How do phenotypic plasticity and adaptive evolution interact in a novel or changing environment? Does evolution by natural selection generally reinforce initially plastic phenotypic responses, or does it instead oppose them? And to what extent does evolution of a trait involve evolution of its plasticity? These questions have lied at the heart of research on phenotypic evolution in heterogeneous environments ever since it was realized that the environment is likely to affect the expression of many (perhaps most) characters of an individual. Importantly, this broad definition of phenotypic plasticity as change in the average phenotype of a given genotype in response to its environment of development (or expression) does not involve any statement about the adaptiveness of the plastic changes. Theory on the evolution of plasticity has devoted much effort to understanding how reaction norm should evolve under different regimes of environmental change in space and time, and depending on genetic constraints on reaction norm shapes. However on an empirically ground, the questions above have mostly been addressed for individual traits, often chosen a priori for their likeliness to exhibit adaptive plasticity, and we still lack more systematic answers. These can be provided by so-called ‘phenomic’ approaches, where a large number of traits are tracked without prior information on their biological or ecological function. A problem is that the number of phenotypic characters that can be measured in an organism is virtually infinite (and to some extent arbitrary), and that scaling issues makes it difficult to compare different sets of traits. Gene-expression levels offer a partial solution to this dilemma, as they can be considered as a very large number of traits (one per typed gene) that can be measured easily and uniformly (fold change in the number of reads in RNAseq). As for any traits, expression levels of different genes may be genetically correlated, to an extent that depends on their regulation mechanism: cis-regulatory sequences that only affect expression of neighboring genes are likely to cause independent gene expression, while more systematic modifiers of expression (e.g. trans-regulators such as transcription factors) may cause correlated genetic responses of the expression of many genes. Huang and Agrawal [1] have studied plasticity and evolution of gene expression level in young larvae of populations of Drosophila melanogaster that have evolved for about 130 generations under either a constant environment (salt or cadmium), or an environment that is heterogeneous in time or space (combining salt and cadmium). They report a wealth of results, of which we summarize the most striking here. First, among genes that (i) were initially highly plastic and (ii) evolved significant divergence in expression levels between constant environment treatments, the evolved divergence is predominantly in the opposite direction to the initial plastic response. This suggests that either plasticity was initially maladaptive, or the selective pressure changed during the evolutionary process (see below). This somewhat unexpected result strikingly mirrors that from a study published last year in Nature [2], where the same pattern was found for responses of guppies to the presence of predators. However, Huang and Agrawal [1] went beyond this study by deciphering the underlying mechanisms in several interesting ways. First, they showed that change in gene expression often occurred at genes close to SNPs with differentiated frequencies across treatments (but not at genes with differentiated SNPs in their coding sequences), suggesting that cis-regulatory sequences are involved. This is also suggested by the fact that changes in gene expression are mostly caused by the increased expression of only one allele at polymorphic loci, and is a first step towards investigating the genetic underpinnings of (co)variation in gene expression levels. Another interesting set of findings concerns evolution of plasticity in treatments with variable environments. To compare the gene-expression plasticity that evolved in these treatments to an expectation, the authors considered that the expression levels in populations maintained for a long time under constant salt or cadmium had reached an optimum. The differences between these expression levels were thus assumed to predict the level of plasticity that should evolve in a heterogeneous environment (with both cadmium and salt) under perfect environmental predictability. The authors showed that plasticity did evolve more in the expected direction in heterogeneous than in constant environments, resulting in better adapted final expression levels across environments. Taken collectively, these results provide an unprecedented set of patterns that are greatly informative on how plasticity and evolution interact in constant versus changing environments. But of course, interpretations in terms of adaptive versus maladaptive plasticity are more challenging, as the authors themselves admit. Even though environmentally determined gene expression is the basic mechanism underlying the phenotypic plasticity of most traits, it is extremely difficult to relate to more integrated phenotypes for which we can understand the selection pressures, especially in multicellular organisms. The authors have recently investigated evolutionary change of quantitative traits in these selected lines, so it might be possible to establish links between reaction norms for macroscopic traits to those for gene expression levels. Such an approach would also involve tracking gene expression throughout life, rather than only in young larvae as done here, thus putting phenotypic complexity back in the picture also for expression levels. Another difficulty is that a plastic response that was originally adaptive may be replaced by an opposite evolutionary response in the long run, without having to invoke initially maladaptive plasticity. For instance, the authors mention the possibility that a generic stress response is initially triggered by cadmium, but is eventually unnecessary and costly after evolution of genetic mechanisms for cadmium detoxification (a case of so-called genetic accommodation). In any case, this study by Huang and Agrawal [1], together with the one by Ghalambor et al. last year [2], reports novel and unexpected results, which are likely to stimulate researchers interested in plasticity and evolution in heterogeneous environments for the years to come.

References

[1] Huang Y, Agrawal AF. 2016. Experimental Evolution of Gene Expression and Plasticity in Alternative Selective Regimes. PLoS Genetics 12:e1006336. doi: 10.1371/journal.pgen.1006336

[2] Ghalambor CK, Hoke KL, Ruell EW, Fischer EK, Reznick DN, Hughes KA. 2015. Non-adaptive plasticity potentiates rapid adaptive evolution of gene expression in nature. Nature 525: 372-375. doi: 10.1038/nature15256

It is a classical result in the virulence evolution literature that treatments decreasing parasite replication within the host should select for higher replication rates, thus driving increased levels of virulence if the two are correlated. There is some evidence for this in vitro but very little in the field. HIV infections in humans offer a unique opportunity to go beyond the simple predictions that treatments should favour more virulent strains because many details of this host-parasite system are known, especially the link between set-point virus load, transmission rate and virulence.

To tackle this question, Herbeck et al. [1] used a detailed individual-based model. This is original because it allows them to integrate existing knowledge from the epidemiology and evolution of HIV (e.g. recent estimates of the ‘heritability’ of set-point virus load from one infection to the next). This detailed model allows them to formulate predictions regarding the effect of different treatment policies; especially regarding the current policy switch away from treatment initiation based on CD4 counts towards universal treatment.

The results show that, perhaps as expected from the theory, treatments based on the level of remaining host target cells (CD4 T cells) do not affect virulence evolution because they do not strongly affect the virulence level that maximizes HIV’s transmission potential. However, early treatments can lead to moderate increase in virulence within several years if coverage is high enough. These results seem quite robust to variation of all the parameters in realistic ranges.

The great step forward in this model is the ability to obtain quantitative prediction regarding how a virus may evolve in response to public health policies. Here the main conclusion is that given our current knowledge in HIV biology, the risk of virulence evolution is perhaps more limited than expected from a direct application of virulence evolution model. Interestingly, the authors also conclude that recently observed increased in HIV virulence [2-3] cannot be explained by the impact of antiretroviral therapy alone; which raises the question about the main mechanism behind this increase. Finally, the authors make the interesting suggestion that “changing virulence is amenable to being monitored alongside transmitted drug resistance in sentinel surveillance”.

References

[1] Herbeck JT, Mittler JE, Gottlieb GS, Goodreau SM, Murphy JT, Cori A, Pickles M, Fraser C. 2016. Evolution of HIV virulence in response to widespread scale up of antiretroviral therapy: a modeling study. Virus Evolution 2:vew028. doi: 10.1093/ve/vew028

[2] Herbeck JT, Müller V, Maust BS, Ledergerber B, Torti C, et al. 2012. Is the virulence of HIV changing? A meta-analysis of trends in prognostic markers of HIV disease progression and transmission. AIDS 26:193-205. doi: 10.1097/QAD.0b013e32834db418

[3] Pantazis N, Porter K, Costagliola D, De Luca A, Ghosn J, et al. 2014. Temporal trends in prognostic markers of HIV-1 virulence and transmissibility: an observational cohort study. Lancet HIV 1:e119-26. doi: 10.1016/s2352-3018(14)00002-2

Evolution is usually studied via two distinct approaches: by inferring evolutionary processes from relatedness patterns among living species or by observing evolution in action in the laboratory or field. A recent study by Baym and colleagues in Science [1] has now combined these approaches by taking advantage of the pattern left behind by spatially evolving bacterial populations.

Evolution is often considered too slow to see, and can only be inferred by studying patterns of relatedness using phylogenetic trees. Increasingly, however, researchers are moving nature into the lab and watching as evolution unfolds under their noses. The field of experimental evolution follows evolutionary change in the laboratory over 10s to 1000s of generations, yielding insights into bacterial, viral, plant, or fly evolution (among many other species) that are simply not possible in the field. Yet, as powerful as experimental evolution is, it lacks a posterchild. There is no Galapagos finch radiation, nor a stunning series of cichlids to showcase to our students to pique their interests. Let’s face it, E. coli is no stickleback! And while practitioners of experimental evolution can explain the virtues of examining 60,000 generations of bacterial evolution in action, appreciating this nevertheless requires a level of insight and imagination that often eludes students, who need to see “it” to get it.

Enter MEGA, an idea and a film that could become the new face of experimental evolution. It replaces big numbers of generations or images of scientists, with an actual picture of the scientific result. MEGA, or Microbial Evolution and Growth Arena, is essentially an enormous petri dish and is the brainchild of Michael Baym, Tami Leiberman and their colleagues in Roy Kishony’s lab at Technion Israel Institute of Technology and Harvard Medical School. The idea of MEGA is to allow bacteria to swim over a spatially defined landscape while adapting to the local conditions, in this case antibiotics. When bacteria are inoculated onto one end of the plate they consume resources while swarming forward from the plate edge. In a few days, the bacteria grow into an area with antibiotics to which they are susceptible. This stops growth until a mutation arises that permits the bacteria to jump this hurdle, after which growth proceeds until the next hurdle of a 10-fold higher antibiotic concentration, and so on. By this simple approach, Baym et al. [1] evolved E. coli that were nearly 105-fold more resistant to two different antibiotics in just over 10 days. In addition, they identified the mutations that were required for these changes, showed that mutations conferring smaller benefits were required before bacteria could evolve maximal resistance, observed changes to the mutation rate, and demonstrated the importance of spatial structure in constraining adaptation.

For one thing, the rate of resistance evolution is impressive, and also quite scary given the mounting threat of antibiotic-resistant pathogens. However, MEGA also offers a uniquely visual insight into evolutionary change. By taking successive images of the MEGA plate, the group was able to watch the bacteria move, get trapped because of their susceptibility to the antibiotic, and then get past these traps as new mutations emerged that increased resistance. Each transition showcases evolution in real time. In addition, by leaving a spatial pattern of evolutionary steps behind, the MEGA plate offers unique opportunities to thoroughly investigate these steps when the experiment is finished. For instance, subsequent steps in mutational pathways can be characterized, but also their effects on fitness can be quantified in situ by measuring changes in survival and reproduction. This new method is undoubtedly a boon to the field of experimental evolution and offers endless opportunities for experimental elaboration. Perhaps of equal importance, MEGA is a tool that is portable to the classroom and to the public at large. Don’t believe in evolution? Watch this. You only have time for a short internship or lab practical? No problem. Don’t worry much about antibiotic resistance? Check this out. Like the best experimental tools, MEGA is simple but allows for complicated insights. And even if it is less charismatic than a finch, it still allows for the kinds of “gee-whiz” insights that will get students hooked on evolutionary biology.

Reference

[1] Baym M, Lieberman TD, Kelsic ED, Chait R, Gross R, Yelin I, Kishony R. 2016. Spatiotemporal microbial evolution on antibiotic landscapes. Science 353:1147-1151. doi: 10.1126/science.aag0822

It has long been known that most multicellular eukaryotes rely on microbial partners for a variety of functions including nutrition, immune reactions and defence against enemies. Lichens are probably the most popular example of a symbiosis involving a photosynthetic microorganism (an algae, a cyanobacteria or both) living embedded within the filaments of a fungus (usually an ascomycete). The latter is the backbone structure of the lichen, whereas the former provides photosynthetic products. Lichens are unique among symbioses because the structures the fungus and the photosynthetic microorganism form together do not resemble any of the two species living in isolation. Classic textbook examples like lichens are not often challenged and this is what Toby Spribille and his co-authors did with their paper published in July 2016 in Science [1]. This story started with the study of two species of macrolichens from the class of Lecanoromycetes that are commonly found in the mountains of Montana (US): Bryoria fremontii and B. tortuosa. For more than 90 years, these species have been known to differ in their chemical composition and colour, but studies performed so far failed in finding differences at the molecular level in both the mycobiont and the photobiont. These two species were therefore considered as nomenclatural synonyms, and the origin of their differences remained elusive. To solve this mystery, the authors of this work performed a transcriptome-wide analysis that, relative to previous studies, expanded the taxonomic range to all Fungi. This analysis revealed higher abundances of a previously unknown basidiomycete yeast from the genus Cyphobasidium in one of the lichen species, a pattern that was further confirmed by combining microscopy imaging and the fluorescent in situ hybridisation technique (FISH).

Finding out that a previously unknown micro-organism changes the colour and the chemical composition of an organism is surprising but not new. For instance, bacterial symbionts are able to trigger colour changes in some insect species [2], and endophyte fungi are responsible for the production of defensive compounds in the leaves of several grasses [3]. The study by Spribille and his co-authors is fascinating because it demonstrates that Cyphobasidium yeasts have played a key role in the evolution and diversification of Lecanoromycetes, one of the most diverse classes of macrolichens. Indeed these basidiomycete yeasts were not only found in Bryoria but in 52 other lichen genera from all six continents, and these included 42 out of 56 genera in the family Parmeliaceae. Most of these sequences formed a highly supported monophyletic group, and a molecular clock revealed that the origin of many macrolichen groups occurred around the same time Cyphobasidium yeasts split from Cystobasidium, their nearest relatives. This newly discovered passenger is therefore an ancient inhabitant of lichens and has driven the evolution of this emblematic group of organisms.

This study raises an important question on the stability of complex symbiotic partnerships. In intimate obligatory symbioses the evolutionary interests of both partners are often identical and what is good for one is also good for the other. This is the case of several insects that feed on poor diets like phloem and xylem sap, and which carry vertically-transmitted symbionts that provide essential nutrients. Molecular phylogenetic studies have repeatedly shown that in several insect groups transition to phloem or xylem feeding occurred at the same time these nutritional symbionts were acquired [4]. In lichens, an outstanding question is to know what was the key feature Cyphobasidium yeasts brought to the symbiosis. As suggested by the authors, these yeasts are likely to be involved in the production of secondary defensive metabolites and architectural structures, but, are these services enough to explain the diversity found in macrolichens? This paper is an appealing example of a multipartite symbiosis where the different partners share an ancient evolutionary history.

References

[1] Spribille T, Tuovinen V, Resl P, et al. 2016. Basidiomycete yeasts in the cortex of ascomycete macrolichens. Science 353:488–92. doi: 10.1126/science.aaf8287

[2] Tsuchida T, Koga R, Horikawa M, et al. 2010. Symbiotic Bacterium Modifies Aphid Body Color. Science 330:1102–1104. doi: 10.1126/science.1195463

[3] Clay K. 1988. Fungal Endophytes of Grasses: A Defensive Mutualism between Plants and Fungi. Ecology 69:10–16. doi: 10.2307/1943155

[4] Moran NA. 2007. Symbiosis as an adaptive process and source of phenotypic complexity. Proceeding of the National Academy of Science USA 104:8627–8633. doi: 10.1073/pnas.0611659104

As plants cannot run from their enemies, natural selection has favoured the evolution of diverse chemical compounds (phytochemicals) to protect them against herbivores and pathogens. This provides an opportunity for plant feeders to exploit these compounds to combat their own enemies. Indeed, it is widely known that herbivores use such compounds as protection against predators [1]. Recently, this reasoning has been extended to pathogens, and elegant studies have shown that some herbivores feed on phytochemical-containing plants reducing both parasite abundance within hosts [2] and their virulence [3].
Suffering less from parasites is clearly beneficial for infected herbivores. Why then, is this behaviour not fixed in nature? There are, at least, two possible explanations. First, feeding on ‘medicinal’, often toxic, plants may impose costs upon uninfected individuals. Second, parasites may evolve resistance to such chemicals. Whereas the first possibility has been explored, and is taken as evidence for ‘self-medication’ [3], the second hypothesis requires investigation. A recent study by Palmer-Young et al. [4] fills this gap. This article reports evolution of resistance to two different phytochemicals, alone and in combination, in the trypanosome Crithidia bombi, a bumble bee (Bombus impatiens) parasite. To show this, the authors experimentally evolved a strain of C. bombi in the presence of thymol, eugenol or both simultaneously. These phytochemicals are commonly found in the nectar of several plant species, in particular those of the Lamiaceae, a family containing several aromatic herbs. Prior to selection both phytochemicals reduced C. bombi growth by about 50%. However, C. bombi rapidly evolved resistance in both single and the double phytochemical treatments. Moreover, no cost of resistance was detected when evolved parasites were placed in the ancestral, phytochemical-free environment. Therefore, resistance to phytochemicals would be expected to spread rapidly in natural populations of C. bombi. Clearly, thus, the herbivore strategy of sequestering plant secondary chemical compounds as a defence against their pathogens should fail. The question then is ‘why do they still do it’? Can self-medication work in the longer-term for bumblebees?
Well, yes. The very fact that resistance evolved shows that resistance is not fixed in natural C. bombi populations. This is surprising considering that resistance is not costly. This might be due to a number of reasons. Firstly, there may be costs of resistance that were not detected in this experiment. Second, it may not be possible to evolve universal resistance to the heterogeneity present in the phytochemical environment. Indeed, phytochemical environments are highly varied in time and space and bumblebees will visit different plants presenting different phytochemical cocktails throughout the season. Furthermore, migration of bees from populations exposed to different phytochemicals may prevent the fixation of one resistance type.
Or, it may be self-medication behaviour itself that prevents the evolution of resistance? Indeed, in the same way that infected bees seek cooler temperatures to slow growth of a parasitoid fly [5], they may also seek a more varied diet with diverse phytochemicals to which the parasite cannot evolve, but which reduces parasite growth. Further understanding of arthropod self-medication may thus be instrumental to prevent the observed worldwide decline of pollinators [6]. Furthermore, it may inform on mechanisms that prevent rapid evolution of drug resistance in other systems.

References

[1] Duffey SS. 1980. Sequestration of plant natural products by insects. Annual Review of Entomology 25: 447-477. doi: 10.1146/annurev.en.25.010180.002311

[2] Richardson LL et al. 2015. Secondary metabolites in floral nectar reduce parasite infections in bumblebees. Proceedings of the Royal Society of London B 282: 20142471. doi: 10.1098/rspb.2014.2471

[3] Lefèvre T et al. 2010. Evidence for trans-generational medication in nature. Ecology Letters 13: 1485-93. doi: 10.1111/j.1461-0248.2010.01537.x

[4] Palmer-Young EC, Sadd BM, Adler LS. 2017. Evolution of resistance to single and combined floral phytochemicals by a bumble bee parasite. Journal of Evolutionary Biology 30: 300-312. doi: 10.1111/jeb.13002

[5] Müller CB, Schmid-Hempel P. 1993. Exploitation of cold temperature as defence against parasitoids in bumblebees. Nature 363: 65-67. doi: 10.1038/363065a0

[6] Potts SG et al. 2010. Global pollinator declines: trends, impacts and drivers. Trends in Ecology and Evolution 25: 345-353. doi: 10.1016/j.tree.2010.01.007