Seul-Ki Jeong

Standard guidelines for the chromosome-centric human proteome project.

The objective of the international Chromosome-Centric Human Proteome Project (C-HPP) is to map and annotate all proteins encoded by the genes on each human chromosome. The C-HPP consortium was established to organize a collaborative network among the research teams responsible for protein mapping of individual chromosomes and to identify compelling biological and genetic mechanisms influencing colocated genes and their protein products. The C-HPP aims to foster the development of proteome analysis and integration of the findings from related molecular -omics technology platforms through collaborations among universities, industries, and private research groups. The C-HPP consortium leadership has elicited broad input for standard guidelines to manage these international efforts more efficiently by mobilizing existing resources and collaborative networks. The C-HPP guidelines set out the collaborative consensus of the C-HPP teams, introduce topics associated with experimental approaches, data production, quality control, treatment, and transparency of data, governance of the consortium, and collaborative benefits. A companion approach for the Biology and Disease-Driven HPP (B/D-HPP) component of the Human Proteome Project is currently being organized, building upon the Human Proteome Organizations organ-based and biofluid-based initiatives (www.hupo.org/research). The common application of these guidelines in the participating laboratories is expected to facilitate the goal of a comprehensive analysis of the human proteome.

Human plasma carboxylesterase 1, a novel serologic biomarker candidate for hepatocellular carcinoma

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.

BiomarkerDigger: a versatile disease proteome database and analysis platform for the identification of plasma cancer biomarkers.

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.

Quantitative proteomic analysis of human embryonic stem cell differentiation by 8-plex iTRAQ labelling.

Analysis of gene expression to define molecular mechanisms and pathways involved in human embryonic stem cells (hESCs) proliferation and differentiations has allowed for further deciphering of the self-renewal and pluripotency characteristics of hESC. Proteins associated with hESCs were discovered through isobaric tags for relative and absolute quantification (iTRAQ). Undifferentiated hESCs and hESCs in different stages of spontaneous differentiation by embryoid body (EB) formation were analyzed. Using the iTRAQ approach, we identified 156 differentially expressed proteins involved in cell proliferation, apoptosis, transcription, translation, mRNA processing, and protein synthesis. Proteins involved in nucleic acid binding, protein synthesis, and integrin signaling were downregulated during differentiation, whereas cytoskeleton proteins were upregulated. The present findings added insight to our understanding of the mechanisms involved in hESC proliferation and differentiation.

C. elegans: an invaluable model organism for the proteomics studies of the cholesterol-mediated signaling pathway.

With the availability of its complete genome sequence and unique biological features relevant to human disease, Caenorhabditis elegans has become an invaluable model organism for the studies of proteomics, leading to the elucidation of nematode gene function. A journey from the genome to proteome of C. elegans may begin with preparation of expressed proteins, which enables a large-scale analysis of all possible proteins expressed under specific physiological conditions. Although various techniques have been used for proteomic analysis of C. elegans, systematic high-throughput analysis is still to come in order to accommodate studies of post-translational modification and quantitative analysis. Given that no integrated C. elegans protein expression database is available, it is about time that a global C. elegans proteome project is launched through which datasets of transcriptomes, protein–protein interaction and functional annotation can be integrated. As an initial target of a pilot project of the C. elegans proteome project, the cholesterol-mediated signaling pathway will be an excellent example since, like in other organisms, it is one of the key controlling pathways in cell growth and development in C. elegans. As this field tends to broaden to functional proteomics, there is a high demand to develop the versatile proteome informatics tools that can mange many different data in an integrative manner.

PanelComposer: a web-based panel construction tool for multivariate analysis of disease biomarker candidates.

Measuring and evaluating diagnostic efficiency is important in biomarker discovery and validation. The receiver operating characteristic (ROC) curve is a graphical plot for assessing the performance of a classifier or predictor that can be used to test the sensitivity and specificity of diagnostic biomarkers. In this study, we describe PanelComposer, a Web-based software tool that uses statistical results from proteomic expression data and validates biomarker candidates based on ROC curves and the area under the ROC curve (AUC) values using a logistic regression model and provides an ordered list that includes ROC graphs and AUC values for proteins (individually or in combination). This tool allows users to easily compare and assess the effectiveness and diagnostic efficiency of single or multiprotein biomarker candidates. PanelComposer is available publicly at http://panelcomposer.proteomix.org/ and is compatible with major Web browsers.

Normalization using a tagged-internal standard assay for analysis of antibody arrays and the evaluation of serological biomarkers for liver disease

For minimizing systemic experimental variation in the analysis of antibody array data, we developed a novel median-centered/IgM-tagged-internal standard (TIS) assay normalization using median-centering and TIS assay-based determination of serum IgM concentrations. We evaluated five normalization methods by analyzing correlation coefficients and coefficients of variation for six serum proteins using human serum samples from normal controls (n=25) and patients with liver cirrhosis (n=25) or hepatocellular carcinoma (HCC; n=29). Median-centered normalization improved correlation coefficients, while IgM-based normalizations improved coefficients of variation. The TIS assay was more efficient, economical, and reproducible for determining IgM concentrations than enzyme-linked immunosorbent assay. Additionally, we normalized antibody array data for six serum proteins using the median-centered/IgM-TIS assay, and evaluated serum biomarkers through distribution analysis of normalized fluorescence intensities and receiver operating characteristic analyses for the diagnosis of liver cirrhosis and HCC. Apolipoprotein A-1 and a combination of alpha-fetoprotein and C-reactive protein were determined to be potential serological biomarkers for liver cirrhosis and HCC, respectively. Thus, median-centered/IgM-TIS assay normalization is a useful approach for analyzing antibody array data and evaluating serological biomarkers for the diagnosis of liver disease or cancers.

A potential biochemical mechanism underlying the influence of sterol deprivation stress on Caenorhabditis elegans longevity.

To investigate the biochemical mechanism underlying the effect of sterol deprivation on longevity in Caenorhabditis elegans, we treated parent worms (P0) with 25-azacoprostane (Aza), which inhibits sitosterol-to-cholesterol conversion, and measured mean lifespan (MLS) in F2 worms. At 25 μm (∼EC50), Aza reduced total body sterol by 82.5%, confirming sterol depletion. Aza (25 μm) treatment of wild-type (N2) C. elegans grown in sitosterol (5 μg/ml) reduced MLS by 35%. Similar results were obtained for the stress-related mutants daf-16(mu86) and gas-1(fc21). Unexpectedly, Aza had essentially no effect on MLS in the stress-resistant daf-2(e1370) or mitochondrial complex II mutant mev-1(kn1) strains, indicating that Aza may target both insulin/IGF-1 signaling (IIS) and mitochondrial complex II. Aza increased reactive oxygen species (ROS) levels 2.7-fold in N2 worms, but did not affect ROS production by mev-1(kn1), suggesting a direct link between Aza treatment and mitochondrial ROS production. Moreover, expression of the stress-response transcription factor SKN-1 was decreased in amphid neurons by Aza and that of DAF-28 was increased when DAF-6 was involved, contributing to lifespan reduction.

Data management and functional annotation of the Korean reference plasma proteome

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/).

IntelliMS : A platform to efficiently manage and visualize tandem mass spectral data

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.