代谢工程和在各行业中的应用

描述

优化细胞内基因和监管职能促进细胞合成的一种特定的物质被称为代谢工程。这些化学网络让细胞生存所需的原始资源转换成分子的细胞通过一系列生化反应和酶。特别是,代谢工程的目标是这些网络数学模型,确定有用的产品的产量和识别网络组件,限制这些产品的生产。

能够使用这些生物制造有价值的化合物工业规模有效代谢工程的最终目标。生产的啤酒,葡萄酒,奶酪,药物和其他生物技术产品当前的例子。由于细胞依赖这些代谢网络生存,改变可以产生重大影响细胞的生存能力。因此,代谢工程,必须做出取舍之间的细胞的能力生产所需的材料和其生存的必要性。因此,当前的重点是针对细胞有效监管网络工程师新陈代谢而不是直接删除和/或overexpressing代谢酶的基因编码。在过去,被化学诱导转基因微生物突变的突变株中目标代谢物被选为了最大化的生产力所需的代谢物。这种方法的关键问题之一就是代谢物的代谢途径生产没有检查,所以生产限制和需要修改的相关途径酶是未知的。代谢工程是变得更加实用、经济、工业规模。50多个生物炼油厂设施被修建在北美生物技术工业组织。代谢工程是用来生产生物燃料和可再生生物质化学物质,可以帮助降低温室气体排放。 Short-chain alcohols and alkanes, fatty acid methyl esters and fatty alcohols and biofuels based on fatty acids and isoprenoids are all examples of potential biofuels. With the help of innovations in synthetic biology and advancements in our understanding of metabolite damage and how to prevent or repair it, metabolic engineering processes and efficiency are continuing to improve. Early metabolic engineering experiments shown that if corresponding damage control systems are absent or insufficient, buildup of reactive intermediates can limit flux in constructed pathways and be harmful to host cells. Synthetic biologists improve genetic pathways, which therefore have an impact on cellular metabolic outputs. Recent reductions in the price of synthetic DNA and advancements in genetic circuits have an impact on metabolic engineering's capacity to achieve desired results. The first step in the procedure is to decide what desired outcome you want to attain by enhancing or changing an organism's metabolism. Research on the reactions and metabolic processes that can result in this substance or outcome is conducted using reference materials and online resources. These databases are replete with genetic and chemical data, including metabolic and other biological process pathways. An organism that will be employed to produce the intended product or result is selected using this research. When making this choice, factors such how closely the organism's metabolic pathway resembles the required pathway, how expensive it is to maintain the organism and how simple it is to change the organism's pathway are taken into account. To determine the potential yield of the product or the reaction fluxes in the cell, the finished metabolic pathway is mathematically modeled. The frequency with which a specific network reaction takes place is known as a flux. Simple metabolic pathway analysis can be carried out manually, however the majority of computations require the use of software. To solve these models, these applications employ sophisticated linear algebraic techniques. The necessary data regarding the pertinent reactions and their fluxes must be supplied in order to solve a network using the equation for determined systems presented below. It is crucial to identify which reactions can be changed in order to maximize the yield of the target product after solving for the fluxes of reactions in the network. Utilizing computational techniques like Opt Gene or Opt Flux is important to decide which specific genetic alterations to carry out. They offer suggestions for the genes that have to be overexpressed, eliminated or added to a cell in order to increase production of the desired product. The required genetic changes can be carried out using conventional molecular biology methods. Depending on how they affect the pathway and the end aim, genes may be overexpressed or eliminated from an organism. It is frequently important to have certain fluxes known or experimentally observed in order to build a solvable model. Additionally, experimental measurements of the network's fluxes are required to confirm the impact of genetic modifications on the metabolic network. Carbon flow measurements are conducted using carbon-13 isotope tagging to measure reaction fluxes.