerant obese (NO) and 9 diabetic obese (DO) patients before and 1-week, 3-months, 1-year after RYGB. 146 proteins and 128 metabolites from both NO and DO groups at all four stages were selected for further analysis. By analyzing a set of bi-molecular associations among the corresponding network of the subjects with our newly developed computational method, we defined the represented physiological states (called the edge-states that reflect the interactions among the bio-molecules), and the related molecular networks of NO and DO patients, respectively. The principal component analyses (PCA) revealed that the edge states of the post-RYGB NO subjects were significantly different from those of the post-RYGB DO patients. Particularly, the time-dependent changes of the molecular hub-networks differed between DO and NO groups after RYGB. In conclusion, by developing molecular network-based systems signatures, we for the first time reveal that RYGB generates a unique path for diabetes remission independent of weight loss.

De novo identification and quantification of single amino-acid variants in human brain.

The detection of single amino-acid variants (SAVs) usually depends on single-nucleotide polymorphisms (SNPs) database. Here, we describe a novel method that discovers SAVs at proteome level independent of SNPs data. Using mass spectrometry-based de novo sequencing algorithm, peptide-candidates are identified and compared with theoretical protein database to generate SAVs under pairing strategy, which is followed by database re-searching to control false discovery rate. In human brain tissues, we can confidently identify known and novel protein variants with diverse origins. Combined with DNA/RNA sequencing, we verify SAVs derived from DNA mutations, RNA alternative splicing, and unknown post-transcriptional mechanisms. Furthermore, quantitative analysis in human brain tissues reveals several tissue-specific differential expressions of SAVs. This approach provides a novel access to high-throughput detection of protein variants, which may offer the potential for clinical biomarker discovery and mechanistic research.

SRMBuilder: a user-friendly tool for selected reaction monitoring data analysis.

With high sensitivity and reproducibility, selected reaction monitoring (SRM) has become increasingly popular in proteome research for targeted quantification of low abundance proteins and post translational modification. SRM is also well accepted in other mass-spectrometry based research areas such as lipidomics and metabolomics, which necessitates the development of easy-to-use software for both post-acquisition SRM data analysis and quantification result validation. Here, we introduce a software tool SRMBuilder, which can automatically parse SRM data in multiple file formats, assign transitions to compounds, match light/heavy transition/compound pairs and provide a user-friendly graphic interface to manually validate the quantification result at transition/compound/sample level. SRMBuilder will greatly facilitate processing of the post-acquisition data files and validation of quantification result for SRM. The software can be downloaded for free from http://www.proteomics.ac.cn/software/proteomicstools/index.htm as part of the software suite ProteomicsTools.

Quantitative detection of single amino acid polymorphisms by targeted proteomics.

Single-nucleotide polymorphisms (SNPs) are recognized as one kind of major genetic variants in population scale. However, polymorphisms at the proteome level in population scale remain elusive. In the present study, we named amino acid variances derived from SNPs within coding regions as single amino acid polymorphisms (SAPs) at the proteome level, and developed a pipeline of non-targeted and targeted proteomics to identify and quantify SAP peptides in human plasma. The absolute concentrations of three selected SAP-peptide pairs among 290 Asian individuals were measured by selected reaction monitoring (SRM) approach, and their associations with both obesity and diabetes were further analyzed. This work revealed that heterozygotes and homozygotes with various SAPs in a population could have different associations with particular traits. In addition, the SRM approach allows us for the first time to separately measure the absolute concentration of each SAP peptide in the heterozygotes, which also shows different associations with particular traits.