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 工具渗透到生物学的许多领域，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，但进展缓慢，因为社区对蛋白质如何 序列与蛋白质的功能有关。 社区的一个长期目标是发展对序列功能的更详细的理解 两性关系。这一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。获取详细的序列-功能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：有接近无限的可能性 将二十种氨基酸中的任何一种放置在蛋白质的数百到数千个残基位置。一个典型的 实验室可能会对这种情况的一小部分进行筛查，这些突变散布在整个 蛋白质或靶向蛋白质的关键区域。即使在这些筛选期间，资源规模的限制 需要对单个蛋白质变体进行功能性评估或对单个变体进行测序，这阻碍了对 顺序-功能关系。典型的实验室要么在功能上详细筛选考生，要么将 候选人的细节，但不是两个都是。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，该技术可以探索详细的 具有完整序列和功能信息的蛋白质适合性景观，标度比标度大1-2个数量级 现有屏幕的数量。我们将通过使用光学成像来执行功能评估来达到此级别 和原位测序。我们将在三个目标上开发这样的技术：(1)我们将光学量化 培养井内大规模荧光蛋白突变体库的功能。(2)在同一口井里，我们 将使用最近开发的商业化学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口井进行，我们将开发 单蛋白质变异体分辨时序列与功能的关系。(3)我们会发展一套 图像处理技术的流水线，可以自动准确地分割单个细胞，并调用 在整个培养过程中，每个细胞内的碱基足迹都很好。如果成功，我们三个目标的结合将 使典型的实验室能够大规模地筛选具有完整序列和功能信息的蛋白质工具。我们预计 我们的技术可以利用现有的商品，并轻松地从一个实验室移植到另一个实验室。增加的 然后，拟议技术的规模和开源特性可以广泛影响蛋白质工具的开发 社区。