Sivaloganathan Darshan M, Wan Xuanqing, Brynildsen Mark P
Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ, USA.
Department of Chemical and Biological Engineering, Princeton University, Princeton, NJ, USA.
Methods Mol Biol. 2020;2088:161-188. doi: 10.1007/978-1-0716-0159-4_8.
Nitric oxide (NO) is a radical that is used as an attack molecule by immune cells. NO can interact and damage a range of biomolecules, and the biological outcome for bacteria assaulted with NO will be governed by how the radical distributes within their biochemical reaction networks. Measurement of those NO fluxes is complicated by the low abundance and transience of many of its reaction products. To overcome this challenge, we use computational modeling to translate measurements of several biochemical species (e.g., NO, O, NO) into NO flux distributions. In this chapter, we provide a detailed protocol, which includes experimental measurements and computational modeling, to estimate the NO flux distribution in an Escherichia coli culture. Those fluxes will have uncertainty associated with them and we also discuss how further experiments and modeling can be employed for flux refinement.
一氧化氮（NO）是一种自由基，被免疫细胞用作攻击分子。NO 可以与一系列生物分子相互作用并造成损害，遭受 NO 攻击的细菌的生物学结果将取决于该自由基在其生化反应网络中的分布方式。许多反应产物的丰度低且具有瞬时性，这使得对这些 NO 通量的测量变得复杂。为了克服这一挑战，我们使用计算模型将几种生化物质（例如，NO、O、NO）的测量值转化为 NO 通量分布。在本章中，我们提供了一个详细的方案，包括实验测量和计算模型，以估计大肠杆菌培养物中的 NO 通量分布。这些通量会存在相关的不确定性，我们还将讨论如何通过进一步的实验和模型来优化通量。
