Developing an ultra-high throughput droplet microfluidic workflow for genetic circuit characterization

开发用于遗传电路表征的超高通量液滴微流体工作流程

• 批准号: 10680017
• 负责人: Rohan Thakur
• 金额: $ 4.77万
• 依托单位: MASSACHUSETTS INSTITUTE OF TECHNOLOGY
• 依托单位国家: 美国
• 财政年份: 2023
• 资助国家: 美国
• 起止时间: 2023-06-01 至 2025-05-31
• 项目状态: 未结题
• 来源: https://reporter.nih.gov/project-details/10680017
• 关键词: Acceleration; Address; Antibodies; Attention; Back; Bar Codes; Behavior; Biological; Cancer Biology; Cell Separation; Cells; Cellular Morphology; Clinical; Communicable Diseases; Complex; Custom; DNA; Data; Data Set; Development; Developmental Biology; Disease; Elements; Engineering; Fluorescence; Fluorescent Antibody Technique; Gene Expression Profile; Genetic; Genome; Genomics; Goals; Hand; Individual; Libraries; Link; Maps; Membrane Proteins; Methods; Microfluidics; Microscopy; Optics; Pathology; Phenotype; Photobleaching; Plasmids; Proteome; RNA Sequences; Research; Resolution; Sampling; Scheme; Signal Transduction; System; Systems Biology; Technology; Time; Work; behavioral phenotyping; biological research; cell behavior; dosage; epigenome; frontier; interest; microscopic imaging; multiple datasets; multiple omics; novel; novel sequencing technology; sequencing platform; single cell sequencing; single cell technology; single-cell RNA sequencing; synthetic biology; targeted sequencing; technology platform; technology validation; tool; transcriptome; transcriptomics

PROJECT SUMMARY Existing single cell sequencing technologies provide an unprecedented understanding of the unique genomic and transcriptomic differences that underlie heterogeneous biological samples. These differences are key to understand disease pathologies in clinical samples and fundamental mechanisms in basic biological applications. Recent attention has been directed towards the development of multiomic technologies that better capture the differences in paired datasets such as genome and transcriptome or transcriptome and epigenome. Currently however, there is no single cell technology that can profile sequence information with the corresponding phenotypic behavior of the cell. The purpose of this project is to develop a novel sequencing platform to address this technology gap. To demonstrate the utility of this platform, I will then apply it to rapidly characterize a tunable genetic oscillator. To accomplish this goal, I propose the following 2 specific aims. In Aim 1, I will develop FAB-seq (Fluorescence Annotated Barcoding and Sequencing). I will first demonstrate a novel dual barcoding approach that co-delivers optical and DNA barcodes to create single cell maps between microscopy image data and sequence data. I will also show that FAB-seq can be used to perform targeted sequencing according to an arbitrary phenotype. Then, I will leverage additional injected DNA barcodes to enhance the total barcode space of FAB-seq. In Aim 2, I will then demonstrate that FAB-seq can be used to rapidly characterize a tunable genetic oscillator. First, I will demonstrate that FAB-seq can detect oscillatory phenotypes from a circuit library containing oscillatory and non-oscillatory genetic circuits. Then I will show that when the oscillatory behavior of the circuit is perturbed, FAB-seq can map individual oscillation dynamics to the corresponding single cell transcriptome. The long-term goal of this project is to develop a platform technology that can map single cell microscopy data to single cell sequencing data at ultra-high throughput. I envision FAB-seq to be a transformative tool in addressing questions at the frontier of the genomics field.

项目摘要 现有的单细胞测序技术提供了对独特基因组的前所未有的理解 以及基础异质生物样品的基础的转录组差异。这些差异是 了解临床样本中的疾病病理和基本生物学的基本机制 申请。最近的关注是针对多构技术的发展 捕获成对数据集的差异，例如基因组和转录组或转录组，以及 表观基因组。但是，目前尚无单一细胞技术可以用 细胞的相应表型行为。 该项目的目的是开发一个新颖的测序平台来解决这一技术差距。到 演示该平台的实用性，然后将其应用于快速表征可调的遗传振荡器。 为了实现这一目标，我提出了以下两个特定目标。在AIM 1中，我将开发Fab-Seq （荧光注释的条形码和测序）。我将首先展示一个新颖的双条形码 方法可以在显微镜图像之间创建光学和DNA条形码，以创建单细胞图 数据和序列数据。我还将证明Fab-Seq可用于执行目标测序 进行任意表型。然后，我将利用其他注入的DNA条形码来增强总条形码 Fab-Seq的空间。在AIM 2中，我将证明Fab-Seq可用于快速表征可调的 遗传振荡器。首先，我将证明Fab-Seq可以从电路库中检测到振荡表型 包含振荡和非振荡遗传回路。然后，我将证明当振荡行为的行为 电路受到干扰，fab-seq可以将单个振荡动力学映射到相应的单个单元格 转录组。 该项目的长期目标是开发可以映射单细胞显微镜数据的平台技术 在超高吞吐量下单细胞测序数据。我设想fab-seq成为一种变革性的工具 在基因组学领域的边界解决问题。