Transcription profiling of human lypmphocyte T cells after Azaspiracid exposure
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: Mike Twiner
PROVIDER: E-GEOD-8845 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
Similar Datasets
Project description:Azaspiracid-1 (AZA-1) is a marine phycotoxin that accumulates in shellfish and known to cause severe gastrointestinal intoxications in humans. As the mechanism of action of AZA-1 is currently unknown, human DNA microarrays were used to profile gene expression in human lymphocyte T cells following AZA-1 exposure. Highly significant early (1 hr) genes consisted of a T cell specific transcription factor, membrane proteins, receptors, and inflammatory genes. At 4 hr, responding genes included transcription factors and cell growth genes, in addition to 16 genes involved in fatty acid and cholesterol synthesis. Similarly, at 24 hr, 17 of the top 35 signature genes were involved in fatty acid and cholesterol synthesis. Gene Map Annotator and Pathway Profiler software confirmed cell signaling effects targeted toward lipid biosynthesis pathways. The transcriptional profile induced by AZA-1 shared high similarity to expression profiles of in vitro cholesterol synthesis inhibitor studies and in vitro and in vivo cholesterol synthesis gene knockout studies, suggesting a common transcriptional response and possible mechanism of action. Experiment Overall Design: Time course experiment comparing AZA treatment gene expression to vehicle control. Parallel cultures of cells (n=2) were exposed to AZA or vehicle control for 1, 4, 24hr and harvested for RNA extraction. dye swaps were used for the replicate time points. Experiment Overall Design: Log Ratio data are listed as Log10.
2008-04-08 | E-GEOD-5346 | biostudies-arrayexpress
Project description:The functions of the majority of trypanosomatid-specific proteins are unknown, hindering our understanding of the biology and pathogenesis of Trypanosomatida. While protein-protein interactions are highly informative about protein function, a global map of protein interactions and complexes is still lacking for these important human parasites. Here, benefiting from in-depth biochemical fractionation, we systematically examined the protein complexes of more than 3354 protein groups in procyclic life stage of Trypanosoma brucei, the protozoan parasite responsible for human African trypanosomiasis. Using a rigorous methodology, our analysis led to identification of 128 high-confidence complexes encompassing 716 protein groups, including 635 protein groups that had no available experimental annotation. These complexes correlate well with known pathways as well as for proteins co-expressed across the T. brucei life cycle, and provide potential functions for a large number of previously uncharacterized proteins. We validated the functions of several novel proteins associated with the RNA-editing machinery, identifying candidates potentially involved in the life stage specific post-transcriptional regulation in T. brucei. Our data provide an unprecedented view of the protein complex map of T. brucei, and serve as a reliable resource for further characterization of trypanosomatid proteins.
2016-02-29 | PXD002640 | Pride
Project description:Dissecting the shared etiology of different diseases could benefit from a systematic search for associated molecules and their interactions. We investigated genome-wide disruptions in the co-regulation of genes in two neurodegenerative diseases, Alzheimer's or Huntington's disease (AD or HD), using expression profiles from postmortem prefrontal cortex samples of 624 demented patients and non-demented control individuals with matched genotype and clinical data. A meta-analysis based screen for changes in coordinate expression patterns revealed differentially co-expressed (DC) gene pairs that either gained or lost correlation in disease cases relative to the control group, with the former being dominant for both AD and HD. Integration of disruptions common to AD and HD with large-scale data on protein-protein and protein-DNA interactions yielded a 242-gene sub-network that was enriched for proteins involved in neuronal differentiation and genetic associations to brain structural changes and dementia in subjects aged over 70 years. Replication of the AD DC network in independent human and mouse cohorts lends confidence to the comprehensive view we offer on dysregulated brain molecular pathways in AD and HD. DLPFC (BA9) brain tissues of AD patients, HD patients and non-demented controls samples were obtained from Harvard Brain tissue resource center (HBTRC). The HBTRC samples were primarily of Caucasian ancestry, as only eight non-Caucasian outliers were identified, and therefore excluded for further analysis. Post-mortem interval (PMI) was 17.8+8.3 hours (mean ± standard deviation), sample pH was 6.4±0.3 and RNA integrity number (RIN) was 6.8±0.8 for the average sample in the overall cohort. Tissues were profiled on a custom-made Agilent 44K array (GPL4372). 624 individual DLPFC samples were profiled against a common DLPFC pool constructed from the same set of samples.
2014-07-31 | E-GEOD-33000 | biostudies-arrayexpress
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2015-06-30 | E-GEOD-62958 | biostudies-arrayexpress
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2015-06-30 | E-GEOD-62959 | biostudies-arrayexpress
Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains. Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1). All subjects were diagnosed at intake and each brain underwent extensive LOAD-related pathology examination. Gene expression analyses were adjusted for age and sex, postmortem interval (PMI) in hours, sample pH and RNA integrity number (RIN). In the overall cohort of LOAD and non-demented brains the mean ± SD for sample PMI, pH and RIN were 17.8±8.3, 6.4±0.3 and 6.8±0.8, respectively. 230 samples with all PFC, VC, and CR tissue profiled were included for further multi-tissue analysis.
2013-04-25 | E-GEOD-44768 | biostudies-arrayexpress
Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains. Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1). All subjects were diagnosed at intake and each brain underwent extensive LOAD-related pathology examination. Gene expression analyses were adjusted for age and sex, postmortem interval (PMI) in hours, sample pH and RNA integrity number (RIN). In the overall cohort of LOAD and non-demented brains the mean ± SD for sample PMI, pH and RIN were 17.8±8.3, 6.4±0.3 and 6.8±0.8, respectively. 230 samples with all PFC, VC, and CR tissue profiled were included for further multi-tissue analysis.
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Project description:The genetics of complex disease produce alterations in molecular interactions of cellular pathways which collective effect may become clear through the organized structure of molecular networks. To characterize molecular systems associated with late-onset Alzheimer´s disease (LOAD), we constructed gene regulatory networks in hundreds of autopsied brain tissues from LOAD patients and non-demented subjects. We demonstrate that LOAD reconfigures specific portions of the molecular interaction structure, and via an integrative network-based approach we rank ordered these sub-networks (modules) for relevance to LOAD pathology, highlighting the immune/microglia module as the top ranking. Through a Bayesian inference approach we identified multiple key causal regulators for LOAD brains. Autopsied tissues from dorsolateral prefrontal cortex (PFC), visual cortex (VC) and cerebellum (CR) in brains of LOAD patients, and non-demented healthy controls, collected through the Harvard Brain Tissue Resource Center (HBTRC), were profiled on a custom-made Agilent 44K array (GPL4372_1). All subjects were diagnosed at intake and each brain underwent extensive LOAD-related pathology examination. Gene expression analyses were adjusted for age and sex, postmortem interval (PMI) in hours, sample pH and RNA integrity number (RIN). In the overall cohort of LOAD and non-demented brains the mean ± SD for sample PMI, pH and RIN were 17.8±8.3, 6.4±0.3 and 6.8±0.8, respectively. 230 samples with all PFC, VC, and CR tissue profiled were included for further multi-tissue analysis.
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Project description:This SuperSeries is composed of the SubSeries listed below. Refer to individual Series
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