Biomedical subjects

Eugene Yi

Publications and source records attributed to Eugene Yi.

9 recordsLinked to original sources

PubMed2006

A statistical method for chromatographic alignment of LC-MS data.

Integrated liquid-chromatography mass-spectrometry (LC-MS) is becoming a widely used approach for quantifying the protein composition of complex samples. The output of the LC-MS system measures the intensity of a peptide with a specific mass-charge ratio and retention time. In the last few years, this technology has been used to compare complex biological samples across multiple conditions. One challenge for comparative proteomic profiling with LC-MS is to match corresponding peptide features from different experiments. In this paper, we propose a new method--Peptide Element Alignment (PETAL) that uses raw spectrum data and detected peak to simultaneously align features from multiple LC-MS experiments. PETAL creates spectrum elements, each of which represents the mass spectrum of a single peptide in a single scan. Peptides detected in different LC-MS data are aligned if they can be represented by the same elements. By considering each peptide separately, PETAL enjoys greater flexibility than time warping methods. While most existing methods process multiple data sets by sequentially aligning each data set to an arbitrarily chosen template data set, PETAL treats all experiments symmetrically and can analyze all experiments simultaneously. We illustrate the performance of PETAL on example data sets.

Animals↗

PubMed2005

Quantitative proteomic analysis of age-related changes in human cerebrospinal fluid.

Identification of cerebrospinal fluid (CSF) biomarkers of the common age-related neurodegenerative diseases would be of great value to clinicians because of the difficulties in differential diagnoses of these diseases in clinical practice. Proteins are one class of potential biomarkers currently under investigation in the hope that different ensembles of proteins will aid in the diagnosis of these diseases, as well as in the assessment of progression and response to therapy. However, before undertaking a rational approach to CSF protein biomarkers of age-related neurodegeneration, we must first systematically identify CSF proteins and determine whether their levels change with normal aging. In this study, we used a powerful shotgun proteomic method, two-dimensional microcapillary liquid chromatography electrospray ionization tandem mass spectrometry, to identify proteins in human CSF. Additionally, using pooled CSF samples, we quantitatively compared the CSF proteome of younger adults with that of older adults using isotope-coded affinity tags (ICAT). From these studies we identified more than 300 proteins in CSF and found that there were 30 proteins with >20% change in concentrations between older and younger individuals. Finally, we validated changes in concentration for two of these proteins using Western blots in CSF from a separate set of individuals. These data not only expand substantially our current knowledge regarding human CSF proteins, but also supply the necessary information to appropriately interpret protein biomarkers of age-related neurodegenerative diseases.

Adult↗

PubMed2005

Quantitative proteomics of cerebrospinal fluid from patients with Alzheimer disease.

Biomarkers to assist in the diagnosis and medical management of Alzheimer disease (AD) are a pressing need. We have employed a proteomic approach, microcapillary liquid chromatography mass spectrometry of proteins labeled with isotope-coded affinity tags (ICAT), to quantify relative changes in the proteome of human cerebrospinal fluid (CSF) obtained from the lumbar cistern. Using CSF from well-characterized AD patients and age-matched controls at 2 different institutions, we quantified protein concentration ratios of 42% of the 390 CSF proteins that we have identified and found differences > or = 20% in over half of them. We confirmed our findings by western blot and validated this approach by quantifying relative levels of amyloid precursor protein and cathepsin B in 17 AD patients and 16 control individuals. Quantitative proteomics of CSF from AD patients compared to age-matched controls, as well as from other neurodegenerative diseases, will allow us to generate a roster of proteins that may serve as specific biomarker panels for AD and other geriatric dementias.

Adult↗

PubMed2004

Quantitative mass spectrometry reveals a role for the GTPase Rho1p in actin organization on the peroxisome membrane.

We have combined classical subcellular fractionation with large-scale quantitative mass spectrometry to identify proteins that enrich specifically with peroxisomes of Saccharomyces cerevisiae. In two complementary experiments, isotope-coded affinity tags and tandem mass spectrometry were used to quantify the relative enrichment of proteins during the purification of peroxisomes. Mathematical modeling of the data from 306 quantified proteins led to a prioritized list of 70 candidates whose enrichment scores indicated a high likelihood of them being peroxisomal. Among these proteins, eight novel peroxisome-associated proteins were identified. The top novel peroxisomal candidate was the small GTPase Rho1p. Although Rho1p has been shown to be tethered to membranes of the secretory pathway, we show that it is specifically recruited to peroxisomes upon their induction in a process dependent on its interaction with the peroxisome membrane protein Pex25p. Rho1p regulates the assembly state of actin on the peroxisome membrane, thereby controlling peroxisome membrane dynamics and biogenesis.

Actins↗

PubMed2004

Quantitative proteomic analysis of proteins released by neoplastic prostate epithelium.

Prostate cancer is unusual among neoplasms in that it may be diagnosed at a curable stage through detection of a protein in serum, the serine protease prostate-specific antigen (PSA). PSA is secreted by both normal and neoplastic prostate epithelial cells in response to androgenic hormones and has found widespread use in cancer screening. Because PSA screening is controversial due to sensitivity and specificity issues, efforts continue to focus on the identification and characterization of additional markers that may be used for diagnostic and therapeutic purposes. In this study, we report the application of quantitative proteomic techniques that incorporate isotope coded affinity tag reagents and tandem mass spectrometry to comprehensively identify secreted and cell surface proteins from neoplastic prostate epithelium. LNCaP cells, a prostate tumor-derived cell line that secretes PSA in response to androgen exposure, were grown in a low protein-defined media under androgen-stimulated (A+) and -starved (A-) conditions. Proteomic analysis of the media identified in excess of 600 proteins, 524 of which could be quantified. Nine percent of the proteins had A+/A- ratios > 2.0, including PSA, and 2.5% had ratios < 0.5. A subset of these androgen-regulated proteins appeared to be expressed in abundance. Of these, selected mass spectrometry observations were confirmed by Western analysis. The findings suggest that androgen-mediated release of proteins may occur through the activation of proteolytic enzymes rather than exclusively through transcriptional or translational control mechanisms. On the basis of their known functional roles, several of the abundant androgen-regulated proteins may participate in the progression of neoplastic epithelial cell growth and should be considered as potential serum markers of neoplastic prostate diseases.

Biomarkers, Tumor↗

PubMed2004

Lipid raft proteins and their identification in T lymphocytes.

This review focuses on how membrane lipid rafts have been detected and isolated, mostly from lymphocytes, and their associated proteins identified. These proteins include transmembrane antigens/receptors, GPI-anchored proteins, cytoskeletal proteins, Src-family protein kinases, G-proteins, and other proteins involved in signal transduction. To further understand the biology of lipid rafts, new methodological approaches are needed to help characterize the raft protein component, and changes that occur in this component as a result of cell perturbation. We describe the application of new proteomic approaches to the identification and quantification of raft proteins in T-lymphocytes. Similar approaches, applied to other model cell systems, will provide valuable new insights into both cellular signal transduction and lipid raft biology.

Animals↗

PubMed2003

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: I. Statistically annotated datasets for peptide sequences and proteins identified via the application of ICAT and tandem mass spectrometry to proteins copurifying with T cell lipid rafts.

Lipid rafts were prepared according to standard protocols from Jurkat T cells stimulated via T cell receptor/CD28 cross-linking and from control (unstimulated) cells. Co-isolating proteins from the control and stimulated cell preparations were labeled with isotopically normal (d0) and heavy (d8) versions of the same isotope-coded affinity tag (ICAT) reagent, respectively. Samples were combined, proteolyzed, and resultant peptides fractionated via cation exchange chromatography. Cysteine-containing (ICAT-labeled) peptides were recovered via the biotin tag component of the ICAT reagents by avidin-affinity chromatography. On-line micro-capillary liquid chromatography tandem mass spectrometry was performed on both avidin-affinity (ICAT-labeled) and flow-through (unlabeled) fractions. Initial peptide sequence identification was by searching recorded tandem mass spectrometry spectra against a human sequence data base using SEQUEST software. New statistical data modeling algorithms were then applied to the SEQUEST search results. These allowed for discrimination between likely "correct" and "incorrect" peptide assignments, and from these the inferred proteins that they collectively represented, by calculating estimated probabilities that each peptide assignment and subsequent protein identification was a member of the "correct" population. For convenience, the resultant lists of peptide sequences assigned and the proteins to which they corresponded were filtered at an arbitrarily set cut-off of 0.5 (i.e. 50% likely to be "correct") and above and compiled into two separate datasets. In total, these data sets contained 7667 individual peptide identifications, which represented 2669 unique peptide sequences, corresponding to 685 proteins and related protein groups.

Amino Acid Sequence↗

PubMed2003

The application of new software tools to quantitative protein profiling via isotope-coded affinity tag (ICAT) and tandem mass spectrometry: II. Evaluation of tandem mass spectrometry methodologies for large-scale protein analysis, and the application of statistical tools for data analysis and interpretation.

Proteomic approaches to biological research that will prove the most useful and productive require robust, sensitive, and reproducible technologies for both the qualitative and quantitative analysis of complex protein mixtures. Here we applied the isotope-coded affinity tag (ICAT) approach to quantitative protein profiling, in this case proteins that copurified with lipid raft plasma membrane domains isolated from control and stimulated Jurkat human T cells. With the ICAT approach, cysteine residues of the two related protein isolates were covalently labeled with isotopically normal and heavy versions of the same reagent, respectively. Following proteolytic cleavage of combined labeled proteins, peptides were fractionated by multidimensional chromatography and subsequently analyzed via automated tandem mass spectrometry. Individual tandem mass spectrometry spectra were searched against a human sequence database, and a variety of recently developed, publicly available software applications were used to sort, filter, analyze, and compare the results of two repetitions of the same experiment. In particular, robust statistical modeling algorithms were used to assign measures of confidence to both peptide sequences and the proteins from which they were likely derived, identified via the database searches. We show that by applying such statistical tools to the identification of T cell lipid raft-associated proteins, we were able to estimate the accuracy of peptide and protein identifications made. These tools also allow for determination of the false positive rate as a function of user-defined data filtering parameters, thus giving the user significant control over and information about the final output of large-scale proteomic experiments. With the ability to assign probabilities to all identifications, the need for manual verification of results is substantially reduced, thus making the rapid evaluation of large proteomic datasets possible. Finally, by repeating the experiment, information relating to the general reproducibility and validity of this approach to large-scale proteomic analyses was also obtained.

Amino Acid Sequence↗

PubMed2003

Initial proteome analysis of model microorganism Haemophilus influenzae strain Rd KW20.

The proteome of Haemophilus influenzae strain Rd KW20 was analyzed by liquid chromatography (LC) coupled with ion trap tandem mass spectrometry (MS/MS). This approach does not require a gel electrophoresis step and provides a rapidly developed snapshot of the proteome. In order to gain insight into the central metabolism of H. influenzae, cells were grown microaerobically and anaerobically in a rich medium and soluble and membrane proteins of strain Rd KW20 were proteolyzed with trypsin and directly examined by LC-MS/MS. Several different experimental and computational approaches were utilized to optimize the proteome coverage and to ensure statistically valid protein identification. Approximately 25% of all predicted proteins (open reading frames) of H. influenzae strain Rd KW20 were identified with high confidence, as their component peptides were unambiguously assigned to tandem mass spectra. Approximately 80% of the predicted ribosomal proteins were identified with high confidence, compared to the 33% of the predicted ribosomal proteins detected by previous two-dimensional gel electrophoresis studies. The results obtained in this study are generally consistent with those obtained from computational genome analysis, two-dimensional gel electrophoresis, and whole-genome transposon mutagenesis studies. At least 15 genes originally annotated as conserved hypothetical were found to encode expressed proteins. Two more proteins, previously annotated as predicted coding regions, were detected with high confidence; these proteins also have close homologs in related bacteria. The direct proteomics approach to studying protein expression in vivo reported here is a powerful method that is applicable to proteome analysis of any (micro)organism.

Aerobiosis↗