SBIR Phase I: Hardware and Software Systems for High Throughput, High Cell Density Fermentation

SBIR 第一阶段：用于高通量、高细胞密度发酵的硬件和软件系统

• 批准号: 1722440
• 负责人: Matthew Ball
• 金额: $ 22.5万
• 依托单位: Culture Robotics, Inc
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2017
• 资助国家: 美国
• 起止时间: 2017-07-01 至 2018-06-30
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1722440&HistoricalAwards=false
• 关键词: SBIR; Phase; Hardware; Software; Systems

This SBIR Phase I project proposes to develop a high throughput, imagery-based single cell analysis system. The system will be used to characterize high cell density polymicrobial samples captured during biological research. Initially, the technology will be applied to the problem of quantifying extremely low levels of microbial contamination in biological samples. The quantification and control of microbial contamination is an important challenge in industrial fermentation and in the manufacturing of biologics. Methods for rapid and sensitive detection of microbial contaminants do not exist. Traditional contamination detection methods involve time-consuming culturing of cells or manual and imprecise checks with a microscope. The proposed technology will provide automated and rapid sample characterization, allowing a speed of analysis that is 1000 times faster than current systems. This increased throughput will additionally allow lower levels of contamination to be quantified. While initially applied to research, the technology can also be used as an analytical and diagnostic tool in the medical field. For example, this analysis system could be used to search for malformed red blood cells in a human sample that might arise due to a disease like sickle cell anemia, or to determine the relative abundance and morphology of immune cells, an analysis that would help identify certain leukemias.This project will create a hardware platform and a parallelized computer vision system that is capable of fully characterizing each cell in a 1mL biological sample in under five minutes. To analyze samples taken from a fermentation process with high cell densities requires the micrography system to be capable of processing over one billion cells in the analysis window. The project aims to develop four subsystems: a high pressure microfluidic system for separating and isolating cells, an imaging system, a set of high throughput algorithms to classify the cellular imagery data and a horizontally-scalable computing platform on which to run the classifying code. The project will begin by developing a low throughput, fully functioning prototype. The efforts will then focus on developing the four primary subsystems in parallel, using knowledge gained in the prototyping efforts to guide the later work. Additional phases will focus on the integration of high throughput versions of the subsystems. The fully realized single cell micrography system will represent a leap forward in speed and specificity compared to traditional cytometry systems. With no manual intervention and in an open-ended, label-free manner, researchers will be able to conduct parts per billion-level inspection of a biological sample.

该SBIR一期项目旨在开发一种高通量、基于图像的单细胞分析系统。该系统将用于表征生物研究期间捕获的高细胞密度多微生物样品。最初，该技术将应用于生物样品中极低水平微生物污染的定量问题。微生物污染的定量和控制是工业发酵和生物制剂生产中的一个重要挑战。目前还不存在快速灵敏的微生物污染物检测方法。传统的污染检测方法需要花费大量时间培养细胞，或者用显微镜进行人工和不精确的检查。所提出的技术将提供自动化和快速的样品表征，使分析速度比现有系统快1000倍。这种增加的吞吐量还将允许对较低水平的污染进行量化。虽然最初应用于研究，但该技术也可以用作医疗领域的分析和诊断工具。例如，该分析系统可用于在人体样本中搜索可能由镰状细胞性贫血等疾病引起的畸形红细胞，或用于确定免疫细胞的相对丰度和形态，这一分析将有助于识别某些白血病。该项目将创建一个硬件平台和并行计算机视觉系统，能够在五分钟内完全表征1mL生物样本中的每个细胞。要分析从高细胞密度的发酵过程中提取的样品，需要显微照相系统能够在分析窗口中处理超过10亿个细胞。该项目旨在开发四个子系统：一个用于分离和隔离细胞的高压微流体系统，一个成像系统，一套用于对细胞图像数据进行分类的高通量算法，以及一个用于运行分类代码的水平可扩展计算平台。该项目将首先开发一个低吞吐量、全功能的原型机。然后工作将集中于并行地开发四个主要子系统，使用在原型工作中获得的知识来指导后期的工作。其他阶段将关注子系统的高吞吐量版本的集成。与传统的细胞测定系统相比，完全实现的单细胞显微照相系统将在速度和特异性方面取得飞跃。在没有人工干预和开放式、无标签的方式下，研究人员将能够对生物样本进行十亿分之一级别的检查。