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Knowledge based design of complex synthetic microbial communities for plant protection

Periodic Reporting for period 2 - DeCoCt (Knowledge based design of complex synthetic microbial communities for plant protection)

Reporting period: 2020-09-01 to 2022-02-28

Plant diseases on crop plants caused by fungi are constantly increasing causing a major thread to food production (Fisher et al., 2012). In addition, many fungal pathogens have become resistant to a broad range of fungicides and multidrug resistance is becoming a main problem in agricultural and in the medical field (Rhodes, 2019). The discovery and acceptance for new chemicals in agriculture is at the same time decreasing. A key question is: where do those “new” pathogens originate from and why are they coming up now? What can we do to protect our crops from such pathogens or what can we do to avoid these pathogens coming up at all?
A paradigm shift in plant sciences has been taking place that is opening up new resources: Over decades, the focus was on direct plant-microbe interactions while plants, such as all other living organisms, are in tight association with a broad range of microbes. All microbes associated with an organism including those with short transient interactions, are called the microbiota and a system of a host and associated microbiota is called the holobiont. Within the holobiont, microbes interact with their host and what is less well understood with each other. A complex mixture of host and microbial properties determines microbial community structure including diversity and stability, while stability is defined by how much microbiota vary if repeatedly sampled under same conditions. A stable community has been hypothesized to protect a host from developing disease. In fact, our data shows, that almost all microbiota of healthy looking plants from fields contain potential pathogens (Karasov et al., 2018), called facultative pathogens. Under disturbed conditions such as high temperature or humidity, facultative pathogens can become a severe problem. In lab experiments, we and others have shown, that microbial isolates from natural sites can protect plants from disease. We therefore hypothesize that it is possible to assemble microbial communities that are able to protect plants from pathogens, particularly facultative pathogens through community stabilization.
A problem of using such beneficial plant protective microbes on a broader scale is the lack of persistence under natural conditions. Our goal therefore is to design complex knowledge based synthetic communities that are robust to biotic and abiotic perturbation and strengthen the host associated microbiota in a host dependent manner.
Key to design a synthetic microbial community for plant protection is to understand how microbial communities gain robustness under natural conditions and how much fluctuation there is. Further it is crucial to define main stabilizing and destabilizing drivers of communities.
Our results revealed multifactorial drivers being important for community dynamics and stability. We could narrow those down to three main groups that impact community structure over time:
1) Abiotic factors: One such factor we could pin down is temperature (Almario et al., 2021). While the plant host is most likely responsible for buffering high temperature, low temperature strongly impacts microbial stability. For Arabidopsis microbiota that stay over winter, cold resistance is key to survive and might therefore explain why on Arabidopsis slow growing microbes can still be abundant key microbes that do not grow well under laboratory conditions. Another factor is humidity and precipitation. Particularly leaf associated communities are directly affected by precipitation through mechanical influences and dissemination of microbes. To investigate this, we make us of natural plant communities that were sheltered to different degrees from precipitation over several years (in collaboration with group for Plant Ecology headed by Katja Tielbörger). We have isolated a broad range of microbes from those natural sites and are testing them for their robustness to such dominant biotic factors.
2) Internal and external biotic interactions: We have designed three synthetic communities that protect plants from the pathogen Pseudomonas syringae. Using amplicon sequencing to analyze community dynamics over time, we were able to identify stabilizing and destabilizing microbes. We have further identified plant specific communities from Lotus corniculatus and Arabidopsis thaliana. These communities are used to test coherence when confronted with each other on one host or the other.
3) Host factors: To identify host factors that impact microbial communities under natural conditions, we have collected host genome data and microbiome data from natural Arabidopsis populations. We are currently calculating models that will enable us to identify host genes that impact microbial communities. Our goal is to use this information to manipulate plants to host specific microbial communities. On the other hand, we are interested in those microbes that independent of the host genotype confer robustness to a synthetic community.

In the second phase of DeCoCt, our main focus will be to test our already designed synthetic communities and better understand mechanisms by which these communities are stabilized. Mechanisms will help us to further optimize synthetic communities and particularly to reduce complexity that is crucial to develop a product that can be used in agriculture.
Synthetic microbial communities are more and more used to investigate microbe-microbe interactions under laboratory conditions with the aim of understanding fundamental mechanisms that can be applied to increase yield and protect crops from pathogens. Synthetic communities used so far, are mainly based on empirical isolation methods for microbes and therefore dominated by fast growing, easy to isolate microbes. Our goal is to fist identify key players of natural microbial communities based on cultivation independent profiling and deep computational analyses in order to assemble knowledge based microbial communities. We could show that under natural conditions, high fluctuations of microbes occur and time series at different scales are key to understand microbial dynamics and identify robustness. We could show, that over the course of an A. thaliana growth period under natural conditions, microbial communities gain robustness and get less diverse (Almario et al., 2021). Only very few microbes persist from one growth period to the next. A key finding was, that previously identified hub microbes are often not robust over time and hub microbes can vary between timepoints (Almario et al., 2021). Correlating our data to abiotic factors such as temperature led to the hypothesis that cold is one of the main factors shaping microbial communities. For the next phase of the DeCoCt project, those abiotic factors together with host factors that impact microbial interactions will be the main focus.
Fig 1) Factors impacting the design of synthetic microbial communities.