Fasting blood glucose in a Ghanaian adult is causally affected by malaria parasite load: a mechanistic case study using convergent cross mapping.

BACKGROUND: Adults with diabetes mellitus (DM) in malaria-endemic areas might be more susceptible to Plasmodium infection than healthy individuals. Herein, the study was aimed at verifying the hypothesis that increased fasting blood glucose (FBG) promotes parasite growth as reflected by increased parasite density. METHODS: Seven adults without DM were recruited in rural Ghana to determine the relationships between FBG and malaria parasite load. Socio-economic data were recorded in questionnaire-based interviews. Over a period of 6 weeks, FBG and Plasmodium sp. Infection were measured in peripheral blood samples photometrically and by polymerase chain reaction (PCR)-assays, respectively. Daily physical activity and weather data were documented via smartphone recording. For the complex natural systems of homeostatic glucose control and Plasmodium sp. life cycle, empirical dynamic modelling was applied. RESULTS: At baseline, four men and three women (median age, 33 years; interquartile range, 30-48) showed a median FBG of 5.5 (5.1-6.0 mmol/L); one participant had an asymptomatic Plasmodium sp. infection (parasite density: 240/µL). In this participant, convergent cross mapping (CCM) for 34 consecutive days, showed that FBG was causally affected by parasite density (p < 0.02), while the reciprocal relationship was not discernible (p > 0.05). Additionally, daily ambient temperature affected parasite density (p < 0.01). CONCLUSION: In this study population living in a malaria-endemic area, time series analyses were successfully piloted for the relationships between FBG and Plasmodium sp. density. Longer observation periods and larger samples are required to confirm these findings and determine the direction of causality.

Evolutionary stability of plant-pollinator networks: efficient communities and a pollination dilemma.

Mutualistic interactions between species are ubiquitous in nature and essential for ecosystem functioning. Often dozens or even hundreds of species with different degrees of specialisation form complex networks. How this complexity evolves is a fundamental question in ecology. Here, we present a new game theoretical approach to model complex coevolutionary processes and apply it to pollination networks. A theoretical analysis reveals multiple evolutionary stable network structures that depend on the availability of pollination service. In particular, we find efficient communities, in which a high percentage of pollen are transported conspecifically, to evolve only when plant and pollinator abundances are well balanced. Both pollinator shortage and oversupply select for more inefficient network structures. The results suggest that availability of pollination services is a key factor structuring pollination networks and may offer a new explanation for geographical differences in pollination communities that have long been recognised by ecologists.

Theory of coevolution of cytoplasmic male-sterility, nuclear restorer and selfing.

Gynodioecy is a sexual polymorphism in angiosperms, where hermaphroditic and female individuals coexist. This is often caused by a cytoplasmic genetic element (CGE) that destroys male functions, which is called cytoplasmic male-sterility (CMS). On the other hand, nuclear genes tend to evolve the ability to restore male function. The coevolutionary process of CMS and the restoration has been studied theoretically. Recently, a theoretical study suggested that these coevolutionary dynamics could be influenced by the rate of selfing within populations, although it assumed that the selfing rate of a population was a fixed parameter. Accordingly, we theoretically study the coevolution of three traits in this paper: CMS, nuclear restorer and selfing rate, in which we hypothesize that selfing evolution can suppress CMS evolution under some conditions. The analysis indicates three significant properties of the system; (1) CMS-restorer evolution can result in bistability under a given selfing rate, (2) the coevolution of three traits can realize intermediate levels of selfing, and (3) the evolution of high levels of selfing is conditionally associated with no CMS and/or no restoration, which may support our hypothesis.

Host-Pathogen Coevolution: The Selective Advantage of Bacillus thuringiensis Virulence and Its Cry Toxin Genes.

Reciprocal coevolution between host and pathogen is widely seen as a major driver of evolution and biological innovation. Yet, to date, the underlying genetic mechanisms and associated trait functions that are unique to rapid coevolutionary change are generally unknown. We here combined experimental evolution of the bacterial biocontrol agent Bacillus thuringiensis and its nematode host Caenorhabditis elegans with large-scale phenotyping, whole genome analysis, and functional genetics to demonstrate the selective benefit of pathogen virulence and the underlying toxin genes during the adaptation process. We show that: (i) high virulence was specifically favoured during pathogen-host coevolution rather than pathogen one-sided adaptation to a nonchanging host or to an environment without host; (ii) the pathogen genotype BT-679 with known nematocidal toxin genes and high virulence specifically swept to fixation in all of the independent replicate populations under coevolution but only some under one-sided adaptation; (iii) high virulence in the BT-679-dominated populations correlated with elevated copy numbers of the plasmid containing the nematocidal toxin genes; (iv) loss of virulence in a toxin-plasmid lacking BT-679 isolate was reconstituted by genetic reintroduction or external addition of the toxins. We conclude that sustained coevolution is distinct from unidirectional selection in shaping the pathogen's genome and life history characteristics. To our knowledge, this study is the first to characterize the pathogen genes involved in coevolutionary adaptation in an animal host-pathogen interaction system.

Spatial spread of Wolbachia in Rhagoletis cerasi populations.

The bacterial endosymbiont Wolbachia has been used to control insect pests owing to its ability to manipulate their life history and suppress infectious diseases. Therefore, knowledge on Wolbachia dynamics in natural populations is fundamental. The European cherry fruit fly, Rhagoletis cerasi, is infected with the Wolbachia strain wCer2, mainly present in southern and central European populations, and is currently spreading into wCer2-uninfected populations driven by high unidirectional cytoplasmic incompatibility. Here, we describe the distribution of wCer2 along two transition zones where the infection is spreading into wCer2-uninfected R. cerasi populations. Fine-scale sampling of 19 populations in the Czech Republic showed a smooth decrease of wCer2 frequency from south to north within a distance of less than 20 km. Sampling of 12 Hungarian populations, however, showed a sharp decline of wCer2 infection frequency within a few kilometres. We fitted a standard wave equation to our empirical data and estimated a Wolbachia wave speed of 1.9 km yr-1 in the Czech Republic and 1.0 km yr-1 in Hungary. Considering the univoltine life cycle and limited dispersal ability of R. cerasi, our study highlights a rapid Wolbachia spread in natural host populations.

Infections of Wolbachia may destabilize mosquito population dynamics.

Recent efforts in controlling mosquito-borne diseases focus on biocontrol strategies that incapacitate pathogens inside mosquitoes by altering the mosquito's microbiome. A case in point is the introduction of Wolbachia into natural mosquito populations in order to eliminate Dengue virus. However, whether this strategy can successfully control vector-borne diseases is debated; particularly, how artificial infection affects population dynamics of hosts remains unclear. Here, we show that natural Wolbachia infections are associated with unstable mosquito population dynamics by contrasting Wolbachia-infected versus uninfected cage populations of the Asian tiger mosquito (Aedes albopictus). By analyzing weekly data of adult mosquito abundances, we found that the variability of the infected populations is significantly higher than that of the uninfected. The elevated population variability is explained by increased instability in dynamics, as quantified by system nonlinearity (i.e., state-dependence). In addition, predictability of infected populations is substantially lower. A mathematical model analysis suggests that Wolbachia may alter mosquito population dynamics by modifying larval competition of hosts. These results encourage examination for effects of artificial Wolbachia establishment on mosquito populations, because an enhancement of population variability with reduced predictability could pose challenges in management. Our findings have implications for application of microbiome alterations in biocontrol programs.

A Comparison of Wolbachia Infection Frequencies in Varroa With Prevalence of Deformed Wing Virus.

Wolbachia are widely distributed bacterial endosymbionts of arthropods and filarial nematodes. These bacteria can affect host fitness in a variety of ways, such as protecting hosts against viruses and other pathogens. Here, we investigate the possible role of Wolbachia in the prevalence of the deformed wing virus (DWV), a highly virulent pathogen of honey bees (Apis mellifera) that is transmitted by parasitic Varroa mites (Varroa destructor). About 180 Varroa mites from 18 beehives were tested for infection with Wolbachia and DWV. We first screened for Wolbachia using two standard primers (wsp and 16S rDNA), and found 26% of the mites to be positive for Wolbachia using the wsp primer and 64% of the mites to be positive using the 16S rDNA primer. Using these intermediate Wolbachia frequencies, we then tested for statistical correlations with virus infection frequencies. The analysis revealed a significant positive correlation between DWV and Wolbachia using the wsp primer, but no significant association between DWV and Wolbachia using the 16S rDNA primer. In conclusion, there is no evidence for an anti-pathogenic effect of Wolbachia in V. destructor, but weak evidence for a pro-pathogenic effect. These results encourage further examination of Wolbachia-virus interactions in Varroa mites since an increased vector competence of the mites may significantly impact disease outbreaks in honey bees.

The hitchhiker's guide to Europe: the infection dynamics of an ongoing Wolbachia invasion and mitochondrial selective sweep in Rhagoletis cerasi.

Wolbachia is a maternally inherited and ubiquitous endosymbiont of insects. It can hijack host reproduction by manipulations such as cytoplasmic incompatibility (CI) to enhance vertical transmission. Horizontal transmission of Wolbachia can also result in the colonization of new mitochondrial lineages. In this study, we present a 15-year-long survey of Wolbachia in the cherry fruit fly Rhagoletis cerasi across Europe and the spatiotemporal distribution of two prevalent strains, wCer1 and wCer2, and associated mitochondrial haplotypes in Germany. Across most of Europe, populations consisted of either 100% singly (wCer1) infected individuals with haplotype HT1, or 100% doubly (wCer1&2) infected individuals with haplotype HT2, differentiated only by a single nucleotide polymorphism. In central Germany, singly infected populations were surrounded by transitional populations, consisting of both singly and doubly infected individuals, sandwiched between populations fixed for wCer1&2. Populations with fixed infection status showed perfect association of infection and mitochondria, suggesting a recent CI-driven selective sweep of wCer2 linked with HT2. Spatial analysis revealed a range expansion for wCer2 and a large transition zone in which wCer2 splashes appeared to coalesce into doubly infected populations. Unexpectedly, the transition zone contained a large proportion (22%) of wCer1&2 individuals with HT1, suggesting frequent intraspecific horizontal transmission. However, this horizontal transmission did not break the strict association between infection types and haplotypes in populations outside the transition zone, suggesting that this horizontally acquired Wolbachia infection may be transient. Our study provides new insights into the rarely studied Wolbachia invasion dynamics in field populations.

Rapid evolution of virulence leading to host extinction under host-parasite coevolution.

BACKGROUND: Host-parasite coevolution is predicted to result in changes in the virulence of the parasite in order to maximise its reproductive success and transmission potential, either via direct host-to-host transfer or through the environment. The majority of coevolution experiments, however, do not allow for environmental transmission or persistence of long lived parasite stages, in spite of the fact that these may be critical for the evolutionary success of spore forming parasites under natural conditions. We carried out a coevolution experiment using the red flour beetle, Tribolium castaneum, and its natural microsporidian parasite, Paranosema whitei. Beetles and their environment, inclusive of spores released into it, were transferred from generation to generation. We additionally took a modelling approach to further assess the importance of transmissive parasite stages on virulence evolution. RESULTS: In all parasite treatments of the experiment, coevolution resulted in extinction of the host population, with a pronounced increase in virulence being seen. Our modelling approach highlighted the presence of environmental transmissive parasite stages as being critical to the trajectory of virulence evolution in this system. CONCLUSIONS: The extinction of host populations was unexpected, particularly as parasite virulence is often seen to decrease in host-parasite coevolution. This, in combination with the increase in virulence and results obtained from the model, suggest that the inclusion of transmissive parasite stages is important to improving our understanding of virulence evolution.

Anticipating the occurrence and type of critical transitions.

Critical transition can occur in many real-world systems. The ability to forecast the occurrence of transition is of major interest in a range of contexts. Various early warning signals (EWSs) have been developed to anticipate the coming critical transition or distinguish types of transition. However, no effective method allows to establish practical threshold indicating the condition when the critical transition is most likely to occur. Here, we introduce a powerful EWS, named dynamical eigenvalue (DEV), that is rooted in bifurcation theory of dynamical systems to estimate the dominant eigenvalue of the system. Theoretically, the absolute value of DEV approaches 1 when the system approaches bifurcation, while its position in the complex plane indicates the type of transition. We demonstrate the efficacy of the DEV approach in model systems with known bifurcation types and also test the DEV approach on various critical transitions in real-world systems.

Bistability of endosymbiont evolution of genome size and host sex control.

Eukaryotic organisms often harbor several genetic factors in their cytoplasm. These cytoplasmic genetic elements (CGEs) include both eukaryotic organelles (mitochondria, chloroplasts) and bacterial endosymbionts, which have evolved from free-living bacteria. A common feature of CGEs is their cytoplasmic inheritance from mother to offspring. A striking difference is that some CGEs have evolved a short genome size (e.g., animal mitochondria), while others cause a sex ratio distortion (SRD) in their hosts (e.g., Wolbachia). In this study, we sought to resolve the evolution of these endosymbiont properties using a population genetics approach. Our model divides the endosymbiont genome into a functional part and a part that can cause SRD, and our results indicate that the cytoplasmic inheritance system at the initiation of symbiosis plays a key role in determining the evolutionary trajectory of CGEs. We show that in endosymbiotic evolution, two states can be bistable, depending on the parameters. The evolution of the cytoplasmic inheritance system from biparental to uniparental can result in hysteresis in the evolution of cytoplasmic symbionts.

Evolution of cytoplasmic sex ratio distorters: Effect of paternal transmission.

Eukaryotic organisms carry various genetic factors the so-called cytoplasmic genetic elements (CGEs), in their cytoplasm. Numerous examples are known in which CGEs possess the ability to control sex determination of their host organisms and cause sex ratio distortion (SRD). In general, CGEs are inherited maternally from female hosts, via egg cytoplasm to offspring. Thus, the elements tend to evolve abilities to avoid entrance into "dead-end" males. Previous theoretical studies have revealed that, as long as maternal transmission is perfect, CGEs evolve the highest levels of ability to cause SRD. However, it is recently reported that some CGEs transmit from male to offspring through infection to female in mating. This raises the question of how such a paternal contribution alters selective forces and SRD evolution. In the present study, the evolutionary process of SRD ability of CGEs was analyzed theoretically. The main finding is that paternal transmission results in evolution towards intermediate levels of SRD. Further, coexistence was observed of different CGEs inducing different levels of SRD. These results point to the importance of paternal transmission in the evolution of CGEs.

Genetic Incompatibilities Between Mitochondria and Nuclear Genes: Effect on Gene Flow and Speciation.

The process of speciation is, according to the biological species concept, the reduction in gene flow between genetically diverging populations. Most of the previous theoretical studies analyzed the effect of nuclear genetic incompatibilities on gene flow. There is, however, an increasing number of empirical examples suggesting that cytoplasmically inherited genetic elements play an important role in speciation. Here, we present a theoretical analysis of mitochondrial driven speciation, in which genetic incompatibilities occur between mitochondrial haplotypes and nuclear alleles. Four population genetic models with mainland-island structure were analyzed that differ with respect to the type of incompatibility and the underlying genetics. Gene flow reduction was measured on selectively neutral alleles of an unlinked locus and quantified by the effective migration rate. Analytical formulae for the different scenarios were derived using the fitness graph method. For the models with haploid genetics, we found that mito-nuclear incompatibilities (MtNI) are as strong as nuclear-nuclear incompatibilities (NNI) in reducing gene flow at the unlinked locus, but only if males and females migrate in equal number. For models with diploid genetics, we found that MtNI reduce gene flow stronger than NNI when incompatibilities are recessive, but weaker when they are dominant. For both haploid and diploid MtNI, we found that gene flow reduction is stronger if females are the migrating sex, but weaker than NNI when males are the migrating sex. These results encourage further examination on the role of mitochondria on genetic divergence and speciation and point toward specific factors (e.g., migrating sex) that could be the focus of an empirical test.

The neutral effective migration rate in a mainland-island context.

Genetic influx into a population often does not correspond to the real migration rate (m) of individuals, due to class structure within the population. The effective migration rate (m(e)) is a concept to measure gene flow in such a situation. The ratio of the effective migration rate to the real migration rate (m(e)/m) is called the gene flow factor, and represents the degree of gene flow modification. Prior authors proposed different definitions of the effective migration rate. These may be categorized into two groups: the neutral effective migration rate and the selective effective migration rate. In this article, we construct a general model of a class-structured population with a mainland-island structure. Using the model, we prove that the gene flow factor of the neutral effective migration rate converges to the mean reproductive value of immigrants if the limit is taken with the real migration rate converging to zero. This limit theorem provides a novel interpretation of gene flow and can be used to derive approximation formulae of the neutral effective migration rate. We illustrate this method analyzing two examples, sex ratio distortion due to extrinsic factors and hybrid zones with underdominance.

How many species are infected with Wolbachia?--A statistical analysis of current data.

Wolbachia are intracellular bacteria found in many species of arthropods and nematodes. They manipulate the reproduction of their arthropod hosts in various ways, may play a role in host speciation and have potential applications in biological pest control. Estimates suggest that at least 20% of all insect species are infected with Wolbachia. These estimates result from several Wolbachia screenings in which numerous species were tested for infection; however, tests were mostly performed on only one to two individuals per species. The actual percent of species infected will depend on the distribution of infection frequencies among species. We present a meta-analysis that estimates percentage of infected species based on data on the distribution of infection levels among species. We used a beta-binomial model that describes the distribution of infection frequencies of Wolbachia, shedding light on the overall infection rate as well as on the infection frequency within species. Our main findings are that (1) the proportion of Wolbachia-infected species is estimated to be 66%, and that (2) within species the infection frequency follows a 'most-or-few' infection pattern in a sense that the Wolbachia infection frequency within one species is typically either very high (>90%) or very low (<10%).

Assortment of Flowering Time and Immunity Alleles in Natural Arabidopsis thaliana Populations Suggests Immunity and Vegetative Lifespan Strategies Coevolve.

The selective impact of pathogen epidemics on host defenses can be strong but remains transient. By contrast, life-history shifts can durably and continuously modify the balance between costs and benefits of immunity, which arbitrates the evolution of host defenses. Their impact on the evolutionary dynamics of host immunity, however, has seldom been documented. Optimal investment into immunity is expected to decrease with shortening lifespan, because a shorter life decreases the probability to encounter pathogens or enemies. Here, we document that in natural populations of Arabidopsis thaliana, the expression levels of immunity genes correlate positively with flowering time, which in annual species is a proxy for lifespan. Using a novel genetic strategy based on bulk-segregants, we partitioned flowering time-dependent from -independent immunity genes and could demonstrate that this positive covariation can be genetically separated. It is therefore not explained by the pleiotropic action of some major regulatory genes controlling both immunity and lifespan. Moreover, we find that immunity genes containing variants reported to impact fitness in natural field conditions are among the genes whose expression covaries most strongly with flowering time. Taken together, these analyses reveal that natural selection has likely assorted alleles promoting lower expression of immunity genes with alleles that decrease the duration of vegetative lifespan in A. thaliana and vice versa. This is the first study documenting a pattern of variation consistent with the impact that selection on flowering time is predicted to have on diversity in host immunity.

Empirical Dynamic Modelling Identifies different Responses of Aedes Polynesiensis Subpopulations to Natural Environmental Variables.

To control mosquito populations for managing vector-borne diseases, a critical need is to identify and predict their response to causal environmental variables. However, most existing attempts rely on linear approaches based on correlation, which cannot apply in complex, nonlinear natural systems, because correlation is neither a necessary nor sufficient condition for causation. Applying empirical dynamic modelling that acknowledges nonlinear dynamics on nine subpopulations of tiger mosquitos from three neighbouring reef islets of the Raiatea atoll, we identified temperature, precipitation, dew point, air pressure, and mean tide level as causal environmental variables. Interestingly, responses of subpopulations in close proximity (100-500 m) differed with respect to their causal environmental variables and the time delay of effect, highlighting complexity in mosquito-environment causality network. Moreover, we demonstrated how to explore the effects of changing environmental variables on number and strength of mosquito outbreaks, providing a new framework for pest control and disease vector ecology.

Geographical variation in the heterogeneity of mutualistic networks.

Plant-animal mutualistic networks are characterized by highly heterogeneous degree distributions. The majority of species interact with few partner species, while a small number are highly connected to form network hubs that are proposed to play an important role in community stability. It has not been investigated, however, if or how the degree distributions vary among types of mutualisms or communities, or between plants and animals in the same network. Here, we evaluate the degree distributions of pollination and seed-dispersal networks, which are two major types of mutualistic networks that have often been discussed in parallel, using an index based on Pielou's evenness. Among 56 pollination networks we found strong negative correlation of the heterogeneity between plants and animals, and geographical shifts of network hubs from plants in temperate regions to animals in the tropics. For 28 seed-dispersal networks, by contrast, the correlation was positive, and there is no comparable geographical pattern. These results may be explained by evolution towards specialization in the presence of context-dependent costs that occur if plants share the animal species as interaction partner. How the identity of network hubs affects the stability and resilience of the community is an important question for future studies.

Experimental evolution in silico: a custom-designed mathematical model for virulence evolution of Bacillus thuringiensis.

Most mathematical models on the evolution of virulence are based on epidemiological models that assume parasite transmission follows the mass action principle. In experimental evolution, however, mass action is often violated due to controlled infection protocols. This "theory-experiment mismatch" raises the question whether there is a need for new mathematical models to accommodate the particular characteristics of experimental evolution. Here, we explore the experimental evolution model system of Bacillus thuringiensis as a parasite and Caenorhabditis elegans as a host. Recent experimental studies with strict control of parasite transmission revealed that one-sided adaptation of B. thuringiensis with non-evolving hosts selects for intermediate or no virulence, sometimes coupled with parasite extinction. In contrast, host-parasite coevolution selects for high virulence and for hosts with strong resistance against B. thuringiensis. In order to explain the empirical results, we propose a new mathematical model that mimics the basic experimental set-up. The key assumptions are: (i) controlled parasite transmission (no mass action), (ii) discrete host generations, and (iii) context-dependent cost of toxin production. Our model analysis revealed the same basic trends as found in the experiments. Especially, we could show that resistant hosts select for highly virulent bacterial strains. Moreover, we found (i) that the evolved level of virulence is independent of the initial level of virulence, and (ii) that the average amount of bacteria ingested significantly affects the evolution of virulence with fewer bacteria ingested selecting for highly virulent strains. These predictions can be tested in future experiments. This study highlights the usefulness of custom-designed mathematical models in the analysis and interpretation of empirical results from experimental evolution.