Picot, A., Shibasaki, S., Meacock, O.J. orcid.org/0000-0001-6269-9855 et al. (1 more author) (2023) Microbial interactions in theory and practice: when are measurements compatible with models? Current Opinion in Microbiology, 75. 102354. ISSN 1369-5274
Abstract
Most predictive models of ecosystem dynamics are based on interactions between organisms: their influence on each other's growth and death. We review here how theoretical approaches are used to extract interaction measurements from experimental data in microbiology, particularly focusing on the generalised Lotka–Volterra (gLV) framework. Though widely used, we argue that the gLV model should be avoided for estimating interactions in batch culture — the most common, simplest and cheapest in vitro approach to culturing microbes. Fortunately, alternative approaches offer a way out of this conundrum. Firstly, on the experimental side, alternatives such as the serial-transfer and chemostat systems more closely match the theoretical assumptions of the gLV model. Secondly, on the theoretical side, explicit organism-environment interaction models can be used to study the dynamics of batch-culture systems. We hope that our recommendations will increase the tractability of microbial model systems for experimentalists and theoreticians alike.
Metadata
Item Type: | Article |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
Keywords: | Ecosystem; Models, Theoretical; Models, Biological; Microbial Interactions |
Dates: |
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Institution: | The University of Sheffield |
Academic Units: | The University of Sheffield > Faculty of Science (Sheffield) > School of Biosciences (Sheffield) |
Depositing User: | Symplectic Sheffield |
Date Deposited: | 11 Dec 2024 15:31 |
Last Modified: | 11 Dec 2024 15:31 |
Status: | Published |
Publisher: | Elsevier BV |
Refereed: | Yes |
Identification Number: | 10.1016/j.mib.2023.102354 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:220168 |