Fitness, the competitive advantage of an organism or gene, is the basis for adaptation and the emergence of complexity in biology. Competitive advantage is contextual, as it is affected by environmental pressures and ecological interactions. To enable experiments with complex environmental dynamics, we developed eVOLVER, a novel platform for scalable programmable continuous culture. In this thesis, we apply eVOLVER to interrogate how competitive outcomes between strains change according to environmental conditions.
Using soil microbe communities as a model ecological system, we tuned dilution rate and frequency across 112 cultures in eVOLVER and observed replicable changes in composition and diversity. Our experimental results challenge intuition about the relationship between diversity and disturbance. In collaborative work, we compared different models of competitive growth in simulations. A Monod growth model outperforms Lotka-Volterra and linear consumer resource models at predicting the effect of varying dilution profiles on microbial diversity. We hypothesize that trade-offs in growth rate and nutritional requirements (r/K) create distinct niches which permit coexistence at certain mortality rates, but collapse under others. These findings suggest a mechanism that potentially affects diversity-disturbance relationships, and confirm that temporal fluctuations can promote diversity.
In separate studies, we apply these methods and concepts to 1) study selection on a genome-scale library in yeast under conditions of fluctuating temperature stress in eVOLVER and 2) evaluate the persistence of engineered microbial spores relative to native strains in different “real-world” environments (e.g. soil) and perturbations. Broadly, this dissertation demonstrates that the combination of next-generation sequencing and scalable programmable culture technologies finally enables the types of experiments needed to test decades of theoretical work in ecology and evolution. / 2021-05-18T00:00:00Z
| Identifer | oai:union.ndltd.org:bu.edu/oai:open.bu.edu:2144/41027 |
| Date | 19 May 2020 |
| Creators | Mancuso, Christopher Patrick |
| Contributors | Khalil, Ahmad S. |
| Source Sets | Boston University |
| Language | en_US |
| Detected Language | English |
| Type | Thesis/Dissertation |
| Rights | Attribution-ShareAlike 4.0 International, http://creativecommons.org/licenses/by-sa/4.0/ |
Page generated in 0.0021 seconds