Synthetic and engineered microbiomes

Compared to natural microbial communities, synthetic microbiomes offer a high degree of experimental control. This allows research to go beyond correlative studies, to establish causation and to identify mechanisms that underlie community dynamics.

Synthetic microbiomes allow the quantification of interspecies interactions and of spatial positioning of members with high precision. These factors can be manipulated experimentally to identify the ecological principles that govern microbiome dynamics and functioning. This knowledge is needed to better engineer microbiomes with desired properties.

The objectives of WP4 are to:

  • Build synthetic microbiomes based on the systems from WP1–3
  • Identify pairwise interactions and predict community behaviour in synthetic microbiomes
  • Map interaction networks to dynamical behaviours and spatial patterns
  • Compare synthetic microbiomes to extract unifying principles

WP4 involves a large number of synthetic microbiomes across systems, including designed communities of well-studied strains, an oil-degrading microbial consortium, and simplified microbiomes from the ocean, the mouse, the honeybee, the leaf, and the soil.

WP4 aims to derive fundamental principles that can be harnessed to engineer microbiomes for biotechnological applications. The approach integrates an evolutionary perspective, providing testable predictions and a framework to understand the functioning and stability of complex biological systems over extended periods of time.

Work Package Leaders
Prof. Martin Ackermann
ETH Zurich

Prof. Sara Mitri
University of Lausanne

Latest publications

LCMSpector: A simple open-source viewer for targeted hyphenated mass spectrometry analysis
Fido, M., Hoesli, E., Cappio Barazzone, E., Zenobi, R., Slack E. (2025).
https://doi.org/10.1371/journal.pcbi.1013095
Deciphering microbial spatial organization: insights from synthetic and engineered communities
Pignon, E., Schaerli, Y. (2025).
https://doi.org/10.1093/ismejo/wraf122
Uptake and leakage rates differentially shape community arrangement and composition of microbial consortia
Pignon, E. , Holló, G. , Steiner, T. , van Vliet, S., Schaerli, Y. (2025).
https://doi.org/10.1093/ismejo/wraf122