Modeling-Guided Amendments Lead to Enhanced Biodegradation in Soil

Dhakar, Kusum; Zarecki, Raphy; Medina, Shlomit; Ziadna, Hamam; Igbaria, Karam; Lati, Ran Nisim; Ronen, Zeev; Eizenberg, Hanan; Freilich, Shiri

doi:10.1128/msystems.00169-22

Cited by 3 publications

(3 citation statements)

References 78 publications

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“…Simulations can guide validation experiments' design by ranking potential solutions that outperform ‘trial and error’ based solutions. In a recent study, we have demonstrated that model‐guided manipulation strategies for enhancing the biodegradation of agrochemicals in the soil can outperform trial and error‐based biodegradation solutions (Dhakar et al, 2022). Similarly, data‐guided manipulation strategies can pave the way for the future development of practical protocols for maintaining long shelf life while reducing the dependency on pesticides and agrochemicals.…”

Section: Discussionmentioning

confidence: 99%

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

Bartuv

Vetcos

Medina

et al. 2023

Environmental Microbiology

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Fruits harbour abundant and diverse microbial communities that protect them from post‐harvest pathogens. Identification of functional traits associated with a given microbiota can provide a better understanding of their potential influence. Here, we focused on the epiphytic microbiome of apple fruit. We suggest that shotgun metagenomic data can indicate specific functions carried out by different groups and provide information on their potential impact. Samples were collected from the surface of ‘Golden Delicious’ apples from four orchards that differ in their geographic location and management practice. Approximately 1 million metagenes were predicted based on a high‐quality assembly. Functional profiling of the microbiome of fruits from orchards differing in their management practice revealed a functional shift in the microbiota. The organic orchard microbiome was enriched in pathways involved in plant defence activities; the conventional orchard microbiome was enriched in pathways related to the synthesis of antibiotics. The functional significance of the variations was explored using microbial network modelling algorithms to reveal the metabolic role of specific phylogenetic groups. The analysis identified several associations supported by other published studies. For example, the analysis revealed the nutritional dependencies of the Capnodiales group, including the Alternaria pathogen, on aromatic compounds.

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Section: Discussionmentioning

confidence: 99%

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

Bartuv

Vetcos

Medina

et al. 2023

Environmental Microbiology

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“…The framework presented is designed to be used as a platform to generate educated hypotheses regarding bacterial function in a specific environment in conjunction with actual carbon substrates available in the particular ecosystem under study. The hypotheses generated provide a starting point for experimental testing required to gain actual, targeted and feasible applicable insights 38,42 . While recognizing its limitations, this framework is in fact highly versatile and can be used for the characterization of a variety of microbial communities and environments.…”

Section: Discussionmentioning

confidence: 99%

“…An accurate representation of microbial metabolic networks depends on the origin of the genomes analyzed. To date, most studies attempting to model the microbiome of specific ecosystems by GSMM represent native species using corresponding genome sequences from public depositories, a process which is usually referred to as 16S-based genome imputation 26,35,37 . Genome recovery, or genome-resolved metagenomes, often referred to as Metagenomes Assembled Genomes (MAGs) allows one to obtain full genomes directly from metagenomes 38,39 .…”

Section: Introductionmentioning

confidence: 99%

A metabolic modeling-based framework for predicting trophic dependencies in native rhizobiomes of crop plants

Ginatt,

Berihu,

Castel

et al. 2023

Preprint

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The exchange of metabolites (i.e., metabolic interactions) between bacteria in the rhizosphere determines various plant-associated functions. Systematically understanding the metabolic interactions in the rhizosphere, as well as in other types of microbial communities, would open the door to the optimization of specific pre-defined functions of interest, and therefore to the harnessing of the functionality of various types of microbiomes. However, mechanistic knowledge regarding the gathering and interpretation of these interactions is limited. Here, we present a framework utilizing genomics and constraint based modeling approaches, aiming to interpret the hierarchical trophic interactions in the soil environment. 243 genome-scale metabolic models of bacteria associated with a specific disease suppressive vs disease conductive apple rhizospheres were drafted based on genome resolved metagenomes, comprising anin-siliconative microbial community. Iteratively simulating microbial community members' growth in a metabolomics-based apple root-like environment produced novel data on potential trophic successions, used to form a network of communal trophic dependencies. Network-based analyses have characterized interactions associated with beneficial vs non-beneficial microbiome functioning, pinpointing specific compounds and microbial species as potential disease supporting and suppressing agents. This framework provides a means for capturing trophic interactions and formulating a range of testable hypotheses regarding the metabolic capabilities of microbial communities within their natural environment. Essentially, it can be applied to different environments and biological landscapes, elucidating the conditions for the targeted manipulation of various microbiomes, and the execution of countless predefined functions.

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Comparative study of bacterial community dynamics in different soils following application of the herbicide atrazine

Dhakar

Medina

Ziadna

et al. 2023

Environmental Research

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Modeling-Guided Amendments Lead to Enhanced Biodegradation in Soil

Abstract: Providing the food requirements of a growing population comes at the cost of intensive use of agrochemicals, including pesticides. Native microbial soil communities are considered key players in the degradation of such exogenous substances.

Cited by 3 publications

References 78 publications

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

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

A metabolic modeling-based framework for predicting trophic dependencies in native rhizobiomes of crop plants

Comparative study of bacterial community dynamics in different soils following application of the herbicide atrazine

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