From diversity to complexity: Microbial networks in soils. (June 2022)

• Record Type: Journal Article
• Authors: Guseva, Ksenia; Darcy, Sean; Simon, Eva; Alteio, Lauren V.; Montesinos-Navarro, Alicia; Kaiser, Christina
• Is Part Of: Soil biology and biochemistry. Volume 169(2022)
• Publication Date: 2022-06
• Subjects: Microbial network analysis -- Co-occurrence networks -- Ecological networks -- Microbial community structure -- Soil microbial ecology; Soil biochemistry -- Periodicals; Soil biology -- Periodicals; Sols -- Biochimie -- Périodiques; Sols -- Biologie -- Périodiques; Sols -- Microbiologie -- Périodiques; Bodembiologie; Biochemie; 631.46
• DOI: 10.1016/j.soilbio.2022.108604
• Languages: English
• ISSNs: 0038-0717

Abstract

Abstract: 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. Highlights: Networks are used to study the relationships within microbial communities. Construction methods and experimental design influence conclusions. Applying network analysis to soil microbial datasets holds specific challenges. Soil heterogeneity and the nature of soil sequencing data has to be considered. Network analysis can offer novel insights into soil microbial ecosystems.