Improving the penicillin fermentation by modelling and optimising its metabolic network and transporterome

青霉素是亚历山大·弗莱明（Alexander Fleming）于1928年（再）发现的，并在20世纪40年代初由弗洛里（Florey）、钱恩（Chain）和希特利（Heatley）发展成最初的发酵过程。尽管抗菌素耐药性不断增加，但它仍然是英国发酵行业的顶级产品之一（通常与青霉酶抑制剂clavulanic酸结合使用，如Augmentin）。然而，就糖原料中的碳转化为青霉素产品中的碳的效率而言，这是一个糟糕的发酵，因为这个效率不超过10%。许多其他发酵，如生产味精的发酵，其碳转化效率接近100%。因此，有很大的改进空间，并使青霉素工艺在经济上更具竞争力。与波音777等工程人工制品的设计一样，需要的是青霉素生产者P. chrysogenum代谢网络的数学模型。每个基因的表达量告诉我们发生了什么，这被称为转录组。为此，GSK将提供生产菌株本身的转录组数据。从（已知的）基因组序列，我们可以产生一个计算机版本的代谢网络进行分析。重要的是，青霉素过程中使用的培养基已经完全确定，这使得进行这种建模是可行的。制作出模型后，我们可以初步定性地预测它将产生什么分子，这些分子将在GSK提供的细胞提取物和培养基上进行实验测量。模型和转录组的结合使我们能够计算所有的通量，包括产品和非盈利的地方。这将有助于确定青霉菌真菌基因组成的哪些变化最有可能导致更高的碳转化效率。这些变化将由葛兰素史克（GSK）做出，并在新的生产菌株上进行测试。对细胞提取物和计算机内部进行这些分析的能力意味着，虽然我们可以访问数据，但我们既没有也不需要访问专有生产菌株本身。重要的是，我们将在一个合适的数据库中管理所有数据。

Penicillin was famously (re)discovered by Alexander Fleming in 1928, and developed into an initial fermentation process by Florey, Chain and Heatley during the early 1940s. Despite increasing antimicrobial resistance, it remains one of the UK fermentation industry's top products (often combined with the penicillinase inhibitor clavulanic acid in products such as Augmentin). However, in terms of the efficiency of conversion of carbon in the sugar feedstock to carbon in the penicillin product it is a lousy fermentation as this efficiency is no more than 10%. Many other fermentations, such as that producing monosodium glutamate, have a carbon conversion efficiency approaching 100%. Consequently, there is much room for improvement, and for making the penicillin process more competitive economically. As with the design of engineering artefacts such as the Boeing 777, what is needed is a mathematical model of the metabolic network of the penicillin producer, P. chrysogenum. The amount that each gene is expressed tells us what is going on, and is known as the transcriptome. To this end, transcriptome data FROM THE PRODUCTION STRAIN ITSELF will be made available by GSK. From the (known) genome sequence we can produce a computer version of the metabolic network for analysis. Importantly, the media used for the penicillin process are fully defined, which makes it feasible to do this modelling. Having produced the model, we can predict, initially qualitatively, what molecules it will produce, and these will be measured experimentally on extracts of cells and medium provided by GSK. The combination of the model and the transcriptome allows us to calculate all the fluxes, both to product and to non-profitable places. This will help determine which changes in the genetic make-up of the Penicillium fungi are most likely to lead to a higher carbon conversion efficiency. These changes will be made (by GSK) and tested on the new production strains. The ability to do these analyses on cell extracts and inside a computer means that while we have access to the data we neither have nor need access to the proprietary production strains themselves.Importantly, we shall curate all of the data in a suitable database.