1. Promoting enhanced degradation of herbicides in soil


In a pioneering project, we demonstrated the usefulness of metabolic modeling approaches for the design of microbial consortium with soil-pollutant (the herbicide atrazine) degrading activity. To this end, we used sequence-based genomic information on the dynamics in soil community from atrazine treated fields in order to construct a corresponding imputed in silico community, and used simulations for exploring functional significance of community dynamics and for predicting possible bioremediation strategies. Based on simulations, we established a novel biodegradation consortium composed of endogenous soil bacteria, and predicted the mechanisms – specific metabolic exchanges - behind improvement in degradation performance. Predictions were experimentally validated and the consortium outperformed the known primary atrazine degrader Arthrobacter.

The study demonstrates how a combination of genomic and metabolic modeling approaches can solve a challenging problem that cannot be solved with a single technique alone and that

bioremediation strategies should aim to be designed based on knowledge of:

(1) the microorganisms that are present in the contaminated environments;

(2) their metabolic capabilities; and (3) how they respond to changes in environmental conditions.

Nowadays, we are testing the application of the approach towards the development of commercial clean up solutions of agricultural soil.

(In collaboration with Prof Hanan Eizenberg and Prof. Zeev Ronen ; Metabolic modelling is lead by Dr Raphy Zarecki  ).

Summary of the work in Xu et al, ISMEJ 2019 ( Identification of potential biodegradation consortium members by comparing the microbiota in control and polluted soil. In simulations with a metabolic model as well as in in vitro experiments, the ArthrobacterHalobacillus consortium degraded the pollutant atrazine more efficiently than other consortia or than Arthrobacter alone. The model also predicted that the boost in degradation efficiencyis due to cross-feeding between Arthrobacter and Halobacillus, which was confirmed in vitro (Figure is taken from Faust, Trends in Biotechnology 2018, a spotlight on our work,

Testing the application of the approach towards the development of commercial clean up solutions of agricultural soil. Left: experimental design; Right: experiment in the green house. In the Figure below: Kusum Dhakar, in charge of the experiments.

2. Deciphering microbial functions in amendment-based solutions for soil-borne disease suppression

Many soil-borne diseases have efficient and sustainable, amendment based solutions. Success of such a substrate-based (amendment-based) treatment to stimulate a microbiome-mediated disease control strategy is determined by the introduction of accessible metabolites that are beneficial to organisms functional in disease control or deleterious to organisms contributing to disease progression. Metagenomic surveys allow exploring the significance of shifts in community structure through comparing the functional potential of different samples.

We apply network approaches for finding environmental friendly solutions for soil borne diseases, based on the analyses of metagenomics data from healthy vs.  symptomatic apple orchards following effective and non-effective soil amendment treatments. Such integration of metagenomics data will hopefully lay foundations for the educated design of sustainable solutions for suppressing soilborne disease symptoms through substrate mediated recruitment of disease-suppressive microbiomes in cropping systems.


(In collaboration with Prof Mark Mazzola ).











Use of soil amendment treatments for the suppression of soil amendment treatment in apple orchards (Mark Mazzola, USDA-ARS, Figure taken from Mazolla & Freilich Phytopathology 2017, Relative growth performance of apple trees on a soil-borne disease infected site when cultivated in (left to right) fumigated soil (chemical treatment), substrate-based amended soil or non-treated infected orchard soil. Soil amendment produced a soil microbiological environment that was resistant to re-infestation by apple root pathogens. In contrast, fumigated soils were rapidly recolonized by pathogens. Below: PCA of the abundance of enzymes identified in metagenomics libraries constructed from root-soil libraries from treated and untreated sites. Analysis indicate that the symptomatic change is associated with a change of function in the microbial communities. Network approaches are applied for deciphering this change (From Vetcos et al In prepartion). 

3. Eco-systems biology approach for modeling tritrophic networks of plant host, sap-feeding insect and their symbionts.

Ecological interactions are based on the metabolic capacities of individual organisms, and the metabolic exchanges between them. Such exchanges enable organisms to complement their nutritional needs. We aim to decipher one such ecological puzzle by integrating in-silico network modeling, with experimental validations. Interactions among host-plants, sap-feeding insect (sweet potato whitefly Bemisia tabaci) and its bacterial symbionts, form a tri-trophic network. Based on genomic information, we predict possible interactions, and their effect on community dynamics. This relatively simple and well-defined eco-system, can provide a model for the application of genomics on the study of community dynamics.

(In collaboration with Einat Zchori-Fein)




(A) Illustration of whitefly feeding on phloem sap from host leaf. (B) Illustration of the network of holobiont's (whitefly-symbionts) using phloem nutrients, (C) Nutritional puzzle in a plant-host-symbiont system, with a variety of plant phloems. The obligatory symbiont Portiera is evolved to complement the amino acids of its whitefly host in the nutritionally poor phloem environment. Network based simulations predict complementation patterns in different plant environments, and demonstrate the catalytic plasticity allowing a polyphagous life style. Each column represents phloem environment in a different plant. Green boxes- amino acids found in the phloem; black boxes – amino acids synthesized by the insect; pink boxes – amino acids produced by an obligatory, evolutionary adapted, bacterial symbiont, solely or through complementary interactions with the insect. Figure is adapted from Selvaraj et al, In preparation.

4. Promoting enhanced degradation of BTEX contaminants

Soils contaminated with hazardous organic pollutants are rapidly increasing worldwide introducing a need in remediation approaches. Bioremediation - the breakdown of pollutants through microbial metabolism is increasingly acknowledged as a cost-effective, environmentally friendly strategy for environmental cleaning. To date, bioremediation strategies are mostly driven by intuition and rely on experience derived from trial and error experiments.  Understanding the required conditions for natural enhancement of desired endogenous consortia under anaerobic conditions can improve the rate of success of bioremediation treatments. The aromatic hydrocarbons Benzene, toluene, ethylbenzene and xylenes (BTEXs), global-wide contaminants that are of great environmental concern, are usually used as model compounds to study anaerobic degradation in soil.  Under anaerobic conditions, BTEXs  degradation is a complex, multi-stages processes, involving many microbial species. The current project aims at integration of electrochemical-anaerobic reactors and genomic based modeling approaches for studying the degradation processes of BTEXs under anaerobic conditions. We will use continuous three-chamber bioreactors that allows simplifying, dissecting and monitoring the dynamics of biodegradation. The designed continuous bioreactor will include three chambers, optimal for different biodegradation stages: fermentation, iron-reducing conditions, and methanogenesis. The dynamics and activity of microbial communities exposed to toluene will be monitored in each chamber; key species (especially archaea) involved in degradation of toluene will be identified and selected for in silico representation; genome scale metabolic modeling approaches will be applied in order to simulate community activity and predict optimal solutions in terms of degradation efficiency; optimal conditions for bioremediation based on predictions will be tested and validated in soil-like conditions in order to suggest practical strategies for improved bioremediation of BTEXs-contaminated sites. (Project was designed and is headed by Dr. Keren Golub-Yanuka; Metabolic modelling is led by Dr Raphy Zarecky).

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