UC San Diego

Protein mass is a major constituent of bacterial cell dry weight. An exponentially growing cell diverts most of its nutrient uptake to protein synthesis. The optimal allocation of a cell's total proteins, or proteome, to various cellular functions is a major concern for the cell growing in different growth conditions. Obligatory relations between ribosomal proteome fraction and growth rate impose further constraints on proteome resources allocation. In this dissertation, I am interested in understanding the global strategy of proteome resources allocation and exploring its physiological consequences in E. coli.

To understand the global strategy of proteome allocation, we apply a series of metabolic challenges to probe the responses of the proteome of exponentially growing E. coli using quantitative mass spectrometry. Despite the enormous complexity in the details of the underlying regulatory network, the proteome partitions into several coarse-grained sectors whose total abundances exhibit linear relations with the growth rate. These growth-rate dependent proteome fractions comprise about half of the proteome by mass, and their mutual dependencies can be characterized quantitatively by a simple proteome-based flux model involving only two effective parameters. The success and apparent generality of this simple model is due to the tight coordination between proteome partition and metabolism, suggesting a principle for resource-allocation in proteome economy. This general strategy of global gene regulation should serve as a basis for future studies on gene expression and constructing synthetic biological circuits.

We also show that proteome resources allocation has important consequences in cell physiology. An important yet mysterious phenomenon in bacterial physiology is the overflow metabolism, where the cell excretes acetate in the case of E. coli. We observed a set linear relations between acetate excretion rate and growth rate under different modes of growth limitation. By including both the carbon and proteome resources in a simple resource allocation model, we can quantitatively describe the observed linear relations. Key model parameters of protein costs were determined directly using flux analysis and protein mass spectrometry measurements. These results suggest optimal allocation of carbon and proteome resources as a possible driving force for the occurrence of overflow metabolism.