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Sinking enhances the degradation of organic particles by marine bacteria

Nature Geoscience volume 14, pages 775–780 (2021)Cite this article

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Abstract

The sinking of organic particles in the ocean and their degradation by marine microorganisms is one of the main drivers of the biological pump. Yet, the mechanisms determining the magnitude of the pump remain poorly understood, limiting our ability to predict this carbon flux in future ocean scenarios. Current ocean models assume that the biological pump is governed by the competition between sinking speed and degradation rate, with the two processes independent from one another. Contrary to this paradigm, we show that sinking itself is a primary determinant of the rate at which bacteria degrade particles. Heterotrophic bacterial degradation rates were obtained from a laboratory study on model surface-colonized particles at atmospheric pressure under a range of flow speeds to mimic different sinking velocities. We find that even modest sinking speeds of 8 m day−1 enhance degradation rates more than 10-fold compared with degradation rates of non-sinking particles. We discovered that the molecular mechanism underlying this sinking-enhanced degradation is the flow-induced removal from the particles of the oligomeric breakdown products, which otherwise compete for enzymatic activity. This mechanism applies across several substrates and bacterial strains, suggesting its potentially broad occurrence under natural marine conditions. Integrating our findings into a mathematical model of particulate carbon flux, we propose that the coupling of sinking and degradation may contribute, in conjunction with other processes, to determining the magnitude of the vertical carbon flux in the ocean.

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Fig. 1: Marine particle degradation is flow dependent.
Fig. 2: Flow plays a key role in determining bacterial growth on, and degradation of, model marine particles.
Fig. 3: High concentrations of oligo-alginate inhibit the degradation of alginate particles.
Fig. 4: The coupling of sinking and degradation can have a major effect on vertical flux of POC in the ocean.

Data availability

The datasets and representative videos generated and analysed during the study are available in the Supplementary Information of the paper. The raw videos generated and analysed during the study are available for download from: https://doi.org/10.3929/ethz-b-000488179. Source data are provided with this paper.

Code availability

The computer codes used during the study are available for download from Zenodo (COMSOL transport model, https://doi.org/10.5281/zenodo.4818505; model of sinking-enhanced degradation, https://doi.org/10.5281/zenodo.5233234).

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Acknowledgements

We thank R. Naisbit for help with editing and members of the Simons Foundation PriME collaboration for fruitful discussions. We gratefully acknowledge funding from the European Molecular Biology Organization (EMBO; ALTF 1109-2016) and the Human Frontier Science Program (HFSP; LT001209/2017) to U.A.; the European Union’s Horizon 2020 research and innovation programme under a Marie Skłodowska-Curie grant agreement (No. 798411) to F.J.P.; the Science for Life Laboratory (SciLifeLab Fellowship grant, SLL 2019/2) to L.B.; and from a Gordon and Betty Moore Foundation Symbiosis in Aquatic Systems Investigator Award (GBMF9197; https://doi.org/10.37807/GBMF9197), the Simons Foundation through the Principles of Microbial Ecosystems (PriME) collaboration (grant 542395) and the Swiss National Science Foundation, National Centre of Competence in Research (NCCR) Microbiomes (No. 51NF40_180575) to R.S.

Author information

Authors and Affiliations

  1. Institute of Environmental Engineering, Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland

    Uria Alcolombri, François J. Peaudecerf, Vicente I. Fernandez, Lars Behrendt, Kang Soo Lee & Roman Stocker

  2. Science for Life Laboratory, Department of Environmental Toxicology, Uppsala University, Uppsala, Sweden

    Lars Behrendt

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  1. Uria Alcolombri
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Contributions

U.A., F.J.P., V.I.F. and R.S. designed the research. U.A., K.S.L. and L.B. conducted the experiments. U.A. analysed the data. F.J.P., V.I.F. and U.A. developed the theoretical models. F.J.P. performed the numerical simulations. U.A., F.J.P., V.I.F. and R.S. wrote the paper.

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Correspondence to Uria Alcolombri or Roman Stocker.

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The authors declare no competing interests.

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Peer review information Nature Geoscience thanks Philip Boyd and the other, anonymous, reviewer(s) for their contribution to the peer review of this work. Primary handling editor: James Super.

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Extended data

Extended Data Fig. 1 Growth, respiration and localisation of alginate lyases of Vibrio cyclitrophicus ZF270 grown on alginate as a sole carbon source.

(a) Growth of Vibrio cyclitrophicus ZF270 on alginate particles under different flow rates. Bacterial growth was quantified as the average GFP fluorescence intensity at the interface between the alginate particle and the glass slide. All data normalized to initial values, error bars are standard deviations of three independent replicates. An expanded view of the exponential phase (0–20 h) is presented in Fig. 1c. A.U. = arbitrary units. (b) Respiration rate of Vibrio cyclitrophicus ZF270 grown on alginate particles. Respiration was measured in 2 ml vials each containing 18 alginate particles (diameter = 0.80 ± 0.05 mm) pre-colonized with Vibrio cyclitrophicus ZF270. O2 concentration was measured using O2-sensitive optode sensors and plotted as a function of time for three replicates (see Methods). Values were used to estimate O2 consumption per particle (8.9 ± 0.7 pmol min−1 particle−1; at peak growth, 40 h post-inoculation, n = 3) and per bacterium (0.07 ± 0.02 fmol min−1 cell−1, based on counts of 1.3 ± 0.3 × 106 cells per particle, at peak growth, 40 h post-inoculation, n = 3). The background consumption rate obtained from the no-bacteria control (blue curve) was subtracted from the bacterial respiration rate. (c) Vibrio cyclitrophicus ZF270 uses membrane-bound/periplasmic alginate lyases for growth on alginate. Images of Vibrio colonies grown on a 0.5% alginate-containing agar plate. Alginate lyase secretion by Vibrio splendidus FF6 (lower panel) leads to the formation of a transparent ring (marked with arrows) on the opaque plate due to degradation of alginate. This ring is absent around the Vibrio cyclitrophicus ZF270 colony (upper panel), indicating that this strain does not secrete alginate lyase into the surrounding medium.

Extended Data Fig. 2 Raman microscopy of alginate particles during degradation by Vibrio cyclitrophicus ZF270 suggests an accumulation of oligo-alginate on the surface of the particle even at intermediate flow rates during bacterial degradation, consumption and growth.

(a, b) Stitched bright-field microscopy images (22 × 30 = 660 and 29 × 35 = 1,015 images per picture) of a degraded particle (a; 42 h post-inoculation with bacteria) and a control particle (b; sterile particle). A flow rate of 7.25 m day-1 was imposed in both experiments. (c, d) Raman images of the spatial distribution of the carboxyl group (COOH) at the mid plane of the particle. Carboxyl groups are found on the mannuronate and guluronate subunits of alginate. The Raman map of the carboxyl group (I1390–1440; integrated intensity in the spectral region 1390–1440 cm−1) was normalized by the background intensity from the glass slide (I520–570). Soluble oligo-alginate, the product of bacterial degradation, diffuses into and out of the particle and results in a higher Raman signal (c). The Raman signal of the carboxyl ion, indicating the presence of dissolved oligo-alginate, was highest around the periphery of the particle, and decreased towards the particle centre. In contrast, the spatial distribution of the carboxyl ion in the absence of bacterial degradation was homogeneous (d). The white circle represents the boundary of the alginate particle. Panels (c) and (d) are stitched images with 20-µm step size in x- and y-directions. Scale bars: 100 µm.

Extended Data Fig. 3 Vibrio cyclitrophicus ZF270 biofilms on particles 30 h post-inoculation in flow of different concentrations of oligo-alginate or in 1% marine broth 2216.

Bacterial degradation was monitored under a flow of 7.25 m day-1 of medium supplemented with different concentrations of oligo-alginate or with 1% marine broth 2216 (complementary control; see main text). White arrows indicate bacterial biofilms, which form in oligo-alginate concentrations ≥0.04 mg ml-1 and in 1% marine broth 2216. Although more cells reside on particles at higher oligo-alginate concentrations, the degradation rate is lower than at lower oligo-alginate concentrations. For example, upon addition of 0.04 mg ml-1 oligo-alginate, the biofilm thickness was 33 ± 11 µm and the degradation rate was (7.5 ± 0.1) × 10−3 mm3 h-1, whereas for zero addition of oligo-alginate, the biofilm thickness was 8 ± 3 µm and the degradation rate was (20.5 ± 0.8) × 10−3 mm3 h-1. Scale bar: 400 µm.

Extended Data Fig. 4 High concentrations of oligo-alginate inhibit the degradation of alginate particles but do not affect alginate lyase activity.

(a) Particles exposed to alginate lyase enzyme under a flow rate of 7.25 m day-1 for 120 min in the presence or absence of 1 mg ml-1 oligo-alginate <10 kDa (see also Supplementary Movie 4). An experiment with 1 mg ml-1 oligo-alginate but with no alginate lyase enzyme is presented as a negative control. Degradation of the particle is only detected in the presence of alginate lyase but the absence of oligo-alginate. The volume of the particle relative to time zero (Vr) is indicated within each panel. Scale bar: 400 µm. (b) Addition of oligo-alginate does not inhibit the activity of alginate lyase. Alginate lyase activity was measured by monitoring the increase in absorption at 235 nm using a plate reader. Reactions were performed in 10 mm MOPS buffer containing 20 µg ml-1 alginate lyase, 0.1% (w/v) sodium alginate, 2 mM CaCl2 and the concentrations of oligo-alginate <10 kDa given on the x axis (see Methods). No differences in enzyme activity were observed across the range of concentrations tested (n = 3 for each value of concentration).

Extended Data Fig. 5 The coupling of sinking speed and degradation rate in models that consider a fixed minimum particle size.

Shown is the vertical flux of POC as a function of depth, F(Z), normalized by its value F(Z0) at the euphotic layer depth, Z0 = 100 m, predicted by our model when accounting for the observed coupling of sinking and degradation (continuous curves) or when excluding this coupling (reference case, dashed curves). When assuming a fixed lower bound, Rmin = 20 µm, for the radius of particles contributing to the flux (orange curves), our model shows a similar trend to the results presented in Fig. 4 (here shown with black curves), for which the range of radii varies with depth as particles are degraded. The minimum size was chosen by considering the experimental lower bound of the size of particles that can be detected by vision profilers with a fixed lower resolution35,51, to represent the lower bound on particles that are considered in empirical estimates of the POC flux. In both of the coupled approaches (continuous curves), the coupling of sinking speed with degradation results in a faster decrease of the vertical flux with depth compared to the reference case that neglects the coupling. All curves were derived from the following initial conditions: total concentration 200 particles l-1 at initial depth Z0 = 100 m, with a PSD slope of -4 over particles with initial radii in the range 125–750 µm for the varying range assumption (black) and initial radii 20–750 µm for the fixed lower bound assumption (orange).

Extended Data Fig. 6 Comparison of results from models incorporating the coupling of sinking and degradation with a reference case imposing a fixed high degradation rate for all particles.

Shown is the vertical flux of POC as a function of depth, F(Z), normalized by its value F(Z0) at the euphotic layer depth, Z0 = 100 m, predicted by our model when accounting for the observed coupling of sinking and degradation (blue curve) or when excluding this coupling (reference case, red curve). Also shown are results from a variant of the reference case that considers a uniform high rate of shrinking of the radius over the entire range of particle sizes (dash-dotted curve), corresponding to the initial shrinking rate of the largest particle considered at the initial depth Z0 (R0 = 750 µm) in the coupled case. All curves were derived from the following initial conditions: total concentration 200 particles l-1 at initial depth Z0 = 100 m and a PSD slope of -4 over particles of radii ranging between 125 and 750 µm. Note that the uncoupled high degradation case (dash-dotted curve) assumes a constant degradation rate that was measured under high flow, thus it overestimates the degradation compared to the coupled dynamics (blue curve).

Extended Data Fig. 7 Sensitivity of sinking-enhanced degradation to the characteristics of the particle size distribution (PSD).

Using our model, we computed the transfer efficiency of the vertical flux of POC to a depth of 100 m below the euphotic zone, denoted T100, that is T100 = F(Z0 + 100)/F(Z0) with Z0 = 100 m the depth of the euphotic zone, for different PSDs covering the range of existing oceanic regimes. By varying the PSD slope from -5 to -2, we move from typical oligotrophic PSDs dominated by small particles to typical eutrophic PSDs where larger particles are more prominent and can dominate in volume. For each PSD slope, we also considered a narrow range of initial particle size (R0 = 125 to 750 µm, circles), and a wider range representative of extended capabilities of Underwater Video Profilers to detect particles51 (R0 = 22.5 to 2500 µm, crosses). For each set of initial conditions, we ran our model including the sinking-enhanced degradation mechanism (coupled case, in blue) and without the coupling as a null model (uncoupled, in red). These results demonstrate that as the PSD skews towards small particles with slope closer to -5, typical of oligotrophic regions, the difference in flux between the uncoupled and coupled models becomes smaller. In contrast, a PSD with a greater contribution from large particles, with slope close to -2 like that in eutrophic regions, results in a greater difference between the coupled and uncoupled models. This is intuitive given the stronger enhancement of degradation for larger particles resulting from their faster sinking. In the same manner, we observe that including a wider range of particle sizes in the distribution for oligotrophic regions (with slopes -5 to -4) results in a weaker effect of the coupling of sinking and degradation on the POC flux, through the dominant contribution of very small particles. In contrast, the same wider range of particle sizes reinforces the effect of coupling in eutrophic regions (with PSD slopes of -2), where larger particles make a dominant contribution to the flux.

Extended Data Fig. 8 Modelling the coupling of sinking and degradation while including the effect of the water column temperature gradient on degradation rate.

Shown is the vertical flux of POC as a function of depth, F(Z), normalized by its value F(Z0) at the euphotic layer depth, Z0 = 100 m. Continuous curves account for the observed coupling of sinking and degradation (blue continuous curve) or exclude this coupling (reference case, red continuous curve), as in Fig. 4, for estimates of degradation rate at temperature T = 25 °C. The degradation rates of both coupled and uncoupled cases were also modelled while considering the reduction of degradation rate with decreasing temperature, assuming a reduction by a factor 2.5 for each 10 °C decrease in temperature, (i.e. temperature coefficient Q10 = 2.5). The results are presented for two alternative assumptions: 1) the degradation rate is uniform over the water column but corresponds to a temperature T = 15 °C (dashed curves); 2) a fitted temperature profile T(Z) for subtropical waters (see equation (17) Supplementary Information) modulates degradation over the water column (dash-dotted curves). For both assumptions, red curves correspond to the uncoupled reference case while blue curves correspond to the sinking–degradation coupled case. All curves were derived from the following initial conditions: total concentration 200 particles l-1 at initial depth Z0 = 100 m and a PSD slope of -4 over particles of radii ranging between 125 and 750 µm. As our experimental degradation rate was measured at T = 25 °C, the reduction of degradation rate imposed by considering T = 15 °C or a complex profile T(Z) both result in a weaker attenuation of the flux with depth. However, note that regardless of this effect of temperature, there remains a strong attenuation of POC flux with sinking–degradation coupling with respect to the reference uncoupled case.

Extended Data Fig. 9 Varying viscosity with seawater temperature has only a minor effect on the modelled POC flux.

Shown is the vertical flux of POC as a function of depth, F(Z), normalized by its value F(Z0) at the euphotic layer depth, Z0 = 100 m, predicted by our model when accounting for the observed coupling of sinking and degradation (blue continuous curve) or when excluding this coupling (reference case, red continuous curve), as in Fig. 4. Also shown are results from models in which seawater viscosity varies with temperature, both in the coupled (dark blue dashed curve) and uncoupled case (dark red dashed curve). The temperature profile corresponds to subtropical waters with a sharp decrease with depth (see equation (17) Supplementary Information). All curves were derived from the following initial conditions: total concentration 200 particles l-1 at initial depth Z0 = 100 m and a PSD slope of -4 over particles of radii ranging between 125 and 750 µm.

Extended Data Fig. 10 Flow plays a key role in determining bacterial degradation of chitin and chitosan particles.

(a,c) Time series of particle volume during bacterial degradation of chitin (a) and short-chain chitosan (c) particles under flow of 7.25 m day-1 and under no-flow conditions (shown relative to initial volume; mean and SD; n = 3 replicate experiments, except for flow in (a) for which n = 4). (b,d) Maximum degradation rate of chitin (b) and chitosan (d) particles. The apparent degradation rate is ~4-fold faster (chitin) or ~2.5-fold faster (chitosan) in flow compared to no-flow conditions. Note that the degradation rate estimated from volume loss in the case of chitin and chitosan is only a proxy for the mass loss, since Vibrio splendidus (1A01) and Psychromonas (6C06) degrade the particle using membrane-bound enzymes but possibly also by using secreted enzymes52,53. Thus, unlike the case for alginate, degradation may occur from within the particle as well as on the surface, so that measurements of volume reduction may underestimate degradation rate. Flow speed in all panels is represented by colour; blue – no flow, orange – flow speed of 7.25 m day-1. Movies showing the degradation dynamics can be provided by the authors upon request.

Supplementary information

Supplementary Information

Supplementary model description, text, discussion, captions for Supplementary Videos 1–5 and references.

Supplementary Table 1 Description of V. cyclitrophicus ZF270.

Supplementary Table 2 Alginate lyases of V. cyclitrophicus ZF270 (NCBI Taxon ID - 1136176).

41561_2021_817_MOESM4_ESM.mp4

Supplementary Video 1 Alginate degradation dynamics are flow dependent. Degradation dynamics of alginate particles, observed in a microfluidic channel, under different rates of flow. Images of the mid plane of each particle were acquired in phase and fluorescence microscopy every 20 min for 70 h (Methods). Brightness and contrast in the green channel (bacterial fluorescence) were adjusted in each panel to better visualize bacterial growth. a, No flow. b, 1.1 m day−1. c, 4.4 m day−1. d, 21.8 m day−1. Presented are representative movies of the degradation dynamics.

41561_2021_817_MOESM5_ESM.mp4

Supplementary Video 2 Growth dynamics on alginate particles are flow dependent. Representative movie of bacterial growth on an alginate particle. Images acquired as in Supplementary Video 1, but at the interface between the glass slide and the alginate particle. a,b, Growth dynamics without flow (a) and with a slow flow rate of 1.1 m day−1 (b).

41561_2021_817_MOESM6_ESM.mp4

Supplementary Video 3 High concentrations of oligo-alginate promote bacterial biofilm formation and inhibit the degradation of alginate particles. Representative movie of the degradation dynamics of particles exposed to different concentrations of oligo-alginate (<10 kDa) or marine broth 2216 medium (1%). Images acquired as in Supplementary Video 1. Brightness and contrast are comparable between panels. Flow of oligo-alginate or 1% 2216 medium in the channel was started 17 h after the beginning of the experiment (Methods). All experiments were performed at a flow rate of 7.25 m day−1.

41561_2021_817_MOESM7_ESM.mp4

Supplementary Video 4 High concentrations of oligo-alginate inhibit the enzymatic degradation of alginate particles. Enzymatic degradation of alginate particles in the presence of oligo-alginate. Images were acquired every minute for 127 min for the control and for 180 min for the experiments (Methods). a, Control (oligo-alginate only, 1 mg ml−1). b, Alginate lyase (10 µg ml−1). c, Oligo-alginate (1 mg ml−1) and alginate lyase (10 µg ml−1). All experiments were performed at a flow rate of 7.25 m day−1.

41561_2021_817_MOESM8_ESM.mp4

Supplementary Video 5 Degradation dynamics of chitin particles is flow dependent. Degradation dynamics of chitin particles by V. splendidus (1A01) and Psychromonas (6CO6), observed in a microfluidic channel, under a flow rate of 7.25 m day−1 or with no flow. Images of the mid plane of each particle were acquired in phase microscopy every 20 min for 240 h (Methods). a, No flow. b, 7.25 m day−1. Presented are representative movies of the degradation dynamics.

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Alcolombri, U., Peaudecerf, F.J., Fernandez, V.I. et al. Sinking enhances the degradation of organic particles by marine bacteria. Nat. Geosci. 14, 775–780 (2021). https://doi.org/10.1038/s41561-021-00817-x

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