Selected Grantee Publications
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.
TGF-β1 Signaling Is Essential for Tissue Regeneration in the Xenopus Tadpole Tail
Nakamura et al., Biochemical and Biophysical Research Communications. 2021.
https://www.sciencedirect.com/science/article/pii/S0006291X21008731
Amphibians, such as Xenopus tropicalis, exhibit a remarkable capacity for tissue regeneration after traumatic injury. Nakamura et al. show that inhibition of TGF-β1 function prevents tail regeneration in Xenopus tropicalis tadpoles. CRISPR-mediated knock-out (KO) of tgfb1 retards tail regeneration; the phenotype of tgfb1 KO tadpoles can be rescued by injection of tgfb1 mRNA. Cell proliferation, critical for tissue regeneration, is downregulated in tgfb1 KO tadpoles; tgfb1 KO reduces the expression of phosphorylated Smad2/3 (pSmad2/3). These results show that TGF-β1 regulates cell proliferation through the activation of Smad2/3. They propose that TGF-β1 plays a critical role in TGF-β receptor-dependent tadpole tail regeneration in Xenopus. Supported by ORIP (P40OD010997, R24OD030008).