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Ameur, S.

Publications and source records attributed to Ameur, S..

2 recordsLinked to original sources

Single-Cell Multimodal Profiling Reveals Maternal Diabetes-Nkx2-5 Interaction in Congenital Heart Disease in a Genetic Model Recapitulating Human Embryopathies

The etiological complexity of congenital heart disease (CHD) arises from the interaction between genetic and environmental factors. We hypothesized that environmental exposure could potentiate a genetic susceptibility, leading to an increased incidence of specific cardiac defects. To test this hypothesis, we used betaV59M+ female mice exhibiting severe hyperglycemia (>28 mmol/L) without dyslipidemia, a model we characterized that faithfully recapitulates human diabetic embryopathy. These females were crossed with males haploinsufficient for Nkx2-5, a transcription factor essential for cardiac development and implicated in human CHD. Our results show that the combination of genetic susceptibility and a hyperglycemic maternal environment (GxE) leads to a higher frequency and severity of cardiac malformations, including ventricular septal defects specifically involving the muscular septum, univentricular morphologies, and dilation with thinning of the myocardium. These structural abnormalities were associated with transcriptional changes affecting the contractile identity of the chamber myocardium. Single-nucleus multiomic profiling (snRNA-seq and snATAC-seq) of the E9.5 cardiac region revealed that the interaction between maternal diabetes and Nkx2-5 haploinsufficiency profoundly reshapes transcriptional and chromatin accessibility landscapes. These changes affect not only metabolic pathways, but also cell cycle progression in second heart field (SHF) progenitors, likely contributing to the observed structural cardiac defects. Multiomic integration further identifies a disrupted indirect Nkx2-5-Aldh1a2 regulatory axis in posterior SHF progenitors, while demonstrating that maternal diabetes selectively affects a restricted subset of Nkx2-5-dependent regulatory elements associated with cardiomyocyte maturation. Our findings establish a comprehensive single-cell multiomic resource that will facilitate the integration of human GWAS and other genomic datasets, enabling the identification and functional interpretation of disease-associated loci.

developmental biology↗

Multiplex imaging combined to machine learning enable automated profiling of cortical malformations applications in tuberous sclerosis complex

Malformations of cortical development such as tuberous sclerosis complex arise within a heterogeneous cellular landscape that conventional histopathology only partially resolves. Here, we combined a 19-marker multiplex immunofluorescence panel with a machine learning-driven image analysis pipeline to map and quantify over 365 000 cells from paediatric surgical cortex, defining the single-cell architecture of TSC lesions. Microtubers were objectively delineated by vimentin and detected in all TSC samples but absent from non-dysplastic controls. Within these structures, balloon cells exhibiting strong pS6 activation occupied lesion cores and were confined to microtuber boundaries, whereas dysmorphic neurons were more diffusely distributed into adjacent cortex. The microtuber niche was dominated by astroglial remodeling: immature and reactive vimentin-positive astrocytes, including Lamp5-positive subsets, accumulated at and around lesion rims, while mature GFAP-positive astrocytes showed only modest changes. Distance-based spatial analyses revealed neuronal exclusion from microtuber centres with gradual recovery in surrounding tissue, indicating local network disruption. Unsupervised clustering and niche modelling recapitulated these spatial gradients, identifying a glial-dominated ecosystem that concentrates balloon cells, increases inter-neuronal distances, and reduces cell-cell interactions. Together, these data support a model in which cortical tubers arise through the coalescence of microtubers orchestrated by balloon cells and reactive gliosis during corticogenesis. Beyond elucidating disease architecture, our automated framework enables reproducible lesion detection, quantitative cell-state mapping, and spatial readouts applicable across malformations of cortical development. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=126 SRC="FIGDIR/small/690101v1_ufig1.gif" ALT="Figure 1"> View larger version (57K): org.highwire.dtl.DTLVardef@dc3258org.highwire.dtl.DTLVardef@6d4149org.highwire.dtl.DTLVardef@d93354org.highwire.dtl.DTLVardef@1b8f83d_HPS_FORMAT_FIGEXP M_FIG C_FIG

neuroscience↗