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AM fungal-bacterial relationships: what can they tell us about ecosystem sustainability and soil functioning?

Journal

FRONTIERS IN FUNGAL BIOLOGY
Volume 4, Issue -, Pages -

Publisher

FRONTIERS MEDIA SA
DOI: 10.3389/ffunb.2023.1141963

Keywords

arbuscular mycorrhizal fungi; AM fungal-bacterial relationships; interactions; symbioses; microbial functional traits; biogeochemical cycling; synthetic communities

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Given the increasing population and degradation of soil environments, understanding the fundamental ecology of soil biota and plant microbiomes is crucial for the sustainability of soil systems. This study focuses on the drivers and complexity of arbuscular mycorrhizal (AM) fungal-bacterial relationships, emphasizes the need for interdisciplinary tools in AM fungal research, and suggests the utilization of bacterial datasets to gain insights into these relationships. The findings highlight the importance of interdependent microbial relationships and propose the use of pattern-based inference tools and synthetic communities to improve microbial inocula and products.
Considering our growing population and our continuous degradation of soil environments, understanding the fundamental ecology of soil biota and plant microbiomes will be imperative to sustaining soil systems. Arbuscular mycorrhizal (AM) fungi extend their hyphae beyond plant root zones, creating microhabitats with bacterial symbionts for nutrient acquisition through a tripartite symbiotic relationship along with plants. Nonetheless, it is unclear what drives these AM fungal-bacterial relationships and how AM fungal functional traits contribute to these relationships. By delving into the literature, we look at the drivers and complexity behind AM fungal-bacterial relationships, describe the shift needed in AM fungal research towards the inclusion of interdisciplinary tools, and discuss the utilization of bacterial datasets to provide contextual evidence behind these complex relationships, bringing insights and new hypotheses to AM fungal functional traits. From this synthesis, we gather that interdependent microbial relationships are at the foundation of understanding microbiome functionality and deciphering microbial functional traits. We suggest using pattern-based inference tools along with machine learning to elucidate AM fungal-bacterial relationship trends, along with the utilization of synthetic communities, functional gene analyses, and metabolomics to understand how AM fungal and bacterial communities facilitate communication for the survival of host plant communities. These suggestions could result in improving microbial inocula and products, as well as a better understanding of complex relationships in terrestrial ecosystems that contribute to plant-soil feedbacks.

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