Proteome analysis by three-dimensional protein separation: turnover of cytosolic proteins in hepatocytes

We performed a three-dimensional separation of pulse-chase dual-labelled rat liver cytosolic proteins using hydrophobic interaction chromatography, isoelectric focusing, and SDS gel electrophoresis. Due to very different expression rates but similar size and pI of rat liver cytosolic proteins, we demonstrate the impossibility of successful two-dimensional separations of such complex protein mixtures. A pre-fractionation of proteins by hydrophobic interaction chromatography is therefore recommended prior to two-dimensional gel electrophoresis. Our studies confirmed the correlation between protein turnover rates and surface hydrophobicity.     

Molecular mass sorting of proteome using hollow fiber flow field-flow fractionation for proteomics

Hollow fiber flow field-flow fractionation (HF FlFFF) has been demonstrated as a tool for pre-fractionating proteomes by differences in molecular mass (Mr), where the resulting protein fractions are subsequently digested and analyzed by shotgun proteomics using two-dimensional liquid chromatography-electrospray ionization-tandem mass spectrometry (2D-LC-ESI-MS/MS). HF FlFFF is a separation device capable of fractionating proteins or cells by hydrodynamic radius, and protein fraction can be readily collected as intact conditions in aqueous buffer solutions. In this study, HF FlFFF was applied to fractionate the proteome of Corynebacterium glutamicum, a well known soil bacterium that has been widely used in bioindustry due to its remarkable ability to secrete high amounts of glutamic acid. The collected HF FlFFF fractions of different MW intervals were enzymatically digested for protein identification by 2D-LC-ESI-MS/MS. Experiments showed improvements in protein identification when HF FlFFF pre-fractionation was applied, due to decreases in the ionization suppression effect and the MS exclusion effect by spectral congestion. Pre-fractionation of C. glutamicum proteome allowed us to find 90 additional proteins by 2D-LC-ESI-MS/MS that were not found by a direct shotgun analysis without pre-fractionation. A total of 415 proteins were found overall with 203 proteins commonly found from experiments with and without pre-fractionation.     

Development and application of a two-phase, on-membrane digestion method in the analysis of membrane proteome

Analysis of membrane proteins, particularly integral membrane proteins, still presents a great challenge due to their poor water solubility and low abundance though much effort has been devoted to the solubilization and enrichment of the protein class. In this paper, a two-phase, on-membrane digestion method was developed and applied in the analysis of rat liver membrane proteome. The two-phase system was constituted by mixing n-butanol and 25 mM NH4HCO3. Comparative experiments indicated that the proteins on membranes could be digested in the two-phase system more efficiently than in both 60% methanol and 25 mM NH4HCO3 solutions under the same conditions, thereby improving the identification of the membrane proteins. When the established two-phase system and CapLC-MS/MS was used to analyze rat liver membrane proteome, a total of 411 membrane proteins were identified, more than 80% of which were transmembrane proteins with 1-12 mapped transmembrane domains (TMDs). Because of its extraction and dissolution actions, the two-phase on-membrane digestion system we developed could efficiently improve the digestion and removal of adsorbed nonmembrane proteins, and remarkably increase the number and coverage of identified membrane proteins, particularly the transmembrane proteins. Using our procedure to identify a complementary protein set from all fractions of the two-phase system could achieve a higher coverage of the membrane proteome.     

Analysis of the mouse liver proteome using advanced mass spectrometry

We report a large-scale analysis of mouse liver tissue comprising a novel fractionation approach and high-accuracy mass spectrometry techniques. Two fractions enriched for soluble and membrane proteins from 20 mg of frozen tissue were separated by one-dimensional electrophoresis followed by LC-MS/MS on the hybrid linear ion trap (LTQ)-Orbitrap mass spectrometer. Confident identification of 2210 proteins relied on at least two peptides. We combined this proteome with our previously reported organellar map (Foster et al. Cell 2006, 125, 187-199) to generate a very high confidence mouse liver proteome of 3244 proteins. The identified proteins represent the liver proteome with no discernible bias due to protein physicochemical properties, subcellular distribution, or biological function. Forty-seven percent of identified proteins were annotated as membrane-bound, and for 35.3%, transmembrane domains were predicted. For potential application in toxicology or clinical studies, we demonstrate that it is possible to consistently identify more than 1000 proteins in a single run.     

Extensive analysis of the human platelet proteome by two-dimensional gel electrophoresis and mass spectrometry

Platelets play a key role in the control of bleeding and wound healing, contributing to the formation of vascular plugs. Under pathologic circumstances, they are involved in thrombotic disorders, including heart disease. Since platelets do not have a nucleus, proteomics offers a powerful alternative approach to provide data on protein expression in these cells, helping to address their biology. In this publication we extend the previously reported analysis of the pI 4-5 region of the human platelet proteome to the pI 5-11 region. By using narrow pI range two-dimensional electrophoresis (2-DE) for protein separation followed by high-throughput tandem mass spectrometry (MS/MS) for protein identification, we were able to identify 760 protein features, corresponding to 311 different genes, resulting in the annotation of 54% of the pI 5-11 range 2-DE proteome map. We evaluated the physicochemical properties and functions of the identified platelet proteome. Importantly, the main group of proteins identified is involved in intracellular signalling and regulation of the cytoskeleton. In addition, 11 hypothetical proteins are reported. In conclusion, this study provides a unique inventory of the platelet proteome, contributing to our understanding of platelet function and building the basis for the identification of new drug targets.     

Application of displacement chromatography for the analysis of a lipid raft proteome

Defining membrane proteomes is fundamental to understand the role of membrane proteins in biological processes and to find new targets for drug development. Usually multidimensional chromatography using step or gradient elution is applied for the separation of tryptic peptides of membrane proteins prior to their mass spectrometric analysis. Displacement chromatography (DC) offers several advantages that are helpful for proteome analysis. However, DC has so far been applied for proteomic investigations only in few cases. In this study we therefore applied DC in a multidimensional LC–MS approach for the separation and identification of membrane proteins located in cholesterol-enriched membrane microdomains (lipid rafts) obtained from rat kidney by density gradient centrifugation. The tryptic peptides were separated on a cation-exchange column in the displacement mode with spermine used as displacer. Fractions obtained from DC were analyzed using an HPLC-chip system coupled to an electrospray-ionization ion-trap mass spectrometer. This procedure yielded more than 400 highly significant peptide spectrum matches and led to the identification of more than 140 reliable protein hits within an established rat kidney lipid raft proteome. The majority of identified proteins were membrane proteins. In sum, our results demonstrate that DC is a suitable alternative to gradient elution separations for the identification of proteins via a multidimensional LC–MS approach.     

Metabolic control of seed germination

We have used proteomics to better characterize germination and early seedling vigor in sugarbeet. Our strategy includes (1) construction of proteome reference maps for dry and germinating seeds of a high-vigor reference seed lot; (2) investigation of the specific tissue accumulation of proteins (root, cotyledon, perisperm); (3) investigation of changes in protein expression profiles detected in the reference seed lot subjected to different vigor-modifying treatments, e.g. aging and/or priming. More than 1 000 sugarbeet seed proteins have been identified by LC/MS-MS mass spectrometry (albumins, globulins and glutelins have been analyzed separately). Due to the conservation of protein sequences and the quality of MS sequencing (more than 10 000 peptide sequences have been obtained), the success rate of protein identification was on the average of 80%. This is to our knowledge the best detailed proteome analysis ever carried out in seeds. The data allowed us to build a detailed metabolic chart of the sugarbeet seed, generating new insights into the molecular mechanisms determining the development of a new seedling. Also, the proteome of a seed-storage tissue as the perisperm is described for the first time.     

Quantitative proteomic comparison of mouse peroxisomes from liver and kidney

The peroxisome plays a central role in the catabolic and anabolic pathways that contribute to the lipid homeostasis. Besides this main function, this organelle has gained functional diversity. Although several approaches have been used for peroxisomal proteome analysis, a quantitative protein expression analysis of peroxisomes from different tissues has not been elucidated yet. Here, we applied a 2-DE-based method on mouse liver and kidney peroxisomal enriched fractions to study the tissue-dependent protein expression. Ninety-one spots were identified from the 2-DE maps from pH 3.0-10.0 and 51 spots from the basic range corresponding to 31 peroxisomal proteins, 10 putative peroxisomal, 6 cytosolic, 17 mitochondrial and 1 protein from endoplasmic reticulum. Based on the identification and on the equivalent quality of both tissue preparations, the differences emerging from the comparison could be quantified. In liver, proteins involved in pathways such as alpha- and beta-oxidation, isoprenoid biosynthesis, amino acid metabolism and purine and pyrimidine metabolism were more abundant whereas in kidney, proteins from the straight-chain fatty acid beta-oxidation were highly expressed. These results indicate that tissue-specific functional classes of peroxisomal proteins could be relevant to study peroxisomal cellular responses or pathologies. Finally, a web-based peroxisomal proteomic database was built.     

Expressed proteome analysis of human hepatocellular carcinoma in nude mice (LCI-D20) with high metastasis potential

We report for the first time an expressed proteome for human hepatocellular carcinoma (HCC) in nude mice model. Most cases of human liver cancer are HCC with highly metastatic ability. Therefore, the early prediction or diagnosis and effective treatment are the key points of research. We have previously successfully established a human HCC nude mice model (LCI-D20) with high metastasis potential. To understand better the tumor biology of HCC it is worth to explore the relativity of all expressed protein profiles in the LCI-D20 HCC nude mice model. With advanced proteomics technologies, we have carried out a proteomic analysis with following stages: protein sample preparation of cancer tissue, including total cellular extraction and sequential fractionation, 2-DE and 2-D LC separation, ESI/MALDI-MS/MS identification, as well as data-dependent bioinformatics. The identified proteins were classified bioinformatically respective to their function, biological process and intracellular localization. Some important proteins found in HCC, e.g. metabolism enzymes, proteins regulating cell motility, signaling proteins, and heat shock proteins, are discussed in terms of their metastasis.     

Proteome analysis of liver cells expressing a full-length hepatitis C virus (HCV) replicon and biopsy specimens of posttransplantation liver from HCV-infected patients

The development of a reproducible model system for the study of hepatitis C virus (HCV) infection has the potential to significantly enhance the study of virus-host interactions and provide future direction for modeling the pathogenesis of HCV. While there are studies describing global gene expression changes associated with HCV infection, changes in the proteome have not been characterized. We report the first large-scale proteome analysis of the highly permissive Huh-7.5 cell line containing a full-length HCV replicon. We detected >4,200 proteins in this cell line, including HCV replicon proteins, using multidimensional liquid chromatographic (LC) separations coupled to mass spectrometry. Consistent with the literature, a comparison of HCV replicon-positive and -negative Huh-7.5 cells identified expression changes of proteins involved in lipid metabolism. We extended these analyses to liver biopsy material from HCV-infected patients where a total of >1,500 proteins were detected from only 2 mug of liver biopsy protein digest using the Huh-7.5 protein database and the accurate mass and time tag strategy. These findings demonstrate the utility of multidimensional proteome analysis of the HCV replicon model system for assisting in the determination of proteins/pathways affected by HCV infection. Our ability to extend these analyses to the highly complex proteome of small liver biopsies with limiting protein yields offers the unique opportunity to begin evaluating the clinical significance of protein expression changes associated with HCV infection.     

Optimizing search conditions for the mass fingerprint-based identification of proteins

The two central problems in protein identification by searching a protein sequence collection with MS data are the optimal use of experimental information to allow for identification of low abundance proteins and the accurate assignment of the probability that a result is false. For comprehensive MS-based protein identification, it is necessary to choose an appropriate algorithm and optimal search conditions. We report a systematic study of the quality of PMF-based protein identifications under different sequence collection search conditions using the Probability algorithm, which assigns the statistical significance to each result. We employed 2244 PMFs from 2-DE-separated human blood plasma proteins, and performed identification under various search constraints: mass accuracy (0.01-0.3 Da), maximum number of missed cleavage sites (0-2), and size of the sequence collection searched (5.6 x 10(4)-1.8 x 10(5)). By counting the number of significant results (significance levels 0.05, 0.01, and 0.001) for each condition, we demonstrate the search condition impact on the successful outcome of proteome analysis experiments. A mass correction procedure utilizing mass deviations of albumin matching peptides was tested in an attempt to improve the statistical significance of identifications and iterative searching was employed for identification of multiple proteins from each PMF.     

A combined dataset of human cerebrospinal fluid proteins identified by multi-dimensional chromatography and tandem mass spectrometry

Human cerebrospinal fluid (CSF) is an important source for studying protein biomarkers of age-related neurodegenerative diseases. Before characterizing biomarkers unique to each disease, it is necessary to categorize CSF proteins systematically and extensively. However, the enormous complexity, great dynamic range of protein concentrations, and tremendous protein heterogeneity due to post-translational modification of CSF create significant challenges to the existing proteomics technologies for an in-depth, nonbiased profiling of the human CSF proteome. To circumvent these difficulties, in the last few years, we have utilized several different separation methodologies and mass spectrometric platforms that greatly enhanced the identification coverage and the depth of protein profiling of CSF to characterize CSF proteome. In total, 2594 proteins were identified in well-characterized pooled human CSF samples using stringent proteomics criteria. This report summarizes our efforts to comprehensively characterize the human CSF proteome to date.     

Proteomic analysis of advanced colorectal cancer by laser capture microdissection and two-dimensional difference gel electrophoresis

The emergence of laser capture microdissection (LCM) and two-dimensional difference gel electrophoresis (2D-DIGE) has been shown to greatly improve the accuracy and sensitivity of global protein expression analysis. However, their combined use in profiling tumour proteome has rarely been reported. In this study, we applied these techniques to profile the protein expression changes of the late stage colorectal cancer (CRC) and its liver metastases. The study revealed that both the primary and secondary tumours showed a distinct protein expression profile compared to normal tissues, but were indistinguishable from each other. Differential analysis between the primary tumour and patient-matched normal colon mucosa identified a total of 71 proteins to be altered in CRC. Over 40% of these proteins have been previously reported as CRC-related proteins, validating the accuracy of the current analysis. We have also identified many previously unknown changes including overexpression of ACY1, HSC70, HnRNP I, HnRNP A3, SET, ANP32A and TUFM in CRC, which have been further verified by western blotting and immunohistochemistry. This study demonstrated that LCM in combination with 2D-DIGE is a powerful tool to analyse the proteome of tumour tissues and may lead to the identification of potential novel protein markers and therapeutic targets for cancer.