Exogenous nitrogen input skews estimates of microbial nitrogen use efficiency by ecoenzymatic stoichiometry

Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use effic...

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Published inEcological processes Vol. 12; no. 1; p. 46
Main Authors Sun, Lifei, Moorhead, Daryl L., Cui, Yongxing, Wanek, Wolfgang, Li, Shuailin, Wang, Chao
Format Journal Article
LanguageEnglish
Published Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2023
Springer Nature B.V
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Abstract Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use efficiency (NUE), compared EEST and 18 O-labeling methods for determining NUE, and evaluated EEST’s theoretical assumption that the ratios of standard ecoenzymatic activities balance resource availability with microbial demand. Results We found that NUE estimated by EEST ranged from 0.94 to 0.98. In contrast, estimates of NUE by the 18 O-labeling method ranged from 0.07 to 0.30. The large differences in NUE values estimated by the two methods may be because the sum of β-N-acetylglucosaminidase and leucine aminopeptidase activities in the EEST model was not limited to microbial N acquisition under exogenous N inputs, resulting in an overestimation of microbial NUE by EEST. In addition, the acquisition of carbon by N-acquiring enzymes also likely interferes with the evaluation of NUE by EEST. Conclusions Our results demonstrate that caution must be exercised when using EEST to evaluate NUE under exogenous N inputs that may skew standard enzyme assays.
AbstractList Abstract Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use efficiency (NUE), compared EEST and 18O-labeling methods for determining NUE, and evaluated EEST’s theoretical assumption that the ratios of standard ecoenzymatic activities balance resource availability with microbial demand. Results We found that NUE estimated by EEST ranged from 0.94 to 0.98. In contrast, estimates of NUE by the 18O-labeling method ranged from 0.07 to 0.30. The large differences in NUE values estimated by the two methods may be because the sum of β-N-acetylglucosaminidase and leucine aminopeptidase activities in the EEST model was not limited to microbial N acquisition under exogenous N inputs, resulting in an overestimation of microbial NUE by EEST. In addition, the acquisition of carbon by N-acquiring enzymes also likely interferes with the evaluation of NUE by EEST. Conclusions Our results demonstrate that caution must be exercised when using EEST to evaluate NUE under exogenous N inputs that may skew standard enzyme assays.
BACKGROUND: Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use efficiency (NUE), compared EEST and ¹⁸O-labeling methods for determining NUE, and evaluated EEST’s theoretical assumption that the ratios of standard ecoenzymatic activities balance resource availability with microbial demand. RESULTS: We found that NUE estimated by EEST ranged from 0.94 to 0.98. In contrast, estimates of NUE by the ¹⁸O-labeling method ranged from 0.07 to 0.30. The large differences in NUE values estimated by the two methods may be because the sum of β-N-acetylglucosaminidase and leucine aminopeptidase activities in the EEST model was not limited to microbial N acquisition under exogenous N inputs, resulting in an overestimation of microbial NUE by EEST. In addition, the acquisition of carbon by N-acquiring enzymes also likely interferes with the evaluation of NUE by EEST. CONCLUSIONS: Our results demonstrate that caution must be exercised when using EEST to evaluate NUE under exogenous N inputs that may skew standard enzyme assays.
BackgroundEcoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use efficiency (NUE), compared EEST and 18O-labeling methods for determining NUE, and evaluated EEST’s theoretical assumption that the ratios of standard ecoenzymatic activities balance resource availability with microbial demand.ResultsWe found that NUE estimated by EEST ranged from 0.94 to 0.98. In contrast, estimates of NUE by the 18O-labeling method ranged from 0.07 to 0.30. The large differences in NUE values estimated by the two methods may be because the sum of β-N-acetylglucosaminidase and leucine aminopeptidase activities in the EEST model was not limited to microbial N acquisition under exogenous N inputs, resulting in an overestimation of microbial NUE by EEST. In addition, the acquisition of carbon by N-acquiring enzymes also likely interferes with the evaluation of NUE by EEST.ConclusionsOur results demonstrate that caution must be exercised when using EEST to evaluate NUE under exogenous N inputs that may skew standard enzyme assays.
Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under exogenous nitrogen (N) input has never been clarified. Here, we investigated the effects of long-term N addition (as urea) on microbial N use efficiency (NUE), compared EEST and 18 O-labeling methods for determining NUE, and evaluated EEST’s theoretical assumption that the ratios of standard ecoenzymatic activities balance resource availability with microbial demand. Results We found that NUE estimated by EEST ranged from 0.94 to 0.98. In contrast, estimates of NUE by the 18 O-labeling method ranged from 0.07 to 0.30. The large differences in NUE values estimated by the two methods may be because the sum of β-N-acetylglucosaminidase and leucine aminopeptidase activities in the EEST model was not limited to microbial N acquisition under exogenous N inputs, resulting in an overestimation of microbial NUE by EEST. In addition, the acquisition of carbon by N-acquiring enzymes also likely interferes with the evaluation of NUE by EEST. Conclusions Our results demonstrate that caution must be exercised when using EEST to evaluate NUE under exogenous N inputs that may skew standard enzyme assays.
ArticleNumber 46
Author Sun, Lifei
Moorhead, Daryl L.
Li, Shuailin
Wang, Chao
Cui, Yongxing
Wanek, Wolfgang
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crossref_primary_10_3390_agronomy15030731
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Keywords Nitrogen addition
Isotope labeling
Extracellular enzyme
Resource allocation
Microbial metabolism limitation
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Snippet Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under...
BackgroundEcoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under...
BACKGROUND: Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models under...
Abstract Background Ecoenzymatic stoichiometry models (EEST) are often used to evaluate microbial nutrient use efficiency, but the validity of these models...
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StartPage 46
SubjectTerms Aminopeptidase
carbon
Earth and Environmental Science
Efficiency
Environment
Estimates
Extracellular enzyme
Isotope labeling
Labeling
Leucine
leucyl aminopeptidase
Microbial metabolism limitation
microbial nitrogen
Microorganisms
N-Acetylglucosaminidase
Nitrogen
Nitrogen addition
nutrient use efficiency
Resource allocation
Resource availability
Stoichiometry
Urea
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Title Exogenous nitrogen input skews estimates of microbial nitrogen use efficiency by ecoenzymatic stoichiometry
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