Elucidating the role of protein load for the physiology of Enterococcus faecalis byintegrating proteomics data and genome-scale computational models

了解微生物生长具有高度的生物技术相关性，是了解如何对抗微生物病原体的一个关键方面。虽然对基因和蛋白质的表达以及代谢过程进行了详细的研究，但仍不能全面和复杂地了解微生物的生长。在过去的几年里，理论和实验研究表明，蛋白质负荷-细胞蛋白质的总量-是有限的，从而限制了微生物的生长。一方面，研究表明，蛋白质的总量受到核糖体和RNA聚合酶的数量和催化效率的限制。另一方面，我们和其他人发现了极高的细胞浓度，例如糖酵解酶，这表明蛋白质负荷必须接近细菌细胞的物理极限，这意味着明显更高的浓度会导致晶体形成。因此，当蛋白质负荷处于其物理极限时，例如，为适应环境而表达的特定蛋白质只能通过蛋白质组成的重组来实现。限制蛋白质负载也对分子工程策略或生物技术方法具有实际意义。例如，对总蛋白量的限制将影响产量优化和蛋白质的过表达。因此，越来越清楚的是，物理和（生物）化学对细胞的适应和进化施加了强有力的限制。这样的约束会影响细胞在其生长过程中如何分配有限的资源以优化适应度（细胞经济学）。积累的数据和理论已经证明，适当的资源分配是这种适应的重要驱动因素。所有这些发现表明，在全细胞范围内，严密而敏感的调控机制控制着蛋白质的表达。到目前为止，蛋白质负载及其对细胞过程的影响还没有系统的研究。因此，在本项目中，我们将结合经典的微生物学实验、最新的全细胞定量蛋白质组学技术和计算模型，以全面和全细胞范围的方法研究蛋白质负载对细胞行为的影响。我们将使用粪肠球菌作为本研究的模式生物，因为(a)它在工业上具有重要的相关性，(b)它在遗传学方面的描述相对较好，部分也在其代谢和生长方面，(c)它具有相对较小的基因组，(d)我们手头有一个基因组尺度的代谢模型，(e)我们能够展示将蛋白质组数据整合到该生物的基因组尺度模型中的可行性。我们的目标是了解粪肠杆菌如何平衡和维持细胞内蛋白质负荷，它如何对人工诱导的单一蛋白质高表达做出反应，以及如何控制这种反应。

Understanding microbial growth has high biotechnological relevance and is one key aspect in understanding how to combat microbial pathogens. Although gene and protein expression as well as metabolic processes are studied in detail, still microbial growth cannot be understood in its entirety and complexity. In the last years, theoretical and experimental studies revealed that protein load - the total amount of cellular proteins - is limited and thus constrains microbial growth. On the one hand, it has been shown that the total amount of proteins is limited by the amount and the catalytic efficiency ofribosomes and RNA polymerases. On the other hand, we and others found extremely high cellular concentrations of for instance glycolytic enzymes which indicate that the protein load must be close to the physical limit of the bacterial cell, meaning that significantly higher concentrations would lead to crystal formation. Consequently, when protein load is at its physical limit, e.g., expression of specific proteins for environmental adaptation can only be achieved by a reshuffling of the protein composition. A limiting protein load has also practical implications for molecular engineering strategies or biotechnological approaches. E.g., constraints on the amount of total protein will affect yieldoptimizations and the overexpression of proteins. Thus, it is becoming increasingly clear that physics and (bio)chemistry impose strong constraints on adaptation and evolution of cells. Such constraints have an impact on how a cell should partition that limited resource over its growth processes to optimize fitness (cellular economics). Accumulating data and theory have established that proper resource allocation isan important driver for such adaptations. All these findings imply that tight and sensitive regulatory mechanisms control protein expression on a cell-wide scale. Up to now, the protein load and its impact on cellular processes have not been studied systematically. Thus, in this proposed project we aim on investigating the effect of protein load oncellular behavior in a comprehensive and cell-wide approach, combining classical microbiological experiments, the latest quantitative whole-cell proteomic technique and computational modeling. We will use E. faecalis as a model organism for this study because (a) it is of major relevance in industry, (b) it is relatively well described in terms of genetics, and partially also in its metabolism and growth, (c) it has a relatively small genome, (d) we have a genome-scale metabolic model at hand, and (e) we were able to show feasibility of the integration of proteome data into the genome-scale model for thisorganism. We aim to learn how the intracellular protein load is balanced and maintained in E. faecalis, how it responds to artificially induced hyper expression of single proteins and how this response is controlled.