Tauno Metsalu

Bio: Tauno Metsalu is an academic researcher from University of Tartu. The author has contributed to research in topics: Gene expression profiling & Gene. The author has an hindex of 7, co-authored 8 publications receiving 2000 citations.

ClustVis: a web tool for visualizing clustering of multivariate data using Principal Component Analysis and heatmap

Abstract: The Principal Component Analysis (PCA) is a widely used method of reducing the dimensionality of high-dimensional data, often followed by visualizing two of the components on the scatterplot. Although widely used, the method is lacking an easy-to-use web interface that scientists with little programming skills could use to make plots of their own data. The same applies to creating heatmaps: it is possible to add conditional formatting for Excel cells to show colored heatmaps, but for more advanced features such as clustering and experimental annotations, more sophisticated analysis tools have to be used. We present a web tool called ClustVis that aims to have an intuitive user interface. Users can upload data from a simple delimited text file that can be created in a spreadsheet program. It is possible to modify data processing methods and the final appearance of the PCA and heatmap plots by using drop-down menus, text boxes, sliders etc. Appropriate defaults are given to reduce the time needed by the user to specify input parameters. As an output, users can download PCA plot and heatmap in one of the preferred file formats. This web server is freely available at http://biit.cs.ut.ee/clustvis/.

MethSurv: a web tool to perform multivariable survival analysis using DNA methylation data.

Abstract: AIM To develop a web tool for survival analysis based on CpG methylation patterns. MATERIALS & METHODS We utilized methylome data from 'The Cancer Genome Atlas' and used the Cox proportional-hazards model to develop an interactive web interface for survival analysis. RESULTS MethSurv enables survival analysis for a CpG located in or around the proximity of a query gene. For further mining, cluster analysis for a query gene to associate methylation patterns with clinical characteristics and browsing of top biomarkers for each cancer type are provided. MethSurv includes 7358 methylomes from 25 different human cancers. CONCLUSION The MethSurv tool is a valuable platform for the researchers without programming skills to perform the initial assessment of methylation-based cancer biomarkers.

Mechanisms of IFN-γ-induced apoptosis of human skin keratinocytes in patients with atopic dermatitis

Abstract: Background Enhanced apoptosis of keratinocytes is the main cause of eczema and spongiosis in patients with the common inflammatory skin disease atopic dermatitis (AD). Objective The aim of the study was to investigate molecular mechanisms of AD-related apoptosis of keratinocytes. Methods Primary keratinocytes isolated from patients with AD and healthy donors were used to study apoptosis by using annexin V/7-aminoactinomycin D staining. Illumina mRNA Expression BeadChips, quantitative RT-PCR, and immunofluorescence were used to study gene expression. In silico analysis of candidate genes was performed on genome-wide single nucleotide polymorphism data. Results We demonstrate that keratinocytes of patients with AD exhibit increased IFN-γ–induced apoptosis compared with keratinocytes from healthy subjects. Further mRNA expression analyses revealed differential expression of apoptosis-related genes in AD keratinocytes and skin and the upregulation of immune system–related genes in skin biopsy specimens of chronic AD lesions. Three apoptosis-related genes ( NOD2 , DUSP1 , and ADM ) and 8 genes overexpressed in AD skin lesions ( CCDC109B , CCL5 , CCL8 , IFI35 , LYN , RAB31 , IFITM1 , and IFITM2 ) were induced by IFN-γ in primary keratinocytes. The protein expression of IFITM1, CCL5, and CCL8 was verified in AD skin. In line with the functional studies and AD-related mRNA expression changes, in silico analysis of genome-wide single nucleotide polymorphism data revealed evidence of an association between AD and genetic markers close to or within the IFITM cluster or RAB31 , DUSP1 , and ADM genes. Conclusion Our results demonstrate increased IFN-γ responses in skin of patients with AD and suggest involvement of multiple new apoptosis- and inflammation-related factors in the development of AD.

Capturing complex tumour biology in vitro: Histological and molecular characterisation of precision cut slices

Abstract: Precision-cut slices of in vivo tumours permit interrogation in vitro of heterogeneous cells from solid tumours together with their native microenvironment. They offer a low throughput but high content in vitro experimental platform. Using mouse models as surrogates for three common human solid tumours, we describe a standardised workflow for systematic comparison of tumour slice cultivation methods and a tissue microarray-based method to archive them. Cultivated slices were compared to their in vivo source tissue using immunohistochemical and transcriptional biomarkers, particularly of cellular stress. Mechanical slicing induced minimal stress. Cultivation of tumour slices required organotypic support materials and atmospheric oxygen for maintenance of integrity and was associated with significant temporal and loco-regional changes in protein expression, for example HIF-1α. We recommend adherence to the robust workflow described, with recognition of temporal-spatial changes in protein expression before interrogation of tumour slices by pharmacological or other means.

疟原虫var基因转换速率变化导致抗原变异[英]／Paul H, Robert P, Christodoulou Z, et al//Proc Natl Acad Sci U S A

Abstract: 抗原变异可使得多种致病微生物易于逃避宿主免疫应答。表达在感染红细胞表面的恶性疟原虫红细胞表面蛋白1（PfPMP1）与感染红细胞、内皮细胞、树突状细胞以及胎盘的单个或多个受体作用，在黏附及免疫逃避中起关键的作用。每个单倍体基因组var基因家族编码约60种成员，通过启动转录不同的var基因变异体为抗原变异提供了分子基础。

g:Profiler: a web server for functional enrichment analysis and conversions of gene lists (2019 update).

Abstract: Biological data analysis often deals with lists of genes arising from various studies. The g:Profiler toolset is widely used for finding biological categories enriched in gene lists, conversions between gene identifiers and mappings to their orthologs. The mission of g:Profiler is to provide a reliable service based on up-to-date high quality data in a convenient manner across many evidence types, identifier spaces and organisms. g:Profiler relies on Ensembl as a primary data source and follows their quarterly release cycle while updating the other data sources simultaneously. The current update provides a better user experience due to a modern responsive web interface, standardised API and libraries. The results are delivered through an interactive and configurable web design. Results can be downloaded as publication ready visualisations or delimited text files. In the current update we have extended the support to 467 species and strains, including vertebrates, plants, fungi, insects and parasites. By supporting user uploaded custom GMT files, g:Profiler is now capable of analysing data from any organism. All past releases are maintained for reproducibility and transparency. The 2019 update introduces an extensive technical rewrite making the services faster and more flexible. g:Profiler is freely available at https://biit.cs.ut.ee/gprofiler.

g:Profiler—a web server for functional interpretation of gene lists (2016 update)

Abstract: Functional enrichment analysis is a key step in interpreting gene lists discovered in diverse high-throughput experiments. g:Profiler studies flat and ranked gene lists and finds statistically significant Gene Ontology terms, pathways and other gene function related terms. Translation of hundreds of gene identifiers is another core feature of g:Profiler. Since its first publication in 2007, our web server has become a popular tool of choice among basic and translational researchers. Timeliness is a major advantage of g:Profiler as genome and pathway information is synchronized with the Ensembl database in quarterly updates. g:Profiler supports 213 species including mammals and other vertebrates, plants, insects and fungi. The 2016 update of g:Profiler introduces several novel features. We have added further functional datasets to interpret gene lists, including transcription factor binding site predictions, Mendelian disease annotations, information about protein expression and complexes and gene mappings of human genetic polymorphisms. Besides the interactive web interface, g:Profiler can be accessed in computational pipelines using our R package, Python interface and BioJS component. g:Profiler is freely available at http://biit.cs.ut.ee/gprofiler/.

Interleukins (from IL-1 to IL-38), interferons, transforming growth factor β, and TNF-α: Receptors, functions, and roles in diseases

Abstract: There have been extensive developments on cellular and molecular mechanisms of immune regulation in allergy, asthma, autoimmune diseases, tumor development, organ transplantation, and chronic infections during the last few years. Better understanding the functions, reciprocal regulation, and counterbalance of subsets of immune and inflammatory cells that interact through interleukins, interferons, TNF-α, and TGF-β offer opportunities for immune interventions and novel treatment modalities in the era of development of biological immune response modifiers particularly targeting these molecules or their receptors. More than 60 cytokines have been designated as interleukins since the initial discoveries of monocyte and lymphocyte interleukins (called IL-1 and IL-2, respectively). Studies of transgenic or gene-deficient mice with altered expression of these cytokines or their receptors and analyses of mutations and polymorphisms in human genes that encode these products have provided essential information about their functions. Here we review recent developments on IL-1 to IL-38, TNF-α, TGF-β, and interferons. We highlight recent advances during the last few years in this area and extensively discuss their cellular sources, targets, receptors, signaling pathways, and roles in immune regulation in patients with allergy and asthma and other inflammatory diseases.

The 3 major types of innate and adaptive cell-mediated effector immunity.

Abstract: The immune system has tailored its effector functions to optimally respond to distinct species of microbes. Based on emerging knowledge on the different effector T-cell and innate lymphoid cell (ILC) lineages, it is clear that the innate and adaptive immune systems converge into 3 major kinds of cell-mediated effector immunity, which we propose to categorize as type 1, type 2, and type 3. Type 1 immunity consists of T-bet + IFN-γ–producing group 1 ILCs (ILC1 and natural killer cells), CD8 + cytotoxic T cells (T C 1), and CD4 + T H 1 cells, which protect against intracellular microbes through activation of mononuclear phagocytes. Type 2 immunity consists of GATA-3 + ILC2s, T C 2 cells, and T H 2 cells producing IL-4, IL-5, and IL-13, which induce mast cell, basophil, and eosinophil activation, as well as IgE antibody production, thus protecting against helminthes and venoms. Type 3 immunity is mediated by retinoic acid–related orphan receptor γt + ILC3s, T C 17 cells, and T H 17 cells producing IL-17, IL-22, or both, which activate mononuclear phagocytes but also recruit neutrophils and induce epithelial antimicrobial responses, thus protecting against extracellular bacteria and fungi. On the other hand, type 1 and 3 immunity mediate autoimmune diseases, whereas type 2 responses can cause allergic diseases.