Evaluation of subsequent passaging on whole genome expression
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
SUBMITTER: SeyedAhmad Mousavi
PROVIDER: E-GEOD-43447 | biostudies-arrayexpress |
REPOSITORIES: biostudies-arrayexpress
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Project description:Heart diseases are as most leading causes of morbidity and mortality in the world. One of the promising approaches to cure these diseases is cell therapy using endogenous cardiac precursor cells resident in heart tissues. These cells are isolated from heart biopsies, cultured and passaged to reach to the desirable cell count necessary for transplantation. The process of cell propagation and subsequent passages may cause gene expression alteration unsuitable and dangerous for cell therapy; so in our study, we analyzed whole genome expression using microarray technology to compare expressed transcripts in 4 passages 6, 9, 12 and 15.
2013-01-15 | GSE43447 | GEO
Project description:Understanding the pathogenic mechanisms and host responses to Johne's disease, caused by Mycboacterium avium subspecies paratuberculosis (MAP), is complicated by a number of challenges of the disease progression and lack of ex vivo models to study the disease. We describe novel cell culture passage model which mimics the course of infection in vivo. Using this model we determined that cell culture passaged MAP develops an inflammatory phenotype initiating higher levels of pro-inflammatory cytokines and chemokines compared to levels initiated by non-passaged MAP. To verify that the MAP phenotypes were changing, we conducted transcriptome analysis of each population during the passage model and identified a change in gene expression, specifically and upregulation of genes involved in the biosynthesis of lipid components within the cell. Lipidomic analysis showed dramatically different lipid profiles between the 2 populations. These transcriptome changes were validated by the identification of high levels of upregulated transcripts from MAP-infected cattle ileal tissue. In total, this study described a novel model used to show that MAP changes phenotype during intracellular passage, thus changing its lipid profile and triggering an inflammatory response in the host leading to the severe clinical phage of Johne's disease. In total 6 slides were analyzed. Of the 2 phenotypes under investigation, the P0 samples (non-inflammatory) were analyzed in triplate and the P2 samples (inflammatory) were analyzed in triplicate. Each slide fluorescence intensity was measured at PMT400, 600 and 750. Each oligo on each slide was spotted in triplicate and each slide had its own internal controls.
2014-11-01 | E-GEOD-62566 | biostudies-arrayexpress
Project description:MicroRNAs (miRNAs) are small non-coding RNA molecules which function as negative gene regulators. The tissue expression profile of miRNAs shows great promise as a novel biomarker for diagnosis of cancer and other diseases. In addition, some recent reports have demonstrated that are present in human serum and plasma which could make them an ideal non-invasive biomarker for diagnosis of cancer. The aim of this study is to analyze the value/efficacy of the expression profile of plasma miRNAs in differentiating between patients with advanced adenomas and CRC and healthy individuals. The microRNA profiling study comprises serum plasmas from 20 Control, 21 colorectal cancer,20 advanced adenomas.The study also include some samples from patients after treatment.
2013-01-11 | E-GEOD-25609 | biostudies-arrayexpress
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Project description:Background Bone marrow stromal cells (BMSCs) are a heterogeneous population that participates in wound healing, immune modulation and tissue regeneration. Next generation sequencing was used to analyze transcripts from single BMSCs in order to better characterize BMSC subpopulations. Methods Cryopreserved passage 2 BMSCs from one healthy subject were cultured through passage 10. The transcriptomes of bulk BMSCs from designated passages were analyzed with microarrays and RNA sequencing (RNA-Seq). For some passages, single BMSCs were separated using microfluidics and their transcriptomes were analyzed by RNA-Seq. Results Transcriptome analysis microarray and RNA-Seq of unseparated BMSCs from passages 2, 4, 6, 8, 9 and 10 yielded similar results; both data sets grouped passages 4 and 6 and passages 9 and 10 together and genes differentially expressed among these early and late passage BMSCs were similar. 3D Diffusion map visualization of single BMSCs from passages 3, 4, 6, 8 and 9 clustered passage 3 and 9 into two distinct groups, but there was considerable overlap for passage 4, 6 and 8 cells. Markers for early passage, FGFR2, and late passage BMSCs, PLAT, were able to identify three subpopulations within passage 3 BMSCs; one that expressed high levels of FGFR2 and low levels of PLAT; one that expressed low levels of FGFR2 and high levels of PLAT and one that expressed intermediate levels of FGFR2 and low levels of PLAT. Conclusions Single BMSCs can be separated by microfluidics and their transcriptome analyzed by next generation sequencing. Single cell analysis of early passage BMSCs identified a subpopulation of cells expressing high levels of FGFR2 that might include skeletal stem cells.
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Project description:Background Bone marrow stromal cells (BMSCs) are a heterogeneous population that participates in wound healing, immune modulation and tissue regeneration. Next generation sequencing was used to analyze transcripts from single BMSCs in order to better characterize BMSC subpopulations. Methods Cryopreserved passage 2 BMSCs from one healthy subject were cultured through passage 10. The transcriptomes of bulk BMSCs from designated passages were analyzed with microarrays and RNA sequencing (RNA-Seq). For some passages, single BMSCs were separated using microfluidics and their transcriptomes were analyzed by RNA-Seq. Results Transcriptome analysis microarray and RNA-Seq of unseparated BMSCs from passages 2, 4, 6, 8, 9 and 10 yielded similar results; both data sets grouped passages 4 and 6 and passages 9 and 10 together and genes differentially expressed among these early and late passage BMSCs were similar. 3D Diffusion map visualization of single BMSCs from passages 3, 4, 6, 8 and 9 clustered passage 3 and 9 into two distinct groups, but there was considerable overlap for passage 4, 6 and 8 cells. Markers for early passage, FGFR2, and late passage BMSCs, PLAT, were able to identify three subpopulations within passage 3 BMSCs; one that expressed high levels of FGFR2 and low levels of PLAT; one that expressed low levels of FGFR2 and high levels of PLAT and one that expressed intermediate levels of FGFR2 and low levels of PLAT. Conclusions Single BMSCs can be separated by microfluidics and their transcriptome analyzed by next generation sequencing. Single cell analysis of early passage BMSCs identified a subpopulation of cells expressing high levels of FGFR2 that might include skeletal stem cells.
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