Bugs as Drugs: Understanding Microbial Interaction Networks to Prevent and Treat Infections

Project Information

BugDrug

Grant agreement ID: 948753

DOI

10.3030/948753

EC signature date 3 November 2020

Start date 1 January 2021

End date 31 December 2026

Funded under

• EXCELLENT SCIENCE - European Research Council (ERC)

Total cost

€ 1 494 437,00

EU contribution

€ 1 494 437,00

Coordinated by

EBERHARD KARLS UNIVERSITAET TUEBINGEN
Germany

Periodic Reporting for period 3 - BugDrug (Bugs as Drugs: Understanding Microbial Interaction Networks to Prevent and Treat Infections)

Reporting period: 2024-01-01 to 2025-06-30

Summary of the context and overall objectives of the project

More and more pathogens become resistant to antibiotics which causes a serious health crisis. Infections that could be easily treated in the past become lethal threats again. This situation requires new ways of treating and curing infections. The goal of this project is to find an alternative infection treatment that is not based on antibiotics but that harnesses the natural interactions between microbes. Pathogens that want to infect our body must first deal with the natural bacteria that already live there (commensals). Only if these bacteria allow the pathogen to grow in our body we can become sick. Accordingly, if we find commensals that inhibit pathogens we could use them as a natural treatment against infections. Developing a method to find such anti-pathogenic commensals is the central idea of this project. For that purpose, we image and identify microbes inside the gut of the host C. elegans. We will then use this data to identify microbes that out-compete pathogens – these are microbes that the pathogen cannot locally live together. We complement measurements within the worm gut with in vitro measurements outside the worms, where we will measure complete interaction networks for microbial communities. We are in particular interested in how the structure of those networks decides if a pathogen can persist in the community or not. Finally, we will add microbes - that we identified to repel pathogens - to the sick host to see if diseases can be treated this way. This method would allow for a completely new and highly individualized way to treat infections with only minor side effects.

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

We could achieve first images of bacteria inside the gut of C. elegans and currently aim to expand this technology towards more complex communities.
We also established an assay to measure microbial interactions ( in particular between commensals and pathogens) in high-throughput resulting in around 10.000 measured interactions per run in vitro. The resulting dataset allowed us to predict interaction between microbes with quite high accuracy. We want to use this information to predict which bacteria can fight pathogens even without measuring it.
Finally, we could establish an assay that allows us to measure pathogenicity of microbes and their communities in C. elegans in high-throughput. This will allow us to study how microbes and their communities impact a host and in particular which microbes can protect a host from pathogens. We will combine this assay with our findings from the bacteria interaction assay described above to test if we can really identify bacteria that can fight pathogens and thus heal hosts from infections from their genomes alone.

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)

Our high-throughput assays for bacterial interactions and worm pathogenesis allow us to study the effect of commensals on pathogens and their effect on hosts in combination in very high numbers. This is not possible with other interaction assays and animal models that allow for only much lower throughput. I am optimistic that in particular the combination between in vitro interaction studies and in vivo impact on host will allow us to identify bacteria and mechanisms by which commensals suppress pathogens. We want to use this knowledge to specifically fight infections within hosts.

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