Research

Evolutionary Game Theory

Our research is centered on applying Evolutionary Game Theory to understanding evolving social interactions in the animal and microbial worlds. By integrating relevant biological factors and processes into evolutionary game theory models, we aim to provide a deeper understanding of their impacts on community dynamics across space and time. These include resource competition, predation, environmental heterogeneity, and dispersal patterns observed in animal and microbial systems.

Transmission of diseases between wild animals, humans and livestock

In particular, we use microorganisms to build controllable and manipulable model systems to study real-world problems. We use microbes to construct model systems and study them in the laboratory, offering insights into solving pressing societal issues such as disease transmission between wildlife, humans, and livestock, as illustrated in Figure 1. Additionally, our work helps make testable predictions on the repercussions of climate change on biodiversity, and concerns arising from deteriorating soil ecosystem health due to the misuse and overuse of fertilizers, herbicides, and pesticides.

Figure 1. An illustration of the research approach of using microbial communities as model systems to study real-world problems, such as disease transmission between migrating birds and poultry farms. We use different strains of bacteria to represent wild and farm animals, and use a bacteriophage to represent the transmitting pathogen. We then integrate laboratory experiments, mathematical modelling, and computer simulations to study different pathogen spread scenarios and disease control strategies.

Fundamental research in evolutionary biology

To build realistic microbial model systems that can generate reliable predictions and be used to produce and evaluate possible solutions to real-world problems, we take advantage of various cutting-edge technologies. In the computational part, we perform mathematical analysis, numerical resolution, and individual-based simulations using high-performance parallel computation. On the experimental front, we design and 3D-print customized devices to set up high-throughput experiments that can realistically capture the features of natural processes and allow rigorous statistical tests. We also use advanced imaging to record microscopic videos of microbial movements at high temporal resolutions, allowing accurate tracking and analysis of individual bacterial cell behaviors in collective dispersal.

In summary, our work aims to bridge fundamental evolutionary biology research with solving pressing societal problems. We do so by developing Evolutionary Game Theory models and performing experiments using advanced and emerging technologies. An important feature of our work is to use microorganisms to build study systems that capture the interactions in humans and animals. By understanding and possibly manipulating dispersal and other collective behaviors in the model systems, we aim to gain insights that can be applied to the real world.