Spatially resolved high throughput lineage tracing by targeted in situ DNA diversification

通过有针对性的原位 DNA 多样化进行空间分辨高通量谱系追踪

• 批准号: 10196380
• 负责人: Jingyi Fei
• 金额: $ 24.6万
• 依托单位: UNIVERSITY OF CHICAGO
• 依托单位国家: 美国
• 财政年份: 2021
• 资助国家: 美国
• 起止时间: 2021-06-01 至 2023-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10196380
• 关键词: Adult; Bar Codes; Biology; CRISPR/Cas technology; Cell Culture Techniques; Cell Differentiation process; Cell Line; Cell Lineage; Cell division; Cells; Cellular Stress; Cicatrix; Code; Collection; Color; Complex; Consumption; DNA; DNA Modification Process; DNA Sequence; DNA Sequence Alteration; Development; Devices; Double Strand Break Repair; Fluorescent in Situ Hybridization; Generations; Guide RNA; Hela Cells; Hybrids; Image; In Situ; In Situ Hybridization; Individual; Information Retrieval; Inherited; Label; Laboratories; Lead; Mediating; Methods; Mind; Mutation; Outcome; Pattern; Point Mutation; Population; Positioning Attribute; Process; RNA; Reading; Reporter; Resolution; Scientist; Site; Spatial Distribution; Structure; Technology; Tissue Sample; Tissues; Tracer; Transcript; base; biological systems; cell type; cytotoxicity; design; ds-DNA; experimental study; imaging platform; insight; interest; multiplexed imaging; next generation sequencing; nuclease; precise genome editing; programs; promoter; repaired; simulation; tool

Project Summary Cell division and differentiation are fundamental processes in biology. Lineage information for individual cells in an adult represents the missing key to understanding the origins of different cell types and how cells choose certain developmental trajectories. However, lineage tracing, especially that at a high resolution, is technically demanding. We reason that an ideal lineage tracing tool must meet two requirements: (1) a programable recording mechanism with large storage capacity that labels every cell division in a developmental window of interest, and (2) an error-robust readout mechanism that can reveal the lineage labels in individual cells without disrupting their spatial distribution. With these two requirements in mind, we propose to develop a widely applicable tool for spatially resolved single-cell lineage tracing. Our lineage tracing tool constitutes two modular key technologies: targeted in situ DNA diversification for lineaging recording and 2D multiplexed imaging for lineaging reading. To enable dynamic tracing at single-cell resolution, every cell division must be uniquely labeled, and these lineage labels must be stable and inheritable. To this end, we will develop a targeted in situ DNA diversification technology using base editors, which are precise genome-editing agents that introduce C:G to T:A or A:T to G:C transitions in double-stranded DNA. Our simulation suggests that by including 20 editable bases for base editors in a short DNA sequence, a maximum of 300k unique reads can be obtained with 20 generations of unrestricted cell division from a single ancestor cells, reinforcing the large sequence diversity that can be accessed by our recording technology. To retrieve these lineage labels from intact tissue samples, we will develop and validate a 2D multiplexed imaging platform that can efficiently read out the mutations generated during lineage recording. In this imaging platform, each editing position will be read out in a sequential way by each hybridization-imaging cycle, and each cassette will be presented by unique color codes in each hybridization-imaging cycle using degenerate probes. This 2D multiplexed imaging platform can efficiently read out the 220 unique labels from 20 editable bases using 5 colors in only 4 imaging cycles, dramatically facilitating the information retrieval process. This multiplexed imaging platform is only made possible by the unique binary functional mode of base editing and is not compatible with the vast majority of CRSIPR-based tracers, which function by introducing random DNA mutations to label cell lineage. Finally, we will apply both technologies for a proof-of-concept tracing experiment in HeLa cells. Collectively, the proposed technologies, once developed, will enable the collection of spatially resolved lineage information from single cells in intact tissues. We expect our tool can be widely applicable to various biological systems.

项目摘要 细胞分裂和分化是生物学中的基本过程。中单个细胞的谱系信息 一个成年人代表了理解不同细胞类型的起源和细胞如何选择的缺失关键。 某些发展轨迹。然而，血统追踪，特别是高分辨率的血统追踪，在技术上是不可能的。 要求很高。我们认为一个理想的世系追踪工具必须满足两个要求：（1）可编程的 具有大存储容量的记录机制，标记发育窗口中的每一次细胞分裂， 感兴趣的，和（2）错误鲁棒的读出机制，可以揭示个体细胞中的谱系标记，而不需要 破坏了它们的空间分布。考虑到这两项要求，我们建议广泛发展 适用于空间分辨单细胞谱系追踪的工具。 我们的谱系追踪工具包括两个模块化的关键技术：靶向原位DNA多样化， 谱系记录和用于谱系阅读的2D多路复用成像。在单个像元上启用动态跟踪 解决方案，每个细胞分裂都必须被唯一标记，并且这些谱系标记必须是稳定的和可遗传的。 为此，我们将开发一种使用碱基编辑器的靶向原位DNA多样化技术， 精确的基因组编辑剂，在双链DNA中引入C：G到T：A或A：T到G：C的转换。我们 模拟表明，通过在短DNA序列中包括20个用于碱基编辑器的可编辑碱基， 30万个独特的读段可以从单个祖先用20代无限制的细胞分裂获得 细胞，加强了我们的记录技术可以访问的大序列多样性。检索 这些谱系标签来自完整的组织样本，我们将开发和验证一个2D多路复用成像平台 它可以有效地读出在谱系记录过程中产生的突变。在该成像平台中，每个 编辑位置将通过每个杂交成像循环以顺序方式读出，并且每个盒将 在使用简并探针的每个杂交成像循环中通过独特的颜色代码呈现。该2D 多路复用成像平台可以使用5种颜色从20个可编辑的碱基中有效地读出220个独特的标签 仅需4个成像周期，极大地促进了信息检索过程。这种多重成像 平台只能通过基本编辑的独特二进制功能模式才能实现，并且不兼容 绝大多数基于CRSIPR的示踪剂通过引入随机DNA突变来标记细胞， 脉最后，我们将应用这两种技术在HeLa细胞中进行概念验证追踪实验。 总的来说，所提出的技术一旦开发出来，将能够收集空间分辨的谱系 完整组织中的单个细胞的信息。我们希望我们的工具可以广泛应用于各种生物 系统.