The MSE group is co-lead by Dr. Olga Schubert and Prof. Martin Ackermann and is affiliated with Eawag and ETH Zurich.
Microbes are essential for the integrity of environmental ecosystems and may be harnessed to provide sustainable and scalable solutions to the challenges posed by climate change and environmental degradation. Our group's research aims at better understanding how microbes and microbiomes function in order to, for example, provide insights into microbial processes underlying the marine carbon cycle and inform the engineering of microbes or microbiomes to provide sustainable solutions, from wastewater treatment to plastic degradation and CO2 sequestration. We often focus first on understanding fundamental processes at the level of single cells and then ask how the behavior of individual microbes and interactions between them gives rise to the function of microbial communities and entire microbial ecosystems. In our studies, we use microfluidics-based live-cell imaging and a variety of omics methods including genomics, transcriptomics and proteomics and metabolomics. We furthermore use bioinformatics approaches as well as mathematical and computational modeling to gain further mechanistic insights and to conceptualize our findings. To connect our work to tangible solutions for concrete problems, we collaborate with environmental physicists, chemists and engineers. Our research is funded by the SNSF, Innosuisse and the Simons Foundation.
More information on our ongoing projects can be found on our group webite here.
For a full list of publications please visit Martin's and Olga's Google Scholar profiles.
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title => protected'Antagonism as a foraging strategy in microbial communities' (58 chars)
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description => protected'In natural habitats, nutrient availability limits bacterial growth. We disco vered that bacteria can overcome this limitation by acquiring nutrients by l ysing neighboring cells through contact-dependent antagonism. Using single-c ell live imaging and isotopic markers, we found that during starvation, the type VI secretion system (T6SS) lysed neighboring cells and thus provided nu trients from lysing cells for growth. Genomic adaptations in antagonists, ch aracterized by a reduced metabolic gene repertoire, and the previously unexp lored distribution of the T6SS across bacterial taxa in natural environments suggest that bacterial antagonism may contribute to nutrient transfer withi n microbial communities in many ecosystems.' (727 chars)
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authors => protected'Henderson, A.; Del Panta, A.; Schubert, O. T.; Mitri,&nb sp;S.; van Vliet, S.' (101 chars)
title => protected'Disentangling the feedback loops driving spatial patterning in microbial com munities' (84 chars)
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description => protected'The properties of multispecies biofilms are determined by how species are ar ranged in space. How these patterns emerge is a complex and largely unsolved problem. Here, we synthesize the known factors affecting pattern formation, identify the interdependencies and feedback loops coupling them, and discus s approaches to disentangle their effects. Finally, we propose an interdisci plinary research program that could create a predictive understanding of pat tern formation in microbial communities.' (496 chars)
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authors => protected'Huelsmann, M.; Schubert, O. T.; Ackermann, M.' (65 chars)
title => protected'A framework for understanding collective microbiome metabolism' (62 chars)
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description => protected'Microbiome metabolism underlies numerous vital ecosystem functions. Individu al microbiome members often perform partial catabolism of substrates or do n ot express all of the metabolic functions required for growth. Microbiome me mbers can complement each other by exchanging metabolic intermediates and ce llular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial met abolism and how metabolic functions are distributed among them. Here we argu e that natural selection for proteome efficiency—that is, performing essen tial metabolic fluxes at a minimal protein investment—explains partial met abolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of coll ective metabolism, the conditions under which these motifs increase the prot eome efficiency of individuals and the metabolic interactions they result in . In summary, we propose a mechanistic framework for how collective metaboli c functions emerge from selection on individuals.' (1113 chars)
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authors => protected'Dal Co, A.; van Vliet, S.; Kiviet, D. J.; Schlegel,  ;S.; Ackermann, M.' (99 chars)
title => protected'Short-range interactions govern the dynamics and functions of microbial comm unities' (83 chars)
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description => protected'Communities of interacting microorganisms play important roles across all ha bitats on Earth. These communities typically consist of a large number of sp ecies that perform different metabolic processes. The functions of microbial communities ultimately emerge from interactions between these different mic roorganisms. To understand the dynamics and functions of microbial communiti es, we thus need to know the nature and strength of these interactions. Here , we quantified the interaction strength between individual cells in microbi al communities. We worked with synthetic communities of <em>Escherichia coli </em> bacteria that exchange metabolites to grow. We combined single-cell gr owth rate measurements with mathematical modelling to quantify metabolic int eractions between individual cells and to map the spatial interaction networ k in these communities. We found that cells only interact with other cells i n their immediate neighbourhood. This short interaction range limits the cou pling between different species and reduces their ability to perform metabol ic processes collectively. Our experiments and models demonstrate that the s patial scale of biotic interaction plays a fundamental role in shaping the e cological dynamics of communities and the functioning of ecosystems.' (1284 chars)
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Antagonism as a foraging strategy in microbial communities
In natural habitats, nutrient availability limits bacterial growth. We discovered that bacteria can overcome this limitation by acquiring nutrients by lysing neighboring cells through contact-dependent antagonism. Using single-cell live imaging and isotopic markers, we found that during starvation, the type VI secretion system (T6SS) lysed neighboring cells and thus provided nutrients from lysing cells for growth. Genomic adaptations in antagonists, characterized by a reduced metabolic gene repertoire, and the previously unexplored distribution of the T6SS across bacterial taxa in natural environments suggest that bacterial antagonism may contribute to nutrient transfer within microbial communities in many ecosystems.
Stubbusch, A. K. M.; Peaudecerf, F. J.; Lee, K. S.; Paoli, L.; Schwartzman, J.; Stocker, R.; Basler, M.; Schubert, O. T.; Ackermann, M.; Magnabosco, C.; D’Souza, G. G. (2025) Antagonism as a foraging strategy in microbial communities, Science, 388(6752), 1214-1217, doi:10.1126/science.adr8286, Institutional Repository
Disentangling the feedback loops driving spatial patterning in microbial communities
The properties of multispecies biofilms are determined by how species are arranged in space. How these patterns emerge is a complex and largely unsolved problem. Here, we synthesize the known factors affecting pattern formation, identify the interdependencies and feedback loops coupling them, and discuss approaches to disentangle their effects. Finally, we propose an interdisciplinary research program that could create a predictive understanding of pattern formation in microbial communities.
Henderson, A.; Del Panta, A.; Schubert, O. T.; Mitri, S.; van Vliet, S. (2025) Disentangling the feedback loops driving spatial patterning in microbial communities, npj Biofilms and Microbiomes, 11, 32 (14 pp.), doi:10.1038/s41522-025-00666-1, Institutional Repository
A framework for understanding collective microbiome metabolism
Microbiome metabolism underlies numerous vital ecosystem functions. Individual microbiome members often perform partial catabolism of substrates or do not express all of the metabolic functions required for growth. Microbiome members can complement each other by exchanging metabolic intermediates and cellular building blocks to achieve a collective metabolism. We currently lack a mechanistic framework to explain why microbiome members adopt partial metabolism and how metabolic functions are distributed among them. Here we argue that natural selection for proteome efficiency—that is, performing essential metabolic fluxes at a minimal protein investment—explains partial metabolism of microbiome members, which underpins the collective metabolism of microbiomes. Using the carbon cycle as an example, we discuss motifs of collective metabolism, the conditions under which these motifs increase the proteome efficiency of individuals and the metabolic interactions they result in. In summary, we propose a mechanistic framework for how collective metabolic functions emerge from selection on individuals.
Short-range interactions govern the dynamics and functions of microbial communities
Communities of interacting microorganisms play important roles across all habitats on Earth. These communities typically consist of a large number of species that perform different metabolic processes. The functions of microbial communities ultimately emerge from interactions between these different microorganisms. To understand the dynamics and functions of microbial communities, we thus need to know the nature and strength of these interactions. Here, we quantified the interaction strength between individual cells in microbial communities. We worked with synthetic communities of Escherichia coli bacteria that exchange metabolites to grow. We combined single-cell growth rate measurements with mathematical modelling to quantify metabolic interactions between individual cells and to map the spatial interaction network in these communities. We found that cells only interact with other cells in their immediate neighbourhood. This short interaction range limits the coupling between different species and reduces their ability to perform metabolic processes collectively. Our experiments and models demonstrate that the spatial scale of biotic interaction plays a fundamental role in shaping the ecological dynamics of communities and the functioning of ecosystems.
Dal Co, A.; van Vliet, S.; Kiviet, D. J.; Schlegel, S.; Ackermann, M. (2020) Short-range interactions govern the dynamics and functions of microbial communities, Nature Ecology & Evolution, 4, 366-375, doi:10.1038/s41559-019-1080-2, Institutional Repository
Projects
How do phages - the viruses that infect bacteria - change the membership and activities of microbial communities?
In order to better understand natural processes and also to be able to better control the activities of microbial communities in technical systems such as wastewater treatment plants, we need to understand how microbial communities work.
