Cargando…

From diversity to complexity: Microbial networks in soils

Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial eco...

Descripción completa

Detalles Bibliográficos
Autores principales: Guseva, Ksenia, Darcy, Sean, Simon, Eva, Alteio, Lauren V., Montesinos-Navarro, Alicia, Kaiser, Christina
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125165/
https://www.ncbi.nlm.nih.gov/pubmed/35712047
http://dx.doi.org/10.1016/j.soilbio.2022.108604
_version_ 1784711887252881408
author Guseva, Ksenia
Darcy, Sean
Simon, Eva
Alteio, Lauren V.
Montesinos-Navarro, Alicia
Kaiser, Christina
author_facet Guseva, Ksenia
Darcy, Sean
Simon, Eva
Alteio, Lauren V.
Montesinos-Navarro, Alicia
Kaiser, Christina
author_sort Guseva, Ksenia
collection PubMed
description Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research. Analysing microbial networks in soils opens a window to a better understanding of the complexity of microbial communities. However, this approach is unfortunately often used to draw conclusions which are far beyond the scientific evidence it can provide, which has damaged its reputation for soil microbial analysis. In this Perspectives Paper, we would like to sharpen the view for the real potential of microbial co-occurrence analysis in soils, and at the same time raise awareness regarding its limitations and the many ways how it can be misused or misinterpreted.
format Online
Article
Text
id pubmed-9125165
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher Elsevier
record_format MEDLINE/PubMed
spelling pubmed-91251652022-06-14 From diversity to complexity: Microbial networks in soils Guseva, Ksenia Darcy, Sean Simon, Eva Alteio, Lauren V. Montesinos-Navarro, Alicia Kaiser, Christina Soil Biol Biochem Perspectives Paper Network analysis has been used for many years in ecological research to analyze organismal associations, for example in food webs, plant-plant or plant-animal interactions. Although network analysis is widely applied in microbial ecology, only recently has it entered the realms of soil microbial ecology, shown by a rapid rise in studies applying co-occurrence analysis to soil microbial communities. While this application offers great potential for deeper insights into the ecological structure of soil microbial ecosystems, it also brings new challenges related to the specific characteristics of soil datasets and the type of ecological questions that can be addressed. In this Perspectives Paper we assess the challenges of applying network analysis to soil microbial ecology due to the small-scale heterogeneity of the soil environment and the nature of soil microbial datasets. We review the different approaches of network construction that are commonly applied to soil microbial datasets and discuss their features and limitations. Using a test dataset of microbial communities from two depths of a forest soil, we demonstrate how different experimental designs and network constructing algorithms affect the structure of the resulting networks, and how this in turn may influence ecological conclusions. We will also reveal how assumptions of the construction method, methods of preparing the dataset, and definitions of thresholds affect the network structure. Finally, we discuss the particular questions in soil microbial ecology that can be approached by analyzing and interpreting specific network properties. Targeting these network properties in a meaningful way will allow applying this technique not in merely descriptive, but in hypothesis-driven research. Analysing microbial networks in soils opens a window to a better understanding of the complexity of microbial communities. However, this approach is unfortunately often used to draw conclusions which are far beyond the scientific evidence it can provide, which has damaged its reputation for soil microbial analysis. In this Perspectives Paper, we would like to sharpen the view for the real potential of microbial co-occurrence analysis in soils, and at the same time raise awareness regarding its limitations and the many ways how it can be misused or misinterpreted. Elsevier 2022-06 /pmc/articles/PMC9125165/ /pubmed/35712047 http://dx.doi.org/10.1016/j.soilbio.2022.108604 Text en © 2022 The Author(s) https://creativecommons.org/licenses/by/4.0/This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Perspectives Paper
Guseva, Ksenia
Darcy, Sean
Simon, Eva
Alteio, Lauren V.
Montesinos-Navarro, Alicia
Kaiser, Christina
From diversity to complexity: Microbial networks in soils
title From diversity to complexity: Microbial networks in soils
title_full From diversity to complexity: Microbial networks in soils
title_fullStr From diversity to complexity: Microbial networks in soils
title_full_unstemmed From diversity to complexity: Microbial networks in soils
title_short From diversity to complexity: Microbial networks in soils
title_sort from diversity to complexity: microbial networks in soils
topic Perspectives Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9125165/
https://www.ncbi.nlm.nih.gov/pubmed/35712047
http://dx.doi.org/10.1016/j.soilbio.2022.108604
work_keys_str_mv AT gusevaksenia fromdiversitytocomplexitymicrobialnetworksinsoils
AT darcysean fromdiversitytocomplexitymicrobialnetworksinsoils
AT simoneva fromdiversitytocomplexitymicrobialnetworksinsoils
AT alteiolaurenv fromdiversitytocomplexitymicrobialnetworksinsoils
AT montesinosnavarroalicia fromdiversitytocomplexitymicrobialnetworksinsoils
AT kaiserchristina fromdiversitytocomplexitymicrobialnetworksinsoils