Exosomes are vesicles of endocytic origin released by many types of cells into the extracellular environment. In an attempt to further examine the exosome-mediated cellular communication, we show that exosomes from a mouse mast cell line (MC/9), exosomes from primary bone marrow derived mast cells, and exosomes from a human mast cell line (HMC-1) contain RNA but not DNA.
Exosome-mediated transfer of mRNAs and microRNAs is a novel mechanism of genetic exchange between cells.
No sample metadata fields
View SamplesBackground: Exosomes are nanovesicles of endocytic origin believed to be involved in communication between cells. Recently, it has been shown that mast cell exosomes contain RNA named "exosomal shuttle RNA". The aim of this study was to evaluate whether exosomal shuttle RNA could play a role in the communication between human mast cells and between human mast cells and human CD34 positive progenitor cells. Results: Exosomes from the human mast cell line HMC-1 contain RNA. The exosomes contain no or very little ribosomal RNA compared to their donor cells. The mRNA and microRNA content in exosomes and their donor cells was examined using microarray analyses. We found 116 microRNA in the exosomes and 134 microRNA in the cells, from which some were expressed at different level. DNA microarray experiments revealed the presence of approximately 1800 mRNAs in the exosomes, which represent 15% of the donor cell mRNA content. Transfer experiments revealed that exosomes and their RNA can transfer to other HMC-1 cells and to CD34 positive progenitors. Conclusions: To conclude, HMC-1 exosomes contain mRNA and microRNA that can be transferred to other mast cells and to CD34 progenitors. This shuttle of exosomal RNA may represent a powerful mode of communication between cells where cells send genetic information to other cells over a distance via exosomes.
Characterization of mRNA and microRNA in human mast cell-derived exosomes and their transfer to other mast cells and blood CD34 progenitor cells.
Cell line
View SamplesCD8+ T cells are pre-programmed for cytotoxic differentiation. However, a subset of effector CD8+ T cells (Tc17) produce IL-17 and fail to express cytotoxic genes. Here, we show that the transcription factors directing IL-17 production inhibit cytotoxicity despite persistent Runx3 expression. Cytotoxic gene repression did not require the transcription factor Thpok. We further show that STAT3 restrained cytotoxic gene expression in CD8+ T cells and that RORgt represses cytotoxic genes by inhibiting the functions but not the expression of the cytotoxic transcription factors T-bet and Eomesodermin. Thus, the transcriptional circuitry directing IL-17 expression inhibits cytotoxic functions.
A STAT3-dependent transcriptional circuitry inhibits cytotoxic gene expression in T cells.
Specimen part
View SamplesCD8+ T cells are pre-programmed for cytotoxic differentiation. However, a subset of effector CD8+ T cells (Tc17) produce IL-17 and fail to express cytotoxic genes. Here, we show that the transcription factors directing IL-17 production inhibit cytotoxicity despite persistent Runx3 expression. Cytotoxic gene repression did not require the transcription factor Thpok. We further show that STAT3 restrained cytotoxic gene expression in CD8+ T cells and that RORgt represses cytotoxic genes by inhibiting the functions but not the expression of the cytotoxic transcription factors T-bet and Eomesodermin. Thus, the transcriptional circuitry directing IL-17 expression inhibits cytotoxic functions.
A STAT3-dependent transcriptional circuitry inhibits cytotoxic gene expression in T cells.
Specimen part
View SamplesISWI is an evolutionary conserved ATPase that catalyzes nucleosome remodeling in several different complexes. Two mammalian ISWI orthologs, SNF2H and SNF2L, have specialized functions despite their high similarity. Due to the lack of reagents the functions of SN2L in human cells had not been established. Newly established specific monoclonal antibodies and selective RNA interference protocols now enabled a comprehensive characterization of loss-of-function phenotypes in human cells. Contrasting earlier results obtained in the mouse model, we found SNF2L broadly expressed in primary human tissues. Depletion of SNF2L in HeLa cells led to enhanced proliferation, morphological alterations and increased migration. These phenomena were explained by transcriptome profiling, which identified SNF2L as a modulator of the Wnt signaling network. The cumulative effects of SNF2L depletion on gene expression portray the cell in a state of activated Wnt signaling characterized by increased proliferation and chemotactic locomotion. High levels of SNF2L expression in normal melanocytes contrast to undetectable expression in malignant melanoma. In summary, our data document an anti-correlation between SNF2L expression and several features characteristic of malignant cells.
Nucleosome remodeler SNF2L suppresses cell proliferation and migration and attenuates Wnt signaling.
Cell line
View SamplesMicroRNAs (miRs) function primarily as post-transcriptional negative regulators of gene expression through binding to their mRNA targets. Reliable prediction of a miRs targets is a considerable bioinformatic challenge of great importance for inferring the miRs function. Sequence-based prediction algorithms have high false-positive rates, are not in agreement, and are not biological context specific. Here we introduce CoSMic (Context-Specific MicroRNA analysis), an algorithm that combines sequence-based prediction with miR and mRNA expression data. CoSMic differs from existing methodsit identifies miRs that play active roles in the specific biological system of interest and predicts with less false positives their functional targets. We applied CoSMic to search for miRs that regulate the migratory response of human mammary cells to epidermal growth factor (EGF) stimulation. Several such miRs, whose putative targets were significantly enriched by migration processes were identified. We tested three of these miRs experimentally, and showed that they indeed affected the migratory phenotype; we also tested three negative controls. In comparison to other algorithms CoSMic indeed filters out false positives and allows improved identification of context-specific targets. CoSMic can greatly facilitate miR research in general and, in particular, advance our understanding of individual miRs function in a specific context.
Context-specific microRNA analysis: identification of functional microRNAs and their mRNA targets.
Cell line
View Samplesp53 is a pivotal tumor suppressor and a major barrier against cancer. We now report that silencing of the Hippo pathway tumor suppressors LATS1 and LATS2 in non-transformed mammary epithelial cells reduces p53 phosphorylation and increases its association with the p52 NF-?B subunit. Moreover, it partly shifts p53’s conformation and transcriptional output towards a state resembling cancer-associated p53 mutants, and endow p53 with the ability to promote cell migration. Notably, LATS1 and LATS2 are frequently downregulated in breast cancer; we propose that such downregulation might benefit cancer by converting p53 from a tumor suppressor into a tumor facilitator. Overall design: MCF10A cells transfected with siRNA against LATS1/2 alone, p53 alone or LATS1/2 and p53 together. Two independent MCF10A batches provided biological replicates
Down-regulation of LATS kinases alters p53 to promote cell migration.
No sample metadata fields
View SamplesBackground & Aims: Overnutrition is one of the major causes of non-alcoholic fatty liver disease (NAFLD) and its advanced form non-alcoholic steatohepatitis (NASH). Besides the quantity of consumed calories, distinct dietary components are increasingly recognized as important contributor to the pathogenesis of NASH. We aimed to develop and characterize a hitherto missing murine model which resembles both the pathology and nutritional situation of NASH-patients in Western societies.
Increased expression of c-Jun in nonalcoholic fatty liver disease.
Age, Specimen part, Treatment
View SamplesDuring 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.
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Specimen part, Subject
View SamplesDuring 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.
Predicting bacterial infection outcomes using single cell RNA-sequencing analysis of human immune cells.
Specimen part, Disease stage, Subject
View Samples