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Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions

Microbes serve as sensitive indicators of ecosystem change due to their vast diversity and tendency to change in abundance in response to environmental conditions. Although we most frequently observe these changes to study the microbial community itself, it is increasingly common to use them to unde...

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Detalles Bibliográficos
Autor principal: Bowman, Jeff S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Society for Microbiology 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668242/
https://www.ncbi.nlm.nih.gov/pubmed/34463569
http://dx.doi.org/10.1128/mSystems.00993-21
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author Bowman, Jeff S.
author_facet Bowman, Jeff S.
author_sort Bowman, Jeff S.
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description Microbes serve as sensitive indicators of ecosystem change due to their vast diversity and tendency to change in abundance in response to environmental conditions. Although we most frequently observe these changes to study the microbial community itself, it is increasingly common to use them to understand the surrounding environment. In this way microbial communities can be thought of as powerful sensors capable of reporting shifts in chemical or physical conditions with high fidelity. In this commentary, I further explore this idea by drawing a comparison to the olfactory system, where populations of sensory neurons respond to the presence of specific odorants. The possible combinations of sensory neurons that can transduce a signal are virtually limitless. Yet, the brain can deconvolute the signal into recognizable and actionable data. The further development of machine learning techniques and its application hold great promise for our ability to interpret microbes to detect environmental change.
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spelling pubmed-86682422021-12-27 Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions Bowman, Jeff S. mSystems Commentary Microbes serve as sensitive indicators of ecosystem change due to their vast diversity and tendency to change in abundance in response to environmental conditions. Although we most frequently observe these changes to study the microbial community itself, it is increasingly common to use them to understand the surrounding environment. In this way microbial communities can be thought of as powerful sensors capable of reporting shifts in chemical or physical conditions with high fidelity. In this commentary, I further explore this idea by drawing a comparison to the olfactory system, where populations of sensory neurons respond to the presence of specific odorants. The possible combinations of sensory neurons that can transduce a signal are virtually limitless. Yet, the brain can deconvolute the signal into recognizable and actionable data. The further development of machine learning techniques and its application hold great promise for our ability to interpret microbes to detect environmental change. American Society for Microbiology 2021-08-31 /pmc/articles/PMC8668242/ /pubmed/34463569 http://dx.doi.org/10.1128/mSystems.00993-21 Text en Copyright © 2021 Bowman. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Commentary
Bowman, Jeff S.
Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title_full Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title_fullStr Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title_full_unstemmed Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title_short Making Sense of a Scent-Sensing Metaphor for Microbes and Environmental Predictions
title_sort making sense of a scent-sensing metaphor for microbes and environmental predictions
topic Commentary
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8668242/
https://www.ncbi.nlm.nih.gov/pubmed/34463569
http://dx.doi.org/10.1128/mSystems.00993-21
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