| Literature DB >> 35337132 |
Alejandra Daruich1,2, Emilie Picard1, Justine Guégan3, Thara Jaworski1, Léa Parenti1, Kimberley Delaunay1, Marie-Christine Naud1, Marianne Berdugo1, Jeffrey H Boatright4,5, Francine Behar-Cohen1,6.
Abstract
Ursodeoxycholic (UDCA) and tauroursodeoxycholic (TUDCA) acids have shown neuroprotective properties in neurodegenerative diseases, but differential effects of the two bile acids have been poorly explored. The aim of this study was to evaluate the neuroprotective effects of UDCA versus TUDCA in a neuroretinal degeneration model and to compare transcriptionally regulated pathways. The WERI-Rb-1 human cone-like cell line and retinal explants were exposed to albumin and TUDCA or UDCA. Viability, cell death, and microglial activation were quantified. Transcriptionally regulated pathways were analyzed after RNA sequencing using the edgeR bioconductor package. Pre-treatment of cone-like cells with UDCA or TUDCA significantly protected cells from albumin toxicity. On retinal explants, either bile acid reduced apoptosis, necroptosis, and microglia activation at 6 h. TUDCA induced the regulation of 463 genes, whilst 31 genes were regulated by UDCA. Only nineteen common genes were regulated by both bile acids, mainly involved in iron control, cell death, oxidative stress, and cell metabolism. As compared to UDCA, TUDCA up-regulated genes involved in endoplasmic reticulum stress pathways and down-regulated genes involved in axonal and neuronal development. Either bile acid protected against albumin-induced cell loss. However, TUDCA regulated substantially more neuroprotective genes than UDCA.Entities:
Keywords: TUDCA; UDCA; neuroprotection; retina; retinal degeneration; retinal detachment
Year: 2022 PMID: 35337132 PMCID: PMC8955596 DOI: 10.3390/ph15030334
Source DB: PubMed Journal: Pharmaceuticals (Basel) ISSN: 1424-8247
Figure 1UDCA and TUDCA protect from albumin-induced cell death in vitro. (A) The % of viable cones cells decreased with albumin (20 mg/mL) but was higher when cones received 1 µM of UDCA or TUDCA, with only significance for TUDCA. No significantly difference was seen between UDCA and TUDCA. (B) LDH release was increased by albumin. Treatment by UDCA or TUDCA decreased LDH release, with only significance for UDCA. No significant difference was seen between UDCA and TUDCA treatment outcomes. The results are presented as the means ± SEM, n = 4–8, Kruskal–Wallis and Dunn’s multiple comparisons post hoc test (* p < 0.05; ** p < 0.01, *** p < 0.001).
Figure 2UDCA protects from albumin-induced cell death ex vivo. Rat retina explants were treated by albumin 12 mg/mL or albumin and UDCA or TUDCA 10 ng/mL and cultured 6 h. (A) Western blotting quantification. Receptor-interacting protein (RIP)/actin ratio was lower in retinas treated by UDCA or TUDCA, with only significance between for TUDCA vs. albumin. No significant difference was seen between UDCA and TUDCA. (B) Cleaved/pro-Caspase 3 ratio was lower in retinas treated by UDCA or TUDCA with only significance between for UDCA vs. albumin. No significant difference was seen between UDCA and TUDCA. (C) Number of photoreceptors TUNEL + was reduced in retinas treated by UDCA and TUDCA compared to albumin alone, with only significance for TUDCA. No significant difference was seen between UDCA and TUDCA. (D) Round/ramified ionized calcium-binding adapter molecule (IBA1)-positive cells (red) ratio was lower in UDCA or TUDCA-treated retinas, with significance only between for TUDCA vs. Albumin. No significant difference was seen between UDCA and TUDCA (p = 0.2). Scale bars: 100 µm. The results were presented as the means ± SEM, n = 4–8, Kruskal–Wallis and Dunn’s multiple comparisons post hoc test (* p < 0.05; ** p < 0.01, p < 0.001).
Figure 3Nineteen common genes differentially regulated by both UDCA versus albumin and TUDCA versus albumin and gene ontology biological process. Differential analysis was performed on UDCA vs. albumin and TUDCA vs. albumin. Differentially expressed genes were selected with FDR < 0.05 and logFC > 0.5. 19 genes were in common between these two analyses. A network was constructed with StrinDB to connect those genes. Then Enrichr was used to select the most regulated pathways for those genes. Finally, the graph was created with Cytoscape tool.
Figure 4Genes differentially regulated by TUDCA vs. UDCA and main biological pathway. Starting with genes deregulated in TUDCA vs. UDCA, a heatmap was constructed with diverging color scale (red for up-regulated genes and blue for down-regulated genes). Genes (in line) were ordered using Euclidean distance. Two major gene clusters appeared. They were annotated with Enrichr.