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Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales

Regina L. Wilpiszeski, Jayde A. Aufrecht, Scott T. Retterer, Matthew B. Sullivan, David E. Graham, Eric M. Pierce, Olivier D. Zablocki, Anthony V. Palumbo, Dwayne A. Elias
Volker Müller, Editor
Regina L. Wilpiszeski
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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  • ORCID record for Regina L. Wilpiszeski
Jayde A. Aufrecht
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Scott T. Retterer
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Matthew B. Sullivan
bDepartment of Microbiology, The Ohio State University, Columbus, Ohio, USA
dDepartment of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA
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David E. Graham
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Eric M. Pierce
cEnvironmental Sciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Olivier D. Zablocki
bDepartment of Microbiology, The Ohio State University, Columbus, Ohio, USA
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Anthony V. Palumbo
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Dwayne A. Elias
aBiosciences Division, Oak Ridge National Laboratory, Oak Ridge, Tennessee, USA
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Volker Müller
Goethe University Frankfurt am Main
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DOI: 10.1128/AEM.00324-19
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  • FIG 1
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    FIG 1

    Simplified schematic of soil horizon and soil macro- and microaggregates. Important properties include local chemistry, surface area, pore sizes within and between aggregates, surface roughness, and connectivity. POM, particulate organic matter.

  • FIG 2
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    FIG 2

    Conceptual drawing of isolated micro- and macroaggregates during (left) dry conditions and (right) wet conditions. Wet conditions would allow for nutritional, microbial, viral and metabolite dispersal.

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    FIG 3

    Microfluidic approaches can recreate soil features for lab-based studies. (A) A heterogeneous porous medium design replicates the natural shape and distribution of sand particles. (B) Within these pore spaces, bacteria grow (green) and decay (red) under the influence of pressure-driven flow (scale bar = 100 μm). (C) A consistent particle layout between replicates allows the pore space hydrodynamics to be computationally simulated. (D) This system showed that a soil bacteria initially clogs pores with high shear rates (scale bar = 100 μm). (E) A random pore network generated from Voronoi tessellations was used to study two-phase flow underground. (F) A microfluidic design created by a particle-generating algorithm was used to study the influence of microbial extracellular polysaccharides on pore space water retention. For more information regarding the associated techniques, see references 124 (A to D), 125 (E), and 126 (F).

Tables

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  • TABLE 1

    Length scales relevant for interactions between soil particles and microbes

    Size (μm)Biological relevanceSoil relevanceInteraction
    <1Viral particle sizes,a E. coli cells deform (300 nm)bParticle surface roughness promotes selective adhesion of specific bacterial species (10–100 nm)cLysogeny and gene transfer,d bacterial shape deformation,b surface attachmentc
    1–2Bacterial cell sizebPores within soil microaggregateseNitrogen fixationf
    1–15Fungal hyphal diam,g bacterial biofilm thickness in (0.12-mm-diameter) sandhFungal mycelia reinforce aggregate tensile strength,i bacterial biofilm EPS production binds soil particles togetherj
    10–30Distance at which majority of bacterial cell interactions occur (<20 μm)kPores between soil microaggregates, can retain water against gravity for multiple dayseDenitrification,l quorum-sensing bacteria exhibit inhibited cell divisionm
    • ↵a Williamson et al. (134).

    • ↵b Männik et al. (137).

    • ↵c Hol and Dekker (127).

    • ↵d Canchaya et al. (64).

    • ↵e Watt et al. (36).

    • ↵f Chotte et al. (44).

    • ↵g Friese and Allen (138).

    • ↵h Or et al. (139).

    • ↵i Rillig et al. (140).

    • ↵j Alami et al. (141).

    • ↵k Raynaud and Nunan (35).

    • ↵l Lensi et al. (43).

    • ↵m Boedicker et al. (142).

  • TABLE 2

    Advanced analytical techniques used to determine the physicochemical characteristics of aggregatesa

    MethodSample sizeResolutionLimitationsInformation collectedReference(s)
    SANS150-μm-thick sections1 nm to 0.8 μmTechnique relies on the contrasting agent (D2O/H2O), diffusion of contrasting agent to estimate pore connectivity, requires a long time to collect data, and pore geometry is assumed for when analyzing natural samplesParticle size distribution, pore vol, surface roughness, surface area, and interconnected porosity143
    USANS150-μm-thick sections60 nm to 20 μm
    FIB-T10 μm310 nm to 0.1 μmSmall sample volume used in analysis, and the technique is destructive, which limits reproducibilityPore vol, porosity, pore size statistics, and connected and unconnected pore network; also, data can be correlated to elemental composition using EDS144, 145
    ET100-nm needle<1 nm to 0.05 μmSmall sample volume, fixed-needle geometry, and technique relies on image analysis and 3D reconstructionPore geometry and connectivity; pore data can be cross-correlated with elemental composition using EDS146
    BSEMThin sections100 nm to ∼500 μm2D analysis of a 3D geometry requires sample prep, and technique relies on image analysis to distinguish intra- and intergrain porosityPore geometry and connectivity; pore data can be cross-correlated with elemental composition using EDS145
    XCT1 mm by 5-mm cylinders to 10-cm-diam cores300 nm to 100 μmbTechnique relies on image analysis and 3D reconstructionResults allow for full reconstruction of pore network147
    MIP3.38 cm32 nm to 500 μmTechnique only measures connected porosity and assumes pore geometryResults provide details on pore vol, pore size distribution, and surface area148
    PGAPowder samples0.5 nm to 0.2 μmTechnique only measures connected porosity and assumes pore geometryResults provide details on pore vol, pore size distribution, and surface area149
    • ↵a SANS, small-angle neutron scattering; USANS, ultrasmall-angle neutron scattering; FIB-T, focused ion beam tomography; ET, electron tomography; BSEM, backscattered scanning electron microscopy; XCT, X-ray computed tomography; MIP, mercury intrusion porosimetry; PGA, physical gas adsorption; EDS, energy dispersive spectroscopy. Table adapted from Zachara et al. (89).

    • ↵b Actual detectable pore size resolution will vary depending upon X-ray source, optics, and material.

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Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales
Regina L. Wilpiszeski, Jayde A. Aufrecht, Scott T. Retterer, Matthew B. Sullivan, David E. Graham, Eric M. Pierce, Olivier D. Zablocki, Anthony V. Palumbo, Dwayne A. Elias
Applied and Environmental Microbiology Jul 2019, 85 (14) e00324-19; DOI: 10.1128/AEM.00324-19

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Soil Aggregate Microbial Communities: Towards Understanding Microbiome Interactions at Biologically Relevant Scales
Regina L. Wilpiszeski, Jayde A. Aufrecht, Scott T. Retterer, Matthew B. Sullivan, David E. Graham, Eric M. Pierce, Olivier D. Zablocki, Anthony V. Palumbo, Dwayne A. Elias
Applied and Environmental Microbiology Jul 2019, 85 (14) e00324-19; DOI: 10.1128/AEM.00324-19
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  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • OVERVIEW OF SOIL AGGREGATES
    • IMPACTS OF AGGREGATE STRUCTURE ON SOIL COMMUNITIES
    • VIRUSES IN SOIL AGGREGATES
    • STUDIES SUPPORTING AGGREGATES AS THE FUNCTIONAL UNIT OF SOIL ECOSYSTEMS
    • APPROACHES FOR ISOLATING AGGREGATE COMMUNITIES FROM NATURAL ENVIRONMENTS
    • NANOSCALE TECHNIQUES TO CHARACTERIZE AGGREGATE SCALE COMMUNITIES
    • ARTIFICIAL AGGREGATES FOR LAB-BASED COMMUNITY STUDIES
    • FUTURE DIRECTIONS
    • CONCLUSION
    • ACKNOWLEDGMENTS
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

microbial communities
soil
soil aggregate
virus

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