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调控性DNA与蛋白质相互作用的单细胞图谱

Single-cell mapping of regulatory DNA:Protein interactions.

作者信息

Chi Wei-Yu, Yoon Sang-Ho, Mekerishvili Levan, Ganesan Saravanan, Potenski Catherine, Izzo Franco, Landau Dan, Raimondi Ivan

机构信息

Division of Hematology and Medical Oncology, Department of Medicine and Meyer Cancer Center, Weill Cornell Medicine, New York, NY, USA.

New York Genome Center, New York, NY, USA.

出版信息

bioRxiv. 2025 Jan 2:2024.12.31.630903. doi: 10.1101/2024.12.31.630903.

DOI:10.1101/2024.12.31.630903
PMID:39803441
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11722406/
Abstract

Gene expression is coordinated by a multitude of transcription factors (TFs), whose binding to the genome is directed through multiple interconnected epigenetic signals, including chromatin accessibility and histone modifications. These complex networks have been shown to be disrupted during aging, disease, and cancer. However, profiling these networks across diverse cell types and states has been limited due to the technical constraints of existing methods for mapping DNA:Protein interactions in single cells. As a result, a critical gap remains in understanding where TFs or other chromatin remodelers bind to DNA and how these interactions are perturbed in pathological contexts. To address this challenge, we developed a transformative single-cell immuno-tethering DNA:Protein mapping technology. By coupling a species-specific antibody-binding nanobody to a cytosine base editing enzyme, this approach enables profiling of even weak or transient factor binding to DNA, a task that was previously unachievable in single cells. Thus, our Docking & Deamination followed by sequencing (D&D-seq) technique induces cytosine-to-uracil edits in genomic regions bound by the target protein, offering a novel means to capture DNA:Protein interactions with unprecedented resolution. Importantly, this technique can be seamlessly incorporated into common single-cell multiomics workflows, enabling multimodal analysis of gene regulation in single cells. We tested the ability of D&D-seq to record TF binding both in bulk and at the single-cell level by profiling CTCF and GATA family members, obtaining high specificity and efficiency, with clear identification of TF footprint and signal retention in the targeted cell subpopulations. Furthermore, the deamination reaction showed minimal off-target activity, with high concordance to bulk ChIP-seq reference data. Applied to primary human peripheral blood mononuclear cells (PBMCs), D&D-seq successfully identified CTCF binding sites and enabled integration with advanced machine-learning algorithms for predicting 3D chromatin structure. Furthermore, we integrated D&D-seq with single-cell genotyping to assess the impact of mutations on CTCF binding in a human clonal hematopoiesis sample, uncovering altered binding and chromatin co-accessibility patterns in mutant cells. Altogether, D&D-seq represents an important technological advance enabling the direct mapping of TF or chromatin remodeler binding to the DNA in primary human samples, opening new avenues for understanding chromatin and transcriptional regulation in health and disease.

摘要

基因表达由众多转录因子(TFs)协调,这些转录因子与基因组的结合是通过多个相互关联的表观遗传信号来指导的,包括染色质可及性和组蛋白修饰。这些复杂的网络在衰老、疾病和癌症过程中会被破坏。然而,由于现有单细胞DNA:蛋白质相互作用图谱绘制方法的技术限制,在不同细胞类型和状态下对这些网络进行分析一直受到限制。因此,在理解TFs或其他染色质重塑因子与DNA的结合位置以及这些相互作用在病理情况下如何受到干扰方面,仍然存在关键差距。为了应对这一挑战,我们开发了一种变革性的单细胞免疫系链DNA:蛋白质图谱绘制技术。通过将物种特异性抗体结合纳米抗体与胞嘧啶碱基编辑酶偶联,这种方法能够对即使是与DNA的微弱或短暂因子结合进行分析,这是以前在单细胞中无法完成的任务。因此,我们的对接与脱氨后测序(D&D-seq)技术在与目标蛋白结合的基因组区域诱导胞嘧啶到尿嘧啶的编辑,提供了一种以空前分辨率捕获DNA:蛋白质相互作用的新方法。重要的是,该技术可以无缝整合到常见的单细胞多组学工作流程中,实现对单细胞基因调控的多模态分析。我们通过分析CTCF和GATA家族成员,测试了D&D-seq在整体水平和单细胞水平记录TF结合的能力,获得了高特异性和效率,在目标细胞亚群中清晰地识别出TF足迹和信号保留。此外,脱氨反应显示出最小的脱靶活性,与整体ChIP-seq参考数据高度一致。应用于原代人外周血单核细胞(PBMCs)时,D&D-seq成功鉴定了CTCF结合位点,并能够与先进的机器学习算法整合以预测三维染色质结构。此外,我们将D&D-seq与单细胞基因分型整合,以评估突变对人类克隆造血样本中CTCF结合的影响,揭示突变细胞中结合和染色质共可及性模式的改变。总之,D&D-seq代表了一项重要的技术进步,能够直接绘制TF或染色质重塑因子与原代人样本中DNA的结合图谱,为理解健康和疾病中的染色质及转录调控开辟了新途径。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/df6a5764caec/nihpp-2024.12.31.630903v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/e1ac27d0642a/nihpp-2024.12.31.630903v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/c9ec59d0ce00/nihpp-2024.12.31.630903v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/a29f556046aa/nihpp-2024.12.31.630903v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/df6a5764caec/nihpp-2024.12.31.630903v1-f0004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/e1ac27d0642a/nihpp-2024.12.31.630903v1-f0001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/c9ec59d0ce00/nihpp-2024.12.31.630903v1-f0002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/a29f556046aa/nihpp-2024.12.31.630903v1-f0003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/fb30/11722406/df6a5764caec/nihpp-2024.12.31.630903v1-f0004.jpg

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