I-Corps: Software and Services to Enable Metabolic Flux Analysis

代谢通量分析（MFA）允许测定活细胞内的生化反应速率，否则不可能直接测量。与谷歌Maps报告高速公路网络中的交通流量类似，MFA可以识别生物化学网络中的细胞通路瓶颈（路障）和浪费的代谢过程（弯路）。这些信息可用于设计用于工业生物工艺或农业的改进生产系统（例如，宿主生物和/或栽培平台）。MFA技术还可用于生物医学研究，以确定潜在的治疗靶点或代谢性疾病的诊断性生物标志物。然而，由于需要复杂的计算算法和数据分析，大多数公司没有必要的专业知识来使用MFA评估其测量结果。简而言之，该项目旨在扩大使用先进的代谢工程软件和PI？S实验室应用于生物技术和制药行业。代谢通量分析（MFA）是一种复杂的分析技术，它涵盖了分子生物学、化学、生物化学、细胞生物学、植物生理学、数学、计算机科学和工程学。提议的MFA方法将是严格的，因为这个团队的目标是从公司可以从他们的实验系统中获得的可用测量中获取尽可能多的信息。正因为如此，在一个组织内的直接影响将是科学质量的提高。这个I-Corps团队旨在以身作则，通过创建可测试的假设，验证其假设，解释所有错误来源，并关注细节分析数据。MFA，加上所提出的方法，有可能更好地改变公司如何执行代谢工程。评估细胞代谢的改进方法不仅有可能推动生产效率的巨大进步，这对从生物燃料生产到食品生产的所有领域都很有用，而且对药物发现和癌症或糖尿病等代谢性疾病的治疗应用也很有用。

Metabolic flux analysis (MFA) allows for the determination of biochemical reaction rates inside of living cells, which are otherwise impossible to measure directly. Similar to how Google Maps reports traffic flows within highway networks, MFA can identify cellular pathway bottlenecks (roadblocks) and wasteful metabolic processes (detours) within biochemical networks. This information can be used to engineer improved production systems (e.g., host organisms and/or cultivation platforms) for use in industrial bioprocesses or agriculture. The MFA technology can also be used in biomedical research to identify potential therapeutic targets or diagnostic biomarkers for metabolic diseases. However, most companies do not have the necessary expertise to assess their measurements using MFA due to the sophisticated computational algorithms and data analysis required. At its simplest, the proposed project seeks to broaden the use of advanced metabolic engineering software and techniques developed in the PI?s laboratory for applications in the biotechnology and pharmaceutical industries.Metabolic flux analysis (MFA) is a complex analysis technique that encompasses molecular biology, chemistry, biochemistry, cell biology, plant physiology, mathematics, computer science, and engineering. The proposed approach to MFA will be rigorous because this team aims to capture as much information as possible from the available measurements that companies can obtain from their experimental system. Because of this, the immediate impacts within an organization will be an increase in the quality of the science performed. This I-Corps team aims to lead by example by creating testable hypotheses, validating its assumptions, accounting for all sources of error, and analyzing data with attention to detail. MFA, coupled with the proposed approach, has the potential to change for the better how companies perform metabolic engineering. Improved methodologies to assess cellular metabolism have the potential to drive tremendous advances in not just manufacturing efficiency, which is useful for everything from biofuels production to food production, but also for drug discovery and therapeutic applications in metabolic diseases such as cancer or diabetes.