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We investigated the Southern Ocean (SO) prokaryote community structure via zero-radius operational taxonomic unit (zOTU) libraries generated from 16S rRNA gene sequencing of 223 full water column profiles. Samples reveal the prokaryote diversity trend between discrete water masses across multiple depths and latitudes in Indian (71-99°E, summer) and Pacific (170-174°W, autumn-winter) sectors of the SO. At higher taxonomic levels (phylum-family) we observed water masses to harbour distinct communities across both sectors, but observed sectorial variations at lower taxonomic levels (genus-zOTU) and relative abundance shifts for key taxa such as Flavobacteria, SAR324/Marinimicrobia, Nitrosopumilus and Nitrosopelagicus at both epi- and bathy-abyssopelagic water masses. Common surface bacteria were abundant in several deep-water masses and vice-versa suggesting connectivity between surface and deep-water microbial assemblages. Bacteria from same-sector Antarctic Bottom Water samples showed patchy, high beta-diversity which did not correlate well with measured environmental parameters or geographical distance. Unconventional depth distribution patterns were observed for key archaeal groups: Crenarchaeota was found across all depths in the water column and persistent high relative abundances of common epipelagic archaeon Nitrosopelagicus was observed in deep-water masses. Our findings reveal substantial regional variability of SO prokaryote assemblages that we argue should be considered in wide-scale SO ecosystem microbial modelling., (© 2022 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd.)

Global oceanographic monitoring initiatives originally measured abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling programs. There is, however, a large knowledge gap on how to infer bacterial functions, the information sought by biogeochemists, ecologists, and modelers, from the bacterial taxonomic information (produced by bacterial marker gene surveys). Here, we provide a correlative understanding of how a bacterial marker gene (16S rRNA) can be used to infer latitudinal trends for metabolic pathways in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we infer ten metabolic pathways from 16S rRNA gene sequences and 11 corresponding metagenome samples, which relate to metabolic processes of primary productivity, temperature-regulated thermodynamic effects, coping strategies for nutrient limitation, energy metabolism, and organic matter degradation. This study demonstrates that low-cost, high-throughput bacterial marker gene data, can be used to infer shifts in the metabolic strategies at the community scale.