SCAnDi: Single-cell and single molecule analysis for DNA identification

我们体内的每一个有核细胞都至少包含我们整个基因组的一个拷贝，因此有可能识别我们。无论我们走到哪里，细胞都会脱落，通常是以特定的方式：不同类型的接触会导致不同细胞类型的转移和混合。在来自性侵犯的样本中，回收的细胞和DNA将包括受害者和攻击者的混合物;包括“触摸”DNA样本在内的其他接触将包含来自多个贡献者的细胞和DNA。事实上，在英国刑事司法系统中，高达45%的法医样本含有来自两个或更多个人的人类DNA，通常会阻止成功搜索这些配置文件对DNA databases.The目的是联合收割机的单细胞分离和分析的进步与建立和新的方法进行DNA分析。通常，当从混合样品中回收DNA时，细胞物质被裂解，细胞和非细胞DNA分子被混合，导致关于DNA来源的细胞的形态信息完全丢失。获得细胞起源信息可以在解卷积这些样本（特别是高阶混合样本）和归因于DNA来自哪个细胞、如何转移以及由谁转移的背景叙述方面产生关键差异。单细胞基因组学在过去十年中发展迅速。我们现在可以测量单个细胞的遗传多样性，以及细胞“类型”的分子标记，以及细胞形态的显微镜分析。这些技术的进步已经彻底改变了发育和癌症生物学的研究，但在法医学方面仍然很大程度上未被探索。激光捕获显微切割（LCM）以前已被证明适用于去卷积细胞混合物，但分子生物学，基因组学，微流体和成像细胞分选的进步现在提供了分离和分析单个细胞的潜力。在法医环境中，这可以实现：1）获得用于DNA谱分析的单细胞; 2）混合DNA谱的解卷积-其中来自多个个体的DNA /细胞存在于样品中; 3）特定细胞类型与DNA谱的关联（表型或表观遗传/转录组标记）;以及4）从背景DNA中分离细胞DNA。我们的多学科团队将开发单细胞分离和随后的单细胞DNA分析的方法，使用常规和下一代技术。代测序方法，将读数与散装材料上的金标准分析进行基准测试。我们将提供来自单个人类细胞的原理验证数据，包括单一来源细胞的人工混合物以及性交后混合物。我们将证明单细胞分析的能力，以区分单个供体信息从复杂的混合物。此外，我们将展示使用成像细胞分选将细胞类型信息分配给单细胞DNA谱的潜力，再加上细胞类型分类的自动化方法。这些新方法需要原理证明数据来测试和证明它们支持法医调查的能力，但我们预计这项技术的应用将补充传统方法，大大提高情报和法庭证据等信息的可靠性。重要的是，我们将利用这个项目作为利益相关者参与和推广的平台。我们将建立一个由法医从业人员、商业供应商、研究人员以及调查和法律的代表组成的网络，并主办两次面对面的讲习班和额外的双月会议，以确保技术交付始终符合最终用户的需求。该项目还将为我们的实验室之间的样本/数据采集和传输提供一个框架，从而能够访问关键基础设施和能力，以支持可持续的长期社区建设。

Every nucleated cell in our bodies contains at least one copy of our entire genome, and thus has the potential to identify us. We shed cells wherever we go, often in a context specific manner: different types of contact will result in the transfer and mixture of different cell types. In samples derived from sexual assaults, the cells and DNA recovered will include mixtures of the victim(s) and attacker(s); other contacts including 'touch' DNA samples will contain cells and DNA from multiple contributors. Indeed, up to 45% of forensic samples within the UK criminal justice system contain human DNA from two or more individuals, often preventing successful search of these profiles against DNA databases.The aim of this project is to combine advances in single-cell isolation and analysis with established and novel approaches for DNA profiling. Typically when DNA is recovered from a mixed sample, cellular material is lysed and cellular and acellular DNA molecules are mixed, resulting in a complete loss of morphological information about the cell the DNA originated from. Obtaining cell-of-origin information could make a critical difference in deconvoluting these samples - especially higher order mixed samples - and ascribing a contextual narrative as to what cell the DNA came from, how it was transferred and by whom. Single-cell genomics has advanced rapidly over the last decade. We can now measure genetic diversity in individual cells, as well as molecular markers of cell "type" in addition to microscopic analysis of cell morphology. These technological advances have revolutionised studies in developmental and cancer biology but still remain largely unexplored in a forensic context.Laser Capture Microdissection (LCM) has previously been demonstrated to have applicability in deconvoluting cell mixtures, but advances in molecular biology, genomics, microfluidics and imaging cell sorting now offer the potential to isolate and profile individual cells. In a forensic setting this could enable: 1) obtaining single cells for DNA profiling; 2) the deconvolution of mixed DNA profiles - where DNA / cells from multiple individuals are present in a sample; 3) Linkage of specific cell types with DNA profiles (phenotype or epigenetic/transcriptomic markers); and 4) separation of cellular DNA from background DNA.Our multidisciplinary team will develop approaches for single-cell separation and subsequent single-cell DNA profiling using conventional and next-generation sequencing approaches, benchmarking the readout against gold standard profiling on bulk material. We will deliver proof-of-principle data from individual human cells, including artificial mixtures of single-source cells as well as post-coital mixtures. We will demonstrate the capability of single-cell profiling to distinguish individual donor information from complex mixtures. Furthermore, we will demonstrate the potential to assign cell type information to single-cell DNA profiles using imaging cell sorting, coupled with automated approaches for cell-type classification. These novel approaches need proof-of-principle data to test and demonstrate their ability to support forensic investigations, but we anticipate the application of this technology will complement traditional methods to considerably improve the reliability of such information as intelligence and as evidence in court. Critically, we will use this project as a platform for stakeholder engagement and outreach. We will establish a network of forensic practitioners, commercial suppliers, researchers and investigative and legal representatives and host two in-person workshops and additional bi-monthly meetings, to ensure the technical deliveries remain aligned with the needs of end-users. The project will also enable a framework for sample/data acquisition and transfer between our labs, enabling access to critical infrastructure and capability to support sustainable, longer-term community building.