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CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity

We present CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation), an extension of CFDEM(®)Coupling to model biological flows, growth, and mass transfer in artificial microgravity devices. For microbes that accompany humans into space, microgravity-induced alterations...

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Detalles Bibliográficos
Autores principales: An, Rocky, Lee, Jessica Audrey
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144607/
https://www.ncbi.nlm.nih.gov/pubmed/35629329
http://dx.doi.org/10.3390/life12050660
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author An, Rocky
Lee, Jessica Audrey
author_facet An, Rocky
Lee, Jessica Audrey
author_sort An, Rocky
collection PubMed
description We present CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation), an extension of CFDEM(®)Coupling to model biological flows, growth, and mass transfer in artificial microgravity devices. For microbes that accompany humans into space, microgravity-induced alterations in the fluid environment are likely to be a major factor in the microbial experience of spaceflight. Computational modeling is needed to investigate how well ground-based microgravity simulation methods replicate that experience. CAMDLES incorporates agent-based modeling to study inter-species metabolite transport within microbial communities in rotating wall vessel bioreactors (RWVs). Preexisting CFD modeling of RWVs has not yet incorporated growth; CAMDLES employs the simultaneous modeling of biological, chemical, and mechanical processes in a micro-scale rotating reference frame environment. Simulation mass transfer calculations were correlated with Monod dynamic parameters to predict relative growth rates between artificial microgravity, spaceflight microgravity, and 1 g conditions. By simulating a microbial model community of metabolically cooperative strains of Escherichia coli and Salmonella enterica, we found that the greatest difference between microgravity and an RWV or 1 g gravity was when species colocalized in dense aggregates. We also investigated the influence of other features of the system on growth, such as spatial distribution, product yields, and diffusivity. Our simulation provides a basis for future laboratory experiments using this community for investigation in artificial microgravity and spaceflight microgravity. More broadly, our development of these models creates a framework for novel hypothesis generation and design of biological experiments with RWVs, coupling the effects of RWV size, rotation rate, and mass transport directly to bacterial growth in microbial communities.
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spelling pubmed-91446072022-05-29 CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity An, Rocky Lee, Jessica Audrey Life (Basel) Article We present CAMDLES (CFD-DEM Artificial Microgravity Developments for Living Ecosystem Simulation), an extension of CFDEM(®)Coupling to model biological flows, growth, and mass transfer in artificial microgravity devices. For microbes that accompany humans into space, microgravity-induced alterations in the fluid environment are likely to be a major factor in the microbial experience of spaceflight. Computational modeling is needed to investigate how well ground-based microgravity simulation methods replicate that experience. CAMDLES incorporates agent-based modeling to study inter-species metabolite transport within microbial communities in rotating wall vessel bioreactors (RWVs). Preexisting CFD modeling of RWVs has not yet incorporated growth; CAMDLES employs the simultaneous modeling of biological, chemical, and mechanical processes in a micro-scale rotating reference frame environment. Simulation mass transfer calculations were correlated with Monod dynamic parameters to predict relative growth rates between artificial microgravity, spaceflight microgravity, and 1 g conditions. By simulating a microbial model community of metabolically cooperative strains of Escherichia coli and Salmonella enterica, we found that the greatest difference between microgravity and an RWV or 1 g gravity was when species colocalized in dense aggregates. We also investigated the influence of other features of the system on growth, such as spatial distribution, product yields, and diffusivity. Our simulation provides a basis for future laboratory experiments using this community for investigation in artificial microgravity and spaceflight microgravity. More broadly, our development of these models creates a framework for novel hypothesis generation and design of biological experiments with RWVs, coupling the effects of RWV size, rotation rate, and mass transport directly to bacterial growth in microbial communities. MDPI 2022-04-29 /pmc/articles/PMC9144607/ /pubmed/35629329 http://dx.doi.org/10.3390/life12050660 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
An, Rocky
Lee, Jessica Audrey
CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title_full CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title_fullStr CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title_full_unstemmed CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title_short CAMDLES: CFD-DEM Simulation of Microbial Communities in Spaceflight and Artificial Microgravity
title_sort camdles: cfd-dem simulation of microbial communities in spaceflight and artificial microgravity
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9144607/
https://www.ncbi.nlm.nih.gov/pubmed/35629329
http://dx.doi.org/10.3390/life12050660
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