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Disease biomarkers are predicted to be in low abundance; thus, the most crucial step of biomarker discovery is the efficient fractionation of clinical samples into protein sets that define disease stages and/or predict disease development. For this purpose, we developed a new platform that uses peptide-based size exclusion chromatography (pep-SEC) to quantify disease biomarker candidates. This new platform has many advantages over previously described biomarker profiling platforms, including short run time, high resolution, and good reproducibility, which make it suitable for large-scale analysis. We combined this platform with isotope labeling and label-free methods to identify and quantitate differentially expressed proteins in hepatocellular carcinoma (HCC) tissues. When we combined pep-SEC with a gas phase fractionation method, which broadens precursor ion selection, the protein coverage was significantly increased, which is critical for the global profiling of HCC specimens. Furthermore, pep-SEC-LC-MS/MS analysis enhanced the detection of low-abundance proteins (e.g. insulin receptor substrate 2 and carboxylesterase 1) and glycopeptides in HCC plasma. Thus, our pep-SEC platform is an efficient and versatile pre-fractionation system for the large-scale profiling and quantitation of candidate biomarkers in complex disease proteomes., (Copyright © 2011 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

The Asia Oceania Human Proteome Organisation (AOHUPO) has embarked on a Membrane Proteomics Initiative with goals of systematic comparison of strategies for analysis of membrane proteomes and discovery of membrane proteins. This multilaboratory project is based on the analysis of a subcellular fraction from mouse liver that contains endoplasmic reticulum and other organelles. In this study, we present the strategy used for the preparation and initial characterization of the membrane sample, including validation that the carbonate-washing step enriches for integral and lipid-anchored membrane proteins. Analysis of 17 independent data sets from five types of proteomic workflows is in progress., (Copyright © 2010 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.)

As human plasma is clinically valuable, reference data from healthy donors can be a useful source for serological biomarker studies. To make a reliable protein catalog of the Korean plasma proteome, various experimental methods, such as 1-D HPLC, 2-D LC, and narrow ranged 2-DE prior to MALDI-TOF and LC-MS/MS, were used to identify unique plasma proteins in this population. To compile candidates with high confidence, two different search engines were used to select proteins with a false discovery rate of less than or equal to 1%. From this rigorous selection process, we initially identified 494 distinct Korean plasma proteins. After multilevel stepwise filtrations with stringent, identification parameters were applied to acquire plasma protein list with the maximum confidence; a total 185 distinct plasma proteins were identified and integrated into our Korean human plasma proteome project database along with several bioinformatics analysis results, including gene ontology, biological pathways, tissue expression, and disease association. This is the first publicly available single ethnic group-specific plasma proteome database (http://proteomix.org/khppp/).

Caenorhabditis elegans, a free-living soil nematode, is an ideal model system for studying various physiological problems relevant to human diseases. Despite its short history, C. elegans proteomics is receiving great attention in multiple research areas, including the genome annotation, major signaling pathways (e.g. TGF-beta and insulin/IGF-1 signaling), verification of RNA interference-mediated gene targeting, aging, disease models, as well as peptidomic analysis of neuropeptides involved in behavior and locomotion. For example, a proteome-wide profiling of developmental and aging processes not only provides basic information necessary for constructing a molecular network, but also identifies important target proteins for chemical modulation. Although C. elegans has a simple body system and neural circuitry, it exhibits very complicated functions ranging from feeding to locomotion. Investigation of these functions through proteomic analysis of various C. elegans neuropeptides, some of which are not found in the predicted genome sequence, would open a new field of peptidomics. Given the importance of nematode infection in plants and mammalian pathogenesis pathways, proteomics could be applied to investigate the molecular mechanisms underlying plant- or animal-nematode pathogenesis and to identify novel antinematodal drugs. Thus, C. elegans proteomics, in combination of other molecular, biological and genetic techniques, would provide a versatile new tool box for the systematic analysis of gene functions throughout the entire life cycle of this nematode.

Biomarkers for the detection of early hepatocellular carcinoma (HCC) are urgently needed. To identify biomarkers of HCC, we performed a comparative proteomics analysis, based on 2-DE of HCC tissues and surrounding non-tumor tissues. Six xenobiotic enzymes were significantly down-regulated in the HCC tissue. Among these, phenol sulfotransferase (SULT1A1) was confirmed by Western blot analysis in 105 HCC patients. SULT1A1 showed a significant decrease in 98.1% of the HCC tissues, with 88.6% sensitivity and 66.7% specificity for the detection of HCC. Immunohistochemistry for SULT1A1 was performed and compared with glypican-3, which is a well-known marker of HCC. The results showed down-regulation of SULT1A1 and up-regulation of glypican-3 in 52.6 and 71.9% of the HCCs, and the use of both markers improved the sensitivity up to 78.9%. Moreover, SULT1A1 was useful in differentiating early HCC from benign dysplastic nodules. Clinically, the down-regulation of SULT1A1 was closely associated with an advanced International Union Against Cancer stage and high levels of serum alpha-fetoprotein. In conclusion, the results of this study demonstrate that the loss of SULT1A1 appears to be a characteristic molecular signature of HCC. SULT1A1 might be a useful biomarker for the detection of early HCC and help predict the clinical outcome of patients with HCC.

To identify and characterize a serologic glycoprotein biomarker for hepatocellular carcinoma (HCC), multi-lectin affinity chromatography was used to isolate intracellular N-linked glycoprotein fractions from five paired non-tumor and tumor tissues. From the series of 2-D DIGE targeted differentially expressed N-linked glycoproteins, we identified human liver carboxylesterase 1 (hCE1), which was remarkably down-regulated in tumor tissues, a finding confirmed by Western blot, a quantitative real-time RT-PCR, and immunohistochemical staining of non-tumor and tumor tissues from total 58 HCC patients. To investigate whether hCE1 is also present in human plasma, we employed a magnetic bead-based immunoprecipitation followed by nano-LC-MS/MS analysis, and we found for the first time that hCE1 is present in human plasma as opposed to that in liver tissues. That is, from normalization of hCE1 signal by the immunoprecipitation and Western blot analysis, hCE1 levels were increased in plasma specimens from HCC patients than in plasma from other disease patient groups (e.g. liver cirrhosis, chronic hepatitis, cholangiocarcinoma, stomach cancer, and pancreatic cancer). From the receiver operating characteristic analysis in HCC, both sensitivity and specificity were shown to be greater than 70.0 and 85.0%, respectively. Thus, the high-resolution proteomic approach demonstrates that hCE1 is a good candidate for further validation as a serologic glycoprotein biomarker for HCC.

We have developed a proteome database (DB), BiomarkerDigger (http://biomarkerdigger.org) that automates data analysis, searching, and metadata-gathering function. The metadata-gathering function searches proteome DBs for protein-protein interaction, Gene Ontology, protein domain, Online Mendelian Inheritance in Man, and tissue expression profile information and integrates it into protein data sets that are accessed through a search function in BiomarkerDigger. This DB also facilitates cross-proteome comparisons by classifying proteins based on their annotation. BiomarkerDigger highlights relationships between a given protein in a proteomic data set and any known biomarkers or biomarker candidates. The newly developed BiomarkerDigger system is useful for multi-level synthesis, comparison, and analyses of data sets obtained from currently available web sources. We demonstrate the application of this resource to the identification of a serological biomarker for hepatocellular carcinoma by comparison of plasma and tissue proteomic data sets from healthy volunteers and cancer patients.

Reversible phosphorylation of proteins is the most common PTM in cell-signaling pathways. Despite this, high-throughput methods for the systematic detection, identification, and quantification of phosphorylated peptides have yet to be developed. In this paper, we describe the establishment of an efficient online titaniuim dioxide (TiO2)-based 3-D LC (strong cationic exchange/TiO2/C18)-MS(3)-linear ion trap system, which provides fully automatic and highly efficient identification of phosphorylation sites in complex peptide mixtures. Using this system, low-abundance phosphopeptides were isolated from cell lines, plasma, and tissue of healthy and hepatocellular carcinoma (HCC) patients. Furthermore, the phosphorylation sites were identified and the differences in phosphorylation levels between healthy and HCC patient specimens were quantified by labeling the phosphopeptides with isotopic analogs of amino acids (stable isotope labeling with amino acids in cell culture for HepG2 cells) or water (H(2) (18)O for tissues and plasma). Two examples of potential HCC phospho-biomarkers including plectin-1(phopho-Ser-4253) and alpha-HS-glycoprotein (phospho-Ser 138 and 312) were identified by this analysis. Our results suggest that this comprehensive TiO2-based online-3-D LC-MS(3)-linear ion trap system with high-throughput potential will be useful for the global profiling and quantification of the phosphoproteome and the identification of disease biomarkers.

With the development of high-speed mass spectrometric techniques, it becomes important to manage large amounts of spectrometric data accurately. We have developed a new data management system with a visualization function named IntelliMS, which can load data into a search engine, filter out the insignificant data, create diagrams of the identification process from spectra to protein and share all the resulting datasets. This software can be used to efficiently manage complicated mass spectral data and the corresponding protein identification information obtained from various proteomics analyses.

A peptide-based 2-D liquid phase fractionation (PF2D) system was used in a quantitative proteomic analysis of hepatocellular carcinoma. 2-D liquid maps of peptide specimens showed better resolution than those of proteins, leading to the identification of differentially expressed proteins. Peptide-based PF2D gave well-matched theoretical and experimental pI values and was proven to be a very efficient and versatile analytical tool for both large-scale profiling and quantification of phosphoproteins in disease biomarker discovery.

Current proteome profiling techniques have identified relatively few mammalian membrane proteins despite their numerous important functions. To establish a standard throughput-potential profiling platform for membrane proteins, Triton X-100-solubilized rat liver microsomal proteins were separated on a 2-D separation system (2-D liquid phase fractionation (PF2D)) in two different pH ranges (4.0-8.5 and 7.0-10.5). This system produced 182 proteins with more than two transmembrane domain (TMD), including 16 TMDs with high confidence. Comparative 2-D liquid maps with high resolution and reproducibility have been constructed for liver microsome from the phenobarbital (PB) treated rats. PF2D was also found to be useful for the semiquantification of some representative cytochrome P450 family proteins (e.g., cytochrome P450 2B2) that were induced by PB treatment compared with untreated controls. Thus, the combination of both high-detection capacity and rapid preliminary semiquantification in a PF2D platform could become a standard system for the routine analysis of membrane proteins.

Though ulcerative colitis (UC)-associated colon cancer develops from dysplastic lesions caused by chronic inflammation, the specific mechanistic link between chronic inflammation and carcinogenesis in colon has not been integrated into molecular understanding. We therefore established an experimental animal model for colitic cancer, and used proteomic analysis, based on 2-DE and MALDI-TOF MS, to identify proteins involved in colitic cancer. In our model, 6-week-old C57BL/6J mice were exposed to 15 cycles of dextran sodium sulfate (DSS), with each cycle consisting of 0.7% DSS for 1 week followed by distilled water for 10 days. Colorectal tumors developed in 22 of 24 mice (91.6%), with a tumor multiplicity of 1.727 per tumor-bearing mouse. Comparative 2-DE analysis showed that 38 protein spots were differentially expressed in colon tumors and normal colon. We identified 27 of these proteins, including GRP94, HSC70, enolase, prohibitin, and transgelin. The reduction of transgelin expression in mouse colon tumors was confirmed by Western blotting and immunohistochemistry. We also found that transgelin expression was significantly reduced in human colon tumors compared with adjacent nontumorous tissues. In conclusion, these results suggest that loss of transgelin could be a candidate for biomarker of repeated colitis-associated colon cancer.

To develop a standard method for separating highly basic proteins in mammalian cells, we established a 2-D LC separation system coupled with chromatofocusing/nonporous RP column chromatography (CF/NPRPC) in a ProteomeLab PF2D system. After standardizing conditions for 2-D LC, a 2-D liquid protein map of uninfected macrophage proteins with pH range 8.3-11.3 was constructed, and then compared with a macrophage protein map made after infection with Candida albicans. The results demonstrate that 2-D LC offers both high resolution and reproducibility for separation of highly basic, macrophage proteins. After protein identification using a nano 2-D LC-MS/MS Proteomics Solution System, quantitative determination of the changes in the differentially expressed proteins (e.g., galectin-3) in C. albicans-infected macrophages was also accomplished by measuring the peak area of the chromatogram in 2-D LC. The result from this measurement of galectin-3 expression shows a 3.41-fold decrease in the infected macrophage cells, which was further confirmed by that from the RT-PCR of mRNA of galectin-3. Thus, 2-D LC coupled with CF/NPRPC could be applicable to common analysis of highly basic proteins in a high-throughput manner.

Niemann-Pick disease type C (NPC) is a fatal autosomal recessive cholesterol disorder characterized by severe progressive neurodegeneration. To unveil the mechanism of neurodegeneration, proteomic and morphological approaches were applied to the hippocampus in NPC -/- mouse. Two-DE was utilized to resolve the hippocampal protein expression profiles of 4- and 8-week-old NPC +/+ and -/- mice. Differentially expressed protein spots were identified by MALDI-TOF MS and database searching. At 4 weeks of age, there was no significant difference in protein profiles between NPC +/+ and -/- mice. However, at the age of 8 weeks, NPC +/+ and -/- mice showed marked difference in protein expressions. Among these, glutamate receptor 2 precursor was identified. The immunohistochemical study on neurotransporters showed that glial GABA transporter (GAT-3) increased in both 4- and 8-week-old NPC -/- mouse and glutamic acid decarboxylase (GAD-6) increased in 8-week-old NPC -/- mouse. Glial glutamate transporter, excitatory amino acids carrier-1 (EAAC1), decreased in 8-week-old NPC -/- mouse. In conclusion, our data may provide insight into the understanding of the basic mechanism through perturbation of protein networks and neurotransporter systems in a single gene knockout model of NPC disease.

In shotgun proteomics, proteins can be fractionated by 1-D gel electrophoresis and digested into peptides, followed by liquid chromatography to separate the peptide mixture. Mass spectrometry generates hundreds of thousands of tandem mass spectra from these fractions, and proteins are identified by database searching. However, the search scores are usually not sufficient to distinguish the correct peptides. In this study, we propose a confident protein identification method for high-throughput analysis of human proteome. To build a filtering protocol in database search, we chose Pseudomonas putida KT2440 as a reference because this bacterial proteome contains fewer modifications and is simpler than the human proteome. First, the P. putida KT2440 proteome was filtered by reversed sequence database search and correlated by the molecular weight in 1-D-gel band positions. The characterization protocol was then applied to determine the criteria for clustering of the human plasma proteome into three different groups. This protein filtering method, based on bacterial proteome data analysis, represents a rapid way to generate higher confidence protein list of the human proteome, which includes some of heavily modified and cleaved proteins.

Most gastrointestinal stromal tumors (GIST) have activating mutations in either KIT or PDGFRA. However, a small subset of GIST lacks either mutation. To investigate the molecular characteristics of GIST according to mutation type, protein expression profiles in 12 GIST (2 cases with PDGFRA mutations, 8 cases with KIT mutations and 2 cases lacking either mutation) were analyzed using 2-DE and MALDI-TOF-MS. Comparative analysis of the respective spot patterns using 2-DE showed that 15 proteins were differently expressed according to the mutation status. Expression levels of septin and heat shock protein (HSP) 27 were increased in GIST with KIT mutations and annexin V was overexpressed in GIST lacking either mutation. Among the 15 proteins, overexpression of 5 proteins [annexin V, high mobility group protein 1 (HMGB1), C13orf2, glutamate dehydrogenase 1 and fibrinogen beta chain] and decreased expression of RoXaN correlated with a higher tumor grade. These findings suggest that differential protein expression can be used as a diagnostic biomarker. Moreover, it may play a role in the development and progression of GIST according to activating mutation type, as these proteins have been shown to be involved in tumor metastasis, apoptosis and immune response.

Recently, we reported altered protein expression in primary cultured fibroblasts from atopic dermatitis (AD) patients. As a sequential study, we conducted proteomic analysis of primary keratinocytes derived from AD patients to further identify AD-related proteins. Three pH ranges, 4-7, 6-9, and 7-11, were used to profile the altered protein expression in AD. We obtained 46 candidate spots from the 2-D gel image analysis: 18 proteins were up-regulated and 27 proteins were down-regulated. Among the several important candidate proteins, NCC27 showed the same profile of a defect in PTM in both AD-derived keratinocytes and fibroblasts. On the basis of current and previous reports, real-time PCR was performed on select candidate genes to compare RNA and protein expression levels in AD-derived keratinocytes and fibroblasts. Our results provide new clues to aid in understanding the mechanism of atopic alterations in keratinocytes and suggest new AD-associated proteins that are important in AD pathogenesis.

In the last ten years, the field of proteomics has expanded at a rapid rate. A range of exciting new technology has been developed and enthusiastically applied to an enormous variety of biological questions. However, the degree of stringency required in proteomic data generation and analysis appears to have been underestimated. As a result, there are likely to be numerous published findings that are of questionable quality, requiring further confirmation and/or validation. This manuscript outlines a number of key issues in proteomic research, including those associated with experimental design, differential display and biomarker discovery, protein identification and analytical incompleteness. In an effort to set a standard that reflects current thinking on the necessary and desirable characteristics of publishable manuscripts in the field, a minimal set of guidelines for proteomics research is then described. These guidelines will serve as a set of criteria which editors of PROTEOMICS will use for assessment of future submissions to the Journal.

Human plasma is the most clinically valuable specimen, containing not only a dynamic concentration range of protein components, but also several groups of high-abundance proteins that seriously interfere with the detection of low-abundance potential biomarker proteins. To establish a high-throughput method for efficient depletion of high-abundance proteins and subsequent fractionation, prior to molecular analysis of proteins, we explored how coupled immunoaffinity columns, commercially available as multiple affinity removal columns (MARC) and free flow electrophoresis (FFE), could apply to the HUPO plasma proteome project. Here we report identification of proteins and construction of a human plasma 2-DE map devoid of six major abundance proteins (albumin, transferrin, IgG, IgA, haptoglobin, and antitrypsin) using MARC. The proteins were identified by PMF, matching with various internal 2-DE maps, resulting in a total of 144 nonredundant proteins that were identified from 398 spots. Tissue plasminogen activator, usually present at 10-60 ng/mL plasma, was also identified, indicative of a potentially low-abundance biomarker. Comparison of representative 2-D gel images of three ethnic groups (Caucasian, Asian-American, African-American) plasma exhibited minor differences in certain proteins between races and sample pretreatment. To establish a throughput fractionation of plasma samples by FFE, either MARC flow-through fractions or untreated samples of Korean serum were subjected to FFE. After separation of samples on FFE, an aliquot of each fraction was analyzed by 1-D gel, in which MARC separation was a prerequisite for FFE work. Thus, a working scheme of MARC --> FFE --> 1-D PAGE --> 2-D-nanoLC-MS/MS may be considered as a widely applicable standard platform technology for fractionation of complex samples like plasma.

The proteome of a HUPO human serum reference sample was analyzed using multidimensional separation techniques at both the protein and the peptide levels. To eliminate false-positive identifications from the search results, we employed a data filtering method using molecular weight (MW) correlations derived from denaturing 1-DE. First, the six most abundant serum proteins were removed from the sample using immunoaffinity chromatography. 1-DE was then used to fractionate the remaining serum proteins according to the MW. Gel bands were isolated and in-gel digested with trypsin, and the resulting peptides were analyzed by 2-D LC/ESI-MS/MS. A SEQUEST search using the MS/MS results identified 494 proteins. Of these, 202 were excluded formally using protein data filtering as they were single-assignment proteins and their theoretical and electrophoretically-derived MWs did not correlate at high confidence. To evaluate this method, the results were compared with those of 1-D LC/MALDI-TOF/TOF and HUPO Plasma Proteome Project analyses. Our data filtering approach proved valuable in analysis of complex, large-scale proteomes such as human serum.

HUPO initiated the Plasma Proteome Project (PPP) in 2002. Its pilot phase has (1) evaluated advantages and limitations of many depletion, fractionation, and MS technology platforms; (2) compared PPP reference specimens of human serum and EDTA, heparin, and citrate-anti-coagulated plasma; and (3) created a publicly-available knowledge base (www.bioinformatics.med.umich.edu/hupo/ppp; www.ebi.ac.uk/pride). Thirty-five participating laboratories in 13 countries submitted datasets. Working groups addressed (a) specimen stability and protein concentrations; (b) protein identifications from 18 MS/MS datasets; (c) independent analyses from raw MS-MS spectra; (d) search engine performance, subproteome analyses, and biological insights; (e) antibody arrays; and (f) direct MS/SELDI analyses. MS-MS datasets had 15 710 different International Protein Index (IPI) protein IDs; our integration algorithm applied to multiple matches of peptide sequences yielded 9504 IPI proteins identified with one or more peptides and 3020 proteins identified with two or more peptides (the Core Dataset). These proteins have been characterized with Gene Ontology, InterPro, Novartis Atlas, OMIM, and immunoassay-based concentration determinations. The database permits examination of many other subsets, such as 1274 proteins identified with three or more peptides. Reverse protein to DNA matching identified proteins for 118 previously unidentified ORFs. We recommend use of plasma instead of serum, with EDTA (or citrate) for anticoagulation. To improve resolution, sensitivity and reproducibility of peptide identifications and protein matches, we recommend combinations of depletion, fractionation, and MS/MS technologies, with explicit criteria for evaluation of spectra, use of search algorithms, and integration of homologous protein matches. This Special Issue of PROTEOMICS presents papers integral to the collaborative analysis plus many reports of supplementary work on various aspects of the PPP workplan. These PPP results on complexity, dynamic range, incomplete sampling, false-positive matches, and integration of diverse datasets for plasma and serum proteins lay a foundation for development and validation of circulating protein biomarkers in health and disease.

The data collected by Human Proteome Organization's Plasma Proteome Pilot project phase was analyzed by members of our working group. Accordingly, a functional annotation of the human plasma proteome was carried out. Here, we report the findings of our analyses. First, bioinformatic analyses were undertaken to determine the likely sources of plasma proteins and to develop a protein interaction network of proteins identified in this project. Second, annotation of these proteins was performed in the context of functional subproteomes involved in the coagulation pathway, the mononuclear phagocytic system, the inflammation pathway, the cardiovascular system, and the liver; as well as the subset of proteins associated with DNA binding activities. Our analyses contributed to the Plasma Proteome Database (http://www.plasmaproteomedatabase.org), an annotated database of plasma proteins identified by HPPP as well as from other published studies. In addition, we address several methodological considerations including the selective enrichment of post-translationally modified proteins by the use of multi-lectin chromatography as well as the use of peptidomic techniques to characterize the low molecular weight proteins in plasma. Furthermore, we have performed additional analyses of peptide identification data to annotate cleavage of signal peptides, sites of intra-membrane proteolysis and post-translational modifications. The HPPP-organized, multi-laboratory effort, as described herein, resulted in much synergy and was essential to the success of this project.

Atopic dermatitis (AD) is a chronic relapsing inflammatory skin disease typically characterized by a distribution of eczematous skin lesions with lichenification, pruritic excoriations, and dry skin with wide varieties of pathophysiologic aspects. Recently, AD was divided into extrinsic and intrinsic forms according to the presence or absence of an allergy. We investigated alterations in protein expression in primary cultured AD cells from the patient biopsy samples by two-dimensional gel electrophoresis (2-DE) and matrix-assisted laser desorption/ionization-time of flight. In the primary cultured fibroblasts, we obtained 31 candidate proteins from the two-dimensional gel image analysis in which 18 proteins were up-regulated, eight proteins were down-regulated and five proteins were post-translationally modified. From these 2-DE results, we found several candidate genes matched proteomic expression patterns by semiquantitative reverse transcription PCR. Since the exact mechanism of atopic alterations in fibroblasts remains unknown, our results may provide new clues to aid in understanding AD.

Heat shock proteins (HSPs) are crucial for the maintenance of cell integrity during normal cellular growth as well as during pathophysiological conditions. While functioning mainly as molecular chaperones, HSPs also appear to be involved in diverse biological activities, such as apoptosis, carcinogenesis, and cytoprotection from cytotoxic damage. Infection with Helicobacter pylori causes inflammation in the gastric mucosa, leading to gastritis, gastric ulcers, duodenal ulcer disease, and even gastric cancer, but the role of HSPs in H. pylori-associated gastropathy is not known. Using two-dimensional electrophoretic analysis, we have observed significant shifts in HSP profiles after H. pylori infection in RGM-1 cells. We therefore evaluated the effect of treatments that induce HSPs on H. pylori-induced inducible nitric oxide synthase (iNOS) expression. We found that H. pylori infection significantly attenuated the expression of HSP70, whereas exposure of cells to noncytotoxic heat shock or geranylgeranylacetone restored HSP70 expression, as well as suppressing the expression of iNOS, a major cause of H. pylori-induced gastric tissue damage. Our results suggest that induction of HSP70 confers cytoprotection against H. pylori infection by inhibiting the expression of iNOS. In conclusion, these results provide important insights into the flux in HSPs profiles in response to H. pylori infection and highlight the cytoprotective role of HSP70 in H. pylori infection.

The histopathologic type of lung cancer is known to be correlated with tumor behavior and prognosis. However, this classification is subjective and no specific molecular markers have been identified. The aim of this study was to identify protein markers in different types of nonsmall cell lung cancers. Two-dimensional polyacrylamide gel electrophoresis analysis was performed with paired samples of three squamous cell carcinomas, three adenocarcinomas, four large cell carcinomas, and four basaloid carcinomas. We found that 25 proteins in 14 cases of lung cancer were differentially expressed compared to matched nontumorous lung tissues. Among these 25 proteins, 11 proteins were down-regulated and 14 were up-regulated in these four types of lung cancer. Alloalbumin venezia, selenium-binding protein 1, carbonic dehydratase, heat shock 20KD-like protein, and SM22 alpha protein were down-regulated in all 14 cases of lung cancer examined, whereas alpha enolase was consistently up-regulated. Supervised hierarchical cluster analysis based on the 25 differentially expressed proteins showed that basaloid carcinoma formed one independent group, whereas the other three cancer types were not uniquely classifiable. Our findings suggest that basaloid carcinoma is a unique subtype of nonsmall cell lung carcinoma.

Proteomic analysis of brain tissues obtained from two inbred mice, C57BL/6J (B6, an alcohol-preferring strain) and DBA/2J (D2, an alcohol-avoiding strain), that were orally administered 1.5 g/kg ethanol, was performed to investigate alcohol-responsive proteins. To analyze relationships of alcohol-responsive protein spots between B6 and D2 mice, we have developed a simple spot classification method (SCM) for the fully matched spot data sets produced by the Melanie 4 analysis software using the paired two-dimensional (2-D) gels of two strains over time. By applying SCM, 55 protein spots that were differentially expressed in brain tissue were classified into 16 patterns as mirror images (2x8 patterns), and additionally in an ordered fashion such as 'fast turn over' and 'slow turn over' forms, depending on the frequency of repetition and rate of changed expression profile in 2-D gels over time. Searching for any interaction proteins through databases of interacting proteins using the classified data set has led to the construction of a linkage map, which reveals the interrelationship of the alcohol-responsive proteins between different species. Thus, it is suggested that the different responses for alcohol between B6 and D2 may come from differences of the response rates and interactions of different variants of the alcohol-responsive protein family.

To study alcohol-related metabolism across inbred mouse strains, liver tissues from C57BL/6J (B6, an alcohol-preferring mouse) and DBA/2J (D2, an alcohol-avoiding strain) mice were analyzed for proteomic expression patterns over time after a single-dose of alcohol (1.5 g/kg ingestion). Despite no significant difference in the elimination rate of blood ethanol, two-dimensional electrophoresis gel images of liver proteins showed that proteins in B6 mice exhibited faster response and more quantitative (spot numbers) and qualitative (spot densities) changes than in D2 mice. Among the differentially expressed metabolic enzymes, four variants (alpha, beta, gamma and delta) of fructose 1,6-bisphosphatase (FBPase), a key regulatory gluconeogenic enzyme, showed remarkable changes in expression with time across the strains. The degree of spot alteration in alpha- and gamma-variants of FBPase in B6 mice was much higher than in D2 mice, while the beta- and delta-forms were not changed as much. Mass spectrometry (MS) analysis showed that the 1714.9 +/- 1 mass peak from the alpha- and gamma-variants of FBPase was much stronger than that of the beta- and delta-variants in both strains regardless of spot density. This MS peak contains 2-ANHAPFETDISTLTR-16, located at the N-terminal of FBPase, where the N-terminal alanine was found to be trimethylated. Thus, we propose this N-terminal fragment as a potential site for enzyme modification in response to ethanol, allowing for differences in two-dimensional gel spot intensity of variants of FBPase in the two mouse strains.

We report here a proteomic analysis of differentially expressed liver proteins of both C57BL/6J (B6, atherosclerosis-susceptible strain) and C3H/HeJ mice (C3H, atherosclerosis-resistant strain), which were fed either control or a high-fat enriched atherogenic diet for eight weeks. We observed differential patterns of plasma lipids between the two strains when both were fed atherogenic diets. That is, although low density lipoprotein cholesterol level was highly elevated in both, the levels of total cholesterol and triglyceride in B6 mice were much lower than those in C3H mice when they were fed atherogenic diets. However, the high density lipoprotein cholesterol level was increased in the latter but decreased in the former. Histopathological observation revealed that more prominent lipid droplets were present in B6 mice than in C3H mice, when they were maintained on the atherogenic diets. Proteomic analysis of liver tissues of these two strains showed that a total of 30 proteins were significantly changed in the livers obtained from both strains after being fed the atherogenic diet. Of these, 14 protein spots including carbonic anhydrase III, senescence marker protein 30 and selenium binding protein 2 were differentially changed only in B6 mice, which was also confirmed in part by Western blotting. An additional 16 protein spots including glutathione S-transferase subclass, apolipoprotein E and chaperonin proteins were changed in both strains. We also identified 28 proteins that were differentially expressed in the livers of both B6 and C3H mice, regardless of diet feeding condition. Of these, 4 protein spots in B6 mice and 11 protein spots in C3H mice were up-regulated. Thirteen strain specific protein spots including antioxidant protein 2, apolipoprotein E and apolipoprotein A-I were also detected in different positions in two-dimensional electrophoresis. These results suggest a clear distinction in differential expression of oxidative stress proteins and lipid metabolism related proteins between the two strains in response to atherogenic diet feeding, which might account for their difference in susceptibility to atherogenesis.

Lightning Fast is a sensitive fluorescence-based stain for detecting proteins in one-dimensional and two-dimensional polyacrylamide electrophoresis gels. It contains the fluorophore epicocconone from the fungus Epicoccum nigrum that interacts noncovalently with sodium dodecyl sulfate and protein. Stained proteins can be excited optimally by near-ultraviolet light of about 395 nm or with visible light of about 520 nm. The stain can be excited using a range of sources used in image analysis systems including UVA (ca. 365 nm) and UVB (ca. 302 nm) transilluminators; Xenon-arc lamps; 488 nm and 457 nm Argon-ion lasers; 473 nm and 532 nm neodymium: yttrium aluminum garnet (Nd:YAG) solid-state lasers; 543 nm helium-neon lasers, and emerging violet, blue and green diode lasers. Maximum fluorescence emission of the dye is at approximately 610 nm. The limit of detection in one-dimensional gels stained with Lightning Fast protein gel stain is less than 100 pg of protein, rivaling the current limits of matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS). Lightning Fast was found to be considerably more sensitive than SYPRO Ruby, SYPRO Orange, silver and Coomassie Brilliant Blue G-250 in matched experiments. Staining takes as little as 3.5 h and stained proteins displayed quantitative linearity over more than four orders of magnitude, thereby allowing visualization of entire proteomes. Lightning Fast protein gel staining is compatible with subsequent peptide mass fingerprinting using MALDI-MS and Edman-based sequencing chemistry.

Mass spectrometric peptide mapping of proteins separated by two-dimensional gel electrophoresis can be routinely performed by matrix-assisted laser desorption/ionization mass spectrometry (MALDI-MS) which has become a standard tool. Since MALDI-MS detection relies heavily on the quality of the MALDI target, development of an efficient sample preparation technique for removal of sample contaminants is necessary. To date, among the several sample preparation techniques for MALDI targets available, multistep perfusion chromatography (MSPC) using Poros R2 and Oligo R3 has been most commonly used. However, MSPC requires at least four working steps and is not efficient for high-throughput analysis and recovery of low abundance proteins. During the course of proteomic analysis of a large set of rat liver tissues and the immortalized human sebaceous gland cells (SZ95 cells), we were interested in developing an alternative to MSPC. Here, we describe a single-step perfusion chromatography (SSPC) method for MALDI target preparation, which uses a tiny column packed with a mixture of Poros R2 and Oligo R3 resins. The SSPC method significantly improves not only detection of peptides but also efficiency of sample handling, thus enabling high-throughput sample preparation for analyzing large set of samples with high resolution and reproducibility.

The senescence-accelerated mouse (SAM) is a useful animal model to study aging or age-associated disorders due to its inherited aging phenotype. To investigate proteins involved in the aging process in liver, we compared the young (4- or 20-week old) and the aged group (50-week-old) of SAMP8 (short life span) and SAMR1 (control) mice, and identified 85 differentially expressed distinct proteins comprising antioxidation, glucose/amino acid metabolism, signal transduction and cell cycle systems using proteomics tools. For the antioxidation system, the aged SAMP8 mice showed a large increase in glutathione peroxidase and decreases in glutathione-S-transferase and peroxiredoxin, ranging from 2.5- to 5-fold, suggesting lower detoxification potentials for oxidants in the aged SAMP8 liver. Similarly, levels of key glycolytic enzymes decreased greatly in the aged SAMP8 compared to SAMR1, indicating a disturbance in glucose homeostasis that may be closely related to the typical deficits in learning and memory of the aged SAMP8. Protein profiles of amino acid metabolic enzymes suggest that accumulation of glutamine and glutamate in tissues of the aged SAMP8 may be due to hyperexpression of ornithine aminotransferase and/or glutamate dehydrogenase. Decreases in levels of proteins involved in signal transduction/apoptosis (e.g., cathepsin B) in the aged SAMP8 may support the previously proposed negative relationship between apoptosis and aging. However, the changes described above were not markedly seen in the young group of both strains. For cell cycle systems, levels of selenium binding protein increased about four-fold with age in SAMP8. Yet, almost no change occurred in either the young or the aged SAMR1, which may explain problems associated with cell proliferation and tissue regeneration in the aged SAMP8. In conclusion, composite profiles of key proteins involved in age-related processes enable assessment of accelerated senescence and the appearance of senescence-related pathologies in the aged SAMP8.

Two-dimensional gel electrophoresis (2-DE) is currently the method of choice for separating complex mixtures of proteins for visual comparison in proteome analysis. This technology, however, is biased against certain classes of proteins including low abundance and hydrophobic proteins. Proteins with extremely alkaline isoelectric points (pI) are often very poorly represented using 2-DE technology, even when complex mixtures are separated using commercially available pH 6-11 or pH 7-10 immobilized pH gradients. The genome of the human gut pathogen, Helicobacter pylori, is dominated by genes encoding basic proteins, and is therefore a useful model for examining methodology suitable for separating such proteins. H. pylori proteins were separated on pH 6-11 and novel pH 9-12 immobilized pH gradients and 65 protein spots were subjected to matrix-assisted laser desorption/ionization-time of flight mass spectrometry, leading to the identification of 49 unique proteins. No proteins were characterized with a theoretical pI of greater than 10.23. A second approach to examine extremely alkaline proteins (pI > 9.0) utilized a prefractionation isoelectric focusing. Proteins were separated into two fractions using Gradiflow technology, and the extremely basic fraction subjected to both sodium dodecyl sulphate-polyacrylamide gel electrophoresis and liquid chromatography (LC) - tandem mass spectrometry post-tryptic digest, allowing the identification of 17 and 13 proteins, respectively. Gradiflow separations were highly specific for proteins with pI > 9.0, however, a single LC separation only allowed the identification of peptides from highly abundant proteins. These methods and those encompassing multiple LC 'dimensions' may be a useful complement to 2-DE for 'near-to-total' proteome coverage in the alkaline pH range.

We describe an integrated proteome database, termed Yonsei Proteome Research Center Proteome Database (YPRC-PDB) which can store, retrieve and analyze various information including two-dimensional electrophoresis (2-DE) images and associated spot information that were obtained during studies of hepatocellular carcinoma (HCC). YPRC-PDB is also designed to perform as a laboratory information management system that manages sample information, clinical background, conditions of both sample preparation and 2-DE, and entire sets of experimental results. It also features query system and data-mining applications, which are amenable to automatically analyze expression level changes of a specific protein and directly link to clinical information. The user interface is web-based, so that the results from other laboratories can be shared effectively. In particular, the master gel image query is equipped with a graphic tool that can easily identify the relationship between the specific pathological stage of HCC and expression levels of a potential marker protein on the master gel image. Thus, YPRC-PDB is a versatile integrated database suitable for subsequent analyses. The information in YPRC-PDB is updated easily and it is available to authorized users on the World Wide Web (http://yprcpdb.proteomix.org/ approximately damduck/).