Lotka–Volterra dynamics kills the Red Queen: population size fluctuations and associated stochasticity dramatically change host-parasite coevolution

Background: Host-parasite coevolution is generally believed to follow Red Queen dynamics consisting of ongoing oscillations in the frequencies of interacting host and parasite alleles. This belief is founded on previous theoretical work, which assumes infinite or constant population size. To what extent are such sustained oscillations realistic? Results: Here, we use a related mathematical modeling approach to demonstrate that ongoing Red Queen dynamics is unlikely. In fact, they collapse rapidly when two critical pieces of realism are acknowledged: (i) population size fluctuations, caused by the antagonism of the interaction in concordance with the Lotka-Volterra relationship; and (ii) stochasticity, acting in any finite population. Together, these two factors cause fast allele fixation. Fixation is not restricted to common alleles, as expected from drift, but also seen for originally rare alleles under a wide parameter space, potentially facilitating spread of novel variants. Conclusion: Our results call for a paradigm shift in our understanding of host-parasite coevolution, strongly suggesting that these are driven by recurrent selective sweeps rather than continuous allele oscillations

Host-parasite coevolution in populations of constant and variable size

The matching-allele and gene-for-gene models are widely used in math- ematical approaches that study the dynamics of host-parasite interactions. Agrawal and Lively (Evolutionary Ecology Research 4:79-90, 2002) captured these two models in a single framework and numerically explored the associated time discrete dynamics of allele frequencies. Here, we present a detailed analytical investigation of this unifying framework in continuous time and provide a generalization. We extend the model to take into account changing population sizes, which result from the antagonistic nature of the interaction and follow the Lotka-Volterra equations. Under this extension, the population dynamics become most complex as the model moves away from pure matching-allele and becomes more gene-for-gene-like. While the population densities oscillate with a single oscillation frequency in the pure matching-allele model, a second oscillation frequency arises under gene-for-gene-like conditions. These observations hold for general interaction parameters and allow to infer generic patterns of the dynamics. Our results suggest that experimentally inferred dynamical patterns of host-parasite coevolution should typically be much more complex than the popular illustrations of Red Queen dynamics. A single parasite that infects more than one host can substantially alter the cyclic dynamics

Alternative evolutionary paths to bacterial antibiotic resistance cause distinct collateral effects.

Published onlineJournal ArticleThis is the author accepted manuscript. The final version is available from Oxford University Press via the DOI in this record.When bacteria evolve resistance against a particular antibiotic, they may simultaneously gain increased sensitivity against a second one. Such collateral sensitivity may be exploited to develop novel, sustainable antibiotic treatment strategies aimed at containing the current, dramatic spread of drug resistance. To date, the presence and molecular basis of collateral sensitivity has only been studied in few bacterial species and is unknown for opportunistic human pathogens such as Pseudomonas aeruginosa. In the present study, we assessed patterns of collateral effects by experimentally evolving 160 independent populations of P. aeruginosa to high levels of resistance against eight commonly used antibiotics. The bacteria evolved resistance rapidly and expressed both collateral sensitivity and cross-resistance. The pattern of such collateral effects differed to those previously reported for other bacterial species, suggesting inter-specific differences in the underlying evolutionary trade-offs. Intriguingly, we also identified contrasting patterns of collateral sensitivity and cross-resistance among the replicate populations adapted to the same drug. Whole-genome sequencing of 81 independently evolved populations revealed distinct evolutionary paths of resistance to the selective drug, which determined whether bacteria became cross-resistant or collaterally sensitive towards others. Based on genomic and functional genetic analysis, we demonstrate that collateral sensitivity can result from resistance mutations in regulatory genes such as nalC or mexZ, which mediate aminoglycoside sensitivity in β-lactam-adapted populations, or the two-component regulatory system gene pmrB, which enhances penicillin sensitivity in gentamicin-resistant populations. Our findings highlight substantial variation in the evolved collateral effects among replicates, which in turn determine their potential in antibiotic therapy.We thank Anette Friedrichs, Lutz Becks, and the Schulenburg group for valuable advice and Melanie Vollstedt for technical support during genome sequencing. We are grateful for financial support from the German Science Foundation (DFG grant SCHU 1415/12-1) and the International Max-Planck Research School for Evolutionary Biology at the University of Kiel. We acknowledge infrastructural support by the DFG excellence cluster Inflammation at Interfaces

Bdellovibrio and Like Organisms Are Predictors of Microbiome Diversity in Distinct Host Groups

Biodiversity is generally believed to be a main determinant of ecosystem functioning. This principle also applies to the microbiome and could consequently contribute to host health. According to ecological theory, communities are shaped by top predators whose direct and indirect interactions with community members cause stability and diversity. Bdellovibrio and like organisms (BALOs) are a neglected group of predatory bacteria that feed on Gram-negative bacteria and can thereby influence microbiome composition. We asked whether BALOs can predict biodiversity levels in microbiomes from distinct host groups and environments. We demonstrate that genetic signatures of BALOs are commonly found within the 16S rRNA reads from diverse host taxa. In many cases, their presence, abundance, and especially richness are positively correlated with overall microbiome diversity. Our findings suggest that BALOs can act as drivers of microbial alpha-diversity and should therefore be considered candidates for the restoration of microbiomes and the prevention of dysbiosis

Cellular hysteresis as a principle to maximize the efficacy of antibiotic therapy

Rapid evolution is central to the current antibiotic crisis. Sustainable treatments must thus take account of the bacteria’s potential for adaptation. We identified cellular hysteresis as a principle to constrain bacterial evolution. Cellular hysteresis is a persistent change in bacterial physiology, reminiscent of cellular memory, which is induced by one antibiotic and enhances susceptibility toward another antibiotic. Cellular hysteresis increases bacterial extinction in fast sequential treatments and reduces selection of resistance by favoring responses specific to the induced physiological effects. Fast changes between antibiotics are key, because they create the continuously high selection conditions that are difficult to counter by bacteria. Our study highlights how an understanding of evolutionary processes can help to outsmart human pathogens.Antibiotic resistance has become one of the most dramatic threats to global health. While novel treatment options are urgently required, most attempts focus on finding new antibiotic substances. However, their development is costly, and their efficacy is often compromised within short time periods due to the enormous potential of microorganisms for rapid adaptation. Here, we developed a strategy that uses the currently available antibiotics. Our strategy exploits cellular hysteresis, which is the long-lasting, transgenerational change in cellular physiology that is induced by one antibiotic and sensitizes bacteria to another subsequently administered antibiotic. Using evolution experiments, mathematical modeling, genomics, and functional genetic analysis, we demonstrate that sequential treatment protocols with high levels of cellular hysteresis constrain the evolving bacteria by (i) increasing extinction frequencies, (ii) reducing adaptation rates, and (iii) limiting emergence of multidrug resistance. Cellular hysteresis is most effective in fast sequential protocols, in which antibiotics are changed within 12 h or 24 h, in contrast to the less frequent changes in cycling protocols commonly implemented in hospitals. We found that cellular hysteresis imposes specific selective pressure on the bacteria that disfavors resistance mutations. Instead, if bacterial populations survive, hysteresis is countered in two distinct ways, either through a process related to antibiotic tolerance or a mechanism controlled by the previously uncharacterized two-component regulator CpxS. We conclude that cellular hysteresis can be harnessed to optimize antibiotic therapy, to achieve both enhanced bacterial elimination and reduced resistance evolution

Company Town Diversification And Designing Its Future

The urban development of a company town in Russia currently depends on the opportunity to diversify the core industry attracting investments into developed projects that offers the variety of directions of future designing. Although the great majority of company towns prepared Complex investment plans of monotown modernization stated the goal and the directions of diversification, the appropriate financing of the created projects is hardly exist. The authors argue that the basic measures that identify the diversification efficiency are the variety of concentration indexes, dynamics indicators and shift-shares; nevertheless, the possibility to evaluate how the new economic activity changes the structure in dynamics is rather low. This article offers the way to estimate the diversification in dynamics caused by the emerging economic activity using the diversification in dexon the basis of dynamic approach for evaluation of company town diversification efficiency. The authors suggest the diversification index that shows both the dynamics of structural change and the new economic activity emerging in company town. The index allows measuring the diversification shift in company town implementing the diversification strategy. The article conducts the case study of Kaltansky urban district located in Kemerovskaya oblast and makes conclusions that higher diversification in investments does not relates with the appropriate dynamics in dispatched goods. This fact allows low efficiency of the diversification and creates the negative image of the town in future designing

Bottleneck size and selection level reproducibly impact evolution of antibiotic resistance

During antibiotic treatment, the evolution of bacterial pathogens is fundamentally affected by bottlenecks and varying selection levels imposed by the drugs. Bottlenecks—that is, reductions in bacterial population size—lead to an increased influence of random effects (genetic drift) during bacterial evolution, and varying antibiotic concentrations during treatment may favour distinct resistance variants. Both aspects influence the process of bacterial evolution during antibiotic therapy and thereby treatment outcome. Surprisingly, the joint influence of these interconnected factors on the evolution of antibiotic resistance remains largely unexplored. Here we combine evolution experiments with genomic and genetic analyses to demonstrate that bottleneck size and antibiotic-induced selection reproducibly impact the evolutionary path to resistance in pathogenic Pseudomonas aeruginosa, one of the most problematic opportunistic human pathogens. Resistance is favoured—expectedly—under high antibiotic selection and weak bottlenecks, but—unexpectedly—also under low antibiotic selection and severe bottlenecks. The latter is likely to result from a reduced probability of losing favourable variants through drift under weak selection. Moreover, the absence of high resistance under low selection and weak bottlenecks is caused by the spread of low-resistance variants with high competitive fitness under these conditions. We conclude that bottlenecks, in combination with drug-induced selection, are currently neglected key determinants of pathogen evolution and outcome of antibiotic treatment

Effect of anisotropy on the ground-state magnetic ordering of the spin-one quantum J1XXZJ_{1}^{XXZ}--J2XXZJ_{2}^{XXZ} model on the square lattice

We study the zero-temperature phase diagram of the $J_{1}^{XXZ}$--$J_{2}^{XXZ}$ Heisenberg model for spin-1 particles on an infinite square lattice interacting via nearest-neighbour ($J_1 \equiv 1$) and next-nearest-neighbour ($J_2 > 0$) bonds. Both bonds have the same $XXZ$-type anisotropy in spin space. The effects on the quasiclassical N\'{e}el-ordered and collinear stripe-ordered states of varying the anisotropy parameter $\Delta$ is investigated using the coupled cluster method carried out to high orders. By contrast with the spin-1/2 case studied previously, we predict no intermediate disordered phase between the N\'{e}el and collinear stripe phases, for any value of the frustration $J_2/J_1$, for either the $z$-aligned ($\Delta > 1$) or $xy$-planar-aligned ($0 \leq \Delta < 1$) states. The quantum phase transition is determined to be first-order for all values of $J_2/J_1$ and $\Delta$. The position of the phase boundary $J_{2}^{c}(\Delta)$ is determined accurately. It is observed to deviate most from its classical position $J_2^c = {1/2}$ (for all values of $\Delta > 0$) at the Heisenberg isotropic point ($\Delta = 1$), where $J_{2}^{c}(1) = 0.55 \pm 0.01$. By contrast, at the XY isotropic point ($\Delta = 0$), we find $J_{2}^{c}(0) = 0.50 \pm 0.01$. In the Ising limit ($\Delta \to \infty$) $J_2^c \to 0.5$ as expected.Comment: 20 pages, 5 figure

The genomic basis of rapid adaptation to antibiotic combination therapy in Pseudomonas aeruginosa

Combination therapy is a common antibiotic treatment strategy that aims at minimizing the risk of resistance evolution in several infectious diseases. Nonetheless, evidence supporting its efficacy against the nosocomial opportunistic pathogen Pseudomonas aeruginosa remains elusive. Identification of the possible evolutionary paths to resistance in multidrug environments can help to explain treatment outcome. For this purpose, we here performed whole-genome sequencing of 127 previously evolved populations of P. aeruginosa adapted to sublethal doses of distinct antibiotic combinations and corresponding single-drug treatments, and experimentally characterized several of the identified variants. We found that alterations in the regulation of efflux pumps are the most favored mechanism of resistance, regardless of the environment. Unexpectedly, we repeatedly identified intergenic variants in the adapted populations, often with no additional mutations and usually associated with genes involved in efflux pump expression, possibly indicating a regulatory function of the intergenic regions. The experimental analysis of these variants demonstrated that the intergenic changes caused similar increases in resistance against single and multidrug treatments as those seen for efflux regulatory gene mutants. Surprisingly, we could find no substantial fitness costs for a majority of these variants, most likely enhancing their competitiveness toward sensitive cells, even in antibiotic-free environments. We conclude that the regulation of efflux is a central target of antibiotic-mediated selection in P. aeruginosa and that, importantly, changes in intergenic regions may represent a usually neglected alternative process underlying bacterial resistance evolution, which clearly deserves further attention in the future