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Evolving interactions in microbial communities

Periodic Reporting for period 3 - EVOMICROCOMM (Evolving interactions in microbial communities)

Reporting period: 2020-05-01 to 2021-10-31

Microbes play an important role in various aspects of our lives, from our own health to the health of our environment. In almost all of their natural habitats, microbes live in dense communities composed of different strains and species that interact with each other. As these microbes evolve, so do the interactions between them, which alters the functioning of the community as a whole.

In this project, we are developing theoretical and experimental tools to study and control evolving interactions between cells and species living in microbial ecosystems. We have three main research objectives: first, we are coupling theory and experiments to disentangle and characterize the social interactions between four bacterial species that make up an ecosystem used to degrade industrial pollutants. Our second objective is to use this knowledge to control this same ecosystem, by directing it toward increased productivity and stability. Finally, our third objective is to "breed" novel communities from scratch using experimental evolution to promote cooperative interactions between community members and thereby increase productivity.

This interdisciplinary and ambitious research will allow us to improve existing methods in pollution degradation, and to design new microbial communities for this and other purposes. More generally, our model system will provide an in-depth conceptual understanding of microbial ecosystems and their evolution, and the tools to investigate more complex microbial communities. Our ultimate vision is to possess the technology to use microbial communities to degrade waste, generate efficient biofuels, and design customized treatments for intestinal diseases. This project promises to create the foundations needed to develop this technology, and open many exciting avenues for future research.
In the past months, we have characterized the interactions between the four species in the liquid industrial pollutants. We were surprised to find that the species had exclusively positive effects on one another (or no effects). This appeared at first to contradict with the predictions of previously published models. However, we then became aware of the so-called "stress-gradient hypothesis", which predicts that stressful environments - which the industrial pollutant surely is for bacteria - can promote positive interactions. We then performed a series of experiments that confirmed that the stressful composition of the liquid is indeed what explains our results. This work also showed that pollution degradation can be improved as more species are added to a community, but that community size saturates quite quickly, at which point productivity cannot be improved. We have published these findings that can now be integrated into our understanding of microbial ecology.

In parallel, we have worked on a side-project involving infection by phage (bacterial viruses) of a community of two bacterial strains growing on a surface. Although this project seems unrelated, its goal is essentially to explore interspecies interactions, and the effect of the environment on them. We found that growing on a surface can protect bacteria from their phage attackers, and that they are less likely to become resistant to the phage if they are competing with other strains. This project has also been published

We have also been working on developing a chemically-defined version of the complex industrial pollutant to explore how inter-species interactions depend on their environment. We have also performed a year-long evolutionary experiment to explore how our four-species community can evolve over time, which is accompanied by bioinformatic analysis as well as the development of a mathematical model. Finally, we are working on "breeding" a novel community that is able to degrade the pollutant better than our current community. This work is still ongoing.
In this project, we have developed a powerful model system composed of just four bacterial species in a defined environment, which can be used to answer a number of important ecological and evolutionary questions. We have been successful at advancing the state of the art by showing how environmental toxicity can qualitatively shape interactions between bacterial species. We are currently working on how precisely to change the environment to quantitatively predict and control species abundances. We have also provided important insights into making our existing community more productive, and are currently generating results that will further instruct on how to evolve such productive communities from scratch. All of these results are expected to be robust, as they will be supported by both experimental data and mathematical and computational models.
Pictures of colonies of different mixtures of the four bacterial species