This talk discusses combining experimental and theoretical approaches (drawn from graph theory and game theory) to study microbes in diverse scenarios.

First, we present a general, rigorous mathematical framework to address mutagenesis -- from the level of a single protein to the organism level. We theoretically test the effectiveness of our measure in diverse microbial species to capture the reported effects of well-studied mutations and predict new ones. We further examine the usefulness of our procedure on a mutant of Mycobacterium smegmatis mc2155, generated in our lab, which is resistant to the mycobacteriophage D29 and exhibits significant phenotypic alterations [1]. 

Using simple game theoretical modeling, we then show how mass testing and proactiveness affect epidemic spreading [2].

Along the way, we also show that games on scale-free networks may not witness cooperation to the wide extent, as commonly thought [3].


References:
[1] Bioinformatics [Oxford],  37,  213-220 (2021)  
[2] J. Indian Institute of Science [Springer], 101, 371-380 (2021)
[3] Europhysics Letters [EPL], 134, 60002 (2021)