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SRP067960
Homo sapiens
16 Downloadable Samples
IlluminaHiSeq1500
Description
RNA sequencing data of macrophages after differentiation in the presence of TPC1 thyroid cancer cell line Overall design: Co-incubation in trans-well system between TPC1 cell lines and human primary macrophages
Publication Title
Transcriptional and metabolic reprogramming induce an inflammatory phenotype in non-medullary thyroid carcinoma-induced macrophages.
Sample Metadata Fields
No sample metadata fields
View Samples- Mus musculus
- 8 Downloadable Samples
Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Recent studies have identified intracellular metabolism as a fundamental determinant of macrophage function. In obesity, proinflammatory macrophages accumulate in adipose tissue and trigger chronic low-grade inflammation, that promotes the development of systemic insulin resistance, yet changes in their intracellular energy metabolism are currently unknown. We therefore set out to study metabolic signatures of adipose tissue macrophages (ATMs) in lean and obese conditions. F4/80-positive ATMs were isolated from obese vs lean mice. High-fat feeding of wild-type mice and myeloid-specific Hif1-/- mice was used to examine the role of hypoxia-inducible factor-1 (HIF-1) in ATMs part of obese adipose tissue. In vitro, bone marrow-derived macrophages were co-cultured with adipose tissue explants to examine adipose tissue-induced changes in macrophage phenotypes. Transcriptome analysis, real-time flux measurements, ELISA and several other approaches were used to determine the metabolic signatures and inflammatory status of macrophages. In addition, various metabolic routes were inhibited to determine their relevance for cytokine production. Transcriptome analysis and extracellular flux measurements of mouse ATMs revealed unique metabolic rewiring in obesity characterised by both increased glycolysis and oxidative phosphorylation. Similar metabolic activation of CD14+ cells in obese individuals was associated with diabetes outcome. These changes were not observed in peritoneal macrophages from obese vs lean mice and did not resemble metabolic rewiring in M1-primed macrophages. Instead, metabolic activation of macrophages was dose-dependently induced by a set of adipose tissue-derived factors that could not be reduced to leptin or lactate. Using metabolic inhibitors, we identified various metabolic routes, including fatty acid oxidation, glycolysis and glutaminolysis, that contributed to cytokine release by ATMs in lean adipose tissue. Glycolysis appeared to be the main contributor to the proinflammatory trait of macrophages in obese adipose tissue. HIF-1, a key regulator of glycolysis, nonetheless appeared to play no critical role in proinflammatory activation of ATMs during early stages of obesity. Our results reveal unique metabolic activation of ATMs in obesity that promotes inflammatory cytokine release. Further understanding of metabolic programming in ATMs will most likely lead to novel therapeutic targets to curtail inflammatory responses in obesity.
Publication Title
Unique metabolic activation of adipose tissue macrophages in obesity promotes inflammatory responses.
Sample Metadata Fields
Sex, Specimen part
View Samples- Homo sapiens
- 16 Downloadable Samples
- Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)
Description
During systemic inflammation, different neutrophil subsets are mobilized to the blood circulation. These neutrophil subsets can be distinguished from normal circulating neutrophils (CD16bright/CD62Lbright) based on either an immature CD16dim/CD62Lbright or a CD16bright/CD62Ldim phenotype. Interestingly, the latter neutrophil subset is known to suppress lymphocyte proliferation ex vivo, but the underlying mechanism is largely unknown.
Publication Title
IFN-γ-stimulated neutrophils suppress lymphocyte proliferation through expression of PD-L1.
Sample Metadata Fields
Specimen part, Disease, Disease stage, Treatment
View Samples- Homo sapiens
- 71 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: PBMCs were isolated from 8 individuals bearing or not TLR10 polymorphism and were infected ex vivo with Salmonella enterica serovar Typhimurium. RNA was extracted before infection, 4 hours post infection and 8 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 62 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: Whole-blood (WB) cells and PBMCs were isolated from 4 healthy individuals and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. RNA was extracted 4 hours later.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Disease stage, Subject
View Samples- Homo sapiens
- 13 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: PBMCs were isolated from a healthy individual and were infected ex vivo with Salmonella enterica serovar Typhimurium or with PBS as control. Monocytes and NKT cells were sorted from naïve and infected PBMCs. RNA was extracted 4 hours post infection.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Subject
View Samples- Homo sapiens
- 12 Downloadable Samples
- NextSeq 500
Description
During host-pathogen encounters, the complex interactions between different immune cell-types can determine the outcome of infection. Advances in single cell RNA-seq (scRNA-seq) allow to probe this complexity of immunity, and afforded the basis for deconvolution algorithms that infer cell-type compositions from bulk RNA-seq measurements. However, immune activation, an important aspect of immune surveillance, is not represented in current algorithms. Here, using scRNA-seq of human peripheral blood cells infected with Salmonella, we developed a novel deconvolution algorithm to infer dynamic immune states from bulk measurements. We applied our dynamic deconvolution algorithm both to cohorts of healthy individuals challenged ex vivo with Salmonella and to cohorts of tuberculosis patients during different stages of disease. We revealed cell-type specific immune responses associated not only with ex vivo infection phenotype but also with clinical disease stage. We propose that our approach provides a predictive power to identify risk for disease, and can be applied to comprehensively study human infection outcome. Overall design: Frozen PBMCs from healthy individual were defrosted and infectd ex vivo with Salmonella enterica serovar Typhimurium.
Publication Title
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Sample Metadata Fields
Specimen part, Subject
View Samples- Homo sapiens
- 15 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Recent studies have demonstrated that upon encountering a pathogenic stimulus, robust metabolic rewiring of immune cells occurs. A switch away from oxidative phosphorylation to glycolysis, even in the presence of sufficient amounts of oxygen (akin the Warburg effect), is typically observed in activated innate and adaptive immune cells and is thought to accommodate adequate inflammatory responses. However, whether the Warburg effect is a general phenomenon applicable in human monocytes exposed to different pathogenic stimuli is unknown. Our results using human monocytes from healthy donors demonstrate that the Warburg effect only holds true for TLR4 activated cells. Although activation of other TLRs leads to an increase in glycolysis, no reduction or even an enhancement in oxidative phosphorylation is observed. Moreover, specific metabolic rewiring occurs in TLR4 vs. TLR2 stimulated cells characterized by altered gene expression profiles of pathways related to metabolism, changes in spare respiratory capacity of the cells and differential regulation of mitochondrial enzyme activity. Similarly, results from ex vivo and in vivo studies demonstrate metabolic rewiring of immune cells that is highly dependent on the type of pathogenic stimulus. Although the Warburg effect is observed in human monocytes after TLR4 activation, we propose that this typical metabolic response is not applicable to other inflammatory signalling routes including TLR2 in human monocytes. Instead, each pathogenic stimulus and subsequently activated inflammatory signalling cascade induces specific metabolic rewiring of the immune cell to accommodate an appropriate response.
Publication Title
Microbial stimulation of different Toll-like receptor signalling pathways induces diverse metabolic programmes in human monocytes.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples- Homo sapiens
- 40 Downloadable Samples
- NextSeq 500
Description
Transcriptomes of circulating monocytes in Q fever fatigue syndrome (QFS) patients, chronic fatigue syndrome (CFS) patients, asymptomatic Q fever seropositive controls and healthy controls Overall design: Circulating monocytes from QFS patinets, CFS patients, asymptomatic Q fever seropositive controls and healthy controls were isolated from PBMCs by menas of Percoll
Publication Title
A possible role for mitochondrial-derived peptides humanin and MOTS-c in patients with Q fever fatigue syndrome and chronic fatigue syndrome.
Sample Metadata Fields
Specimen part, Disease stage, Subject
View Samples- Mus musculus
- 16 Downloadable Samples
- Affymetrix Mouse Gene 1.1 ST Array (mogene11st)
Description
Peroxisome proliferator-activated receptor alpha (PPAR) is a key regulator of hepatic fat oxidation that serves as an energy source during starvation. Vanin-1 has been described as a putative PPAR target gene in liver, but its function in hepatic lipid metabolism is unknown. We investigated the regulation of vanin-1, and total vanin activity, by PPAR in mice and humans. Furthermore, the function of vanin-1 in the development of hepatic steatosis in response to starvation was examined in Vnn1 deficient mice, and in rats treated with an inhibitor of vanin activity. Liver microarray analyses reveals that Vnn1 is the most prominently regulated gene after modulation of PPAR activity. In addition, activation of mouse PPAR regulates hepatic- and plasma vanin activity. In humans, consistent with regulation by PPAR, plasma vanin activity increases in all subjects after prolonged fasting, as well as after treatment with the PPAR agonist fenofibrate. In mice, absence of vanin-1 exacerbates the fasting-induced increase in hepatic triglyceride levels. Similarly, inhibition of vanin activity in rats induces accumulation of hepatic triglycerides upon fasting. Microarray analysis reveal that the absence of vanin-1 associates with gene sets involved in liver steatosis, and reduces pathways involved in oxidative stress and inflammation. We show that hepatic vanin-1 is under extremely sensitive regulation by PPAR and that plasma vanin activity could serve as a readout of changes in PPAR activity in human subjects. In addition, our data propose a role for vanin-1 in regulation of hepatic TG levels during fasting.
Publication Title
PPAR-alpha dependent regulation of vanin-1 mediates hepatic lipid metabolism.
Sample Metadata Fields
Sex, Specimen part, Time
View Samples