Date of Award

6-7-2024

Document Type

Dissertation

Degree Name

Doctor of Philosophy (PhD)

Department

Applied Science

First Advisor

Qingfang He

Abstract

In the world of microorganisms, cyanobacteria are a uniquely skilled powerhouse. They participate in global nutrient and carbon cycling. They can photosynthesize, which allows them to use sunlight and carbon dioxide to produce cellular energy. However, photosynthesis involves a lot of molecular interactions where environmental stresses can interfere, increasing the chances of oxidative stress and nutrient imbalances that can amplify deleterious effects. One such stress, iron limitation, is well-studied and its responses in the cell are known. This study assesses the differences between responses when induced by two different iron limitation methods. Then, a specific stress response regulator DspA, also known as Hik33, is a histidine kinase that perceives and regulates multiple overlapping stress responses was also studied. A program was developed to help automatically process images of Synechocystis cells. A machine learning algorithm was trained to classify images by their cell line. This project found that iron limitation stress, when induced by different methods, exhibited differing severity and expression. TEM images showed that ΔdspA cells also have less organized, abnormal thylakoid membranes compared to WT cells. This project helped illuminate variation in stress responses related to the method of induction. This study also illuminated cellular characteristics related to the inability to thrive observed in ΔdspA cells. The image analysis and classification code in this study helps bring the field of cyanobacteria microscopy analysis into the forefront of current AI-based analysis techniques. These techniques will increase researcher efficiency in preprocessing images and measuring ultrastructural traits. The results of this study add to the body of knowledge about cyanobacteria, ultrastructure, and biological applications of high-powered computational methods.

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