Knowledge based design of complex synthetic microbial communities for plant protection

Project Information

DeCoCt

Grant agreement ID: 820124

DOI

10.3030/820124

Project closed

EC signature date 4 February 2019

Start date 1 March 2019

End date 28 February 2025

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 925 500,00

EU contribution

€ 1 925 500,00

Coordinated by

EBERHARD KARLS UNIVERSITAET TUEBINGEN
Germany

Periodic Reporting for period 4 - DeCoCt (Knowledge based design of complex synthetic microbial communities for plant protection)

Reporting period: 2023-09-01 to 2025-02-28

Summary of the context and overall objectives of the project

Crop losses caused by plant diseases are increasing worldwide, with fungal and fungal-like pathogens playing a major role. At the same time, many pathogens are becoming resistant to fungicides, and the development and approval of new chemical control agents are in decline. This creates an urgent need for sustainable alternatives to protect plants. One promising approach is to understand and utilize the plant microbiota—the diverse communities of bacteria, fungi, and protists that live on and inside plant tissues.
Historically, plant research has focused on direct interactions between plants and individual microbes. However, it is now clear that plants live in association with complex microbial communities that interact both with the host and with each other. These communities include beneficial microbes as well as latent pathogens. Facultative pathogens, for example, are often present even in healthy plants but can cause disease when environmental conditions change. Studies have shown that these interactions can remain stable over long evolutionary timescales. Beneficial microbes, on the other hand, can suppress such pathogens, especially when acting as part of a stable and diverse community.
The DeCoCt project set out to design complex synthetic microbial communities (SynComs) that support plant health through ecological stability. Using Arabidopsis thaliana as a model, the project combined long-term field data, microbial profiling, host genotyping, and computational approaches to identify microbial traits, community structures, and environmental drivers that underpin robustness and protection. SynComs were constructed that could suppress Albugo laibachii, the causal agent of white blister rust on Brassicaceae, even under non-sterile, competitive conditions.
Key traits contributing to SynCom stability included biofilm formation, the production and sharing of siderophores, and functional redundancy among microbial taxa. These findings show that microbiota-based disease protection is achievable, but strongly influenced by environmental context and community composition.
The project has laid a conceptual and methodological foundation for microbiome-informed strategies in sustainable agriculture.

Work performed from the beginning of the project to the end of the period covered by the report and main results achieved so far

To design effective synthetic microbial communities (SynComs) for plant protection, it is essential to understand how microbiota achieve robustness under natural conditions and which factors shape their composition and stability. The DeCoCt project systematically investigated the abiotic, biotic, and host-related drivers of microbial community dynamics in Arabidopsis thaliana, integrating long-term field studies, computational modeling, and experimental validation.
1) Abiotic factors:
We demonstrated that environmental parameters, especially temperature and precipitation, are key determinants of microbial community stability. Low temperatures, in particular, favor slow-growing, cold-tolerant microbes that persist over winter on Arabidopsis (Almario et al., 2021).
2) Internal and external biotic interactions:
Using machine learning and longitudinal field data, we identified microbial taxa that contribute to disease suppression and community stability (Kemen et al., 2025). SynComs were designed and tested for their ability to protect against Albugo laibachii, revealing that protective function depends on strain identity, community context, and intermicrobial interactions. Specific combinations of Cystofilobasidium and Pseudomonas enhanced robustness, while other microbes introduced instability. Cross-host experiments with Lotus corniculatus confirmed that host-specific communities vary in their ability to persist and function across plant species.
3) Host factors:
By combining microbiome profiles with genomic data from natural Arabidopsis populations over ten years, we quantified the influence of host genotype on community composition. While genetic effects were generally modest, they became more apparent under specific environmental conditions. These findings suggest that host-mediated microbiota recruitment is context-dependent, and that microbial traits such as biofilm formation and iron acquisition often override host effects in shaping communities.
In the final phase of the project, we validated key findings experimentally. SynComs suppressed pathogen infection even in non-sterile environments, showing ecological resilience. We identified traits such as siderophore sharing and antimicrobial peptide production as key mechanisms contributing to this stability (Gómez-Pérez et al., 2023; Höhn et al., 2024). Long-read metagenomics, proteomics, and metabolomics enabled deep functional characterization of SynCom performance.
A major outcome was the release of structured, FAIR-compliant datasets via the NFDI DataPlant infrastructure. The amplicon and genotype data are publicly available under DOI 10.57754/FDAT.61ckt-vm178. The proteomics dataset will be released shortly. These resources are actively disseminated through preprints, peer-reviewed publications, and conference presentations.
The DeCoCt project has achieved its primary goals. It has demonstrated that predictive and stable SynCom design is feasible and has uncovered the complexity and context dependence of microbiome function. These insights provide a foundation for microbiota-based strategies in sustainable agriculture.

Progress beyond the state of the art and expected potential impact (including the socio-economic impact and the wider societal implications of the project so far)

Synthetic microbial communities are increasingly used to dissect microbe–microbe and microbe–host interactions in controlled systems. However, most SynComs used to date have relied on empirically selected, fast-growing microbes that are easy to isolate in the lab, rather than reflecting the ecological complexity of natural plant microbiota. DeCoCt has advanced beyond this state by identifying key community members and functions based on cultivation-independent amplicon sequencing, environmental time series, and machine learning-guided selection (Mahmoudi et al., 2024).
We combined high-resolution microbial and environmental data from natural Arabidopsis thaliana populations sampled over a decade. This allowed us to identify robust taxa, assess seasonal and interannual stability, and quantify the influence of abiotic and host-associated factors. A central insight was that community robustness increases over the plant life cycle while overall diversity declines (Almario et al., 2021). Longitudinal analyses also revealed that microbial "hub" taxa are not static but can change with season, site, or stress regime.
By integrating host genotype data, we showed that genotype effects on microbiome structure are real but context-dependent. In parallel, we demonstrated that key traits such as siderophore production and biofilm formation contribute to SynCom stability in vivo. These insights were confirmed through direct experimentation with synthetic communities under non-sterile laboratory conditions.
The final stage of the project successfully delivered FAIR-compliant, publicly available datasets. The results have been disseminated through multiple publications, preprints, and public data releases.
DeCoCt has not only demonstrated the feasibility of designing predictive, stable SynComs for plant protection but has also contributed new insights into microbiota dynamics, trait redundancy, and community buffering mechanisms. These findings are expected to support future development of microbiome-based applications in agriculture.

Fig 1) Factors impacting the design of synthetic microbial communities.