defense announcement

I am defending a thesis where I will present my contributions to the field. Mostly in microbiology, some in statistics.
I’ve decided to publicize, appreciating the way that science benefits the society.

PhD Thesis Defense Announcement

Title: Bioinstrumentation and Statistical Methods for Investigating Host-Microbial Interactions
Candidate: Hyungseok Kim
Date: April 28th, 2023
Time: 1:00–2:30 pm (Eastern Time)
Location: Hybrid. In person at MIT 3-333. Zoom Link

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Abstract
Metabolic interactions between hosts and their associated microbiota, the latter referred to as the microbiome, contribute to the host phenotype and nutrient cycling within the ecosystem. There is broad diversity in the type and complexity of interactions for a given host and environment. Quantitative and qualitative resolution of the associations between hosts and the microbiome remain a key challenge in modern microbiology.

The universal mechanism of interaction is the diffusive exchange of metabolites. In the first part of this thesis, I propose a microbial co-culture assay (“porous microplate”) that spatially controls diffusion mediated metabolite exchange. Using a model host alga Phaeodactylum tricornutum, I describe bacterial responses to algal metabolites in the porous microplate. I extend the findings to provide an insight into how different bacterial species partition host nutrients.

The host-microbiota relationship requires proximity between the organisms, and it is strengthened by physical attachment. In the second part of this thesis, I utilize a microfluidic electrokinetic platform to characterize bacterial surfaces and their envelope components. The motivation for this is to ascertain the influence of surface charge on physical attachment. The results indicate that bacterial surface charge is correlated with the ability to attach to the algal host and the production of extracellular polymeric substances.

Lastly, I introduce a multivariate analysis technique to visualize microbial community structure. I explain how statistical hypothesis testing can be simultaneously addressed while reducing its dimensionality. I verify the technique’s performance by comparing it to an existing dimensionality reduction method.

Taken together, the combined microfluidic and data analysis approaches developed can help bridge several technological gaps in microbial ecology.

Thesis Committee:
Prof. Cullen R. Buie, MIT (Advisor / Chair)
Dr. Xavier Mayali, LLNL
Prof. Themistoklis Sapsis, MIT
Prof. Xuanhe Zhao, MIT

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