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Kaspar, L.* ; Dony, L.* ; Cruceanu, C.* ; Binder, E.B.* ; Theis, F.J.

Effects of glucocorticoid exposure on gene expression and cell fate specification in cerebral organoids.

Neurosci. App. 2:101038 (2023)
Publ. Version/Full Text DOI
Open Access Gold (Paid Option)
Glucocorticoid hormones and glucocorticoid receptor activation are essential for in utero organ maturation and fetal development [1]. Increased exposure to glucocorticoids during pregnancy, either caused by elevated stress levels or administration of synthetic hormones such as dexamethasone, have been associated with lasting negative effects on the offspring, including on neurodevelopment and psychiatric disease risk [2,3]. The molecular mechanisms mediating these adverse outcomes, however, remain unclear, especially given the challenges of studying human fetal brain development. Using human cerebral organoids, we have previously shown 4 that a 12 hour exposure to dexamethasone leads to activation of the glucocorticoid receptor, and to targeted regulation of differentiation- and maturation- related transcripts. In this study we were interested in further analysing the effects of glucocorticoids on neurogenic processes and cell fate specification. We exposed cerebral organoids to dexamethasone for a prolonged period of time (from day 60 to day 70 of organoid development) and used single cell RNA sequencing (scRNA-seq) to study transcriptional responses to glucocorticoids and neurodevelopmental trajectories. We used MAST to analyze differential gene expression after dexamethasone, and identified robust transcriptional changes in all eight fine-mapped cell clusters (q≤0.05). To identify genes that are reliably regulated by dexamethasone, we aggregated data from organoids generated from two different cell lines and filtered for genes that were significantly up- or down-regulated in both cell lines, maintaining the same directionality. We identified between 55 significantly differentially expressed genes (DEGs) in radial glia cells and 224 significant DEGs in telencephalic neurons (q < 0.05), confirming that a prolonged exposure to glucocorticoids induces a robust and reproducible transcriptional response. Next, by leveraging our whole dataset we identified genes that were most significantly up- or down-regulated between the progenitor cell classes (radial glia and cycling progenitors) and each of the identified neuronal cell classes (dorsal and ventral telencephalic neurons and non-telencephalic neurons) and thus are most likely drivers of cell fate specification during development. Interestingly, when comparing the top 3% of most strongly associated driver genes with dexamethasone-DEGs, we found a significant overlap between the two gene sets, showing that genes that are crucial for neuronal fate specification, are, in part, also regulated by glucocorticoids (approximately 30%, adjusted p ≤ 0.05 ). This indicates that glucocorticoids impact cell fate specification and possibly neuronal composition in the developing brain. Risk for psychiatric disorders is largely conferred by common variants located in non-coding regulatory regions. Given the role of glucocorticoids on cell fate specification we are working on elucidating the specific regulatory elements mediating glucocorticoid-effects on driver genes and thus on cell fate specification, using CAGE-sequencing. By identifying specific glucocorticoids-responsive regulatory elements that affect developmental driver genes expression we can further study the role of psychiatric disorders-associated risk variants located in those and analyse their effects using STARR-sequencing in a cell-type specific way across development. With this work we aim on identifying developmental processes affected by glucocorticoids and associated with risk for psychiatric disorders.
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Publication type Article: Journal article
Document type Meeting abstract
Corresponding Author
ISSN (print) / ISBN 2772-4085
e-ISSN 2772-4085
Journal Neuroscience Applied
Quellenangaben Volume: 2, Issue: , Pages: , Article Number: 101038 Supplement: ,
Publisher Elsevier
Non-patent literature Publications
Reviewing status Peer reviewed
Institute(s) Institute of Computational Biology (ICB)