Search bioRxiv⌕ Search
Home/Archive/bioRxiv

bioRxiv · 10.64898/2026.11.04.764078

Prenatal THC exposure alters metabolic gene expression and KEAP1 regulation in the mouse placental labyrinth

Sia, E.·Gobira, P. H.·Chen, F.·Sezer, G.·Muller, H. K.·Joca, S.·Cruceanu, C.·Grassi-Oliveira, R.
View original source ↗Export metadata ↓

Abstract

Introduction: Prenatal cannabinoid exposure may influence fetal development through changes in placental biology, yet its effects on metabolic gene regulation remain poorly understood. We examined the effects of {Delta}9-tetrahydrocannabinol (THC) and cannabidiol (CBD) on the mouse placental labyrinth zone. Methods: Pregnant C57BL/6JRj mice received THC (5 mg/kg), CBD (5 mg/kg), or vehicle daily by intraperitoneal injection from gestational day 5 to 17.5. Targeted NanoString profiling and pathway analysis were combined with RT-qPCR and protein measurements. Results: THC exposure reduced glutaminase (Gls), Kelch-like ECH-associated protein 1 (Keap1), and FMS-like tyrosine kinase 3 (Flt3) expression (false discovery rate = 0.0904 for each). Pathway analysis identified transcriptional changes in the nine-gene arginine-metabolism set (false discovery rate = 0.0527). No genes or pathways met the significance criteria following CBD exposure. RT-qPCR confirmed lower Keap1 expression with sexes pooled and identified lower Gls and Flt3 expression in male samples. KEAP1 protein abundance increased despite lower Keap1 mRNA, while nuclear factor erythroid 2-related factor 2 localization and heme oxygenase 1 (Hmox1) expression showed no significant differences. Discussion: These findings identify amino acid metabolic gene expression and KEAP1 regulation as complementary components of the placental response to prenatal THC exposure, connecting transcriptional changes with protein regulation within the placental exchange region.

Explore related subjects

developmental biologyPreprint

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Sia, E., Gobira, P. H., Chen, F., Sezer, G., Muller, H. K., Joca, S., Cruceanu, C., Grassi-Oliveira, R.. 2026-11-06. Prenatal THC exposure alters metabolic gene expression and KEAP1 regulation in the mouse placental labyrinth. https://doi.org/10.64898/2026.11.04.764078

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

bioRxiv2026

Mutually Repressive Transcription Factors Drive Intestinal Maturation for Weaning

In mammals, rapid neonatal growth depends on specialized intestinal enterocytes that absorb nutrients from milk. These cells exhibit distinct functions, morphologies, and gene expression programs that support neonatal nutrition before transitioning to an adult state at weaning. However, the transcriptional mechanisms that establish neonatal enterocyte identity and coordinate their maturation remain poorly understood. Here we show that the transcription factors BLIMP1 and CASZ1 form a central switch in the timing of enterocyte maturation. While BLIMP1 marks and promotes neonatal enterocytes, CASZ1 is expressed in adult enterocytes and is required for the proper timing of their emergence. Genetic analysis indicates that these neonatal and adult factors are mutually repressive, forming a genetic switch underlying weaning. This regulatory mechanism also controls glucocorticoid-induced maturation, a process relevant to both normal weaning and the clinical use of corticosteroids to promote epithelial maturation in preterm infants. We show that corticosteroids act directly on the intestinal epithelium and require CASZ1 to induce maturation. Together, these findings reveal a transcriptional mechanism that coordinates intestinal epithelial identity with the changing nutritional demands of early life and mediates the response to maturation-promoting hormones.

developmental biology↗
bioRxiv2026

Functional Data Clustering of Filopodia Dynamics

Notch signaling plays a significant role in tissue patterning. During patterning of the fruit fly dorsal thorax peripheral nervous system, basal filopodia extend the spatial range of cell-cell communication, yet it is still unclear how Notch is activated in long range signaling via filopodia interaction. Filopodia undergo dynamic length changes during their lifetime, which could supply the mechanical pulling force required for notch activation. However, their dynamics are often characterized using individual scalar values such as maximum length and extension rate which could obscure more intricate dynamics. Our hypothesis is that signaling filopodia exhibit distinct and recurrent temporal patterns which can be identified by a consideration of their complete lifetime trajectories. Our work analyzes 60 filopodia trajectories at the basal surface of the fly dorsal thorax during patterning. Length profiles were smoothed using cubic B-splines and clustered by first reducing them to their dominant functional principal component followed by the application of various clustering algorithms. We found that 94.29% of the overall trajectory variation is explained by the first four functional principal components which account for variations in maximal length, extension and retraction rate, duration of stationary phase and length fluctuation frequency. Five recurrent temporal profiles (dynamic extension modes) with varying trajectory shapes and physical attributes, were identified using trimmed K-means. These findings demonstrate that whereas the major source of structural variation in filopodia profiles remains the length, extension rate and retraction rate, nontrivial combinations of these create distinct dynamic modes of extension which provide new insight into their length profiles. Our work thus offers a quantitative framework for future research connecting filopodia dynamic extension modes to productive Notch activation.

developmental biology↗
bioRxiv2026

SOPSim: A cell vertex-based application for simulating sensory bristle patterning with dynamic filopodia

Repeating patterns, such as the bristles on the thorax of fruit flies developed from sensory organ precursor (SOP) cells, play important roles in the lives of flies as they are connected to the central nervous system and help detect environmental cues and threats. Notch signaling is known to regulate the formation of these patterns. Primarily, Notch signaling involves local communication between neighboring cells in direct contact (apical or junctional interaction). However, this short-range interaction alone cannot fully explain the complex biological patterns observed. Further studies have revealed long-range communication between cells through actin-based protrusions known as filopodia. The precise understanding of how the dynamics of filopodia, such as protrusion and retraction, lead to Notch-Delta activation remains unclear, which limits our ability to fully comprehend the mechanisms underlying cell fate decisions and the emergence of spatially organized patterns during tissue development and regeneration. In this study, we extend the modeling framework for Notch signaling by incorporating a filopodia dynamics model driven by myosin-mediated contraction. We address existing gaps by defining criteria under which any given pair of filopodia will physically intersect. We also introduce the local sensory area (LSA), a metric for quantifying local SOP spacing, and use experimental data to calibrate a Notch threshold that distinguishes SOP from epithelial cells. Through numerical simulations, we confirm that long-range communication via filopodia is essential for reproducing the refined patterns observed in vivo. Additionally, we explore how filopodia length, lifetime, and orientation influence the spatial organization of SOP cells. To this end, a Python library has been developed which allows users to perform simulations of Notch Delta signaling via a (1) Graphical User Interface/website, local to the user's computer, (2) via commands in the command line interface, or (3) by calling the simulation using a function via a Python API. This library allows users without computational expertise to easily specify a small number of input parameters and generate simulations of the model.

developmental biology↗