Jaewook Joo

Bacteriophage-mediated competition in Bordetella bacteria

Apparent competition between species is believed to be one of the principal driving forces that structure ecological communities, although the precise mechanisms have yet to be characterized. Here we develop a model system that isolates phage-mediated interactions by neutralizing resource competition with a large excess of nutrients, and consists of two genetically identical Bordetella strains that differ only in that one is the carrier of phage and the other is susceptible to the phage. We observe and quantify the competitive advantage of the bacterial strain bearing the prophage in both invading and in resisting invasion by the bacterial strain sensitive to the phage, and use our experimental measurements to develop a mathematical model of phage-mediated competition. The model predicts, and experimental evidence confirms, that the competitive advantage conferred by the lysogenic phage depends only on the phage pathology on the sensitive bacterial strain and is independent of other phage and host parameters, such as the infection-causing contact rate, the spontaneous and infection-induced lysis rates and the phage burst size. This work combines experimental and mathematical approaches to the study of phage-driven competition, and provides an experimentally tested framework for evaluation of the effects of pathogens/parasites on interspecific competition.

Sensitivity analysis of a computational model of the IKK NF-kappaB IkappaBalpha A20 signal transduction network.

Abstract:  The NF‐κB signaling network plays an important role in many different compartments of the immune system during immune activation. Using a computational model of the NF‐κB signaling network involving two negative regulators, IκBα and A20, we performed sensitivity analyses with three different sampling methods and present a ranking of the kinetic rate variables by the strength of their influence on the NF‐κB signaling response. We also present a classification of temporal‐response profiles of nuclear NF‐κB concentration into six clusters, which can be regrouped to three biologically relevant clusters. Last, we constructed a reduced network of the IKK–NF‐κB–IκBα–A20 signal transduction based on the ranking.

Understanding virulence mechanisms in M. tuberculosis infection via A circuit-based simulation framework

Tuberculosis (TB), caused by the bacterium Mycobacterium tuberculosis (Mtb), is a growing international health crisis. Mtb is able to persist in host tissues in a non-replicating persistent (NRP) or latent state. This presents a challenge in the treatment of TB. Latent TB can re-activate in 10% of individuals with normal immune systems, higher for those with compromised immune systems. A quantitative understanding of latency-associated virulence mechanisms may help researchers develop more effective methods to battle the spread and reduce TB associated fatalities. Leveraging BioXyces ability to simulate whole-cell and multi-cellular systems we are developing a circuit-based framework to investigate the impact of pathogenicity-associated pathways on the latency/reactivation phase of tuberculosis infection. We discuss efforts to simulate metabolic pathways that potentially impact the ability of Mtb to persist within host immune cells. We demonstrate how simulation studies can provide insight regarding the efficacy of potential anti-TB agents on biological networks critical to Mtb pathogenicity using a systems chemical biology approach.

Effects of Noise on Ecological Invasion Processes: Bacteriophage-Mediated Competition in Bacteria

Pathogen-mediated competition, through which an invasive species carrying and transmitting a pathogen can be a superior competitor to a more vulnerable resident species, is one of the principle driving forces influencing biodiversity in nature. Using an experimental system of bacteriophage-mediated competition in bacterial populations and a deterministic model, we have shown in Joo et al. [Proc. R. Soc. B273,1843–1848 (2006)] that the competitive advantage conferred by the phage depends only on the relative phage pathology and is independent of the initial phage concentration and other phage and host parameters such as the infection-causing contact rate, the spontaneous and infection-induced lysis rates, and the phage burst size. Here we investigate the effects of stochastic fluctuations on bacterial invasion facilitated by bacteriophage, and examine the validity of the deterministic approach. We use both numerical and analytical methods of stochastic processes to identify the source of noise and assess its magnitude. We show that the conclusions obtained from the deterministic model are robust against stochastic fluctuations, yet deviations become prominently large when the phage are more pathological to the invading bacterial strain.