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Visualizing spatial assay data in anatomical images is vital for understanding biological processes in cell, tissue, and organ organizations. Technologies requiring this functionality include traditional one-at-a-time assays, and bulk and single-cell omics experiments, including RNA-seq and proteomics. The spatialHeatmap software provides a series of powerful new methods for these needs, and allows users to work with adequately formatted anatomical images from public collections or custom images. It colors the spatial features (e.g. tissues) annotated in the images according to the measured or predicted abundance levels of biomolecules (e.g. mRNAs) using a color key. This core functionality of the package is called a spatial heatmap plot. Single-cell data can be co-visualized in composite plots that combine spatial heatmaps with embedding plots of high-dimensional data. The resulting spatial context information is essential for gaining insights into the tissue-level organization of single-cell data, or vice versa. Additional core functionalities include the automated identification of biomolecules with spatially selective abundance patterns and clusters of biomolecules sharing similar abundance profiles. To appeal to both non-expert and computational users, spatialHeatmap provides a graphical and a command-line interface, respectively. It is distributed as a free, open-source Bioconductor package (https://bioconductor.org/packages/spatialHeatmap) that users can install on personal computers, shared servers, or cloud systems.

 

The health benefits of switching from tobacco to electronic cigarettes (ECs) are neither confirmed nor well characterized. To address this problem, we used RNA-seq analysis to compare the nasal epithelium transcriptome from the following groups (n = 3 for each group): (1) former smokers who completely switched to second generation ECs for at least 6 months, (2) current tobacco cigarette smokers (CS), and (3) non-smokers (NS). Group three included one former cigarette smoker. The nasal epithelial biopsies from the EC users vs. NS had a higher number of differentially expressed genes (DEGs) than biopsies from the CS vs. NS and CS vs. EC sets (1817 DEGs total for the EC vs. NS, 407 DEGs for the CS vs. NS, and 116 DEGs for the CS vs. EC comparison). In the EC vs. NS comparison, enriched gene ontology terms for the downregulated DEGs included cilium assembly and organization, whereas gene ontologies for upregulated DEGs included immune response, keratinization, and NADPH oxidase. Similarly, ontologies for cilium movement were enriched in the downregulated DEGs for the CS vs. NS group. Reactome pathway analysis gave similar results and also identified keratinization and cornified envelope in the upregulated DEGs in the EC vs. NS comparison. In the CS vs. NS comparison, the enriched Reactome pathways for upregulated DEGs included biological oxidations and several metabolic processes. Regulator effects identified for the EC vs. NS comparison were inflammatory response, cell movement of phagocytes and degranulation of phagocytes. Disease Ontology Sematic Enrichment analysis identified lung disease, mouth disease, periodontal disease and pulmonary fibrosis in the EC vs. NS comparison. Squamous metaplasia associated markers, keratin 10, keratin 13 and involucrin, were increased in the EC vs. NS comparison. Our transcriptomic analysis showed that gene expression profiles associated with EC use are not equivalent to those from non-smokers. EC use may interfere with airway epithelium recovery by promoting increased oxidative stress, inhibition of ciliogenesis, and maintaining an inflammatory response. These transcriptomic alterations may contribute to the progression of diseases with chronic EC use. 

Abstract signatureSearch is an R/Bioconductor package that integrates a suite of existing and novel algorithms into an analysis environment for gene expression signature (GES) searching combined with functional enrichment analysis (FEA) and visualization methods to facilitate the interpretation of the search results. In a typical GES search (GESS), a query GES is searched against a database of GESs obtained from large numbers of measurements, such as different genetic backgrounds, disease states and drug perturbations. Database matches sharing correlated signatures with the query indicate related cellular responses frequently governed by connected mechanisms, such as drugs mimicking the expression responses of a disease. To identify which processes are predominantly modulated in the GESS results, we developed specialized FEA methods combined with drug-target network visualization tools. The provided analysis tools are useful for studying the effects of genetic, chemical and environmental perturbations on biological systems, as well as searching single cell GES databases to identify novel network connections or cell types. The signatureSearch software is unique in that it provides access to an integrated environment for GESS/FEA routines that includes several novel search and enrichment methods, efficient data structures, and access to pre-built GES databases, and allowing users to work with custom databases. 

Aging is the dominant risk factor for most chronic diseases. Development of antiaging interventions offers the promise of preventing many such illnesses simultaneously. Cellular stress resistance is an evolutionarily conserved feature of longevity. Here, we identify compounds that induced resistance to the superoxide generator paraquat (PQ), the heavy metal cadmium (Cd), and the DNA alkylator methyl methanesulfonate (MMS). Some rescue compounds conferred resistance to a single stressor, while others provoked multiplex resistance. Induction of stress resistance in fibroblasts was predictive of longevity extension in a published large-scale longevity screen in Caenorhabditis elegans , although not in testing performed in worms and flies with a more restricted set of compounds. Transcriptomic analysis and genetic studies implicated Nrf2/SKN-1 signaling in stress resistance provided by two protective compounds, cardamonin and AEG 3482. Small molecules identified in this work may represent attractive tools to elucidate mechanisms of stress resistance in mammalian cells.