Marine cyanobacteria have developed many genetic defenses in response to viral infection. Similar defense genes have been found in diverse groups of cyanobacteria, suggesting different modes of evolution for defense genes. Berube et. al (2018) identified novel cyanobacterial clusters of orthologous genes (CyCOGs), families of genes with similar genetic sequences. However many of these CyCOGs remain uncharacterized. The goal of my study was to characterize an uncharacterized CyCOG called 60001830, which is expressed in the marine cyanobacteria Prochlorococcus and Synechococcus, and when expressed is correlated with the genes of viruses that infect cyanobacteria (cyanophages). This suggests CyCOG 60001830 has an adaptive response to the presence of cyanophages, which would make it a family of defense genes. Using phylogenetic analysis, I resolved the evolutionary history of CyCOG 60001830 by comparing it to the evolutionary history of a key gene in host genomes. I compared the phylogeny of CyCOG 60001830 to the phylogeny of RecA, a highly conserved and essential gene present in all Prochlorococcus and Synechococcus species because of its key role in DNA repair and/or maintenance. CyCOG 60001830 does not share the same evolutionary pattern as RecA, which suggests that it does not follow a pattern of vertical gene transfer but rather horizontal gene transfer, genes being exchanged between neighboring bacteria. Viral defense genes evolve rapidly in an evolutionary arms race between bacteria and phages, so CyCOG 60001830’s evolutionary pattern makes sense as horizontal gene transfer operates faster than vertical gene transfer.

Protozoa are a diverse field of organisms that impact trophic transfer in marine ecosystems, constituting an important link between producers and higher trophic levels. In this study, I focused on determining how protozoan grazing rates differ in nutrient-rich and poor ecosystems. I used a CTD rosette to collect six seawater samples along the equatorial transect of five degrees south to five degrees north at stations: 5°S,2°S, 1°S, 0°, 1°N, 4°N, and 5°N. These samples were filtered to 10 microns and divided into isolated incubation cultures with 0, 25, and 90 percent dilution of 0.2 micron filtered seawater. Change in Chlorophyll was used to infer the phytoplankton growth rate across the dilution factors. Using a linear model of growth rate by dilution factor, a grazing rate was determined for each sample. Nutrients from the water samples were measured for nitrate, phosphate, and silicate concentrations. A series of linear regression analyses of the protozoan grazing rates by in situ nutrient concentrations were then done to determine the correlation between parameters. The growth rates of phytoplankton ranged from -5.2e-4 day-1 to 3.2e-2 day-1. Ambient nitrate, silicate, and phosphate concentrations reached 2.25 mM, 2.18 mM, and 0.46 mM respectively. Surface temperatures reached 30.46 centigrade, and the grazing rate exhibited a decreasing trend with higher temperatures, eventually reaching zero at 30.3 degrees. As eutrophication events become increasingly common due to climate change and anthropogenic pollution, it is important to determine how protozoan communities respond to changes in dissolved nutrients.

Marine microbes produce over half of the world’s oxygen and are major greenhouse gas processors. These tiny organisms are vital to life on Earth as they cycle nutrients through marine microbial communities via metabolic pathways that are not yet fully characterized. We gain insight into how key compounds are cycled throughout different environments and microbial communities by studying transporter proteins as they mediate nutrient uptake and export in microbes. We aim to compare the abundance of transporters between marine microbial communities by translating and processing sequence data obtained from sequencing the RNA in water samples from multiple locations, capturing a diverse range of organism's genetic information. Currently, there is no standard methodology for identifying genes of transporter proteins from environmental sequence data. We developed a bioinformatic pipeline that identifies transporter genes and allows them to be characterized according to a standardized transporter classification system. This pipeline annotates amino acid sequences from oceanic samples with mathematical models to identify transporters and then annotates these results with taxonomic information. The pipeline enables us to compare transporter abundances between different marine microbial communities, which can be used to infer and map nutrient flow through marine microbial communities.