From populations to single cells: how data shape mathematical models of microbial evolution

Mathematical models have been central to our understanding of microbial population dynamics for decades. Despite major advances in both theory and experiment, the models we use remain closely shaped by what can be measured and by the questions we seek to answer. In this talk, I will argue that many standard models in microbial ecology and evolution can be understood as coarse-grained descriptions of underlying dynamical processes, whose adequacy depends on the scale at which populations are observed. In particular, I will focus on the relationship between population-level measures of growth and the birth and death processes that generate them, and discuss how different combinations of these processes can lead to similar macroscopic behavior while implying distinct evolutionary dynamics. Recent high-resolution measurements at the single-cell level highlight the limitations of such coarse-grained descriptions, revealing extensive cell-to-cell variability even within clonal populations. These observations suggest that the relevant objects of study may often be distributions of cellular states, rather than mean quantities alone, and raise the question of how to appropriately represent microbial populations across scales. More broadly, these examples point to a fundamental problem of coarse-graining: when is a low-dimensional description of a microbial population sufficient, and when does it fail? 

Bio
https://www.ccg.unam.mx/rafael-pena-miller/