Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage.
Hi-C implementation of genome structure for in silico models of radiation-induced DNA damage.
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DOI：
10.1371/journal.pcbi.1008476
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发表时间：
2020-12
影响因子：
4.3
通讯作者：
Merchant MJ
中科院分区：
文献类型：
--
作者：
Ingram SP;Henthorn NT;Warmenhoven JW;Kirkby NF;Mackay RI;Kirkby KJ;Merchant MJ
基因组组织领域的发展导致了最近的方法，直接从实验测量的基因组接触（Hi-C数据）推断基因组的空间构象。这提供了染色体内和染色体间排列的详细描述。染色体混杂是辐射诱导DNA错误修复的重要驱动因素。这是一个与癌症治疗（放射治疗）、公共卫生（生物剂量测定）和太空旅行领域相关的关键生物学终点。我们首次利用这些推断基因组组织的方法，并将其与纳米剂量学辐射轨迹结构建模相结合，以预测细胞类型特定几何形状内DNA损伤的数量和分布。这些纳米剂量模拟高度依赖于几何形状，并受益于包含实验驱动的染色体构象。我们展示了Hi-C契约图的变化如何影响推断的几何形状，从而导致染色体混合的显着差异。我们展示了这些差异如何传播到整个细胞核中DNA损伤分布的显著变化，表明DNA修复保真度和随后的细胞命运的含义。我们认为细胞类型之间染色体几何聚类的差异是导致细胞放射敏感性变化的合理因素。此外，我们研究了细胞形状的变化，如变平，并表明这极大地影响了DNA损伤的分布。在比较体外结果和体内系统时应考虑到这一点。当试图将体外实验水平的辐射敏感性测量转化为患者或人体水平时，这种效应可能特别重要。我们已经使用了一种技术，使我们能够了解我们的部分DNA是如何在细胞核内组织的。这项技术之前已经显示了不同细胞类型之间组织结构的差异。在这项研究中，我们表明，当暴露于辐射中时，这些差异会使我们的DNA受损的方式发生重大变化。了解这一点很重要，因为我们治疗癌症的主要方法之一是使用放射治疗。然而，当我们试图用辐射治疗癌症时，一些健康组织也会受到辐射。正是对健康组织的辐射限制了我们可以安全地对癌症进行多少辐射而不会对患者造成严重的副作用。为了知道我们可以给予多少辐射，随着时间的推移，我们已经了解了通常可以给予健康组织的安全辐射量。即便如此，有时患者仍然会有比我们预测的更严重的副作用。如果我们想进一步改善我们的治疗和患者安全，我们需要更好地了解每个患者的安全限度是如何变化的。完全理解这一过程的第一步是更好地理解不同类型的细胞如何受到辐射的影响，辐射在一定程度上是由DNA组织驱动的，这在这项工作中得到了体现。
Developments in the genome organisation field has resulted in the recent methodology to infer spatial conformations of the genome directly from experimentally measured genome contacts (Hi-C data). This provides a detailed description of both intra- and inter-chromosomal arrangements. Chromosomal intermingling is an important driver for radiation-induced DNA mis-repair. Which is a key biological endpoint of relevance to the fields of cancer therapy (radiotherapy), public health (biodosimetry) and space travel. For the first time, we leverage these methods of inferring genome organisation and couple them to nano-dosimetric radiation track structure modelling to predict quantities and distribution of DNA damage within cell-type specific geometries. These nano-dosimetric simulations are highly dependent on geometry and are benefited from the inclusion of experimentally driven chromosome conformations. We show how the changes in Hi-C contract maps impact the inferred geometries resulting in significant differences in chromosomal intermingling. We demonstrate how these differences propagate through to significant changes in the distribution of DNA damage throughout the cell nucleus, suggesting implications for DNA repair fidelity and subsequent cell fate. We suggest that differences in the geometric clustering for the chromosomes between the cell-types are a plausible factor leading to changes in cellular radiosensitivity. Furthermore, we investigate changes in cell shape, such as flattening, and show that this greatly impacts the distribution of DNA damage. This should be considered when comparing in vitro results to in vivo systems. The effect may be especially important when attempting to translate radiosensitivity measurements at the experimental in vitro level to the patient or human level. We have used a technique which allows us to understand how parts of our DNA are organised within a cell nucleus. This technique has previously shown differences in the organisation between different cell-types. In this study, we show that these differences produce significant change in the way our DNA is damaged when exposed to radiation. This is important to understand as one of the primary ways we treat cancer is using radiotherapy. However, whilst we attempt to target the cancer with radiation, some healthy tissue also receives radiation. It is the radiation delivered to the healthy tissue which limits how much radiation we can safely give to the cancer without causing significant side effects in patients. To know how much radiation we can give, over time, we have learnt generally safe amounts of radiation that can be given to healthy tissue. Even so, sometimes patients will still have worse side effects than what we would have predicted. If we want to further improve our treatments and patient safety, we need to better understand how this safe limit varies between each patient. The first step in to fully understanding this process comes from a better understanding of how different cell-types are affected by radiation, which is partly driven by DNA organisation, shown in this work.
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