Retinoic Acid Functions as a Key GABAergic Differentiation Signal in the Basal Ganglia

Retinoic acid (RA) is essential for the generation of GABAergic inhibitory neurons in the mouse forebrain, and RA treatment of embryonic stem cells induces the production of GABAergic neurons

Transient receptor potential canonical 4 and 5 proteins as targets in cancer therapeutics

Novel approaches towards cancer therapy are urgently needed. One approach might be to target ion channels mediating Ca²+ entry because of the critical roles played by Ca²+ in many cell types, including cancer cells. There are several types of these ion channels, but here we address those formed by assembly of transient receptor potential canonical (TRPC) proteins, particularly those which involve two closely related members of the family: TRPC4 and TRPC5. We focus on these proteins because recent studies point to roles in important aspects of cancer: drug resistance, transmission of drug resistance through extracellular vesicles, tumour vascularisation, and evoked cancer cell death by the TRPC4/5 channel activator (−)-englerin A. We conclude that further research is both justified and necessary before these proteins can be considered as strong targets for anti-cancer cell drug discovery programmes. It is nevertheless already apparent that inhibitors of the channels would be unlikely to cause significant adverse effects, but, rather, have other effects which may be beneficial in the context of cancer and chemotherapy, potentially including suppression of innate fear, visceral pain and pathological cardiac remodelling

Data mining of high density genomic variant data for prediction of Alzheimer's disease risk

<p>Abstract</p> <p>Background</p> <p>The discovery of genetic associations is an important factor in the understanding of human illness to derive disease pathways. Identifying multiple interacting genetic mutations associated with disease remains challenging in studying the etiology of complex diseases. And although recently new single nucleotide polymorphisms (SNPs) at genes implicated in immune response, cholesterol/lipid metabolism, and cell membrane processes have been confirmed by genome-wide association studies (GWAS) to be associated with late-onset Alzheimer's disease (LOAD), a percentage of AD heritability continues to be unexplained. We try to find other genetic variants that may influence LOAD risk utilizing data mining methods.</p> <p>Methods</p> <p>Two different approaches were devised to select SNPs associated with LOAD in a publicly available GWAS data set consisting of three cohorts. In both approaches, single-locus analysis (logistic regression) was conducted to filter the data with a less conservative p-value than the Bonferroni threshold; this resulted in a subset of SNPs used next in multi-locus analysis (random forest (RF)). In the second approach, we took into account prior biological knowledge, and performed sample stratification and linkage disequilibrium (LD) in addition to logistic regression analysis to preselect loci to input into the RF classifier construction step.</p> <p>Results</p> <p>The first approach gave 199 SNPs mostly associated with genes in calcium signaling, cell adhesion, endocytosis, immune response, and synaptic function. These SNPs together with <it>APOE and GAB2 </it>SNPs formed a predictive subset for LOAD status with an average error of 9.8% using 10-fold cross validation (CV) in RF modeling. Nineteen variants in LD with <it>ST5, TRPC1, ATG10, ANO3, NDUFA12, and NISCH </it>respectively, genes linked directly or indirectly with neurobiology, were identified with the second approach. These variants were part of a model that included <it>APOE </it>and <it>GAB2 </it>SNPs to predict LOAD risk which produced a 10-fold CV average error of 17.5% in the classification modeling.</p> <p>Conclusions</p> <p>With the two proposed approaches, we identified a large subset of SNPs in genes mostly clustered around specific pathways/functions and a smaller set of SNPs, within or in proximity to five genes not previously reported, that may be relevant for the prediction/understanding of AD.</p

TRPC5 ion channel permeation promotes weight gain in hypercholesterolaemic mice

Transient Receptor Potential Canonical 5 (TRPC5) is a subunit of a Ca2+-permeable non-selective cationic channel which negatively regulates adiponectin but not leptin in mice fed chow diet. Adiponectin is a major anti-inflammatory mediator and so we hypothesized an effect of TRPC5 on the inflammatory condition of atherosclerosis. Atherosclerosis was studied in aorta of ApoE−/− mice fed western-style diet. Inhibition of TRPC5 ion permeation was achieved by conditional transgenic expression of a dominant negative ion pore mutant of TRPC5 (DNT5). Gene expression analysis in adipose tissue suggested that DNT5 increases transcript expression for adiponectin while decreasing transcript expression of the inflammatory mediator Tnfα and potentially decreasing Il6, Il1β and Ccl2. Despite these differences there was mild or no reduction in plaque coverage in the aorta. Unexpectedly DNT5 caused highly significant reduction in body weight gain and reduced adipocyte size after 6 and 12 weeks of western-style diet. Steatosis and circulating lipids were unaffected but mild effects on regulators of lipogenesis could not be excluded, as indicated by small reductions in the expression of Srebp1c, Acaca, Scd1. The data suggest that TRPC5 ion channel permeation has little or no effect on atherosclerosis or steatosis but an unexpected major effect on weight gain

Present state and future perspectives of using pluripotent stem cells in toxicology research

The use of novel drugs and chemicals requires reliable data on their potential toxic effects on humans. Current test systems are mainly based on animals or in vitro–cultured animal-derived cells and do not or not sufficiently mirror the situation in humans. Therefore, in vitro models based on human pluripotent stem cells (hPSCs) have become an attractive alternative. The article summarizes the characteristics of pluripotent stem cells, including embryonic carcinoma and embryonic germ cells, and discusses the potential of pluripotent stem cells for safety pharmacology and toxicology. Special attention is directed to the potential application of embryonic stem cells (ESCs) and induced pluripotent stem cells (iPSCs) for the assessment of developmental toxicology as well as cardio- and hepatotoxicology. With respect to embryotoxicology, recent achievements of the embryonic stem cell test (EST) are described and current limitations as well as prospects of embryotoxicity studies using pluripotent stem cells are discussed. Furthermore, recent efforts to establish hPSC-based cell models for testing cardio- and hepatotoxicity are presented. In this context, methods for differentiation and selection of cardiac and hepatic cells from hPSCs are summarized, requirements and implications with respect to the use of these cells in safety pharmacology and toxicology are presented, and future challenges and perspectives of using hPSCs are discussed

Benchmarking computational methods for B-cell receptor reconstruction from single-cell RNA-seq data

Multiple methods have recently been developed to reconstruct full-length B-cell receptors (BCRs) from single-cell RNA sequencing (scRNA-seq) data. This need emerged from the expansion of scRNA-seq techniques, the increasing interest in antibody-based drug development and the importance of BCR repertoire changes in cancer and autoimmune disease progression. However, a comprehensive assessment of performance-influencing factors such as the sequencing depth, read length or number of somatic hypermutations (SHMs) as well as guidance regarding the choice of methodology is still lacking. In this work, we evaluated the ability of six available methods to reconstruct full-length BCRs using one simulated and three experimental SMART-seq datasets. In addition, we validated that the BCRs assembled in silico recognize their intended targets when expressed as monoclonal antibodies. We observed that methods such as BALDR, BASIC and BRACER showed the best overall performance across the tested datasets and conditions, whereas only BASIC demonstrated acceptable results on very short read libraries. Furthermore, the de novo assembly-based methods BRACER and BALDR were the most accurate in reconstructing BCRs harboring different degrees of SHMs in the variable domain, while TRUST4, MiXCR and BASIC were the fastest. Finally, we propose guidelines to select the best method based on the given data characteristics