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Abstract Microbial decomposition of Soil Organic Matter (SOM) is largely controlled by environmental and edaphic factors such as temperature, pH, and moisture. However, microbial metabolism is controlled by catabolite repression, which leads microbes to grow on preferred nutrient and energy sources first. In particular, Catabolite Repression for Carbon (CR-C) defines the hierarchical preference of bacteria for particular C sources. This control depends on the presence of signal molecules conferring bacteria a memory for recent growth conditions on less preferred C sources. The combined effect of catabolite repression and microbial memory (called here Memory-Associated Catabolite Repression for Carbon, MACR-C) has not yet been investigated in detail. First, we use observations and a numerical model to test the hypothesis that MACR-C explains substrate preferential consumption in a simple, 2-C substrate system, whereas Michaelis-Menten-Monod kinetics of competitive substrate consumption, non-competitive inhibition, or their combination, do not. Next, we carry out numerical analyses to explore the sensitivity of (1) estimated parameters to experimental observations and (2) model structure to steady-state substrate concentration under pulse or continuous substrate application. Our results show that MACR-C substantially affected substrate consumption and microbial readiness to switch between C sources. Highlights • The Memory-Associated Catabolite Repression for Carbon (MACR-C) is presented. • MACR-C kinetics are tested on carbon catabolite repression (CR-C) observations. • MACR-C can explain regulation of soil carbon consumption by bacteria. • MACR-C may support the development of robust mechanistic land models. • Generalized MACR-C (MACR) may explain macronutrient cycles and their cross-talk. [ABSTRACT FROM AUTHOR]

Mechanistic descriptions of microbial processes are difficult to embed in ecosystem models because they require complex mathematical formulations. The interactions between microbes, soil carbon (C), and water availability are particularly complex, as they involve coupled physical (advection and diffusion in unsaturated media) and biochemical processes (enzymatic reactions, C uptake by microbes). Here we propose an approximated equation based on a quasi-equilibrium assumption that describes microbial uptake of soil C as a function of soil moisture and organic matter content during soil drying. The equation predicts that uptake depends on two terms, one dependent on soil organic C concentration and enzyme availability (analogous to a Michaelis–Menten equation) and one dependent on soil moisture via its effects on enzyme and solute mass transfer, and microbial uptake kinetics. Assuming that uptake is proportional to microbial respiration, model results are compared to measured respiration–water potential curves. Using independently estimated parameter values (except for the calibrated microbial uptake efficiency), the theoretical model captures well the respiration decline during drying and provides an explanation of respiration pulses at rewetting. Thus, this simple formulation could be employed in ecosystem models as an alternative to empirical respiration–moisture response functions. [ABSTRACT FROM AUTHOR]

The response of soil CO2 fluxes (Rsoil) to interactions between carbon (C) and nitrogen (N) availability or C and temperature conditions is not well understood, but may increasingly affect future C storage under the combined anthropogenic impacts of N deposition and climate change. Here we addressed this uncertainty through a series of laboratory incubation experiments using soils from three contrasting ecosystems to investigate how changes in C, N, and temperature regulate Rsoil through changes to Michaelis-Menten parameters (i.e. Vmax and Km). Results of this study demonstrate that Rsoil response to N enrichment and changes in temperature are dependent on the C availability of soil substrates. N addition influenced Rsoil through both the maximum rate (Vmax) and the half saturation constant (Km). The increase in Km corresponded to a decrease in Rsoil when C was limited. Alternatively, when C was abundant, N enrichment increased Rsoil, which corresponded to an increase in Vmax. Regulation of temperature sensitivity through Vmax and Km was also dependent on C availability. Both Vmax and Km demonstrated positive temperature responses, supporting the hypothesis of a canceling effect at low C concentrations. While temperature sensitivity was influenced by both C quantity and C complexity, our results suggested that C quantity is a stronger predictor. Despite strong differences in climate, vegetation, and management of our soils, C-N and C-temperature interactions were markedly similar between sites, highlighting the importance of C availability in the regulation of Rsoil and justifying the use of Michaelis-Menten kinetics in biogeochemical modeling [ABSTRACT FROM AUTHOR]

Abstract: We theoretically derived a general equation describing the enzyme kinetics that could be further simplified to the typical Michaelis–Menten (M–M) kinetics or the reverse M–M equation (RM–M) under the condition of S ≈ S 1 >> E 0 or S 1 << E 0, respectively, where E 0 and S 1 (=S + ES) are the concentrations of total enzyme and substrate including free substrate (S) and enzyme–substrate complex (ES). We showed that the related Schimel and Weintraub RM–M equation (RM–M–SW) can be derived from the Langmuir adsorption isotherm theory with S >> E 0. Both the M–M and the RM-M-SW are appropriate to field soil conditions with S >> E 0 given different values of specific reaction rate (k 3) and half-saturation constant (K s). In contrast to M–M and RM–M–SW models, the RM–M model is not applicable to field conditions because of its limited application to one substrate with a simple enzyme system. However, we demonstrate that the best formulation for the process of enzyme-mediated decomposition may vary depending on whether the process is limited by substrate or enzyme availability. [Copyright &y& Elsevier]

Abstract: We describe experiments to better understand how CH4 oxidation rates by different methanotroph communities respond to changing CH4 concentrations. We used a novel system of automatically monitored chambers to investigate the response of CH4 oxidation rates in a New Zealand pasture and adjacent pine forest soil exposed to varying atmospheric CH4 concentrations. Type II methanotrophs that dominate CH4 oxidation in the forest soil became progressively saturated as CH4 concentrations rose from ambient (1.8ppmv) to 570ppmv, as shown by a decrease in uptake efficiency from 20% to 2% removal. By contrast, CH4 oxidation in the pasture soil where Type I methanotrophs dominate increased in proportion to the increase in CH4 inlet concentration, oxidising about 2% of the inlet CH4 flux throughout. Modelling based on Michaelis-Menten kinetics revealed that low-affinity (Type I) methanotrophs were solely responsible for CH4 oxidation in pasture soils, whereas high affinity (Type II) methanotrophs only contributed about 10% of the CH4 oxidation in the forest soil. Increased aeration status using a soil–perlite (1:1) mixture doubled CH4 oxidation rates at both ambient (1.8ppmv) and 40ppmv atmospheric CH4. A similar volcanic soil previously exposed for 8 y to high CH4 fluxes from a landfill had removal efficiencies consistently above 95% for atmospheric CH4 concentrations up to 7500ppmv when the CH4 oxidation rate was7000μg CH4 kg−1soil h−1. [Copyright &y& Elsevier]

Abstract: We investigated extraction from soil of glomalin, a glycoprotein produced by arbuscular mycorrhizal fungi, and we examined its measurement. The most commonly used protocols for extracting glomalin require autoclaving of soil in citrate solution, followed by centrifugation to separate the supernatant, and then measurement by either Bradford protein assay or enzyme-linked immunosorbent assay (ELISA). We found that lengthening the time of autoclaving increased easily extractable glomalin extraction. Delay of centrifugation after autoclaving, however, diminished Bradford-reactive substances in the supernatant, suggesting that extracted substances might be reversibly immobilized on soil particles. Surprisingly, increasing the volume of extraction solution did not accelerate extraction of “total glomalin”, but instead, substantially increased the amount extracted. Multiple autoclave cycles nevertheless denature glomalin, which may not be as heat-resistant as thought. Repeated 1-h autoclaving of supernatant diminished both its Bradford-reactive substances (7.3%h−1) and immunoreactive protein (22% during the first hour and 9.5%h−1 of the remainder thereafter), although a large initial volume of extractant could reduce the loss of immunoreactive protein. Proteins and polyphenols that survive the extraction process are measured non-specifically by the Bradford assay. When we added other glycoproteins to dry soils, we recovered a maximum 34% bovine serum albumin and 22% bovine mucin, primarily in the first two, 1-h extraction cycles. These added proteins may adhere to soil organic matter and thereby be protected from denaturation. In addressing the endpoint of glomalin extraction, we found that the Michaelis–Menten equation closely fits cumulative glomalin per extraction cycle such that its asymptote provides an objective estimate of total extractable glomalin for a given set of extraction conditions. Additionally, the equation provides a curvature parameter that reflects the soil-specific efficiency of an extraction protocol. Although the soils that we investigated with 7.6% or more soil organic matter had the most asymptotic total glomalin, they were extracted the least efficiently. [Copyright &y& Elsevier]

Membrane zymography is commonly used in rhizosphere ecology to map enzyme activities in intact soil samples and plant roots. The method consists of incubating a membrane saturated with an enzyme-specific fluorogenic substrate on the soil/root surface followed by measurements of fluorescence intensity of the product in the membrane. The traditional zymography is based on assumptions that fluorescence on membrane images is linearly increasing with time during zymography and an increase in product content is numerically equal to enzyme activity in soil below the membrane. These assumptions are unlikely to hold in experimental settings. Here we introduce a new zymography technique, time-lapse zymography (TLZ) ; the approach that eliminates the need for assumptions of the traditional zymography and provides more realistic estimates of enzymatic activities. We assessed the new technique in a series of laboratory and modeling experiments, including quantification of the fluorescent product diffusion (e.g. MUF: 4-methylumbelliferone) from plant roots, enzyme activity measurements on the roots, and HYDRUS-2D & HP2 software calibration with obtained data. The calibrated model was used to analyze the processes governing spatial and temporal dynamics of MUF contents in the membrane. The results indicated that the enzyme diffusion within the membrane-soil system was negligible, and measured zymograms were adequately reproduced solely by accounting for substrate and product diffusions and for catalytic enzyme reaction described by the Michaelis-Menten equation. TLZ enabled identifying and using linear parts on MUF time series and accounting for MUF losses in each zymogram pixel, considerably improving the accuracy as compared to the traditional method. Results demonstrated that enzymatic activity from only a thin soil layer (~0.2 mm) is adequately represented in zymograms. [Display omitted] • Soil zymography ignores product diffusion and underestimates enzyme activity. • New time-lapse zymography (TLZ) accounts for diffusion processes. • TLZ produces realistic assessments of spatial soil enzyme activity. [ABSTRACT FROM AUTHOR]

We consider when to use the reverse Michaelis-Menten (RMM) or original Michaelis-Menten (MM) equation in decomposition models. Both are saturating functions with maximum reaction rates estimated by multiplying rate coefficients by concentrations of substrate or enzyme, respectively. Combining them into a composite function allows saturation by either enzymes or substrate, but is complicated when insoluble substrates and soluble enzymes are combined because they are quantified differently. Instead, we support selecting between equations by comparing their relative parameter estimates with enzyme and substrate concentrations. [ABSTRACT FROM AUTHOR]

Abstract: We show that water-extractable soil organic matter may inhibit activity of added phosphatase. The inhibition was greater for the topsoils than the corresponding subsoils. The enzyme kinetics in buffer and in soil solutions followed Michaelis–Menten kinetics. Vmax decreased and Km increased with increasing soil water-extractable organic carbon. Both kinetic parameters followed similar trends with the intensities of both fluorescence peaks of the solutions. The effect was more marked at pH below the optimum pH. Inhibition was complex, particularly for topsoil solutions where Vmax was decreased and Km increased. This effect could lead to underestimation of catalytic activity of enzymes extracted from soil and could result in the overestimation of decreased specific activity in the adsorbed phase of enzymes added to soils. [Copyright &y& Elsevier]

Plant residues and soil organic matter are predominantly decomposed by exoenzymes. Many soil carbon models now represent enzymatic decomposition, but the mathematical formulation of this process has been debated over the last 15 years. Some models apply the traditional "forward" Michaelis-Menten equation to represent enzyme kinetics, whereas others apply the "reverse" Michaelis-Menten equation, which assumes that kinetic rates saturate at high enzyme concentrations. Recently the equilibrium chemistry approximation (ECA) has been proposed as an alternative to both Michaelis-Menten formulations. However, because of methodological limitations, in-situ enzyme kinetics—especially in the context of soil system heterogeneity—have been difficult to verify experimentally. Therefore, the overarching goal of our study was to evaluate different enzyme kinetic formulations using model-based evidence at microbial to ecosystem scales. We used a spatially explicit individual- and trait-based microbial model, DEMENT, to circumvent methodological challenges. Although DEMENT assumes forward Michaelis-Menten kinetics at local scales, at the grid scale we found saturating relationships between degradation rate and both substrate concentrations and enzyme concentrations that fit the forward and reverse Michaelis-Menten equations, respectively, at specific successional stages during decomposition. Although forward and reverse Michaelis-Menten equations emerged under some conditions, only the ECA adequately represented decay rates emerging from the spatial-temporal variation in substrate and enzyme concentrations throughout the decomposition process. Our results support a more widespread adoption of the ECA equation in soil biogeochemical modelling at ecosystem scales. 1. Representation of enzymatic decomposition in soil carbon models is under debate 2. We use a spatially explicit trait-based model to overcome methodological challenges 3. Michaelis-Menten equations fail to capture emergent spatial-temporal variation 4. Equilibrium Chemistry Approximation (ECA) captures emergent patterns very well 5. ECA can be adopted to scale up fine scale heterogeneity in ecosystem models [ABSTRACT FROM AUTHOR]