Taste receptor T1R1/T1R3 promotes the tumoricidal activity of hepatic CD49a+ CD49b- natural killer cells

Phytochemicals and Inflammation: Is Bitter Better?

The taste of a herb influences its use in traditional medicine. A molecular basis for the taste-based patterns ruling the distribution of herbal (ethno) pharmacological activities may not be excluded. This study investigated the potential correlations between the anti-inflammatory activity (AIA) and the phytocompound taste and/or its chemical class. The study relies on information gathered by an extensive literature (articles, books, databases) search and made public as PlantMolecularTasteDB. Out of a total of 1527 phytotastants with reliably documented taste and structure available in PlantMolecularTasteDB, 592 (for each of which at least 40 hits were found on PubMed searches) were included in the statistical analysis. A list of 1836 putative molecular targets of these phytotastants was afterwards generated with SwissTargetPrediction tool. These targets were systematically evaluated for their potential role in inflammation using an international databases search. The correlations between phytochemical taste and AIA, between chemical class and AIA, and between the taste and the number of inflammation related targets were statistically analyzed. Phytochemical taste may be a better predictor of AIA than the chemical class. Bitter phytocompounds have a higher probability of exerting AIA when compared with otherwise phytotastants. Moreover, bitter phytotastants act upon more inflammation related targets than non-bitter tasting compounds.

Effect of T1R3 Taste Receptor Gene Deletion on Dextran Sulfate Sodium-Induced Colitis in Mice

Taste receptor type 1 member 3 (T1R3) recognize umami or sweet tastes and also contributes type 2 immunity and autophagy in small intestine and muscle cells, respectively. Since imbalance of type 1 and type 2 immunity and autophagy affect intestinal bowel disease (IBD), we hypothesized that T1R3 have a potential role in the incidence and progression of colitis. In the present study, we investigated whether genetic deletion of T1R3 impacted aggravation of DSS-induced colitis in mice. We found that T1R3-KO mice showed reduction in colon damage, including reduced inflammation and colon shrinking relative to those of WT mice following DSS treatment. mRNA expression of tight junction components, particularly claudin1 was significantly lower in T1R3-KO mice with trend to lower inflammation related gene mRNA expression in colon. Other parameters, such as response to microbial stimuli in splenic lymphocytes and peritoneal macrophages, gut microbiota composition, and expression of autophagy-related proteins, were similar between WT and KO mice. Together, these results indicated that deletion of T1R3 has a minor role in intestinal inflammation induced by DSS-induced acute colitis in mice.

Integrating pathway knowledge with deep neural networks to reduce the dimensionality in single-cell RNA-seq data

Background

Single-cell RNA sequencing (scRNA-seq) data provide valuable insights into cellular heterogeneity which is significantly improving the current knowledge on biology and human disease. One of the main applications of scRNA-seq data analysis is the identification of new cell types and cell states. Deep neural networks (DNNs) are among the best methods to address this problem. However, this performance comes with the trade-off for a lack of interpretability in the results. In this work we propose an intelligible pathway-driven neural network to correctly solve cell-type related problems at single-cell resolution while providing a biologically meaningful representation of the data.

Results

In this study, we explored the deep neural networks constrained by several types of prior biological information, e.g. signaling pathway information, as a way to reduce the dimensionality of the scRNA-seq data. We have tested the proposed biologically-based architectures on thousands of cells of human and mouse origin across a collection of public datasets in order to check the performance of the model. Specifically, we tested the architecture across different validation scenarios that try to mimic how unknown cell types are clustered by the DNN and how it correctly annotates cell types by querying a database in a retrieval problem. Moreover, our approach demonstrated to be comparable to other less interpretable DNN approaches constrained by using protein-protein interactions gene regulation data. Finally, we show how the latent structure learned by the network could be used to visualize and to interpret the composition of human single cell datasets.

Conclusions

Here we demonstrate how the integration of pathways, which convey fundamental information on functional relationships between genes, with DNNs, that provide an excellent classification framework, results in an excellent alternative to learn a biologically meaningful representation of scRNA-seq data. In addition, the introduction of prior biological knowledge in the DNN reduces the size of the network architecture. Comparative results demonstrate a superior performance of this approach with respect to other similar approaches. As an additional advantage, the use of pathways within the DNN structure enables easy interpretability of the results by connecting features to cell functionalities by means of the pathway nodes, as demonstrated with an example with human melanoma tumor cells.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13040-021-00285-4.

Biomarker Identification in Membranous Nephropathy Using a Long Non-coding RNA-Mediated Competitive Endogenous RNA Network

PURPOSE

This study was aimed to identify biomarker associated with membranous nephropathy (MN) progression by integration of expression profiles and competitive endogenous RNA (ceRNA) network analysis.

METHODS

The gene (GSE108113) and microRNAs (miRNAs) expression profiles (GSE64306) were downloaded to identify the differentially expressed mRNAs, miRNAs and long non-coding RNAs (lncRNAs) between MN and control groups. The functions and pathways enriched by the differentially expressed mRNAs were analyzed. The mRNA-lncRNA co-expression network was constructed followed by and the ceRNA network construction.

RESULTS

Total 264 upregulated and 196 downregulated differentially expressed mRNAs, 79 upregulated and 4 downregulated lncRNAs, as well as 115 upregulated and 93 downregulated miRNAs were obtained between MN and control groups. After analysis, the differential mRNAs were significantly involved in multiple immune-related processes, and cell proliferation, apoptosis and differentiation processes, as well as pathways of taste transduction and lysosome. Finally, a ceRNA network consisting of 4 mRNAs (EPB41L5, FAM43A, PRKG1 and TTC14), 3 lncRNAs (LINC00052, LINC00641 and N4BP2L2-IT2) and 5 miRNAs (hsa-miR-145-5p, hsa-miR-3605-5p, hsa-miR-148a-3p, hsa-miR-497-5p and hsa-miR-148b-3p) was constructed.

CONCLUSION

Our study indicated dysregulation of immune- and apoptosis-associated functions and taste transduction and lysosome pathways may play important roles in MN progression. Deregulated ceRNAs, such as LINC00052-hsa-miR-145-5p-EPB41L5, LINC00052-hsa-miR-148a-3p-FAM43A and LINC00641-hsa-497-5p-PRKG1, may be associated with MN development.

Loss of the nutrient receptor Tas1R3 reduces atherosclerotic plaque accumulation and hepatic steatosis in ApoE-/- mice

The taste receptor type I (Tas1R) family consists of three G protein-coupled receptors (T1R1, T1R2, and T1R3) that form heterodimers recognizing sweet compounds (T1R2/T1R3) or amino acids (T1R1/T1R3). These receptors are nutrient sensors that facilitate appropriate physiological responses with nutrient availability. However, their contribution to the development of pathologies associated with overnutrition (e.g., atherosclerosis) is unclear. The aim of the present study was to determine if T1R3 deletion would reduce atherosclerotic plaque development in mice. We generated atherosclerotic mice with whole-body deletion of T1R3 by crossing T1R3^-/- mice with ApoE^-/- mice. T1R3^+/+ ApoE^-/- and T1R3^-/- ApoE^-/- mice were maintained on an atherogenic high-fat diet for 8 weeks. Weight gain and food consumption were measured during the 8-week diet. Atherosclerotic lesion development and size were assessed by en face analysis of intact aortas and microscopic analysis of aortic roots. Our results indicate that T1R3 deletion in male and female ApoE^-/- mice reduces aortic atherosclerotic plaque accumulation. Hepatic triglyceride accumulation, which was measured by quantification of oil red O staining, was also reduced in T1R3^-/- mice. While the ablation of T1R3 reduced the final body weight of both males and females by approximately 12%, serum lipids, insulin, and glucose were either unchanged or slightly reduced. Immunoblot analysis of the phosphorylation of p70S6K, an effector of mTORC1, suggests T1R3 ablation reduces mTORC1 activity by approximately 50% in the male livers. Collectively, these findings suggest that the whole-body deletion of T1R3 reduces atherosclerosis and hepatic steatosis in a manner largely independent of the measured effects on whole-body glucose and lipid homeostasis.