簇大小决定人类细胞中转录工厂的内部结构
Cluster size determines internal structure of transcription factories in human cells
AI总结：
该研究通过构建染色质聚合物模型，发现转录工厂的特化或混合状态主要由簇大小决定，非特异性相互作用随簇增大增强混合效应，调和了矛盾实验结果，还为研究转录变化提供了路径。
摘要：
转录是细胞的基本过程，也是基因表达的第一步。在人类细胞中，转录依赖于包括RNA聚合酶和大量转录因子（TFs）在内的多种蛋白质与染色质的结合。观察结果表明，这些蛋白质倾向于形成被称为转录工厂的大分子簇，其形态和组成仍存在争议。一些显微镜实验揭示了特化工厂的存在，这类工厂由相似的转录因子组成，负责转录相关基因家族；而测序实验则认为混合簇可能更为普遍，因为大量不同的转录因子会非特异性地结合同一染色质区域。特化工厂或混合工厂形成的潜在机制仍不明确。为了找到这类机制，我们在此开发了一个染色质聚合物模型，用于模拟不同类型转录因子复合物与染色质的结合-解离动力学。令人惊讶的是，特化（即分层分离的）和混合簇都会自发形成，而具体形成哪一种类型主要取决于簇的大小。促进混合的机制是染色质与蛋白质之间非特异性相互作用的存在，这种相互作用会随着簇的增大而变得愈发重要。我们在简单聚合物模型和更符合实际的人类染色体模型中都观察到了这一结果，它调和了看似矛盾的实验结论。此外，我们还展示了引入不同类型的转录因子如何强烈影响转录网络的形成，为研究基因编辑或自然发生突变后的转录变化提供了途径。
英文摘要：
Transcription is a fundamental cellular process, and the first step of gene expression. In human cells, it depends on the binding to chromatin of various proteins, including RNA polymerases and numerous transcription factors (TFs). Observations indicate that these proteins tend to form macromolecular clusters, known as transcription factories, whose morphology and composition is still debated. While some microscopy experiments have revealed the presence of specialised factories, composed of similar TFs transcribing families of related genes, sequencing experiments suggest instead that mixed clusters may be prevalent, as a panoply of different TFs binds promiscuously the same chromatin region. The mechanisms underlying the formation of specialised or mixed factories remain elusive. With the aim of finding such mechanisms, here we develop a chromatin polymer model mimicking the chromatin binding-unbinding dynamics of different types of complexes of TFs. Surprisingly, both specialised (i.e., demixed) and mixed clusters spontaneously emerge, and which of the two types forms depends mainly on cluster size. The mechanism promoting mixing is the presence of non-specific interactions between chromatin and proteins, which become increasingly important as clusters become larger. This result, that we observe both in simple polymer models and more realistic ones for human chromosomes, reconciles the apparently contrasting experimental results obtained. Additionally, we show how the introduction of different types of TFs strongly affects the emergence of transcriptional networks, providing a pathway to investigate transcriptional changes following gene editing or naturally occurring mutations.
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