Frontiers in Marine Science (Jan 2021)
An Integrative Model of Carbon and Nitrogen Metabolism in a Common Deep-Sea Sponge (Geodia barretti)
Abstract
Deep-sea sponges and their microbial symbionts transform various forms of carbon (C) and nitrogen (N) via several metabolic pathways, which, for a large part, are poorly quantified. Previous flux studies on the common deep-sea sponge Geodia barretti consistently revealed net consumption of dissolved organic carbon (DOC) and oxygen (O2) and net release of nitrate (NO3-). Here we present a biogeochemical metabolic network model that, for the first time, quantifies C and N fluxes within the sponge holobiont in a consistent manner, including many poorly constrained metabolic conversions. Using two datasets covering a range of individual G. barretti sizes (10–3,500 ml), we found that the variability in metabolic rates partially resulted from body size as O2 uptake allometrically scales with sponge volume. Our model analysis confirmed that dissolved organic matter (DOM), with an estimated C:N ratio of 7.7 ± 1.4, is the main energy source of G. barretti. DOM is primarily used for aerobic respiration, then for dissimilatory NO3- reduction to ammonium (NH4+) (DNRA), and, lastly, for denitrification. Dissolved organic carbon (DOC) production efficiencies (production/assimilation) were estimated as 24 ± 8% (larger individuals) and 31 ± 9% (smaller individuals), so most DOC was respired to carbon dioxide (CO2), which was released in a net ratio of 0.77–0.81 to O2 consumption. Internally produced NH4+ from cellular excretion and DNRA fueled nitrification. Nitrification-associated chemoautotrophic production contributed 5.1–6.7 ± 3.0% to total sponge production. While overall metabolic patterns were rather independent of sponge size, (volume-)specific rates were lower in larger sponges compared to smaller individuals. Specific biomass production rates were 0.16% day–1 in smaller compared to 0.067% day–1 in larger G. barretti as expected for slow-growing deep-sea organisms. Collectively, our approach shows that metabolic modeling of hard-to-reach, deep-water sponges can be used to predict community-based biogeochemical fluxes and sponge production that will facilitate further investigations on the functional integration and the ecological significance of sponge aggregations in deep-sea ecosystems.
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