Michael Manhart, Ph.D.
Institute of Integrative Biology
8092 Zurich, Switzerland
CHN K18 (ETHZ), BU F13 (Eawag)
michael.manhart AT env.ethz.ch
+41 44 633 60 32
Multiscale mechanisms of microbial evolution
Evolution strongly couples biological phenomena at a wide range of length and time scales — from genetic to intracellular to the scale of whole populations. This is especially important for predicting the effects of mutations, which modify traits at all biological scales, and determining how selection will act on this variation across scales. To this end my group aims to develop a predictive, multiscale theory of evolution. We combine evolutionary biology with biophysics and systems biology, using quantitative laboratory experiments as well as mathematical and computational approaches.
Microorganisms such as bacteria and single-celled fungi are an ideal setting in which to pursue these questions. There has been a renaissance in the study of microbiology, especially the importance of multi-species microbial communities, thanks to the explosion of -omics data and a renewed appreciation for the multifaceted role of microbes in human health and natural ecosystems. Due to the large sizes and rapid time scales of growth for many microbial populations, evolution is an inextricable feature of all microbiological problems: pathogens evolve to escape antibiotic treatment and immune systems; microbiomes evolve to shape bodily functions; directed evolution aims to engineer new strains or communities to degrade pollutants or synthesize materials. And while high-throughput measurements (genomics, metabolomics, transcriptomics, etc.) have enhanced our ability to quantitatively measure properties of microbes at different biological scales, we lack frameworks for synthesizing this information into a holistic theory. Thus the research of my group is poised to address these critical challenges facing evolutionary microbiology.
Currently our work addresses the evolutionary interplay between three key scales in microbes: mutations at the genetic scale, growth traits at the cellular scale (e.g., lag time when switching to a new environment, maximum growth rate, resource efficiency), and lineage dynamics at the population scale. Specifically, we are studying how both genetic mutations and non-genetic variation in cells (e.g., stochastic changes in gene expression) generate variation in growth traits, and how selection acts on this phenotypic variation to determine the evolutionary trajectory of a population. We are developing mathematical models of these phenomena and testing them in laboratory experiments using E. coli and S. cerevisiae. In E. coli we are especially focused on using high-throughput barcoding methods to track rare lineages and mutations. Currently, we are using these tools to understand how ecological interactions mediate the effects of mutations genome-wide.
Last updated: 27 February 2021