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Marine algae annually sequester petagrams of carbon dioxide into polysaccharides, which are a central metabolic fuel for marine carbon cycling. Diatom microalgae produce sulfated polysaccharides containing methyl pentoses that are challenging to degrade for bacteria compared to other monomers, implicating these sugars as a potential carbon sink. Free-living bacteria occurring in phytoplankton blooms that specialise on consuming microalgal sugars, containing fucose and rhamnose remain unknown. Here, genomic and proteomic data indicate that small, coccoid, free-living Verrucomicrobiota specialise in fucose and rhamnose consumption during spring algal blooms in the North Sea. Verrucomicrobiota cell abundance was coupled with the algae bloom onset and accounted for up to 8% of the bacterioplankton. Glycoside hydrolases, sulfatases, and bacterial microcompartments, critical proteins for the consumption of fucosylated and sulfated polysaccharides, were actively expressed during consecutive spring bloom events. These specialised pathways were assigned to novel and discrete candidate species of the Akkermansiaceae and Puniceicoccaceae families, which we here describe as Candidatus Mariakkermansia forsetii and Candidatus Fucivorax forsetii. Moreover, our results suggest specialised metabolic pathways could determine the fate of complex polysaccharides consumed during algae blooms. Thus the sequestration of phytoplankton organic matter via methyl pentose sugars likely depend on the activity of specialised Verrucomicrobiota populations.

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The formation of sinking particles in the ocean, which promote carbon sequestration into deeper water and sediments, involves algal polysaccharides acting as an adhesive, binding together molecules, cells and minerals. These as yet unidentified adhesive polysaccharides must resist degradation by bacterial enzymes or else they dissolve and particles disassemble before exporting carbon. Here, using monoclonal antibodies as analytical tools, we trace the abundance of 27 polysaccharide epitopes in dissolved and particulate organic matter during a series of diatom blooms in the North Sea, and discover a fucose-containing sulphated polysaccharide (FCSP) that resists enzymatic degradation, accumulates and aggregates. Previously only known as a macroalgal polysaccharide, we find FCSP to be secreted by several globally abundant diatom species including the genera Chaetoceros and Thalassiosira . These findings provide evidence for a novel polysaccharide candidate to contribute to carbon sequestration in the ocean. The fate of ocean carbon is determined by the balance between primary productivity and heterotrophic breakdown of that photosynthate. Here the authors show that diatoms produce a polysaccharide that resists bacterial degradation, accumulates, aggregates and stores carbon during spring blooms.

We investigated Bacteroidetes during spring algae blooms in the southern North Sea in 2010–2012 using a time series of 38 deeply sequenced metagenomes. Initial partitioning yielded 6455 bins, from which we extracted 3101 metagenome-assembled genomes (MAGs) including 1286 Bacteroidetes MAGs covering ~120 mostly uncultivated species. We identified 13 dominant, recurrent Bacteroidetes clades carrying a restricted set of conserved polysaccharide utilization loci (PULs) that likely mediate the bulk of bacteroidetal algal polysaccharide degradation. The majority of PULs were predicted to target the diatom storage polysaccharide laminarin, alpha-glucans, alpha-mannose-rich substrates, and sulfated xylans. Metaproteomics at 14 selected points in time revealed expression of SusC-like proteins from PULs targeting all of these substrates. Analyses of abundant key players and their PUL repertoires over time furthermore suggested that fewer and simpler polysaccharides dominated early bloom stages, and that more complex polysaccharides became available as blooms progressed.

Algal blooms produce large quantities of organic matter that is subsequently remineralised by bacterial heterotrophs. Polysaccharide is a primary component of algal biomass. It has been hypothesised that individual bacterial heterotrophic niches during algal blooms are in part determined by the available polysaccharide substrates present. Measurement of the expression of TonB-dependent transporters, often specific for polysaccharide uptake, might serve as a proxy for assessing bacterial polysaccharide consumption over time. To investigate this, we present here high-resolution metaproteomic and metagenomic datasets from bacterioplankton of the 2016 spring phytoplankton bloom at Helgoland island in the southern North Sea, and expression profiles of TonB-dependent transporters during the bloom, which demonstrate the importance of both the Gammaproteobacteria and the Bacteroidetes as degraders of algal polysaccharide. TonB-dependent transporters were the most highly expressed protein class, split approximately evenly between the Gammaproteobacteria and Bacteroidetes , and totalling on average 16.7% of all detected proteins during the bloom. About 93% of these were predicted to take up organic matter, and for about 12% of the TonB-dependent transporters, we predicted a specific target polysaccharide class. Most significantly, we observed a change in substrate specificities of the expressed transporters over time, which was not reflected in the corresponding metagenomic data. From this, we conclude that algal cell wall-related compounds containing fucose, mannose, and xylose were mostly utilised in later bloom stages, whereas glucose-based algal and bacterial storage molecules including laminarin, glycogen, and starch were used throughout. Quantification of transporters could therefore be key for understanding marine carbon cycling.

Since the discovery of archaeoplankton in 1992, the euryarchaeotal Marine Group II (MGII) remains uncultured and less understood than other planktonic archaea. We characterized the seasonal dynamics of MGII populations in the southern North Sea on a genomic and microscopic level over the course of four years. We recovered 34 metagenome-assembled genomes (MAGs) of MGIIa and MGIIb that corroborated proteorhodopsin-based photoheterotrophic lifestyles. However, MGIIa and MGIIb MAG genome sizes differed considerably (~1.9 vs. ~1.4 Mbp), as did their transporter, peptidase, flagella and sulfate assimilation gene repertoires. MGIIb populations were characteristic of winter samples, whereas MGIIa accounted for up to 23% of the community at the beginning of summer. Both clades consisted of annually recurring, sequence-discrete populations with low intra-population sequence diversity. Oligotyping of filtered cell-size fractions and microscopy consistently suggested that MGII cells were predominantly free-living. Cells were coccoid and ~0.7 µm in diameter, likely resulting in grazing avoidance. Based on multiple lines of evidence, we propose distinct niche adaptations of MGIIa and MGIIb Euryarchaeota populations that are characteristic of summer and winter conditions in the coastal North Sea.

Background The planktonic bacterial community associated with spring phytoplankton blooms in the North Sea is responsible for a large amount of carbon turnover in an environment characterised by high primary productivity. Individual clades belonging to the Gammaproteobacteria have shown similar population dynamics to Bacteroidetes species , and are thus assumed to fill competing ecological niches. Previous studies have generated large numbers of metagenome assembled genomes and metaproteomes from these environments, which can be readily mined to identify populations performing potentially important ecosystem functions. In this study we attempt to catalogue these spring bloom-associated Gammaproteobacteria , which have thus far attracted less attention than sympatric Alphaproteobacteria and Bacteroidetes . Methods We annotated 120 non-redundant species-representative gammaproteobacterial metagenome assembled genomes from spring bloom sampling campaigns covering the four years 2010–2012 and 2016 using a combination of Prokka and PfamScan, with further confirmation via BLAST against NCBI-NR. We also matched these gene annotations to 20 previously published metaproteomes covering those sampling periods plus the spring of 2009. Results Metagenome assembled genomes with clear capacity for polysaccharide degradation via dedicated clusters of carbohydrate active enzymes were among the most abundant during blooms. Many genomes lacked gene clusters with clearly identifiable predicted polysaccharide substrates, although abundantly expressed loci for the uptake of large molecules were identified in metaproteomes. While the larger biopolymers, which are the most abundant sources of reduced carbon following algal blooms, are likely the main energy source, some gammaproteobacterial clades were clearly specialised for smaller organic compounds. Their substrates range from amino acids, monosaccharides, and DMSP, to the less expected, such as terpenoids, and aromatics and biphenyls, as well as many ‘unknowns’. In particular we uncover a much greater breadth of apparent methylotrophic capability than heretofore identified, present in several order level clades without cultivated representatives. Conclusions Large numbers of metagenome assembled genomes are today publicly available, containing a wealth of readily accessible information. Here we identified a variety of predicted metabolisms of interest, which include diverse potential heterotrophic niches of spring bloom-associated Gammaproteobacteria . Features such as those identified here could well be fertile ground for future experimental studies.

There is a growing body of empirical evidence documenting the positive effects associated with participation in environmental education and outdoor learning for students, teachers and the wider community. Despite this, there has been a substantial reduction in outdoor learning opportunities for school students, possibly due to the focus on evidenced-based outcomes, high-stakes standardised testing programs, and a lack of teacher knowledge, confidence and expertise in teaching and learning outdoors. Accordingly, this study presents an evidenced based model to support teaching practice. The model will assist teachers in the development and implementation of outdoor learning opportunities and offers applied examples that address curriculum outcomes. A comprehensive literature review methodology was implemented to identify peer-reviewed literature on teaching and learning outdoors and outdoor pedagogies. A thematic synthesis and constant comparative technique enabled development of themes, from which three themes emerged: the environment; the learner; and the educator, which inform the proposed model offered by the authors. The three interrelated components (the environment, the learner and the educator) require consideration for students to gain maximum benefit from outdoor learning experiences. The model, coupled with the applied examples, supports teachers to plan and facilitate immersive outdoor experiences that promote learning. [Author abstract]

A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. Although these dosing algorithms may have been validated using patients derived from the same centre, rarely have they been validated using a patient cohort recruited from another centre. In order to undertake external validation, two cohorts were utilised. One cohort formed by patients from a prospective trial and the second formed by patients in the control arm of the EU-PACT trial. Of these, 641 patients were identified as having attained stable dosing and formed the dataset used for validation. Predicted maintenance doses from six criterion fulfilling regression models were then compared to individual patient stable warfarin dose. Predictive ability was assessed with reference to several statistics including the R-square and mean absolute error. The six regression models explained different amounts of variability in the stable maintenance warfarin dose requirements of the patients in the two validation cohorts; adjusted R-squared values ranged from 24.2% to 68.6%. An overview of the summary statistics demonstrated that no one dosing algorithm could be considered optimal. The larger validation cohort from the prospective trial produced more consistent statistics across the six dosing algorithms. The study found that all the regression models performed worse in the validation cohort when compared to the derivation cohort. Further, there was little difference between regression models that contained pharmacogenetic coefficients and algorithms containing just non-pharmacogenetic coefficients. The inconsistency of results between the validation cohorts suggests that unaccounted population specific factors cause variability in dosing algorithm performance. Better methods for dosing that take into account inter- and intra-individual variability, at the initiation and maintenance phases of warfarin treatment, are needed.