Abstract
Purpose :
Cell replacement holds promise for anatomical and functional restoration and rejuvenation of damaged and aged organs. Current animal studies show that only a small fraction of donor cells can successfully integrate into the host tissues and recapitulate the normal developmental trajectory, which includes survival, migration, differentiation, maturation, specialization, and functional activity. The aim of this study is to develop a sequencing and computational approach capable of identifying key intrinsic and extrinsic factors to be modulated in the transplantation setting by designing optimal computational models for these functions.
Methods :
We used several RNAseq datasets, including grafted retinal pigment epithelium, dopaminergic neurons, retinal organoids, retinal ganglion cells and data from cultured and grafted Crx-tdTomato+ H9 human ESC-derived organoids of day 134. We generate the computational bash-, R-, and Python-dependent pipeline for: 1) pseudo-time- and cell-fates- based approaches, splicing score; 2) ForceAtlas2 3D (2D + Z-function of interest) approach for biologically relevant dimensionality reduction; 3) cell-cell interactions pipeline, based on cell type and single-cell resolution to identify conservative and unique extrinsic factors (CellChat, Scriabin). We subset the cone population out of the dataset to perform the RNA Velocity and scFates analysis on the ForceAtlas2-projected graph.
Results :
Our analysis showed several patterns of changes that cones undergo upon grafting. We identified three transitionary states for the cultured cells, and four to be present in the transplanted group. We observe transcriptomic changes for the studied groups upon their pseudotime- and latent time-ranked maturation, where the maturation driving genes upon transplantation are SAT1, OPN1LW, ARR3, GUCA1C, TFPI2, RELN, GNB1, PCAT4, SMIM40, and GNAT1.
Conclusions :
We developed a new strategy for transcriptomics data analysis focusing on identifying the intrinsic and extrinsic drivers of donor cell maturation. Those include early and late cell fate decision drivers, ligands, receptors, and transcriptional factors. Together, the GHOST-seq approach holds the promise of improving the transplantation outcome by modifying the donor cells and microenvironment before, during, and upon transplantation.
This abstract was presented at the 2024 ARVO Annual Meeting, held in Seattle, WA, May 5-9, 2024.