A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data

Abstract

Background The design of ecologically sustainable and plant-beneficial soil systems is a key goal in actively manipulating root-associated microbiomes. Community engineering efforts commonly seek to harness the potential of the indigenous microbiome through substrate-mediated recruitment of beneficial members. In most sustainable practices, microbial recruitment mechanisms rely on the application of complex organic mixtures where the resources/metabolites that act as direct stimulants of beneficial groups are not characterized. Outcomes of such indirect amendments are unpredictable regarding engineering the microbiome and achieving a plant-beneficial environment. Results This study applied network analysis of metagenomics data to explore amendment-derived transformations in the soil microbiome, which lead to the suppression of pathogens affecting apple root systems. Shotgun metagenomic analysis was conducted with data from ‘sick’ vs ‘healthy/recovered’ rhizosphere soil microbiomes. The data was then converted into community-level metabolic networks. Simulations examined the functional contribution of treatment-associated taxonomic groups and linked them with specific amendment-induced metabolites. This analysis enabled the selection of specific metabolites that were predicted to amplify or diminish the abundance of targeted microbes functional in the healthy soil system. Many of these predictions were corroborated by experimental evidence from the literature. The potential of two of these metabolites (dopamine and vitamin B12) to either stimulate or suppress targeted microbial groups was evaluated in a follow-up set of soil microcosm experiments. The results corroborated the stimulant’s potential (but not the suppressor) to act as a modulator of plant beneficial bacteria, paving the way for future development of knowledge-based (rather than trial and error) metabolic-defined amendments. Our pipeline for generating predictions for the selective targeting of microbial groups based on processing assembled and annotated metagenomics data is available at https://github.com/ot483/NetCom2. Conclusions This research demonstrates how genomic-based algorithms can be used to formulate testable hypotheses for strategically engineering the rhizosphere microbiome by identifying specific compounds, which may act as selective modulators of microbial communities. Applying this framework to reduce unpredictable elements in amendment-based solutions promotes the development of ecologically-sound methods for re-establishing a functional microbiome in agro and other ecosystems.

Rhizosphere Mysteries: Metabolite Reduction Down-regulated Fungal Diversity and Community Function

“…They also contain signaling molecules required to establish "plant-microorganisms" interactions. Furthermore, the repulsive behaviour is that plants produce antimicrobial, insecticide, and nematicide compounds to repel pathogens and invaders, as a first line of plant protection, provide biological and physical barriers that can be beneficial to plant health (8). Overall, plants produce root secretions that selectively shape unique soil microbial communities, providing protection and favorable feedback to the plant.…”

Functional analysis of the apple fruit microbiome based on shotgun metagenomic sequencing of conventional and organic orchard samples

“…We used the expansion algorithm to predict metabolic activities in each environment through its implantation in NetCom (Tal et al, 2021;Berihu et al, 2023).…”

“…Although data analysis derived from shotgun metagenome sequencing is more complex than amplicon data analysis, it promotes an understanding of potential function. This approach has been applied in the rhizosphere and phyllosphere microbial communities studies of many staple crops, including cucumber, wheat (Ofek-Lalzar et al, 2014), soybean (Mendes et al, 2014), rice (Knief et al, 2012), apple (Berihu et al, 2023) and barley (Bulgarelli et al, 2015). Angeli et al (2019) utilized shotgun metagenomic sequencing to taxonomically and functionally characterize the bacterial and fungal communities on surfaces of organic 'Pinova' apple fruits.…”

Strategies for tailoring functional microbial synthetic communities

“…Central to the challenge of designing SynComs is the selection of candidates that are representative of the taxonomic and/or functional characteristics of a microbiome under study. One way to do that is by using taxonomic profiles such as high abundance/representativeness across samples [ 24 , 25 ], co-occurrence with other community members [ 26 ], or differential abundance between samples with contrasting phenotypes [ 27 ]. There has been a growing focus in the last decade to explore the microbial biosynthetic potential through (meta)genome mining as a complementary approach to SynCom design in addition to traditional laboratory screening [ 28 , 29 ].…”