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Adapting to Change: Experimental Evolution of Environmental Sensing Systems in Bacteria

Periodic Reporting for period 1 - ESSEVOL (Adapting to Change: Experimental Evolution of Environmental Sensing Systems in Bacteria)

Reporting period: 2017-12-01 to 2019-11-30

Understanding how life copes with ever-changing conditions has intrigued biologists for decades, and it is currently in the spotlight due to global climate change. One solution that organisms have adopted repeatedly is the evolution of systems that allow them to sense and respond to their surroundings. Environmental sensing systems (ESS) can exhibit high degrees of complexity and are pervasive throughout the Tree of Life – a testimony of their evolutionary success. While theory has identified a range of conditions that promote the emergence of ESS, empirical tests are scarce, largely due to the practical difficulties of observing these processes in real time. Here, we addressed this challenge by taking an laboratory evolution approach, in which we exposed bacteria for hundreds of generations to fluctuating selection for and against motility, a readily tractable behaviour that allows bacteria to find favourable growth conditions and move away from bad ones. The experiments show that bacterial populations are able to evolve a variety of adaptive strategies in response to fluctuating conditions, including the emergence of specialists (non-motile and extra-motile) and generalists (intermediate-motile and conditionally-motile). These observations match the theoretical predictions, but only qualitatively. Indeed, the explosion of diversity is well captured by simple theoretical models. However, conditionally-motile phenotypes (that is, mutants with novel ESS) are expected to dominate this scenario, while in reality they only were found at very low frequencies. Further analyses explained this discrepancy as due to the fact that behaviour-altering mutations are typically of small effect and can be costly in non-selective environments. In other words, while many mutational paths towards conditionally-motile phenotypes may exist, only a few of them can be easily trodden. These insights advance our understanding of both the constraints and facilitators of behavioural evolution in bacteria, contributing to a knowledge base that may help in the design of anti-virulence drugs and microbe-based biosensors and bioreporters.
We first run preliminary tests to find experimental conditions that promoted or penalised bacterial motility. Once these conditions were set, we conducted competition experiments with fluorescently-labelled, motile and non-motile bacteria in the different environments, which produced empirical estimates for the fitness, generation times and maximal population sizes of the different competitors. These estimates allowed us to build a computer model mimicking our experimental setting so that we could generate predictions on the evolution of novel behaviours that can be tested in the laboratory. Next, these predictions were tested by propagating thirty parallel experimental populations alternating between motility-promoting and motility-penalising conditions. After several weeks of evolution, single colonies were isolated, their behaviour classified, and their numbers were compared with the theoretical predictions. Some discrepancies between simulations and experimental data made us rethink our original assumptions, which lead us to propose new hypothesis that were again subjected to experimental tests. In particular, we conducted a new set of experiments to assess the number of mutational steps and possible trade-offs involved in the rewiring of the regulatory networks controlling motility. These experiments revealed that many mutational paths towards conditionally-motile phenotypes indeed exist, but also that only a few of them can be easily trodden. To gain a detailed picture of the molecular underpinnings of these mutational pathways, a collection of end-point isolates from the evolution experiments were subjected to whole-genome sequencing. In terms of dissemination, while peer-review journal articles are still in preparation, other activities have been undertaken to communicate aspects of the action to academic and non-academic beneficiaries, including scientists directly studying the evolution of environmental sensing (e.g. publication of the code in GitHub), researchers more broadly interested in evolutionary biology (e.g. speaking at major international conferences) and the general public (e.g. press interviews). Finally, over the lifetime of the action, the Fellow has engaged in activities complementary to research such as teaching, supervising and grant writing; highly-valuable assets towards a successful career as a independent researcher.
This project has produced much-needed insights into how the interplay between ecological and molecular constraints shape the evolution of plastic responses to environmental fluctuations. While this topic had received much attention over the decades, this project went beyond the state of the art in that it combined experimental with theoretical approaches in a single work, hence being in a unique position to distinguish general from idiosyncratic processes and mechanisms. Our results not only advance our mechanistic understanding of how just a handful of mutations can give rise to complex phenotypes such as the ability to sense and respond to the environment, but also provides a tractable model system that can be readily expandable to query about the vast diversity of environmental sensing systems found across microbes. On the applied side, this work will inform current models of how populations respond to sustained environmental degradation, a classical question and a highly topical issue in conservation biology given the current rate of global climate change. In addition, it advances our knowledge about the evolutionary flexibility of bacterial motility signalling networks, considered a promising target for both biotechnological applications (e.g. biosensors and bioreporters) and antimicrobial therapy (e.g. anti-virulence drugs).
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