Activation of the EGFR/MAPK pathway drives transdifferentiation of quiescent niche cells to stem cells in the Drosophila testis niche.
Adult stem cells are maintained in niches, specialized microenvironments that regulate their self-renewal and differentiation. In the adult Drosophila testis stem cell niche, somatic hub cells produce signals that regulate adjacent germline stem cells (GSCs) and somatic cyst stem cells (CySCs). Hub cells are normally quiescent, but after complete genetic ablation of CySCs, they can proliferate and transdifferentiate into new CySCs. Here we find that Epidermal growth factor receptor (EGFR) signaling is upregulated in hub cells after CySC ablation and that the ability of testes to recover from ablation is inhibited by reduced EGFR signaling. In addition, activation of the EGFR pathway in hub cells is sufficient to induce their proliferation and transdifferentiation into CySCs. We propose that EGFR signaling, which is normally required in adult cyst cells, is actively inhibited in adult hub cells to maintain their fate but is repurposed to drive stem cell regeneration after CySC ablation.
View details for DOI 10.7554/eLife.70810
View details for PubMedID 35468055
PyRosetta Jupyter Notebooks Teach Biomolecular Structure Prediction and Design.
Biophysicist (Rockville, Md.)
2021; 2 (1): 108-122
Biomolecular structure drives function, and computational capabilities have progressed such that the prediction and computational design of biomolecular structures is increasingly feasible. Because computational biophysics attracts students from many different backgrounds and with different levels of resources, teaching the subject can be challenging. One strategy to teach diverse learners is with interactive multimedia material that promotes self-paced, active learning. We have created a hands-on education strategy with a set of sixteen modules that teach topics in biomolecular structure and design, from fundamentals of conformational sampling and energy evaluation to applications like protein docking, antibody design, and RNA structure prediction. Our modules are based on PyRosetta, a Python library that encapsulates all computational modules and methods in the Rosetta software package. The workshop-style modules are implemented as Jupyter Notebooks that can be executed in the Google Colaboratory, allowing learners access with just a web browser. The digital format of Jupyter Notebooks allows us to embed images, molecular visualization movies, and interactive coding exercises. This multimodal approach may better reach students from different disciplines and experience levels as well as attract more researchers from smaller labs and cognate backgrounds to leverage PyRosetta in their science and engineering research. All materials are freely available at https://github.com/RosettaCommons/PyRosetta.notebooks.
View details for DOI 10.35459/tbp.2019.000147
View details for PubMedID 35128343