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Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism

Microbial communities are of considerable significance for biogeochemical processes, for the health of both animals and plants, and for biotechnological purposes. A key feature of microbial interactions is the exchange of nutrients between cells. Isotope labelling followed by analysis with secondary...

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Autores principales: Laeverenz Schlogelhofer, Hannah, Peaudecerf, François J., Bunbury, Freddy, Whitehouse, Martin J., Foster, Rachel A., Smith, Alison G., Croze, Ottavio A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136852/
https://www.ncbi.nlm.nih.gov/pubmed/34014955
http://dx.doi.org/10.1371/journal.pone.0251643
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author Laeverenz Schlogelhofer, Hannah
Peaudecerf, François J.
Bunbury, Freddy
Whitehouse, Martin J.
Foster, Rachel A.
Smith, Alison G.
Croze, Ottavio A.
author_facet Laeverenz Schlogelhofer, Hannah
Peaudecerf, François J.
Bunbury, Freddy
Whitehouse, Martin J.
Foster, Rachel A.
Smith, Alison G.
Croze, Ottavio A.
author_sort Laeverenz Schlogelhofer, Hannah
collection PubMed
description Microbial communities are of considerable significance for biogeochemical processes, for the health of both animals and plants, and for biotechnological purposes. A key feature of microbial interactions is the exchange of nutrients between cells. Isotope labelling followed by analysis with secondary ion mass spectrometry (SIMS) can identify nutrient fluxes and heterogeneity of substrate utilisation on a single cell level. Here we present a novel approach that combines SIMS experiments with mechanistic modelling to reveal otherwise inaccessible nutrient kinetics. The method is applied to study the onset of a synthetic mutualistic partnership between a vitamin B(12)-dependent mutant of the alga Chlamydomonas reinhardtii and the B(12)-producing, heterotrophic bacterium Mesorhizobium japonicum, which is supported by algal photosynthesis. Results suggest that an initial pool of fixed carbon delays the onset of mutualistic cross-feeding; significantly, our approach allows the first quantification of this expected delay. Our method is widely applicable to other microbial systems, and will contribute to furthering a mechanistic understanding of microbial interactions.
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spelling pubmed-81368522021-06-02 Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism Laeverenz Schlogelhofer, Hannah Peaudecerf, François J. Bunbury, Freddy Whitehouse, Martin J. Foster, Rachel A. Smith, Alison G. Croze, Ottavio A. PLoS One Research Article Microbial communities are of considerable significance for biogeochemical processes, for the health of both animals and plants, and for biotechnological purposes. A key feature of microbial interactions is the exchange of nutrients between cells. Isotope labelling followed by analysis with secondary ion mass spectrometry (SIMS) can identify nutrient fluxes and heterogeneity of substrate utilisation on a single cell level. Here we present a novel approach that combines SIMS experiments with mechanistic modelling to reveal otherwise inaccessible nutrient kinetics. The method is applied to study the onset of a synthetic mutualistic partnership between a vitamin B(12)-dependent mutant of the alga Chlamydomonas reinhardtii and the B(12)-producing, heterotrophic bacterium Mesorhizobium japonicum, which is supported by algal photosynthesis. Results suggest that an initial pool of fixed carbon delays the onset of mutualistic cross-feeding; significantly, our approach allows the first quantification of this expected delay. Our method is widely applicable to other microbial systems, and will contribute to furthering a mechanistic understanding of microbial interactions. Public Library of Science 2021-05-20 /pmc/articles/PMC8136852/ /pubmed/34014955 http://dx.doi.org/10.1371/journal.pone.0251643 Text en © 2021 Laeverenz Schlogelhofer et al https://creativecommons.org/licenses/by/4.0/This is an open access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Laeverenz Schlogelhofer, Hannah
Peaudecerf, François J.
Bunbury, Freddy
Whitehouse, Martin J.
Foster, Rachel A.
Smith, Alison G.
Croze, Ottavio A.
Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title_full Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title_fullStr Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title_full_unstemmed Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title_short Combining SIMS and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
title_sort combining sims and mechanistic modelling to reveal nutrient kinetics in an algal-bacterial mutualism
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8136852/
https://www.ncbi.nlm.nih.gov/pubmed/34014955
http://dx.doi.org/10.1371/journal.pone.0251643
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