recSysBio - A Systems Biology approach for optimization of recombinant fermentation processes
FCT POCI/BIO/60139/2004

Partners: IST (Josť Cardoso Meneses)


The purpose of this project is to derive strategies for increasing the productivity of recombinant protein production processes by applying a systems biology perspective to the phenomena occurring in the recombinant cell using genome-scale analysis of the transcriptome, proteome, fluxome and metabolome.

Escherichia coli has been the organism of choice for the production of many recombinant proteins with high therapeutic value. However, while the research on molecular biology has allowed the development of very strong promoters, there are still two main phenomena associated with this process that have hampered the full use of that promoter strength: aerobic acetate production associated with high specific growth rates, and stringent response that usually occurs after induction takes place. Acetate production is known to reduce both biomass yield on the chosen carbon source and protein productivity while totally inhibiting growth when present at high concentrations due to its toxic effect. On the other hand, stringent response is caused by an imbalance in intracellular amino acid uptake and the endogenous amino acid synthesis rate that occurs due to high demands of amino acids for recombinant protein production, causing several cellular responses, from the inhibition of the synthesis of rRNA and of translation and transcription apparatus to induction / repression of several metabolic pathways or induction of proteases. This response reduces the specific growth rate and protein production and has many similarities to other stress responses found in E. coli, like heat shock or the exhaustion of a carbon source in a diauxic growth.

While there have been several studies covering the recombinant protein production process with the bacterium Escherichia coli, including genome-scale analysis of the transcriptome, proteome, fluxome or metabolome, there has been a lack of an integrative approach that is able to combine genomic and physiological information about those processes with high-throughput analysis. In fact, most of the published work on this field is usually limited to one or two types of those analyses for the extraction of some local hypothesis that need to be tested afterwards. Moreover, as we are dealing with very complex phenomena, it is very difficult to elucidate which phenomena represents the causes and which ones the consequences, most of the times the derivation of hypothesis being based on misassumptions. Finally, some of the conclusions extracted from those studies are difficult to apply directly to industrial processes, as the experiments are often run in shake flaks or batch fermentations with low cellular densities, while most industrial fermentations in this field are conducted in the fed-batch mode at very high-cell densities.

Also, the existence of genome-scale models that cover both stoichiometry and regulation of some pathways has not been taken into account in genome-scale data analysis and for the consequent formulation of hypothesis and development of new strategies for improving the performance of the process.

In this work, the high-cell density fed-batch recombinant protein production process in E. coli will be studied, giving particular relevance to acetate production and stringent response phenomena. The approach is intended to be systematic, by first compiling the existing knowledge about those phenomena, extending existing genome-scale models to accommodate that knowledge, derive hypothesis in silico that will then be tested by using genome-scale analysis of the omes. A reliable fermentation process will be developed to be able to reproducibly study those phenomena in different strains in order to reduce external variances to a minimum. This approach will certainly improve our understanding of those important phenomena as well as formulate new strategies for improving the process performance either by genetic manipulations or fermentation strategies.