Approaches for engineering transcriptional state of fibroblasts and other differentiated cell types

The National Institutes of Health National Human Genome Research Institute awarded Sloan-Kettering Institute for Cancer Research $1,579,478 on September 19, 2025, under the Human Genome Research program (CFDA 93.172) to develop experimental and computational tools that extend perturb-seq into a platform for engineering cellular transcriptional states.

The project aims to transform perturb-seq into a rational tool for reconstructing diverse transcriptional states in vitro using combinatorial genetic perturbations, with initial focus on fibroblasts—a cell type exhibiting extensive transcriptional heterogeneity linked to tissue homeostasis, wound healing, and disease. The research addresses a gap in cell atlas studies by moving beyond observational mapping toward functional understanding of how transcriptional states are established and whether they confer specific properties. Three complementary approaches will be pursued: Aim 1 will establish an iterative selection strategy for reconstructing states when a cell surface marker is known, targeting reconstruction of a universal fibroblast state in vitro using ordered combinations of CRISPRi/a perturbations. Aim 2 will develop multiomic perturb-seq to test whether perturbation-induced chromatin remodeling can predict synergistic effects. Preliminary CRISPRa perturb-seq screens identified perturbations inducing physiological transcription factor levels and gene programs resembling in vivo fibroblast states, establishing method feasibility.

Performance occurs in New York, New York, with a period of performance through August 31, 2029.

Abstract

The overarching goal of this proposal is to transform perturb-SEQ into a platform for rationally engineering cellular transcriptional states. We are motivated by ongoing cell atlas projects, which have revealed remarkable diversity in the form of hundreds of distinct cell types, but also highlighted that even greater heterogeneity exists at the level of transcriptional states within tissues and across disease contexts. However, these observational studies leave open the questions of how these diverse transcriptional states are established and whether they confer specific functional properties. Answering these questions in vivo is labor-intensive due to the rarity and number of states. To address this GAP, we pursue a complementary approach, developing a combination of experimental and computational tools that extend perturb-SEQ to enable systematic reconstruction of these states in vitro using combinatorial genetic perturbations. We will focus on fibroblasts, a cell type with extensive transcriptional heterogeneity linked to their diverse roles in tissue homeostasis, wound healing, and disease. Our preliminary data from crispra perturb-SEQ screens identified perturbations that induced physiological levels of relevant transcription factors and that elicited gene programs resembling in vivo fibroblast states, supporting the feasibility of our method. We will develop three complementary approaches to transform perturb-SEQ into a tool for engineering cell states: aim 1 will establish an iterative selection strategy suitable for reconstructing states when a cell surface marker is known. We apply IT to realizing an interesting universal fibroblast state in vitro using ordered combinations of crispri/a perturbations. Aim 2 will develop and apply multiomic perturb-SEQ to test the hypothesis that perturbation-induced chromatin remodeling can predict synergistic gene combinations genome-wide, yielding a biologically grounded approach for choosing which combinations of perturbations to prioritize. Aim 3 will produce innsight, an invertible neural network that learns the manifold of reachable fibroblast transcriptional states, removes technical confounders, and enables rational experiment design from perturb-SEQ data. The innovation of our approach lies in the use of crispra to perform nuanced perturbations, our development of novel technological extensions of perturb-SEQ, our focus on developing principles for efficient, biased exploration of possible combinatorial perturbations, and the development of innsight, a model that can provably disentangle independent sources of transcriptional variation. The project is significant because IT will (1) enable in vitro models of in vivo transcriptional states, facilitating the study of their regulation and functional properties; (2) enhance our understanding of the transcriptional heterogeneity of fibroblasts, a major current area of research in cancer and autoimmune disease; and (3) establish principles for the rational engineering of transcriptional state in differentiated cell types that are directly relevant to engineering cell therapies.