laboratoire de physique statistique
laboratoire de physique statistique


Bistability in a Metabolic Network Underpins the De Novo Evolution of Colony Switching in Pseudomonas fluorescens - Gallie, Jenna and Libby, Eric and Bertels, Frederic and Remigi, Philippe and Jendresen, Christian B. and Ferguson, Gayle C. and Desprat, Nicolas and Buffing, Marieke F. and Sauer, Uwe and Beaumont, Hubertus J. E. and Martinussen, Jan and Kilstrup, Mogens and Rainey, Paul B.
PLOS BIOLOGY 13 (2015) 

Abstract : Phenotype switching is commonly observed in nature. This prevalence has allowed the elucidation of a number of underlying molecular mechanisms. However, little is known about how phenotypic switches arise and function in their early evolutionary stages. The first opportunity to provide empirical insight was delivered by an experiment in which populations of the bacterium Pseudomonas fluorescens SBW25 evolved, de novo, the ability to switch between two colony phenotypes. Here we unravel the molecular mechanism behind colony switching, revealing how a single nucleotide change in a gene enmeshed in central metabolism (carB) generates such a striking phenotype. We show that colony switching is underpinned by ON/OFF expression of capsules consisting of a colanic acid-like polymer. We use molecular genetics, biochemical analyses, and experimental evolution to establish that capsule switching results from perturbation of the pyrimidine biosynthetic pathway. Of central importance is a bifurcation point at which uracil triphosphate is partitioned towards either nucleotide metabolism or polymer production. This bifurcation marks a cell-fate decision point whereby cells with relatively high pyrimidine levels favour nucleotide metabolism (capsule OFF), while cells with lower pyrimidine levels divert resources towards polymer biosynthesis (capsule ON). This decision point is present and functional in the wild-type strain. Finally, we present a simple mathematical model demonstrating that the molecular components of the decision point are capable of producing switching. Despite its simple mutational cause, the connection between genotype and phenotype is complex and multidimensional, offering a rare glimpse of how noise in regulatory networks can provide opportunity for evolution.
Inferring epigenetic dynamics from kin correlations - Hormoz, Sahand and Desprat, Nicolas and Shraiman, Boris I.

Abstract : Populations of isogenic embryonic stem cells or clonal bacteria often exhibit extensive phenotypic heterogeneity that arises from intrinsic stochastic dynamics of cells. The phenotypic state of a cell can be transmitted epigenetically in cell division, leading to correlations in the states of cells related by descent. The extent of these correlations is determined by the rates of transitions between the phenotypic states. Therefore, a snapshot of the phenotypes of a collection of cells with known genealogical structure contains information on phenotypic dynamics. Here, we use a model of phenotypic dynamics on a genealogical tree to define an inference method that allows extraction of an approximate probabilistic description of the dynamics from observed phenotype correlations as a function of the degree of kinship. The approach is tested and validated on the example of Pyoverdine dynamics in Pseudomonas aeruginosa colonies. Interestingly, we find that correlations among pairs and triples of distant relatives have a simple but nontrivial structure indicating that observed phenotypic dynamics on the genealogical tree is approximately conformal-a symmetry characteristic of critical behavior in physical systems. The proposed inference method is sufficiently general to be applied in any system where lineage information is available.
Microbes are not bound by sociobiology: Response to Kummerli and Ross-Gillespie (2013) - Rainey, Paul B. and Desprat, Nicolas and Driscoll, William W. and Zhang, Xue-Xian
EVOLUTION 683344-3355 (2014) 

Abstract : In recent years, sociobiology has been extended to microorganisms. Viewed through this lens, the microbial world is replete with cooperative behaviors. However, little attention has been paid to alternate hypotheses, making many studies self-confirming. Somewhat apart is a recent analysis of pyoverdin production-a paradigmatic public good and social trait-by Pseudomonas, which has revealed discord between predictions arising from sociobiology and the biology of microbes. This led the authors, Zhang and Rainey (Z\&R), to question the generality of the conclusion that pyoverdin is a social trait, and to question the fit between the sociobiology framework and microbiology. This has unsettled Kummerli and Ross-Gillespie (K\&R), who in a recent ``Technical Comment'' assert that arguments presented by Z\&R are flawed, their experiments technically mistaken, and their understanding of social evolution theory naive. We demonstrate these claims to be without substance and show the conclusions of K\&R to be based on a lack of understanding of redox chemistry and on misinterpretation of data. We also point to evidence of cherry-picking and raise the possibility of confirmation bias. Finally, we emphasize that the sociobiology framework applied to microbes is a hypothesis that requires rigorous and careful appraisal.
Cell-cell contacts confine public goods diffusion inside Pseudomonas aeruginosa clonal microcolonies - Julou, Thomas and Mora, Thierry and Guillon, Laurent and Croquette, Vincent and Schalk, Isabelle J. and Bensimon, David and Desprat, Nicolas

Abstract : The maintenance of cooperation in populations where public goods are equally accessible to all but inflict a fitness cost on individual producers is a long-standing puzzle of evolutionary biology. An example of such a scenario is the secretion of siderophores by bacteria into their environment to fetch soluble iron. In a planktonic culture, these molecules diffuse rapidly, such that the same concentration is experienced by all bacteria. However, on solid substrates, bacteria form dense and packed colonies that may alter the diffusion dynamics through cell-cell contact interactions. In Pseudomonas aeruginosa microcolonies growing on solid substrate, we found that the concentration of pyoverdine, a secreted iron chelator, is heterogeneous, with a maximum at the center of the colony. We quantitatively explain the formation of this gradient by local exchange between contacting cells rather than by global diffusion of pyoverdine. In addition, we show that this local trafficking modulates the growth rate of individual cells. Taken together, these data provide a physical basis that explains the stability of public goods production in packed colonies.
Monitoring microbial population dynamics at low densities - Julou, Thomas and Desprat, Nicolas and Bensimon, David and Croquette, Vincent

Abstract : We propose a new and simple method for the measurement of microbial concentrations in highly diluted cultures. This method is based on an analysis of the intensity fluctuations of light scattered by microbial cells under laser illumination. Two possible measurement strategies are identified and compared using simulations and measurements of the concentration of gold nanoparticles. Based on this comparison, we show that the concentration of Escherichia coli and Saccharomyces cerevisiae cultures can be easily measured in situ across a concentration range that spans five orders of magnitude. The lowest measurable concentration is three orders of magnitude (1000x) smaller than in current optical density measurements. We show further that this method can also be used to measure the concentration of fluorescent microbial cells. In practice, this new method is well suited to monitor the dynamics of population growth at early colonization of a liquid culture medium. The dynamic data thus obtained are particularly relevant for microbial ecology studies. (C) 2012 American Institute of Physics. []
Some nonlinear challenges in biology - Mosconi, Francesco and Julou, Thomas and Desprat, Nicolas and Sinha, Deepak Kumar and Allemand, Jean-Francois and Croquette, Vincent and Bensimon, David
NONLINEARITY 21T131-T147 (2008) 

Abstract : Driven by a deluge of data, biology is undergoing a transition to a more quantitative science. Making sense of the data, building new models, asking the right questions and designing smart experiments to answer them are becoming ever more relevant. In this endeavour, nonlinear approaches can play a fundamental role. The biochemical reactions that underlie life are very often nonlinear. The functional features exhibited by biological systems at all levels (from the activity of an enzyme to the organization of a colony of ants, via the development of an organism or a functional module like the one responsible for chemotaxis in bacteria) are dynamically robust. They are often unaffected by order of magnitude variations in the dynamical parameters, in the number or concentrations of actors (molecules, cells, organisms) or external inputs (food, temperature, pH, etc). This type of structural robustness is also a common feature of nonlinear systems, exemplified by the fundamental role played by dynamical fixed points and attractors and by the use of generic equations (logistic map, Fisher-Kolmogorov equation, the Stefan problem, etc.) in the study of a plethora of nonlinear phenomena. However, biological systems differ from these examples in two important ways: the intrinsic stochasticity arising from the often very small number of actors and the role played by evolution. On an evolutionary time scale, nothing in biology is frozen. The systems observed today have evolved from solutions adopted in the past and they will have to adapt in response to future conditions. The evolvability of biological system uniquely characterizes them and is central to biology. As the great biologist T Dobzhansky once wrote: `nothing in biology makes sense except in the light of evolution'.