Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome

Salazar, Guillem; Paoli, Lucas; Alberti, Adriana; Huerta-Cepas, Jaime; Ruscheweyh, Hans‐Joachim; Cuenca, Miguelangel; Field, Christopher M.; Coelho, Luís Pedro; Cruaud, Corinne; Engelen, Stéfan; Gregory, Ann C.; Labadie, Karine; Marec, Claudie; Pelletier, Éric; Royo-Llonch, Marta; Roux, Simon; Sánchez, Pablo; Uehara, Hideya; Zayed, Ahmed A.; Zeller, Georg; Carmichael, Margaux; Dimier, Céline; Ferland, Joannie; Kandels, Stefanie; Picheral, Marc; Pisarev, Sergey; Poulain, Julie; Acinas, Silvia G.; Babin, Marcel; Bork, Peer; Boss, Emmanuel; Bowler, Chris; Cochrane, Guy; Vargas, Colomban de; Follows, Michael J.; Gorsky, Gabriel; Grimsley, Nigel; Guidi, Lionel; Hingamp, Pascal; Iudicone, Daniele; Jaillon, Olivier; Kandels‐Lewis, Stefanie; Karp‐Boss, Lee; Karsenti, Eric; Not, Fabrice; Ogata, Hiroyuki; Pesant, Stéphane; Poulton, Nicole; Raes, Jeroen; Sardet, Christian; Speich, Sabrina; Stemmann, Lars; Sullivan, Matthew B.; Sunagawa, Shinichi; Wincker, Patrick

doi:10.1016/j.cell.2019.10.014

Cited by 271 publications

(322 citation statements)

References 129 publications

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“…3) is coherent with the importance of this variable, as TARA Oceans sampled a wider temperature range (range ≈ 0-30°C, mean ≈ 21°C, SD ≈ 7°C) than Malaspina (range ≈ 15-30°C, mean ≈ 24°C, SD ≈ 3°C). Furthermore, and consistent with our results, recent global-scale studies reported strong correlations between ocean-microbiota composition (predominantly prokaryotic) and temperature, and weak correlations with nutrients [56,57]. In sum, the previous agrees with our results indicating that temperature is one of the most important agents exerting abiotic selection on the surface-ocean microbiota, although we cannot rule out the selective action of other unmeasured abiotic factors.…”

Section: Discussionsupporting

confidence: 92%

Disentangling the mechanisms shaping the surface ocean microbiota

et al. 2020

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Background: The ocean microbiota modulates global biogeochemical cycles and changes in its configuration may have large-scale 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 this, 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.

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Section: Discussionsupporting

confidence: 92%

Disentangling the mechanisms shaping the surface ocean microbiota

et al. 2020

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“…The higher abundance of Cluster 1 and Cluster 2 transcripts in few (three) stations must be interpreted carefully because the abundance of metatranscriptomic reads does not solely and directly reflect the differential expression of a gene. Transcript abundance is also a function of the bacterial abundance and maybe biased by several technical issues such as difference of coverage between samples (Salazar et al ., ). As an example, the apparent overexpression of Cluster 1‐ hgcA in the Marquesas Islands could result from oversequencing at these stations.…”

Section: Resultsmentioning

confidence: 97%

“…We aim to resolve the paradox between several biogeochemical evidences for in situ MeHg production and the absence of known anaerobic Hg methylating prokaryotes in the open ocean. Metagenomic and metatranscriptomic data from 243 and 187 Tara Oceans samples, collected from 68 and 108 open ocean locations covering most ocean basins respectively, were analysed to generate an ocean microbial reference gene catalogue (Sunagawa et al ., ; Salazar et al ., ). We screened the Tara Oceans metagenomes and metatranscriptomes for the presence of the key hgcA methylating gene.…”

Section: Introductionmentioning

confidence: 97%

Widespread microbial mercury methylation genes in the global ocean

Villar

Cabrol

Heimbürger‐Boavida

2020

Environ Microbiol Rep

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Methylmercury is a neurotoxin that bioaccumulates from seawater to high concentrations in marine fish, putting human and ecosystem health at risk. High methylmercury levels have been found in the oxic subsurface waters of all oceans, but only anaerobic microorganisms have been shown to efficiently produce methylmercury in anoxic environments. The microaerophilic nitrite-oxidizing bacteria Nitrospina have previously been suggested as possible mercury methylating bacteria in Antarctic sea ice. However, the microorganisms responsible for processing inorganic mercury into methylmercury in oxic seawater remain unknown. Here, we show metagenomic and metatranscriptomic evidence that the genetic potential for microbial methylmercury production is widespread in oxic seawater. We find high abundance and expression of the key mercury methylating genes hgcAB across all ocean basins, corresponding to the taxonomic relatives of known mercury methylating bacteria from Deltaproteobacteria, Firmicutes and Chloroflexi. Our results identify Nitrospina as the predominant and widespread microorganism carrying and actively expressing hgcAB. The highest hgcAB abundance and expression occurs in the oxic subsurface waters of the global ocean where the highest MeHg concentrations are typically observed.

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“…As described previously 31 20-200 m). The sampling strategy and methodology have been described elsewhere 35 .…”

Section: Sample and Environmental Data Collectionmentioning

confidence: 99%

“…Previous studies have provided an overview of the microbial taxonomic diversity in the Arctic 16,20,[24][25][26] , including functions relevant to the ecosystem, like nitrification processes 15,27 , heterotrophy 13,21,24 or photoheterotrophy 28,29 . Finally, the uniqueness of polar environments has been evidenced when studying global biogeographical patterns by means of amplicon sequencing 30 or metagenomics and metatranscriptomics 31 . Recent technological advances such as the reconstruction of genomes from metagenomes are allowing to go beyond the community level and explore the functional capabilities of specific taxa.…”

Section: Introductionmentioning

confidence: 99%

Ecogenomics of key prokaryotes in the arctic ocean

Royo-Llonch¹,

Sánchez²,

Ruiz‐González³

et al. 2020

Preprint

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The Arctic Ocean is a key player in the regulation of climate and at the same time is under increasing pressure as a result of climate change. Predicting the future of this ecosystem requires understanding of the responses of Arctic microorganisms to environmental change, as they are the main drivers of global biogeochemical cycles. However, little is known about the ecology and metabolic potential of active Arctic microbes. Here, we reconstructed a total of 3,550 metagenomic bins from 41 seawater metagenomes collected as part of the Tara Oceans expedition, covering five different Arctic Ocean regions as well as the sub-Arctic North Atlantic Ocean and including various depths and different seasons (spring to autumn). Of these bins, 530 could be classified as Metagenome Assembled Genomes (MAGs) and over 75% of them represented novel species. We describe their habitat range and environmental preferences, as well as their metabolic capabilities, building the most comprehensive dataset of uncultured bacterial and archaeal genomes from the Arctic Ocean to date. We found a prevalence of mixotrophs, while chemolithoautotrophs were mostly present in the mesopelagic Arctic Ocean during spring and autumn. Finally, the catalogue of Arctic MAGs was complemented with metagenomes and metatranscriptomes from the global ocean to identify the most active MAGs present exclusively in polar metagenomes. These polar MAGs, which display a range of metabolic strategies, might represent Arctic sentinels of climate change and should be considered in prospective studies of the future state of the Arctic Ocean.

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Gene Expression Changes and Community Turnover Differentially Shape the Global Ocean Metatranscriptome

Cited by 271 publications

References 129 publications

Disentangling the mechanisms shaping the surface ocean microbiota

Disentangling the mechanisms shaping the surface ocean microbiota

Widespread microbial mercury methylation genes in the global ocean

Ecogenomics of key prokaryotes in the arctic ocean

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