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A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data
Year:
2023
Source of publication :
microbiome
Authors :
Doron-Faigenboim, Adi
;
.
Freilich, Shiri
;
.
Medina, Shlomit
;
.
Volume :
11
Co-Authors:
  • Maria Berihu, 
  • Tracey S. Somera, 
  • Assaf Malik, 
  • Shlomit Medina, 
  • Edoardo Piombo, 
  • Ofir Tal, 
  • Matan Cohen, 
  • Alon Ginatt, 
  • Maya Ofek-Lalzar, 
  • Adi Doron-Faigenboim, 
  • Mark Mazzola 
    Shiri Freilich 
Facilitators :
From page:
0
To page:
0
(
Total pages:
1
)
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.

Note:
Related Files :
Biostimulants
MAG
metagenomics
microbial community
microbiome
Pathway
rhizosphere
Rootstocks
Show More
Related Content
More details
DOI :
10.1186/s40168-022-01438-1
Article number:
0
Affiliations:
Database:
Scopus
Publication Type:
article
;
.
Language:
English
Editors' remarks:
ID:
63289
Last updated date:
22/01/2023 17:45
Creation date:
22/01/2023 17:45
You may also be interested in
Scientific Publication
A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data
11
  • Maria Berihu, 
  • Tracey S. Somera, 
  • Assaf Malik, 
  • Shlomit Medina, 
  • Edoardo Piombo, 
  • Ofir Tal, 
  • Matan Cohen, 
  • Alon Ginatt, 
  • Maya Ofek-Lalzar, 
  • Adi Doron-Faigenboim, 
  • Mark Mazzola 
    Shiri Freilich 
A framework for the targeted recruitment of crop-beneficial soil taxa based on network analysis of metagenomics data

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.

Scientific Publication
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