Literature DB >> 28618201

Targeted quantification of functional enzyme dynamics in environmental samples for microbially mediated biogeochemical processes.

Minjing Li1, Yuqian Gao2, Wei-Jun Qian2, Liang Shi2, Yuanyuan Liu2, William C Nelson2, Carrie D Nicora2, Charles T Resch2, Christopher Thompson2, Sen Yan1, James K Fredrickson2, John M Zachara2, Chongxuan Liu2,3.   

Abstract

Microbial enzymes catalytically drive biogeochemical processes in environments. The dynamic linkage between functional enzymes and biogeochemical species transformation has, however, rarely been investigated for decades because of the challenges to directly quantify enzymes in environmental samples. The diversity of microorganisms, the low amount of available biomass and the complexity of chemical composition in environmental samples represent the main challenges. To address the diversity challenge, we first identify several signature peptides that are conserved in the targeted enzymes with the same functionality across many phylogenetically diverse microorganisms using metagenome-based protein sequence data. Quantification of the signature peptides then allows estimation of the targeted enzyme abundance. To achieve analyses of the requisite sensitivity for complex environmental samples with low available biomass, we adapted a recently developed ultrasensitive targeted quantification technology, termed high-pressure high-resolution separations with intelligent selection and multiplexing (PRISM) by improving peptide separation efficiency and method detection sensitivity. Nitrate reduction dynamics catalyzed by dissimilatory and assimilatory enzymes in a hyporheic zone sediment was used as an example to demonstrate the application of the enzyme quantification approach. Together with the measurements of biogeochemical species, the approach enables investigating the dynamic linkage between functional enzymes and biogeochemical processes.
© 2017 Society for Applied Microbiology and John Wiley & Sons Ltd.

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Year:  2017        PMID: 28618201     DOI: 10.1111/1758-2229.12558

Source DB:  PubMed          Journal:  Environ Microbiol Rep        ISSN: 1758-2229            Impact factor:   3.541


  3 in total

1.  Regulation-Structured Dynamic Metabolic Model Provides a Potential Mechanism for Delayed Enzyme Response in Denitrification Process.

Authors:  Hyun-Seob Song; Dennis G Thomas; James C Stegen; Minjing Li; Chongxuan Liu; Xuehang Song; Xingyuan Chen; Jim K Fredrickson; John M Zachara; Timothy D Scheibe
Journal:  Front Microbiol       Date:  2017-09-29       Impact factor: 5.640

2.  Does It Pay Off to Explicitly Link Functional Gene Expression to Denitrification Rates in Reaction Models?

Authors:  Anna Störiko; Holger Pagel; Adrian Mellage; Olaf A Cirpka
Journal:  Front Microbiol       Date:  2021-06-18       Impact factor: 5.640

3.  Enzyme promiscuity in natural environments: alkaline phosphatase in the ocean.

Authors:  Abhishek Srivastava; Daniel E M Saavedra; Blair Thomson; Juan A L García; Zihao Zhao; Wayne M Patrick; Gerhard J Herndl; Federico Baltar
Journal:  ISME J       Date:  2021-05-28       Impact factor: 10.302

  3 in total

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