Rongxia Li

Localized-Statistical Quantification of Human Serum Proteome Associated with Type 2 Diabetes

Background Recent advances in proteomics have shed light to discover serum proteins or peptides as biomarkers for tracking the progression of diabetes as well as understanding molecular mechanisms of the disease. Results In this work, human serum of non-diabetic and diabetic cohorts was analyzed by proteomic approach. To analyze total 1377 high-confident serum-proteins, we developed a computing strategy called localized statistics of protein abundance distribution (LSPAD) to calculate a significant bias of a particular protein-abundance between these two cohorts. As a result, 68 proteins were found significantly over-represented in the diabetic serum (p<0.01). In addition, a pathway-associated analysis was developed to obtain the overall pathway bias associated with type 2 diabetes, from which the significant over-representation of complement system associated with type 2 diabetes was uncovered. Moreover, an up-stream activator of complement pathway, ficolin-3, was observed over-represented in the serum of type 2 diabetic patients, which was further validated with statistic significance (p = 0.012) with more clinical samples. Conclusions The developed LSPAD approach is well fit for analyzing proteomic data derived from biological complex systems such as plasma proteome. With LSPAD, we disclosed the comprehensive distribution of the proteins associated with diabetes in different abundance levels and the involvement of ficolin-related complement activation in diabetes.

A comprehensive and non-prefractionation on the protein level approach for the human urinary proteome: touching phosphorylation in urine

Increasing attention has been paid to the urinary proteome because it holds the promise of discovering various disease biomarkers. However, most of the urine proteomics studies routinely relied on protein pre-fractionation and so far did not present characterization on phosphorylation status. Two robust approaches, integrated multidimensional liquid chromatography (IMDL) and Yin-yang multidimensional liquid chromatography (MDLC) tandem mass spectrometry, were recently developed in our laboratory, with high-coverage identification of peptide mixtures. In this study, we adopted a strategy without pre-fractionation on the protein level for urinary proteome identification, using both the IMDL and the Yin-yang MDLC methods for peptide fractionation followed by identification using a linear ion trap-orbitrap (LTQ-Orbitrap) mass spectrometer with high resolution and mass accuracy. A total of 1310 non-redundant proteins were highly confidently identified from two experiments, significantly including 59 phosphorylation sites. More than half the annotated identifications were membrane-related proteins. In addition, the lysosomal as well as kidney-associated proteins were detected. Compared with the six largest datasets of urinary proteins published previously, we found our data included most of the reported proteins. Our study developed a robust approach for exploring the human urinary proteome, which would provide a catalogue of urine proteins on a global scale. It is the first report, to our best knowledge, to profile the urinary phosphoproteome. This work significantly extends current comprehension of urinary protein modification and its potential biological significance. Moreover, the strategy could further serve as a reference for biomarker discovery.

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.

Systematic variations associated with renal disease uncovered by parallel metabolomics of urine and serum

BackgroundMembranous nephropathy is an important glomerular disease characterized by podocyte injury and proteinuria, but no metabolomics research was reported as yet. Here, we performed a parallel metabolomics study, based on human urine and serum, to comprehensively profile systematic metabolic variations, identify differential metabolites, and understand the pathogenic mechanism of membranous nephropathy.ResultsThere were obvious metabolic distinctions between the membranous nephropathy patients with urine protein lower than 3.5 g/24 h (LUPM) and those higher than 3.5 g/24 h (HUPM) by Partial Least Squares Discriminant Analysis (PLS-DA) model analysis. In total, 26 urine metabolites and 9 serum metabolites were identified to account for such differences, and the majority of metabolites were significantly increased in HUPM patients for both urines and serums. Combining the results of urine with serum, all differential metabolites were classified to 5 classes. This classification helps globally probe the systematic metabolic alterations before and after blood flowing through kidney. Citric acid and 4 amino acids were markedly increased only in the serum samples of HUPM patients, implying more impaired filtration function of kidneys of HUPM patients than LUPM patients. The dicarboxylic acids, phenolic acids, and cholesterol were significantly elevated only in urines of HUPM patients, suggesting more severe oxidative attacks than LUPM patients.ConclusionsParallel metabolomics of urine and serum revealed the systematic metabolic variations associated with LUPM and HUPM patients, where HUPM patients suffered more severe injury of kidney function and oxidative stresses than LUPM patients. This research exhibited a promising application of parallel metabolomics in renal diseases.

Large Scale Phosphoproteome Profiles Comprehensive Features of Mouse Embryonic Stem Cells

Embryonic stem cells are pluripotent and capable of unlimited self-renewal. Elucidation of the underlying molecular mechanism may contribute to the advancement of cell-based regenerative medicine. In the present work, we performed a large scale analysis of the phosphoproteome in mouse embryonic stem (mES) cells. Using multiplex strategies, we detected 4581 proteins and 3970 high confidence distinct phosphosites in 1642 phosphoproteins. Notably, 22 prominent phosphorylated stem cell marker proteins with 39 novel phosphosites were identified for the first time by mass spectrometry, including phosphorylation sites in NANOG (Ser-65) and RE1 silencing transcription factor (Ser-950 and Thr-953). Quantitative profiles of NANOG peptides obtained during the differentiation of mES cells revealed that the abundance of phosphopeptides and non-phosphopeptides decreased with different trends. To our knowledge, this study presents the largest global characterization of phosphorylation in mES cells. Compared with a study of ultimately differentiated tissue cells, a bioinformatics analysis of the phosphorylation data set revealed a consistent phosphorylation motif in human and mouse ES cells. Moreover, investigations into phosphorylation conservation suggested that phosphoproteins were more conserved in the undifferentiated ES cell state than in the ultimately differentiated tissue cell state. However, the opposite conclusion was drawn from this conservation comparison with phosphosites. Overall, this work provides an overview of phosphorylation in mES cells and is a valuable resource for the future understanding of basic biology in mES cells.

Urinary pigment epithelium-derived factor as a marker of diabetic nephropathy.

Background: Pigment epithelium-derived factor (PEDF), a serine protease inhibitor, regulates extracellular matrix production in the kidney. We sought the association between urinary PEDF (uPEDF) and development of nephropathy among patients with type 2 diabetes (T2DM). Methods: Two human studies were performed in which uPEDF was determined by ELISA. These studies included (1) a cross-sectional study of T2DM (n = 228) and healthy controls (n = 49) and (2) a longitudinal study of hypertensive T2DM with microalbuminuria (MA; n = 42) treated with irbesartan for 6 months. An animal study was performed in which PEDF was measured in the kidney and urine samples of control rats, rats rendered diabetic with streptozotocin that were also fed a high-fat diet, and diabetic rats treated with irbesartan for 3 months. Results: Cross-sectional study: compared to controls, uPEDF was significantly higher in patients with diabetic nephropathy. uPEDF independently correlated with MA. In the MA group, uPEDF in patients with diabetic retinopathy was significantly higher than that in patients without diabetic retinopathy. Longitudinal study: irbesartan significantly decreased uPEDF in T2DM with MA. Animal study: in diabetic rats, increased PEDF was observed in both the urine and kidney samples. uPEDF showed a significant correlation with the expression of PEDF in the kidney. Irbesartan could significantly decrease the PEDF expression in the kidneys of diabetic rats as well as uPEDF. Conclusion: uPEDF may serve as a novel marker for screening for nephropathy among patients with T2DM and monitoring the response to therapy.

Fractionation of complex protein mixture by virtual three-dimensional liquid chromatography based on combined pH and salt steps

The complexity and diversity of biological samples in proteomics require intensive fractionation ahead of mass spectrometry identification. This work developed a chromatographic method called virtual three-dimensional chromatography to fractionate complex protein mixtures. By alternate elution with different pHs and salt concentrations, we implemented pH and salt steps by turns on a single strong cation exchange column to fully exploit its chromatographic ability. Given standard proteins that were not resolved solely by pH or salt gradient elution could be successfully separated using this combined mode. With a reversed phase column tandem connected behind, we further fractionated as well as desalted proteins as the third dimension. This present strategy could readily be adapted with respect to special complexity of biological samples. Crude plasma without depleting high abundance proteins were fractionated by this three-dimensional mode and then analyzed by reversed phase liquid chromatography coupled with LTQ mass spectrometry. In total, 1933 protein groups with wide dynamic ranges were identified from a single experiment. Some characteristics that correlated to the behavior of proteins on strong cation exchange columns are also discussed.

Hsp90α forms a stable complex at the cilium neck for the interaction of signalling molecules in IGF-1 receptor signalling.

ABSTRACT The primary cilium is composed of an axoneme that protrudes from the cell surface, a basal body beneath the membrane and a transition neck in between. It is a sensory organelle on the plasma membrane, involved in mediating extracellular signals. In the transition neck region of the cilium, the microtubules change from triplet to doublet microtubules. This region also contains the transition fibres that crosslink the axoneme with the membrane and the necklace proteins that regulate molecules being transported into and out of the cilium. In this protein-enriched, complex area it is important to maintain the correct assembly of all of these proteins. Here, through immunofluorescent staining and protein isolation, we identify the molecular chaperone Hsp90&agr; clustered at the periciliary base. At the transition neck region, phosphorylated Hsp90&agr; forms a stable ring around the axoneme. Heat shock treatment causes Hsp90&agr; to dissipate and induces resorption of cilia. We further identify that Hsp90&agr; at the transition neck region represents a signalling platform on which IRS-1 interacts with intracellular downstream signalling molecules involved in IGF-1 receptor signalling.

Early Prediction of Developing Type 2 Diabetes by Plasma Acylcarnitines: Population-Based Study

OBJECTIVE Acylcarnitines were suggested as early biomarkers even prior to insulin resistance in animal studies, but their roles in predicting type 2 diabetes were unknown. Therefore, we aimed to determine whether acylcarnitines could independently predict type 2 diabetes by using a targeted metabolic profiling approach. RESEARCH DESIGN AND METHODS A population-based prospective study was conducted among 2,103 community-living Chinese individuals aged 50–70 years from Beijing and Shanghai with a mean follow-up duration of 6 years. Fasting glucose, glycohemoglobin, and insulin were determined at baseline and in a follow-up survey. Baseline plasma acylcarnitines were profiled by liquid chromatography–tandem mass spectrometry. RESULTS Over the 6-year period, 507 participants developed diabetes. A panel of acylcanitines, especially with long chain, was significantly associated with increased risk of type 2 diabetes. The relative risks of type 2 diabetes per SD increase of the predictive model score were 2.48 (95% CI 2.20–2.78) for the conventional and 9.41 (95% CI 7.62–11.62) for the full model including acylcarnitines, respectively. Moreover, adding selected acylcarnitines substantially improved predictive ability for incident diabetes, as area under the receiver operator characteristic curve improved to 0.89 in the full model compared with 0.73 in the conventional model. Similar associations were obtained when the predictive models were established separately among Beijing or Shanghai residents. CONCLUSIONS A panel of acylcarnitines, mainly involving mitochondrial lipid dysregulation, significantly improved predictive ability for type 2 diabetes beyond conventional risk factors. These findings need to be replicated in other populations, and the underlying mechanisms should be elucidated.

Secretome-derived isotope tags (SDIT) reveal adipocyte-derived apolipoprotein C-I as a predictive marker for cardiovascular disease.

We developed a quantitative strategy, named secretome-derived isotopic tag (SDIT), to concurrently identify and quantify the adipocyte-secreted plasma proteins from normal and high-fat-diet (HFD) induced obese mice, based on the application of isotope-labeled secreted proteins from cultured mouse adipocytes as internal standards. We detected 197 proteins with significant changes between normal and obese mice plasma. Importantly, a novel adipocyte-secreted plasma protein, apolipoprotein C-I (apoC-I), significantly increased in the obese mice plasma. The expression and secretion of adipocyte apoC-I was detected in differentiated 3T3-L1 and primary rat adipocytes. Our in vitro experiments proved that functional Golgi apparatus was required for apoC-I secretion. Additionally, obese mice had increased apoC-I production in adipose tissue. Population survey of 367 participants showed that the plasma level of apoC-I was significantly increased in obese individuals compared with healthy individuals. After multiple adjustments for age and sex, the odds ratios for risk factors of cardiovascular disease including high LDL cholesterol, hypercholesterolemia, and hypertriglyceridemia, respectively, were used to compare the highest with the lowest apoC-I quartile. Taken together, our studies provide a novel strategy to concurrently identify and quantify tissue-specific secreted proteins. This strategy can be used to identify the largest global characterization of adipocyte-derived plasma proteome and provides a potential disease-related biomarker for clinical diagnoses. By selectively analyzing adipocyte-secreted proteins in plasma from obese vs lean murine and/or human subjects, we discovered that apoC-I is an adipocyte-secreted plasma protein and a predictive marker for cardiovascular disease.