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Dallakyan, K.

Publications and source records attributed to Dallakyan, K..

2 recordsLinked to original sources

In utero transduction resolves gut cell lineages and enables conditional gene perturbation in the developing enteric nervous system

How diverse cell lineages emerge and are genetically regulated during organogenesis are central questions in understanding the developmental origins of disease. However, the mouse gut, including its intrinsic enteric nervous system (ENS) derived from migratory neural crest, has remained difficult to experimentally target. Here, we introduce an in utero lentiviral nano-injection strategy that enables early and efficient access to progenitor cells of all major cell types within the developing gut as well as gut-innervating ganglia. Leveraging this approach in combination with DNA barcoding and single cell transcriptomics, we resolve clonal relationships in all gut lineages, including epithelial, neural, immune, and mesenchymal cell types. Clonal coupling between distinct subsets of fibroblasts and either pericytes, mesothelial cells, or interstitial cells of Cajal, suggested a developmental logic whereby the mesenchymal compartment arises from a set of fate-biased progenitors. Yet, mesenchymal regionalization along the anterior-posterior axis establishes early, whereas the ENS displays broad clonal dispersion across gut regions and acquires subsequent regional identities. We further adapted the platform for temporally controlled cell-type specific gene manipulation and, as a proof-of-principle, show that induced expression of the proneural factor Ascl1 biases ENS progenitor cells toward neuronal differentiation. Together, this work provides insights into refined spatiotemporal lineage relationships within a multigerm-layer organ and establishes a broadly applicable in vivo framework for probing gene function during gastrointestinal and neural crest development. SIGNIFICANCEThe gastrointestinal tract comprises diverse cell types originating from all three germ layers and includes the neural crest-derived enteric nervous system (ENS). Progress in defining these lineages and their gene regulation is challenged by the limited experimental access to the developing gut. Here, we establish in utero lentiviral transduction as an efficient approach to resolve clonal lineages and address gene functions in defined gut cell types. We show that mesenchyme assumes positional allocation early and differentiates through fate-restricted progenitors, linking specialized mesenchymal cell types to different fibroblasts. In contrast, the ENS differentiates stochastically and acquires late regional identities. Our study reveals fundamental principles of multi-lineage organogenesis and provides a framework to dissect the contribution of developmental programs to visceral dysfunction.

developmental biology↗

Prediction of cellular morphology change under perturbations with transcriptome-guided diffusion model

Investigating the cell morphology change after perturbations with high-throughput image-based profiling is of growing interest, considering its wide applications in phenotypic drug discovery, including MOA (Mechanism Of Action) prediction, compound bioactivity prediction, and drug repurposing. However, the vast space of chemical and genetic perturbations makes it infeasible to fully explore all the potential perturbations with image-profiling technologies. Consequently, developing a powerful in-silico method to simulate high-fidelity cell morphological response under perturbations can reduce the experiment costs and accelerate drug discovery. Motivated by this, we proposed MorphDiff, a transcriptome-guided latent diffusion model for accurately predicting the cell morphology response to perturbations. We applied MorphDiff to two large-scale datasets, including one drug perturbation and one genetic perturbation cell morphology dataset covering thousands of diverse perturbations. Extensive benchmarking and comparison with baseline methods show the remarkable accuracy and fidelity of MorphDiff in predicting cell morphological changes under unseen perturbations. Furthermore, we explored the utilities of MorphDiff in identifying and retrieving the MOAs of drugs, which is a crucial application in phenotypic drug discovery. With the designed pipeline for MOA retrieval, we demonstrated MorphDiffs capability to boost the retrieval of the drugs MOAs (Mechanism Of Actions) by generating realistic cell morphology profiles. The average MOA retrieval accuracy of MorphDiff-generated morphology is comparable with that of the ground truth cell morphology, and consistently outperforms the baseline method and gene expressionbased retrieval by 29.1% and 9.7% respectively. We also validated that complementary information provided by cell morphology generated by MorphDiff can help discover drugs with dissimilar structures but the same MOAs. In summary, with its strong capabilities in generating high-fidelity cell morphology on unseen perturbations, we envision MorphDiff as a powerful tool in phenotypic drug discovery by accelerating the phenotypic screening of vast perturbation space and improving MOA identification.

cell biology↗