Relating the Diversity, Abundance, and Activity of Ammonia-Oxidizing Archaeal Communities to Nitrification Rates in the Coastal Ocean

Abstract:

Ammonia oxidation, the rate-limiting first step of nitrification, is an important link between reduced (ammonia) and oxidized (nitrate) nitrogen, and controls the relative distribution of these forms of inorganic nitrogen. This process is catalyzed via the ammonia monooxygenase enzyme of both ammonia-oxidizing Bacteria (AOB) and Archaea (AOA); the α subunit of this enzyme is encoded by the amoA gene and has been used as the molecular marker to detect this process. In the ocean, AOA are typically 10-1000 times more and are likely more active than AOB, and thus are key players in the marine nitrogen cycle. Monterey Bay is a dynamic site to study nitrification, as seasonal upwelling brings deep water and nutrients into surface waters, which can promote phytoplankton blooms and impact biogeochemical processes such as the nitrogen cycle. We have sampled two sites within Monterey Bay bimonthly for two years as part of the ongoing Monterey Bay Time Series (MBTS) to quantify AOA genes, transcripts, and nitrification rates. Two ecotypes of AOA are routinely found in Monterey Bay – the ‘shallow’ water column A (WCA) and ‘deep’ water column B (WCB) clades, which are thought to have distinct physiological properties and can be distinguished based on the amoA gene sequence. Previous work has shown a strong relationship between nitrification rates in Monterey Bay with the abundance of WCA amoA genes and transcripts. Additionally, we found a correlation between the relative abundance of Marine Group I (MGI) Thaumarchaeota 16S rRNA reads (as % of total) and the absolute abundance of AOA amoA genes (determined via qPCR) in Monterey Bay and the California Current System. AOA 16S rRNA gene abundances in turn correlated significantly with changes in nitrification rate with depth, while the relative abundance of genes and transcripts binned to a single AOA (Nitrosopumilus maritimus) was not significantly correlated to nitrification rate. Further analysis of the sequenced AOA metagenomes and metatranscriptomes will allow us to determine whether nitrification rates correspond to a particular group of AOA, and the inclusion of the MBTS dataset will provide a seasonal framework to allow for predictions of how AOA abundance and activity will be impacted by a changing environment.