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Calculation and Interpretation of Substrate Assimilation Rates in Microbial Cells Based on Isotopic Composition Data Obtained by nanoSIMS
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SYSNO ASEP 0550065 Document Type J - Journal Article R&D Document Type Journal Article Subsidiary J Článek ve WOS Title Calculation and Interpretation of Substrate Assimilation Rates in Microbial Cells Based on Isotopic Composition Data Obtained by nanoSIMS Author(s) Polerecky, L. (NL)
Eichner, Meri (MBU-M) ORCID, RID
Masuda, Takako (MBU-M) ORCID
Zavřel, Tomáš (UEK-B) RID, SAI, ORCID
Rabouille, S. (FR)
Campbell, D. A. (CA)
Halsey, K. (US)Article number 621634 Source Title Frontiers in Microbiology. - : Frontiers Research Foundation - ISSN 1664-302X
Roč. 12, NOV 30 2021 (2021)Number of pages 17 s. Language eng - English Country CH - Switzerland Keywords stable isotope probing ; assimilation rates ; storage inclusions ; cell growth model Subject RIV EE - Microbiology, Virology OECD category Microbiology Subject RIV - cooperation Global Change Research Institute R&D Projects GA20-17627S GA ČR - Czech Science Foundation (CSF) GJ20-02827Y GA ČR - Czech Science Foundation (CSF) EF16_026/0008413 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) GA18-24397S GA ČR - Czech Science Foundation (CSF) EF16_027/0007990 GA MŠMT - Ministry of Education, Youth and Sports (MEYS) Method of publishing Open access Institutional support MBU-M - RVO:61388971 ; UEK-B - RVO:86652079 UT WOS 000729982700001 EID SCOPUS 85121394529 DOI 10.3389/fmicb.2021.621634 Annotation Stable isotope probing (SIP) combined with nano-scale secondary ion mass spectrometry (nanoSIMS) is a powerful approach to quantify assimilation rates of elements such as C and N into individual microbial cells. Here, we use mathematical modeling to investigate how the derived rate estimates depend on the model used to describe substrate assimilation by a cell during a SIP incubation. We show that the most commonly used model, which is based on the simplifying assumptions of linearly increasing biomass of individual cells over time and no cell division, can yield underestimated assimilation rates when compared to rates derived from a model that accounts for cell division. This difference occurs because the isotopic labeling of a dividing cell increases more rapidly over time compared to a non-dividing cell and becomes more pronounced as the labeling increases above a threshold value that depends on the cell cycle stage of the measured cell. Based on the modeling results, we present formulae for estimating assimilation rates in cells and discuss their underlying assumptions, conditions of applicability, and implications for the interpretation of intercellular variability in assimilation rates derived from nanoSIMS data, including the impacts of storage inclusion metabolism. We offer the formulae as a Matlab script to facilitate rapid data evaluation by nanoSIMS users. Workplace Institute of Microbiology Contact Eliška Spurná, eliska.spurna@biomed.cas.cz, Tel.: 241 062 231 Year of Publishing 2022 Electronic address https://hal.archives-ouvertes.fr/hal-03469894/
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