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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
- 36 Downloadable Samples
Sentrix Human-6 Expression BeadChip
Description
In cervical cancer, an important mechanism by which tumour cells escape immune surveillance is loss of HLA class I, enabling tumours to evade recognition and lysis by cytotoxic T lymphocytes. Some tumours, however, escape from immune surveillance without accumulating defects in antigen presentation. We hypothesized that tumours with no or partial loss of HLA class I develop alternative mechanisms to prevent immune surveillance. To investigate this hypothesis, genome-wide expression profiling using Illumina arrays was performed on cervical squamous cell carcinomas showing overall loss of HLA class I, partial and normal HLA class I protein expression. Statistical analyses revealed no significant differences in gene expression between tumours with partial (n = 11) and normal HLA class I expression (n = 10). Comparison of tumours with normal/partial HLA class I expression (n = 21) with those with overall loss of HLA class I expression (n = 11) identified 150 differentially expressed genes. Most of these genes were involved in the defense response (n = 27), and, in particular, inflammatory and acute phase responses. Especially SerpinA1 and SerpinA3 were found to be upregulated in HLA positive tumours (3.6 and 8.2 fold, respectively), and this was confirmed by real-time PCR and immunohistochemistry. In a group of 117 tumours, high SerpinA1 and SerpinA3 expression in association with normal/partial HLA expression correlated significantly with poor overall survival (p = 0.035 and p = 0.05, respectively). This study shows that HLA positive tumours are characterized by a higher expression of genes associated with an inflammatory profile and that expression of the acute phase proteins SerpinA1 and SerpinA3 in HLA positive tumours is associated with worse prognosis.
Publication Title
Elevated expression of SerpinA1 and SerpinA3 in HLA-positive cervical carcinoma.
Sample Metadata Fields
No sample metadata fields
View Samples- Homo sapiens
- 17 Downloadable Samples
- Affymetrix Human Genome U95 Version 2 Array (hgu95av2)
Description
The similarity in gene-expression profiles suggest that PGL2, like SDHD, is involved in the functionality of the SDH complex, and that tumor formation in these three subgroups involves the same pathways as in SDH linked paragangliomas. We were not able to clarify the identity of PGL2 on 11q13. The lack of differential gene-expression of chromosome 11 genes might indicate that chromosome 11 loss, as demonstrated in SDHD-linked paragangliomas, is an important feature in the formation of a paraganglioma regardless of the genetic background.
Publication Title
Similar gene expression profiles of sporadic, PGL2-, and SDHD-linked paragangliomas suggest a common pathway to tumorigenesis.
Sample Metadata Fields
No sample metadata fields
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- Mus musculus
- 6 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This SuperSeries is composed of the SubSeries listed below.
Publication Title
JAK/STAT3 signalling is sufficient and dominant over antagonistic cues for the establishment of naive pluripotency.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples- Mus musculus
- 4 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This microarray was performed to gain insight in the effect of GY118F stimulation in EpiSCs. This array is part of the following paper to be published in Nature Communications: JAK/STAT3 signalling is sufficient and dominant over antagonistic cues for the establishment of nave pluripotency by Anouk L. van Oosten, Yael Costa, Austin Smith & Jos C.R. Silva
Publication Title
JAK/STAT3 signalling is sufficient and dominant over antagonistic cues for the establishment of naive pluripotency.
Sample Metadata Fields
Specimen part, Treatment
View Samples- Mus musculus
- 2 Downloadable Samples
- Illumina MouseWG-6 v2.0 expression beadchip
Description
This microarray was performed to gain insight in the downstream targets of GY118F in iPS cells. This array is part of the following paper to be published in Nature Communications: JAK/STAT3 signalling is sufficient and dominant over antagonistic cues for the establishment of nave pluripotency by Anouk L. van Oosten, Yael Costa, Austin Smith & Jos C.R. Silva
Publication Title
JAK/STAT3 signalling is sufficient and dominant over antagonistic cues for the establishment of naive pluripotency.
Sample Metadata Fields
Sex, Specimen part, Treatment
View Samples- Homo sapiens
- 127 Downloadable Samples
- Affymetrix Human Gene 1.1 ST Array (hugene11st)
Description
Early perturbations in vascular health can be detected by imposing subjects to a high fat (HF) challenge and measure response capacity. Subtle responses can be determined by assessment of whole-genome transcriptional changes. We aimed to magnify differences in health by comparing gene-expression changes in peripheral blood mononuclear cells (PBMCs) towards a high MUFA or SFA challenge between subjects with different cardiovascular disease risk profiles and to identify fatty-acid specific gene-expression pathways.
Publication Title
High fat challenges with different fatty acids affect distinct atherogenic gene expression pathways in immune cells from lean and obese subjects.
Sample Metadata Fields
Sex, Specimen part, Subject
View Samples