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

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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.