Protein burden in protein overproduction

We define 'the protein burden effect' as the set of generic complications that compromise the overproduction of proteins in living cells. Five complications will be quantified by systems approaches that combine quantitative experimentation and calculation/modelling, and an industrial and University laboratory: 1.Competition for ribosomes: Assuming that the mRNA for the extra protein competes equally with the mRNAs of cellular proteins, the effect on growth rate and protein production can be calculated using Control Analysis [our earlier Z. mobilis work]. Implications for optimization of production processes between growth phase and defined stationary phase, will be modelled. 2.Competition within subclass of membrane-inserted proteins: Determination of the control coefficient of the produced functional protein and of the ribosomes on the cells' growth and protein production rates. With this we could explain 25 % of the protein burden effect for an important membrane protein in E. coli. This might have to do with competition for synthesis within the subclass of membrane proteins, or for membrane surface area. 3.Competition with ribosomes: With our nonlinear flux balance analysis, the competition between ribosomal protein synthesis and extra protein synthesis can be calculated by using a simple model that does not depend on kinetic parameter values. 4. Competition for chaperonins: Thermal denaturation is a default stress against which cells are armed by a number of chaperonins. The overproduced exogenous protein may depend much on the refolding activities of chaperonins. Because the effects of this depends on temperature in an experimentally accessible way (Arrhenius-type factor), one should be able to predict (and test) the temperature dependence of this part of the protein burden effect. 5.Inclusion bodies: When the extra protein is not properly refolded by the chaperonins, it may form inclusion bodies. Because of the saturability of the chaperonin activity with the concentration of their substrates, a very steep dependence on this on the concentration of overproduced protein (and temperature) is expected. In addition inclusion body formation initiation is likely to depend on both the concentration of the extra protein and the physico-chemical tendency for a protein to form inclusion bodies. Proteins vary widely in their solubility (Niwa et al 2009). Our own bioinformatics work shows that solubility correlates well with features that can be calculated for proteins. Work plan: 1st semester: Basic training in systems biology in the Manchester DTC. 2nd sem: On-site project training in the company (MSD). 3rd sem: Replay of the Zymomonas mobilis work in E. coli with proteins relevant for the company and some proteins of known catalytic activity (partly at company [culturing in practice], partly at University [focusing on academically defined culturing conditions]). Construction of simple flux, MCA and kinetic models. 4th sem: Experimental determination of the sensitivity coefficients of production and growth rate to the induction level of the proteins [variation of induction levels], and of the control coefficients of the ribosomes [inhibitors; in-vivo protein synthesis assay]. 5th sem: Modulation of cytosolic versus membrane proteins being overproduced, modulation of lipid synthesis. Measurement of relative negative effects on the production of some host cell membrane and cytosolic catalytic proteins [enzyme assays]. 6th sem: With as input the protein concentration and as output the predicted protein solubility, temperature is a key variable in the physico-chemical modelling, as well as in the upstream chaperonin component. Temperature-dependence will be used to test modelling against experiment in wild-type and chaperonin mutant strains. 7th sem: Write up in thesis. Systematic data management. 8th sem: Buffer time. Wrap up: scientific publications and in-company proof of value.