Metacommunity structure preserves genome diversity in the presence of gene-specific selective sweeps under moderate rates of horizontal gene transfer.

The horizontal transfer of genes is fundamental for the eco-evolutionary dynamics of microbial communities, such as oceanic plankton, soil, and the human microbiome. In the case of an acquired beneficial gene, classic population genetics would predict a genome-wide selective sweep, whereby the genome spreads clonally within the community and together with the beneficial gene, removing genome diversity. Instead, several sources of metagenomic data show the existence of "gene-specific sweeps", whereby a beneficial gene spreads across a bacterial community, maintaining genome diversity. Several hypotheses have been proposed to explain this process, including the decreasing gene flow between ecologically distant populations, frequency-dependent selection from linked deleterious allelles, and very high rates of horizontal gene transfer. Here, we propose an additional possible scenario grounded in eco-evolutionary principles. Specifically, we show by a mathematical model and simulations that a metacommunity where species can occupy multiple patches, acting together with a realistic (moderate) HGT rate, helps maintain genome diversity. Assuming a scenario of patches dominated by single species, our model predicts that diversity only decreases moderately upon the arrival of a new beneficial gene, and that losses in diversity can be quickly restored. We explore the generic behaviour of diversity as a function of three key parameters, frequency of insertion of new beneficial genes, migration rates and horizontal transfer rates.Our results provides a testable explanation for how diversity can be maintained by gene-specific sweeps even in the absence of high horizontal gene transfer rates.

Dynamics of Bacterial Chromosomes by Locus Tracking in Fluorescence Microscopy.

In the last two decades, it has been shown that bacterial chromosomes have remarkable spatial organization at various scales, and they display well-defined movements during the cell cycle, for example to reliably segregate daughter chromosomes. More recently, various labs have begun investigating also the short time dynamics (displacements during time intervals of 0.1 s-100 s), which should be related to the molecular structure. Probing these dynamics is analogous to "microrheology" approaches that have been applied successfully to study mechanical response of complex fluids. These studies of chromosome fluctuation dynamics have revealed differences of fluctuation amplitude across the chromosome, and different characters of motion depending on the time window of interest. Different fluctuation amplitudes have also been observed for the same chromosomal loci under antibiotic treatments, with magnitudes that are correlated to changes in intracellular density and thus crowding. We describe how to carry out tracking experiments of single loci and how to analyze locus motility. We point out the importance of considering in the analysis the number of GFP molecules per fluorescent locus, as well as the nature of the protein they are fused to, and also how to measure intracellular density.

Protein degradation sets the fraction of active ribosomes at vanishing growth.

Growing cells adopt common basic strategies to achieve optimal resource allocation under limited resource availability. Our current understanding of such "growth laws" neglects degradation, assuming that it occurs slowly compared to the cell cycle duration. Here we argue that this assumption cannot hold at slow growth, leading to important consequences. We propose a simple framework showing that at slow growth protein degradation is balanced by a fraction of "maintenance" ribosomes. Consequently, active ribosomes do not drop to zero at vanishing growth, but as growth rate diminishes, an increasing fraction of active ribosomes performs maintenance. Through a detailed analysis of compiled data, we show that the predictions of this model agree with data from E. coli and S. cerevisiae. Intriguingly, we also find that protein degradation increases at slow growth, which we interpret as a consequence of active waste management and/or recycling. Our results highlight protein turnover as an underrated factor for our understanding of growth laws across kingdoms.

Cytosolic Crowding Drives the Dynamics of Both Genome and Cytosol in Escherichia coli Challenged with Sub-lethal Antibiotic Treatments.

In contrast to their molecular mode of action, the system-level effect of antibiotics on cells is only beginning to be quantified. Molecular crowding is expected to be a relevant global regulator, which we explore here through the dynamic response phenotypes in Escherichia coli, at single-cell resolution, under sub-lethal regimes of different classes of clinically relevant antibiotics, acting at very different levels in the cell. We measure chromosomal mobility through tracking of fast (<15 s timescale) fluctuations of fluorescently tagged chromosomal loci, and we probe the fluidity of the cytoplasm by tracking cytosolic aggregates. Measuring cellular density, we show how the overall levels of macromolecular crowding affect both quantities, regardless of antibiotic-specific effects. The dominant trend is a strong correlation between the effects in different parts of the chromosome and between the chromosome and cytosol, supporting the concept of an overall global role of molecular crowding in cellular physiology.

Role of the nuclear membrane protein Emerin in front-rear polarity of the nucleus.

Cell polarity refers to the intrinsic asymmetry of cells, including the orientation of the cytoskeleton. It affects cell shape and structure as well as the distribution of proteins and organelles. In migratory cells, front-rear polarity is essential and dictates movement direction. While the link between the cytoskeleton and nucleus is well-studied, we aim to investigate if front-rear polarity can be transmitted to the nucleus. We show that the knock-down of emerin, an integral protein of the nuclear envelope, abolishes preferential localization of several nuclear proteins. We propose that the frontally biased localization of the endoplasmic reticulum, through which emerin reaches the nuclear envelope, is sufficient to generate its observed bias. In primary emerin-deficient myoblasts, its expression partially rescues the polarity of the nucleus. Our results demonstrate that front-rear cell polarity is transmitted to the nucleus and that emerin is an important determinant of nuclear polarity.

Adaptive mutability of colorectal cancers in response to targeted therapies.

The emergence of drug resistance limits the efficacy of targeted therapies in human tumors. The prevalent view is that resistance is a fait accompli: when treatment is initiated, cancers already contain drug-resistant mutant cells. Bacteria exposed to antibiotics transiently increase their mutation rates (adaptive mutability), thus improving the likelihood of survival. We investigated whether human colorectal cancer (CRC) cells likewise exploit adaptive mutability to evade therapeutic pressure. We found that epidermal growth factor receptor (EGFR)/BRAF inhibition down-regulates mismatch repair (MMR) and homologous recombination DNA-repair genes and concomitantly up-regulates error-prone polymerases in drug-tolerant (persister) cells. MMR proteins were also down-regulated in patient-derived xenografts and tumor specimens during therapy. EGFR/BRAF inhibition induced DNA damage, increased mutability, and triggered microsatellite instability. Thus, like unicellular organisms, tumor cells evade therapeutic pressures by enhancing mutability.

Zipf and Heaps laws from dependency structures in component systems.

Complex natural and technological systems can be considered, on a coarse-grained level, as assemblies of elementary components: for example, genomes as sets of genes or texts as sets of words. On one hand, the joint occurrence of components emerges from architectural and specific constraints in such systems. On the other hand, general regularities may unify different systems, such as the broadly studied Zipf and Heaps laws, respectively concerning the distribution of component frequencies and their number as a function of system size. Dependency structures (i.e., directed networks encoding the dependency relations between the components in a system) were proposed recently as a possible organizing principles underlying some of the regularities observed. However, the consequences of this assumption were explored only in binary component systems, where solely the presence or absence of components is considered, and multiple copies of the same component are not allowed. Here we consider a simple model that generates, from a given ensemble of dependency structures, a statistical ensemble of sets of components, allowing for components to appear with any multiplicity. Our model is a minimal extension that is memoryless and therefore accessible to analytical calculations. A mean-field analytical approach (analogous to the "Zipfian ensemble" in the linguistics literature) captures the relevant laws describing the component statistics as we show by comparison with numerical computations. In particular, we recover a power-law Zipf rank plot, with a set of core components, and a Heaps law displaying three consecutive regimes (linear, sublinear, and saturating) that we characterize quantitatively.

Cell-to-cell variability and robustness in S-phase duration from genome replication kinetics.

Genome replication, a key process for a cell, relies on stochastic initiation by replication origins, causing a variability of replication timing from cell to cell. While stochastic models of eukaryotic replication are widely available, the link between the key parameters and overall replication timing has not been addressed systematically. We use a combined analytical and computational approach to calculate how positions and strength of many origins lead to a given cell-to-cell variability of total duration of the replication of a large region, a chromosome or the entire genome. Specifically, the total replication timing can be framed as an extreme-value problem, since it is due to the last region that replicates in each cell. Our calculations identify two regimes based on the spread between characteristic completion times of all inter-origin regions of a genome. For widely different completion times, timing is set by the single specific region that is typically the last to replicate in all cells. Conversely, when the completion time of all regions are comparable, an extreme-value estimate shows that the cell-to-cell variability of genome replication timing has universal properties. Comparison with available data shows that the replication program of three yeast species falls in this extreme-value regime.

Contrasting evolutionary genome dynamics between domesticated and wild yeasts.

Structural rearrangements have long been recognized as an important source of genetic variation, with implications in phenotypic diversity and disease, yet their detailed evolutionary dynamics remain elusive. Here we use long-read sequencing to generate end-to-end genome assemblies for 12 strains representing major subpopulations of the partially domesticated yeast Saccharomyces cerevisiae and its wild relative Saccharomyces paradoxus. These population-level high-quality genomes with comprehensive annotation enable precise definition of chromosomal boundaries between cores and subtelomeres and a high-resolution view of evolutionary genome dynamics. In chromosomal cores, S. paradoxus shows faster accumulation of balanced rearrangements (inversions, reciprocal translocations and transpositions), whereas S. cerevisiae accumulates unbalanced rearrangements (novel insertions, deletions and duplications) more rapidly. In subtelomeres, both species show extensive interchromosomal reshuffling, with a higher tempo in S. cerevisiae. Such striking contrasts between wild and domesticated yeasts are likely to reflect the influence of human activities on structural genome evolution.

Relevant parameters in models of cell division control.

A recent burst of dynamic single-cell data makes it possible to characterize the stochastic dynamics of cell division control in bacteria. Different models were used to propose specific mechanisms, but the links between them are poorly explored. The lack of comparative studies makes it difficult to appreciate how well any particular mechanism is supported by the data. Here, we describe a simple and generic framework in which two common formalisms can be used interchangeably: (i) a continuous-time division process described by a hazard function and (ii) a discrete-time equation describing cell size across generations (where the unit of time is a cell cycle). In our framework, this second process is a discrete-time Langevin equation with simple physical analogues. By perturbative expansion around the mean initial size (or interdivision time), we show how this framework describes a wide range of division control mechanisms, including combinations of time and size control, as well as the constant added size mechanism recently found to capture several aspects of the cell division behavior of different bacteria. As we show by analytical estimates and numerical simulations, the available data are described precisely by the first-order approximation of this expansion, i.e., by a "linear response" regime for the correction of size fluctuations. Hence, a single dimensionless parameter defines the strength and action of the division control against cell-to-cell variability (quantified by a single "noise" parameter). However, the same strength of linear response may emerge from several mechanisms, which are distinguished only by higher-order terms in the perturbative expansion. Our analytical estimate of the sample size needed to distinguish between second-order effects shows that this value is close to but larger than the values of the current datasets. These results provide a unified framework for future studies and clarify the relevant parameters at play in the control of cell division.

Stochastic timing in gene expression for simple regulatory strategies.

Timing is essential for many cellular processes, from cellular responses to external stimuli to the cell cycle and circadian clocks. Many of these processes are based on gene expression. For example, an activated gene may be required to reach in a precise time a threshold level of expression that triggers a specific downstream process. However, gene expression is subject to stochastic fluctuations, naturally inducing an uncertainty in this threshold-crossing time with potential consequences on biological functions and phenotypes. Here, we consider such 'timing fluctuations' and we ask how they can be controlled. Our analytical estimates and simulations show that, for an induced gene, timing variability is minimal if the threshold level of expression is approximately half of the steady-state level. Timing fluctuations can be reduced by increasing the transcription rate, while they are insensitive to the translation rate. In presence of self-regulatory strategies, we show that self-repression reduces timing noise for threshold levels that have to be reached quickly, while self-activation is optimal at long times. These results lay a framework for understanding stochasticity of endogenous systems such as the cell cycle, as well as for the design of synthetic trigger circuits.

Bacterial Chromosome Dynamics by Locus Tracking in Fluorescence Microscopy.

Bacterial chromosomes have been shown in the last two decades to have remarkable spatial organization at various scales, and also well-defined movements during the cell cycle, for example, to reliably segregate daughter chromosomes. More recently, various labs have begun investigating the short-time dynamics (displacements during time intervals of 0.1-100 s), which one hopes to link to structure, in analogy to "microrheology" approaches applied successfully to study mechanical response of complex fluids. These studies of chromosome fluctuation dynamics have revealed differences of fluctuation amplitude across the chromosome, and different characters of motion depending on the time window of interest. The highly nontrivial motion at the shortest experimentally accessible times is still not fully understood in terms of physical models of DNA and cytosol. We describe how to carry out tracking experiments of single locus and how to analyze locus motility. We point out the importance of considering in the analysis the number of GFP molecules per fluorescent locus.

From structure to function of bacterial chromosomes: Evolutionary perspectives and ideas for new experiments.

The link between chromosome structure and function is a challenging open question because chromosomes in vivo are highly dynamic and arduous to manipulate. Here, we examine several promising approaches to tackle this question specifically in bacteria, by integrating knowledge from different sources. Toward this end, we first provide a brief overview of experimental tools that have provided insights into the description of the bacterial chromosome, including genetic, biochemical and fluorescence microscopy techniques. We then explore the possibility of using comparative genomics to isolate functionally important features of chromosome organization, exploiting the fact that features shared between phylogenetically distant bacterial species reflect functional significance. Finally, we discuss possible future perspectives from the field of experimental evolution. Specifically, we propose novel experiments in which bacteria could be screened and selected on the basis of the structural properties of their chromosomes.

Characterizing the size and shape of sea ice floes.

Monitoring drift ice in the Arctic and Antarctic regions directly and by remote sensing is important for the study of climate, but a unified modeling framework is lacking. Hence, interpretation of the data, as well as the decision of what to measure, represent a challenge for different fields of science. To address this point, we analyzed, using statistical physics tools, satellite images of sea ice from four different locations in both the northern and southern hemispheres, and measured the size and the elongation of ice floes (floating pieces of ice). We find that (i) floe size follows a distribution that can be characterized with good approximation by a single length scale , which we discuss in the framework of stochastic fragmentation models, and (ii) the deviation of their shape from circularity is reproduced with remarkable precision by a geometric model of coalescence by freezing, based on random Voronoi tessellations, with a single free parameter expressing the shape disorder. Although the physical interpretations remain open, this advocates the parameters and as two independent indicators of the environment in the polar regions, which are easily accessible by remote sensing.

The genome-scale interplay amongst xenogene silencing, stress response and chromosome architecture in Escherichia coli.

The gene expression state of exponentially growing Escherichia coli cells is manifested by high expression of essential and growth-associated genes and low levels of stress-related and horizontally acquired genes. An important player in maintaining this homeostasis is the H-NS-StpA gene silencing system. A Δhns-stpA deletion mutant results in high expression of otherwise-silent horizontally acquired genes, many located in the terminus-half of the chromosome, and an indirect downregulation of many highly expressed genes. The Δhns-stpA double mutant displays slow growth. Using laboratory evolution we address the evolutionary strategies that E. coli would adopt to redress this gene expression imbalance. We show that two global gene regulatory mutations-(i) point mutations inactivating the stress-responsive sigma factor RpoS or σ38 and (ii) an amplification of ∼40% of the chromosome centred around the origin of replication-converge in partially reversing the global gene expression imbalance caused by Δhns-stpA. Transcriptome data of these mutants further show a three-way link amongst the global gene regulatory networks of H-NS and σ38, as well as chromosome architecture. Increasing gene expression around the terminus of replication results in a decrease in the expression of genes around the origin and vice versa; this appears to be a persistent phenomenon observed as an association across ∼300 publicly-available gene expression data sets for E. coli. These global suppressor effects are transient and rapidly give way to more specific mutations, whose roles in reversing the growth defect of H-NS mutations remain to be understood.

Soft bounds on diffusion produce skewed distributions and Gompertz growth.

Constraints can affect dramatically the behavior of diffusion processes. Recently, we analyzed a natural and a technological system and reported that they perform diffusion-like discrete steps displaying a peculiar constraint, whereby the increments of the diffusing variable are subject to configuration-dependent bounds. This work explores theoretically some of the revealing landmarks of such phenomenology, termed "soft bound." At long times, the system reaches a steady state irreversibly (i.e., violating detailed balance), characterized by a skewed "shoulder" in the density distribution, and by a net local probability flux, which has entropic origin. The largest point in the support of the distribution follows a saturating dynamics, expressed by the Gompertz law, in line with empirical observations. Finally, we propose a generic allometric scaling for the origin of soft bounds. These findings shed light on the impact on a system of such "scaling" constraint and on its possible generating mechanisms.

Measuring bacterial adaptation dynamics at the single-cell level using a microfluidic chemostat and time-lapse fluorescence microscopy.

We monitored the dynamics of cell dimensions and reporter GFP expression in individual E. coli cells growing in a microfluidic chemostat using time-lapse fluorescence microscopy. This combination of techniques allows us to study the dynamical responses of single bacterial cells to nutritional shift-down or shift-up for longer times and with more precision over the chemical environment than similar experiments performed on conventional agar pads. We observed two E. coli strains containing different promoter-reporter gene constructs and measured how both their cell dimensions and the GFP expression change after nutritional upshift and downshift. As expected, both strains have similar adaptation dynamics for cell size rearrangement. However, the strain with a ribosomal RNA promoter dependent reporter has a faster GFP production rate than the strain with a constitutive promoter reporter. As a result, the mean GFP concentration in the former strain changes rapidly with the nutritional shift, while that in the latter strain remains relatively stable. These findings characterize the present microfluidic chemostat as a versatile platform for measuring single-cell bacterial dynamics and physiological transitions.

Persistent super-diffusive motion of Escherichia coli chromosomal loci.

The physical nature of the bacterial chromosome has important implications for its function. Using high-resolution dynamic tracking, we observe the existence of rare but ubiquitous 'rapid movements' of chromosomal loci exhibiting near-ballistic dynamics. This suggests that these movements are either driven by an active machinery or part of stress-relaxation mechanisms. Comparison with a null physical model for subdiffusive chromosomal dynamics shows that rapid movements are excursions from a basal subdiffusive dynamics, likely due to driven and/or stress-relaxation motion. Additionally, rapid movements are in some cases coupled with known transitions of chromosomal segregation. They do not co-occur strictly with replication, their frequency varies with growth condition and chromosomal coordinate, and they show a preference for longitudinal motion. These findings support an emerging picture of the bacterial chromosome as off-equilibrium active matter and help developing a correct physical model of its in vivo dynamic structure.

Bacterial nucleoid structure probed by active drag and resistive pulse sensing.

Recent biophysical approaches have provided key insights into the enthalpic and entropic forces that compact the nucleoid in the cell. Our biophysical approach combines two complementary, non-invasive and label-free techniques: a precisely timed steerable optical trap and a high throughput microcapillary Coulter counter. We demonstrate the ability of the latter technique to probe the physical properties and size of many purified nucleoids, at the individual nucleoid level. The DNA-binding protein H-NS is central to the organization of the bacterial genome. Our results show that nucleoids purified from the Δhns strain in the stationary phase expand approximately five fold more than the form observed in WT bacteria. This compaction is consistent with the role played by H-NS in regulating the nucleoid structure and the significant organizational changes that occur as the cell adapts to the stationary phase. We also study the permeability to the flow of ions and find that in the experiment nucleoids behave as solid colloids.

Growth-rate-dependent dynamics of a bacterial genetic oscillator.

Gene networks exhibiting oscillatory dynamics are widespread in biology. The minimal regulatory designs giving rise to oscillations have been implemented synthetically and studied by mathematical modeling. However, most of the available analyses generally neglect the coupling of regulatory circuits with the cellular "chassis" in which the circuits are embedded. For example, the intracellular macromolecular composition of fast-growing bacteria changes with growth rate. As a consequence, important parameters of gene expression, such as ribosome concentration or cell volume, are growth-rate dependent, ultimately coupling the dynamics of genetic circuits with cell physiology. This work addresses the effects of growth rate on the dynamics of a paradigmatic example of genetic oscillator, the repressilator. Making use of empirical growth-rate dependencies of parameters in bacteria, we show that the repressilator dynamics can switch between oscillations and convergence to a fixed point depending on the cellular state of growth, and thus on the nutrients it is fed. The physical support of the circuit (type of plasmid or gene positions on the chromosome) also plays an important role in determining the oscillation stability and the growth-rate dependence of period and amplitude. This analysis has potential application in the field of synthetic biology, and suggests that the coupling between endogenous genetic oscillators and cell physiology can have substantial consequences for their functionality.