Genealogical structure changes as range expansions transition from pushed to pulled

Range expansions accelerate evolution through multiple mechanisms, including gene surfing and genetic drift. The inference and control of these evolutionary processes ultimately rely on the information contained in genealogical trees. Currently, there are two opposing views on how range expansions shape genealogies. In invasion biology, expansions are typically approximated by a series of population bottlenecks producing genealogies with only pairwise mergers between lineages—a process known as the Kingman coalescent. Conversely, traveling wave models predict a coalescent with multiple mergers, known as the Bolthausen–Sznitman coalescent. Here, we unify these two approaches and show that expansions can generate an entire spectrum of coalescent topologies. Specifically, we show that tree topology is controlled by growth dynamics at the front and exhibits large differences between pulled and pushed expansions. These differences are explained by the fluctuations in the total number of descendants left by the early founders. High growth cooperativity leads to a narrow distribution of reproductive values and the Kingman coalescent. Conversely, low growth cooperativity results in a broad distribution, whose exponent controls the merger sizes in the genealogies. These broad distribution and non-Kingman tree topologies emerge due to the fluctuations in the front shape and position and do not occur in quasi-deterministic simulations. Overall, our results show that range expansions provide a robust mechanism for generating different types of multiple mergers, which could be similar to those observed in populations with strong selection or high fecundity. Thus, caution should be exercised in making inferences about the origin of non-Kingman genealogies.

Interplay between meropenem and human serum albumin on expression of carbapenem resistance genes and natural competence in Acinetobacter baumannii

Acinetobacter baumannii A118, a mostly susceptible strain and AB5075, carbapenem-resistant, were cultured in Lysogeny broth (LB) or LB with different supplements: 3.5% human serum albumin (HSA), human serum (HS), meropenem, or meropenem plus 3.5% HSA. Natural transformation levels were enhanced in A. baumannii A118 and AB5075 cultured in medium supplemented with 3.5% HSA. Addition of meropenem plus 3.5% HSA caused synergistic enhancement of natural transformation in A. baumannii A118. Medium containing 3.5% HSA or meropenem enhanced the expression levels of the competence and type IV pilus associated genes. The combination meropenem plus 3.5% HSA produced a synergistic enhancement in the expression levels of many of these genes. The addition of HS, which has a high content of HSA, was also an inducer of these genes. Cultures grown in medium supplemented with HS or 3.5% HSA also affected resistance genes, which were expressed at higher or lower levels depending on the modification required to enhance resistance. The inducing or repressing activity of these modulators also occurred in three more carbapenem-resistant strains tested. An exception was the A. baumannii AMA16 bla NDM-1 gene, which was repressed in the presence of 3.5% HSA. In conclusion, HSA produces an enhancement of natural transformation and a modification in expression levels of competence genes and antibiotic resistance. Furthermore, when HSA is combined with carbapenems, which may increase the stress response, the expression of genes involved in natural competence is increased in A. baumannii . This process may favor the acquisition of foreign DNA and accelerate evolution. Importance Acinetobacter baumannii causes a variety of nosocomial- and community-infections that are usually resistant to multiple antimicrobial agents. As new strains acquire more resistance genes, these infections become more difficult to treat and mortality can reach up to 39%. The high genomic plasticity exhibited by A. baumannii must be the consequence of numerous mechanisms that include acquiring foreign DNA and recombination. Here, we describe the ability of A. baumannii to induce competence genes when exposed to environments that resemble those found in the human body during untreated infection or after administration of carbapenems. In this latter scenario expression of genes related to resistance also modify their expression levels such that resistance is increased. The contributions of this article are two-fold. Firstly, when A. baumannii is exposed to products present during infection, it responds, augmenting the ability to capture DNA and accelerate evolution. Secondly, in those conditions, the bacterium also modifies the expression of resistance genes to increase its resistance levels. In summary, recognition of substances that are naturally (e.g., HSA) or artificially (treatment with carbapenems) induces A. baumannii to enhance expression of resistance determinants and genes regulating competence.

SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection

SARS-CoV-2 spillback from humans into domestic and wild animals has been well-documented. We compared variants of cell culture-expanded SARS-CoV-2 inoculum and virus recovered from four species following experimental exposure. Five nonsynonymous changes in nsp12, S, N and M genes were near fixation in the inoculum, but reverted to wild-type sequences in RNA recovered from dogs, cats and hamsters within 1-3 days post-exposure. Fourteen emergent variants were detected in viruses recovered from animals, including substitutions at spike positions H69, N501, and D614, which also vary in human lineages of concern. The rapidity of in vitro and in vivo SARS-CoV-2 selection reveals residues with functional significance during host-switching, illustrating the potential for spillback reservoir hosts to accelerate evolution, and demonstrating plasticity of viral adaptation in animal models.One-Sentence SummarySARS-CoV-2 variants rapidly arise in non-human hosts, revealing viral evolution and potential risk for human reinfection.

Spatiotemporal manipulation of the mismatch repair system of Pseudomonas putida accelerates phenotype emergence

ABSTRACTDeveloping complex phenotypes in industrially-relevant bacteria is a major goal of metabolic engineering, which encompasses the implementation of both rational and random approaches. In the latter case, several tools have been developed towards increasing mutation frequencies—yet the precise spatiotemporal control of mutagenesis processes continues to represent a significant technical challenge. Pseudomonas species are endowed with one of the most efficient DNA mismatch repair (MMR) systems found in bacteria. Here, we investigated if the endogenous MMR system could be manipulated as a general strategy to artificially alter mutation rates in Pseudomonas species. To bestow a conditional mutator phenotype in the platform bacterium Pseudomonas putida, we constructed inducible mutator devices to modulate the expression of the dominant-negative mutLE36K allele. Regulatable overexpression of mutLE36K in a broad-host-range, easy-to-cure plasmid format resulted in a transitory inhibition of the MMR machinery, leading to a significant increase (up to 438-fold) in mutation frequencies and a heritable fixation of genome mutations. Following such accelerated mutagenesis-followed-by selection approach, three phenotypes were successfully evolved: resistance to antibiotics streptomycin and rifampicin and reversion of a synthetic uracil auxotrophy. Thus, these mutator devices could be applied to accelerate evolution of metabolic pathways in long-term evolutionary experiments, alternating cycles of (inducible) mutagenesis coupled to selection schemes.

Genealogical structure changes as range expansions transition from pushed to pulled

Range expansions accelerate evolution through multiple mechanisms including gene surfing and genetic drift. The inference and control of these evolutionary processes ultimately relies on the information contained in genealogical trees. Currently, there are two opposing views on how range expansions shape genealogies. In invasion biology, expansions are typically approximated by a series of population bottlenecks producing genealogies with only pairwise mergers between lineages—a process known as the Kingman coalescent. Conversely, traveling-wave models predict a coalescent with multiple mergers, known as the Bolthausen–Sznitman coalescent. Here, we unify these two approaches and show that expansions can generate an entire spectrum of coalescent topologies. Specifically, we show that tree topology is controlled by growth dynamics at the front and exhibits large differences between pulled and pushed expansions. These differences are explained by the fluctuations in the total number of descendants left by the early founders. High growth cooperativity leads to a narrow distribution of reproductive values and the Kingman coalescent. Conversely, low growth cooperativity results in a broad distribution, whose exponent controls the merger sizes in the genealogies. These broad distribution and non-Kingman tree topologies emerge due to the fluctuations in the front shape and position and do not occur in quasi-deterministic simulations. Overall, our results show that range expansions provide a robust mechanism for generating different types of multiple mergers, which could be similar those observed in populations with strong selection or high fecundity. Thus, caution should be exercised in making inferences about the origin of non-Kingman genealogies.Significance statementSpatial dynamics are important for understanding genetic diversity in many contexts, such as cancer and infectious diseases. Coalescent theory offers a powerful framework for interpreting and predicting patters of genetic diversity in populations, but incorporating spatial structure into the theory has proven difficult. Here, we address this long-standing problem by studying the coalescent in a spatially expanding population. We find the topology of the coalescent changes depending on the growth dynamics at the front. Using analytical arguments, we show that the transition between coalescent topologies is universal and is controlled by a parameter related to the expansion velocity. Our theory makes precise predictions about the effects of population dynamics on genetic diversity at the expansion front, which we confirm in simulations.

Ecological effects of stress drive bacterial evolvability under sub-inhibitory antibiotic treatments

1AbstractStress is thought to increase mutation rate and thus to accelerate evolution. In the context of antibiotic resistance, sub-inhibitory treatments could then lead to enhanced evolvability, thereby fueling the adaptation of pathogens. Conducting a meta-analysis of published experimental data as well as our own experiments, we found that the increase in mutation rates triggered by antibiotic treatments is often canceled out by reduced population size, resulting in no overall increase in genetic diversity. A careful analysis of the effect of ecological factors on genetic diversity revealed that the potential for regrowth during recovery phase after treatment plays a crucial role in evolvability and is the main predictor of increased genetic diversity in experimental data.

Limit cycle dynamics can guide the evolution of gene regulatory networks towards point attractors

Developmental dynamics in Boolean models of gene networks self-organize, either into point attractors (stable repeating patterns of gene expression) or limit cycles (stable repeating sequences of patterns), depending on the network interactions specified by a genome of evolvable bits. Genome specifications for dynamics that can map specific gene expression patterns in early development onto specific point attractor patterns in later development are essentially impossible to discover by chance mutation alone, even for small networks. We show that selection for approximate mappings, dynamically maintained in the states comprising limit cycles, can accelerate evolution by at least an order of magnitude. These results suggest that self-organizing dynamics that occur within lifetimes can, in principle, guide natural selection across lifetimes.

Seasonal Declines in Cry1Ac and Cry2Ab Concentration in Maturing Cotton Favor Faster Evolution of Resistance to Pyramided Bt Cotton in Helicoverpa zea (Lepidoptera: Noctuidae)

Under ideal conditions, widely adopted transgenic crop pyramids producing two or more distinct insecticidal proteins from Bacillus thuringiensis (Bt) that kill the same pest can substantially delay evolution of resistance by pests. However, deviations from ideal conditions diminish the advantages of such pyramids. Here, we tested the hypothesis that changes in maturing cotton producing Cry1Ac and Cry2Ab affect evolution of resistance in Helicoverpa zea (Boddie) (Lepidoptera: Noctuidae), a pest with low inherent susceptibility to both toxins. In terminal leaves of field-grown Bt cotton, the concentration of both toxins was significantly higher for young, squaring plants than for old, fruiting plants. We used laboratory bioassays with plant material from field-grown cotton to test H. zea larvae from a strain selected for resistance to Cry1Ac in the laboratory, its more susceptible parent strain, and their F1 progeny. On young Bt cotton, no individuals survived to pupation. On old Bt cotton, survival to pupation was significantly higher for the lab-selected strain and the F1 progeny relative to the unselected parent strain, indicating dominant inheritance of resistance. Redundant killing, the extent to which insects resistant to one toxin are killed by another toxin in a pyramid, was complete on young Bt cotton, but not on old Bt cotton. No significant fitness costs associated with resistance were detected on young or old non-Bt cotton. Incorporation of empirical data into simulations indicates the observed increased selection for resistance on old Bt cotton could accelerate evolution of resistance to cotton producing Cry1Ac and Cry2Ab in H. zea.

Protein evolution speed depends on its stability and abundance and on chaperone concentrations

Proteins evolve at different rates. What drives the speed of protein sequence changes? Two main factors are a protein’s folding stability and aggregation propensity. By combining the hydrophobic–polar (HP) model with the Zwanzig–Szabo–Bagchi rate theory, we find that: (i) Adaptation is strongly accelerated by selection pressure, explaining the broad variation from days to thousands of years over which organisms adapt to new environments. (ii) The proteins that adapt fastest are those that are not very stably folded, because their fitness landscapes are steepest. And because heating destabilizes folded proteins, we predict that cells should adapt faster when put into warmer rather than cooler environments. (iii) Increasing protein abundance slows down evolution (the substitution rate of the sequence) because a typical protein is not perfectly fit, so increasing its number of copies reduces the cell’s fitness. (iv) However, chaperones can mitigate this abundance effect and accelerate evolution (also called evolutionary capacitance) by effectively enhancing protein stability. This model explains key observations about protein evolution rates.