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Title: Calibration of 2-D soil zymography for correct analysis of enzyme distribution

Abstract

Soil zymography is a new technique developed to visualize two-dimensional distributions of enzyme activities. The method is composed 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. Thus, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We investigated 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 μm MUFmore » 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.« less

Authors:
ORCiD logo [1];  [2];  [3];  [4];  [5]
  1. Michigan State Univ., East Lansing, MI (United States)
  2. Michigan State Univ., East Lansing, MI (United States); Gottingen Univ., Gottingen (Germany)
  3. Gottingen Univ., Gottingen (Germany); Univ. of Kiel, Kiel (Germany)
  4. Gottingen Univ., Gottingen (Germany); Inst. of Physicochemical and Biological Problems in Soil Science, Pushchino (Russia)
  5. RUDN Univ., Moscow (Russia)
Publication Date:
Research Org.:
Univ. of Wisconsin, Madison, WI (United States)
Sponsoring Org.:
USDOE Office of Science (SC), Biological and Environmental Research (BER) (SC-23)
OSTI Identifier:
1506661
Grant/Contract Number:  
SC0018409
Resource Type:
Accepted Manuscript
Journal Name:
European Journal of Soil Science
Additional Journal Information:
Journal Volume: 0; Journal Issue: 0; Journal ID: ISSN 1351-0754
Country of Publication:
United States
Language:
English
Subject:
59 BASIC BIOLOGICAL SCIENCES; zymography; calibration and validation; image processing

Citation Formats

Guber, Andrey K., Kravchenko, Alexandra N., Razavi, Bahar S., Blagodatskaya, Evgenia, and Kuzyakov, Yakov. Calibration of 2-D soil zymography for correct analysis of enzyme distribution. United States: N. p., 2018. Web. doi:10.1111/ejss.12744.
Guber, Andrey K., Kravchenko, Alexandra N., Razavi, Bahar S., Blagodatskaya, Evgenia, & Kuzyakov, Yakov. Calibration of 2-D soil zymography for correct analysis of enzyme distribution. United States. doi:10.1111/ejss.12744.
Guber, Andrey K., Kravchenko, Alexandra N., Razavi, Bahar S., Blagodatskaya, Evgenia, and Kuzyakov, Yakov. Fri . "Calibration of 2-D soil zymography for correct analysis of enzyme distribution". United States. doi:10.1111/ejss.12744. https://www.osti.gov/servlets/purl/1506661.
@article{osti_1506661,
title = {Calibration of 2-D soil zymography for correct analysis of enzyme distribution},
author = {Guber, Andrey K. and Kravchenko, Alexandra N. and Razavi, Bahar S. and Blagodatskaya, Evgenia and Kuzyakov, Yakov},
abstractNote = {Soil zymography is a new technique developed to visualize two-dimensional distributions of enzyme activities. The method is composed 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. Thus, unification of the zymography methodology is required for correct estimations and comparisons of various studies. We investigated 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 μm MUF 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.},
doi = {10.1111/ejss.12744},
journal = {European Journal of Soil Science},
number = 0,
volume = 0,
place = {United States},
year = {2018},
month = {10}
}

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Figures / Tables:

Table 1 Table 1: Parameters $a$ and $b$ of the calibration Equations (1) and (2) together with root-mean-square errors (RMSEs) of MUF mass calculations from calibrations and validations. The RMSE values are followed by the name of the data set that was either used for the equation fitting (Calibration) or for equationmore » testing (Validation). All units in the Table 1 are pmol pixel-1.« less

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    Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.