Exploration-exploitation tradeoffs dictate the optimal distributions of phenotypes for populations subject to fitness fluctuations

We study a minimal model for the growth of a phenotypically heterogeneous population of cells subject to a fluctuating environment in which they can replicate (by exploiting available resources) and modify their phenotype within a given landscape (thereby exploring novel configurations). The model displays an exploration-exploitation trade-off whose specifics depend on the statistics of the environment. Most notably, the phenotypic distribution corresponding to maximum population fitness (i.e. growth rate) requires a non-zero exploration rate when the magnitude of environmental fluctuations changes randomly over time, while a purely exploitative strategy turns out to be optimal in two-state environments, independently of the statistics of switching times. We obtain analytical insight into the limiting cases of very fast and very slow exploration rates by directly linking population growth to the features of the environment.Comment: 13 pages, 5 figure

Phenotypic Variation and Bistable Switching in Bacteria

Microbial research generally focuses on clonal populations. However, bacterial cells with identical genotypes frequently display different phenotypes under identical conditions. This microbial cell individuality is receiving increasing attention in the literature because of its impact on cellular differentiation, survival under selective conditions, and the interaction of pathogens with their hosts. It is becoming clear that stochasticity in gene expression in conjunction with the architecture of the gene network that underlies the cellular processes can generate phenotypic variation. An important regulatory mechanism is the so-called positive feedback, in which a system reinforces its own response, for instance by stimulating the production of an activator. Bistability is an interesting and relevant phenomenon, in which two distinct subpopulations of cells showing discrete levels of gene expression coexist in a single culture. In this chapter, we address techniques and approaches used to establish phenotypic variation, and relate three well-characterized examples of bistability to the molecular mechanisms that govern these processes, with a focus on positive feedback.

Genome-Scale Oscillations in DNA Methylation during Exit from Pluripotency

Pluripotency is accompanied by the erasure of parental epigenetic memory, with naive pluripotent cells exhibiting global DNA hypomethylation both in vitro and in vivo. Exit from pluripotency and priming for differentiation into somatic lineages is associated with genome-wide de novo DNA methylation. We show that during this phase, co-expression of enzymes required for DNA methylation turnover, DNMT3s and TETs, promotes cell-to-cell variability in this epigenetic mark. Using a combination of single- cell sequencing and quantitative biophysical modeling, we show that this variability is associated with coherent, genome-scale oscillations in DNA methylation with an amplitude dependent on CpG density. Analysis of parallel single-cell transcriptional and epigenetic profiling provides evidence for oscillatory dynamics both in vitro and in vivo. These observations provide insights into the emergence of epigenetic heterogeneity during early embryo development, indicating that dynamic changes in DNA methylation might influence early cell fate decisions

Network properties of the mammalian circadian clock

The biological clock regulates daily and seasonal rhythms in mammals. This clock is located in the suprachiasmatic nuclei (SCN), which are two small nuclei each consisting of 10,000 neurons. The neurons of the SCN endogenously generate a rhythm of approximately 24 hours. Under the influence of the light-dark cycle, the SCN produce a coordinated output that is subjected to daily environmental changes. The adaptation to the light-dark cycle is a property of the neuronal network of the SCN. This neuronal network also explains the adjustment to long summer days and short winter days, and to shifts in the light-dark cycle caused by transatlantic flights or shift work. In this thesis the neuronal network of the SCN is investigated using computational techniques. The computer simulations were directed by experimental results, while, vice versa, new experiments were guided by results from the simulations. These coordinated efforts of computational science and life sciences show how properties emerge at the neuronal network level, that are not present in individual cells.NWO, program grant nr 805.47.212 ‘From Molecule to Cell’ and ASCI graduate schoolUBL - phd migration 201

Noise Expands the Response Range of the Bacillus subtilis Competence Circuit

Gene regulatory circuits must contend with intrinsic noise that arises due to finite numbers of proteins. While some circuits act to reduce this noise, others appear to exploit it. A striking example is the competence circuit in Bacillus subtilis, which exhibits much larger noise in the duration of its competence events than a synthetically constructed analog that performs the same function. Here, using stochastic modeling and fluorescence microscopy, we show that this larger noise allows cells to exit terminal phenotypic states, which expands the range of stress levels to which cells are responsive and leads to phenotypic heterogeneity at the population level. This is an important example of how noise confers a functional benefit in a genetic decision-making circuit

Gene switching rate determines response to extrinsic perturbations in the self-activation transcriptional network motif

International audienc

Heterogeneity and noise in living systems: statistical physics perspectives

Even the most distracted observer could hardly miss noticing the extensive heterogeneity of traits and behaviors displayed by living systems. So great a variability is commonly ascribed to differences at the level of the genome, which originated from the evolution process to adapt the organisms to the different environments they live in. However, phenotypic heterogeneity is found even in genetically identical organisms, from monoclonal cellular populations to human twins. The multitude of microscopic causes that sum up to give such variability is commonly referred to as biological noise, coming both in the form of environmental fluctuations affecting the development of individual organisms (extrinsic noise) and as the unavoidable results of stochasticity at the level of molecular reaction (intrinsic noise). The latter persisting even when genetically identical organisms are kept under nearly identical conditions. For quite a long time, such fluctuations were considered a nuisance that makes experiments just difficult to interpret, needing to enlarge the number of observations to have reliable outcomes, and from the point of view of cells, a disturbance cells need to deal with. In the last two decades, however, experimental progresses allowed to investigate the system at single-cell scale. The emerging view is that noise under some circumstances can have a beneficial role, like promoting survival to adverse environments or enhancing differentiation. Ultimately, evolution tunes the systems so they can take advantage of natural stochastic fluctuations. We will follow noise and fluctuation from the cellular level to the higher level of organization of the cellular population where heterogeneity in the molecular reactions translate in the variability of phenotypes. Biology is very broad though, and noise affects all biological processes. Time restraint and my limited knowledge of biological systems did not allow for an exhaustive discussion of all the aspects in which noise and the subsequent heterogeneity play a role. Instead, we will focus on the regulation of noise. More in details, the first part of the thesis introduces to the impact of noise on gene expression and the regulation mechanisms cells use to control it. The action of large regulatory networks is to coordinate a huge of number molecular interactions to obtain robust system-level outcomes. This capability can emerge even when individual interactions are weak and/or strongly heterogeneous. This is the case of post-transcriptional regulation driven by microRNAs (miRNAs). microRNAs are small non-coding RNA molecules able to regulate gene expression at the post-transcriptional level by repressing target RNA molecules. It has been found that such regulation may lead the system to bimodal distributions in the expression of the target mRNA, usually fingerprint of the presence of two distinct phenotypes. Moreover, the nature of the interaction between miRNAs and their targets gives rise to a complex network of miRNAs interacting with several mRNA targets. Such targets may then cross-regulate each other in an indirect miRNA-mediated manner. This effect, called `competing endogenous RNA (ceRNA) effect', despite being typically weak, has been found to possess remarkable properties in the presence of extrinsic noise, where fluctuations affect all the components of the system. We will discuss crosstalk and illustrate how crosstalk patterns are enhanced by both transcriptional and kinetic heterogeneities and achieve high intensities even for RNAs that are not co-regulated. Moreover, we will see that crosstalk patterns are significantly non-local, i.e. correlate weakly with miRNA-RNA interaction parameters. Since these features appear to be encoded in the network's topology this suggests that such crosstalk is tunable by natural selection. Moving at the cellular level, we focus on the outcomes of gene expression, i.e. the observable phenotypes. Depending on the degree of regulation the cell manages to exert with respect to noise, the distribution of those phenotypes will display a certain extent of heterogeneity. Such cell-to-cell variability is found to have many implications especially for the growth of the whole population. In the second part of the thesis, we discuss some properties of those heterogeneous distributions. First, we focus on the dependence on the initial conditions for the different phases of growth, i.e. the adaptive phase and exponential growth phase. Since cellular populations grow in an exponential fashion, the size and composition of the inoculum shall matter. We discuss this following a novel extensive experimental investigation recently done on cancer cell lines in a controlled environment. Finally, we focus on the effects that a heterogeneous phenotype has on the growth in hostile environments, i.e. environments fluctuating between states in which the growth is favored and others where growth is inhibited. In such a case, if cells can only replicate (by exploiting available resources) and modify their phenotype within a given landscape (thereby exploring novel configurations), an exploration-exploitation trade-off is established, whose specifics depend on the statistics of the environment. The phenotypic distribution corresponding to maximum population fitness requires a non-zero exploration rate when the magnitude of environmental fluctuations changes randomly over time, while a purely exploitative strategy turns out to be optimal in periodic two-state environments. Most notably, the key parameter overseeing the trade-off is linked to the amount of regulation cells can exert