Biomedical subjects

Eugene C Yi

Publications and source records attributed to Eugene C Yi.

At least 19 recordsLinked to original sources

PubMed2006

UniPep--a database for human N-linked glycosites: a resource for biomarker discovery.

There has been considerable recent interest in proteomic analyses of plasma for the purpose of discovering biomarkers. Profiling N-linked glycopeptides is a particularly promising method because the population of N-linked glycosites represents the proteomes of plasma, the cell surface, and secreted proteins at very low redundancy and provides a compelling link between the tissue and plasma proteomes. Here, we describe UniPep http://www.unipep.org--a database of human N-linked glycosites--as a resource for biomarker discovery.

Computational Biology↗

PubMed2006

Proteome analysis of Halobacterium sp. NRC-1 facilitated by the biomodule analysis tool BMSorter.

To better understand the extremely halophilic archaeon Halobacterium species NRC-1, we analyzed its soluble proteome by two-dimensional liquid chromatography coupled to electrospray ionization tandem mass spectrometry. A total of 888 unique proteins were identified with a ProteinProphet probability (P) between 0.9 and 1.0. To evaluate the biochemical activities of the organism, the proteomic data were subjected to a biological network analysis using our BMSorter software. This allowed us to examine the proteins expressed in different biomodules and study the interactions between pertinent biomodules. Interestingly an integrated analysis of the enzymes in the amino acid metabolism and citrate cycle networks suggested that up to eight amino acids may be converted to oxaloacetate, fumarate, or oxoglutarate in the citrate cycle for energy production. In addition, glutamate and aspartate may be interconverted from other amino acids or synthesized from citrate cycle intermediates to meet the high demand for the acidic amino acids that are required to build the highly acidic proteome of the organism. Thus this study demonstrated that proteome analysis can provide useful information and help systems analyses of organisms.

Amino Acids↗

PubMed2006

Quantitative proteomic profiling of pancreatic cancer juice.

Pancreatic juice is an exceptionally rich source of cancer-specific proteins shed from cancerous ductal cells into the pancreatic juice. Quantitative proteomic analysis of the proteins specific to pancreatic cancer juice has not previously been reported. We used isotope-code affinity tag (ICAT) technology and MS/MS to perform quantitative protein profiling of pancreatic juice from pancreatic cancer patients and normal controls. ICAT technology coupled with MS/MS allows the systematic study of the proteome and measures the protein abundance in pancreatic juice with the potential for development of biomarkers. A total of 105 proteins were identified and quantified in the pancreatic juice from a pancreatic cancer patient, of which 30 proteins showed abundance changes of at least twofold in pancreatic cancer juice compared to normal controls. Many of these proteins have been externally validated. This is the first comprehensive study of the pancreatic juice proteome by quantitative global protein profiling, and the study reveals numerous proteins that are shown for the first time to be associated with pancreatic cancer, providing candidates for diagnostic biomarkers. One of the identified proteins, insulin-like growth factor binding protein-2 was further validated by Western blotting to be elevated in pancreatic cancer juice and overexpressed in pancreatic cancer tissue.

Amino Acid Sequence↗

PubMed2005

The mobile nucleoporin Nup2p and chromatin-bound Prp20p function in endogenous NPC-mediated transcriptional control.

Nuclear pore complexes (NPCs) govern macromolecular transport between the nucleus and cytoplasm and serve as key positional markers within the nucleus. Several protein components of yeast NPCs have been implicated in the epigenetic control of gene expression. Among these, Nup2p is unique as it transiently associates with NPCs and, when artificially tethered to DNA, can prevent the spread of transcriptional activation or repression between flanking genes, a function termed boundary activity. To understand this function of Nup2p, we investigated the interactions of Nup2p with other proteins and with DNA using immunopurifications coupled with mass spectrometry and microarray analyses. These data combined with functional assays of boundary activity and epigenetic variegation suggest that Nup2p and the Ran guanylyl-nucleotide exchange factor, Prp20p, interact at specific chromatin regions and enable the NPC to play an active role in chromatin organization by facilitating the transition of chromatin between activity states.

Active Transport, Cell Nucleus↗

PubMed2005

A software suite for the generation and comparison of peptide arrays from sets of data collected by liquid chromatography-mass spectrometry.

There is an increasing interest in the quantitative proteomic measurement of the protein contents of substantially similar biological samples, e.g. for the analysis of cellular response to perturbations over time or for the discovery of protein biomarkers from clinical samples. Technical limitations of current proteomic platforms such as limited reproducibility and low throughput make this a challenging task. A new LC-MS-based platform is able to generate complex peptide patterns from the analysis of proteolyzed protein samples at high throughput and represents a promising approach for quantitative proteomics. A crucial component of the LC-MS approach is the accurate evaluation of the abundance of detected peptides over many samples and the identification of peptide features that can stratify samples with respect to their genetic, physiological, or environmental origins. We present here a new software suite, SpecArray, that generates a peptide versus sample array from a set of LC-MS data. A peptide array stores the relative abundance of thousands of peptide features in many samples and is in a format identical to that of a gene expression microarray. A peptide array can be subjected to an unsupervised clustering analysis to stratify samples or to a discriminant analysis to identify discriminatory peptide features. We applied the SpecArray to analyze two sets of LC-MS data: one was from four repeat LC-MS analyses of the same glycopeptide sample, and another was from LC-MS analysis of serum samples of five male and five female mice. We demonstrate through these two study cases that the SpecArray software suite can serve as an effective software platform in the LC-MS approach for quantitative proteomics.

Amino Acid Sequence↗

PubMed2005

Nop53p is a novel nucleolar 60S ribosomal subunit biogenesis protein.

Ribosome biogenesis in Saccharomyces cerevisiae occurs primarily in a specialized nuclear compartment termed the nucleolus within which the rRNA genes are transcribed by RNA polymerase I into a large 35 S rRNA precursor. The ensuing association/dissociation and catalytic activity of numerous trans-acting protein factors, RNAs and ribosomal proteins ultimately leads to the maturation of the precursor rRNAs into 25, 5.8 and 18 S rRNAs and the formation of mature cytoplasmic 40 and 60 S ribosomal subunits. Although many components involved in ribosome biogenesis have been identified, our understanding of this essential cellular process remains limited. In the present study we demonstrate a crucial role for the previously uncharacterized nucleolar protein Nop53p (Ypl146p) in ribosome biogenesis. Specifically, Nop53p appears to be most important for biogenesis of the 60 S subunit. It physically interacts with rRNA processing factors, notably Cbf5p and Nop2p, and co-fractionates specifically with pre-60 S particles on sucrose gradients. Deletion or mutations within NOP53 cause significant growth defects and display significant 60 S subunit deficiencies, an imbalance in the 40 S:60 S ratio, as revealed by polysome profiling, and defects in progression beyond the 27 S stage of 25 S rRNA maturation during 60 S biogenesis.

Cell Nucleolus↗

PubMed2005

Evidence for the presence of disease-perturbed networks in prostate cancer cells by genomic and proteomic analyses: a systems approach to disease.

Prostate cancer is initially responsive to androgen ablation therapy and progresses to androgen-unresponsive states that are refractory to treatment. The mechanism of this transition is unknown. A systems approach to disease begins with the quantitative delineation of the informational elements (mRNAs and proteins) in various disease states. We employed two recently developed high-throughput technologies, massively parallel signature sequencing (MPSS) and isotope-coded affinity tag, to gain a comprehensive picture of the changes in mRNA levels and more restricted analysis of protein levels, respectively, during the transition from androgen-dependent LNCaP (model for early-stage prostate cancer) to androgen-independent CL1 cells (model for late-stage prostate cancer). We sequenced >5 million MPSS signatures, obtained >142,000 tandem mass spectra, and built comprehensive MPSS and proteomic databases. The integrated mRNA and protein expression data revealed underlying functional differences between androgen-dependent and androgen-independent prostate cancer cells. The high sensitivity of MPSS enabled us to identify virtually all of the expressed transcripts and to quantify the changes in gene expression between these two cell states, including functionally important low-abundance mRNAs, such as those encoding transcription factors and signal transduction molecules. These data enable us to map the differences onto extant physiologic networks, creating perturbation networks that reflect prostate cancer progression. We found 37 BioCarta and 14 Kyoto Encyclopedia of Genes and Genomes pathways that are up-regulated and 23 BioCarta and 22 Kyoto Encyclopedia of Genes and Genomes pathways that are down-regulated in LNCaP cells versus CL1 cells. Our efforts represent a significant step toward a systems approach to understanding prostate cancer progression.

Cell Line, Tumor↗

PubMed2005

Increased quantitative proteome coverage with (13)C/(12)C-based, acid-cleavable isotope-coded affinity tag reagent and modified data acquisition scheme.

Quantitative protein profiling using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS) enables the pair-wise comparison of protein expression levels in biological samples. A new version of the ICAT reagent with an acid-cleavable bond, which allows removal of the biotin moiety prior to MS and which utilizes (13)C substitution for (12)C in the heavy-ICAT reagent rather than (2)H (for (1)H) as in the original reagent, was investigated. We developed and validated an MS data acquisition strategy using this new reagent that results in an increased number of protein identifications per experiment, without losing the accuracy of protein quantification. This was achieved by following a single survey (precursor) ion scan and serial collision induced dissociations (CIDs) of four different precursor ions observed in the prior survey scan. This strategy is common to many high-performance liquid chromatography-electrospray ionization (HPLC-ESI)-MS shotgun proteomic strategies, but heretofore not to ICAT experiments. This advance is possible because the new ICAT reagent uses (13)C as the "heavy" element rather than (2)H, thus, eliminating the slight delay in retention time of ICAT-labeled "light" peptides on a C18-based HPLC separation that occurs with (2)H and (1)H. Analyses using this new scheme of an ICAT-labeled trypsin-digested six protein mixture as well as a tryptic digest of a total yeast lysate, indicated that about two times more proteins were identified in a single analysis, and that there was no loss in accuracy of quantification.

Carbon↗

PubMed2005

Human Plasma PeptideAtlas.

Peptide identifications of high probability from 28 LC-MS/MS human serum and plasma experiments from eight different laboratories, carried out in the context of the HUPO Plasma Proteome Project, were combined and mapped to the EnsEMBL human genome. The 6929 distinct observed peptides were mapped to approximately 960 different proteins. The resulting compendium of peptides and their associated samples, proteins, and genes is made publicly available as a reference for future research on human plasma.

Blood Proteins↗

PubMed2005

Proteomic identification of potential susceptibility factors in drug-induced liver disease.

Drug-induced liver disease (DILD) causes significant morbidity and mortality and impairs new drug development. Currently, no known criteria can predict whether a drug will cause DILD or what risk factors make an individual susceptible. Although it has been shown in mouse studies that the disruption of key regulatory factors, such as cyclooxygenase-2 (COX-2), interleukin (IL)-6, and IL-10, increased susceptibility to DILD caused by acetaminophen (APAP), no single factor seems to be absolute. As an approach to better understand the multifactorial basis of DILD, we compared the hepatic proteome of mice that are resistant (SJL) and susceptible (C57Bl/6) to APAP-induced liver disease (AILD), using solution-based isotope-coded affinity tag (ICAT) liquid chromatography mass spectrometry. Several novel factors were identified that were more highly expressed in the livers of SJL mice, including those involved in stress response, cell proliferation and tissue regeneration, and protein modification, implicating these proteins as potential hepatoprotective factors. There was also a selective loss of several mitochondrial proteins from the livers of the susceptible C57Bl/6 mice, suggesting that the loss of functional mitochondria may indeed play a role in AILD. These findings indicate that comparative hepatic proteomic analyses of susceptible and resistant mouse strains may provide a global approach for identifying potential risk factors and mechanistic pathways responsible for DILD.

Acetaminophen↗

PubMed2005

Pancreatic cancer proteome: the proteins that underlie invasion, metastasis, and immunologic escape.

BACKGROUND & AIMS: Pancreatic cancer is a highly lethal disease that has seen little headway in diagnosis and treatment for the past few decades. The effective treatment of pancreatic cancer is critically relying on the diagnosis of the disease at an early stage, which still remains challenging. New experimental approaches, such as quantitative proteomics, have shown great potential for the study of cancer and have opened new opportunities to investigate crucial events underlying pancreatic tumorigenesis and to exploit this knowledge for early detection and better intervention. METHODS: To systematically study protein expression in pancreatic cancer, we used isotope-coded affinity tag technology and tandem mass spectrometry to perform quantitative proteomic profiling of pancreatic cancer tissues and normal pancreas. RESULTS: A total of 656 proteins were identified and quantified in 2 pancreatic cancer samples, of which 151 were differentially expressed in cancer by at least 2-fold. This study revealed numerous proteins that are newly discovered to be associated with pancreatic cancer, providing candidates for future early diagnosis biomarkers and targets for therapy. Several differentially expressed proteins were further validated by tissue microarray immunohistochemistry. Many of the differentially expressed proteins identified are involved in protein-driven interactions between the ductal epithelium and the extracellular matrix that orchestrate tumor growth, migration, angiogenesis, invasion, metastasis, and immunologic escape. CONCLUSIONS: Our study is the first application of isotope-coded affinity tag technology for proteomic analysis of human cancer tissue and has shown the value of this technology in identifying differentially expressed proteins in cancer.

Humans↗

PubMed2004

High throughput quantitative analysis of serum proteins using glycopeptide capture and liquid chromatography mass spectrometry.

It is expected that the composition of the serum proteome can provide valuable information about the state of the human body in health and disease and that this information can be extracted via quantitative proteomic measurements. Suitable proteomic techniques need to be sensitive, reproducible, and robust to detect potential biomarkers below the level of highly expressed proteins, generate data sets that are comparable between experiments and laboratories, and have high throughput to support statistical studies. Here we report a method for high throughput quantitative analysis of serum proteins. It consists of the selective isolation of peptides that are N-linked glycosylated in the intact protein, the analysis of these now deglycosylated peptides by liquid chromatography electrospray ionization mass spectrometry, and the comparative analysis of the resulting patterns. By focusing selectively on a few formerly N-linked glycopeptides per serum protein, the complexity of the analyte sample is significantly reduced and the sensitivity and throughput of serum proteome analysis are increased compared with the analysis of total tryptic peptides from unfractionated samples. We provide data that document the performance of the method and show that sera from untreated normal mice and genetically identical mice with carcinogen-induced skin cancer can be unambiguously discriminated using unsupervised clustering of the resulting peptide patterns. We further identify, by tandem mass spectrometry, some of the peptides that were consistently elevated in cancer mice compared with their control littermates.

Animals↗

PubMed2004

Integration with the human genome of peptide sequences obtained by high-throughput mass spectrometry.

A crucial aim upon the completion of the human genome is the verification and functional annotation of all predicted genes and their protein products. Here we describe the mapping of peptides derived from accurate interpretations of protein tandem mass spectrometry (MS) data to eukaryotic genomes and the generation of an expandable resource for integration of data from many diverse proteomics experiments. Furthermore, we demonstrate that peptide identifications obtained from high-throughput proteomics can be integrated on a large scale with the human genome. This resource could serve as an expandable repository for MS-derived proteome information.

Amino Acid Sequence↗

PubMed2004

Quantitative proteomic analysis of metabolic regulation by copper ions in Methylococcus capsulatus (Bath).

Copper ions switch the oxidation of methane by soluble methane monooxygenase to particulate methane monooxygenase in Methylococcus capsulatus (Bath). Toward understanding the change in cellular metabolism related to this transcriptional and metabolic switch, we have undertaken genomic sequencing and quantitative comparative analysis of the proteome in M. capsulatus (Bath) grown under different copper-to-biomass ratios by cleavable isotope-coded affinity tag technology. Of the 682 proteins identified, the expressions of 60 proteins were stimulated by at least 2-fold by copper ions; 68 proteins were down-regulated by 2-fold or more. The 60 proteins overexpressed included the methane and carbohydrate metabolic enzymes, while the 68 proteins suppressed were mainly responsible for cellular signaling processes, indicating a role of copper ions in the expression of the genes associated with the metabolism of the organism downstream of methane oxidation. The study has also provided a complete map of the C1 metabolism pathways in this methanotroph and clarified the interrelationships between them.

Bacterial Proteins↗

PubMed2004

System-based proteomic analysis of the interferon response in human liver cells.

BACKGROUND: Interferons (IFNs) play a critical role in the host antiviral defense and are an essential component of current therapies against hepatitis C virus (HCV), a major cause of liver disease worldwide. To examine liver-specific responses to IFN and begin to elucidate the mechanisms of IFN inhibition of virus replication, we performed a global quantitative proteomic analysis in a human hepatoma cell line (Huh7) in the presence and absence of IFN treatment using the isotope-coded affinity tag (ICAT) method and tandem mass spectrometry (MS/MS). RESULTS: In three subcellular fractions from the Huh7 cells treated with IFN (400 IU/ml, 16 h) or mock-treated, we identified more than 1,364 proteins at a threshold that corresponds to less than 5% false-positive error rate. Among these, 54 were induced by IFN and 24 were repressed by more than two-fold, respectively. These IFN-regulated proteins represented multiple cellular functions including antiviral defense, immune response, cell metabolism, signal transduction, cell growth and cellular organization. To analyze this proteomics dataset, we utilized several systems-biology data-mining tools, including Gene Ontology via the GoMiner program and the Cytoscape bioinformatics platform. CONCLUSIONS: Integration of the quantitative proteomics with global protein interaction data using the Cytoscape platform led to the identification of several novel and liver-specific key regulatory components of the IFN response, which may be important in regulating the interplay between HCV, interferon and the host response to virus infection.

Cell Line, Tumor↗

PubMed2004

Integrated genomic and proteomic analyses of gene expression in Mammalian cells.

Using DNA microarrays together with quantitative proteomic techniques (ICAT reagents, two-dimensional DIGE, and MS), we evaluated the correlation of mRNA and protein levels in two hematopoietic cell lines representing distinct stages of myeloid differentiation, as well as in the livers of mice treated for different periods of time with three different peroxisome proliferative activated receptor agonists. We observe that the differential expression of mRNA (up or down) can capture at most 40% of the variation of protein expression. Although the overall pattern of protein expression is similar to that of mRNA expression, the incongruent expression between mRNAs and proteins emphasize the importance of posttranscriptional regulatory mechanisms in cellular development or perturbation that can be unveiled only through integrated analyses of both proteins and mRNAs.

Animals↗

PubMed2004

A tool to visualize and evaluate data obtained by liquid chromatography-electrospray ionization-mass spectrometry.

We present a software tool for visualizing data obtained from analyzing complex peptide mixtures by liquid chromatography (LC) electrospray ionization (ESI) mass spectrometry (MS). The data are represented as a two-dimensional density plot. For experiments employing collision-induced dissociation (CID), links are embedded in the image to the CID spectra and the corresponding peptide sequences that are represented by the respective feature. The image provides an intuitive method to evaluate sample quality and the performance of an LC-ESI-MS system and can be used to optimize experimental conditions. Local patterns of the image can also be used to identify chemical contaminants and specific peptide features. Therefore, this software tool may have broad application in MS-based proteomics.

Chromatography, Liquid↗

PubMed2004

Identification of TFB5, a new component of general transcription and DNA repair factor IIH.

We previously described the use of quantitative proteomics to study macromolecular complexes. Applying the method to analyze a yeast RNA polymerase II preinitiation complex, we identified a new 8-kDa protein, encoded by the uncharacterized open reading frame YDR079c-a, as a potential new component of the preinitiation complex. Here we show that YDR079c-a is a bona fide component of polymerase II preinitiation complexes and investigate its role in transcription. YDR079c-a is recruited to promoters both in vivo and in vitro and is required for efficient transcription in vitro and for normal induction of GAL genes. In addition, YDR079c-a is a core component of general transcription and DNA repair factor IIH and is required for efficient recruitment of TFIIH to a promoter. Yeast lacking YDR079c-a grow slowly, and, like strains carrying mutations in core TFIIH subunits, are sensitive to ultraviolet radiation. YDR079c-a is conserved throughout evolution, and mutations in the human ortholog account for a DNA repair-deficient form of the tricothiodystrophy disorder called TTD-A(2). The identification of a new, evolutionarily conserved, core TFIIH subunit is essential for our understanding of TFIIH function in transcription, DNA repair and human disease.

DNA Polymerase II↗