The Effect of Noisy Protein Expression on E. coli/Phage Dynamics

It has long been suspected that population heterogeneity, either at a genetic level or at a protein level, can improve the fitness of an organism under a variety of environmental stresses. However, quantitative measurements to substantiate such a hypothesis turn out to be rather difficult and have rarely been performed. We examine the response of Escherichia coli (E. coli) to infection by viruses known as phage. In order to inject its DNA into a bacterium, the phage must first bind to a specific receptor protein and consequently the number of receptors per bacterium is related to the bacterial susceptibility to infection. Like many proteins in a bacterial population, the number of expressed receptor proteins in an individual cell is not deterministic but stochastic. In this project, experiments and model calculations are used to study how the noisy expression of phage receptors in a bacterial population changes the short-time population dynamics of an isolated and well-mixed E. coli/phage system. We find that when phage are present in the system, the selective killing of bacteria expressing high numbers of phage receptors creates a phenotype selection and the bacterial population can no longer be considered as having a homogeneous susceptibility to the phage pressure. It is shown that a heterogeneous bacterial population is significantly more fit compared to a homogeneous population when confronting a phage attack. We find that a small percentage of cells which are expressing few phage receptors become important because these bacteria persist despite the presence of phage. In view of their important roles in environmental adaptation, in various diseases and potentially in evolution, a fundamental understanding of this minority of cells remains a significant challenge

Cooling load differences between radiant and air systems

Unlike the case of air systems where the cooling load is purely convective, the cooling load for radiant systems consists of both convective and radiant components. The main objectives of this energy simulation study were to investigate whether the same design cooling load calculation methods can be used for radiant and air systems by studying the magnitude of the cooling load differences between radiant and air systems over a range of configurations and to suggest potential improvements in current design guidelines. Simulation results show that 1) zone level 24-hour total cooling energy of radiant systems can be 5-15% higher than air systems due to differences in conduction load through the building envelope; 2) peak cooling load at the radiant system hydronic level can be 7-31% higher than air system for zones without solar load. The differences can increase up to 93% at the hydronic level for floor system in zones with solar load; 3) the cooling load differences between the two systems originate from: a) radiant cooling surface(s) directly remove part of the radiant heat gain and reduce heat accumulation in the building mass; b) only part of the convective heat gain becomes instantaneous cooling load. This indicates that simplified methods such as Radiant Time Series Method is not appropriate for cooling load calculation in radiant system design. Radiant systems should be modeled using a dynamic simulation tool that is capable of capturing radiant heat transfer for cooling load calculation.&nbsp