Numerical investigation of microbial quorum sensing under various flow conditions
Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess t...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
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PeerJ Inc.
2020-09-01
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| Series: | PeerJ |
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| Online Access: | https://peerj.com/articles/9942.pdf |
| _version_ | 1797425560960368640 |
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| author | Heewon Jung Christof D. Meile |
| author_facet | Heewon Jung Christof D. Meile |
| author_sort | Heewon Jung |
| collection | DOAJ |
| description | Microorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations. |
| first_indexed | 2024-03-09T08:17:53Z |
| format | Article |
| id | doaj.art-a5141615b90a4325903e79b6157e8e79 |
| institution | Directory Open Access Journal |
| issn | 2167-8359 |
| language | English |
| last_indexed | 2024-03-09T08:17:53Z |
| publishDate | 2020-09-01 |
| publisher | PeerJ Inc. |
| record_format | Article |
| series | PeerJ |
| spelling | doaj.art-a5141615b90a4325903e79b6157e8e792023-12-02T21:59:40ZengPeerJ Inc.PeerJ2167-83592020-09-018e994210.7717/peerj.9942Numerical investigation of microbial quorum sensing under various flow conditionsHeewon JungChristof D. MeileMicroorganisms efficiently coordinate phenotype expressions through a decision-making process known as quorum sensing (QS). We investigated QS amongst distinct, spatially distributed microbial aggregates under various flow conditions using a process-driven numerical model. Model simulations assess the conditions suitable for QS induction and quantify the importance of advective transport of signaling molecules. In addition, advection dilutes signaling molecules so that faster flow conditions require higher microbial densities, faster signal production rates, or higher sensitivities to signaling molecules to induce QS. However, autoinduction of signal production can substantially increase the transport distance of signaling molecules in both upstream and downstream directions. We present empirical approximations to the solutions of the advection–diffusion–reaction equation that describe the concentration profiles of signaling molecules for a wide range of flow and reaction rates. These empirical relationships, which predict the distribution of dissolved solutes along pore channels, allow to quantitatively estimate the effective communication distances amongst multiple microbial aggregates without further numerical simulations.https://peerj.com/articles/9942.pdfQuorum sensingCalling distanceAdvectionAutoinduction |
| spellingShingle | Heewon Jung Christof D. Meile Numerical investigation of microbial quorum sensing under various flow conditions PeerJ Quorum sensing Calling distance Advection Autoinduction |
| title | Numerical investigation of microbial quorum sensing under various flow conditions |
| title_full | Numerical investigation of microbial quorum sensing under various flow conditions |
| title_fullStr | Numerical investigation of microbial quorum sensing under various flow conditions |
| title_full_unstemmed | Numerical investigation of microbial quorum sensing under various flow conditions |
| title_short | Numerical investigation of microbial quorum sensing under various flow conditions |
| title_sort | numerical investigation of microbial quorum sensing under various flow conditions |
| topic | Quorum sensing Calling distance Advection Autoinduction |
| url | https://peerj.com/articles/9942.pdf |
| work_keys_str_mv | AT heewonjung numericalinvestigationofmicrobialquorumsensingundervariousflowconditions AT christofdmeile numericalinvestigationofmicrobialquorumsensingundervariousflowconditions |