Selected Grantee Publications
Plural Molecular and Cellular Mechanisms of Pore Domain KCNQ2 Encephalopathy
Abreo et al., eLife. 2025.
https://pmc.ncbi.nlm.nih.gov/articles/PMC11703504
This study investigates the cellular and molecular mechanisms underlying KCNQ2 encephalopathy, a severe type of early-onset epilepsy caused by mutations in the KCNQ2 gene. Researchers describe a case study of a child with a specific KCNQ2 gene mutation, G256W, and found that it disrupts normal brain activity, leading to seizures and developmental impairments. Male and female Kcnq2G256W/+ mice have reduced KCNQ2 protein levels, epilepsy, brain hyperactivity, and premature deaths. As seen in the patient study, ezogabine treatment rescued seizures in mice, suggesting a potential treatment avenue. These findings provide important insights into KCNQ2-related epilepsy and highlight possible therapeutic strategies. Supported by ORIP (U54OD020351, S10OD026804, U54OD030187), NCI, NHLBI, NICHD, NIGMS, NIMH, and NINDS.
Profiling Development of Abdominal Organs in the Pig
Gabriel et al., Scientific Reports. 2022.
https://www.doi.org/10.1038/s41598-022-19960-5
The pig is a model system for studying human development and disease due to its similarities to human anatomy, physiology, size, and genome. Moreover, advances in CRISPR gene editing have made genetically engineered pigs a viable model for the study of human pathologies and congenital anomalies. However, a detailed atlas illustrating pig development is necessary for identifying and modeling developmental defects. Here, the authors describe normal development of the pig abdominal system (i.e., kidney, liver, pancreas, spleen, adrenal glands, bowel, gonads) and compare them with congenital defects that can arise in gene-edited SAP130 mutant pigs. This atlas and the methods described here can be used as tools for identifying developmental pathologies of the abdominal organs in the pig at different stages of development. Supported by ORIP (U42OD011140), NHLBI, NIAID, NIBIB, NICHD, and NINDS.
Deep Learning Is Widely Applicable to Phenotyping Embryonic Development and Disease
Naert et al., Development. 2021.
https://pubmed.ncbi.nlm.nih.gov/34739029/
Genome editing simplifies the generation of new animal models for congenital disorders. The authors illustrate how deep learning (U-Net) automates segmentation tasks in various imaging modalities. They demonstrate this approach in embryos with polycystic kidneys (pkd1 and pkd2) and craniofacial dysmorphia (six1). They provide a library of pre-trained networks and detailed instructions for applying deep learning to datasets and demonstrate the versatility, precision, and scalability of deep neural network phenotyping on embryonic disease models. Supported by ORIP (P40OD010997, R24OD030008), NICHD, NIDDK, and NIMH.