A new genomic taxonomy system for the Synechococcus collective.

Cyanobacteria of the genus Synechococcus are major contributors to global primary productivity and are found in a wide range of aquatic ecosystems. This Synechococcus collective (SC) is metabolically diverse, with some lineages thriving in polar and nutrient-rich locations and others in tropical or riverine waters. Although many studies have discussed the ecology and evolution of the SC, there is a paucity of knowledge on its taxonomic structure. Thus, we present a new taxonomic classification framework for the SC based on recent advances in microbial genomic taxonomy. Phylogenomic analyses of 1085 cyanobacterial genomes demonstrate that organisms classified as Synechococcus are polyphyletic at the order rank. The SC is classified into 15 genera, which are placed into five distinct orders within the phylum Cyanobacteria: (i) Synechococcales (Cyanobium, Inmanicoccus, Lacustricoccus gen. Nov., Parasynechococcus, Pseudosynechococcus, Regnicoccus, Synechospongium gen. nov., Synechococcus and Vulcanococcus); (ii) Cyanobacteriales (Limnothrix); (iii) Leptococcales (Brevicoccus and Leptococcus); (iv) Thermosynechococcales (Stenotopis and Thermosynechococcus) and (v) Neosynechococcales (Neosynechococcus). The newly proposed classification is consistent with habitat distribution patterns (seawater, freshwater, brackish and thermal environments) and reflects the ecological and evolutionary relationships of the SC.

Unlocking the Genomic Taxonomy of the Prochlorococcus Collective.

Prochlorococcus is the most abundant photosynthetic prokaryote on our planet. The extensive ecological literature on the Prochlorococcus collective (PC) is based on the assumption that it comprises one single genus comprising the species Prochlorococcus marinus, containing itself a collective of ecotypes. Ecologists adopt the distributed genome hypothesis of an open pan-genome to explain the observed genomic diversity and evolution patterns of the ecotypes within PC. Novel genomic data for the PC prompted us to revisit this group, applying the current methods used in genomic taxonomy. As a result, we were able to distinguish the five genera: Prochlorococcus, Eurycolium, Prolificoccus, Thaumococcus, and Riococcus. The novel genera have distinct genomic and ecological attributes.

"Pink power"-the importance of coralline algal beds in the oceanic carbon cycle.

Current evidence suggests that macroalgal-dominated habitats are important contributors to the oceanic carbon cycle, though the role of those formed by calcifiers remains controversial. Globally distributed coralline algal beds, built by pink coloured rhodoliths and maerl, cover extensive coastal shelf areas of the planet, but scarce information on their productivity, net carbon flux dynamics and carbonate deposits hampers assessing their contribution to the overall oceanic carbon cycle. Here, our data, covering large bathymetrical (2-51 m) and geographical ranges (53°N-27°S), show that coralline algal beds are highly productive habitats that can express substantial carbon uptake rates (28-1347 g C m-2 day-1), which vary in function of light availability and species composition and exceed reported estimates for other major macroalgal habitats. This high productivity, together with their substantial carbonate deposits (0.4-38 kilotons), renders coralline algal beds as highly relevant contributors to the present and future oceanic carbon cycle.

Metaphor-A workflow for streamlined assembly and binning of metagenomes.

Recent advances in bioinformatics and high-throughput sequencing have enabled the large-scale recovery of genomes from metagenomes. This has the potential to bring important insights as researchers can bypass cultivation and analyze genomes sourced directly from environmental samples. There are, however, technical challenges associated with this process, most notably the complexity of computational workflows required to process metagenomic data, which include dozens of bioinformatics software tools, each with their own set of customizable parameters that affect the final output of the workflow. At the core of these workflows are the processes of assembly-combining the short-input reads into longer, contiguous fragments (contigs)-and binning, clustering these contigs into individual genome bins. The limitations of assembly and binning algorithms also pose different challenges depending on the selected strategy to execute them. Both of these processes can be done for each sample separately or by pooling together multiple samples to leverage information from a combination of samples. Here we present Metaphor, a fully automated workflow for genome-resolved metagenomics (GRM). Metaphor differs from existing GRM workflows by offering flexible approaches for the assembly and binning of the input data and by combining multiple binning algorithms with a bin refinement step to achieve high-quality genome bins. Moreover, Metaphor generates reports to evaluate the performance of the workflow. We showcase the functionality of Metaphor on different synthetic datasets and the impact of available assembly and binning strategies on the final results.