Periodic Reporting for period 1 - MICROCOSMS (Exploring microbial community stability across mutational spectra)
Période du rapport: 2023-07-01 au 2025-06-30
Mutualistic interactions – where both species benefit – lie at the core of many human-relevant microbial communities, such as polymicrobial infections, the human-, plant-, and animal-associated beneficial microbiomes, and synthetic microbial communities in biotechnology. However, previous work has suggested that mutualisms can break down when under particularly strong selective pressures, such as strong antibiotics. Therefore the ability to predict and prevent mutualism breakdown is an important goal for many fundamental and applied fields of biology. To help bridge this gap, our work combines evolutionary biology and ecology to elucidate the role of mutation rate and bias on the stability of mutualisms under stress.
In brief, I conducted evolution experiments in obligate mutualistic pairs of non-pathogenic E. coli under strong antibiotic selection. These communities contained mutator strains, which are microbial strains that have highly elevated mutation rates and biases towards specific classes of mutations. We were able to uncover adaptive pathways only accessible to communities containing multiple mutators, and adaptive pathways in other communities only accessible by specific types of mutator strains. This helps provide us insights into the role of mutation biases in the adaptation to both abiotic and biotic factors in microbial communities. Our results advance our understanding of the predictability of mutualism breakdown in pairwise mutualistic communities, ultimately contributing to the prevention or elicitation of microbial community collapse in both natural and synthetic microbial ecosystems.
In brief, I conducted evolution experiments in obligate mutualistic pairs of non-pathogenic E. coli under strong antibiotic selection. These communities contained mutator strains, which are microbial strains that have highly elevated mutation rates and biases towards specific classes of mutations. We were able to uncover adaptive pathways only accessible to communities containing multiple mutators, and adaptive pathways in other communities only accessible by specific types of mutator strains. This helps provide us insights into the role of mutation biases in the adaptation to both abiotic and biotic factors in microbial communities. Our results advance our understanding of the predictability of mutualism breakdown in pairwise mutualistic communities, ultimately contributing to the prevention or elicitation of microbial community collapse in both natural and synthetic microbial ecosystems.
I succesfully engineered laboratory strains of E. coli to contain a combination of three characteristics: an amino acid auxotrophy (i.e. inability to growht unless it is externally provided), an elevated (and biased) mutation rate, and a fluorescent marker. These characteristics ensured that we had pairwise mutualistic communities that contained mutator strains, and that the composition of these communities could be tracked over time. After pairing these engineered strains into either single mutator or double mutator communities, I conducted two separate evolution experiments.
In the first evolution experiment, communities were exposed to increasing concentrations of the beta-lactam antibiotic cefotaxime. In this adaptive evolution experiment, we found large differences in the survivability of each community to antibiotic stress. We found that only communities in which both members had elevated mutation rates were able to survive increased antibiotic concentrations across all replicates. Following this evolution experiment, we extensively characterised the type of interaction each community contained, categorising each community as either ‘revertant’, ‘commensal’ and ‘mutualistic’, depending on if each strain needed the other strain to survive. We found similar rates of mainenance of mutualism in our double mutator communities as ‘wild type’ communities that evolved without antibiotic, indicating that adaptation to environmental stress does not need to come at the expense of mutualistic interactions (as previously suggested).
In the second evolution experiment, we serially bottlenecked our communities through individual clones of each constituent species, before growing both species together again. During this non-adaptive portion of this evolution experiment, mutations were able to accumulate in each species’ genome, potentially destabilising the mutualistic interaction: as mutator strains have increased mutation rates, we should expect to see a higher degree of metabolic reversions and extinctions in these communities. However, so far we have observed the opposite, with slightly more extinctions witnessed in the non-mutator communities. We are continuing this work with more bottlenecks to get a stronger signal of mutualism breakdown.
Overall, this work shows that communities can be protected from environmental stress without compromising on community structure and function, and that this is predictable based on the presence of mutator strains in the populations. Furthermore, it reiterates the importance of incorporating knowledge of mutator strains into evolutionary predictions.
In the first evolution experiment, communities were exposed to increasing concentrations of the beta-lactam antibiotic cefotaxime. In this adaptive evolution experiment, we found large differences in the survivability of each community to antibiotic stress. We found that only communities in which both members had elevated mutation rates were able to survive increased antibiotic concentrations across all replicates. Following this evolution experiment, we extensively characterised the type of interaction each community contained, categorising each community as either ‘revertant’, ‘commensal’ and ‘mutualistic’, depending on if each strain needed the other strain to survive. We found similar rates of mainenance of mutualism in our double mutator communities as ‘wild type’ communities that evolved without antibiotic, indicating that adaptation to environmental stress does not need to come at the expense of mutualistic interactions (as previously suggested).
In the second evolution experiment, we serially bottlenecked our communities through individual clones of each constituent species, before growing both species together again. During this non-adaptive portion of this evolution experiment, mutations were able to accumulate in each species’ genome, potentially destabilising the mutualistic interaction: as mutator strains have increased mutation rates, we should expect to see a higher degree of metabolic reversions and extinctions in these communities. However, so far we have observed the opposite, with slightly more extinctions witnessed in the non-mutator communities. We are continuing this work with more bottlenecks to get a stronger signal of mutualism breakdown.
Overall, this work shows that communities can be protected from environmental stress without compromising on community structure and function, and that this is predictable based on the presence of mutator strains in the populations. Furthermore, it reiterates the importance of incorporating knowledge of mutator strains into evolutionary predictions.
This proposal is part of a wave of cutting-edge studies that leverage experimental evolution techniques to test fundamental hypothesis in evolutionary biology, with applications for clinical, agricultural and biotechnological settings. Predicting the evolution of communities is a timely endeavour, considering the rate of environmental collapse due to climate change, or the increase in antibiotic resistance in both clinical and environmental microbial strains. A major outcome of this proposal is to show the mechanisms of adaptation to rapid environmental change do not necessarily need to lead to mutualism collapse, giving hope to the efforts to protect vulnerable and vital ecosystems. Overall, this project contributes important fundamental knowledge about the predictability of evolution, and can be applied to improving biodiversity in the wild, and improving therapeutic practice in the clinic.