How the chemotactic characteristics of bacteria can determine their population patterns

Gharasoo, Mehdi; Centler, Florian; Fetzer, Ingo; Thullner, Martin

doi:10.1016/j.soilbio.2013.11.019

Cited by 27 publications

(32 citation statements)

References 60 publications

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“…Crucial extensions could include the explicit representation of enzyme dynamics (Burns et al, 2013;Moyano et al, 2018;Wang and Allison, 2019) and the implementation specific fungal traits (Yang and van Elsas, 2018). Similarly, microbial dispersal and chemotactic behavior (Valdés-Parada et al, 2009; see e.g., Gharasoo et al, 2014;Locey et al, 2017;König et al, 2018) should be included in future. Other promising extensions are quorum sensing (Williams et al, 2007;Melke et al, 2010;Mund et al, 2016;McBride and Strickland, 2019;Schmidt et al, 2019) as regulator of biological interactions, as well as to improve the modeling of top-down control of microbial communities by predators and viruses (Pratama and van Elsas, 2018;Thakur and Geisen, 2019).…”

Section: Discussionmentioning

confidence: 99%

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Pagel

Kriesche

Uksa

et al. 2020

Front. Environ. Sci.

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Trait-based models have improved the understanding and prediction of soil organic matter dynamics in terrestrial ecosystems. Microscopic observations and pore scale models are now increasingly used to quantify and elucidate the effects of soil heterogeneity on microbial processes. Combining both approaches provides a promising way to accurately capture spatial microbial-physicochemical interactions and to predict overall system behavior. The present study aims to quantify controls on carbon (C) turnover in soil due to the mm-scale spatial distribution of microbial decomposer communities in soil. A new spatially explicit trait-based model (SpatC) has been developed that captures the combined dynamics of microbes and soil organic matter (SOM) by taking into account microbial life-history traits and SOM accessibility. Samples of spatial distributions of microbes at µm-scale resolution were generated using a spatial statistical model based on Log Gaussian Cox Processes which was originally used to analyze distributions of bacterial cells in soil thin sections. These µm-scale distribution patterns were then aggregated to derive distributions of microorganisms at mm-scale. We performed Monte-Carlo simulations with microbial distributions that differ in mm-scale spatial heterogeneity and functional community composition (oligotrophs, copiotrophs, and copiotrophic cheaters). Our modeling approach revealed that the spatial distribution of soil microorganisms triggers spatiotemporal patterns of C utilization and microbial succession. Only strong spatial clustering of decomposer communities induces a diffusion limitation of the substrate supply on the microhabitat scale, which significantly reduces the total decomposition of C compounds and the overall microbial growth. However, decomposer communities act as functionally redundant microbial guilds with only slight changes in C utilization. The combined statistical and process-based modeling approach derives distribution patterns of microorganisms at the mm-scale from microbial biogeography at microhabitat scale (µm) and quantifies the emergent macroscopic (cm) microbial and C dynamics. Thus, it effectively links observable process dynamics to the spatial control by microbial communities. Our study highlights a powerful approach that can provide further insights into the biological control of soil organic matter turnover.

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Section: Discussionmentioning

confidence: 99%

Spatial Control of Carbon Dynamics in Soil by Microbial Decomposer Communities

Pagel

Kriesche

Uksa

et al. 2020

Front. Environ. Sci.

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“…The bottom layer was continuous and represented the agar, while the top layer was obtained by digitizing a microscopic image of actual fungal hyphae to represent the hyphal network. Microbial cells performed random walks (as implemented earlier52) on both layers with prescribed diffusion constants D agar and D hyphae , and could switch layers at locations where a fungal grid cell was present on top the agar grid cell according to…”

Section: Methodsmentioning

confidence: 99%

Mycelia as a focal point for horizontal gene transfer among soil bacteria

Berthold

Centler

Hübschmann

et al. 2016

Sci Rep

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Horizontal gene transfer (HGT) is a main mechanism of bacterial evolution endowing bacteria with new genetic traits. The transfer of mobile genetic elements such as plasmids (conjugation) requires the close proximity of cells. HGT between genetically distinct bacteria largely depends on cell movement in water films, which are typically discontinuous in natural systems like soil. Using laboratory microcosms, a bacterial reporter system and flow cytometry, we here investigated if and to which degree mycelial networks facilitate contact of and HGT between spatially separated bacteria. Our study shows that the network structures of mycelia promote bacterial HGT by providing continuous liquid films in which bacterial migration and contacts are favoured. This finding was confirmed by individual-based simulations, revealing that the tendency of migrating bacteria to concentrate in the liquid film around hyphae is a key factor for improved HGT along mycelial networks. Given their ubiquity, we propose that hyphae can act as focal point for HGT and genetic adaptation in soil.

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“…Implementation of these motility concepts into reactive transport models have allowed to match high resolution data on bacterial chemotaxis (Pedit et al 2002;Banitz et al 2012) and predict traveling bands of bacteria (Hilpert 2005;Saragosti et al 2010) as well as to simulate the formation of aggregated population patterns (Centler et al 2011;Gharasoo et al 2014;Centler and Thullner 2015) or the spreading of chemotactic bacteria at larger scales (Valdés-Parada et al 2009). Microorganisms can also promote the dispersal of other microbial species (Ben-Jacob et al 2016).…”

Section: Interactions Between Microbes and Their Physical Environmentmentioning

confidence: 99%

“…Thullner & Regnier 2017;Leveau et al 2018), an approach that allows considering random variations of microbial behavior or intra-species variations of cell properties. Such individual-based models have been considered also within reactive transport approaches (Gras et al 2011;Ebrahimi and Or 2014;Gharasoo et al 2014;Centler and Thullner 2015;Ebrahimi and Or 2015;Kim and Or 2016) but applications are necessarily limited to small-scale (cm-scale or below) systems given typical abundances of 10 6 cells per cm 3 or more in most porous medium environments.…”

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confidence: 99%