Biomarker discovery: proteome fractionation and separation in biological samples.

Proteomics, analogous with genomics, is the analysis of the protein complement present in a cell, organ, or organism at any given time. While the genome provides information about the theoretical status of the cellular proteins, the proteome describes the actual content, which ultimately determines the phenotype. The broad application of proteomic technologies in basic science and clinical medicine has the potential to accelerate our understanding of the molecular mechanisms underlying disease and may facilitate the discovery of new drug targets and diagnostic disease markers. Proteomics is a rapidly developing and changing scientific discipline, and the last 5 yr have seen major advances in the underlying techniques as well as expansion into new applications. Core technologies for the separation of proteins and/or peptides are one- and two-dimensional gel electrophoresis and one- and two-dimensional liquid chromatography, and these are coupled almost exclusively with mass spectrometry. Proteomic studies have shown that the most effective analysis of even simple biological samples requires subfractionation and/or enrichment before protein identification by mass spectrometry. Selection of the appropriate technology or combination of technologies to match the biological questions is essential for maximum coverage of the selected subproteome and to ensure both the full interpretation and the downstream utility of the data. In this review, we describe the current technologies for proteome fractionation and separation of biological samples, based on our lab workflow for biomarker discovery and validation.     

Hiding behind hydrophobicity. Transmembrane segments in mass spectrometry

Proteomics of membrane proteins is essential for the understanding of cellular function. However, mass spectrometric analysis of membrane proteomes has been less successful than the proteomic determination of soluble proteins. To elucidate the mystery of transmembrane proteins in mass spectrometry, we present a detailed statistical analysis of experimental data derived from chloroplast membranes. This approach was further accomplished by the analysis of the Arabidopsis thaliana proteome after in silico digestion. We demonstrate that both the length and the hydrophobicity of the proteolytic fragments containing transmembrane segments are major determinants for detection by mass spectrometry. Based on a comparative analysis, we discuss possibilities to overcome the problem and provide possible protocols to shift the hydrophobicity of transmembrane segment-containing peptides to facilitate their detection.     

Proteomic analysis of HBV-associated HCC: Insights on mechanisms of disease onset and biomarker discovery

The development of hepatocellular carcinoma (HCC) can be considered as an end-stage outcome of chronic hepatitis B virus (HBV) infection. Early prognostic markers are needed to allow effective treatments and prevent HCC from developing. Proteomics analysis has been used to identify markers from clinical samples from HCC patients. This approach can be further improved by identifying early biomarkers before the onset of HCC. One way would be to use the cell-based HBV replication system, which is reflective of the early stage of virus infection and thus secreted proteins identified at this stage may have relevance in HCC prognosis. In this review, we focus the discussion on the current status of proteomics analysis of cellular proteins and HCC biomarker identification, with a special highlight on the potential of the cell-based HBV replication system for the identification of prognostic HCC biomarkers.     

Proteomics signature profiling (PSP): a novel contextualization approach for cancer proteomics

Traditional proteomics analysis is plagued by the use of arbitrary thresholds resulting in large loss of information. We propose here a novel method in proteomics that utilizes all detected proteins. We demonstrate its efficacy in a proteomics screen of 5 and 7 liver cancer patients in the moderate and late stage, respectively. Utilizing biological complexes as a cluster vector, and augmenting it with submodules obtained from partitioning an integrated and cleaned protein-protein interaction network, we calculate a Proteomics Signature Profile (PSP) for each patient based on the hit rates of their reported proteins, in the absence of fold change thresholds, against the cluster vector. Using this, we demonstrated that moderate- and late-stage patients segregate with high confidence. We also discovered a moderate-stage patient who displayed a proteomics profile similar to other poor-stage patients. We identified significant clusters using a modified version of the SNet approach. Comparing our results against the Proteomics Expansion Pipeline (PEP) on which the same patient data was analyzed, we found good correlation. Building on this finding, we report significantly more clusters (176 clusters here compared to 70 in PEP), demonstrating the sensitivity of this approach. Gene Ontology (GO) terms analysis also reveals that the significant clusters are functionally congruent with the liver cancer phenotype. PSP is a powerful and sensitive method for analyzing proteomics profiles even when sample sizes are small. It does not rely on the ratio scores but, rather, whether a protein is detected or not. Although consistency of individual proteins between patients is low, we found the reported proteins tend to hit clusters in a meaningful and informative manner. By extracting this information in the form of a Proteomics Signature Profile, we confirm that this information is conserved and can be used for (1) clustering of patient samples, (2) identification of significant clusters based on real biological complexes, and (3) overcoming consistency and coverage issues prevalent in proteomics data sets.     

蛋白质组学在干细胞研究中的应用

蛋白质组学技术通过整合多项技术来分析生物体的全部蛋白质成分,通过考察不同状态下细胞或组织蛋白质组的变化情况来了解细胞活动的分子机理。干细胞分化过程中受外界条件的影响其蛋白表达模式也表现出一定的差异,对干细胞分化过程中进行蛋白质组学研究将有利于从蛋白质分子水平上阐明干细胞的分化机理。本文对蛋白质组学及其在干细胞研究中的应用加以评述。     

Proteomics of multiprotein complexes: answering fundamental questions in neuroscience

Proteomics tools offer new ways to analyse networks of proteins that control important neurobiological phenomena such as learning and memory. In this review, we discuss how a combined proteomic, pharmacological and genetic approach reveals that multiprotein complexes process neural information and encode memories. Simultaneous analysis of multiple proteins enables the development of new concepts and approaches for neuroscience research.     

Proteomics of multiprotein complexes: answering fundamental questions in neuroscience

Proteomics tools offer new ways to analyse networks of proteins that control important neurobiological phenomena such as learning and memory. In this review, we discuss how a combined proteomic, pharmacological and genetic approach reveals that multiprotein complexes process neural information and encode memories. Simultaneous analysis of multiple proteins enables the development of new concepts and approaches for neuroscience research.     

蛋白质组学进展

在蛋白质水平上定量、动态、整体性研究生物体的蛋白质组学 ,将在后基因组时代大大增进我们对基因功能的理解。简要介绍了蛋白质组学的概念、研究手段 ,及最新进展     

Methods and approaches for the comprehensive characterization and quantification of cellular proteomes using mass spectrometry.

Proteomics has been proposed as one of the key technologies in the postgenomic era. So far, however, the comprehensive analysis of cellular proteomes has been a challenge because of the dynamic nature and complexity of the multitude of proteins in cells and tissues. Various approaches have been established for the analyses of proteins in a cell at a given state, and mass spectrometry (MS) has proven to be an efficient and versatile tool. MS-based proteomics approaches have significantly improved beyond the initial identification of proteins to comprehensive characterization and quantification of proteomes and their posttranslational modifications (PTMs). Despite these advances, there is still ongoing development of new technologies to profile and analyze cellular proteomes more completely and efficiently. In this review, we focus on MS-based techniques, describe basic approaches for MS-based profiling of cellular proteomes and analysis methods to identify proteins in complex mixtures, and discuss the different approaches for quantitative proteome analysis. Finally, we briefly discuss novel developments for the analysis of PTMs. Altered levels of PTM, sometimes in the absence of protein expression changes, are often linked to cellular responses and disease states, and the comprehensive analysis of cellular proteome would not be complete without the identification and quantification of the extent of PTMs of proteins.     

Identification and evaluation of a panel of serum biomarkers for predicting response to thalidomide in multiple myeloma patients

Evaluation of: Rajpal R, Dowling P, Meiller J et al. A novel panel of protein biomarkers for predicting response to thalidomide-based therapy in newly diagnosed multiple myeloma patients. Proteomics 11(8), 1391-1402 (2011). Predicting response to thalidomide-based therapy remains a challenging task faced by clinicians in the treatment of multiple myeloma. The pioneering work reported by Rajpal et al. moves one step further towards solving this challenge. They developed a proteomics-based approach that combines immunodepletion, 2D-difference gel electrophoresis analysis and mass spectrometry to search for serum proteins with expressions that show significant correlations to thalidomide treatment. This integrated approach allowed them to identify a panel of protein biomarkers. By using ELISA-based validation and strict statistical analysis, the authors have achieved an overall 84.0% predictive accuracy, with associated sensitivity and specificity values of 81.8 and 86.2%, respectively. Their methods and significant findings are reviewed within this article. This panel of biomarkers may not only guide initial therapy, but can also provide direct implications for personalized medicine in multiple myeloma patients.     

Differential response to intracellular stress in the skin from osteogenesis imperfecta Brtl mice with lethal and non lethal phenotype: a proteomic approach

Phenotypic variability in the presence of an identical molecular defect is a recurrent feature in heritable disorders and it was also reported in osteogenesis imperfecta (OI). OI is a prototype for skeletal dysplasias mainly caused by mutations in the two genes coding for type I collagen. No definitive cure is available for this disorder, but the understanding of molecular basis in OI phenotypic modulation will have a pivotal role in identifying possible targets to develop novel drug therapy. We used a functional proteomic approach to address the study of phenotypic variability using the skin of the OI murine model Brtl. Brtl mice reproduce the molecular defect, dominant transmission and phenotypic variability of human OI patients. In the presence of a Gly349Cys substitution in α1(I)-collagen Brtl mice can have a lethal or a moderately severe outcome. Differential expression of chaperones, proteasomal subunits, metabolic enzymes, and proteins related to cellular fate demonstrated that a different ability to adapt to cellular stress distinguished mutant from wild-type mice and mutant lethal from surviving mutant animals. Interestingly, class discovery analysis identified clusters of differentially expressed proteins associated with a specific outcome, and functional analysis contributed to a deeper investigation into biochemical and cellular pathways affected by the disease. This article is part of a Special Issue entitled: Translational Proteomics.     

Proteomics analysis of conditioned media from three breast cancer cell lines: a mine for biomarkers and therapeutic targets

A "bottom-up" proteomics approach and a two-dimensional (strong cation exchange followed by reversed-phase) LC-MS/MS strategy on a linear ion trap (LTQ) were utilized to identify and compare expressions of extracellular and membrane-bound proteins in the conditioned media of three breast cell lines (MCF-10A, BT474, and MDA-MB-468). Proteomics analysis of the media identified in excess of 600, 500, and 700 proteins in MCF-10A, BT474, and MDA-MB-468, respectively. We successfully identified the internal control proteins, kallikreins 5, 6, and 10 (ranging in concentration from 2 to 50 microg/liter) in MDA-MB-468 conditioned medium as validated by ELISA and confidently identified Her-2/neu in BT474 cells. Subcellular localization was determined based on Genome Ontology terms for all the 1,139 proteins of which 34% were classified as extracellular and membrane-bound. Proteomics analysis of MDA-MB-468 cell lysate demonstrated that only 5% of all identified proteins were extracellular. This confirmed our hypothesis that examining the CM of cell lines, as opposed to the cell lysates, leads to a significant enrichment in secreted proteins. Tissue specificity, functional classifications, and spectral counting were performed. Elafin, a protease inhibitor, identified in the conditioned media of BT474 and MDA-MB-468 and the three kallikreins (KLK5, KLK6, and KLK10) were validated using an immunoassay on various serum and biological samples. Some of the secreted proteins identified have established roles in breast cancer development (cell growth, differentiation, and metastasis) and/or are linked to early onset breast cancer. Our approach to mining for low abundance molecules could identify proteins in various stages of breast cancer development. Many of the identified proteins are potentially useful to investigate as circulating serum breast cancer biomarkers.     

药物蛋白质组学与药物发现

21世纪,科学家面临着从基因组到蛋白质组的转变,蛋白质组学是基因组和药物发现的效率。药物蛋白质组学研究不仅有助于发现治疗的可能靶点,也将明显提高药物发现的效率。药物蛋白质组学的研究内容,在临床前包括发现新的治疗靶点和发现针对所有靶点的全部化合物,在临床研究方面应包括药物作用的特异蛋白作为诊断和治疗的标志,或以蛋白质谱的差异来分类者。本文主要综述了蛋白质组学在药物靶点的发现和确认,以有药物发现过程中最有关的技术物研究进展。     

LC-MS/MS based proteomic analysis and functional inference of hypothetical proteins in Desulfovibrio vulgaris

High efficiency capillary liquid chromatography-tandem mass spectrometry (LC-MS/MS) was used to examine the proteins extracted from Desulfovibrio vulgaris cells across six treatment conditions. While our previous study provided a proteomic overview of the cellular metabolism based on proteins with known functions [W. Zhang, M.A. Gritsenko, R.J. Moore, D.E. Culley, L. Nie, K. Petritis, E.F. Strittmatter, D.G. Camp II, R.D. Smith, F.J. Brockman, A proteomic view of the metabolism in Desulfovibrio vulgaris determined by liquid chromatography coupled with tandem mass spectrometry, Proteomics 6 (2006) 4286-4299], this study describes the global detection and functional inference for hypothetical D. vulgaris proteins. Using criteria that a given peptide of a protein is identified from at least two out of three independent LC-MS/MS measurements and that for any protein at least two different peptides are identified among the three measurements, 129 open reading frames (ORFs) originally annotated as hypothetical proteins were found to encode expressed proteins. Functional inference for the conserved hypothetical proteins was performed by a combination of several non-homology based methods: genomic context analysis, phylogenomic profiling, and analysis of a combination of experimental information, including peptide detection in cells grown under specific culture conditions and cellular location of the proteins. Using this approach we were able to assign possible functions to 20 conserved hypothetical proteins. This study demonstrated that a combination of proteomics and bioinformatics methodologies can provide verification of the expression of hypothetical proteins and improve genome annotation.     

Proteomics of boar seminal plasma - current studies and possibility of their application in biotechnology of animal reproduction

Proteomics is critical to identify the properties and functions of proteins involved in the mechanism regulating the male reproductive tract function. This approach is important in male fertility assessment and clinical diagnosis of the physiological state of individual reproductive organs. Proteomics also provides a tool to understand the interactions of seminal plasma proteins with spermatozoa, which could provide a useful model for studying ligand-cell interaction occurring at the sperm cell surface. This review covers a selection of advances in the realm of functional proteomics of boar seminal plasma proteins and is focused on some fundamental proteomic technologies. Also, this review explores key themes in proteomics and their application in animal reproductive techniques.     

Proteomics of blood and derived products: what’s next?

Proteomics has changed the way proteins are analyzed in living systems. This approach has been applied to blood products and protein profiling has evolved in parallel with the development of techniques. The identification of proteins belonging to red blood cell, platelets or plasma was achieved at the end of the last century. Then, the questions on the applications emerged. Hence, several studies have focused on problems related to blood banking and products, such as the aging of blood products, identification of biomarkers, related diseases and the protein–protein interactions. More recently, a mass spectrometry-based proteomics approach to quality control has been applied in order to offer solutions and improve the quality of blood products. The current challenge we face is developing a closer relationship between transfusion medicine and proteomics. In this article, these issues will be approached by focusing first on the proteome identification of blood products and then on the applications and future developments within the field of proteomics and blood products.