Biology subjects

Nordstroem, K.

Publications and source records attributed to Nordstroem, K..

3 recordsLinked to original sources

bioRxiv2018

Sodium chloride is an ionic checkpoint for human Th2 cell responses and shapes the atopic skin microenvironment

One sentence summarySodium is an ionic checkpoint for the induction and amplification of human Th2 cell responses and shapes the atopic skin microenvironment, where it could serve as a novel therapeutic target for Th2 mediated diseases.\n\nAbstractThere has been a strong increase in the incidence of allergic diseases over the last 50 years. Environmental factors most likely account for this phenomenon. However, the nature of these factors and the mode of action by which they induce the type 2 immune deviation, which is characteristic of atopic diseases, remains unclear. It has previously been reported that dietary sodium chloride promotes the polarization of Th17 cells with implications for autoimmune diseases such as multiple sclerosis. Here, we demonstrate that sodium chloride also potently promotes Th2 cell responses on multiple regulatory levels. Sodium chloride enhanced IL-4 and IL-13 production while suppressing IFN-{gamma} production in effector T cells. It diverted alternative T cell fates into the Th2 cell phenotype and also induced de novo Th2 cell polarization from naive T cell precursors. Mechanistically, it exerted its effects via the osmosensitive transcription factor NFAT-5 and the kinase SGK-1, which regulated Th2 signature cytokines and master transcription factors in hyperosmolar salt conditions. The skin of patients suffering from atopic dermatitis contained highly elevated amounts of sodium compared to non-lesional atopic and healthy skin. This demonstrates that sodium chloride represents a so far overlooked cutaneous microenvironmental factor in atopic dermatitis that can induce Th2 cell responses, the orchestrators of allergic diseases. Together, our data propose ionic signaling through sodium chloride as a novel checkpoint and potential therapeutic target for type 2 immunity and its associated allergic diseases.

immunology↗

bioRxiv2018

Integrative analysis of single cell expression data reveals distinct regulatory states in bidirectional promoters

BackgroundBidirectional promoters (BPs) are prevalent in eukaryotic genomes. However, it is poorly understood how the cell integrates different epigenomic information, such as transcription factor (TF) binding and chromatin marks, to drive gene expression at BPs. Single cell sequencing technologies are revolutionizing the field of genome biology. Therefore, this study focuses on the integration of single cell RNA-seq data with bulk ChIP-seq and other epigenetics data, for which single cell technologies are not yet established, in the context of BPs.\n\nResultsWe performed integrative analyses of novel human single cell RNA-seq (scRNA-seq) data with bulk ChIP-seq and other epigenetics data. scRNA-seq data revealed distinct transcription states of BPs that were previously not recognized. We find associations between these transcription states to distinct patterns in structural gene features, DNA accessibility, histone modification, DNA methylation and TF binding profiles.\n\nConclusionsOur results suggest that a complex interplay of all of these elements is required to achieve BP-specific transcriptional output in this specialized promoter configuration. Further, our study implies that novel statistical methods can be developed to deconvolute masked subpopulations of cells measured with different bulk epigenomic assays using scRNA-seq data.

genomics↗

bioRxiv2016

Combining transcription factor binding affinities with open-chromatin data for accurate gene expression prediction

The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq datasets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

bioinformatics↗