scholarly journals Sinking particles promote vertical connectivity in the ocean microbiome

2018 ◽  
Vol 115 (29) ◽  
pp. E6799-E6807 ◽  
Author(s):  
Mireia Mestre ◽  
Clara Ruiz-González ◽  
Ramiro Logares ◽  
Carlos M. Duarte ◽  
Josep M. Gasol ◽  
...  
Keyword(s):  
Surface Waters ◽  
Deep Ocean ◽  
Rrna Gene ◽  
Carbon Export ◽  
Size Fractions ◽  
Sinking Particles ◽  
Prokaryotic Diversity ◽  
Compositional Variability ◽  
Organic Particles ◽  
Community Connectivity

The sinking of organic particles formed in the photic layer is a main vector of carbon export into the deep ocean. Although sinking particles are heavily colonized by microbes, so far it has not been explored whether this process plays a role in transferring prokaryotic diversity from surface to deep oceanic layers. Using Illumina sequencing of the 16S rRNA gene, we explore here the vertical connectivity of the ocean microbiome by characterizing marine prokaryotic communities associated with five different size fractions and examining their compositional variability from surface down to 4,000 m across eight stations sampled in the Atlantic, Pacific, and Indian Oceans during the Malaspina 2010 Expedition. Our results show that the most abundant prokaryotes in the deep ocean are also present in surface waters. This vertical community connectivity seems to occur predominantly through the largest particles because communities in the largest size fractions showed the highest taxonomic similarity throughout the water column, whereas free-living communities were more isolated vertically. Our results further suggest that particle colonization processes occurring in surface waters determine to some extent the composition and biogeography of bathypelagic communities. Overall, we postulate that sinking particles function as vectors that inoculate viable particle-attached surface microbes into the deep-sea realm, determining to a considerable extent the structure, functioning, and biogeography of deep ocean communities.

scholarly journals Biological composition and microbial dynamics of sinking particulate organic matter at abyssal depths in the oligotrophic open ocean

2019 ◽  
pp. 201903080 ◽  
Author(s):  
Dominique Boeuf ◽  
Bethanie R. Edwards ◽  
John M. Eppley ◽  
Sarah K. Hu ◽  
Kirsten E. Poff ◽  
...  
Keyword(s):  
Organic Matter ◽  
Particulate Organic Matter ◽  
Deep Sea ◽  
Deep Ocean ◽  
Sediment Traps ◽  
Rrna Gene ◽  
North Pacific Subtropical Gyre ◽  
Near Surface ◽  
The North ◽  
Sinking Particles

Sinking particles are a critical conduit for the export of organic material from surface waters to the deep ocean. Despite their importance in oceanic carbon cycling and export, little is known about the biotic composition, origins, and variability of sinking particles reaching abyssal depths. Here, we analyzed particle-associated nucleic acids captured and preserved in sediment traps at 4,000-m depth in the North Pacific Subtropical Gyre. Over the 9-month time-series, Bacteria dominated both the rRNA-gene and rRNA pools, followed by eukaryotes (protists and animals) and trace amounts of Archaea. Deep-sea piezophile-like Gammaproteobacteria, along with Epsilonproteobacteria, comprised >80% of the bacterial inventory. Protists (mostly Rhizaria, Syndinales, and ciliates) and metazoa (predominantly pelagic mollusks and cnidarians) were the most common sinking particle-associated eukaryotes. Some near-surface water-derived eukaryotes, especially Foraminifera, Radiolaria, and pteropods, varied greatly in their abundance patterns, presumably due to sporadic export events. The dominance of piezophile-like Gammaproteobacteria and Epsilonproteobacteria, along with the prevalence of their nitrogen cycling-associated gene transcripts, suggested a central role for these bacteria in the mineralization and biogeochemical transformation of sinking particulate organic matter in the deep ocean. Our data also reflected several different modes of particle export dynamics, including summer export, more stochastic inputs from the upper water column by protists and pteropods, and contributions from sinking mid- and deep-water organisms. In total, our observations revealed the variable and heterogeneous biological origins and microbial activities of sinking particles that connect their downward transport, transformation, and degradation to deep-sea biogeochemical processes.

scholarly journals Seasonal Prokaryotic Community Linkages Between Surface and Deep Ocean Water

2021 ◽  
Vol 8 ◽  
Author(s):  
Jess Wenley ◽  
Kim Currie ◽  
Scott Lockwood ◽  
Blair Thomson ◽  
Federico Baltar ◽  
...  
Keyword(s):  
Time Series ◽  
Surface Waters ◽  
Bacterial Abundance ◽  
Deep Ocean ◽  
Community Diversity ◽  
Seasonal Patterns ◽  
Ocean Water ◽  
Deep Ocean Water ◽  
Organic Particles ◽  
Heterotrophic Production

Sinking organic particles from surface waters provide key nutrients to the deep ocean, and could serve as vectors transporting microbial diversity to the deep ocean. However, the effect of this seasonally varying connectivity with the surface on deep microbial communities remains unexplored. Here, a three-year time-series from surface and deep (500 m) waters part of the Munida Microbial Observatory Time-Series (MOTS) was used to study the seasonality of epipelagic and mesopelagic prokaryotic communities. The goal was to establish how seasonally dynamic these two communities are, and any potential linkages between them. Both surface and deep prokaryotic communities displayed seasonality with high variation in community diversity. Deep prokaryotic communities mirrored the seasonal patterns in heterotrophic production and bacterial abundance displayed by surface communities, which were related to changes in chlorophyll-a concentration. However, the magnitude of this temporal variability in deeper waters was generally smaller than in the surface. Detection of surface prokaryotes in the deep ocean seemed seasonally linked to phytoplankton blooms, but other copiotrophic or typically algal-associated surface groups were not detected in the mesopelagic suggesting only specific populations were surviving the migration down the water column. We show transfer of organisms across depths is possibly not always unidirectional, with typically deep ocean microbes being seasonally abundant in surface waters. This indicates the main mechanism linking surface and deep communities changes seasonally: sinking of organic particles during productive periods, and vertical convection during winter overturning.

scholarly journals Characterization and Transcriptome Analysis of a Long-Chain n-Alkane-Degrading Strain Acinetobacter Pittii SW-1

2021 ◽  
Vol 18 (12) ◽  
pp. 6365
Author(s):  
Weina Kong ◽  
Cheng Zhao ◽  
Xingwang Gao ◽  
Liping Wang ◽  
Qianqian Tian ◽  
...  
Keyword(s):  
Unsaturated Fatty Acids ◽  
Sulfur Metabolism ◽  
Quantitative Polymerase Chain Reaction ◽  
Deep Ocean ◽  
Rrna Gene ◽  
Alkane Hydroxylase ◽  
Degradation Rates ◽  
Acinetobacter Pittii ◽  
Ocean Environment ◽  
Long Chain

Strain sw-1, isolated from 7619-m seawater of the Mariana Trench, was identified as Acinetobacter pittii by 16S rRNA gene and whole-genome sequencing. A. pittii sw-1 was able to efficiently utilize long-chain n-alkanes (C18–C36), but not short- and medium-chain n-alkanes (C8–C16). The degradation rate of C20 was 91.25%, followed by C18, C22, C24, C32, and C36 with the degradation rates of 89.30%, 84.03%, 80.29%, 30.29%, and 13.37%, respectively. To investigate the degradation mechanisms of n-alkanes for this strain, the genome and the transcriptome analyses were performed. Four key alkane hydroxylase genes (alkB, almA, ladA1, and ladA2) were identified in the genome. Transcriptomes of strain sw-1 grown in C20 or CH3COONa (NaAc) as the sole carbon source were compared. The transcriptional levels of alkB and almA, respectively, increased 78.28- and 3.51-fold in C20 compared with NaAc, while ladA1 and ladA2 did not show obvious change. The expression levels of other genes involved in the synthesis of unsaturated fatty acids, permeases, membrane proteins, and sulfur metabolism were also upregulated, and they might be involved in n-alkane uptake. Reverse transcription quantitative polymerase chain reaction (RT-qPCR) confirmed that alkB expression was significantly induced by C20, C24, and C32, and almA induction extent by C24 and C32 was higher than that with C20. Furthermore, ladA2 expression was only induced by C32, and ladA1 expression was not induced by any of n-alkanes. In addition, A. pittii sw-1 could grow with 0%–3% NaCl or 8 out of 10 kinds of the tested heavy metals and degrade n-alkanes at 15 °C. Taken together, these results provide comprehensive insights into the degradation of long-chain n-alkanes by Acinetobacter isolated from the deep ocean environment.

scholarly journals Microbial Diversity Profiling of Gut Microbiota of Macropus giganteus Using Three Hypervariable Regions of the Bacterial 16S rRNA

2021 ◽  
Vol 9 (8) ◽  
pp. 1721
Author(s):  
Christian O’Dea ◽  
Roger Huerlimann ◽  
Nicole Masters ◽  
Anna Kuballa ◽  
Cameron Veal ◽  
...  
Keyword(s):  
16S Rrna ◽  
Gut Microbiota ◽  
Microbial Diversity ◽  
Surface Waters ◽  
Bacterial Species ◽  
Rrna Gene ◽  
Faecal Contamination ◽  
Hypervariable Regions ◽  
Geographical Regions ◽  
V3 Region

Animal faecal contamination of surface waters poses a human health risk, as they may contain pathogenic bacteria or viruses. Of the numerous animal species residing along surface waterways in Australia, macropod species are a top contributor to wild animals’ faecal pollution load. We characterised the gut microbiota of 30 native Australian Eastern Grey Kangaroos from six geographical regions (five kangaroos from each region) within South East Queensland in order to establish their bacterial diversity and identify potential novel species-specific bacteria for the rapid detection of faecal contamination of surface waters by these animals. Using three hypervariable regions (HVRs) of the 16S rRNA gene (i.e., V1–V3, V3–V4, and V5–V6), for their effectiveness in delineating the gut microbial diversity, faecal samples from each region were pooled and microbial genomic DNA was extracted, sequenced, and analysed. Results indicated that V1-V3 yielded a higher taxa richness due to its larger target region (~480 bp); however, higher levels of unassigned taxa were observed using the V1-V3 region. In contrast, the V3–V4 HVR (~569 bp) attained a higher likelihood of a taxonomic hit identity to the bacterial species level, with a 5-fold decrease in unassigned taxa. There were distinct dissimilarities in beta diversity between the regions, with the V1-V3 region displaying the highest number of unique taxa (n = 42), followed by V3–V4 (n = 11) and V5–V6 (n = 8). Variations in the gut microbial diversity profiles of kangaroos from different regions were also observed, which indicates that environmental factors may impact the microbial development and, thus, the composition of the gut microbiome of these animals.

scholarly journals Optimizing models of the North Atlantic spring bloom using physical, chemical and bio-optical observations from a Lagrangian float

2010 ◽  
Vol 7 (6) ◽  
pp. 8477-8520 ◽  
Author(s):  
W. Bagniewski ◽  
K. Fennel ◽  
M. J. Perry ◽  
E. A. D'Asaro
Keyword(s):  
North Atlantic ◽  
Spring Bloom ◽  
Deep Ocean ◽  
Complex Model ◽  
Optical Observations ◽  
Model Parameters ◽  
Carbon Export ◽  
The North ◽  
Chemical Measurements ◽  
The North Atlantic

Abstract. The North Atlantic spring bloom is one of the main events that lead to carbon export to the deep ocean and drive oceanic uptake of CO2 from the atmosphere. Here we use a suite of physical, bio-optical and chemical measurements made during the 2008 spring bloom to optimize and compare three different models of biological carbon export. The observations are from a Lagrangian float that operated south of Iceland from early April to late June, and were calibrated with ship-based measurements. The simplest model is representative of typical NPZD models used for the North Atlantic, while the most complex model explicitly includes diatoms and the formation of fast sinking diatom aggregates and cysts under silicate limitation. We carried out a variational optimization and error analysis for the biological parameters of all three models, and compared their ability to replicate the observations. The observations were sufficient to constrain most phytoplankton-related model parameters to accuracies of better than 15%. However, the lack of zooplankton observations leads to large uncertainties in model parameters for grazing. The simulated vertical carbon flux at 100 m depth is similar between models and agrees well with available observations, but at 600 m the simulated flux is much larger for the model with diatom aggregation. While none of the models can be formally rejected based on their misfit with the available observations, the model that includes export by diatom aggregation has slightly better fit to the observations and more accurately represents the mechanisms and timing of carbon export based on observations not included in the optimization. Thus models that accurately simulate the upper 100 m do not necessarily accurately simulate export to deeper depths.

Using new observations and Machine Learning to improve organic sinking processes in the PlankTOM global ocean biogeochemical model 

2021 ◽  
Author(s):  
Anna Denvil-Sommer ◽  
Corinne Le Quéré ◽  
Erik Buitenhuis ◽  
Lionel Guidi ◽  
Jean-Olivier Irisson
Keyword(s):  
Organic Carbon ◽  
Carbon Cycle ◽  
Deep Ocean ◽  
Ecosystem Dynamics ◽  
Global Ocean ◽  
Biogeochemical Model ◽  
Carbon Export ◽  
Mixing Depth ◽  
Chl A ◽  
Biogeochemical Models

<p>A lot of effort has been put in the representation of surface ecosystem processes in global carbon cycle models, in particular through the grouping of organisms into Plankton Functional Types (PFTs) which have specific influences on the carbon cycle. In contrast, the transfer of ecosystem dynamics into carbon export to the deep ocean has received much less attention, so that changes in the representation of the PFTs do not necessarily translate into changes in sinking of particulate matter. Models constrain the air-sea CO<sub>2</sub> flux by drawing down carbon into the ocean interior. This export flux is five times as large as the CO<sub>2</sub> emitted to the atmosphere by human activities. When carbon is transported from the surface to intermediate and deep ocean, more CO<sub>2 </sub>can be absorbed at the surface. Therefore, even small variability in sinking organic carbon fluxes can have a large impact on air-sea CO<sub>2</sub> fluxes, and on the amount of CO<sub>2</sub> emissions that remain in the atmosphere.</p><p>In this work we focus on the representation of organic matter sinking in global biogeochemical models, using the PlankTOM model in its latest version representing 12 PFTs. We develop and test a methodology that will enable the systematic use of new observations to constrain sinking processes in the model. The approach is based on a Neural Network (NN) and is applied to the PlankTOM model output to test its ability to reconstruction small and large particulate organic carbon with a limited number of observations. We test the information content of geographical variables (location, depth, time of year), physical conditions (temperature, mixing depth, nutrients), and ecosystem information (CHL a, PFTs). These predictors are used in the NN to test their influence on the model-generation of organic particles and the robustness of the results. We show preliminary results using the NN approach with real plankton and particle size distribution observations from the Underwater Vision Profiler (UVP) and plankton diversity data from Tara Oceans expeditions and discuss limitations.</p>

Deep marine anoxia of the southern Panthalassa during the Permian-Triassic – global impacts of the Siberian Traps

2021 ◽  
Author(s):  
Stephen Grasby ◽  
David Bond ◽  
Paul Wignall ◽  
Runsheng Yin ◽  
Lorna Strachan ◽  
...  
Keyword(s):  
Global Warming ◽  
Ocean Circulation ◽  
Surface Waters ◽  
Mass Extinction ◽  
Bottom Water ◽  
Deep Ocean ◽  
Marine Life ◽  
Siberian Traps ◽  
Southern Latitude ◽  
Global Impacts

<p>The deep-water record of marine anoxia across the Permo-Triassic mass extinction (PTME) is highly controversial; both the length of time and severity of anoxic conditions are uncertain. Panthalassa Ocean circulation models show varying results, ranging from a well-ventilated deep ocean to rapidly developing northern, but not southern, latitude anoxia in response to Siberian Traps driven global warming. To address this uncertainty we examined a southern paleo-latitude pelagic record. Trace metal and pyrite framboid data show bottom water euxinc conditions developed in the southern Panthalassa Ocean at the PTME, coincident with enhanced volcanic activity indicated by Hg geochemistry. While a global deep-ocean euxinic event at the PTME placed extraordinary stress on marine life, southern surface waters appear to have recovered more quickly as radiolarian populations return several million years before they do in northern Panthalassa.</p>

scholarly journals On the Linkage between Antarctic Surface Water Stratification and Global Deep-Water Temperature

2011 ◽  
Vol 24 (14) ◽  
pp. 3545-3557 ◽  
Author(s):  
Ralph F. Keeling ◽  
Martin Visbeck
Keyword(s):  
Water Temperature ◽  
North Atlantic ◽  
Deep Water ◽  
Surface Waters ◽  
Feedback Loop ◽  
Deep Ocean ◽  
Static Stability ◽  
Deep Waters ◽  
Water Stratification ◽  
The Antarctic

Abstract The suggestion is advanced that the remarkably low static stability of Antarctic surface waters may arise from a feedback loop involving global deep-water temperatures. If deep-water temperatures are too warm, this promotes Antarctic convection, thereby strengthening the inflow of Antarctic Bottom Water into the ocean interior and cooling the deep ocean. If deep waters are too cold, this promotes Antarctic stratification allowing the deep ocean to warm because of the input of North Atlantic Deep Water. A steady-state deep-water temperature is achieved such that the Antarctic surface can barely undergo convection. A two-box model is used to illustrate this feedback loop in its simplest expression and to develop basic concepts, such as the bounds on the operation of this loop. The model illustrates the possible dominating influence of Antarctic upwelling rate and Antarctic freshwater balance on global deep-water temperatures.

scholarly journals The relative contribution of fast and slow sinking particles to ocean carbon export

2012 ◽  
Vol 26 (1) ◽  
pp. n/a-n/a ◽  
Author(s):  
J. S. Riley ◽  
R. Sanders ◽  
C. Marsay ◽  
F. A. C. Le Moigne ◽  
E. P. Achterberg ◽  
...  
Keyword(s):  
Carbon Export ◽  
Relative Contribution ◽  
Sinking Particles ◽  
Ocean Carbon

Impacts of meso and submesoscale dynamics on the horizontal dispersion of sinking particles from the surface to the deep ocean

2020 ◽  
Author(s):  
Lu Wang ◽  
Jonathan Gula ◽  
Jeremy Collin ◽  
Laurent Memery
Keyword(s):  
General Structure ◽  
Finite Size ◽  
Deep Ocean ◽  
Sediment Traps ◽  
Horizontal Distribution ◽  
Particle Dispersion ◽  
Small Scale ◽  
Transport Pathways ◽  
Horizontal Dispersion ◽  
Sinking Particles

<p>Energetic eddy fields generated by meso and submesoscale dynamics induce tridimensional particle transport pathways, which complicate the interpretation of observed Particulate Organic Carbon (POC) fluxes using sediment traps. It is therefore of importance to understand how horizontal dispersion of particles is structured by these dynamics from surface to depth. In this modelling study, we use a Lagrangian method to backtrack sinking particles collected at various depths ranging from 500 m to 4700 m at the PAP (Porcupine Abyssal Plain) site. Particle trajectories are computed using high-resolution simulations of the Regional Ocean Modelling System (ROMS). Our results show that the horizontal distribution of particles with sinking velocities below 100 m d<sup>-1</sup> presents a large small-scale heterogeneity. Mesoscale eddies act to define the general structure of particle patches while submesoscale features shape particle distributions through convergence/divergence processes. Distribution patterns of particles tracked from different depths suggest regime shifts of particle dispersion between subsurface layers. To identify and quantify these regimes, we perform 2d experiments at specific depths from 100 m to 4000 m and relate the Lagrangian statistics to the characteristics of the different dynamical regimes identified using vertical profiles of eddy energy and Finite Size Lyapunov Exponents (FSLE) approach.                                                                                                                                                               </p>

Sign in / Sign up

Export Citation Format

Share Document