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Abstract Delineation of microbial habitats within the soil matrix and characterization of their environments and metabolic processes are crucial to understand soil functioning, yet their experimental identification remains persistently limited. We combined single- and triple-energy X-ray computed microtomography with pore specific allocation of¹³C labeled glucose and subsequent stable isotope probing to demonstrate how long-term disparities in vegetation history modify spatial distribution patterns of soil pore and particulate organic matter drivers of microbial habitats, and to probe bacterial communities populating such habitats. Here we show striking differences between large (30-150 µm Ø) and small (4-10 µm Ø) soil pores in (i) microbial diversity, composition, and life-strategies, (ii) responses to added substrate, (iii) metabolic pathways, and (iv) the processing and fate of labile C. We propose a microbial habitat classification concept based on biogeochemical mechanisms and localization of soil processes and also suggests interventions to mitigate the environmental consequences of agricultural management. 

Abstract Delineation of microbial habitats within the soil matrix and characterization of their environments are crucial to understand soil functioning and carbon (C) cycling. Yet, experimental identification of microbial communities populating specific micro-habitats and assessments of their biochemical properties have been persistently limited. Here we demonstrate how long-term disparities in vegetation history modify spatial distribution patterns and properties of soil pores and particulate organic matter (POM), and show striking differences in bacterial communities populating pores of contrasting sizes in soils from three vegetation systems on the same soil type: an intensive corn (Zea mays L.) rotation, monoculture switchgrass (Panicum virgatum L.), and restored North American prairie. We combined single- and triple-energy X-ray computed microtomography (µCT) with pore specific allocation of 13 C labeled glucose and subsequent stable isotope probing (¹³C-DNA/RNA-SIP) to show that large (30-150 µm Ø) and small (4-10 µm Ø) soil pores differed in (i) microbial diversity, composition, and life-strategies, (ii) responses to added substrate, (iii) metabolic pathways, and (iv) the processing and fate of labile C. Results demonstrate that soil pores created by different plant communities differ in ways that strongly influence microbial composition and activity, and thus impact ecosystem processes such as decomposition, nitrogen processing, and carbon sequestration. A proposed classification scheme may improve biogeochemical models of soil processes and as well suggest interventions to mitigate the environmental consequences of agricultural management. 

Abstract Understanding N uptake by plants, the N cycle, and their relationship to soil heterogeneity has generated a great deal of interest in the distribution of amino-N compounds in soil. Visualization of the spatial distribution of amino-N in soil can provide insights into the role of labile N in plant-microbial mechanisms of N acquisition and plant N uptake, but until now, it has remained technically challenging. Here, we describe a novel technique to visualize the amino-N distribution at the root-soil interface. The technique is based on time-lapse amino mapping (TLAM) using membranes saturated with the fluorogenic OPAME reagent ( O -phthalaldehyde and β-mercaptoethanol). OPAME in the membrane reacts with organic compounds containing a NH 2 functional group at the membrane-soil interface, generating a fluorescent product visible under UV light and detectable by a digital camera. The TLAM amino-mapping technique was applied to visualize and quantify the concentration of amino-N compounds in the rhizosphere of maize ( Zea Mays L.). A ten times greater amino-N concentration was detected in the rhizosphere compared to non-rhizosphere soil. The high content of amino-N was mainly associated with the root tips and was 3 times larger than the average amino-N content at seminal roots. The amino-N rhizosphere was 2 times broader around the root tips than around other parts of the roots. We concluded that TLAM is a promising approach for monitoring the fate of labile N in soils. However, the technique needs to be standardized for different soil types, plant species, and climate conditions to allow wider application. 

Soil zymography is a new technique developed to visualize two‐dimensional distributions of enzyme activities. The method consists of incubating a membrane saturated with an enzyme‐specific fluorogenic substrate on a surface of the soil sample, followed by recording the membrane image generated by a fluorescent product (e.g. MUF: methylumbelliferone) in ultraviolet light. Despite its relative ease of use, performing zymography involves multiple user‐made decisions that might affect the accuracy of enzyme activity estimates. Therefore, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We evaluated the following methodological aspects of the implementation of zymography: (a) camera settings and image processing, (b) effects of evaporation and (c) calibration procedures. Camera settings (shutter speeds or exposure time) affected the intensity of background fluorescence and signal‐to‐noise ratios (SNR). However, because their combined effects varied depending on MUF concentrations, light and camera setting need to be optimized for the expected range of MUF concentrations prior to zymography. Evaporation of MUF solution from the membrane had no effect on fluorescence. Relations between MUF concentration and intensity of fluorescence during calibrations demonstrated a saturated pattern and were strongly affected by image noise outside the optimal range (e.g. 8–14 μmMUF pixel⁻¹). We developed a new calibration approach that is based on a piecewise linear regression. The new approach accounted for specific ranges of MUF concentration and uses nonuniformly saturated membranes, reflecting the real distribution of enzyme activities in soil. The new calibration algorithm eliminated biases of the standard calibration and resulted in greater accuracy in predicting MUF concentrations. HighlightsWe developed a new approach to calibration for 2‐D soil zymography.The approach accounted for spatial nonuniformity of soil zymograms.Standard calibration resulted in systematic underestimation of enzyme activity.Soil zymography requires pixel‐based calibration with nonuniformly saturated membranes.