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Proteome analysis of human lymphotropic tumor viruses

ABSTRACT: Detection/identification of virola proteins from tumor cells

OTHER RELATED OMICS DATASETS IN: PRJNA151379GSE34538

INSTRUMENT(S): LTQ XL ETD, LTQ

ORGANISM(S): Homo Sapiens (ncbitaxon:9606)

SUBMITTER: Richard D. Smith

PROVIDER: MSV000079036 | MassIVE | Thu Feb 12 19:26:00 GMT 2015

SECONDARY ACCESSION(S): PXD001811

REPOSITORIES: MassIVE

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Coupled transcriptome and proteome analysis of human lymphotropic tumor viruses: insights on the detection and discovery of viral genes.

Dresang Lindsay R LR Teuton Jeremy R JR Feng Huichen H Jacobs Jon M JM Camp David G DG Purvine Samuel O SO Gritsenko Marina A MA Li Zhihua Z Smith Richard D RD Sugden Bill B Moore Patrick S PS Chang Yuan Y

BMC genomics 20111220

<h4>Background</h4>Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spec ...[more]

PMID: 22185355

Similar Datasets

Coupled Transcriptome and Proteome Analysis of Human Lymphotropic Tumor Viruses: Insights on the Detection and Discovery of Viral Genes

Project description:Kaposi’s sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt’s lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions. The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. The expression of several previously uncharacterized latent genes were validated at both transcript and protein levels. This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.

2011-12-30 | GSE34538 | GEO

Coupled Transcriptome and Proteome Analysis of Human Lymphotropic Tumor Viruses: Insights on the Detection and Discovery of Viral Genes

Project description:Coupled Transcriptome and Proteome Analysis of Human Lymphotropic Tumor Viruses: Insights on the Detection and Discovery of Viral Genes

| PRJNA151379 | ENA

Coupled transcriptome and proteome analysis of human lymphotropic tumor viruses: insights on the detection and discovery of viral genes.

Project description:BACKGROUND:Kaposi's sarcoma-associated herpesvirus (KSHV) and Epstein-Barr virus (EBV) are related human tumor viruses that cause primary effusion lymphomas (PEL) and Burkitt's lymphomas (BL), respectively. Viral genes expressed in naturally-infected cancer cells contribute to disease pathogenesis; knowing which viral genes are expressed is critical in understanding how these viruses cause cancer. To evaluate the expression of viral genes, we used high-resolution separation and mass spectrometry coupled with custom tiling arrays to align the viral proteomes and transcriptomes of three PEL and two BL cell lines under latent and lytic culture conditions. RESULTS:The majority of viral genes were efficiently detected at the transcript and/or protein level on manipulating the viral life cycle. Overall the correlation of expressed viral proteins and transcripts was highly complementary in both validating and providing orthogonal data with latent/lytic viral gene expression. Our approach also identified novel viral genes in both KSHV and EBV, and extends viral genome annotation. Several previously uncharacterized genes were validated at both transcript and protein levels. CONCLUSIONS:This systems biology approach coupling proteome and transcriptome measurements provides a comprehensive view of viral gene expression that could not have been attained using each methodology independently. Detection of viral proteins in combination with viral transcripts is a potentially powerful method for establishing virus-disease relationships.

| S-EPMC3282826 | biostudies-literature

MaizePath: A CHG microarray for detection and identification of bacteria and viruses pathogenic on maize

Project description:A CHG microarray for detection and identification of bacteria and viruses pathogenic on maize

2016-07-01 | GSE69895 | GEO

Viruses

Project description:Detection of Human Viruses from wastewater sewage extracts

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Detection of Human Viruses from wastewater sewage extracts

Project description:Sewage samples were collected and concentrated for Human and animal viruses. Viruses were cultured on Buffalo Green Monkey Cells (BGMK) and their genomic DNA/RNA were extracted and labeled with Cy3 and Cy5 respectively. Labeled DNA/RNA were hybridized unto the array and signals generated were analyzed to indicate the presence of target viruses. Keywords: Detection of pathogens within environmental sample (Viruses)

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19 K14Cre; p53F/F mouse mammary tumor analysis

Project description:Tumor formation is in part driven by copy number alterations (CNAs), which can be measured using array Comparative Genomic Hybridization (aCGH). Identifying regions of DNA that are gained or lost in a significant fraction of tumor samples can facilitate identification of genes possibly related to the development of cancer. Until now, no method has been described that provides a statistical framework in which these regions can be identified without prior discretization of the aCGH data. Kernel Convolution - a Statistical Method for Aberrant Region deTection (KC-SMART) is a new approach which inputs continuous aCGH data to identify regions that are significantly aberrant across an entire tumor set. KC-SMART uses kernel convolution to generate a Kernel Smoothed Estimate (KSE) of CNAs across the genome, aggregated over all tumors. By varying the width of the kernel function, a scale space is created which enables the detection of aberrations of varying size. In an analysis of 89 human sporadic breast tumors KC-SMART performs better than a previously published method, STAC. Our method not only identified aberrations that are strongly associated with clinical parameters, but also showed stronger enrichment for known cancer genes in the detected regions. Furthermore, KC-SMART identifies 18 aberrant regions in mammary tumors from p53 conditional knock-out mice. These regions, combined with gene expression micro-array data, point to known cancer genes and novel candidate cancer genes. 19 mouse mammary tumors samples were measured against spleen-derived DNA from the same animal on our in-house aCGH platform. Goal of the study was to assess recurrent genomic aberrations in these tumors. This is a tissue specific knockout of p53. Experiments were perfomed in dye-swap

2010-05-26 | E-GEOD-7794 | biostudies-arrayexpress

Viruses

Project description:Viral Detection Microarray Analysis of Unknown Tropical Febrile Illness Cases

| PRJNA139553 | ENA

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MaizePath: A CHG microarray for detection and identification of bacteria and viruses pathogenic on maize

Project description:A CHG microarray for detection and identification of bacteria and viruses pathogenic on maize Two-condition experiment, Agilent SurePrint G3 Cust. CGH Microarray 4x180K

2016-07-01 | E-GEOD-69895 | biostudies-arrayexpress

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