Interspecific matings are by definition rare events in nature, but when they occur they can be very important, and not only because they might condition gene flow between species. Even when such matings have no genetic consequence, for instance if they do not yield any fertile hybrid offspring, they can still have an impact on the population dynamics of the species involved [1]. Such atypical pairings between heterospecific partners are usually regarded as detrimental or undesired; as they interfere with the occurrence or success of intraspecific matings, they are expected to cause a decline in absolute fitness.
The story is not always so simple however, and it might all depend on the timing of events and on the identity of the partners. Using the herbivorous mite Tetranychus urticae as a model, Clemente et al. [2] experimentally arranged matings with two other Tetranychus species that commonly share the same host plants as T. urticae. They carefully controlled the history of events: heterospecific matings could occur just before, just after, 24h before, or 24h after, a conspecific mating. Interestingly, the oviposition rate (total fecundity) of females was increased when mating with a heterospecific individual. This suggests that heterospecic sperm can stimulate oogenesis just as conspecific sperm does. Such a positive effect was observed for matings involving T. ludeni females and T. urticae males, but a negative effect is found in the interaction with T. evansi. Sex-ratio (fertilization success in those species) could also be impacted but, unlike fertilization, this occurred when the mating events were distant in time. This is is at odds with what is observed in conspecific matings, where sperm displacement occurs only if mating events are temporally close. Overall, the effects of heterospecific mating were quite variable and it is challenging to predict a single, general, effect of interspecific matings. The net effect will likely be context-dependent, depending on the relative frequency of the difference mating sequences and on how fecundity and sex-ratio contribute to overall fitness, both aspect strongly influenced by the population dynamics and structure.

References

[1] Gröning J. & Hochkirch A. 2008. Reproductive interference between animal species. The Quarterly Review of Biology 83: 257-282. doi: 10.1086/590510

[2] Clemente SH, Santos I, Ponce AR, Rodrigues LR, Varela SAM & Magalhaes S. 2017 Despite reproductive interference, the net outcome of reproductive interactions among spider mite species is not necessarily costly. bioRxiv 113274, ver. 4 of the 30th of June 2017. doi: 10.1101/113274

Many parasites can manipulate their hosts, thus increasing their transmission to new hosts [1]. This is particularly the case for vector-borne parasites, which can alter the feeding behaviour of their hosts. However, predicting the optimal strategy is not straightforward because three actors are involved and the interests of the parasite may conflict with that of the vector. There are few models that consider the evolution of host manipulation by parasites [but see 2-4], but there are virtually none that investigated how parasites can manipulate the host choice of vectors. Even on the empirical side, many aspects of this choice remain unknown. Gandon [5] develops a simple evolutionary epidemiology model that allows him to formulate clear and testable predictions. These depend on which actor controls the trait (the vector or the parasite) and, when there is manipulation, whether it is realised via infected hosts (to attract vectors) or infected vectors (to change host choice). In addition to clarifying the big picture, Gandon [5] identifies some nice properties of the model, for instance an independence of the density/frequency-dependent transmission assumption or a backward bifurcation at R0=1, which suggests that parasites could persist even if their R0 is driven below unity. Overall, this study calls for further investigation of the different scenarios with more detailed models and experimental validation of general predictions.

References

[1] Hughes D, Brodeur J, Thomas F. 2012. Host manipulation by parasites. Oxford University Press.

[2] Brown SP. 1999. Cooperation and conflict in host-manipulating parasites. Proceedings of the Royal Society of London B: Biological Sciences 266: 1899–1904. doi: 10.1098/rspb.1999.0864

[3] Lion S, van Baalen M, Wilson WG. 2006. The evolution of parasite manipulation of host dispersal. Proceedings of the Royal Society of London B: Biological Sciences. 273: 1063–1071. doi: 10.1098/rspb.2005.3412

[4] Vickery WL, Poulin R. 2010. The evolution of host manipulation by parasites: a game theory analysis. Evolutionary Ecology 24: 773–788. doi: 10.1007/s10682-009-9334-0

[5] Gandon S. 2017. Evolution and manipulation of vector host choice. bioRxiv 110577, ver. 3 of 7th June 2017. doi: 10.1101/110577

Many viruses are transmitted by biological vectors, i.e. organisms that transfer the virus from one host to another. Dengue virus (DENV) is one of them. Dengue is a mosquito-borne viral disease that has rapidly spread around the world since the 1940s. One recent estimate indicates 390 million dengue infections per year [1]. As many arthropod-borne vertebrate viruses, DENV has to cross several anatomical barriers in the vector, to multiply in its body and to invade its salivary glands before getting transmissible. As a consequence, vectors are not passive carriers but genuine hosts of the viruses that potentially have important effects on the composition of virus populations and, ultimately, on virus epidemiology and virulence. Within infected vectors, virus populations are expected to acquire new mutations and to undergo genetic drift and selection effects. However, the intensity of these evolutionary forces and the way they shape virus genetic diversity are poorly known.

In their study, Lequime et al. [2] finely disentangled the effects of genetic drift and selection on DENV populations during their infectious cycle within mosquito (Aedes aegypti) vectors. They evidenced that the genetic diversity of viruses within their vectors is shaped by genetic drift, selection and vector genotype. The experimental design consisted in artificial acquisition of purified virus by mosquitoes during a blood meal. The authors monitored the diversity of DENV populations in Ae. aegypti individuals at different time points by high-throughput sequencing (HTS). They estimated the intensity of genetic drift and selection effects exerted on virus populations by comparing the DENV diversity at these sampling time points with the diversity in the purified virus stock (inoculum).

Disentangling the effects of genetic drift and selection remains a methodological challenge because both evolutionary forces operate concomitantly and both reduce genetic diversity. However, selection reduces diversity in a reproducible manner among experimental replicates (here, mosquito individuals): the fittest variants are favoured at the expense of the weakest ones. In contrast, genetic drift reduces diversity in a stochastic manner among replicates. Genetic drift acts equally on all variants irrespectively of their fitness. The strength of genetic drift is frequently evaluated with the effective population size Ne: the lower Ne, the stronger the genetic drift [3]. The estimation of the effective population size of DENV populations by Lequime et al. [2] was based on single-nucleotide polymorphisms (SNPs) that were (i) present both in the inoculum and in the virus populations sampled at the different time points and (ii) that were neutral (or nearly-neutral) and therefore subjected to genetic drift only and insensitive to selection. As expected for viruses that possess small and constrained genomes, such neutral SNPs are extremely rare. Starting from a set of >1800 SNPs across the DENV genome, only three SNPs complied with the neutrality criteria and were enough represented in the sequence dataset for a precise Ne estimation. Using the method described by Monsion et al. [4], Lequime et al. [2] estimated Ne values ranging from 5 to 42 viral genomes (95% confidence intervals ranged from 2 to 161 founding viral genomes). Consequently, narrow bottlenecks occurred at the virus acquisition step, since the blood meal had allowed the ingestion of ca. 3000 infectious virus particles, on average. Interestingly, bottleneck sizes did not differ between mosquito genotypes. Monsion et al.’s [4] formula provides only an approximation of Ne. A corrected formula has been recently published [5]. We applied this exact Ne formula to the means and variances of the frequencies of the three neutral markers estimated before and after the bottlenecks (Table 1 in [2]), and nearly identical Ne estimates were obtained with both formulas.

Selection intensity was estimated from the dN/dS ratio between the nonsynonymous and synonymous substitution rates using the HTS data on DENV populations. DENV genetic diversity increased following initial infection but was restricted by strong purifying selection during virus expansion in the midgut. Again, no differences were detected between mosquito genotypes. However and importantly, significant differences in DENV genetic diversity were detected among mosquito genotypes. As they could not be related to differences in initial genetic drift or to selection intensity, the authors raise interesting alternative hypotheses, including varying rates of de novo mutations due to differences in replicase fidelity or differences in the balancing selection regime. Interestingly, they also suggest that this observation could simply result from a methodological issue linked to the detection threshold of low-frequency SNPs.
 

References

[1] Bhatt S, Gething PW, Brady OJ, Messina JP, Farlow AW, Moyes CL, Drake JM, et al. 2013. The global distribution and burden of dengue. Nature 496: 504–7 doi: 10.1038/nature12060

[2] Lequime S, Fontaine A, Gouilh MA, Moltini-Conclois I and Lambrechts L. 2016. Genetic drift, purifying selection and vector genotype shape dengue virus intra-host genetic diversity in mosquitoes. PloS Genetics 12: e1006111 doi: 10.1371/journal.pgen.1006111

[3] Charlesworth B. 2009. Effective population size and patterns of molecular evolution and variation. Nature Reviews Genetics 10: 195-205 doi: 10.1038/nrg2526

[4] Monsion B, Froissart R, Michalakis Y and Blanc S. 2008. Large bottleneck size in cauliflower mosaic virus populations during host plant colonization. PloS Pathogens 4: e1000174 doi: 10.1371/journal.ppat.1000174

[5] Thébaud G and Michalakis Y. 2016. Comment on ‘Large bottleneck size in cauliflower mosaic virus populations during host plant colonization’ by Monsion et al. (2008). PloS Pathogens 12: e1005512 doi: 10.1371/journal.ppat.1005512

The Ebola virus (EBOV) epidemic that started in December 2013 resulted in around 28,000 cases and more than 11,000 deaths. Since the emergence of the disease in Zaire in 1976 the virus had produced a number of outbreaks in Africa but until 2013 the reported numbers of human cases had never risen above 500. Could this exceptional epidemic size be due to the spread of a human-adapted form of the virus?

The large mutation rate of the virus [1-2] may indeed introduce massive amounts of genetic variation upon which selection may act. Several earlier studies based on the accumulation of genome sequences sampled during the epidemic led to contrasting conclusions. A few studies discussed evidence of positive selection on the glycoprotein that may be linked to phenotypic variations on infectivity and/or immune evasion [3-4]. But the heterogeneity in the transmission of some lineages could also be due to environmental heterogeneity and/or stochasticity. Most studies could not rule out the null hypothesis of the absence of positive selection and human adaptation [1-2 and 5].

In a recent experimental study, Urbanowicz et al. [6] chose a different method to tackle this question. A phylogenetic analysis of genome sequences from viruses sampled in West Africa revealed the existence of two main lineages (one with a narrow geographic distribution in Guinea, and the other with a wider geographic distribution) distinguished by a single amino acid substitution in the glycoprotein of the virus (A82V), and of several sub-lineages characterised by additional substitutions. The authors used this phylogenetic data to generate a panel of mutant pseudoviruses and to test their ability to infect human and fruit bat cells. These experiments revealed that specific amino acid substitutions led to higher infectivity of human cells, including A82V. This increased infectivity on human cells was associated with a decreased infectivity in fruit bat cell cultures. Since fruit bats are likely to be the reservoir of the virus, this paper indicates that human adaptation may have led to a specialization of the virus to a new host.

An accompanying paper in the same issue of Cell by Diehl et al. [7] reports results that confirm the trend identified by Urbanowicz et al. [6] and further indicate that the increased infectivity of A82V is specific for primate cells. Diehl et al. [7] also report some evidence for higher virulence of A82V in humans. In other words, the evolution of the virus may have led to higher abilities to infect and to kill its novel host. This work thus confirms the adaptive potential of RNA virus and the ability of Ebola to specialize to a novel host. In this context, the availability of an effective vaccine against the disease is particularly welcome [8].

The study of Urbanowicz et al. [6] is also remarkable because it illustrates the need of experimental approaches for the study of phenotypic variation when inference methods based on phylodynamics fail to extract a clear biological message. The analysis of genomic evolution is still in its infancy and there is a need for new theoretical developments to help detect more rapidly candidate mutations involved in adaptations to new environmental conditions.

References

[1] Gire, S.K., Goba, A., Andersen, K.G., Sealfon, R.S.G., Park, D.J., Kanneh, L., Jalloh, S., Momoh, M., Fullah, M., Dudas, G., et al. (2014). Genomic surveillance elucidates Ebola virus origin and transmission during the 2014 outbreak. Science 345, 1369–1372. doi: 10.1126/science.1259657
[2] Hoenen, T., Safronetz, D., Groseth, A., Wollenberg, K.R., Koita, O.A., Diarra, B., Fall, I.S., Haidara, F.C., Diallo, F., Sanogo, M., et al. (2015). Mutation rate and genotype variation of Ebola virus from Mali case sequences. Science 348, 117–119. doi: 10.1126/science.aaa5646
[3] Liu, S.-Q., Deng, C.-L., Yuan, Z.-M., Rayner, S., and Zhang, B. (2015). Identifying the pattern of molecular evolution for Zaire ebolavirus in the 2014 outbreak in West Africa. Infection, Genetics and Evolution 32, 51–59. doi: 10.1016/j.meegid.2015.02.024
[4] Holmes, E.C., Dudas, G., Rambaut, A., and Andersen, K.G. (2016). The evolution of Ebola virus: Insights from the 2013–2016 epidemic. Nature 538, 193–200. doi: 10.1038/nature19790
[5] Azarian, T., Lo Presti, A., Giovanetti, M., Cella, E., Rife, B., Lai, A., Zehender, G., Ciccozzi, M., and Salemi, M. (2015). Impact of spatial dispersion, evolution, and selection on Ebola Zaire Virus epidemic waves. Scientific Reports. 5, 10170. doi: 10.1038/srep10170
[6] Urbanowicz, R.A., McClure, C.P., Sakuntabhai, A., Sall, A.A., Kobinger, G., Müller, M.A., Holmes, E.C., Rey, F.A., Simon-Loriere, E., and Ball, J.K. (2016). Human adaptation of Ebola virus during the West African outbreak. Cell 167, 1079–1087. doi: 10.1016/j.cell.2016.10.013
[7] Diehl, W.E., Lin, A.E., Grubaugh, N.D., Carvalho, L.M., Kim, K., Kyawe, P.P., McCauley, S.M., Donnard, E., Kucukural, A., McDonel, P., et al. (2016). Ebola virus glycoprotein with increased infectivity dominated the 2013-2016 epidemic. Cell 167, 1088–1098. doi: 10.1016/j.cell.2016.10.014
[8] Henao-Restrepo, A.M., Camacho, A., Longini, I.M., Watson, C.H., Edmunds, W.J., Egger, M., Carroll, M.W., Dean, N.E., Diatta, I., Doumbia, M., et al. (2016). Efficacy and effectiveness of an rVSV-vectored vaccine in preventing Ebola virus disease: final results from the Guinea ring vaccination, open-label, cluster-randomised trial (Ebola Ça Suffit!). The Lancet 389, 505-518. doi: 10.1016/S0140-6736(16)32621-6

Adaptations to a new ecological niche allow species to access new resources and circumvent competitors and are hence obvious pathways of evolutionary success. The evolution of agricultural pest species represents an important case to study how a species adapts, on various timescales, to a novel ecological niche. Among the numerous insects that are agricultural pests, the ability to lay eggs (or oviposit) in ripe fruit appears to be a recurrent scenario. Fruit flies (family Tephritidae) employ this strategy, and include amongst their members some of the most destructive pests (e.g., the olive fruit fly Bactrocera olea or the medfly Ceratitis capitata). In their ms, Karageorgi et al. [1] studied how Drosophila suzukii, a new major agricultural pest species that recently invaded Europe and North America, evolved the novel behavior of laying eggs into undamaged fresh fruit. The close relatives of D. suzukii lay their eggs on decaying plant substrates, and thus this represents a marked change in host use that links to substantial economic losses to the fruit industry. Although a handful of studies have identified genetic changes causing new behaviors in various species, the question of the evolution of behavior remains a largely uncharted territory. The study by Karageorgi et al. [1] represents an original and most welcome contribution in this domain for a non-model species. Using clever behavioral experiments to compare D. suzukii to several related Drosophila species, and complementing those results with neurogenetics and mutant analyses using D. suzukii, the authors nicely dissect the sensory changes at the origin of the new egg-laying behavior. The experiments they describe are easy to follow, richly illustrate through figures and images, and particularly well designed to progressively decipher the sensory bases driving oviposition of D. suzukii on ripe fruit. Altogether, Karageorgi et al.’s [1] results show that the egg-laying substrate preference of D. suzukii has considerably evolved in concert with its morphology (especially its enlarged, serrated ovipositor that enables females to pierce the skin of many ripe fruits). Their observations clearly support the view that the evolution of traits that make D. suzukii an agricultural pest included the modification of several sensory systems (i.e. mechanosensation, gustation and olfaction). These differences between D. suzukii and its close relatives collectively underlie a radical change in oviposition behavior, and were presumably instrumental in the expansion of the ecological niche of the species. The authors tentatively propose a multi-step evolutionary scenario from their results with the emergence of D. suzukii as a pest species as final outcome. Such formalization represents an interesting evolutionary model-framework that obviously would rely upon further data and experiments to confirm and refine some of the evolutionary steps proposed, especially the final and recent transition of D. suzukii from non-invasive to invasive species.

References

[1] Karageorgi M, Bräcker LB, Lebreton S, Minervino C, Cavey M, Siju KP, Grunwald Kadow IC, Gompel N, Prud’homme B. 2017. Evolution of multiple sensory systems drives novel egg-laying behavior in the fruit pest Drosophila suzukii. Current Biology, 27: 1-7. doi: 10.1016/j.cub.2017.01.055