Disentangling the mechanisms shaping the surface ocean microbiota

Abstract

Background The ocean microbiota modulates global biogeochemical cycles and changes in its configuration may have largescale consequences. Yet, the underlying ecological mechanisms structuring it are unclear. Here we investigate how fundamental ecological mechanisms ( selection , dispersal and ecological drift ) shape the smallest members of the tropical and subtropical surface-ocean microbiota: prokaryotes and minute eukaryotes (picoeukaryotes). Furthermore, we investigate the agents exerting abiotic selection on this assemblage as well as the spatial patterns emerging from the action of ecological mechanisms. To explore the previous, we analysed the composition of surface-ocean prokaryotic and picoeukaryotic communities using DNA-sequence data (16S- and 18S-rRNA genes) collected during the circumglobal expeditions Malaspina-2010 and TARA-Oceans . Results We found that the two main components of the tropical and subtropical surface-ocean microbiota, prokaryotes and picoeukaryotes, appear to be structured by different ecological mechanisms. Picoeukaryotic communities were predominantly structured by dispersal-limitation, while prokaryotic counterparts appeared to be shaped by the combined action of dispersal-limitation, selection and drift. Temperature-driven selection appeared as a major factor, out of a few selected factors, influencing species co-occurrence networks in prokaryotes but not in picoeukaryotes, indicating that association patterns may contribute to understand ocean microbiota structure and response to selection. Other measured abiotic variables seemed to have limited selective effects on community structure in the tropical and subtropical ocean. Picoeukaryotes displayed a higher spatial differentiation between communities and a higher distance decay when compared to prokaryotes, consistent with a scenario of higher dispersal limitation in the former after considering environmental heterogeneity. Lastly, random dynamics or drift seemed to have a more important role in structuring prokaryotic communities than picoeukaryotic counterparts. Conclusions The differential action of ecological mechanisms seems to cause contrasting biogeography, in the tropical and subtropical ocean, among the smallest surface plankton, prokaryotes and picoeukaryotes. This suggests that the idiosyncrasy of the main constituents of the ocean microbiota should be considered in order to understand its current and future configuration, which is especially relevant in a context of global change, where the reaction of surface ocean plankton to temperature increase is still unclear.

Perspectives from Ten Years of Protist Studies by High‐Throughput Metabarcoding

“…) and Malaspina (Logares et al. ). Time series have been ongoing for more than a decade on sites of the Mediterranean coast (Giner et al.…”

“…Null models based on metabarcoding data suggest, for example, that communities of eukaryotic and prokaryotic microbes are structured by different processes in the global ocean: Picoeukaryotes are predominantly structured by dispersal limitation, while bacterial communities are shaped by the combined action of dispersal limitation, selection, and drift (Logares et al. ). These estimates are expected to be influenced by geographical scale (Heino et al.…”

A continuously changing selective context on microbial communities associated with fish, from egg to fork

“…Although there are numerous works documenting the impact of abiotic factors (i.e. environmental) such as nutrients, xenobiotics, temperature, pH, salinity, and others, on different microbial communities, both aquatic and terrestrial, either free‐living or host‐associated (Díaz‐Sánchez et al., 2018; Lladó, López‐Mondéjar, & Baldrian, 2018; Logares et al., 2020; Zhao et al., 2018), biotic factors, which include interactions between host and associated living communities (either microbial or parasitic), are much less documented. The same can be said for the impact of abiotic and biotic factors on food microbial communities.…”

Applications of weighted association networks applied to compositional data in biology

“…transcripts, 16/18SS rRNA, marker genes) within a community by sampling from a pool of nucleic acid fragments. A typical NGS 16SrRNA experiment consists of (i) sequencing 16S rRNA amplicons at a specified sequencing depth from environmental samples (Caporaso et al, 2011;Logares et al, 2020), human tissues/biofluids (Goodrich et al, 2016;Gomez et al, 2017;Voorhies et al, 2019) or built environments (Weiss et al, 2018;Checinska Sielaff et al, 2019); (ii) clustering highly similar sequences into operational taxonomic units (OTU) as a representative for closely related taxa (Sneath and Sokal, 1962;Schloss et al, 2009;Edgar, 2013) or using amplicon sequencing variants (ASV) (Callahan et al, 2016;Amir et al, 2017); (iii) generating abundance tables by counting NGS reads mapped to ecological units (e.g. OTU or ASV); and (iv) analysing the resulting abundance tables such as alpha/beta-diversity, differential abundance or network analysis.…”