Date of Award
2026
Degree Type
Dissertation
Degree Name
Doctor of Philosophy in Oceanography
Specialization
Biological Oceanography
Department
Oceanography
First Advisor
Keisuke Inomura
Abstract
Microorganisms are microscopic, typically unicellular organisms widely distributed across the world’s environments. In the global ocean, they account for the majority of primary production and decompose organic matter to drive nutrient cycles. Through their metabolic processes, including photosynthesis, dinitrogen (N2) fixation, sulfur oxidation, and methanogenesis, microbes contribute to global biogeochemical processes, and establish their ecological niches in suitable habitats. Their biological interactions, including competition, symbiosis, and grazing, are important links among different functional groups in marine communities. Consequently, quantifying microbial metabolisms and their biological interactions is important to investigate their ecological functions in marine ecosystems and the global ocean.
However, quantitative studies of some microorganisms remain limited. Many of their biological processes are difficult to quantify through measurement, making modeling an important tool for simulating microbial mechanisms and supporting empirical studies. This dissertation applies coarse-grained models to simulate various microorganisms in different ecological scales. The complexity of our models lies between simple equation models and detailed metabolic models, balancing resolution and computational efficiency.
The one-cell-level model is for Trichodesmium, one of the dominant N2-fixing phytoplankton in the ocean. Previous studies have shown that Trichodesmium can rapidly fluctuate photosynthetic activity within the same cells. Here we model key cellular processes based on this observation, including photosynthesis, respiration, biosynthesis, and N2fixation. We calculated intracellular O2 dynamics, and elemental carbon (C) and nitrogen (N) allocation under two alternating physiological states: a photosynthetic state and a non-photosynthetic state. The model results suggested that rapid switching between two states can facilitate growth and optimize C and N allocation. This work highlights the importance of fluctuating photosynthetic activity and provides a mechanistic framework for understanding how Trichodesmium can sustain daytime N2 fixation under aerobic conditions in the global ocean.
As for the next level - one symbiotic group, we develop the metabolic model for diatom - diazotroph associations (DDAs), one of the essential symbiotic dinitrogen (N2)-fixing groups in the oligotrophic ocean. We simulate the effects of extracellular ammonium (NH4+) on growth rates, metabolic pathways, and nutrient transfer between symbionts. The simulations show that, at a fixed growth rate, increasing NH4+ concentrations can decrease N2 fixation and photosynthesis, and reduce carbon (C) and nitrogen (N) transfer between cells. In contrast, lower NH4+ concentrations enhance nutrient exchange and increase N2 fixation rates. This study demonstrates a strong effect of NH4+ on metabolic processes within DDAs and thus highlights the importance of in situ measurement of NH4+ concentrations.
Next, we built metabolic models representing nine chemotrophic N2-fixing groups, including their potential biochemical pathways, electron transport, and energy flow, to predict whole-cell stoichiometries. By balancing mass, electrons, and energy for metabolic half-reactions, we quantify electron allocation in each N2 fixer. In our results, all modeled organisms fix sufficient N2 for growth, but aerobic groups allocate more electrons to N2 fixation and biomass production, achieving higher growth rates and N2 fixation, whereas methanogens utilizing acetate and organisms utilizing sulfate allocate fewer electrons. This framework provides a mechanistic tool for exploring the depth distribution of N2 fixers in response to nutrient availability and also complements field observations of microbial communities and their biogeochemical processes.
At the ecosystem scale, we model kelp-phytoplankton competition and distribution in the coastal ocean. Our model includes important physical and biological pathways, e.g, nutrient uptake, growth, mortality, remineralization, water movement, and upwelling. We compare the simulated distributions of kelp and phytoplankton and find that in coastal, high-nutrient areas, kelp can accumulate greater biomass than phytoplankton because they are anchored and do not advect with the water, which provides a niche for them. Slower water speed can eliminate kelp’s advantage, which may explain the effect of El Niño and La Niña on kelp forests. This study provided a framework for coastal upwelling. It can be used to predict the impacts of climate change on coastal ecosystems.
This dissertation presents the application of coarse-grained models across different levels of biological research. At the cellular level, coarse-grained models can simulate the mechanisms and quantify the rates and yield. In symbiotic groups, our models can investigate interactions between hosts and symbionts and discuss the effects of environmental factors on these interactions. The nine N2-fixing metabolic models demonstrate the models' potential for biochemical prediction and enable comparisons across metabolic groups. The modeled kelp-phytoplankton comparison presents the application in the coastal ecosystems with changing environmental factors. By modeling metabolic activities and biological interactions at multiple levels, this dissertation examines how different microbes build their survival metabolisms, thereby acquiring their ecological niches in the ocean.
Creative Commons License
This work is licensed under a Creative Commons Attribution 4.0 License.
Recommended Citation
Gao, Meng, "COARSE-GRAINED MODELS FOR MICROBIAL METABOLISMS AND BIOLOGICAL INTERACTIONS" (2026). Open Access Dissertations. Paper 4542.
https://digitalcommons.uri.edu/oa_diss/4542