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Marrase, C.

Publications and source records attributed to Marrase, C..

2 recordsLinked to original sources

Viral infection switches the balance between bacterial and eukaryotic recyclers of organic matter during algal blooms

Algal blooms are hotspots of marine primary production and play central roles in microbial ecology and global nutrient cycling. When blooms collapse, organic carbon is transferred to higher trophic levels, microbial respiration or sinking in proportions that depend on the dominant mortality agent. Viral infection can lead to bloom termination, but its impact on the fate of carbon remains an open question. Here, we characterized the consequences of viral infection on the microbiome composition and biogeochemical landscape of marine ecosystems by conducting a large-scale mesocosm experiment. Moniroting of seven induced coccolithophore blooms, which showed different degrees of viral infection, revealed that only high levels of viral infection caused significant shifts in the composition of free-living bacterial and eukaryotic assemblages. Intriguingly, viral infection favored the growth of eukaryotic heterotrophs (thraustochytrids) over bacteria as potential recyclers of organic matter. By combining modeling and quantification of active viral infection at a single-cell resolution, we estimate that viral infection can increase per-cell rates of extracellular carbon release by 2-4.5 fold. This happened via production of acidic polysaccharides and particulate inorganic carbon, two major contributors to carbon sinking into the deep ocean. These results reveal the impact of viral infection on the fate of carbon through microbial recyclers of organic matter in large-scale coccolithophore blooms.

microbiology↗

Disentangling temporal associations in marine microbial networks

BackgroundMicrobial interactions are fundamental for Earths ecosystem functioning and biogeochemical cycling. Nevertheless, they are challenging to identify and remain barely known. Omics-based censuses are helpful in predicting microbial interactions through the statistical inference of single (static) association networks. Yet, microbial interactions are dynamic and we have limited knowledge of how they change over time. Here we investigate the dynamics of microbial associations in a 10-year marine time series in the Mediterranean Sea using an approach inferring a time-resolved (temporal) network from a single static network. ResultsA single static network including microbial eukaryotes and bacteria was built using metabarcoding data derived from 120 monthly samples. For the decade, we aimed to identify persistent, seasonal, and temporary microbial associations by determining a temporal network that captures the interactome of each individual sample. We found that the temporal network appears to follow an annual cycle, collapsing and reassembling when transiting between colder and warmer waters. We observed higher association repeatability in colder than in warmer months. Only 16 associations could be validated using observations reported in literature, underlining our knowledge gap in marine microbial ecological interactions. ConclusionsOur results indicate that marine microbial associations follow recurrent temporal dynamics in temperate zones, which need to be accounted for to better understand the functioning of the ocean microbiome. The constructed marine temporal network may serve as a resource for testing season-specific microbial interaction hypotheses. The applied approach can be transferred to microbiome studies in other ecosystems.

microbiology↗