Michael Walter Doebeli

Professor

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Graduate Student Supervision

Doctoral Student Supervision (Jan 2008 - Nov 2019)
The Ecology of Microbial Metabolic Pathways (2016)

Microbial metabolic activity drives biogeochemical cycling in virtually every ecosystem. Yet, microbial ecology and its role in ecosystem biochemistry remain poorly understood, partly because the enormous diversity found in microbial communities hinders their modeling. Despite this diversity, the bulk of global biogeochemical fluxes is driven by a few metabolic pathways encoded by a small set of genes, which through time have spread across microbial clades that can replace each other within metabolic niches. Hence, the question arises whether the dynamics of these pathways can be modeled regardless of the hosting organisms, for example based on environmental conditions. Such a pathway-centric paradigm would greatly simplify the modeling of microbial processes at ecosystem scales.Here I investigate the applicability of a pathway-centric paradigm for microbial ecology. By examining microbial communities in replicate "miniature" aquatic environments, I show that similar ecosystems can exhibit similar metabolic functional community structure, despite highly variable taxonomic composition within individual functional groups. Further, using data from a recent ocean survey I show that environmental conditions strongly explain the distribution of microbial metabolic functional groups across the world's oceans, but only poorly explain the taxonomic composition within individual functional groups. Using statistical tools and mathematical models I conclude that biotic interactions, such as competition and predation, likely underlie much of the taxonomic variation within functional groups observed in the aforementioned studies. The above findings strongly support a pathway-centric paradigm, in which the distribution and activity of microbial metabolic pathways is strongly determined by energetic and stoichiometric constraints, whereas additional mechanisms shape the taxonomic composition within metabolic guilds. These findings motivated me to explore concrete pathway-centric mathematical models for specific ecosystems. Notably, I constructed a biogeochemical model for Saanich Inlet, a seasonally anoxic fjord with biogeochemistry analogous to oxygen minimum zones. The model describes the dynamics of individual microbial metabolic pathways involved in carbon, nitrogen and sulfur cycling, and largely explains geochemical depth profiles as well as DNA, mRNA and protein sequence data. This work yields insight into ocean biogeochemistry and demonstrates the potential of pathway-centric models for microbial ecology.

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Five Studies in Life History Evolution (2011)

Assortative mating by fitness has the potential population-level benefit of reducing migration load during times of environmental stasis, while allowing introgression of immigrant genetic variation in the event of environmental change. Assortative mating by fitness was examined with respect to within-population spread of a recombination modifier under selective sweep and mutation-selection balance scenarios. Only the latter scenario boosted modifier frequency, given a strength of assortative mating unlikely to be present in most species.In a second attempt to identify a new general advantage for sexual reproduction, the focus was on how inter-individual reproduction might reduce noise in inheritance and increase the power of selection. Individuals can experience good and bad "luck" at various stages of their life history, in any habitat, and it was found that combining gametes from two separate experiences of this ecological noise could indeed reduce noise in inheritance.The puzzle of small mammal population density cycles was approached from an evolutionary, rather than a population regulation perspective. An appropriate pattern of reproductive effort would seem key to survival through repeated population crashes to low numbers. Small mammals reproduce below their apparent potential through the decline and into the low phase of a cycle, and determining whether this reproductive pattern is adaptive is an important question. A standard cycling analytical model, the Rosenzweig-MacArthur, was carefully examined for the basis of this life history work, and found wanting even after considering several modifications. So an individual-based simulation was done. For simplicity and generality a novel mechanism was used: the "cumulative recent activity" of a population predicts several mortality causes, and has the property of delayed density dependence required to drive cycles. If animals cue from this quantity, then some controversy-causing experimental results might be explained.Branching theory and the simulation model showed that reproductive slowdown evolves under high mortality rates and, given a premium on short term persistence such as might exist at low numbers or densities, at low mortality rates. This explains the reproductive pattern observed in cycling mammals. The known reproductive suppression by stress physiology now appears to be adaptive, rather than inadvertent.

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Adaptive Diversification in Experimental Populations of Escherichia coli (2010)

No abstract available.

Master's Student Supervision (2010 - 2018)
Adaptation in E. coli: Ecological and genetic constraints on diversification (2014)

There is growing evidence that disruptive selection generated by intraspecific resource competition may be a common mechanism for generating biological diversity. Adaptive dynamics models provide a framework describing how frequency dependent selection drives such diversification, but these models don’t consider the complexities that arise as a result of gene interactions. Here, we explore the relative effects of ecological and genetic constraints on diversification using an experimental system of Escherichia coli in which diversification is driven by frequency dependence based on resource use. Diversified populations consist of ecotypes that consume glucose and ac- etate at different rates, and a mutation in the arcA gene has been identified that has a large effect on this phenotype. By isolating clones of each eco- type from a previously diversified population, we find that the effect of the arcA mutation on rediversification depends on both the ecotype and the genetic background. While some of these observations are consistent with predictions made by adaptive dynamics models, others cannot be explained without also accounting for epistasis and genetic constraints, highlighting the importance of considering both ecological and genetic factors when pre- dicting diversification. Adaptation in this system also provides an example of an interaction between ecological and evolutionary processes, adding to a growing number of studies that exhibit a clear feedback between these two processes.

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