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SRP167434
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- Rattus norvegicus
- 6 Downloadable Samples
Affymetrix Rat Genome U34 Array (rgu34a)
Description
Most commonly used models of non-alcoholic steatohepatitis (NASH) are diets based on specific gene knockouts or represent extreme manipulations of diet. We have examined the effects of modest increased caloric intake and high dietary unsaturated fat content on the development of NASH in male rats using a model in which overfeeding is accomplished via intragastric infusion of liquid diets as a part of total enteral nutrition. Male Sprague dawley rats were fed diets 5% corn oil containing diets at 187 Kcal/kg3/4/d or fed 70% corn oil containing diets at 220 Kcal/kg3/4/d for a period of 3 weeks. Hepatic gene expression were assessed at the end of the study. Our results indicate that overfeeding of high unsaturated fat diets leads to pathological, endocrine and metabolic changes characteristic of NASH patients and is associated with increased oxidative stress and TNF-a.
Publication Title
A new model for nonalcoholic steatohepatitis in the rat utilizing total enteral nutrition to overfeed a high-polyunsaturated fat diet.
Sample Metadata Fields
No sample metadata fields
View Samples- Rattus norvegicus
- 12 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
Soy foods have been suggested to have both positive health benefits and potentially adverse effects largely as a result of their content of isoflavone phytoestrogens. Since soy protein isolate (SPI) contains isoflavones, in addition to purported health benefits, safety concerns have been raised regarding the use of SPI and soy formulas, because of potential estrogenic actions during the neonatal period, including the potential for reproductive toxicity, infertility, and the possibility of increased risk for development and recurrence of estrogen sensitive cancers such as breast cancer. In the current study, we used a rat model to compare the effects of SPI with those of 17b-estradiol (E2), on global gene expression profiles and morphology in the female rat mammary gland. Rats were either fed AIN-93G diets containing casein (CAS) or SPI beginning on postnatal day (PND) 30.
Publication Title
Mammary gland morphology and gene expression differ in female rats treated with 17β-estradiol or fed soy protein isolate.
Sample Metadata Fields
Sex
View Samples- Rattus norvegicus
- 12 Downloadable Samples
- Affymetrix Rat Genome U34 Array (rgu34a)
Description
The current study was designed to determine if dietary fatty acid concentration and composition affects the development and progression of nonalcoholic fatty liver disease. Male SD rats were overfed diets low (5%) or high (70%) fat diets via total enteral nutrition where the fat source was olive oil (monounsaturated), or corn oil (polyunsaturated). Overfeeding 5% corn oil produced little steatosis relative to feeding 5% olive oil. This was associated with lower fatty acid synthesis and reduced SREBP-c signaling in the 5% corn oil group. Overfeeding 70% fat diets increased steatosis and lead to increased liver necrosis in the 70% corn oil but not olive oil group. Increased injury after feeding polyunsaturated fat diets was linked to peroxidizability of hepatic free fatty acids and triglycerides and appearance of peroxidaized lipid products HETES and HODES previously linked to clinical nonalcoholic steatohepatitis.
Publication Title
Dietary fat source alters hepatic gene expression profile and determines the type of liver pathology in rats overfed via total enteral nutrition.
Sample Metadata Fields
Sex
View Samples- Rattus norvegicus
- 24 Downloadable Samples
- Affymetrix Rat Genome 230 2.0 Array (rat2302)
Description
In order to properly understand whether xenoestrogens act as estrogens, it is essential to possess a solid portrait of the physiological effects of exogenous estradiol. Because the estrogen-dependent gene expression is one of the primary biomarkers of estrogenic action, we have assessed effects of three doses of exogenous estradiol (0.1, 1.0 and 10 g/kg of body weight/day) on the mammary gland morphology and gene expression profiles by microarray analysis of prepubertal male and female rats of both sexes compared to untreated controls. Estradiol was administered subcutaneously with minipumps from weaning at PND21 to the end of the experiment at PND33. The data suggest that the male mammary is a sensitive tissue for estrogenicity assessment.
Publication Title
Mammary gland morphology and gene expression signature of weanling male and female rats following exposure to exogenous estradiol.
Sample Metadata Fields
Sex
View Samples- Drosophila melanogaster
- 24 Downloadable Samples
- Illumina HiSeq 2500
Description
In order to study the transcriptional response of the fly brain to sugar and complete starvation, we first confirmed that 24 hours of sugar and complete starvation in flies is sufficient to elicit a homeostatic response. Subsequently, we used holidic medium to study effects of deficiency of a specfic macronutrient- cabohydrate in the food. To do so , we generated RNA- seq libraries from brains of 5 day old mated adult male flies maintained on different feeding regimes and used the sequencing data to identify diffrentially expressed genes in the brain under different feeding regimes. Overall design: For each condition, we used RNA prepared from 120-130 manually dissected adult fly brains maintained under complete starvation or sugar starvation regime for 24 hours.
Publication Title
Sugar Promotes Feeding in Flies via the Serine Protease Homolog scarface.
Sample Metadata Fields
Sex, Specimen part, Cell line, Subject
View Samples- Mus musculus
- 12 Downloadable Samples
- Affymetrix Mouse Genome 430 2.0 Array (mouse4302)
Description
While the existence of intestinal epithelial stem cells (IESCs) has been well established, their study has been limited due to the inability to isolate them. Previous work has utilized side population (SP) sorting of the murine small intestinal mucosa to isolate a viable fraction of cells enriched for putative IESCs. We have used microarray analyses to characterize the molecular features of this potential stem cell population.
Publication Title
Molecular properties of side population-sorted cells from mouse small intestine.
Sample Metadata Fields
No sample metadata fields
View Samples