Proteomics Reveals New Salt Responsive Proteins Associated with Rice Plasma Membrane

The signaling processes in plants that initiate cellular responses to biotic and abiotic factors are believed to be located in the plasma membrane (PM). A better understanding of the PM proteome response to environmental stresses might lead to new strategies for improving stress-tolerant crops. A sub-cellular proteomics approach was applied to monitor changes in abundance of PM-associated protein in response to salinity, a key abiotic stress affecting rice productivity worldwide. Proteome was extracted from a root plasma-membrane-rich fraction of a rice salt tolerant variety, IR651, grown under saline and normal conditions. Comparative two-dimensional electrophoresis revealed that 24 proteins were differentially expressed in response to salt stress. From these, eight proteins were identified by mass spectrometry analysis. Most of the proteins identified are likely to be PM-associated and are known to be involved in several important mechanisms of plant adaptation to salt stress. These include regulation of PM pumps and channels, membrane structure, oxidative stress defense, signal transduction, protein folding, and the methyl cycle. To investigate the correlation between mRNA and protein level in response to salinity, we performed quantitative Real-Time PCR analysis of three genes that were salt responsive at the protein level, including 1,4-Benzoquinone reductase, a putative remorin and a hypersensitive induced response protein. No concordance was detected between the changes in levels of gene and protein expression. Our results indicate that the proteomics approach is suitable for expression analysis of membrane associated proteins under salt stress.     

Proteomics reveals new salt responsive proteins associated with rice plasma membrane

The signaling processes in plants that initiate cellular responses to biotic and abiotic factors are believed to be located in the plasma membrane (PM). A better understanding of the PM proteome response to environmental stresses might lead to new strategies for improving stress-tolerant crops. A sub-cellular proteomics approach was applied to monitor changes in abundance of PM-associated protein in response to salinity, a key abiotic stress affecting rice productivity worldwide. Proteome was extracted from a root plasma-membrane-rich fraction of a rice salt tolerant variety, IR651, grown under saline and normal conditions. Comparative two-dimensional electrophoresis revealed that 24 proteins were differentially expressed in response to salt stress. From these, eight proteins were identified by mass spectrometry analysis. Most of the proteins identified are likely to be PM-associated and are known to be involved in several important mechanisms of plant adaptation to salt stress. These include regulation of PM pumps and channels, membrane structure, oxidative stress defense, signal transduction, protein folding, and the methyl cycle. To investigate the correlation between mRNA and protein level in response to salinity, we performed quantitative Real-Time PCR analysis of three genes that were salt responsive at the protein level, including 1,4-Benzoquinone reductase, a putative remorin and a hypersensitive induced response protein. No concordance was detected between the changes in levels of gene and protein expression. Our results indicate that the proteomics approach is suitable for expression analysis of membrane associated proteins under salt stress.     

Statistical identification of differentially labeled peptides from liquid chromatography tandem mass spectrometry

LC-MS/MS with certain labeling techniques such as isotope-coded affinity tag (ICAT) enables quantitative analysis of paired protein samples. However, current identification and quantification of differentially expressed peptides (and proteins) are not reliable for large proteomics screening of complex biological samples. The number of replicates is often limited because of the high cost of experiments and the limited supply of samples. Traditionally, a simple fold change cutoff is used, which results in a high rate of false positives. Standard statistical methods such as the two-sample t-test are unreliable and severely underpowered due to high variability in LC-MS/MS data, especially when only a small number of replicates are available. Using an advanced error pooling technique, we propose a novel statistical method that can reliably identify differentially expressed proteins while maintaining a high sensitivity, particularly with a small number of replicates. The proposed method was applied both to an extensive simulation study and a proteomics comparison between microparticles (MPs) generated from platelet (platelet MPs) and MPs isolated from plasma (plasma MPs). In these studies, we show a significant improvement of our statistical analysis in the identification of proteins that are differentially expressed but not detected by other statistical methods. In particular, several important proteins - two peptides for beta-globin and three peptides for von Willebrand Factor (vWF) - were identified with very small false discovery rates (FDRs) by our method, while none was significant when other conventional methods were used. These proteins have been reported with their important roles in microparticles in human blood cells: vWF is a platelet and endothelial cell product that binds to P-selectin, GP1b, and GP IIb/IIIa, and beta-globin is one of the peptides of hemoglobin involved in the transportation of oxygen by red blood cells.     

Protein alterations associated with pancreatic cancer and chronic pancreatitis found in human plasma using global quantitative proteomics profiling

Pancreatic cancer is a lethal disease that is difficult to diagnose at early stages when curable treatments are effective. Biomarkers that can improve current pancreatic cancer detection would have great value in improving patient management and survival rate. A large scale quantitative proteomics study was performed to search for the plasma protein alterations associated with pancreatic cancer. The enormous complexity of the plasma proteome and the vast dynamic range of protein concentration therein present major challenges for quantitative global profiling of plasma. To address these challenges, multidimensional fractionation at both protein and peptide levels was applied to enhance the depth of proteomics analysis. Employing stringent criteria, more than 1300 proteins total were identified in plasma across 8-orders of magnitude in protein concentration. Differential proteins associated with pancreatic cancer were identified, and their relationship with the proteome of pancreatic tissue and pancreatic juice from our previous studies was discussed. A subgroup of differentially expressed proteins was selected for biomarker testing using an independent cohort of plasma and serum samples from well-diagnosed patients with pancreatic cancer, chronic pancreatitis, and nonpancreatic disease controls. Using ELISA methodology, the performance of each of these protein candidates was benchmarked against CA19-9, the current gold standard for a pancreatic cancer blood test. A composite marker of TIMP1 and ICAM1 demonstrate significantly better performance than CA19-9 in distinguishing pancreatic cancer from the nonpancreatic disease controls and chronic pancreatitis controls. In addition, protein AZGP1 was identified as a biomarker candidate for chronic pancreatitis. The discovery and technical challenges associated with plasma-based quantitative proteomics are discussed and may benefit the development of plasma proteomics technology in general. The protein candidates identified in this study provide a biomarker candidate pool for future investigations.     

Proteomic profiling of human pleural effusion using two-dimensional nano liquid chromatography tandem mass spectrometry

Pleural effusion, an accumulation of pleural fluid, contains proteins originated from plasma filtrate and, especially when tissues are damaged, parenchyma interstitial spaces of lungs and/or other organs. This study details protein profiles in human pleural effusion from 43 lung adenocarcinoma patients by a two-dimensional nano-high performance liquid chromatography electrospray ionization tandem mass spectrometry (2D nano-HPLC-ESI-MS/MS) system. The experimental results revealed the identification of 1415 unique proteins from human pleural effusion. Among these 124 proteins identified with higher confidence levels, some proteins have not been reported in plasma and may represent proteins specifically present in pleural effusion. These proteins are valuable for mass identification of differentially expressed proteins involved in proteomics database and screening biomarker to further study in human lung adenocarcinoma. The significance of the use of proteomics analysis of human pleural fluid for the search of new lung cancer marker proteins, and for their simultaneous display and analysis in patients suffering from lung disorders has been examined.     

Proteomic Profiling of Mouse Helper T Cell Differentiation

Helper T cell differentiation is a key process in the regulation of adaptive immune responses. Here, mouse Th1 and Th2 cells are profiled using high‐throughput proteomics to increase the understanding of the molecular biology of Th differentiation to support the design of prophylactic and therapeutic intervention strategies for (infectious) diseases. Protein profiling of Th1/Th2 differentiated cells results in the quantification of almost 6000 proteins of which 41 are differentially expressed at FDR < 0.1, and 19 at the FDR < 0.05 level, respectively. Differential protein expression analysis identifies a number of the expected canonical Th differentiation markers, and gene set analysis using the REACTOME database and a hypergeometric test (FDR < 0.05) confirms that helper T cell pathways are the top sets that are differentially expressed. Additionally, by network analysis, many differentially expressed proteins are associated with the Th1 and Th2 pathways. Data are available via PRIDE database with identifier PXD004532.     

Proteomic analysis and identification of aqueous humor proteins with a pathophysiological role in diabetic retinopathy

Diabetic retinopathy (DR) can cause irreversible blindness and is the severest microvascular complication in the eyes of patients with diabetic mellitus (DM). The identification of susceptibility factors contributing to development of DR is helpful for identifying predisposed patients and improving treatment efficacy. Although proteomics analysis is useful for identifying protein markers related to diseases, it has never been used to explore DR-associated susceptibility factors in the aqueous humor (AH). To better understand the pathophysiology of DR and to identify DR-associated risk factors, a gel-based proteomics analysis was performed to compare AH protein profiles of DM patients with and without development of DR. MALDI-TOF MS was then performed to identify protein spots that were differentially expressed between the two groups and western blot analysis was used to validate the expressional change of protein demonstrated by proteomics. Our proteomics and bioinformatics analysis identified 11 proteins differentially expressed between DR and control groups. These proteins are linked to biological networks associated with nutrition transport, microstructure reorganization, angiogenesis, anti-oxidation, and neuroprotection. The data may provide potential AH biomarkers and susceptibility factors for predicting DR development, and provide an insight into the underlying pathophysiological mechanisms of DR. This article is part of a Special Issue entitled: Proteomics: The clinical link.     

Further evidence for a role of endothelin-1 (ET-1) in critical limb ischaemia

Critical limb ischaemia (CLI), due to atherosclerotic arterial occlusion, affects over 20,000 people per year in the United Kingdom with many facing lower limb amputation and early death. A role for endothelin-1 (ET-1) in atherosclerosis is well-established and increased circulating and tissue levels of this peptide have been detected in patients with CLI. ET-1 and its receptors were identified in atherosclerotic popliteal arteries obtained from CLI patients undergoing lower limb amputation. In addition, plasma ET-1 levels were compared with those of non-ischaemic controls. ET-1 was associated with regions of atherosclerotic plaque, particularly in regions with high macrophage content. This peptide was also associated with endothelial cells lining the main vessel lumen as well as adventitial microvessels. ET_A and ET_B receptors were located within regions of plaque, adventitial microvessels and perivascular nerves. There was a statistically significant increase (P < 0.001) in plasma ET-1 in CLI patients when compared with controls. These results reveal sources of ET-1 in atherosclerotic popliteal arteries that potentially contribute to increased circulating levels of this peptide. Identification of variable receptor distributions in ischaemic tissue suggests a therapeutic potential of selective receptor targeting in patients with CLI.     

Proteomic analysis of ligamentum flavum from patients with lumbar spinal stenosis

Lumbar spinal stenosis (LSS) is a syndromic degenerative spinal disease and is characterized by spinal canal narrowing with subsequent neural compression causing gait disturbances. Although LSS is a major age‐related musculoskeletal disease that causes large decreases in the daily living activities of the elderly, its molecular pathology has not been investigated using proteomics. Thus, we used several proteomic technologies to analyze the ligamentum flavum (LF) of individuals with LSS. Using comprehensive proteomics with strong cation exchange fractionation, we detected 1288 proteins in these LF samples. A GO analysis of the comprehensive proteome revealed that more than 30% of the identified proteins were extracellular. Next, we used 2D image converted analysis of LC/MS to compare LF obtained from individuals with LSS to that obtained from individuals with disc herniation (nondegenerative control). We detected 64 781 MS peaks and identified 1675 differentially expressed peptides derived from 286 proteins. We verified four differentially expressed proteins (fibronectin, serine protease HTRA1, tenascin, and asporin) by quantitative proteomics using SRM/MRM. The present proteomic study is the first to identify proteins from degenerated and hypertrophied LF in LSS, which will help in studying LSS.     

Proteomics for the analysis of the Candida albicans biofilm lifestyle

Candida albicans is an opportunistic pathogenic fungus capable of causing infections in immunocompromised patients. Candidiasis is often associated with the formation of biofilms on the surface of inert or biological materials. Biofilms are structured microbial communities attached to a surface and encased within a matrix of exopolymeric substance (EPS). At present, very little is known about the changes in protein profiles that occur during the transition from the planktonic to the biofilm mode of growth. Here, we report the use of proteomics for the comparative analysis of subcellular fractions obtained from C. albicans biofilm and planktonic cultures, including cell surface-associated proteins and secreted components present in liquid culture supernatants (for planktonic cultures) and EPS (for biofilms). The analysis revealed a high degree of similarity between the protein profiles associated with the planktonic and biofilm extracts, and led to the identification of several differentially expressed protein spots. Among the differentially expressed proteins, there was a preponderance of metabolic enzymes that have been described as cell surface proteins and immunodominant antigens. Proteins found in the biofilm matrix included a few predicted to form part of the secretome, and also many secretion-signal-less proteins. These observations contribute to our understanding of the C. albicans biofilm lifestyle.     

White spot syndrome virus proteins and differentially expressed host proteins identified in shrimp epithelium by shotgun proteomics and cleavable isotope-coded affinity tag

Shrimp subcuticular epithelial cells are the initial and major targets of white spot syndrome virus (WSSV) infection. Proteomic studies of WSSV-infected subcuticular epithelium of Penaeus monodon were performed through two approaches, namely, subcellular fractionation coupled with shotgun proteomics to identify viral and host proteins and a quantitative time course proteomic analysis using cleavable isotope-coded affinity tags (cICATs) to identify differentially expressed cellular proteins. Peptides were analyzed by offline coupling of two-dimensional liquid chromatography with matrix-assisted laser desorption ionization-tandem time of flight mass spectrometry. We identified 27, 20, and 4 WSSV proteins from cytosolic, nuclear, and membrane fractions, respectively. Twenty-eight unique WSSV proteins with high confidence (total ion confidence interval percentage [CI%], >95%) were observed, 11 of which are reported here for the first time, and 3 of these novel proteins were shown to be viral nonstructural proteins by Western blotting analysis. A first shrimp protein data set containing 1,999 peptides (ion score, > or =20) and 429 proteins (total ion score CI%, >95%) was constructed via shotgun proteomics. We also identified 10 down-regulated proteins and 2 up-regulated proteins from the shrimp epithelial lysate via cICAT analysis. This is the first comprehensive study of WSSV-infected epithelia by proteomics. The 11 novel viral proteins represent the latest addition to our knowledge of the WSSV proteome. Three proteomic data sets consisting of WSSV proteins, epithelial cellular proteins, and differentially expressed cellular proteins generated in the course of WSSV infection provide a new resource for further study of WSSV-shrimp interactions.     

Proteomic analysis of an immortalized mouse pancreatic stellate cell line identifies differentially-expressed proteins in activated vs nonproliferating cell states

Pancreatic stellate cells (PaSC) are mediators in chronic pancreatitis and pancreatic cancer pathogenesis. Proteins regulating the biomolecular pathways involved in the conversion of activated to quiescent PaSC may have a significant influence in the development of chronic pancreatitis. We aim to compare differentially expressed proteins from an immortalized cell line of mouse PaSC in the activated and serum-starved cell states using mass spectrometry-based proteomics. PaSC cultured in media supplemented with fetal bovine serum (FBS) proliferate in the activated state, while serum starvation promotes the cellular transition to a "pseudo-quiescent" state. Using these two cell states, we performed a comparative mass spectrometry (GeLC-MS/MS) proteomic analysis. We identified over 2000 nonredundant proteins in PaSC. Qualitative and label-free quantitative analysis revealed several hundred proteins that were differentially abundant between the cell states. Proteins that were more abundant in activated PaSC included cytoskeletal proteins and ribosomal proteins, while those more abundant in pseudoquiescent PaSC included proteins involved in protein degradation-related pathways (lysosome, ubiquitin-mediated proteolysis, and the proteasome). Investigation of the role of PaSC in the pathogenesis of chronic pancreatitis using the mass spectrometry-based proteomics strategy described herein will lead to further insights into the molecular mechanisms associated with the disease.     

Comparative Proteomics Analysis of Placenta from Pregnant Women with Intrahepatic Cholestasis of Pregnancy

Introduction

Intrahepatic cholestasis of pregnancy (ICP) usually occurs in the third trimester and associated with increased risks in fetal complications. Currently, the exact cause of this disease is unknown. In this study we aim to investigate the potential proteins in placenta, which may participate in the molecular mechanisms of ICP-related fetal complications using iTRAQ-based proteomics approach.

Methods

The iTRAQ analysis combined with liquid chromatography-tandem mass spectrometry (LC-MS/MS) was performed to separate differentially expressed placental proteins from 4 pregnant women with ICP and 4 healthy pregnant women. Bioinformatics analysis was used to find the relative processes that these differentially expressed proteins were involved in. Three apoptosis related proteins ERp29, PRDX6 and MPO that resulted from iTRAQ-based proteomics were further verified in placenta by Western blotting and immunohistochemistry. Placental apoptosis was also detected by TUNEL assay.

Results

Proteomics results showed there were 38 differentially expressed proteins from pregnant women with ICP and healthy pregnant women, 29 were upregulated and 9 were downregulated in placenta from pregnant women with ICP. Bioinformatics analysis showed most of the identified proteins was functionally related to specific cell processes, including apoptosis, oxidative stress, lipid metabolism. The expression levels of ERp29, PRDX6 and MPO were consistent with the proteomics data. The apoptosis index in placenta from ICP patients was significantly increased.

Conclusion

This preliminary work provides a better understanding of the proteomic alterations of placenta from pregnant women with ICP and may provide us some new insights into the pathophysiology and potential novel treatment targets for ICP.     

Unique Protein Profiles of Extracellular Vesicles as Diagnostic Biomarkers for Early and Advanced Non‐Small Cell Lung Cancer

Extracellular vesicles (EVs) mediate intercellular communication via transferring proteins and other biological molecules and have been recently investigated as biomarkers of disease. Sensitive and specific biomarkers are required for lung cancer diagnosis and prognosis. The present study screens for abnormal EV proteins in non‐small cell lung cancer (NSCLC) using a quantitative proteomics strategy involving LC‐MS/MS to identify ideal biomarkers for NSCLC diagnosis. EVs are enriched from the sera of early and advanced NSCLC patients and healthy controls and from cell culture supernatants of lung adenocarcinoma and bronchial epithelial cell lines. In the sera and supernatants, 279 and 632 differentially expressed proteins, respectively, are associated with signaling pathways including extracellular membrane–receptor interaction, focal adhesion, and regulation of the actin cytoskeleton. Thirty‐two EV proteins are identified at the intersection of differentially expressed proteins between the NSCLC groups and cell lines. Based on bioinformatics analysis, in silico immunohistochemical, and PRM verification, fibronectin is selected for following in vitro studies and validation with an independent cohort. Fibronectin on EVs is estimated to perform well in the diagnosis of NSCLC patients based on AUC, showing great potential for clinical use and demonstrating the efficacy of this method for EV‐associated biomarker screening.     

A proteomic investigation of Streptococcus agalactiae reveals that human serum induces the C protein β antigen and arginine deiminase

Streptococcus agalactiae is a major neonatal pathogen. Disease progression is characterised by bacterial adaptation from commensal maternal vaginal colonisation to environments associated with neonatal disease, including exposure to blood. To explore this adaptation in vitro, we have used proteomics to identify proteins differentially expressed following growth on Todd Hewitt agar in the presence or absence of 10% v/v human serum. Twelve differentially expressed proteins were identified. Notably, the C protein β antigen and arginine deiminase proteins were upregulated following growth in the presence of human serum, consistent with previous studies implicating these two proteins in the pathogenesis of S. agalactiae disease.     

基于质谱技术筛选差异表达蛋白的统计学策略研究进展

随着质谱技术的快速发展,蛋白质组学已成为继基因组学、转录组学之后的又一研究热点,寻找可靠的差异表达蛋白对于生物标记物的发现至关重要.因此,如何准确、灵敏地筛选出差异蛋白已成为基于质谱的定量蛋白质组学的主要研究内容之一.目前,针对该问题的研究方法众多,但这些方法策略的适用范围不尽相同.总体来说,基于质谱技术筛选差异蛋白的统计学策略可以分为3类:基于经典统计学派的策略、基于贝叶斯学派的统计检验策略和其他策略,这3类方法有各自的应用范围、特点及不足.此外,筛选过程还将产生部分假阳性结果,可以采用其他方法对差异表达蛋白的质量进行控制,以提高统计检验结果的可靠性.     

卵巢高/低级别浆液性癌的定量蛋白质组学比较研究

目的:探讨卵巢高级别浆液性癌和低级别浆液性癌的差异表达蛋白,为阐明卵巢癌发生机制及寻找诊断和预后标志物的提供线索。方法:收集卵巢癌新鲜组织标本冻存于液氮中,经病理学确诊为高级别浆液性癌和低级别浆液性癌,两种类型各收集15例。应用i TRAQ定量蛋白质组学技术筛选及鉴定高/低级别浆液性癌的差异表达蛋白,并进行生物信息学分析。结果:卵巢高级别和低级别浆液性癌组织的定量蛋白质组学比较研究鉴定出差异表达蛋白314个,其中与低级别浆液性癌组比较,高级别浆液性癌组上调蛋白有97种,下调蛋白有217种。GO分析显示这些差异蛋白在分子功能、生物学功能、细胞成分方面均具有一定分布特点。KEGG分析显示这些差异蛋白涉及复杂的信号通路。结论:高/低级别浆液性癌之间存在差异表达蛋白,这些蛋白涉及复杂的功能和信号通路可能在两型卵巢癌发生机制及肿瘤生物学行为差异中具有重要意义。     

An assessment of false discovery rates and statistical significance in label-free quantitative proteomics with combined filters

Background  

Many studies have provided algorithms or methods to assess a statistical significance in quantitative proteomics when multiple replicates for a protein sample and a LC/MS analysis are available. But, confidence is still lacking in using datasets for a biological interpretation without protein sample replicates. Although a fold-change is a conventional threshold that can be used when there are no sample replicates, it does not provide an assessment of statistical significance such as a false discovery rate (FDR) which is an important indicator of the reliability to identify differentially expressed proteins. In this work, we investigate whether differentially expressed proteins can be detected with a statistical significance from a pair of unlabeled protein samples without replicates and with only duplicate LC/MS injections per sample. A FDR is used to gauge the statistical significance of the differentially expressed proteins.