Eukaryotic Gene Expression Patterns of Microorganisms in the Amazon River Plume Parallel the Biogeochemistry of Plume Waters

Unraveling the microbiological processes that occur as water travels from a river\u27s mouth into the ocean is critical to understanding the role of river plumes in global biogeochemical cycles. Metranscriptomics, the gene expression of a whole community of organisms, was utilized to examine six stations along the Amazon River Plume (ARP) in 2010 to test thehypothesis that there were measurable differences in gene expression for key biogeochemical genes along the ARP. This body of work focuses on methods developed to identify which genes are biogeochemically important for a particular environment along extreme salinity, nutrient and community gradients in the ARP, and the interpretation of these data. The metatranscriptome of a marine algal bloom of Protoperidinium quinquecorne was collected, as a pilot study, and represented the first published eukaryotic marine algal bloom metatranscriptome. Of the 232 transcripts examined, over 70% were eukaryotic mRNAs, thus demonstrating the successful isolation of eukaryotic transcripts from ribosomal RNAs and prokaryotic RNAs. Transcripts for nutrient and carbon uptake were identified, and reinforced the theory that biogeochemically-relevant genes will be amongst the highly-expressed genes in eukaryotic phytoplankton populations. The final two sections of this dissertation detail two different ways to bioinformatically examine metatranscriptomes from the eukaryotic microbial populations of the ARP. The reproducibility of metatranscriptomes was confirmed with very similar patterns of gene expression between true replicates differing by up to 2 hours and 2.5 km. Similar communities, two diatom-diazatroph association (DDA) stations, also showed stability of expression patterns over 25 days and 238.3 km. A gene database of 31 biogeochemical genes was used to enumerate transcript counts for the six different stations along the ARP. Patterns of gene expression reflected the major physical, chemical and biological influences in those communities. DDA blooms exhibited high silicon transporter expression to acquire silicon for diatoms, and the photosystem II D1 protein replacement was high in these low-turbidity blooms. In a low salinity (salinity 20.7) diatom bloom, nitrate transport genes were highly expressed to account for high growth rates fueled by photosynthesis, and carbonic anhydrase helped counter the low pCO2 waters. The last chapter compares all the sequences to the entire protein family (pfam) library to annotate all possible transcripts for important processes missed with a 31-gene database approach. Pfams for chlorophyll A-B binding protein and bacteriorhodopsin-like proteins ranked among the most-expressed pfams. These two pfams together show evolutionary adaptations to maximize ATP generation in surface community algal blooms. Multidimensional scaling plots illustrated that the patterns of gene expression were unique to each station. This body of work will expand our understanding of river plume eukaryotic phytoplankton communities, and when these data are added to metagenome, prokaryote metatranscriptome and modeling data, modelers will be able to better forecast diversity, transcription and community evolution over broad space and time scales