Marine microbes along with microeukaryotes are key regulators of oceanic biogeochemical pathways. Here we present a high-resolution (every 0.5° of latitude) dataset describing microbial pro- and eukaryotic richness in the surface and just below the thermocline along a 7,000-km transect from 66°S at the Antarctic ice edge to the equator in the South Pacific Ocean. The transect, conducted in austral winter, covered key oceanographic features including crossing of the polar front (PF), the subtropical front (STF), and the equatorial upwelling region. Our data indicate that temperature does not determine patterns of marine microbial richness, complementing the global model data from Ladau et al. [Ladau J, et al. (2013) ISME J 7:1669-1677]. Rather, NH, nanophytoplankton, and primary productivity were the main drivers for archaeal and bacterial richness. Eukaryote richness was highest in the least-productive ocean region, the tropical oligotrophic province. We also observed a unique diversity pattern in the South Pacific Ocean: a regional increase in archaeal and bacterial diversity between 10°S and the equator. Rapoport's rule describes the tendency for the latitudinal ranges of species to increase with latitude. Our data showed that the mean latitudinal ranges of archaea and bacteria decreased with latitude. We show that permanent oceanographic features, such as the STF and the equatorial upwelling, can have a significant influence on both alpha-diversity and beta-diversity of pro- and eukaryotes.
Sustained observations of microbial dynamics are rare, especially in southern hemisphere waters. The Australian Marine Microbial Biodiversity Initiative (AMMBI) provides methodologically standardized, continental scale, temporal phylogenetic amplicon sequencing data describing Bacteria, Archaea and microbial Eukarya assemblages. Sequence data is linked to extensive physical, biological and chemical oceanographic contextual information. Samples are collected monthly to seasonally from multiple depths at seven sites: Darwin Harbour (Northern Territory), Yongala (Queensland), North Stradbroke Island (Queensland), Port Hacking (New South Wales), Maria Island (Tasmania), Kangaroo Island (South Australia), Rottnest Island (Western Australia). These sites span ~30° of latitude and ~38° longitude, range from tropical to cold temperate zones, and are influenced by both local and globally significant oceanographic and climatic features. All sequence datasets are provided in both raw and processed fashion. Currently 952 samples are publically available for bacteria and archaea which include 88,951,761 bacterial (72,435 unique) and 70,463,079 archaeal (24,205 unique) 16 S rRNA v1-3 gene sequences, and 388 samples are available for eukaryotes which include 39,801,050 (78,463 unique) 18 S rRNA v4 gene sequences.
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.
Summary 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.
In a previous study, notable differences of several physicochemical properties, as well as the community structure of ammonia oxidizing bacteria as judged by 16S rRNA gene analysis, were observed among several disused tin-mining ponds located in the town of Kampar, Malaysia. These variations were associated with the presence of aquatic vegetation as well as past secondary activities that occurred at the ponds. Here, methane oxidizing bacteria (MOB), which are direct participants in the nutrient cycles of aquatic environments and biological indicators of environmental variations, have been characterised via analysis of pmoA functional genes in the same environments. The MOB communities associated with disused tin-mining ponds that were exposed to varying secondary activities were examined in comparison to those in ponds that were left to nature. Comparing the sequence and phylogenetic analysis of the pmoA clone libraries at the different ponds (idle, lotus-cultivated and post-aquaculture), we found pmoA genes indicating the presence of type I and type II MOB at all study sites, but type Ib sequences affiliated with the Methylococcus/Methylocaldum lineage were most ubiquitous (46.7 % of clones). Based on rarefaction analysis and diversity indices, the disused mining pond with lotus culture was observed to harbor the highest richness of MOB. However, varying secondary activity or sample type did not show a strong variation in community patterns as compared to the ammonia oxidizers in our previous study.
Global oceanographic monitoring initiatives started by measuring abiotic essential ocean variables but are currently incorporating biological and metagenomic sampling. There is, however, a large gap between the taxonomic information produced by bacterial genomic analyses and information on bacterial functions, which is sought by biogeochemists, ecologists, and modellers. Here, we provide a mechanistic understanding of how a bacterial marker gene (16S rRNA) can be used to derive latitudinal trends for core metabolic pathways and, ultimately, be used for mapping ecosystem function change in global monitoring campaigns. From a transect spanning 7000 km in the South Pacific Ocean we identified ten metabolic pathways, which were related to ecological processes of primary productivity, temperature-regulated growth, coping strategies for nutrient limitation, energy metabolism, and degradation. We compared and contrasted these metabolic pathways with measured physico-biochemical parameters within and between oceanographic provinces, and found that functional diversity is as affected by oceanographic boundaries as is taxonomic composition. This study demonstrates that bacterial marker gene data, sampled and analysed with low costs and high throughput, can be used to infer on metabolic changes at the community scale. Such analyses may provide insight into the drivers of ecological changes and, overall, into the effects of biodiversity on marine ecosystem functioning.
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