Metagenome-assembled genomes uncover a global brackish microbiome

Abstract

BackgroundMicrobes are main drivers of biogeochemical cycles in oceans and lakes. Although the genome is a foundation for understanding the metabolism, ecology and evolution of an organism, few bacterioplankton genomes have been sequenced, partly due to difficulties in cultivating them.ResultsWe use automatic binning to reconstruct a large number of bacterioplankton genomes from a metagenomic time-series from the Baltic Sea, one of world’s largest brackish water bodies. These genomes represent novel species within typical freshwater and marine clades, including clades not previously sequenced. The genomes’ seasonal dynamics follow phylogenetic patterns, but with fine-grained lineage-specific variations, reflected in gene-content. Signs of streamlining are evident in most genomes, and estimated genome sizes correlate with abundance variation across filter size fractions. Comparing the genomes with globally distributed metagenomes reveals significant fragment recruitment at high sequence identity from brackish waters in North America, but little from lakes or oceans. This suggests the existence of a global brackish metacommunity whose populations diverged from freshwater and marine relatives over 100,000 years ago, long before the Baltic Sea was formed (8000 years ago). This markedly contrasts to most Baltic Sea multicellular organisms, which are locally adapted populations of freshwater or marine counterparts.ConclusionsWe describe the gene content, temporal dynamics and biogeography of a large set of new bacterioplankton genomes assembled from metagenomes. We propose that brackish environments exert such strong selection that lineages adapted to them flourish globally with limited influence from surrounding aquatic communities.Electronic supplementary materialThe online version of this article (doi:10.1186/s13059-015-0834-7) contains supplementary material, which is available to authorized users.

Shifts in phytoplankton community structure modify bacterial production, abundance and community composition

“…Actinobacteria is a common clade observed in the Baltic Sea, due to the low salinity. They are considered slow-growing and predator-resistant (Eckert et al 2012), and are associated with decaying phytoplankton blooms and Cyanobacteria-derived DOC (Stepanauskas et al 2003, Hugerth et al 2015, Bunse et al 2016.…”

“…In addition to these predominant groups, Actinobacteria and Betaproteobacteria are also common members of the bacterial community in the brackish Baltic Sea during or after phytoplankton blooms (Riemann et al 2008, Herlemann et al 2011, Bunse et al 2016. A recent study using metagenome-assembled genomes linked these phylogenetic lineages with functionality, based on the proportion of various genes involved in metabolic processes (Hugerth et al 2015).…”

Phylogenetic Signals of Salinity and Season in Bacterial Community Composition Across the Salinity Gradient of the Baltic Sea

“…The Baltic Sea, in contrast, is a more tractable system, with a stable salinity gradient that facilitates comparisons of the impact of salinity vs. other environmental factors. Moreover, the central Baltic Sea has a water residence time of 30 years (Reissmann et al, 2009), which has allowed the establishment of mesohaline (“brackish”) microbial communities (Herlemann et al, 2011; Dupont et al, 2014; Hugerth et al, 2015; Hu et al, 2016). The environmental conditions in the Baltic Sea show the typical seasonal changes of high-latitude ecosystems, including strong shifts in temperature, solar radiation, phytoplankton blooms, nutrient levels, and organic matter composition.…”

DNA Sequencing as a Tool to Monitor Marine Ecological Status

“…Many bioinformatic tools and platforms are now tailored to gene sequences derived from environmental samples, particularly for prokaryotic assemblages (Kanehisa et al, 2008;Meyer et al, 2008;Caporaso et al, 2010;Abubucker et al, 2012;Thomas et al, 2012;Kozich et al, 2013;Hunter et al, 2014). Furthermore, de-novo assembly is increasingly being used to derive nearly complete genomes of previously unknown ecologically important organisms from metagenomes (Garza and Dutilh, 2015;Hugerth et al, 2015). A growing number of assemblers (Boisvert et al, 2012;Peng et al, 2012) and binning tools (Alneberg et al, 2014;Imelfort et al, 2014;Nurk et al, 2017) are available that assemble short sequencing reads into larger contigs and subsequently combine them into bins based on, for example, sequence similarity (Teeling and Glöckner, 2012).…”