单细胞水平组蛋白修饰图谱分析以深入了解表观遗传药物治疗对肿瘤细胞的影响

Epigenomic remodeling, such as changes in chromatin state, plays a crucial role in cancer biology by regulating gene expression changes that drive tumor progression, immune evasion, and the evolution of therapeutic resistance. Popular methods to study the epigenome include assay for transposase-accessible chromatin with sequencing (ATAC-seq) and chromatin immunoprecipitation sequencing (ChIP-seq). ATAC-seq only profiles open chromatin, missing critical details about the nature of accessible regions or silenced chromatin. ChIP-seq and its newer relative, cleavage under targets and tagmentation (CUT&Tag), provide more detailed information on chromatin states by targeting histone modifications with specific antibodies. ChIP-seq requires 10 6 cells to generate meaningful data-too high for precious samples. CUT&Tag offers higher sensitivity with 10-100x lower input and a significantly simplified workflow. When studying epigenetic changes in cancer, it is widely accepted that single-cell resolution is essential, given the complexity and heterogeneity of tumors and their microenvironment. Hence, there is a high demand to convert current epigenetic assays from bulk to single-cell resolution. In CUT&Tag, DNA is tagmented with a protein A/G-Tn5 fusion enzyme, which inserts sequencing adapters in situ for cell-specific labeling-enabling single-cell resolution. Some labs have experimented with single-cell CUT&Tag (scCUT&Tag), but here we present a novel, ready-to-use, validated method for automated, high-throughput scCUT&Tag. To assess drug induced changes in acetylation, we profiled H3K27ac patterns in thousands of single cells from a lung cancer cell line (A549 WT and A549 p53 KO) before and after epigenetic treatment (decitabine + panabinistat vs DMSO control).We observed global cell-type-specific acetylation in response to epigenetic therapy in both A549 WT and A549 p53 KO cells. When comparing scCUT&Tag data with single-cell total RNA-seq data we found that increased acetylation at gene promoters and enhancers correlated with increased gene expression, corroborating the observed changes in histone modification. In summary, the validated scCUT&Tag method provides a high-throughput, automated approach to identify genes regulated in response to epigenetic drug treatment of tumor cells at the single-cell level. Integrating this single-cell expression data provides deeper insight into cellular regulation, particularly in the context of drug responses in tumor cells.