Influence of isolation procedure and storage condition on the ex vivo gene expression pattern in peripheral human effector/memory T helper lymphocytes
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ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE54247 | GEO | 2014/03/24
SECONDARY ACCESSION(S): PRJNA236031
REPOSITORIES: GEO
Similar Datasets
Project description:Gene expression profiling of cells isolated ex vivo is a unique tool to assess gene expression in vivo. Exemplified for CD4+CD45RO+ effector/memory T helper (T E/M) lymphocytes of human peripheral blood, we have analyzed different isolation procedures and storage conditions for the introduction of bias. Cells from clinical samples can be sorted to high purity by a flow cytometric sorter and assessed for their gene expression pattern but storage/shipping conditions and often necessary pre-enrichment due to low initial population frequencies bears the danger of introducing artificial changes. To test for changes introduced by different procedures, cells were enriched either by magnetic cell sorting (MACS) with Whole-Blood CD4 beads, density gradient centrifugation, alone or in combination with CD3 MACS, or by lysis of erythrocytes followed by MACS depletion of CD15+ cells prior to fluorescence-activated cell sorting (FACS) as CD3+CD4+CD45RO+ cells. A total of 7 different protocols were compared among each other and to T cells stimulated for 3 hours after isolation with Phorbol-12-myristate-13-acetate and Ionomycin (PMA/Iono). Preparation-induced de novo transcription was blocked in one of the protocols by addition of 2 M-BM-5g/ml Actinomycin D (ActD). To test for changes introduced by delays in sample preparation blood samples were drawn and either processed directly or kept at 4 M-BM-0C or room temperature (RT) for 2 or 6 hours before T E/M cells were isolated. Gene expression was compared among the various cell preparations and to T E/M cells isolated from 1 day old buffy coat fractions stored at RT. Sorted cells were lysed in TRIzol (Invitrogen) and frozen at -80M-BM-0C until used for RNA extraction. Total RNA was extracted using the miRNeasy kit (Qiagen). The integrity and amount of isolated RNA was assessed for each sample using an Agilent 2100 Bioanalyzer (Agilent, Waldbronn, Germany) and a NanoDrop ND-1000 spectrophotometer (NanoDrop Technologies, Wilmington, DE). Double-stranded complementary RNA was synthesized from 1 M-BM-5g total RNA using Message AmpII Biotin (Ambion, USA). Fifteen micrograms of fragmented cRNA of each sample were hybridized to 26 HG-U133A plus 2.0 GeneChips (Affymetrix). Hybridization was performed in a Hybridization Oven 640, and chips were washed and stained in the Fluidics Station 400 (both Affymetrix). Finally, the arrays were scanned with a GeneChip Scanner 3000 using the GCOS software, version 1.4, both Affymetrix. All relevant GCOS data of quality checked microarrays were analyzed with High Performance Chip Data Analysis (HPCDA, unpublished), using the BioRetis database (www.bioretis-analysis.de), as described and validated previously.
2014-03-24 | E-GEOD-54247 | biostudies-arrayexpress
Project description:The aim was to assess miRNA expression in 3 human ex-vivo CD8+ T cell subsets which span from antigen inexperienced cells (Naïve) to early memory cells (central memory, Tcm) and later stage memory cells (effector memory, Tem) CD8+ T cells were sorted on a FACS Aria II machine. N = naïve = CD8+, CCR7+, CD45RA+, CD45RO-, Tcm = central memory = CD8+, CCR7+, CD45RA-, CD45RO-,Tem= effector memory = CD8+, CCR7-, CD45RA-, CD45RO+
2014-10-24 | GSE54867 | GEO
Project description:The aim was to assess miRNA expression in 3 human ex-vivo CD8+ T cell subsets which span from antigen inexperienced cells (NaM-CM-/ve) to early memory cells (central memory, Tcm) and later stage memory cells (effector memory, Tem) CD8+ T cells were sorted on a FACS Aria II machine. N = naM-CM-/ve = CD8+, CCR7+, CD45RA+, CD45RO-, Tcm = central memory = CD8+, CCR7+, CD45RA-, CD45RO-,Tem= effector memory = CD8+, CCR7-, CD45RA-, CD45RO+ PBMC were isolated from 3 healthy human donors and sorted by FACS into 3 CD8+ T cell subsets. Total RNA was purified using the miRVANA kit (Ambion)
2014-10-24 | E-GEOD-54867 | biostudies-arrayexpress
Project description:Genetically engineered T lymphocytes are a promising option for cancer therapy. Prior to adoptive transfer they have to be expanded in vitro to reach therapeutically sufficient numbers. So far, no universal method exists for selective in vitro expansion of engineered T lymphocytes. In order to overcome this problem and for proof of concept we incorporated a novel unique peptide sequence of ten amino acids as epitope (E-Tag) into the binding domains of two novel chimeric antigen receptors (ECARs) directed against either prostate stem cell antigen (PSCA) for the treatment of prostate cancer (PCa) or CD33 for the treatment of acute myeloide leukemia (AML). The epitope tag then was utilized for expanding ECAR engrafted T cells by triggering the modified T cells via a monoclonal antibody directed against the E-Tag (Emab). Moreover, the E-Tag served as an efficient selection epitope for immunomagnetic isolation of modified T cells to high purity. ECAR engrafted T cells were fully functional and mediated profound anti-tumor effects in the respective models of PCa or AML both in vitro and in vivo. The method can be integrated straightforward into clinical protocols to improve therapeutic efficiency of tumor treatment with CAR modified T lymphocytes.
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Project description:Mature human red blood cells (RBCs) are terminally differentiated anuclear cells. While initially thought to lack any nucleic acids, human RBCs are found to contain abundant and diverse species of RNA transcripts with functional relevance. Given the absence of novel transcription, RBCs may provide an interesting cellular context to study RNA metabolism over time. One clinically relevant context is the ex vivo storage of RBCs in blood banks for use in blood transfusion. Some studies have indicated that the transfusion of “old” or aged stored RBCs may be associated with adverse outcomes due to various storage changes termed “storage lesions”. However, other studies do not support these effects, and much remains unknown about the relevant changes associated with RBC storage. Here, we employed the NanoString nCounter assay for global miRNA profiling to comprehensively define the miRNA turnover during ex vivo RBC storage. This profiling demonstrates that the abundance of most RBC miRNAs did not change significantly during the 42 days of refrigerated storage, indicating extremely long decay half-lives. Unexpectedly, miR-720, a cleavage product of tRNAThr, increased dramatically in the first two weeks and persisted during storage. Furthermore, we present evidence for a role of angiogenin in tRNA cleavage to generate miR-720 during RBC storage. The dramatic increase in miR-720 may serve as a new characteristic for storage lesion and may be used to monitor transfused RBCs in clinical patients and athletes performing blood doping.
2020-05-26 | GSE114990 | GEO
Project description:microRNA profiling of RBC transcriptome during ex vivo storage
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Project description:Co-expression network analysis provides useful information for studying gene regulation in biological processes. Examining condition-specific patterns of co-expression can provide insights into the underlying cellular processes activated in a particular condition. One challenge in this type of analysis is that the sample sizes in each condition are usually small, making the statistical inference of co-expression patterns highly underpowered. A joint network construction that borrows information from related structures across conditions has the potential to improve the power of the analysis. One possible approach to constructing the co-expression network is to use the Gaussian graphical model. Though several methods are available for joint estimation of multiple graphical models, they do not fully account for the heterogeneity between samples and between co-expression patterns introduced by condition specificity. Here we develop the condition-adaptive fused graphical lasso (CFGL), a data-driven approach to incorporate condition specificity in the estimation of co-expression networks. We show that this method improves the accuracy with which networks are learned. The application of this method on a rat multi-tissue dataset and The Cancer Genome Atlas (TCGA) breast cancer dataset provides interesting biological insights. In both analyses, we identify numerous modules enriched for Gene Ontology functions and observe that the modules that are upregulated in a particular condition are often involved in condition-specific activities. Interestingly, we observe that the genes strongly associated with survival time in the TCGA dataset are less likely to be network hubs, suggesting that genes associated with cancer progression are likely to govern specific functions or execute final biological functions in pathways, rather than regulating a large number of biological processes. Additionally, we observed that the tumor-specific hub genes tend to have few shared edges with normal tissue, revealing tumor-specific regulatory mechanism.
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Project description:Previous studies indicate that lying consumes cognitive resources, especially working memory (WM) resources. Considering the dual functions that WM might play in lying: holding the truth-related information and turning the truth into lies, the present study examined the relationship between the information storage and processing in the lie construction. To achieve that goal, a deception task based on the old/new recognition paradigm was designed, which could manipulate two levels of WM load (low-load task using 4 items and high-load task using 6 items) during the deception process. The analyses based on the amplitude of the contralateral delay activity (CDA), a proved index of the number of representations being held in WM, showed that the CDA amplitude was lower in the deception process than that in the truth telling process under the high-load condition. In contrast, under the low-load condition, no CDA difference was found between the deception and truth telling processes. Therefore, we deduced that the lie construction and information storage compete for WM resources; when the available WM resources cannot meet this cognitive demand, the WM resources occupied by the information storage would be consumed by the lie construction.
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