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Lambert, A.

Publications and source records attributed to Lambert, A..

42 records · Page 3Linked to original sources

Population persistence under high mutation rate: from evolutionary rescue to lethal mutagenesis

Populations may genetically adapt to severe stress that would otherwise cause their extirpation. Recent theoretical work, combining stochastic demography with Fishers geometric model of adaptation, has shown how evolutionary rescue becomes unlikely beyond some critical intensity of stress. Increasing mutation rates may however allow adaptation to more intense stress, raising concerns about the effectiveness of treatments against pathogens. This previous work assumes that populations are rescued by the rise of a single resistance mutation. However, even in asexual organisms, rescue can also stem from the accumulation of multiple mutations in a single genome. Here, we extend previous work to study the rescue process in an asexual population where the mutation rate is sufficiently high so that such events may be common. We predict both the ultimate extinction probability of the population and the distribution of extinction times. We compare the accuracy of different approximations covering a large range of mutation rates. Moderate increase in mutation rates favors evolutionary rescue. However, larger increase leads to extinction by the accumulation of a large mutation load, a process called lethal mutagenesis. We discuss how these results could help design \"evolution-proof\" anti-pathogen treatments that even highly mutable strains could not overcome.

evolutionary biology↗

Modeling Edar expression reveals the hidden dynamics of tooth signaling center patterning

The generation of patterns during development is generally viewed as a direct process. In the mouse jaw, however, the sequential patterning of molars initiates with abortive tooth signaling centers called MS and R2, thought to be vestiges of the lost rodent premolars. Moreover, the mature signaling center of the first molar (M1) is formed from the fusion of two signaling centers (R2 and early M1). Here, we report that Edar expression reveals the hidden dynamics of signalling centers patterning. First, Edar expression evidenced a hidden two-step patterning process that we modelled with a single activator-inhibitor pair: the epithelium is initially broadly activated, then activation becomes restricted in space to give rise to the signalling centers. Second, Edar expression unveils successive phases of pattern making and pattern erasing events, a phenomenon that we called a developmental palimpsest. MS is erased by a broad activation for the benefit of R2, which itself is erased before it recovers when the first molar signaling center forms. In the lower but not the upper jaw, the two neighboring signaling centers then fuse into a single elongated center. Our model recapitulated the erasure of the R2 signaling center by the wave of activation that precedes the formation of M1 signaling center, and predicted the surprising rescue of R2 in the context of an Edar mutant with reduced activation. It suggested that R2 was not intrinsically defective, but actively outcompeted by M1 formation. We confirmed this by cultivating R2 separately from the posterior tissue and showing it could then generate a tooth. Finally, by introducing chemotaxis as a secondary process of tooth germ maturation, we recapitulated the fusion of R2 and M1 in the lower jaw only, and the loss of fusion when Edar function is impaired in organ cultures. In conclusion, we have uncovered a highly indirect and dynamic nature of pattern formation in the molar field that could nevertheless be simulated with simple mathematical models. Our study argues for viewing embryonic patterns as dynamical objects rather than as fixed endpoints, where dynamics is essential to the outcome of the patterning process.

developmental biology↗

The genomic view of diversification

AO_SCPLOWBSTRACTC_SCPLOWEvolutionary relationships between species are traditionally represented in the form of a tree, the species tree. Its reconstruction from molecular data is hindered by frequent conflicts between gene genealogies. Usually, these disagreements are explained by incomplete lineage sorting (ILS) due to random coalescences of gene lineages inside the edges of the species tree. This paradigm, the multi-species coalescent (MSC), is constantly violated by the ubiquitous presence of gene flow, leading to incongruences between gene trees that cannot be explained by ILS alone. Here we argue instead in favor of a vision acknowledging the importance of gene flow and where gene histories shape the species tree rather than the opposite. We propose a new framework for modeling the joint evolution of gene and species lineages relaxing the hierarchy between the species tree and gene trees. We implement this framework in two mathematical models called the gene-based diversification models (GBD): 1) GBD-forward following all evolving genomes and 2) GBD-backward based on coalescent theory. They feature four parameters tuning colonization, gene flow, genetic drift and genetic differentiation. We propose a quick inference method based on differences between gene trees. Applied to two empirical data-sets prone to gene flow, we find a better support for the GBD model than for the MSC model. Along with the increasing awareness of the extent of gene flow, this work shows the importance of considering the richer signal contained in genomic histories, rather than in the mere species tree, to better apprehend the complex evolutionary history of species.

evolutionary biology↗

Constriction rate modulation can drive cell size control and homeostasis in C. crescentus

Rod-shaped bacteria typically grow first via sporadic and dispersed elongation along their lateral walls, then via a combination of zonal elongation and constriction at the division site to form the poles of daughter cells. Although constriction comprises up to half of the cell cycle, its impact on cell size control and homeostasis has rarely been considered. To reveal the roles of cell elongation and constriction in bacterial size regulation during cell division, we captured the shape dynamics of Caulobacter crescentus with time-lapse structured illumination microscopy and used molecular markers as cell-cycle landmarks. We perturbed constriction rate using a hyperconstriction mutant or fosfomycin inhibition. We report that constriction rate contributes to both size control and homeostasis, by determining elongation during constriction, and by compensating for variation in pre-constriction elongation on a single-cell basis.

biophysics↗

Pathogen evolution: slow and steady spreads the best

The theory of life history evolution provides a powerful framework to understand the evolutionary dynamics of pathogens in both epidemic and endemic situations. This framework, however, relies on the assumption that pathogen populations are very large and that one can neglect the effects of demographic stochasticity. Here we expand the theory of life history evolution to account for the effects of finite population size on the evolution of pathogen virulence. We show that demographic stochasticity introduces additional evolutionary forces that can qualitatively affect the dynamics and the evolutionary outcome. We discuss the importance of the shape of pathogen fitness landscape and host heterogeneity on the balance between mutation, selection and genetic drift. In particular, we discuss scenarios where finite population size can dramatically affect classical predictions of deterministic models. This analysis reconciles Adaptive Dynamics with population genetics in finite populations and thus provides a new theoretical toolbox to study life-history evolution in realistic ecological scenarios.

evolutionary biology↗

Ranked tree shapes, non-random extinctions and the loss of phylogenetic diversity

Phylogenetic diversity (PD) is a measure of the evolutionary legacy of a group of species, which can be used to define conservation priorities. It has been shown that an important loss of species diversity can sometimes lead to a much less important loss of PD, depending on the topology of the species tree and on the distribution of its branch lengths. However, the rate of decrease of PD strongly depends on the relative depths of the nodes in the tree and on the order in which species become extinct. We introduce a new, sampling-consistent, three-parameter model generating random trees with covarying topology, clade relative depths and clade relative extinction risks. This model can be seen as an extension to Aldous one parameter splitting model {beta}, which controls for tree balance) with two additional parameters: a new parameter quantifying the correlation between the richness of a clade and its relative depth, and a parameter{eta} quantifying the correlation between the richness of a clade and its frequency (relative abundance or range), taken herein as a proxy for its overall extinction risk. We show on simulated phylogenies that loss of PD depends on the combined effect of all three parameters, {beta}, and{eta} . In particular, PD may decrease as fast as species diversity when high extinction risks are clustered within small, old clades, corresponding to a parameter range that we term the thin ice zone ({beta} < -1 or < 0;{eta} > 1). Besides, when high extinction risks are clustered within large clades, the loss of PD can be higher in trees that are more balanced ({beta} > 0), in contrast to the predictions of earlier studies based on simpler models. We propose a Monte-Carlo algorithm, tested on simulated data, to infer all three parameters. Applying it to a real dataset comprising 120 bird clades (class Aves) with known range sizes, we show that parameter estimates precisely fall close to close to a thin ice zone: the combination of their ranking tree shape and non-random extinctions risks makes them prone to a sudden collapse of PD.

evolutionary biology↗