Quantifying the Link Between Architectural Integrity and Adaptive Potential in Developing Biofilms

•  Prof. Dr. Oskar Hallatschek Universität Leipzig, Sächsischer Inkubator für KlinischeTranslation (SIKT).

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A fascinating aspect of biofilms is their dynamic self-organization, which produces a rich set of morphological features, including pronounced internal cell ordering, strong surface attachment and, at larger scales, wrinkles, folds, and channels. The emerging architecture supports biofilm survival, endows them with resilience against physical stresses and contributes to antibiotic tolerance.

The integrity and function of the biofilm architecture is, however, threatened by adaptive mutations arising during biofilm growth if they expand and displace the wild type. Mechanisms that buffer against such “cancerous” mutations would promote robust biofilm development. Indeed, recent simulations and colony studies suggest that mechanical at bay, thus promoting the integrity of the architecture. On the other hand, suppressing beneficial mutations to sweep should hamper the community to adapt, for instance, to the very stresses that architecture buffers against (antibiotics, physical stresses).

We, therefore, hypothesize a tradeoff between the architectural integrity of a biofilm and its ability to adapt quickly to environmental challenges. We plan to test whether such a tradeoff exists and explore whether it is tipped towards integrity or adaptability, possibly depending on the mutations and their effect.

V. cholerae is the perfect model system to explore the hypothesized tradeoff. Apart form its public health significance and genetic tractability, V. cholerae biofilms have a well-characterized morphogenesis, much of it studied at single-cell resolution. We can thus build on an excellent understanding of the wild type architecture of V. cholerae biofilms to explore how it is perturbed by or buffers against evolutionary processes. To this end, we employ advanced imaging technologies adapted to the 3D biofilm context and spontaneously mutating fluorescent reporter constructs to track mutant clones in space and time. These data will be used to develop a predictive biofilm model of natural selection and genetic drift, allowing us to test our hypothesis of an emergent tradeoff between adaptive potential and architectural integrity.

Resolving the tradeoff between biofilm development and evolution will be an important step towards understanding eco-evolutionary feedback in single species biofilms. More generally, an improved understanding of the basic forces of evolution in biofilms will provide a baseline to model a wide range of evolutionary processes. We envision the newly developed synthetic mutagenesis system, as well as the biofilm evolution model, to be useful to numerous other SPP projects with interest in studying or accounting for evolutionary processes in biofilms.

Research Focus

The complexity of the biological world demonstrates that chance can produce powerful results since evolution is ultimately driven by random mutational events. Numerous aspects of biology, such as genetic diversity, genome architecture or developmental pathways, are difficult to explain without an understanding of the effects of randomness in evolution. A large fraction of our research efforts aims at quantifying the inherently stochastic trajectory of biological systems using methods of statistical physics.

Our research topics extend from the fundamental physics of stochastic reaction-diffusion systems far from equilibrium to explicit models of adaptive evolution in microbial populations that take into account biophysical aspects of biofilm formation.

These projects are driven by basic evolutionary puzzles such as “How fast is adaptation?” or “When is evolution driven by survival of the luckiest rather than the fittest?” or “How does co-operative behaviour arise in stochastic non-linear systems?”, which are relevant to a host of applied problems such as the emergence of drug resistance, cancer evolution, species invasions or the spread of epidemics. Answering these questions requires an understanding of how population-level phenomena, such as random genetic drift or natural selection, emerge from the stochastic behaviour of individuals and their interaction.  Thus, our research focuses on

• Understand how collective patterns of self-organization emerge from the joint actions of heterogeneous individuals. Studying evolutionary adaptation, random genetic drift, epidemic spreading, collective motion, synchronization and jamming. Although these phenomena occur in many complex systems, our experimental efforts are focused primarily on microbial systems that we can study in our wet lab.
• Our key theoretical challenge is to identify essential dynamical building blocks and to predict how these conspire to generate the complex dynamical patterns observed at the population level.

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