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Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory

Overview of attention for article published in Frontiers in Microbiology, November 2016
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  • In the top 25% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (86th percentile)
  • High Attention Score compared to outputs of the same age and source (83rd percentile)

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Title
Temperature Sensitivity as a Microbial Trait Using Parameters from Macromolecular Rate Theory
Published in
Frontiers in Microbiology, November 2016
DOI 10.3389/fmicb.2016.01821
Pubmed ID
Authors

Charlotte J. Alster, Peter Baas, Matthew D. Wallenstein, Nels G. Johnson, Joseph C. von Fischer

Abstract

The activity of soil microbial extracellular enzymes is strongly controlled by temperature, yet the degree to which temperature sensitivity varies by microbe and enzyme type is unclear. Such information would allow soil microbial enzymes to be incorporated in a traits-based framework to improve prediction of ecosystem response to global change. If temperature sensitivity varies for specific soil enzymes, then determining the underlying causes of variation in temperature sensitivity of these enzymes will provide fundamental insights for predicting nutrient dynamics belowground. In this study, we characterized how both microbial taxonomic variation as well as substrate type affects temperature sensitivity. We measured β-glucosidase, leucine aminopeptidase, and phosphatase activities at six temperatures: 4, 11, 25, 35, 45, and 60°C, for seven different soil microbial isolates. To calculate temperature sensitivity, we employed two models, Arrhenius, which predicts an exponential increase in reaction rate with temperature, and Macromolecular Rate Theory (MMRT), which predicts rate to peak and then decline as temperature increases. We found MMRT provided a more accurate fit and allowed for more nuanced interpretation of temperature sensitivity in all of the enzyme × isolate combinations tested. Our results revealed that both the enzyme type and soil isolate type explain variation in parameters associated with temperature sensitivity. Because we found temperature sensitivity to be an inherent and variable property of an enzyme, we argue that it can be incorporated as a microbial functional trait, but only when using the MMRT definition of temperature sensitivity. We show that the Arrhenius metrics of temperature sensitivity are overly sensitive to test conditions, with activation energy changing depending on the temperature range it was calculated within. Thus, we propose the use of the MMRT definition of temperature sensitivity for accurate interpretation of temperature sensitivity of soil microbial enzymes.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 90 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 1 1%
Unknown 89 99%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 21 23%
Researcher 17 19%
Student > Master 13 14%
Professor 7 8%
Student > Doctoral Student 5 6%
Other 15 17%
Unknown 12 13%
Readers by discipline Count As %
Agricultural and Biological Sciences 24 27%
Environmental Science 20 22%
Biochemistry, Genetics and Molecular Biology 10 11%
Earth and Planetary Sciences 3 3%
Engineering 2 2%
Other 6 7%
Unknown 25 28%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 11. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 January 2017.
All research outputs
#2,827,324
of 22,901,818 outputs
Outputs from Frontiers in Microbiology
#2,508
of 24,952 outputs
Outputs of similar age
#58,025
of 417,510 outputs
Outputs of similar age from Frontiers in Microbiology
#71
of 429 outputs
Altmetric has tracked 22,901,818 research outputs across all sources so far. Compared to these this one has done well and is in the 87th percentile: it's in the top 25% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 24,952 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.3. This one has done well, scoring higher than 89% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 417,510 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 86% of its contemporaries.
We're also able to compare this research output to 429 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 83% of its contemporaries.