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. 2021 May 11;12(3):e03620-20.
doi: 10.1128/mBio.03620-20.

Controls on Interspecies Electron Transport and Size Limitation of Anaerobically Methane-Oxidizing Microbial Consortia

Xiaojia He  1 , Grayson L Chadwick  2 , Christopher P Kempes  3 , Victoria J Orphan  2 , Christof Meile  4
Affiliations

Controls on Interspecies Electron Transport and Size Limitation of Anaerobically Methane-Oxidizing Microbial Consortia

Xiaojia He et al. mBio. .

Abstract

About 382 Tg yr-1 of methane rising through the seafloor is oxidized anaerobically (W. S. Reeburgh, Chem Rev 107:486-513, 2007, https://doi.org/10.1021/cr050362v), preventing it from reaching the atmosphere, where it acts as a strong greenhouse gas. Microbial consortia composed of anaerobic methanotrophic archaea and sulfate-reducing bacteria couple the oxidation of methane to the reduction of sulfate under anaerobic conditions via a syntrophic process. Recent experimental studies and modeling efforts indicate that direct interspecies electron transfer (DIET) is involved in this syntrophy. Here, we explore a fluorescent in situ hybridization-nanoscale secondary ion mass spectrometry data set of large, segregated anaerobic oxidation of methane (AOM) consortia that reveal a decline in metabolic activity away from the archaeal-bacterial interface and use a process-based model to identify the physiological controls on rates of AOM. Simulations reproducing the observational data reveal that ohmic resistance and activation loss are the two main factors causing the declining metabolic activity, where activation loss dominated at a distance of <8 μm. These voltage losses limit the maximum spatial distance between syntrophic partners with model simulations, indicating that sulfate-reducing bacterial cells can remain metabolically active up to ∼30 μm away from the archaeal-bacterial interface. Model simulations further predict that a hybrid metabolism that combines DIET with a small contribution of diffusive exchange of electron donors can offer energetic advantages for syntrophic consortia.IMPORTANCE Anaerobic oxidation of methane is a globally important, microbially mediated process reducing the emission of methane, a potent greenhouse gas. In this study, we investigate the mechanism of how a microbial consortium consisting of archaea and bacteria carries out this process and how these organisms interact with each other through the sharing of electrons. We present a process-based model validated by novel experimental measurements of the metabolic activity of individual, phylogenetically identified cells in very large (>20-μm-diameter) microbial aggregates. Model simulations indicate that extracellular electron transfer between archaeal and bacterial cells within a consortium is limited by potential losses and suggest that a flexible use of electron donors can provide energetic advantages for syntrophic consortia.

Keywords: FISH-nanoSIMS; activation loss; anaerobic oxidation of methane; conductive network density; conductivity; direct interspecies electron transfer; electron conduction; ohmic resistance; spatial statistics; stable isotope probing; syntrophy.

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Figures

FIG 1
FIG 1
Overview of AOM consortium structure, nanoSIMS data acquisition, analysis, and model geometry. (A) Cartoon of AOM consortium structure based on FISH-nanoSIMS observations of five parallel sections corresponding to dashed lines. (B) Five parallel sections highlighted in panel A analyzed by nanoSIMS. Top row, raw 14N12C− secondary ion counts illustrating the position of cells. Bottom row, fractional abundance of 15N calculated as 15N12C−/(15N12C−+14N12C−), all scaled to the same intensity. Note sulfate-reducing bacteria (SRB) assimilate significantly more 15N, on average, than their ANME-2 counterparts, as has been previously shown (17). (C) Illustration of nanoSIMS data extraction and modeled geometry. From left to right, FISH image indicating phylogenetic identity of cells (green, general bacterial probe [Eub338mix]; red, ANME-2b-specific probe [ANME-2b-729]; blue, DNA stain [DAPI]); segmentation image showing SRB and ANME cells manually segmented based on observation of FISH and nanoSIMS data; individual segmented cells shaded by their total 15N fractional abundance; SRB and ANME cells scaled by minimum and maximum values within the population; and illustration of modeled aggregate geometry (the dashed line represents axis of rotation). The yellow X marks the approximate minimum ANME cell activity. Note that additional sections were visually inspected to help verify aggregate structure. Only those analyzed by nanoSIMS analysis are shown. This figure contains tiled images that were stitched together to make these composite images. Black regions within the image are places where the square tiles did not overlap.
FIG 2
FIG 2
Measured and modeled cell-specific activity in aggregates with a radius of 20 μm (A; this study) and 5 μm (B; 17), plotted against their distance from the closest syntrophic partner (interface). Data were fitted using linear regression with 95% confidence intervals. Note that the cell-specific rate constants were not retuned to match the activities in the small aggregate.
FIG 3
FIG 3
Cell-specific activity versus distance from syntrophic partner for archaea (A) and bacteria (B). For a wide range of aggregate sizes (ragg = 5, 20, 40, and 100 μm), the simulated activity distribution is similar and depends on the distance from the interface between archaea and bacteria.
FIG 4
FIG 4
Factors controlling cell activity as a function of the distance from the archaeal-bacterial interface at aggregate radius of 60 μm for archaea (A) and bacteria (B). The left axis reflects electric potential for activation loss (ηact), ohmic resistance loss (ηom), net available potential (ηnet), potential from reaction (ηrxn), and minimum potential required for ATP synthesis (ηATP). The right axis reflects the thermodynamic factor, FT. The shaded areas highlight the range of distances encountered in the observed aggregate with a 20-μm radius (Fig. 1).
FIG 5
FIG 5
Changes of activation loss, Δηact (A), ohmic resistance loss, Δηom (B), and net available potential, Δηnet (C), due to a change in total redox active molecules (Mtot), number of conductive connections (Nnw,cell), conductivity (σ), cell redox active factor (kact×Aact), and cell rate constants (kA and kB). Error bars reflect that the impact is not exactly constant with distance for archaeal-bacterial interface (see Fig. S11 to S13 at https://doi.org/10.6084/m9.figshare.13536086.v2).
FIG 6
FIG 6
Gibbs free energy change (ΔG) against the change of electron conduction via DIET. Circles and triangles represent bacteria and archaea, respectively. Simulations were run at an aggregate radius of 20 μm with baseline parameters. The estimated ΔGR(3) and ΔGR(4) were calculated with CH4 = 4.5 mM, SO42− = 28 mM, HCO3− = 2.3 mM, HS− = 0.1 mM, MH = M = 5 mM, pH = 8.2, and T = 277.15K, with HCOO− varying between 0.1 and 100 μM to reflect different intra-aggregate and/or environmental conditions. The light and dark gray-shaded areas represent the resulting 95% confidence intervals for the Archaea and Bacteria, respectively.
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