Predicting molecular mechanisms of hereditary diseases by using their tissue-selective manifestation.

How do aberrations in widely expressed genes lead to tissue-selective hereditary diseases? Previous attempts to answer this question were limited to testing a few candidate mechanisms. To answer this question at a larger scale, we developed "Tissue Risk Assessment of Causality by Expression" (TRACE), a machine learning approach to predict genes that underlie tissue-selective diseases and selectivity-related features. TRACE utilized 4,744 biologically interpretable tissue-specific gene features that were inferred from heterogeneous omics datasets.

The TissueNet v.3 Database: Protein-protein Interactions in Adult and Embryonic Human Tissue contexts.

Tissue contexts are extremely valuable when studying protein functions and their associated phenotypes. Recently, the study of proteins in tissue contexts was greatly facilitated by the availability of thousands of tissue transcriptomes. To provide access to these data we developed the TissueNet integrative database that displays protein-protein interactions (PPIs) in tissue contexts.

The differential activity of biological processes in tissues and cell subsets can illuminate disease-related processes and cell-type identities.

Motivation: The distinct functionalities of human tissues and cell types underlie complex phenotype-genotype relationships, yet often remain elusive. Harnessing the multitude of bulk and single-cell human transcriptomes while focusing on processes can help reveal these distinct functionalities.

Results: The Tissue-Process Activity (TiPA) method aims to identify processes that are preferentially active or under-expressed in specific contexts, by comparing the expression levels of process genes between contexts.

The landscape of molecular chaperones across human tissues reveals a layered architecture of core and variable chaperones.

The sensitivity of the protein-folding environment to chaperone disruption can be highly tissue-specific. Yet, the organization of the chaperone system across physiological human tissues has received little attention. Through computational analyses of large-scale tissue transcriptomes, we unveil that the chaperone system is composed of core elements that are uniformly expressed across tissues, and variable elements that are differentially expressed to fit with tissue-specific requirements.

Co-assembled Ca Alginate-Sulfate Nanoparticles for Intracellular Plasmid DNA Delivery.

Successful gene therapy requires the development of suitable carriers for the selective and efficient delivery of genes to specific target cells, with minimal toxicity. In this work, we present a non-viral vector for gene delivery composed of biocompatible materials, CaCl, plasmid DNA and the semi-synthetic anionic biopolymer alginate sulfate (AlgS), which spontaneously co-assembled to form nanoparticles (NPs). The NPs were characterized with a slightly anionic surface charge (Zeta potential [ζ] = -14 mV), an average size of 270 nm, and their suspension was stable for several days with no aggregation.

Differential TGF-β Signaling in Glial Subsets Underlies IL-6-Mediated Epileptogenesis in Mice.

TGF-β1 is a master cytokine in immune regulation, orchestrating both pro- and anti-inflammatory reactions. Recent studies show that whereas TGF-β1 induces a quiescent microglia phenotype, it plays a pathogenic role in the neurovascular unit and triggers neuronal hyperexcitability and epileptogenesis. In this study, we show that, in primary glial cultures, TGF-β signaling induces rapid upregulation of the cytokine IL-6 in astrocytes, but not in microglia, via enhanced expression, phosphorylation, and nuclear translocation of SMAD2/3.