Publication Date
2024
Document Type
Dissertation/Thesis
First Advisor
Swingley, Wesley D.
Degree Name
Ph.D. (Doctor of Philosophy)
Legacy Department
Department of Biological Sciences
Abstract
Acaryochloris strains can adapt into far red region of the visible spectrum by utilizing its unique chlorophyll called chlorophyll d (Chl d). The genetic machinery behind Chl d has not been discovered yet. Biosynthetic pathway for other chlorophylls like chlorophyll a, chlorophyll b and chlorophyll f found in cyanobacteria are however well known. This research aims to understand the biosynthetic pathway responsible for chlorophyll d production. Bioinformatics approaches like comparative genomics, machine learning, and weighted gene co-expression network analysis (WGCNA) were central in this study to identify candidate genes and regulatory mechanisms potentially involved in chlorophyll d synthesis.
An important result of this study involved the successful draft genome assembly of Synechococcus species KUAC 3056, expanding the available genomic resources of basal strain to Acaryochloris clade. Comparative analysis of this basal strain with Chl d- lacking Acaryochloris thomasi strain RCC 1774, both of which lack chlorophyll d and plasmids, suggested connections between plasmid acquisition and chlorophyll d biosynthesis which was previously pointed out by other studies. Additionally, identified oxygenase-like and thiol-associated proteins present promising candidates for future experimental validation of their roles in Chl d synthesis.
Conjoint triad and Evolutionary Sequence Model (ESM) based feature extraction were performed for the cyanobacterial proteins to train random forest and neural network-based models. Resulting models have high accuracy and were deployed in Acaryochloris marina MBIC11017 to obtain potential candidate proteins involved in Chl d synthesis. The features embeddings of chlorophyll binding proteins were further studied to gain insights into the role of individual amino acids and their combination frequency in interacting with chlorophyll pigment. These models lay the groundwork for future integration with AlphaFold structural data, aiming to refine the predictive framework and enhance our understanding of chlorophyll-binding domain containing proteins.
WGCNA approach provided distinct co-expression modules, with yellow and blue modules displaying relatively strong associations with Acaryochloris strains. Genes within these modules, including photosystem, biosynthetic and hypothetical, might provide a clue to potential regulatory mechanisms of far-red oxygenic photosynthesis. Future work will include broader transcriptomic analyses across various light conditions, further elucidating the adaptive responses in Acaryochloris.
This research altogether advances the existing approach to understand chlorophyll d biosynthesis. The study also provides list of candidate genes which can hopefully be further studied using gene-knockout based studies to validate their potential role in Chl d synthesis.
Recommended Citation
Gautam, Dikshyant, "Leveraging Bioinformatics to Understand Chlorophyll D Biosynthesis in Acaryochloris Spp." (2024). Graduate Research Theses & Dissertations. 8021.
https://huskiecommons.lib.niu.edu/allgraduate-thesesdissertations/8021
Extent
210 pages
Language
en
Publisher
Northern Illinois University
Rights Statement
In Copyright
Rights Statement 2
NIU theses are protected by copyright. They may be viewed from Huskie Commons for any purpose, but reproduction or distribution in any format is prohibited without the written permission of the authors.
Media Type
Text
