My research is motivated by three overarching questions:

  • What is a system’s capacity to adaptively evolve in response to different selection pressures?
  • What are factors that influence this capacity to adaptively evolve?
  • How do we measure this capacity to adaptively evolve?

I think of evolvability (defined by Riederer et al. (2022) as the capacity of a (biological) system to adaptively evolve) as a useful framework to encapsulate all of these questions. However, evolvability as a field is fraught with disagreement, namely because there is confusion and debate on how exactly we should define it and how it should be measured. Hence, in my research, as I aim to address these three questions, I also hope to offer clarity to the evolvability research front by embarking on a mechanistic understanding of evolvability, using microbes as my study systems.

At present, I focus on how mechanisms shaping the genotype-phenotype(-fitness) map of a given biological system enhance or constraint its evolvability. In other words, how do mechanisms that are involved in the flow of genetic information shape the phenotypic variation for selection to act on (which can affect a biological system’s evolvability)? Below, I describe some of my past, present, and future projects:

How do mechanisms of the genotype-phenotype map contribute to evolvability?

Part of my work involves investigating how specific mechanisms that shape translation of the genotype into the phenotype can affect the evolvability of a microbial system. Examples of mechanisms in the genotype-phenotype map that I’ve been interested it include epistasis (gene-gene interactions) and proteostasis (protein homeostasis). I have been approaching this question through theoretical and experimental approaches, so look out for more updates on this in the future!

Context-dependence and evolvability in fitness landscapes

In addition to focusing on specific mechanisms of the genotype-phenotype map, I am also interested in the genotype-phenotype-fitness space as a whole (i.e., fitness landscapes) to both understand how environmental context shapes adaptive evolution, and in using fitness landscapes as a system to conceptualize measuring evolvability. We have proposed a framework for deconstructing various features of fitness seascapes (i.e., fitness landscapes that also integrate environmental context). Ongoing work on fitness landscapes involves testing existing and developing new frameworks for measuring evolvability in fitness landscapes. Look out for more updates on this in the future!

Mathematical modelling of infectious disease dynamics

While not strictly part of the “evolvability” umbrella of my research interests, I am also generally interested in understanding and predicting the epidemiological, ecological, and/or evolutionary dynamics of infectious diseases. I utilized mathematical modelling to understand how asymptomatic infections with direct recovery could shape the evolutionary dynamics of a pathogen. I have also contributed to a study utilizing causal inference to quantify the impact of social disparities on infectious disease epidemiology.