Interdisciplinary PhD in Structural and Computational Biology and Quantitative Biosciences

David Baum

Department of Botany Professor Lab Website 265-5385

242 Birge Hall
430 Lincoln Drive
Madison, WI 53706-1313


B.A., (Hons.), St. Catherine's College, University of Oxford, Botany
Ph.D., Washington University, Evolutionary and Population Biology

Plant phylogenetics; conceptual issues in evolution and systematics; origin of life

My overarching research goal is to understand how evolution works to generate the remarkable diversity of living organisms around us today. Historically, my lab has conducted research in diverse areas of evolutionary biology, with a focus on plants, development, and molecular evolution. My currently focus is on the origin and early evolution of life, specifically the mechanisms by which evolutionary processes initiate during origins of life. This is a fascinating puzzle, with implications for explaining why cells are the way they are and what life might look like elsewhere in the Universe.

We conduct both theoretical and empirical research to address how adaptive evolution got started prior to the emergence of genetic encoding in RNA. Our theoretical work studies chemical reaction networks with a focus on autocatalytic motifs (subnetworks that have the capacity for collective stoichiometric increase in all their members) and the ecological relationships among these motifs. The guiding principle is that the earliest mode of evolution resembled ecological succession where the “species” accumulating over time are not biological species but autocatalytic motifs. With collaborators in physics, math, and computer science, we are using mathematical analysis and stochastic modeling to explore the capacity of chemical ecosystems to show multistability, respond to selection, and accumulate complexity in spatially explicit environments.

Our empirical research entails assembling plausible prebiotic chemical microcosms and looking for quantitative evidence of autocatalysis and evolution-like dynamics. Our main method is chemical ecosystem selection, a strategy for keeping prebiotic mixtures out of equilibrium by recursive dilution with a fresh “food” soup. Changes over time are tracked with high-performance liquid-chromatography mass-spectrometry and other methods to look for non-linear dynamics. Additionally, we have interests in the origins of compartmentalizations and the emergence of functional biopolymers (peptides and RNAs).

A minor, additional focus is on the origin of eukaryotes: a unique evolutionary event that resulted in a quantum leap in cellular complexity. It is quite clear that eukaryogenesis entailed the merger of an archaeal host with the bacterial progenitors of mitochondria, but how that symbiosis proceeded and how it yielded the characteristic structure of eukaryotic cells remains less well understood. The widespread assumption used to be that the nucleus and endomembrane system emerged from outside-in, via invaginations of the bounding plasma membrane. We argued in 2014 that eukaryotes originated from the inside-out when the archaeal ancestor extruded the original plasma membrane into extracellular structures that ultimately transformed into the outer nuclear membrane, endomembrane system, and eukaryotic plasma membrane. The inside-out model has gained increasing support thanks to new data from Asgard archaea.

figure shows examples of the final configuration of stochastic simulations of chemical ecosystems
The figure shows examples of the final configuration of stochastic simulations of chemical ecosystems with two mutually inhibiting autocatalytic cycles (red and blue) on a 2D-surface. Heatmaps show snapshots of hexagonal reaction-diffusion arrays of diameter 39 for different chemical diffusivity values. Each site was seeded with 10 member molecules of each cycle. The top row shows relative dominance of the two cycles. The middle row summarized the extent to which pixels are dominated be one cycle (white) or contain members of both cycles (purple). The bottom row summarizes the average difference in composition between each pixel and its four neighbors. The results show that system complexity is maximized at intermediate diffusion rates.



Professor David Baum

Areas of Expertise

  • Astrobiology
  • Computational Biology & Bioinformatics