Protein burden in protein overproduction

我们将“蛋白质负担效应”定义为一组危及活细胞中蛋白质过量生产的通用型并发症。五种并发症将通过结合定量实验和计算/模型的系统方法以及工业和大学实验室进行量化：1.核糖体竞争：假设额外蛋白质的信使核糖核酸与细胞蛋白质的信使核糖核酸平等竞争，对生长速度和蛋白质生产的影响可以使用控制分析来计算[我们早先的Z.mobilis工作]。将对生长阶段和定义的固定阶段之间的生产过程进行优化的影响进行建模。2.膜插入蛋白亚类内的竞争：测定产生的功能蛋白和核糖体对细胞生长和蛋白质产量的控制系数。有了这一点，我们就可以解释大肠杆菌中一种重要的膜蛋白的25%的蛋白质负荷效应。这可能与膜蛋白亚类内合成的竞争或膜表面积的竞争有关。3.与核糖体的竞争：通过我们的非线性通量平衡分析，可以用一个不依赖于动力学参数值的简单模型来计算核糖体蛋白质合成和额外蛋白质合成之间的竞争。4.对伴侣蛋白的竞争：热变性是一种默认的压力，细胞由许多伴侣蛋白武装起来抵抗。过量生产的外源蛋白可能在很大程度上依赖于伴侣蛋白的复性活性。因为这一效应以实验可及的方式依赖于温度(Arrhenius类型因子)，所以人们应该能够预测(并测试)这部分蛋白质负荷效应的温度依赖性。5.包涵体：当额外的蛋白质没有被伴侣蛋白正确复性时，它可能会形成包涵体。由于伴侣蛋白活性随底物浓度的变化是饱和的，因此对过量蛋白浓度(和温度)的依赖是非常严重的。此外，包涵体形成的起始可能取决于额外蛋白质的浓度和蛋白质形成包涵体的物理化学倾向。蛋白质的溶解度差异很大(Niwa等人，2009年)。我们自己的生物信息学工作表明，溶解度与可以计算出的蛋白质特征有很好的相关性。工作计划：第一学期：曼彻斯特DTC系统生物学基础培训。第二个项目经理：公司现场项目培训(MSD)。第三个扫描电镜：用与公司相关的蛋白质和一些已知催化活性的蛋白质在大肠杆菌中重播运动发酵单胞菌的工作(部分在公司[实践中培养]，部分在大学[专注于学术定义的培养条件])。建立了简单的通量模型、MCA模型和动力学模型。第4个扫描电子显微镜：实验测定产量和生长速率对蛋白质诱导水平的敏感性系数[诱导水平的变化]，以及核糖体的控制系数[抑制剂；体内蛋白质合成试验]。第5个扫描电子显微镜：调节胞质蛋白相对于膜蛋白的过度生产，调节脂质合成。对某些宿主细胞膜和胞质催化蛋白产生的相对负面影响的测量[酶分析]。第6个扫描电子显微镜：以蛋白质浓度为输入，以预测的蛋白质溶解度为输出，温度是物理化学模型中的关键变量，也是上游伴侣蛋白成分中的关键变量。温度依赖性将被用来在野生型和伴侣蛋白突变株中测试模拟和实验。第七章：在论文中写一篇。系统的数据管理。第8个sem：缓冲时间。总结：科学出版物和公司内部的价值证明。

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.