Development of large-scale sequence-function relationship using in situ optical sequencing

使用原位光学测序开发大规模序列-功能关系

• 批准号: 10575350
• 负责人: Yiyang Gong
• 金额: $ 23万
• 依托单位: DUKE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-09-15 至 2025-08-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10575350
• 关键词: Algorithmic Analysis; Amino Acid Sequence; Amino Acids; Bar Codes; Behavior; Biological Process; Biology; Biomedical Engineering; Biotechnology; Brain; Budgets; Calcium; Cells; Cellular biology; Chemistry; Combinatorics; Communities; Community Developments; DNA Sequence; Data; Data Analyses; Development; Developmental Biology; Dictionary; Directed Molecular Evolution; Discipline; Engineering; Face; Genetic; Goals; Human Resources; Image; In Situ; Individual; Intelligence; Knowledge; Libraries; Mammalian Cell; Messenger RNA; Modernization; Molecular Biology; Mutagenesis; Mutate; Mutation; Nature; Neurosciences; Neurotransmitters; Optical Methods; Optics; Organism; Performance; Positioning Attribute; Preparation; Process; Property; Protein Region; Proteins; Protocols documentation; Rapid screening; Reagent; Reporting; Resolution; Resources; Running; Sampling; Structure; Subcellular structure; System; Systems Biology; Techniques; Technology; Tissue imaging; Translating; Variant; base; biological systems; candidate identification; chromophore; deep learning; design; experimental study; fitness; image processing; improved; in situ sequencing; mutant; open source; optical imaging; prevent; protein function; protein structure; red fluorescent protein; screening; tool; tool development; voltage

The exploration and discovery of living systems has been greatly aided by modern protein tools. These tools pervade many fields of biology, from the sub-cellular scale to the cellular scale to the systems scale. Bioengineers have made substantial progress in expanding the functionality and enhancing the performance of these protein tools, but progress is slow due to the community's limited understanding of how a protein's sequence relates to a protein's function. A long-term goal of the community is to develop a more detailed understanding of the sequence-function relationship. This understanding will allow the field to intelligently predict, design, and identify high-performing protein tools. The technical challenge to accessing the detailed sequence-function relationship is the inability to densely sample the large landscape of potential protein sequences: there are approaching infinite possibilities of placing any of the twenty amino acids in the hundreds to thousands of residue positions of a protein. A typical lab may screen a small portion of this landscape with a limited number of mutations scattered throughout the protein or targeted to key regions of the protein. Even during these screens, limitations in the scale of resources needed to functionally assess individual protein variants or sequence individual variants hinder full access to the sequence-function relationship. The typical lab either functionally screens candidates in detail or sequences the candidates in detail, but not both. This incomplete matching between functional information and sequence information in turn prevents accurate predictions that improve protein function. The immediate goal of this proposal is to create an optical screening technology that explores the detailed protein fitness landscape with full sequence and function information on a scale 1-2 orders larger than the scale of existing screens. We will achieve this scale by using optical imaging to perform both the functional assessment and sequencing in situ. We will develop such a technology across 3 aims: (1) We will optically quantify the function of a library of fluorescent protein mutants on large scales within a culture well. (2) In the same well, we will optically sequence individual mutants using recently-developed commercial chemistries and a barcode lookup system. Because the sequencing and functional assessment occur in the same well, we will develop the relationship between sequence and function at the resolution of single protein variants. (3) We will develop a pipeline of image processing techniques that automatically and accurately segment individual cells and calls the bases within each cell footprint throughout the culture well. If successful, the combination of our three aims will enable a typical lab to screen protein tools on large scales with full sequence and function information. We expect our technology to take advantage of existing commodity goods and translate easily from lab to lab. The increased scale and open-source nature of the proposed technology can then broadly impact the protein tool development community.

现代蛋白质工具极大地帮助了生命系统的探索和发现。这些 工具遍及生物学的许多领域，从亚细胞尺度到细胞尺度再到系统尺度。 生物工程师在扩展功能和增强性能方面取得了实质性进展 这些蛋白质工具，但由于社区对蛋白质如何发挥作用的了解有限，进展缓慢 序列与蛋白质的功能有关。 社区的长期目标是对序列函数有更详细的理解 关系。这种理解将使该领域能够智能地预测、设计和识别高性能 蛋白质工具。访问详细的序列-函数关系的技术挑战是无法 对潜在蛋白质序列的大范围进行密集采样：存在接近无限的可能性 将二十个氨基酸中的任何一个放置在蛋白质的数百到数千个残基位置上。一个典型的 实验室可能会筛选该景观的一小部分，其中分散在整个区域中的数量有限的突变 蛋白质或靶向蛋白质的关键区域。即使在这些屏幕期间，资源规模也受到限制 功能评估单个蛋白质变体或对单个变体进行测序所需的功能阻碍了对单个蛋白质变体的完全访问 序列-函数关系。典型的实验室要么对候选人进行详细的功能筛选，要么对候选人进行排序 候选人的详细信息，但不是两者。功能信息和序列之间的不完全匹配 信息反过来又阻碍了改善蛋白质功能的准确预测。 该提案的直接目标是创建一种光学筛选技术，探索详细的 蛋白质适应度景观，具有比该尺度大 1-2 个数量级的完整序列和功能信息 现有的屏幕。我们将通过使用光学成像来执行功能评估来实现这一规模 和原位测序。我们将开发这样的技术，以实现 3 个目标：(1) 我们将以光学方式量化 培养孔内大规模荧光蛋白突变体文库的功能。 (2) 在同一口井中，我们 将使用最近开发的商业化学物质和条形码对单个突变体进行光学测序 查找系统。由于测序和功能评估在同一孔中进行，因此我们将开发 单个蛋白质变体分辨率下序列和功能之间的关系。 (3) 我们将开发一个 图像处理技术的流程可以自动、准确地分割单个细胞并调用 整个培养孔中每个细胞足迹内的碱基。如果成功的话，我们的三个目标将结合起来 使典型的实验室能够利用完整的序列和功能信息大规模筛选蛋白质工具。我们期望 我们的技术可以利用现有的商品并轻松地从一个实验室转移到另一个实验室。增加的 拟议技术的规模和开源性质可以广泛影响蛋白质工具的开发 社区。