Marina A. Gritsenko

Temporal Proteome and Lipidome Profiles Reveal Hepatitis C Virus-Associated Reprogramming of Hepatocellular Metabolism and Bioenergetics

Proteomic and lipidomic profiling was performed over a time course of acute hepatitis C virus (HCV) infection in cultured Huh-7.5 cells to gain new insights into the intracellular processes influenced by this virus. Our proteomic data suggest that HCV induces early perturbations in glycolysis, the pentose phosphate pathway, and the citric acid cycle, which favor host biosynthetic activities supporting viral replication and propagation. This is followed by a compensatory shift in metabolism aimed at maintaining energy homeostasis and cell viability during elevated viral replication and increasing cellular stress. Complementary lipidomic analyses identified numerous temporal perturbations in select lipid species (e.g. phospholipids and sphingomyelins) predicted to play important roles in viral replication and downstream assembly and secretion events. The elevation of lipotoxic ceramide species suggests a potential link between HCV-associated biochemical alterations and the direct cytopathic effect observed in this in vitro system. Using innovative computational modeling approaches, we further identified mitochondrial fatty acid oxidation enzymes, which are comparably regulated during in vitro infection and in patients with histological evidence of fibrosis, as possible targets through which HCV regulates temporal alterations in cellular metabolic homeostasis.

Reversed-phase chromatography with multiple fraction concatenation strategy for proteome profiling of human MCF10A cells†

In this study, we evaluated a concatenated low pH (pH 3) and high pH (pH 10) reversed‐phase liquid chromatography strategy as a first dimension for two‐dimensional liquid chromatography tandem mass spectrometry (“shotgun”) proteomic analysis of trypsin‐digested human MCF10A cell sample. Compared with the more traditional strong cation exchange method, the use of concatenated high pH reversed‐phase liquid chromatography as a first‐dimension fractionation strategy resulted in 1.8‐ and 1.6‐fold increases in the number of peptide and protein identifications (with two or more unique peptides), respectively. In addition to broader identifications, advantages of the concatenated high pH fractionation approach include improved protein sequence coverage, simplified sample processing, and reduced sample losses. The results demonstrate that the concatenated high pH reversed‐phased strategy is an attractive alternative to strong cation exchange for two‐dimensional shotgun proteomic analysis.

Evaluation of Multiprotein Immunoaffinity Subtraction for Plasma Proteomics and Candidate Biomarker Discovery Using Mass Spectrometry

Strategies for removal of high abundance proteins have been increasingly utilized in proteomic studies of serum/plasma and other body fluids to enhance the detection of low abundance proteins and achieve broader proteome coverage; however, both the reproducibility and specificity of the high abundance protein depletion process still represent common concerns. Here we report a detailed evaluation of immunoaffinity subtraction performed applying the ProteomeLab IgY-12 system that is commonly used in human serum/plasma proteome characterization in combination with high resolution LC-MS/MS. Plasma samples were repeatedly processed using this approach, and the resulting flow-through fractions and bound fractions were individually analyzed for comparison. The removal of target proteins by the immunoaffinity subtraction system and the overall process was highly reproducible. Non-target proteins, including one spiked protein standard (rabbit glyceraldehyde-3-phosphate dehydrogenase), were also observed to bind to the column at different levels but also in a reproducible manner. The results suggest that multiprotein immunoaffinity subtraction systems can be readily integrated into quantitative strategies to enhance detection of low abundance proteins in biomarker discovery studies.

Integrative Analysis of the Mitochondrial Proteome in Yeast

In this study yeast mitochondria were used as a model system to apply, evaluate, and integrate different genomic approaches to define the proteins of an organelle. Liquid chromatography mass spectrometry applied to purified mitochondria identified 546 proteins. By expression analysis and comparison to other proteome studies, we demonstrate that the proteomic approach identifies primarily highly abundant proteins. By expanding our evaluation to other types of genomic approaches, including systematic deletion phenotype screening, expression profiling, subcellular localization studies, protein interaction analyses, and computational predictions, we show that an integration of approaches moves beyond the limitations of any single approach. We report the success of each approach by benchmarking it against a reference set of known mitochondrial proteins, and predict approximately 700 proteins associated with the mitochondrial organelle from the integration of 22 datasets. We show that a combination of complementary approaches like deletion phenotype screening and mass spectrometry can identify over 75% of the known mitochondrial proteome. These findings have implications for choosing optimal genome-wide approaches for the study of other cellular systems, including organelles and pathways in various species. Furthermore, our systematic identification of genes involved in mitochondrial function and biogenesis in yeast expands the candidate genes available for mapping Mendelian and complex mitochondrial disorders in humans.

Integrated proteogenomic characterization of human high-grade serous ovarian cancer

To provide a detailed analysis of the molecular components and underlying mechanisms associated with ovarian cancer, we performed a comprehensive mass-spectrometry-based proteomic characterization of 174 ovarian tumors previously analyzed by The Cancer Genome Atlas (TCGA), of which 169 were high-grade serous carcinomas (HGSCs). Integrating our proteomic measurements with the genomic data yielded a number of insights into disease, such as how different copy-number alternations influence the proteome, the proteins associated with chromosomal instability, the sets of signaling pathways that diverse genome rearrangements converge on, and the ones most associated with short overall survival. Specific protein acetylations associated with homologous recombination deficiency suggest a potential means for stratifying patients for therapy. In addition to providing a valuable resource, these findings provide a view of how the somatic genome drives the cancer proteome and associations between protein and post-translational modification levels and clinical outcomes in HGSC. VIDEO ABSTRACT.

Ischemia in tumors induces early and sustained phosphorylation changes in stress kinase pathways but does not affect global protein levels

Protein abundance and phosphorylation convey important information about pathway activity and molecular pathophysiology in diseases including cancer, providing biological insight, informing drug and diagnostic development, and guiding therapeutic intervention. Analyzed tissues are usually collected without tight regulation or documentation of ischemic time. To evaluate the impact of ischemia, we collected human ovarian tumor and breast cancer xenograft tissue without vascular interruption and performed quantitative proteomics and phosphoproteomics after defined ischemic intervals. Although the global expressed proteome and most of the >25,000 quantified phosphosites were unchanged after 60 min, rapid phosphorylation changes were observed in up to 24% of the phosphoproteome, representing activation of critical cancer pathways related to stress response, transcriptional regulation, and cell death. Both pan-tumor and tissue-specific changes were observed. The demonstrated impact of pre-analytical tissue ischemia on tumor biology mandates caution in interpreting stress-pathway activation in such samples and motivates reexamination of collection protocols for phosphoprotein analysis.

High Dynamic Range Characterization of the Trauma Patient Plasma Proteome

Although human plasma represents an attractive sample for disease biomarker discovery, the extreme complexity and large dynamic range in protein concentrations present significant challenges for characterization, candidate biomarker discovery, and validation. Herein we describe a strategy that combines immunoaffinity subtraction and subsequent chemical fractionation based on cysteinyl peptide and N-glycopeptide captures with two-dimensional LC-MS/MS to increase the dynamic range of analysis for plasma. Application of this “divide-and-conquer” strategy to trauma patient plasma significantly improved the overall dynamic range of detection and resulted in confident identification of 22,267 unique peptides from four different peptide populations (cysteinyl peptides, non-cysteinyl peptides, N-glycopeptides, and non-glycopeptides) that covered 3654 different proteins with 1494 proteins identified by multiple peptides. Numerous low abundance proteins were identified, exemplified by 78 “classic” cytokines and cytokine receptors and by 136 human cell differentiation molecules. Additionally a total of 2910 different N-glycopeptides that correspond to 662 N-glycoproteins and 1553 N-glycosylation sites were identified. A panel of the proteins identified in this study is known to be involved in inflammation and immune responses. This study established an extensive reference protein database for trauma patients that provides a foundation for future high throughput quantitative plasma proteomic studies designed to elucidate the mechanisms that underlie systemic inflammatory responses.

Integrated Molecular Signature of Disease: Analysis of Influenza Virus-Infected Macaques through Functional Genomics and Proteomics

ABSTRACT Recent outbreaks of avian influenza in humans have stressed the need for an improved nonhuman primate model of influenza pathogenesis. In order to further develop a macaque model, we expanded our previous in vivo genomics experiments with influenza virus-infected macaques by focusing on the innate immune response at day 2 postinoculation and on gene expression in affected lung tissue with viral genetic material present. Finally, we sought to identify signature genes for early infection in whole blood. For these purposes, we infected six pigtailed macaques (Macaca nemestrina) with reconstructed influenza A/Texas/36/91 virus and three control animals with a sham inoculate. We sacrificed one control and two experimental animals at days 2, 4, and 7 postinfection. Lung tissue was harvested for pathology, gene expression profiling, and proteomics. Blood was collected for genomics every other day from each animal until the experimental endpoint. Gross and microscopic pathology, immunohistochemistry, viral gene expression by arrays, and/or quantitative real-time reverse transcription-PCR confirmed successful yet mild infections in all experimental animals. Genomic experiments were performed using macaque-specific oligonucleotide arrays, and high-throughput proteomics revealed the host response to infection at the mRNA and protein levels. Our data showed dramatic differences in gene expression within regions in influenza virus-induced lesions based on the presence or absence of viral mRNA. We also identified genes tightly coregulated in peripheral white blood cells and in lung tissue at day 2 postinoculation. This latter finding opens the possibility of using gene expression arrays on whole blood to detect infection after exposure but prior to onset of symptoms or shedding.

Proteomic Profiling of Human Liver Biopsies: Hepatitis C Virus-Induced Fibrosis and Mitochondrial Dysfunction

Liver biopsies from hepatitis C virus (HCV)‐infected patients offer the unique opportunity to study human liver biology and disease in vivo. However, the low protein yields associated with these small samples present a significant challenge for proteomic analysis. In this study we describe the application of an ultrasensitive proteomics platform for performing robust quantitative proteomic studies on microgram amounts of HCV‐infected human liver tissue from 15 patients at different stages of fibrosis. A high‐quality liver protein database containing 5,920 unique protein identifications supported high throughput quantitative studies using 16O/18O stable isotope labeling in combination with the accurate mass and time (AMT) tag approach. A total of 1,641 liver biopsy proteins were quantified, and analysis of variance (ANOVA) identified 210 proteins exhibiting statistically significant differences associated with fibrosis stage. Hierarchical clustering showed that biopsies representative of later fibrosis stages (for example, Batts‐Ludwig stages 3–4) exhibited a distinct protein expression profile, indicating an apparent down‐regulation of many proteins when compared with samples from earlier fibrosis stages (for example, Batts‐Ludwig stages 0–2). Functional analysis of these signature proteins suggests that impairment of key mitochondrial processes including fatty acid oxidation and oxidative phosphorylation, and response to oxidative stress and reactive oxygen species occurs during advanced stage 3 to 4 fibrosis. Conclusion: The results reported here represent a significant advancement in clinical proteomics providing to our knowledge, the first demonstration of global proteomic alterations accompanying liver disease progression in patients chronically infected with HCV. Our findings contribute to a generally emerging theme associating oxidative stress and hepatic mitochondrial dysfunction with HCV pathogenesis. (HEPATOLOGY 2007.)

Proteomic Profiling of Exosomes Leads to the Identification of Novel Biomarkers for Prostate Cancer

Background Current markers for prostate cancer, such as PSA lack specificity. Therefore, novel biomarkers are needed. Unfortunately, the complexity of body fluids often hampers biomarker discovery. An attractive alternative approach is the isolation of small vesicles, i.e. exosomes, ∼100 nm, which contain proteins that are specific to the tissue from which they are derived and therefore can be considered as treasure chests for disease-specific biomarker discovery. Materials and Methods Exosomes were isolated from 2 immortalized primary prostate epithelial cells (PNT2C2 and RWPE-1) and 2 PCa cell lines (PC346C and VCaP) by ultracentrifugation. After tryptic digestion, proteomic analyses utilized a nanoLC coupled with an LTQ-Orbitrap operated in tandem MS (MS/MS) mode. Accurate Mass and Time (AMT) tag approach was employed for peptide identification and quantitation. Candidate biomarkers were validated by Western blotting and Immunohistochemistry. Results Proteomic characterization resulted in the identification of 248, 233, 169, and 216 proteins by at least 2 peptides in exosomes from PNT2C2, RWPE-1, PC346C, and VCaP, respectively. Statistical analyses revealed 52 proteins differently abundant between PCa and control cells, 9 of which were more abundant in PCa. Validation by Western blotting confirmed a higher abundance of FASN, XPO1 and PDCD6IP (ALIX) in PCa exosomes. Conclusions Identification of exosomal proteins using high performance LC-FTMS resulted in the discovery of PDCD6IP, FASN, XPO1 and ENO1 as new candidate biomarkers for prostate cancer.