Epigenome Engineering for Direct Neural Cell Reprogramming

Abstract

The mammalian brain lacks sufficient regenerative capacity to restore neuronal populations lost to brain injury or neurodegeneration. As a result, cell and gene therapies that aim to regenerate neuronal populations have gained significant attention. Direct reprogramming of glial cells to a neuronal state has emerged as a particularly promising approach for generating new neurons. Astrocytes are attractive candidates for neuronal reprogramming due to their shared lineage during neurodevelopment, abundance across brain regions, and latent proliferative potential which can become activated in response to injury or degeneration. However, previous reprogramming approaches have demonstrated mixed efficacy and efficiency, highlighting the need for an expanded toolkit of reprogramming factors and technologies.Here, we establish a CRISPR activation (CRISPRa)-based approach for neuronal reprogramming of primary human astrocytes. We conducted high-throughput CRISPRa screens of all human genes encoding transcription factors (TFs) to identify novel and efficient reprogramming factors. We employ multiple methods including scRNA-seq to characterize top hits and reveal that single TFs reprogram primary human astrocytes towards multiple neuronal subtypes with distinct cell type-specific gene signatures. We demonstrate that INSM1 reprograms astrocytes towards a glutamatergic neuron-like state and has broad neurogenic activity across different cell types and across human and mouse contexts. Finally, we conduct paired CRISPRa screens to identify cofactors that cooperate with INSM1 to enhance neuronal reprogramming and subtype specification and elucidate genomic mechanisms of interaction and downstream regulators.CRISPR-based epigenome engineering approaches are powerful tools for reprogramming cell state and are capable of highly specific single-gene activity. However, some applications of transcriptional network reprogramming require broad, genome-wide effects. Towards this aim, we next utilized our screening and omics datasets to identify a CRISPRa gRNA that is highly effective at reprogramming astrocyte transcriptional state. However, closer analysis revealed that this gRNA achieves this with widespread multi-site activity capable of inducing expression changes in thousands of genes, in contrast to gRNAs targeting neighboring sites and regulating the same target gene. We use this promiscuous gRNA to further study the determinants of gRNA- driven off-target dCas9 binding in the context of transcriptional reprogramming. Employing a combination of ChIP-seq, high-throughput in vitro protein-binding microarrays, and high- throughput screening of gRNA-variant libraries in cells, we demonstrate that critical PAM- proximal bases within the gRNA seed sequence determine genomic binding, that mismatch tolerance varies by gRNA and base residue, and that mutating this PAM-proximal sequence of promiscuous gRNAs can modulate specificity. Finally, we find that CRISPRa-driven phenotypes can result from simultaneous contributions of active off-target effects and dose-dependent on- target activity. These findings highlight the potentially widespread impacts of CRISPRa off-target activity by gRNAs, underscore the need to account for cryptic effects when selecting and evaluating gRNAs for programming cell phenotypes, and demonstrate that multi-site binding in CRISPRa systems, typically viewed as a limitation, can also be exploited as a feature for network-level perturbations in cell reprogramming.Overall, this work expands the list of biological targets and technologies available for neuroregenerative therapies. Specifically, it (1) widely expands the list of potential factors for cell reprogramming-based neuroregenerative therapies, provides new insights into the TF interactions and gene regulatory networks (GRNs) that govern neural cell states, and (2) elucidates mechanisms of gRNA-driven promiscuity in CRISPRa systems and provides proof-of-principle for how they can be creatively exploited to engineer complex cell phenotypes.