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Time after time: detecting annual patterns in stream bacterial biofilm communities

To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rR...

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Detalles Bibliográficos
Autores principales: Gautam, Anju, Lear, Gavin, Lewis, Gillian D.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley & Sons, Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324112/
https://www.ncbi.nlm.nih.gov/pubmed/35466520
http://dx.doi.org/10.1111/1462-2920.16017
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author Gautam, Anju
Lear, Gavin
Lewis, Gillian D.
author_facet Gautam, Anju
Lear, Gavin
Lewis, Gillian D.
author_sort Gautam, Anju
collection PubMed
description To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change.
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spelling pubmed-93241122022-07-30 Time after time: detecting annual patterns in stream bacterial biofilm communities Gautam, Anju Lear, Gavin Lewis, Gillian D. Environ Microbiol Research Articles To quantify the major environmental drivers of stream bacterial population dynamics, we modelled temporal differences in stream bacterial communities to quantify community shifts, including those relating to cyclical seasonal variation and more sporadic bloom events. We applied Illumina MiSeq 16S rRNA bacterial gene sequencing of 892 stream biofilm samples, collected monthly for 36‐months from six streams. The streams were located a maximum of 118 km apart and drained three different catchment types (forest, urban and rural land uses). We identified repeatable seasonal patterns among bacterial taxa, allowing their separation into three ecological groupings, those following linear, bloom/trough and repeated, seasonal trends. Various physicochemical parameters (light, water and air temperature, pH, dissolved oxygen, nutrients) were linked to temporal community changes. Our models indicate that bloom events and seasonal episodes modify biofilm bacterial populations, suggesting that distinct microbial taxa thrive during these events including non‐cyanobacterial community members. These models could aid in determining how temporal environmental changes affect community assembly and guide the selection of appropriate statistical models to capture future community responses to environmental change. John Wiley & Sons, Inc. 2022-05-04 2022-05 /pmc/articles/PMC9324112/ /pubmed/35466520 http://dx.doi.org/10.1111/1462-2920.16017 Text en © 2022 The Authors. Environmental Microbiology published by Society for Applied Microbiology and John Wiley & Sons Ltd. https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc-nd/4.0/ (https://creativecommons.org/licenses/by-nc-nd/4.0/) License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non‐commercial and no modifications or adaptations are made.
spellingShingle Research Articles
Gautam, Anju
Lear, Gavin
Lewis, Gillian D.
Time after time: detecting annual patterns in stream bacterial biofilm communities
title Time after time: detecting annual patterns in stream bacterial biofilm communities
title_full Time after time: detecting annual patterns in stream bacterial biofilm communities
title_fullStr Time after time: detecting annual patterns in stream bacterial biofilm communities
title_full_unstemmed Time after time: detecting annual patterns in stream bacterial biofilm communities
title_short Time after time: detecting annual patterns in stream bacterial biofilm communities
title_sort time after time: detecting annual patterns in stream bacterial biofilm communities
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9324112/
https://www.ncbi.nlm.nih.gov/pubmed/35466520
http://dx.doi.org/10.1111/1462-2920.16017
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