Dataset Information

Evaluating the effect of TLR4-overexpressing on the transcriptome profile in ovine peripheral blood mononuclear cells.

ABSTRACT: Background:Toll-like receptor 4 (TLR4) plays an important role in the elimination of Gram-negative bacteria infections and the initiation of antiinflammatory response. Using the technology of pronuclear microinjection, genetically modified (GM) sheep with TLR4 overexpression were generated. Previous studies have shown that these GM sheep exhibited a higher inflammatory response to Gram-negative bacteria infection than wild type (WT) sheep. In order to evaluate the gene expression of GM sheep and study the co-expressed and downstream genes for TLR4, peripheral blood mononuclear cells (PBMC) from TLR4-overexpressing (Tg) and wild type (WT) sheep were selected to discover the transcriptomic differences using RNA-Seq. Result:An average of 18,754 and 19,530 known genes were identified in the Tg and WT libraries, respectively. A total of 338 known genes and 85 novel transcripts were found to be differentially expressed in the two libraries (p?

SUBMITTER: Guo X

PROVIDER: S-EPMC7392728 | biostudies-literature | 2020 Dec

REPOSITORIES: biostudies-literature

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Evaluating the effect of <i>TLR4</i>-overexpressing on the transcriptome profile in ovine peripheral blood mononuclear cells.

Guo Xiaofei X Zhang Jinlong J Li Yao Y Yang Jing J Li Yihai Y Dong Chunxiao C Liu Guoshi G Lian Zhengxing Z Zhang Xiaosheng X

Journal of biological research (Thessalonike, Greece) 20200729

<h4>Background</h4>Toll-like receptor 4 (TLR4) plays an important role in the elimination of Gram-negative bacteria infections and the initiation of antiinflammatory response. Using the technology of pronuclear microinjection, genetically modified (GM) sheep with <i>TLR4</i> overexpression were generated. Previous studies have shown that these GM sheep exhibited a higher inflammatory response to Gram-negative bacteria infection than wild type (WT) sheep. In order to evaluate the gene expression ...[more]

PMID: 32760682

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Project description:Background: Sepsis, as a clinical emergency, usually causes multiorgan dysfunction and can lead to high mortality. Establishment of specific and sensitive biomarkers for early diagnosis is critical to identify patients who would benefit from targeted therapy. In this study, we investigated this syndrome by analyzing the transcriptome of peripheral blood mononuclear cells (PBMCs) from patients with sepsis and identified sepsis-specific biomarkers. Methods: In this study, a total of 87 patients with sepsis and 40 healthy controls from a prospective multicenter cohort were enrolled. Samples from 44 subjects (24 patients with sepsis and 20 healthy controls) were sequenced and the remaining patients were included in the validation group. Using high-throughput sequencing, a gene expression profile of PBMCs from patients with sepsis was generated to elucidate the pathophysiology of sepsis and identify sepsis-specific biomarkers. Results: Principal component analysis (PCA) and unsupervised hierarchical cluster analysis showed that patients with sepsis separated from healthy controls. A total of 1639 differentially expressed genes (DEGs) were identified (|log2 fold change|>2, adjusted P value <0.05) between these two groups, with 1278 (78.0%) upregulated and 361 (22.0%) downregulated in patients with sepsis. Gene Ontology (GO) analysis of the upregulated DEGs identified 194 GO terms that were clustered into 27 groups, and analysis of the downregulated DEGs identified 20 GO terms that were clustered into 4 groups. Four unique genes were identified that could be predictive of patients with sepsis. External validation of the four genes using quantitative real-time polymerase chain reaction (qRT-PCR) was consistent with the results of mRNA sequencing, revealing their potential in sepsis diagnosis. Conclusions: The transcriptome characteristics of PBMCs, which were significantly altered in sepsis patients, provide new insights into sepsis pathogenesis. The four identified gene expression changes differentiated patients with sepsis from healthy subjects, which could serve as a convenient tool contributing to sepsis diagnosis.

Project description:Trypanosoma cruzi (Tc) infection causes chagasic cardiomyopathy; however, why 30-40% of the patients develop clinical disease is not known. To discover the pathomechanisms in disease progression, we obtained the proteome signature of peripheral blood mononuclear cells (PBMCs) of normal healthy controls (N/H, n = 30) and subjects that were seropositive for Tc-specific antibodies, but were clinically asymptomatic (C/A, n = 25) or clinically symptomatic (C/S, n = 28) with cardiac involvement and left ventricular dysfunction. Protein samples were labeled with BODIPY FL-maleimide (dynamic range: > 4 orders of magnitude, detection limit: 5 f-mol) and resolved by two-dimensional gel electrophoresis (2D-GE). After normalizing the gel images, protein spots that exhibited differential abundance in any of the two groups were analyzed by mass spectrometry, and searched against UniProt human database for protein identification. We found 213 and 199 protein spots (fold change: |≥ 1.5|, p< 0.05) were differentially abundant in C/A and C/S individuals, respectively, with respect to N/H controls. Ingenuity Pathway Analysis (IPA) of PBMCs proteome dataset identified an increase in disorganization of cytoskeletal assembly and recruitment/activation and migration of immune cells in all chagasic subjects, though the invasion capacity of cells was decreased in C/S individuals. IPA predicted with high probability a decline in cell survival and free radical scavenging capacity in C/S (but not C/A) subjects. The MYC/SP1 transcription factors that regulate hypoxia and oxidative/inflammatory stress were predicted to be key targets in the context of control of Chagas disease severity. Further, MARS-modeling identified a panel of proteins that had >93% prediction success in classifying infected individuals with no disease and those with cardiac involvement and LV dysfunction. In conclusion, we have identified molecular pathways and a panel of proteins that could aid in detecting seropositive individuals at risk of developing cardiomyopathy.

Dataset Information

Evaluating the effect of TLR4-overexpressing on the transcriptome profile in ovine peripheral blood mononuclear cells.

Publications

Evaluating the effect of <i>TLR4</i>-overexpressing on the transcriptome profile in ovine peripheral blood mononuclear cells.

Similar Datasets

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