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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- Homo sapiens
- 23 Downloadable Samples
Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
Tumour hypoxia exhibits a highly dynamic spatial and temporal distribution and is associated with increased malignancy and poor prognosis.
Publication Title
Two phases of disulfide bond formation have differing requirements for oxygen.
Sample Metadata Fields
Treatment
View Samples- Homo sapiens
- 46 Downloadable Samples
- Affymetrix Human Gene 1.0 ST Array (hugene10st)
Description
Immunosuppression is needed in HLA identical sibling renal transplantation. We conducted a tolerance trial in this patient cohort using Alemtuzumab induction, donor hematopoietic stem cells, tacrolimus/mycophenolate immunosuppression converted to sirolimus, planning complete drug withdrawal by 24 months post-transplantation. After an additional 12 months with no immunosuppression, normal biopsies and renal function, recipients were considered tolerant. Twenty recipients were enrolled. Of the first 10 (>36 months post-transplantation), 5 had immunosuppression successfully withdrawn for 16-36 months (tolerant), 2 had disease recurrence and 3 had subclinical rejection in protocol biopsies (non-tolerant). Microchimerism disappeared after 1 year, and CD4+CD25highCD127-FOXP3+ T cells and CD19+IgD/M+CD27- B cells increased to 5 years post-transplantation in both groups, whereas immune/inflammatory gene expression pathways in the peripheral blood and urine were differentially downregulated in tolerant compared to non-tolerant recipients. Therefore, in this HLA identical renal transplant tolerance trial, absent chimerism, Treg and Breg immunophenotypes were indistinguishable between tolerant and non-tolerant recipients, but global genomic changes indicating immunomodulation were observed only in tolerant recipients.
Publication Title
Genomic biomarkers correlate with HLA-identical renal transplant tolerance.
Sample Metadata Fields
Specimen part, Time
View Samples- Homo sapiens
- 12 Downloadable Samples
- Affymetrix Human Genome U133A 2.0 Array (hgu133a2)
Description
To identify early processes in carcinogenesis, we used an in vitro model, based on the initiating event in cervical cancer, human papillomavirus (HPV) transformation of keratinocytes. We compared gene expression in primary keratinocytes (K) and HPV16-transformed keratinocytes from early (E) and late (L) passages, and from benzo[a]pyrene treated L cells (BP). The transformed cells exhibit similar transcriptional changes to clinical cervical carcinoma. We revealed a contraction in expression of the apoptotic network during HF1 cell transformation, which affected the ability of L and BP cells to execute apoptosis, but did not lead to resistance to apoptotic stimuli. The contraction in the apoptotic machinery during the process of transformation was accompanied by a switch from apoptosis to necrosis in response to CDDP. The shrinkage of the pro- and anti-apoptotic networks appears to be part of a general contraction in the number of genes transcribed in L and BP cells. We also identified a large group of genes with induced expression, which are involved in cell metabolism and cell cycle, suggesting increased investment of the transformed cell in cellular proliferation. We hypothesize that the decrease in expression of many diverse pathways, including the pro- and anti-apoptotic networks, cuts the energy requirements for cell maintenance, allowing energy to be diverted towards rapid cell proliferation. This study supports the hypothesis that the process of cancer transformation may be accompanied by a shift from apoptosis to necrosis.
Publication Title
Shift from apoptotic to necrotic cell death during human papillomavirus-induced transformation of keratinocytes.
Sample Metadata Fields
Specimen part, Cell line
View Samples- Arabidopsis thaliana
- 6 Downloadable Samples
- Illumina HiSeq 2000
Description
15-20 cm tall 35S::Myc-GR-bdl plants were dipped headfirst in 15 µM dexamethasone or mock solution and after three hours of incubation second internodes were harvested and snap frozen in liquid nitrogen. Frozen plant material was pulverized with pestle and mortar and RNA was isolated by phenol/chlorophorm extraction as described previously (Mallory & Vaucheret 2010, PlantCell) with the modification of two additional concluding 70% EtOH washes Overall design: RNA from three samples was pooled and analyzed by RNAseq.
Publication Title
Spatial specificity of auxin responses coordinates wood formation.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples- Arabidopsis thaliana
- 6 Downloadable Samples
- Illumina HiSeq 2000
Description
15-20 cm tall PXY:GR-MP?III/IV plants were dipped headfirst in 15 µM dexamethasone or mock solution and after three hours of incubation second internodes were harvested and snap frozen in liquid nitrogen. Frozen plant material was pulverized with pestle and mortar and RNA was isolated by phenol/chlorophorm extraction as described previously (Mallory & Vaucheret 2010, PlantCell) with the modification of two additional concluding 70% EtOH washes Overall design: RNA from three samples was pooled and analyzed by RNAseq.
Publication Title
Spatial specificity of auxin responses coordinates wood formation.
Sample Metadata Fields
Specimen part, Treatment, Subject
View Samples- Homo sapiens
- 50 Downloadable Samples
- Affymetrix Human Genome U133 Plus 2.0 Array (hgu133plus2)
Description
One third to one half of all infants born before the 28th wek of gestation develop BPD bronchopulmonary dysplasia. Our objective is to evaluate the feasibility of using expression profiling in umbilical cord tissue to discover molecular signatures for developmental staging and for risk of BPD.
Publication Title
Perturbation of gene expression of the chromatin remodeling pathway in premature newborns at risk for bronchopulmonary dysplasia.
Sample Metadata Fields
No sample metadata fields
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