Response to “Vast (but avoidable) underestimation of global biodiversity”

This Formal Comment provides clarifications on the authors’ recent estimates of global bacterial diversity and the current status of the field, and responds to a Formal Comment from John Wiens regarding their prior work.

We welcome Wiens’ efforts to estimate global animal-associated bacterial richness and thank him for highlighting points of confusion and potential caveats in our previous work on the topic [1]. We find Wiens’ ideas worthy of consideration, as most of them represent a step in the right direction, and we encourage lively scientific discourse for the advancement of knowledge. Time will ultimately reveal which estimates, and underlying assumptions, came closest to the true bacterial richness; we are excited and confident that this will happen in the near future thanks to rapidly increasing sequencing capabilities. Here, we provide some clarifications on our work, its relation to Wiens’ estimates, and the current status of the field.First, Wiens states that we excluded animal-associated bacterial species in our global estimates. However, thousands of animal-associated samples were included in our analysis, and this was clearly stated in our main text (second paragraph on page 3).Second, Wiens’ commentary focuses on “S1 Text” of our paper [1], which was rather peripheral, and, hence, in the Supporting information. S1 Text [1] critically evaluated the rationale underlying previous estimates of global bacterial operational taxonomic unit (OTU) richness by Larsen and colleagues [2], but the results of S1 Text [1] did not in any way flow into the analyses presented in our main article. Indeed, our estimates of global bacterial (and archaeal) richness, discussed in our main article, are based on 7 alternative well-established estimation methods founded on concrete statistical models, each developed specifically for richness estimates from multiple survey data. We applied these methods to >34,000 samples from >490 studies including from, but not restricted to, animal microbiomes, to arrive at our global estimates, independently of the discussion in S1 Text [1].Third, Wiens’ commentary can yield the impression that we proposed that there are only 40,100 animal-associated bacterial OTUs and that Cephalotes in particular only have 40 associated bacterial OTUs. However, these numbers, mentioned in our S1 Text [1], were not meant to be taken as proposed point estimates for animal-associated OTU richness, and we believe that this was clear from our text. Instead, these numbers were meant as examples to demonstrate how strongly the estimates of animal-associated bacterial richness by Larsen and colleagues [2] would decrease simply by (a) using better justified mathematical formulas, i.e., with the same input data as used by Larsen and colleagues [2] but founded on an actual statistical model; (b) accounting for even minor overlaps in the OTUs associated with different animal genera; and/or (c) using alternative animal diversity estimates published by others [3], rather than those proposed by Larsen and colleagues [2]. Specifically, regarding (b), Larsen and colleagues [2] (pages 233 and 259) performed pairwise host species comparisons within various insect genera (for example, within the Cephalotes) to estimate on average how many bacterial OTUs were unique to each host species, then multiplied that estimate with their estimated number of animal species to determine the global animal-associated bacterial richness. However, since their pairwise host species comparisons were restricted to congeneric species, their estimated number of unique OTUs per host species does not account for potential overlaps between different host genera. Indeed, even if an OTU is only found “in one” Cephalotes species, it might not be truly unique to that host species if it is also present in members of other host genera. To clarify, we did not claim that all animal genera can share bacterial OTUs, but instead considered the implications of some average microbiome overlap (some animal genera might share no bacteria, and other genera might share a lot). The average microbiome overlap of 0.1% (when clustering bacterial 16S sequences into OTUs at 97% similarity) between animal genera used in our illustrative example in S1 Text [1] is of course speculative, but it is not unreasonable (see our next point). A zero overlap (implicitly assumed by Larsen and colleagues [2]) is almost certainly wrong. One goal of our S1 Text [1] was to point out the dramatic effects of such overlaps on animal-associated bacterial richness estimates using “basic” mathematical arguments.Fourth, Wiens’ commentary could yield the impression that existing data are able to tell us with sufficient certainty when a bacterial OTU is “unique” to a specific animal taxon. However, so far, the microbiomes of only a minuscule fraction of animal species have been surveyed. One can thus certainly not exclude the possibility that many bacterial OTUs currently thought to be “unique” to a certain animal taxon are eventually also found in other (potentially distantly related) animal taxa, for example, due to similar host diets and or environmental conditions [4–7]. As a case in point, many bacteria in herbivorous fish guts were found to be closely related to bacteria in mammals [8], and Song and colleagues [6] report that bat microbiomes closely resemble those of birds. The gut microbiome of caterpillars consists mostly of dietary and environmental bacteria and is not species specific [4]. Even in animal taxa with characteristic microbiota, there is a documented overlap across host species and genera. For example, there are a small number of bacteria consistently and specifically associated with bees, but these are found across bee genera at the level of the 99.5% similar 16S rRNA OTUs [5]. To further illustrate that an average microbiome overlap between animal taxa at least as large as the one considered in our S1 Text (0.1%) [1] is not unreasonable, we analyzed 16S rRNA sequences from the Earth Microbiome Project [6,9] and measured the overlap of microbiota originating from individuals of different animal taxa. We found that, on average, 2 individuals from different host classes (e.g., 1 mammalian and 1 avian sample) share 1.26% of their OTUs (16S clustered at 100% similarity), and 2 individuals from different host genera belonging to the same class (e.g., 2 mammalian samples) share 2.84% of their OTUs (methods in S1 Text of this response). A coarser OTU threshold (e.g., 97% similarity, considered in our original paper [1]) would further increase these average overlaps. While less is known about insect microbiomes, there is currently little reason to expect a drastically different picture there, and, as explained in our S1 Text [1], even a small average microbiome overlap of 0.1% between host genera would strongly limit total bacterial richness estimates. The fact that the accumulation curve of detected bacterial OTUs over sampled insect species does not yet strongly level off says little about where the accumulation curve would asymptotically converge; rigorous statistical methods, such as the ones used for our global estimates [1], would be needed to estimate this asymptote.Lastly, we stress that while the present conversation (including previous estimates by Louca and colleagues [1], Larsen and colleagues [2], Locey and colleagues [10], Wiens’ commentary, and this response) focuses on 16S rRNA OTUs, it may well be that at finer phylogenetic resolutions, e.g., at bacterial strain level, host specificity and bacterial richness are substantially higher. In particular, future whole-genome sequencing surveys may well reveal the existence of far more genomic clusters and ecotypes than 16S-based OTUs.     

Dredging in the Spratly Islands: Gaining Land but Losing Reefs

Coral reefs on remote islands and atolls are less exposed to direct human stressors but are becoming increasingly vulnerable because of their development for geopolitical and military purposes. Here we document dredging and filling activities by countries in the South China Sea, where building new islands and channels on atolls is leading to considerable losses of, and perhaps irreversible damages to, unique coral reef ecosystems. Preventing similar damage across other reefs in the region necessitates the urgent development of cooperative management of disputed territories in the South China Sea. We suggest using the Antarctic Treaty as a positive precedent for such international cooperation.Coral reefs constitute one of the most diverse, socioeconomically important, and threatened ecosystems in the world [1–3]. Coral reefs harbor thousands of species [4] and provide food and livelihoods for millions of people while safeguarding coastal populations from extreme weather disturbances [2,3]. Unfortunately, the world’s coral reefs are rapidly degrading [1–3], with ~19% of the total coral reef area effectively lost [3] and 60% to 75% under direct human pressures [3,5,6]. Climate change aside, this decline has been attributed to threats emerging from widespread human expansion in coastal areas, which has facilitated exploitation of local resources, assisted colonization by invasive species, and led to the loss and degradation of habitats directly and indirectly through fishing and runoff from agriculture and sewage systems [1–3,5–7]. In efforts to protect the world’s coral reefs, remote islands and atolls are often seen as reefs of “hope,” as their isolation and uninhabitability provide de facto protection against direct human stressors, and may help impacted reefs through replenishment [5,6]. Such isolated reefs may, however, still be vulnerable because of their geopolitical and military importance (e.g., allowing expansion of exclusive economic zones and providing strategic bases for military operations). Here we document patterns of reclamation (here defined as creating new land by filling submerged areas) of atolls in the South China Sea, which have resulted in considerable loss of coral reefs. We show that conditions are ripe for reclamation of more atolls, highlighting the need for international cooperation in the protection of these atolls before more unique and ecologically important biological assets are damaged, potentially irreversibly so.Studies of past reclamations and reef dredging activities have shown that these operations are highly deleterious to coral reefs [8,9]. First, reef dredging affects large parts of the surrounding reef, not just the dredged areas themselves. For example, 440 ha of reef was completely destroyed by dredging on Johnston Island (United States) in the 1960s, but over 2,800 ha of nearby reefs were also affected [10]. Similarly, at Hay Point (Australia) in 2006 there was a loss of coral cover up to 6 km away from dredging operations [11]. Second, recovery from the direct and indirect effects of dredging is slow at best and nonexistent at worst. In 1939, 29% of the reefs in Kaneohe Bay (United States) were removed by dredging, and none of the patch reefs that were dredged had completely recovered 30 years later [12]. In Castle Harbour (Bermuda), reclamation to build an airfield in the early 1940s led to limited coral recolonization and large quantities of resuspended sediments even 32 years after reclamation [13]; several fish species are claimed extinct as a result of this dredging [14,15]. Such examples and others led Hatcher et al. [8] to conclude that dredging and land clearing, as well as the associated sedimentation, are possibly the most permanent of anthropogenic impacts on coral reefs.The impacts of dredging for the Spratly Islands are of particular concern because the geographical position of these atolls favors connectivity via stepping stones for reefs over the region [16–19] and because their high biodiversity works as insurance for many species. In an extensive review of the sparse and limited data available for the region, Hughes et al. [20] showed that reefs on offshore atolls in the South China Sea were overall in better condition than near-shore reefs. For instance, by 2004 they reported average coral covers of 64% for the Spratly Islands and 68% for the Paracel Islands. By comparison, coral reefs across the Indo-Pacific region in 2004 had average coral covers below 25% [21]. Reefs on isolated atolls can still be prone to extensive bleaching and mortality due to global climate change [22] and, in the particular case of atolls in the South China Sea, the use of explosives and cyanine [20]. However, the potential for recovery of isolated reefs to such stressors is remarkable. Hughes et al. [20] documented, for instance, how coral cover in several offshore reefs in the region declined from above 80% in the early 1990s to below 6% by 1998 to 2001 (due to a mixture of El Niño and damaging fishing methods that make use of cyanine and explosives) but then recovered to 30% on most reefs and up to 78% in some reefs by 2004–2008. Another important attribute of atolls in the South China Sea is the great diversity of species. Over 6,500 marine species are recorded for these atolls [23], including some 571 reef coral species [24] (more than half of the world’s known species of reef-building corals). The relatively better health and high diversity of coral reefs in atolls over the South China Sea highlights the uniqueness of such reefs and the important roles they may play for reefs throughout the entire region. Furthermore, these atolls are safe harbor for some of the last viable populations of highly threatened species (e.g., Bumphead Parrotfish [Bolbometopon muricatum] and several species of sawfishes [Pristis, Anoxypristis]), highlighting how dredging in the South China Sea may threaten not only species with extinction but also the commitment by countries in the region to biodiversity conservation goals such as the Convention of Biological Diversity Aichi Targets and the United Nations Sustainable Development Goals.Recently available remote sensing data (i.e., Landsat 8 Operational Land Imager and Thermal Infrared Sensors Terrain Corrected images) allow quantification of the sharp contrast between the gain of land and the loss of coral reefs resulting from reclamation in the Spratly Islands (Fig 1). For seven atolls recently reclaimed by China in the Spratly Islands (names provided in Fig 1D, S1 Data for details); the area of reclamation is the size of visible areas in Landsat band 6, as prior to reclamation most of the atolls were submerged, with the exception of small areas occupied by a handful of buildings on piers (note that the amount of land area was near zero at the start of the reclamation; Fig 1C, S1 Data). The seven reclaimed atolls have effectively lost ~11.6 km² (26.9%) of their reef area for a gain of ~10.7 km² of land (i.e., >75 times increase in land area) from February 2014 to May 2015 (Fig 1C). The area of land gained was smaller than the area of reef lost because reefs were lost not only through land reclamation but also through the deepening of reef lagoons to allow boat access (Fig 1B). Similar quantification of reclamation by other countries in the South China Sea (Fig 1Reclamation leads to gains of land in return for losses of coral reefs: A case example of China’s recent reclamation in the Spratly Islands.Table 1List of reclaimed atolls in the Spratly Islands and the Paracel Islands.The impacts of reclamation on coral reefs are likely more severe than simple changes in area, as reclamation is being achieved by means of suction dredging (i.e., cutting and sucking materials from the seafloor and pumping them over land). With this method, reefs are ecologically degraded and denuded of their structural complexity. Dredging and pumping also disturbs the seafloor and can cause runoff from reclaimed land, which generates large clouds of suspended sediment [11] that can lead to coral mortality by overwhelming the corals’ capacity to remove sediments and leave corals susceptible to lesions and diseases [7,9,25]. The highly abrasive coralline sands in flowing water can scour away living tissue on a myriad of species and bury many organisms beyond their recovery limits [26]. Such sedimentation also prevents new coral larvae from settling in and around the dredged areas, which is one of the main reasons why dredged areas show no signs of recovery even decades after the initial dredging operations [9,12,13]. Furthermore, degradation of wave-breaking reef crests, which make reclamation in these areas feasible, will result in a further reduction of coral reefs’ ability to (1) self-repair and protect against wave abrasion [27,28] (especially in a region characterized by typhoons) and (2) keep up with rising sea levels over the next several decades [29]. This suggests that the new islands would require periodic dredging and filling, that these reefs may face chronic distress and long-term ecological damage, and that reclamation may prove economically expensive and impractical.The potential for land reclamation on other atolls in the Spratly Islands is high, which necessitates the urgent development of cooperative management of disputed territories in the South China Sea. First, the Spratly Islands are rich in atolls with similar characteristics to those already reclaimed (Fig 1D); second, there are calls for rapid development of disputed territories to gain access to resources and increase sovereignty and military strength [30]; and third, all countries with claims in the Spratly Islands have performed reclamation in this archipelago (20]. One such possibility is the generation of a multinational marine protected area [16,17]. Such a marine protected area could safeguard an area of high biodiversity and importance to genetic connectivity in the Pacific, in addition to promoting peace in the region (extended justification provided by McManus [16,17]). A positive precedent for the creation of this protected area is that of Antarctica, which was also subject to numerous overlapping claims and where a recently renewed treaty froze national claims, preventing large-scale ecological damage while providing environmental protection and areas for scientific study. Development of such a legal framework for the management of the Spratly Islands could prevent conflict, promote functional ecosystems, and potentially result in larger gains (through spillover, e.g. [31]) for all countries involved.     

Gauging the Purported Costs of Public Data Archiving for Long-Term Population Studies

It was recently proposed that long-term population studies be exempted from the expectation that authors publicly archive the primary data underlying published articles. Such studies are valuable to many areas of ecological and evolutionary biological research, and multiple risks to their viability were anticipated as a result of public data archiving (PDA), ultimately all stemming from independent reuse of archived data. However, empirical assessment was missing, making it difficult to determine whether such fears are realistic. I addressed this by surveying data packages from long-term population studies archived in the Dryad Digital Repository. I found no evidence that PDA results in reuse of data by independent parties, suggesting the purported costs of PDA for long-term population studies have been overstated.Data are the foundation of the scientific method, yet individual scientists are evaluated via novel analyses of data, generating a potential conflict of interest between a research field and its individual participants that is manifested in the debate over access to the primary data underpinning published studies [1–5]. This is a chronic issue but has become more acute with the growing expectation that researchers publish the primary data underlying research reports (i.e., public data archiving [PDA]). Studies show that articles publishing their primary data are more reliable and accrue more citations [6,7], but a recent opinion piece by Mills et al. [2] highlighted the particular concerns felt by some principal investigators (PIs) of long-term population studies regarding PDA, arguing that unique aspects of such studies render them unsuitable for PDA. The "potential costs to science" identified by Mills et al. [2] as arising from PDA are as follows:

• Publication of flawed research resulting from a "lack of understanding" by independent researchers conducting analyses of archived data
• Time demands placed on the PIs of long-term population studies arising from the need to correct such errors via, e.g., published rebuttals
• Reduced opportunities for researchers to obtain the skills needed for field-based data collection because equivalent long-term population studies will be rendered redundant
• Reduced number of collaborations
• Inefficiencies resulting from repeated assessment of a hypothesis using a single dataset

Each "potential cost" is ultimately predicated on the supposition that reuse of archived long-term population data is common, yet the extent to which this is true was not evaluated. To assess the prevalence of independent reuse of archived data—and thereby examine whether the negative consequences of PDA presented by Mills et al. [2] may be realised—I surveyed datasets from long-term population studies archived in the Dryad Digital Repository (hereafter, Dryad). Dryad is an online service that hosts data from a broad range of scientific disciplines, but its content is dominated by submissions associated with ecological and evolutionary biological research [8]. I examined all the Dryad packages associated with studies from four journals featuring ecological or evolutionary research: The American Naturalist, Evolution, Journal of Evolutionary Biology, and Proceedings of the Royal Society B: Biological Sciences (the latter referred to hereafter as Proceedings B). These four journals together represent 23.3% of Dryad''s contributed packages (as of early February 2016). Mills et al. [2] refer to short- versus long-term studies but do not provide a definition of this dichotomy. However, the shortest study represented by their survey lasted for 5 years, so I used this as the minimum time span for inclusion in my survey. This cut-off seems reasonable, as it will generally exclude studies resulting from single projects, such that included datasets likely relate to studies resulting from a sustained commitment on the part of researchers—although one included package contains data gathered via “citizen science” [9], and two others contain data derived from archived human population records [10,11]. However, as these datasets cover extended time spans and were used to address ecological questions [12–14], they were retained in my survey sample. Following Mills et al. [2], my focus was on population studies conducted in natural (or seminatural) settings, so captive populations were excluded. Because I was assessing the reuse of archived data, I excluded packages published by Dryad after 2013: authors can typically opt to impose a 1-year embargo, and articles based on archived data will themselves take some time to be written and published.Of the 1,264 archived data packages linked to one of the four journals and published on the Dryad website before 2014, 72 were identified as meeting the selection criteria. This sample represents a diverse range of taxa (Fig 1) and is comparable to the 73 studies surveyed by Mills et al. [2], although my methodology permits individual populations to be represented more than once, since the survey was conducted at the level of published articles (S1 Table). Of these 72 data packages, five had long-term embargoes remaining active (three packages with 5-year embargoes [15–17]; two packages with 10-year embargoes [18,19]). For two of these [17,19], the time span of the study could not be estimated because this information is not provided in the associated articles [20,21]. For a third package [22], the archived data indicated 10 years were represented (dummy coding was used to disguise factor level identities, including for year), yet the text of the associated paper suggests data collection covered a considerably greater time span [23]. However, since the study period is not stated in the text, I followed the archived data [22] in assuming data collection spanned a 10-year period. The distribution of study time spans is shown in Fig 2.Open in a separate windowFig 1Taxonomic representation of the 72 data packages included in the survey.The number of packages for each taxon is given in parentheses (note: one data package included data describing both insects and plants [9], while other data packages represented multiple species within a single taxonomic category).Open in a separate windowFig 2The study periods of the 70 data packages included in the survey for which this could be calculated.For each year from 2000 to 2004, these four journals contributed no more than a single data package to Dryad between them. However, around the time that the Joint Data Archiving Policy (JDAP; [24]) was adopted by three of these, we see a surge in PDA by ecologists and evolutionary biologists (Fig 3), such that in 2015 these four journals were collectively represented by 709 data packages. Of course, Mills et al. [2] argue against mandatory archiving of primary data for long-term studies in particular. For this subset of articles published in these four journals, the same pattern is observed: prior to adoption of the JDAP, only two data packages associated with long-term studies had been archived in Dryad, but following the implementation of the JDAP as a condition of publication in The American Naturalist, Evolution, and Journal of Evolutionary Biology, there is a rapid increase in the number of data packages being archived, despite the continuing availability of alternative venues should authors wish to avoid the purported costs of PDA as Mills et al. [2] contend. As the editorial policy of Proceedings B has shifted towards an increasingly strong emphasis on PDA (it is now mandatory), there has similarly been an increase in the representation of articles from this journal in Dryad, both overall (Fig 3) and for long-term studies in particular (Fig 4). These observations suggest that authors rarely chose to publicly archive their data prior to the adoption of PDA policies by journals and that uptake of PDA spread rapidly once it became a prerequisite for publication. In this respect, researchers using long-term population studies are no different to those in other scientific fields, despite the assertion by Mills et al. [2] that they are a special case owing to the complexity of their data. In reality, researchers in many other scientific disciplines also seek to identify relationships within complex systems. Within neuroscience, for example, near-identical objections to PDA were raised at the turn of the century [25], while archiving of genetic and protein sequences by molecular biologists has yielded huge advances but was similarly resisted until revised journal policies stimulated a change in culture [1,26].Open in a separate windowFig 3Total number of data packages archived in the Dryad Digital Repository each year for four leading journals within ecology and evolutionary biology.Arrow indicates when the Joint Data Archiving Policy (JDAP) was adopted by Evolution, Journal of Evolutionary Biology, and The American Naturalist. Note that because data packages are assigned a publication date by Dryad prior to journal publication (even if an embargo is imposed), some data packages will have been published in the year preceding the journal publication of their associated article.Open in a separate windowFig 4Publication dates of the 72 data packages from long-term study populations that were included in the survey.A primary concern raised by opponents of PDA is that sharing their data will see them “scooped” by independent researchers [6,8,27–30]. To quantify this risk for researchers maintaining long-term population studies, I used the Web of Science (wok.mimas.ac.uk) to search for citations of each data package (as of November 2015). For the 67 Dryad packages that were publicly accessible, none were cited by any article other than that from which it was derived. However, archived data could conceivably have been reused without the data package being cited, so I examined all journal articles that cited the study report associated with each data package (median citation count: 9; range: 0–58). Although derived metrics from the main articles were occasionally included in quantitative reviews [31,32] or formal meta-analyses [33], I again found no examples of the archived data being reused by independent researchers. As a third approach, I emailed the corresponding author(s) listed for each article, to ask if they were themselves aware of any examples. The replies I received (n = 35) confirmed that there were no known cases of long-term population data being independently reused in published articles. The apparent concern of some senior researchers that PDA will see them "collect data for 30 years just to be scooped" [30] thus lacks empirical support. It should also be noted that providing primary data upon request precedes PDA as a condition of acceptance for most major scientific journals [8]. PDA merely serves to ensure that authors meet this established commitment, a step made necessary by the failure rate that is otherwise observed, even after the recent revolution in communications technology [34–36]. As my survey shows, in practice the risk of being scooped is a monster under the bed: empirical assessment fails to justify the level of concern expressed. While long-term population studies are unquestionably a highly valuable resource for ecologists [2,37–39] and will likely continue to face funding challenges [37–39], there is no empirical support for the contention of Mills et al. [2] that PDA threatens their viability, although this situation may deserve reassessment in the future if the adoption of PDA increases within ecology and evolutionary biology. Nonetheless, in the absence of assessments over longer time frames (an inevitable result of the historical reluctance to adopt PDA), my survey results raise doubts over the validity of arguments favouring extended embargoes for archived data [29,40], and particularly the suggestion that multidecadal embargoes should be facilitated for long-term studies [2,41].Authors frequently assert that unique aspects of their long-term study render it especially well suited to addressing particular issues. Such claims contradict the suggestion that studies will become redundant if PDA becomes the norm [2] while simultaneously highlighting the necessity of making primary data available for meaningful evaluation of results. For research articles relying on data collected over several decades, independent replication is clearly impractical, such that reproducibility (the ability for a third party to replicate the results exactly [42]) is rendered all the more crucial. Besides permitting independent validation of the original results, PDA allows assessment of the hypotheses using alternative analytical methods (large datasets facilitate multiple analytical routes to test a single biological hypothesis, which likely contributes to poor reproducibility [43]) and reassessment if flaws in the original methodology later emerge [44]. Although I was not attempting to use archived data to replicate published results, and thus did not assess the contents of each package in detail, at least six packages [10,45–49] failed to provide the primary data underlying their associated articles, including a quantitative genetic study [50] for which only pedigree information was archived [47]. This limits exploration of alternative statistical approaches to the focal biological hypothesis and impedes future applications of the data that may be unforeseeable by the original investigators (a classic example being Bumpus'' [51] dataset describing house sparrow survival [52]), but it seems to be a reality of PDA within ecology and evolution at present [53].The "solutions" proffered by Mills et al. [2] are, in reality, alternatives to PDA that would serve to maintain the status quo with respect to data accessibility for published studies (i.e., subject to consent from the PI). This is a situation that is widely recognised to be failing with respect to the availability of studies'' primary data [34–36,54]. Indeed, for 19% (13 of 67 nonembargoed studies) of the articles represented in my survey, the correspondence email addresses were no longer active, highlighting how rapidly access to long-term primary data can be passively lost. It is unsurprising, then, that 95% of scientists in evolution and ecology are reportedly in favour of PDA [1]. Yet, having highlighted the value and irreplaceability of data describing long-term population studies, Mills et al. [2] reject PDA in favour of allowing PIs to maintain postpublication control of primary data, going so far as to discuss the possibility of data being copyrighted. Such an attitude risks inviting public ire, since asserting private ownership ignores the public funding that likely enabled data collection, and is at odds with a Royal Society report urging scientists to "shift away from a research culture where data is viewed as a private preserve" [55]. I contend that primary data would better be considered as an intrinsic component of a published article, alongside the report appearing in the pages of a journal that presents the data''s interpretation. In this way, an article would move closer to being a self-contained product of research that is fully accessible and assessable. For issues that can only be addressed using data covering an extended time span [2,37–39], excusing long-term studies from the expectation of publishing primary data would potentially render the PIs as unaccountable gatekeepers of scientific consensus. PDA encourages an alternative to this and facilitates a change in the treatment of published studies, from the system of preservation (in which a study''s contribution is fixed) that has been the historical convention, towards a conservation approach (in which support for hypotheses can be reassessed and updated) [56]. Given the fundamentally dynamic nature of science, harnessing the storage potential enabled by the Information Age to ensure a study''s contribution can be further developed or refined in the future seems logical and would benefit both the individual authors (through enhanced citations and reputation) and the wider scientific community.The comparison Mills et al. [2] draw between PIs and pharmaceutical companies in terms of how their data are treated is inappropriate: whereas the latter bear the financial cost of developing a drug, a field study''s costs are typically covered by the public purse, such that the personal risks of a failed project are largely limited to opportunity costs. It is inconsistent to highlight funding challenges [2,37] while simultaneously acting to inhibit maximum value for money being derived from funded studies. Several of the studies represented in the survey by Mills et al. [2] comfortably exceed a 50-year time span, highlighting the possibility that current PIs are inheritors rather than initiators of long-term studies. In such a situation, arguments favouring the rights of the PI to maintain control of postpublication access to primary data are weakened still further, given that the data may be the result of someone else''s efforts. Indeed, given the undoubted value of long-term studies for ecological and evolutionary research [2,37,39], many of Mills et al.''s [2] survey respondents will presumably hope to see these studies continue after their own retirement. Rather than owners of datasets, then, perhaps PIs of long-term studies might better be considered as custodians, such that—to adapt the slogan of a Swiss watchmaker—“you never really own a long-term population study; you merely look after it for the next generation.”     

Bacterial Ventures into Multicellularity: Collectivism through Individuality

Multicellular eukaryotes can perform functions that exceed the possibilities of an individual cell. These functions emerge through interactions between differentiated cells that are precisely arranged in space. Bacteria also form multicellular collectives that consist of differentiated but genetically identical cells. How does the functionality of these collectives depend on the spatial arrangement of the differentiated bacteria? In a previous issue of PLOS Biology, van Gestel and colleagues reported an elegant example of how the spatial arrangement of differentiated cells gives rise to collective behavior in Bacillus subtilus colonies, further demonstrating the similarity of bacterial collectives to higher multicellular organisms.Introductory textbooks tend to depict bacteria as rather primitive and simple life forms: the billions of cells in a population are all supposedly performing the exact same processes, independent of each other. According to this perspective, the properties of the population are thus nothing more than the sum of the properties of the individual cells. A brief look at the recent literature shows that life at the micro scale is much more complex and far more interesting. Even though cells in a population share the same genetic material and are exposed to similar environmental signals, they are individuals: they can greatly differ from each other in their properties and behaviors [1,2].One source of such phenotypic variation is that individual cells experience different microenvironments and regulate their genes in response. However, and intriguingly, phenotypic differences can also arise in the absence of environmental variation [3]. The stochastic nature of biochemical reactions makes variation between individuals unavoidable: reaction rates in cells will fluctuate because of the typical small number of the molecules involved, leading to slight differences in the molecular composition between individual cells [4]. While cells cannot prevent fluctuations from occurring, the effect of these extracellular and intracellular perturbations on a cell’s phenotype can be controlled by changing the biochemical properties of molecules or the architecture of gene regulatory networks [4,5]. The degree of phenotypic variation could thus evolve in response to natural selection. This raises the question of whether the high degree of phenotypic variation observed in some traits could offer benefits to the bacteria [5].One potential benefit of phenotypic variation is bet hedging. Bet hedging refers to a situation in which a fraction of the cells express alternative programs, which typically reduce growth in the current conditions but at the same time allow for increased growth or survival when the environment abruptly changes [6–8]. Another potential benefit can arise through the division of labor: phenotypic variation can lead to the formation of interacting subpopulations that specialize in complementary tasks [9]. As a result, the population as a whole can perform existing functions more efficiently or attain new functionality [10]. Division of labor enables groups of bacteria to engage in two tasks that are incompatible with each other but that are both required to attain a certain biological function.One of the most famous examples of division of labor in bacteria is the specialization of multicellular cyanobacteria into photosynthesizing and nitrogen-fixing subpopulations [11]. Here, the driving force behind the division of labor is the biochemical incompatibility between photosynthesis and nitrogen fixation, as the oxygen produced during photosynthesis permanently damages the enzymes involved in nitrogen fixation [12]. Other examples include the division of labor between two subpopulations of Salmonella Typhimurium (Tm) during infections [9] and the formation of multicellular fruiting bodies in Myxococcus xanthus [13]. Division of labor is not restricted to interactions between only two subpopulations; for example, the soil-dwelling bacteria Bacillus subtilis can differentiate into at least five different cell types [14]. Multiple types can simultaneously be present in Bacillus biofilms and colonies, each contributing different essential tasks [14,15].An important question is whether a successful division of labor requires the different subpopulations to coordinate their behavior and spatial arrangement. For some systems, it turns out that spatial coordination is not required. For example, the division of labor in clonal groups of Salmonella Tm does not require that the two cell types are spatially arranged in a particular way [9]. In other systems, spatial coordination between the different cell types seems to be beneficial. For example, differentiation into nitrogen-fixing and photosynthetic cells in multicellular cyanobacteria is spatially regulated in a way that facilitates sharing of nitrogen and carbon [16]. In general, when cell differentiation is combined with coordination of behavior between cells, this can allow for the development of complex, group-level behaviors that cannot easily be deduced from the behavior of individual cells [17–20]. In these cases, a population can no longer be treated as an assembly of independent individuals but must be seen as a union that together shows collective behavior.The study by van Gestel et al. [21] in a previous issue of PLOS Biology offers an exciting perspective on how collective behavior can arise from processes operating at the level of single cells. Van Gestel and colleagues [21] analyzed how groups of B. subtilis cells migrate across solid surfaces in a process known as sliding motility. The authors found that migration requires both individuality—the expression of different phenotypes in clonal populations—and spatial coordination between cells. Migration depends critically on the presence of two cell types: surfactin-producing cells, which excrete a surfactant that reduce surface tension, and matrix-producing cells, which excrete extracellular polysaccharides and proteins that form a connective extracellular matrix (Fig 1B) [14]. These two cell types are not randomly distributed across the bacterial group but are rather spatially organized (Fig 1C). The matrix-producing cells form bundles of interconnected and highly aligned cells, which the authors refer to as “van Gogh” bundles. The surfactant producing cells are not present in the van Gogh bundle but are essential for the formation of the bundles [21].Open in a separate windowFig 1Collective behavior through the spatial organization of differentiated cells.(A) Initially cells form a homogenous population. (B) Differentiation: cells start to differentiate into surfactin- (orange) and matrix- (blue) producing cells. The two cell types perform two complementary and essential tasks, resulting in a division of labor. (C) Spatial organization: the matrix-producing cells form van Gogh bundles, consisting of highly aligned and interconnected cells. Surfactin-producing cells are excluded from the bundles and have no particular spatial arrangement. (D) Collective behavior: growth of cells in the van Gogh bundles leads to buckling of these bundles, resulting in colony expansion. The buckling and resulting expansion depend critically on the presence of the two cell types and on their spatial arrangement.The ability to migrate is a collective behavior that can be linked to the biophysical properties of the multicellular van Gogh bundles. The growth of cells in these bundles causes them to buckle, which in turn drives colony migration (Fig 1D) [21]. This is a clear example of an emergent (group-level) phenotype: the buckling of the van Gogh bundles and the resulting colony motility cannot easily be deduced from properties of individual cells. Rather, to understand colony migration we have to understand the interactions between the two cells type as well as their spatial organization. Building on a rich body of work on the regulation of gene expression and cellular differentiation in Bacillus [14], van Gestel et al. [21] are able to show how these molecular mechanisms lead to the formation of specialized cell types that, through coordinated spatial arrangement, provide the group the ability to move (Fig 1). The study thus uniquely bridges the gap between molecular mechanisms and collective behavior in bacterial multicellularity.This study raises a number of intriguing questions. A first question pertains to the molecular mechanisms underlying the spatial coordination of the two cell types. Can the spatial organization be explained based on known mechanisms of the regulation of gene expression in this organism or does the formation of these patterns depend on hitherto uncharacterized gene regulation based on spatial gradients or cell–cell interaction? A second question is about the selective forces that lead to the evolution of collective migration of this organism. The authors raise the interesting hypothesis that van Gogh bundles evolved to allow for migration. Although this explanation is very plausible, it also raises the question of how selection acting on a property at the level of the group can lead to adaptation at the individual cell level. Possible mechanisms for such selective processes have been described within the framework of multilevel selection theory. However, there are still many questions regarding how, and to what extent, multilevel selection operates in the natural world [22–24]. The system described by van Gestel and colleagues [21] offers exciting opportunities to address these questions using a highly studied and experimentally amenable model organism.Bacterial collectives (e.g., colonies or biofilms) have been likened to multicellular organisms partly because of the presence of cell differentiation and the importance of an extracellular matrix [25,26]. Higher multicellular organisms share these properties; however, they are more than simple lumps of interconnected, differentiated cells. Rather, the functioning of multicellular organisms critically depends on the precise spatial organization of these cells [27]. Even though spatial organization has been suggested before in B. subtilis biofilms [28], there was a gap in our understanding of how spatial organization of unicellular cells can lead to group-level function. The van Gogh bundles in the article by van Gestel et al. [21] provide direct evidence on how differentiated cells can spatially organize themselves to give rise to group-level behavior. This shows once more that bacteria are not primitive “bags of chemicals” but rather are more like us “multicellulars” than we might have expected.     

Adenosine Signaling and the Energetic Costs of Induced Immunity

Life history theory predicts that trait evolution should be constrained by competing physiological demands on an organism. Immune defense provides a classic example in which immune responses are presumed to be costly and therefore come at the expense of other traits related to fitness. One strategy for mitigating the costs of expensive traits is to render them inducible, such that the cost is paid only when the trait is utilized. In the current issue of PLOS Biology, Bajgar and colleagues elegantly demonstrate the energetic and life history cost of the immune response that Drosophila melanogaster larvae induce after infection by the parasitoid wasp Leptopilina boulardi. These authors show that infection-induced proliferation of defensive blood cells commands a diversion of dietary carbon away from somatic growth and development, with simple sugars instead being shunted to the hematopoetic organ for rapid conversion into the raw energy required for cell proliferation. This metabolic shift results in a 15% delay in the development of the infected larva and is mediated by adenosine signaling between the hematopoietic organ and the central metabolic control organ of the host fly. The adenosine signal thus allows D. melanogaster to rapidly marshal the energy needed for effective defense and to pay the cost of immunity only when infected.While sitting around the campfire, evolutionary biologists may tell tales of the Darwinian Demon [1], a mythical being who is reproductively mature upon birth, lives forever, and has infinite offspring. In the morning, though, we know that no such creature can exist. All organisms must make compromises, and fitness is determined by striking the optimal balance among traits with competing demands. This is the central premise of life history theory: adaptations are costly, and increasing investment in one trait often forces decreased investment in others [2].Phenotype plasticity provides a partial solution to this evolutionary conundrum. If traits can be called upon only when required, the costs can be mitigated during periods of disuse. There are many examples of plastic costly adaptations, including the defensive helmets grown by Daphnia species in response to the presence of predators or abiotic factors that signal risk of predation ([3,4] and references therein), the flamboyant plumage that male birds exhibit during breeding season [5], and the inducible immune systems of higher plants and animals [6,7].The very inducibility of immune systems implicitly argues for their cost. If immune defense was cost-free, it would be constantly deployed for maximum protection against pathogenic infection. However, immune reactions have frequently been inferred to be energetically demanding (e.g., [8,9]) and carry the risk of autoimmune damage (e.g., [10,11]). It may therefore be evolutionarily adaptive to minimize immune activity in the absence of infection, to rapidly ramp up immunity in response to infection, and then to quickly shut down the immune response after the infection has been managed [12,13]. A paper by Bajgar et al. in the current issue of PLOS Biology [14] uses the Drosophila–Leptopilina host–pathogen system to quantitatively measure the energetic expense of induced up-regulation of immunity, demonstrating plastic metabolic reallocation toward immune cell proliferation at the expense of nutrient storage, growth, and development.Parasitoid wasps such as Leptopilina species infect their insect larval hosts by laying an egg inside the host body cavity [15]. Unimpeded, the egg hatches into a wasp larva that feeds off and develops inside the still-living host. In the case of Leptopilina boulardi infecting Drosophila melanogaster, the infected host larva survives to enter pupation, but if the parasitization is successful, an adult wasp will ultimately emerge from the pupal case instead of an adult fruit fly. This clearly is against the interest of the D. melanogaster host, so the larval fly attempts to encapsulate the L. boulardi egg in a sheath of specialized blood cells called lamellocytes that collaborate with other cell types to suffocate the wasp egg, deprive it of nutrients, and kill it with oxidative free radicals [16]. The struggle between fly and wasp is of the highest stakes, with guaranteed death and complete loss of evolutionary fitness for the loser.Natural D. melanogaster populations are rife with genetic variation for resistance to parasitoids, and laboratory selection for as few as five generations can increase host survivorship from 1%–5% to 40%–60% (e.g., [17,18]). This evolved resistance comes at a cost, though. Larvae from evolved resistant strains have decreased capacity to compete with their unselected progenitors under crowded or nutrient-poor conditions [17,18]. The general mechanism for enhanced resistance has been recurrently revealed to be an increase in the number of circulating blood cells (hemocytes). But why are the resistant larvae outcompeted by susceptible larvae? One compelling hypothesis is that the extra investment in blood cell proliferation comes at an energetic cost to development of other tissues, a cost which may be exacerbated by a decrease in feeding rate of the selected lines [19] and that leads to impaired development under nutrient-limiting conditions. The cost can be limited, however, by producing the defensive blood cells in large numbers only when the host is infected and has need of them. Effectively achieving this requires the capacity to rapidly signal cell proliferation and to recruit the energy required for hematopoiesis from other physiological processes.Bajgar et al. [14] use a series of careful experiments to document energetic redistributions and costs associated with hemocyte proliferation and lamellocyte differentiation in D. melanogaster infected by L. boulardi. They find that parasitoid infection results in a 15% delay in host development, and that at least a fraction of this delay can be plausibly attributed to a metabolic reallocation that supports blood cell proliferation over somatic growth. Specifically, they find that dietary carbohydrates are shunted away from energetic storage and tissue development, and instead are routed to the lymph gland, where hemocytes are being produced and differentiated. The signal to activate this reallocation emanates from the lymph gland and developing hemocytes themselves in the form of secreted adenosine, which is then received and interpreted by the central metabolic control organ, the fat body. Bajgar et al. [14] are able to show in unprecedented quantitative precision, that secreted adenosine acts as a signal to rapidly trigger inducible immune defense, that this immune induction is costly at the level of individual tissues and the whole organism, and that the cost of induced defense is paid only upon infection.The D. melanogaster metabolic rearrangement after infection by L. boulardi is profound [14]. Within 6–18 hours of infection, host larvae show a strong reduction in the incorporation of dietary carbon into stored lipids and protein and an overall reduction in glycogen stores. The levels of circulating glucose and trehalose spike, with those saccharides seemingly directed to the hemocyte-producing lymph gland. Expression of glycolytic genes is suppressed in the fat body, while fat body expression of a trehalose transporter is up-regulated to promote trehalose secretion into circulation. Glucose and trehalose transporters are concomitantly up-regulated in the lymph gland and developing hemocytes to facilitate import of the circulating saccharides. Genes required for glycolysis—but not the TCA cycle—are simultaneously up-regulated in the lymph gland and nascent hemocytes to turn those sugars into quick energy under the Warburg effect [20]. The totality of the data is consistent with an interpretation that the induced hemocyte proliferation is directly costly to host larval growth as an immediate consequence of substantial energetic reallocation.This same research group had previously shown that extracellular adenosine can be used by Drosophila as a signal in regulating inflammation-like responses [21]. In the present study, they use RNAi to knock down expression of the adenosine transporter ENT2 specifically in the lymph gland and developing hemocytes. This prevention of adenosine export eliminates the spike in circulating glucose and trehalose after infection. Infected larvae with knocked down expression of ENT2 continue to allocate dietary carbon to lipid and proteins as though they were uninfected, they fail to differentiate an adequate number of lamellocytes, and they suffer reduced resistance to the parasitoid. These data firmly implicate extracellular adenosine as a critical trigger mediating the switch in energetic allocation from growth and development to induced immunity. In further support of this interpretation, larvae that are mutant for the adenosine receptor AdoR show a nearly 70% reduction relative to wild type in the number of differentiated lamellocytes after infection and consequently encapsulate the parasitoid egg at nearly 4-fold lower rates. Like the ENT2 knockdowns, AdoR mutant larvae fail to exhibit elevated levels of circulating glucose or trehalose when infected by L. boulardi, although surprisingly, the AdoR mutants do show an appropriate inhibition of glycogen storage when infected. Overall, the genetic results indicate that ENT2 protein allows secretion of adenosine from the lymph gland. This adenosine signal is received in the fat body, which then dampens energetic storage in favor of secretion and circulation of simple saccharides. These sugars are taken up by the lymph gland to rapidly facilitate hemocyte proliferation, lamellocyte differentiation, and immune defense against the parasitoid. In satisfying consistency with this model, Bajgar et al. [14] show that lamellocyte differentiation and host resistance can be partially rescued even in the absence of ENT2 or AdoR by supplementing the D. melanogaster diet with extra glucose, thereby providing the boost in the circulating saccharides required for hematopoiesis.There are key differences between studies of evolutionary tradeoffs, such as those conducted by Kraaijeveld and colleagues (e.g., [17–19]), and studies of physiological costs such as the one conducted by Bajgar et al. [14]. The evolutionary tradeoffs exposed by experimental selection are experienced even in the absence of parasitoid infection. Blood cell number is constitutively higher in the evolved resistant strains, which presumably allows a faster and more robust defense against a wasp egg. However, the resistant larvae always suffer the cost when reared in competitive conditions. Because the costs arise from a constitutive investment in defense, regardless of whether parasitoids are present, these are sometimes referred to as “maintenance” costs or fixed costs [22]. In contrast, Bajgar et al. have measured a physiological “deployment” cost [22], which is conditionally experienced only once the host activates an immune response.It remains an open question the extent to which maintenance costs and deployment costs share mechanistic bases. In the present example, Bajgar et al. [14] show clearly that the machinery is in place to route energetic investment away from growth and development in favor of hemocyte proliferation. Extrapolating from the laboratory selection experiments [17–19], a natural increase in the epidemiological risk of parasitization in the wild might favor greater constitutive investment in hemocyte production. In such a scenario, it is easy to imagine the adaptive value of a mutation or genetic variant that results in higher expression of ENT2 in the lymph gland in the absence of infection, driving constitutively higher hemocyte number and protection against infection at the expense of constitutively lower nutrient storage and growth. In this way, a plastic switch could be converted into a hardwired trait, a deployment cost would become a maintenance cost, and a physiological tradeoff would become an evolutionary one. However, it is important to appreciate that there typically are many solutions to any biological problem, and constitutively elevated blood cell number could also evolve via mechanisms unrelated to adenosine signaling. A key challenge for life history biologists will be to bridge physiological studies such as that by Bajgar and colleagues [14] with the evolutionary studies that preceded it, testing whether physiological and evolutionary tradeoffs share a mechanistic basis.While in the bright light of day, evolutionary biologists can agree that the Darwinian Demon is just a ghost story, we have precious few examples of evolutionary or physiological tradeoffs where the mechanistic bases are well understood. More careful quantitative and genetic studies like that of Bajgar et al. [14] are necessary to carry us beyond reliance on abstract concepts like “resource pools” [2] and into mechanistic understanding of how life history tradeoffs operate on both the physiology of individuals and the evolution of species.     

Using Sex to Cure the Genome

The diversification of prokaryotes is accelerated by their ability to acquire DNA from other genomes. However, the underlying processes also facilitate genome infection by costly mobile genetic elements. The discovery that cells can uptake DNA by natural transformation was instrumental to the birth of molecular biology nearly a century ago. Surprisingly, a new study shows that this mechanism could efficiently cure the genome of mobile elements acquired through previous sexual exchanges.Horizontal gene transfer (HGT) is a key contributor to the genetic diversification of prokaryotes [1]. Its frequency in natural populations is very high, leading to species’ gene repertoires with relatively few ubiquitous (core) genes and many low-frequency genes (present in a small proportion of individuals). The latter are responsible for much of the phenotypic diversity observed in prokaryotic species and are often encoded in mobile genetic elements that spread between individual genomes as costly molecular parasites. Hence, HGT of interesting traits is often carried by expensive vehicles.The net fitness gain of horizontal gene transfer depends on the genetic background of the new host, the acquired traits, the fitness cost of the mobile element, and the ecological context [2]. A study published in this issue of PLOS Biology [3] proposes that a mechanism originally thought to favor the acquisition of novel DNA—natural transformation—might actually allow prokaryotes to clean their genome of mobile genetic elements.Natural transformation allows the uptake of environmental DNA into the cell (Fig 1). It differs markedly from the other major mechanisms of HGT by depending exclusively on the recipient cell, which controls the expression of the transformation machinery and favors exchanges with closely related taxa [4]. DNA arrives at the cytoplasm in the form of small single-stranded fragments. If it is not degraded, it may integrate the genome by homologous recombination at regions of high sequence similarity (Fig 1). This results in allelic exchange between a fraction of the chromosome and the foreign DNA. Depending on the recombination mechanisms operating in the cell and on the extent of sequence similarity between the transforming DNA and the genome, alternative recombination processes may take place. Nonhomologous DNA flanked by regions of high similarity can be integrated by double homologous recombination at the edges (Fig 1E). Mechanisms mixing homologous and illegitimate recombination require less strict sequence similarity and may also integrate nonhomologous DNA in the genome [5]. Some of these processes lead to small deletions of chromosomal DNA [6]. These alternative recombination pathways allow the bacterium to lose and/or acquire novel genetic information.Open in a separate windowFig 1Natural transformation and its outcomes.The mechanism of environmental DNA uptake brings into the cytoplasm small single-stranded DNA fragments (A). Earlier models for the raison d’être of natural transformation have focused on the role of DNA as a nutrient (B), as a breaker of genetic linkage (C), or as a substrate for DNA repair (D). The chromosomal curing model allows the removal of mobile elements by recombination between conserved sequences at their extremities (E). The model is strongly affected by the size of the incoming DNA fragments, since the probability of uptake of a mobile element rapidly decreases with the size of the element and of the incoming fragments (F). This leads to a bias towards the deletion of mobile elements by recombination, especially the largest ones. In spite of this asymmetry, some mobile elements can integrate the genome via natural transformation, following homologous recombination between large regions of high sequence similarity (G) or homology-facilitated illegitimate recombination in short regions of sequence similarity (H).Natural transformation was the first described mechanism of HGT. Its discovery, in the first half of the 20th century, was instrumental in demonstrating that DNA is the support of genetic information. This mechanism is also regularly used to genetically engineer bacteria. Researchers have thus been tantalized by the lack of any sort of consensus regarding the raison d’être of natural transformation.Croucher, Fraser, and colleagues propose that the small size of recombining DNA fragments arising from transformation biases the outcome of recombination towards the deletion of chromosomal genetic material (Fig 1F). Incoming DNA carrying the core genes that flank a mobile element, but missing the element itself, can provide small DNA fragments that become templates to delete the element from the recipient genome (Fig 1E). The inverse scenario, incoming DNA carrying the core genes and a mobile element absent from the genome, is unlikely due to the mobile element being large and the recombining transformation fragments being small. Importantly, this mechanism most efficiently removes the loci at low frequency in the population because incoming DNA is more likely to lack such intervening sequences when these are rare. Invading mobile genetic elements are initially at low frequencies in populations and will be frequently deleted by this mechanism. Hence, recombination will be strongly biased towards the deletion or inactivation of large mobile elements such as phages, integrative conjugative elements, and pathogenicity islands. Simulations at a population scale show that transformation could even counteract the horizontal spread of mobile elements.An obvious limit of natural transformation is that it can''t cope with mobile genetic elements that rapidly take control of the cell, such as virulent phages, or remain extra-chromosomal, such as plasmids. Another limit of transformation is that it facilitates the acquisition of costly mobile genetic elements [7,8], especially if these are small. When these elements replicate in the genome, as is the case of transposable elements, they may become difficult to remove by subsequent events of transformation. Further work will be needed to quantify the costs associated with such infections.Low-frequency adaptive genes might be deleted through transformation in the way proposed for mobile genetic elements. However, adaptive genes rise rapidly to high frequency in populations, becoming too frequent to be affected by transformation. Interestingly, genetic control of transformation might favor the removal of mobile elements incurring fitness costs while preserving those carrying adaptive traits [3]. Transformation could, thus, effectively cure chromosomes and other replicons of deleterious mobile genetic elements integrated in previous events of horizontal gene transfer while preserving recently acquired genes of adaptive value.Prokaryotes encode an arsenal of immune systems to prevent infection by mobile elements and several regulatory systems to repress their expression [9]. Under the new model (henceforth named the chromosomal curing model), transformation has a key, novel position in this arsenal because it allows the expression of the incoming DNA while subsequently removing deleterious elements from the genome.Mobile elements encode their own tools to evade the host immune systems [9]. Accordingly, they search to affect natural transformation [3]. Some mobile genetic elements integrate at, and thus inactivate, genes encoding the machineries required for DNA uptake or recombination. Other elements express nucleases that degrade exogenous DNA (precluding its uptake). These observations suggest an arms race evolutionary dynamics between the host, which uses natural transformation to cure its genome, and mobile genetic elements, which target these functions for their own protection. This gives further credibility to the hypothesis that transformation is a key player in the intra-genomic conflicts between prokaryotes and their mobile elements.Previous studies have proposed alternative explanations for the evolution of natural transformation, including the possibility that it was caused by selection for allelic recombination and horizontal gene transfer [10], for nutrient acquisition [11], or for DNA repair [12]. The latter hypothesis has recently enjoyed regained interest following observations that DNA-damage agents induce transformation [13,14], along with intriguing suggestions that competence might be advantageous even in the absence of DNA uptake [15,16]. The hypothesis that transformation evolved to acquire nutrients has received less support in recent years.Two key specific traits of transformation—host genetic control of the process and selection for conspecific DNA—share some resemblance with recombination processes occurring during sexual reproduction. Yet, the analogy between the two processes must be handled with care because transformation results, at best, in gene conversion of relatively small DNA fragments from another individual. The effect of sexual reproduction on genetic linkage is thought to be advantageous in the presence of genetic drift or weak and negative or fluctuating epistasis [17]. Interestingly, these conditions could frequently be met by bacterial pathogens [18], which might explain why there are so many naturally transformable bacteria among human pathogens, such as Streptococcus pneumoniae, Helicobacter pylori, Staphylococcus aureus, Haemophilus influenzae, or Neisseria spp. The most frequent criticism to the analogy between transformation and sexual reproduction is that environmental DNA from dead individuals is unlikely to carry better alleles than the living recipient [11]. This difficulty is circumvented in bacteria that actively export copies of their DNA to the extracellular environment. Furthermore, recent theoretical studies showed that competence could be adaptive even when the DNA originates from individuals with lower fitness alleles [19,20]. Mathematically speaking, sexual exchanges with the dead might be better than no exchanges at all.The evaluation of the relative merits of the different models aiming to explain the raison d’être of natural transformation is complicated because they share several predictions. For example, the induction of competence under maladapted environments can be explained by the need for DNA repair (more DNA damage in these conditions), by selection for adaptation (through recombination or HGT), and by the chromosomal curing model because mobile elements are more active under such conditions (leading to more intense selection for their inactivation). Some of the predictions of the latter model—the rapid diversification and loss of mobile elements and their targeting of the competence machinery—can also be explained by models involving competition between mobile elements and their antagonistic association with the host. One of the great uses of mathematical models in biology resides in their ability to pinpoint the range of parameters and conditions within which each model can apply. The chromosomal curing model remains valid under broad ranges of variation of many of its key variables. This might not be the case for alternative models [3].While further theoretical work will certainly help to specify the distinctive predictions of each model, realistic experimental evolutionary studies will be required to test them. Unfortunately, the few pioneering studies on this topic have given somewhat contradictory conclusions. Some showed that natural transformation was beneficial to bacteria adapting under suboptimal environments (e.g., in times of starvation or in stressful environments) [21,22], whereas others showed it was most beneficial under exponential growth and early stationary phase [23]. Finally, at least one study showed a negative effect of transformation on adaptation [24]. Part of these discrepancies might reveal differences between species, which express transformation under different conditions. They might also result from the low intraspecies genetic diversity in these experiments, in which case the use of more representative communities might clarify the conditions favoring transformation.Macroevolutionary studies on natural transformation are hindered by the small number of prokaryotes known to be naturally transformable (82 species, following [25]). In itself, this poses a challenge: if transformation is adaptive, then why does it seem to be so rare? The benefits associated with deletion of mobile elements, with functional innovation, or with DNA repair seem sufficiently general to affect many bacterial species. The trade-offs between cost and benefit of transformation might lead to its selection only when mobile elements are particularly deleterious for a given species or when species face particular adaptive challenges. According to the chromosomal curing model, selection for transformation would be stronger in highly structured environments or when recombination fragments are small. There is also some evidence that we have failed to identify numerous naturally transformable prokaryotes, in which case the question above may lose part of its relevance. Many genomes encode key components of the transformation machinery, suggesting that this process might be more widespread than currently acknowledged [25]. As an illustration, the ultimate model for research in microbiology—Escherichia coli—has only recently been shown to be naturally transformable; the conditions leading to the expression of this trait remain unknown [26].The chromosomal curing model might contribute to explaining other mechanisms shaping the evolution of prokaryotic genomes beyond the removal of mobile elements. Transformation-mediated deletion of genetic material, especially by homology-facilitated illegitimate recombination (Fig 1H), could remove genes involved in the mobility of the genetic elements, facilitating the co-option by the host of functions encoded by mobile genetic elements. Several recent studies have pinpointed the importance of such domestication processes in functional innovation and bacterial warfare [27]. The model might also be applicable to other mechanisms that transfer small DNA fragments between cells. These processes include gene transfer agents [28], extracellular vesicles [29], and possibly nanotubes [30]. The chromosomal curing model might help unravel their ecological and evolutionary impact.     

The Need for Evolutionarily Rational Disease Interventions: Vaccination Can Select for Higher Virulence

There is little doubt evolution has played a major role in preventing the control of infectious disease through antibiotic and insecticide resistance, but recent theory suggests disease interventions such as vaccination may lead to evolution of more harmful parasites. A new study published in PLOS Biology by Andrew Read and colleagues shows empirically that vaccination against Marek’s disease has favored higher virulence; without intervention, the birds die too quickly for any transmission to occur, but vaccinated hosts can both stay alive longer and shed the virus. This is an elegant empirical demonstration of how evolutionary theory can predict potentially dangerous responses of infectious disease to human interventions.There is little doubt that evolution continues to play a major role in preventing drug and vector-control programs from eliminating many infectious diseases. How much of the global infectious disease burden is attributable to recent evolution, and how much to social and other forces, remains unclear, but we are unquestionably severely impacted by the evolutionary potential of pathogens [1]. There is a large body of evolutionary theory that seeks to understand the processes that make some infectious diseases acute and lethal while others are chronic and mild [2–5]. More recently, this general theory has been applied to make predictions of the evolutionary outcomes of particular disease interventions within the broader aim of “virulence management” [6,7,9]. Of particular importance is that the theory predicts that there is the potential for certain disease interventions, including certain types of vaccination, to select for the evolution of greater virulence (cause higher mortality) and therefore present a greater threat to their hosts [7]. However, the theory generally makes deliberately simple assumptions, ignoring, for example, the molecular mechanisms that underpin host–parasite interactions. While this is one of the strengths of the approach—since it aims to make general predictions—it has been unclear how relevant this theory is to real infectious diseases. Read et al. have now provided a direct empirical test of one of the key theoretical predictions that “imperfect” vaccination can select for higher virulence [8]. The study is important because although there is increasing interest in evolutionary biology by the medical community [10,11], few empirical tests of evolutionary theory have been conducted that are of immediate relevance to important disease problems. Importantly, this empirical paper confirms the unintuitive and worrying predictions of a very simple theoretical model of the implications of a common disease intervention.In some sense, theory on the evolution of virulence addresses the fundamental question of why infectious diseases kill their hosts. In a classic infectious disease, whether spread by contact, environmental infectious stages, or through vectors, the longer the host is infectious, the greater the chance that transmission will occur. If by killing the host the infectious period is shortened, then all things being equal, parasite genotypes that kill the host more slowly have a longer infectious period and will therefore be favored. Hence, virulence (defined as disease-induced mortality) will be selected against by evolution, and parasites should evolve to become benign; they should evolve away from parasitism towards commensalism (infection without host damage). This is the “conventional wisdom” [3] that leads ultimately to the question: why are some parasites lethal? High virulence in a relatively rare host into which a disease occasionally spills over, such as Ebola in humans, may persist because selection is predominately occurring in the reservoir rather than the rare host. Furthermore, recently emerged, initially virulent disease may be in the process of evolving to lower virulence as they become more endemic in a new host. Also, in principle, disease-induced mortality could be a by-product of infection that is completely unrelated to both the genotype and life history characteristics of the parasite and is therefore not selected against. However, evolutionary theory assumes that virulence has been selected for because fundamentally things are not equal. Specifically, most theory assumes that disease-induced mortality (virulence) results from a “trade-off” (a gain in one trait comes at the expense of another) with another parasite characteristic, so that virulence is a correlated and unavoidable consequence of another factor that increases the chance of transmission. In this “trade-off hypothesis,” people have generally focused on virulence (mortality rate) being a by-product/cost of the transmission rate [2,5,12], as it is an appealing idea that high growth rates within the host may produce more transmission stages and therefore a higher rate of transmission, but also cause more damage and therefore higher virulence. Clearly within-host dynamics are much more complicated than this caricature, and we rarely understand all the mechanisms that underpin any trade-offs, but there is now good evidence for this overall relationship between transmission rate and mortality rate (virulence) in a number of systems [5,13–16]. Given this trade-off relationship, the theory predicts that there is an optimal transmission rate and level of virulence that maximizes the average number of infections that would occur in a completely susceptible population (the so called basic reproductive number, R₀). With any disease intervention, however, there is a clear and present danger that the balance between transmission rate and virulence will be altered, leading to changes in “optimal” virulence. It is here that evolutionary theory can be useful in predicting the impact on infectious disease virulence of different interventions.The theoretical paper that predicted the empirical results tested in the Read paper was inspired by the potential use of “imperfect” or “leaky” vaccines for malaria [7]. The key assumption of the model is that vaccination is “leaky” such that transmission can occur from infected, vaccinated individuals. If, on the other hand, the vaccination is “sterilizing,” preventing the infection (or at least the infectivity) of vaccinated individuals, then vaccinated individuals represent an evolutionary dead-end for parasites, as there is no opportunity for selection to occur. The model is simple in that it explicitly excludes escape mutants (which in some sense also make vaccines imperfect) and is typical of the approach used in evolutionary theory. The power of the approach is that by focusing on one process, the theory can make clear predictions. The key message of the detailed modeling is that leaky vaccination, which reduces the impact of the disease and thereby lowers pathogenicity, selects for a higher growth rate in the parasite, leading to a greater transmission rate and higher virulence [7]. Effectively, the cost of higher exploitation is reduced, which changes the shape of the virulence-transmission rate trade-off and allows for higher optimal growth and transmission rates. An important consequence is that a highly virulent parasite strain that kills its host so quickly that it cannot persist in an unvaccinated population can potentially circulate in a vaccinated population.Read et al. present clear evidence that imperfect vaccines do indeed enable the persistence of much more virulent strains of Marek’s disease to circulate than would be possible in the absence of vaccination. Marek’s is a disease of poultry that is spread by inhalation, persists in the environment, and initially causes paralysis in older birds. Previous work from the group had shown clearly that there is a transmission-virulence trade-off in the disease [15,16]. Leaky vaccination [17] against Marek’s has been common since the 1970s, and over this period the disease has become much more virulent [12]. While during this time there have been a number of changes including the intensification of production [18] and shorter bird life spans [15] that could, in theory, have increased virulence, the Read paper directly examines whether leaky vaccines could be the cause. In the new paper, the vaccine is confirmed to be “leaky” [17]: vaccinated birds can become infected and, critically, they can shed the virus. In the core experiment, Read et al. vaccinated birds from naïve parents (so that there were no maternal antibodies) with five virus strains that vary in virulence from 60% mortality over two months to 100% mortality by 10 days. In terms of classic virulence measures, this approximates as a 10-fold variation in the disease-induced mortality rate. Vaccination does reduce shedding of the virus; however, this positive effect of the intervention is overwhelmed in the more virulent viruses by the fact that unvaccinated birds die much more quickly. Without vaccination, the virulent strains generally kill the hosts before any transmission can take place: a strong example of the transmission virulence trade-off in action. The researchers went further and directly examined transmission using sentinel birds. These sentinel birds were put in enclosures with either vaccinated or unvaccinated birds, both of which had been challenged with the more virulent viruses. Early death in the unvaccinated birds meant that no sentinels were infected, and this contrasted starkly with the vaccinated birds enclosure, where the sentinel birds were infected. As a whole, this paper provides a direct test of the idea that vaccination allows the transmission of virus strains that are too virulent to transmit in non-vaccinated hosts.A key criticism of the Gandon et al. theoretical paper is that there is no clear evidence of higher virulence due to human vaccination programs. However, the established successful human vaccination programs have mostly been “sterilizing” [19], although as we implement human vaccination programs with “leaky” vaccines, we will be carrying out real-world “experiments” that test the theory. The Read paper has shown, however, that this piece of evolutionary theory is pertinent to real-world infectious disease control. More generally, this study highlights the potential usefulness of evolutionary theory for disease control and suggests that it may therefore have an important role to play in the design of medical interventions. If so, it is important that we take a broad view of the evolution of virulence theory and the “trade-off hypothesis” beyond the simple relationship between transmission and mortality rates. Evolutionary theory is directly applicable whenever virulence is an optimum determined by the relative costs and benefits of a number of correlated parasite traits. This broader view is important since, for infectious agents that are obligate killers (i.e., they can only transmit at the death of their host), virulence is positively related to transmission. However, in these diseases there are other trade-offs, such as one between productivity and time to death, that lead to an evolutionarily optimal virulence that is determined by selection [5,20,21]. Indeed, the paper that is often cited as the origin of the trade-off hypothesis [4] described a trade-off between virulence (disease-induced mortality) and recovery (rather than transmission) such that faster growing, more damaging parasite strains are harder to clear, and the hosts take longer to recover [4,22]. Some of the criticism for the trade-off hypothesis focuses on whether there is a transmission–virulence relationship in a particular disease interaction; but if we take this broad view, there is considerable evidence that virulence is shaped by selection [5,12,23]. Furthermore, although “accidental” high virulence in a rare host may not be selected against, selection is likely to be happening in the more common hosts, and even if virulence is caused primarily by host immunopathology, this has the potential to select the parasites to modulate growth or immunomodulation [24–27].In terms of vaccination programs, it would clearly be useful if there were more experimental tests of the theory. However, there are likely to be few systems in which there has been the widespread historical implementation of leaky vaccination that are also amiable to experimentation. There are, however, a number of key issues that still need to be addressed theoretically. In particular, any vaccination program is likely to have incomplete vaccine coverage, and understanding the impact of different levels of heterogeneity in vaccine coverage within the population to the evolution of virulence is a difficult but important problem. Furthermore, there is likely to be genetic variation both in resistance of hosts and the efficacy of vaccination within most populations, and this heterogeneity may have important implications to the outcome of vaccination [28]. It is also the case that there can often be specificity between different parasite strains and host genotypes, and this may be of considerable importance in many systems [12], particularly outside of relatively genetically homogenous agricultural populations. That said, given that we now have this test in Marek’s disease, we are now able, at least, to say that the theory is relevant to real-world disease systems. It seems prudent, therefore, to take this risk seriously and consider the potential for selection in the use of new vaccines. The theory tells us that the key questions we need to ask of a vaccination program are: is the vaccine leaky? Does the vaccine act to reduce the impact of the disease within an individual? And is the virulence of the parasite selected for—whether it is due to the transmission virulence trade-off or some other, broader trade-off relationship? These questions should ideally be addressed before the implementation of any vaccination program, and careful monitoring would be usefully implemented in the light of this potential selection for higher virulence.More broadly, other disease interventions beyond vaccination also have the potential to select upon disease and cause similar problems [6]. It is very hard for us to predict the evolutionary outcome after the emergence of a new disease into a population, but we can and should do much better in predicting the impact of our own disease interventions. If we take it seriously, evolutionary theory gives us the opportunity to move towards a more evolutionarily rational program of disease intervention. While the Read paper shows how the simple theory of the Gandon paper can predict real disease dynamics, there is considerable potential for the development of more disease-specific theory that includes more of the key detailed mechanistic knowledge of a particular host–parasite interaction. There is an opportunity for real advances in the predictive power of the models through tight collaborations between evolutionary modelers and molecular parasitologists and/or virologists. Calls for more serious acceptance of evolutionary biology by the medical community are increasing [10,11], and the Read paper shows that a combination of predictive theory and empirical tests of this theory in real-world disease systems have real potential to improve disease interventions in the light of evolutionary responses.     

Predicting novel candidate human obesity genes and their site of action by systematic functional screening in Drosophila

The discovery of human obesity-associated genes can reveal new mechanisms to target for weight loss therapy. Genetic studies of obese individuals and the analysis of rare genetic variants can identify novel obesity-associated genes. However, establishing a functional relationship between these candidate genes and adiposity remains a significant challenge. We uncovered a large number of rare homozygous gene variants by exome sequencing of severely obese children, including those from consanguineous families. By assessing the function of these genes in vivo in Drosophila, we identified 4 genes, not previously linked to human obesity, that regulate adiposity (itpr, dachsous, calpA, and sdk). Dachsous is a transmembrane protein upstream of the Hippo signalling pathway. We found that 3 further members of the Hippo pathway, fat, four-jointed, and hippo, also regulate adiposity and that they act in neurons, rather than in adipose tissue (fat body). Screening Hippo pathway genes in larger human cohorts revealed rare variants in TAOK2 associated with human obesity. Knockdown of Drosophila tao increased adiposity in vivo demonstrating the strength of our approach in predicting novel human obesity genes and signalling pathways and their site of action.

This study set out to identify novel gene variants that may contribute to human obesity, by combining human exosome sequencing analyses with systematic functional screening in Drosophila. This identifies a number of novel obesity-associated genes which control adiposity in flies, and uncovers a potential role for the Hippo signaling pathway in obesity.

Obesity is a major risk factor for type 2 diabetes, cardiovascular disease, cancers, and, most recently, COVID-19 [1]. Despite the obvious environmental drivers to weight gain, multiple genetic studies have demonstrated that 40% to 70% of the variation in body weight is attributable to genetic variation [2]. The discovery of genes that contribute to the regulation of human body weight can provide insights into the mechanisms involved in energy homeostasis and identify potential targets for weight loss therapy. Moreover, drug targets supported by human genetic evidence are more likely to transit successfully through the drug discovery pipeline [3].A classical approach to the discovery of pathogenic variants is to investigate consanguineous populations with high degrees of parental relatedness (parents who are first or second cousins) where large portions of the genome are identical by descent as a result of family structure in preceding generations (long regions of homozygosity). Indeed, studies in consanguineous families led to the discovery of the first homozygous loss-of-function mutations in the genes encoding leptin (LEP; [4]) and the leptin receptor (LEPR; [5]) associated with severe obesity. However, at the time, the function of leptin and its receptor had already been established in ob/ob and db/db mice, respectively [6], so the pathogenicity of homozygous mutations that resulted in loss of function in cells was readily established.The situation is more complex when studying homozygous mutations in new candidate genes. Some of these genes may play a direct causal role in the development of obesity, others may increase susceptibility to obesity only in certain contexts, and some genes will play no role at all. Recent large-scale studies in healthy people in outbred populations have revealed that a significant proportion of rare homozygous variants that are predicted to cause a loss of function do not result in a clinically discernible phenotype [7,8]. As such, identifying the subset of genes that may be involved in the regulation of adiposity in large human genetic studies presents a major hurdle.For some diseases, functional screens in cultured cells permit rapid testing of candidate genes, as exemplified by studies of insulin secretion in islet cells for genes associated with type 2 diabetes [9]. However, obesity is a systems-level disorder that cannot be replicated in cells. As such, a functional screen in vivo is needed. Here, we use Drosophila to screen the functional consequences of knocking down expression of candidate human obesity genes and to explore the complex interactions between multiple organ systems that are regulated by environmental and genetic factors.Drosophila has been a useful tool in the functional characterisation of human disease-associated genes [10–12]. Many organ systems and metabolic enzymes are highly conserved in Drosophila, as are the major regulatory mechanisms involved in metabolic homeostasis [13,14]. As in humans, Drosophila accumulate lipids and become obese when raised on a high-fat or high-sugar diet, developing cardiomyopathy and diabetic phenotypes [15,16]. Furthermore, more than 60% of the genes identified in an unbiased genome-wide RNAi screen for increased fat levels in Drosophila have human orthologues [17]. Most studies in Drosophila have performed forward genetic screens resulting in obesity [18] before assessing whether misregulation of the corresponding mammalian orthologue affects adiposity [17]. Another report knocked down Drosophila orthologs of human genes near body mass index (BMI) loci from GWAS studies to identify genes regulating adiposity [19].Here, instead, we chose to take advantage of new data from a cohort of patients carrying rare genetic variants that might cause severe early-onset obesity. We set out to identify, in Drosophila, whether any of these genes are likely to be responsible for the obese phenotype. An additional advantage of working with Drosophila is the potential to identify interacting genes and signalling pathways. We proposed that it would then be possible to search for variants in human orthologues of these genes in larger cohorts of patients, to discover further as yet unidentified genes regulating human obesity.To increase our chances of finding pathogenic variants, we focused on rare homozygous variants identified in probands with severe obesity, many from consanguineous families. After knocking down expression of Drosophila orthologues of candidate human obesity genes, we discovered 4 genes that significantly increased triacylglyceride (TAG) levels. Importantly, none of these genes had been associated previously with human obesity, but the pathways in which they act are known and could be further analysed in Drosophila. Knockdown of further members of one of these signalling pathways, the Hippo pathway, also gave an obesity phenotype, highlighting the success of our approach. We then searched for variants in the novel obesity genes we identified in Drosophila, and their associated signalling pathways, in larger cohorts of unrelated obese people and healthy controls. This uncovered yet another gene, which, when knocked down in Drosophila, increased adiposity. We demonstrate that the cross-fertilisation of human and Drosophila genetics is a powerful system to provide novel insights into the genetic and cellular processes regulating adiposity and may ultimately contribute to strategies for the prevention and treatment of obesity.     

Which New Health Technologies Do We Need to Achieve an End to HIV/AIDS?

In the last 15 years, antiretroviral therapy (ART) has been the most globally impactful life-saving development of medical research. Antiretrovirals (ARVs) are used with great success for both the treatment and prevention of HIV infection. Despite these remarkable advances, this epidemic grows relentlessly worldwide. Over 2.1 million new infections occur each year, two-thirds in women and 240,000 in children. The widespread elimination of HIV will require the development of new, more potent prevention tools. Such efforts are imperative on a global scale. However, it must also be recognised that true containment of the epidemic requires the development and widespread implementation of a scientific advancement that has eluded us to date—a highly effective vaccine. Striving for such medical advances is what is required to achieve the end of AIDS.In the last 15 years, antiretroviral therapy (ART) has been the most globally impactful life-saving development of medical research. Antiretrovirals (ARVs) are used with great success for both the treatment and prevention of HIV infection. In the United States, the widespread implementation of combination ARVs led to the virtual eradication of mother-to-child transmission of HIV from 1,650 cases in 1991 to 110 cases in 2011, and a turnaround in AIDS deaths from an almost 100% five-year mortality rate to a five-year survival rate of 91% in HIV-infected adults [1]. Currently, the estimated average lifespan of an HIV-infected adult in the developed world is well over 40 years post-diagnosis. Survival rates in the developing world, although lower, are improving: in sub-Saharan Africa, AIDS deaths fell by 39% between 2005 and 2013, and the biggest decline, 51%, was seen in South Africa [2].Furthermore, the association between ART, viremia, and transmission has led to the concept of “test and treat,” with the hope of reducing community viral load by testing early and initiating treatment as soon as a diagnosis of HIV is made [3]. Indeed, selected regions of the world have begun to actualize the public health value of ARVs, from gains in life expectancy to impact on onward transmission, with a potential 1% decline in new infections for every 10% increase in treatment coverage [2]. In September 2015, WHO released new guidelines removing all limitations on eligibility for ART among people living with HIV and recommending pre-exposure prophylaxis (PrEP) to population groups at significant HIV risk, paving the way for a global onslaught on HIV [4].Despite these remarkable advances, this epidemic grows relentlessly worldwide. Over 2.1 million new infections occur each year, two-thirds in women and 240,000 in children [2]. In heavily affected countries, HIV infection rates have only stabilized at best: the annualized acquisition rates in persons in their first decade of sexual activity average 3%–5% yearly in southern Africa [5–7]. These figures are hardly compatible with the international health community’s stated goal of an “AIDS-free generation” [8,9]. In highly resourced settings, microepidemics of HIV still occur, particularly among gays, bisexuals, and men who have sex with men (MSM) [10]. HIV epidemics are expanding in two geographic regions in 2015—the Middle East/North Africa and Eastern Europe/Central Asia—largely due to challenges in implementing evidence-based HIV policies and programmes [2]. Even for the past decade in the US, almost 50,000 new cases recorded annually, two-thirds among MSM, has been a stable figure for years and shows no evidence of declining [1].While treatment scale-up, medical male circumcision [11], and the implementation of strategies to prevent mother-to-child transmission [12] have received global traction, systemic or topical ARV-based biomedical advances to prevent sexual acquisition of HIV have, as yet, made limited impressions on a population basis, despite their reported efficacy. Factors such as their adherence requirements, cost, potential for drug resistance, and long-term feasibility have restricted the appetite for implementation, even though these approaches may reduce HIV incidence in select populations.Already, several trials have shown that daily oral administration of the ARV tenofovir disoproxil fumarate (TDF), taken singly or in combination with emtricitabine, as PrEP by HIV-uninfected individuals, reduces HIV acquisition among serodiscordant couples (where one partner is HIV-positive and the other is HIV-negative) [13], MSM [14], at-risk men and women [15], and people who inject drugs [16,17] by between 44% and 75%. Long-acting injectable antiretroviral agents such as rilpivirine and cabotegravir, administered every two and three months, respectively, are also being developed for PrEP. All of these PrEP approaches are dependent on repeated HIV testing and adherence to drug regimens, which may challenge effectiveness in some populations and contexts.The widespread elimination of HIV will require the development of new, more potent prevention tools. Because HIV acquisition occurs subclinically, the elimination of HIV on a population basis will require a highly effective vaccine. Alternatively, if vaccine development is delayed, supplementary strategies may include long-acting pre-exposure antiretroviral cocktails and/or the administration of neutralizing antibodies through long-lasting parenteral preparations or the development of a “genetic immunization” delivery system, as well as scaling up delivery of highly effective regimens to eliminate mother-to-child HIV transmission (Fig 1).Open in a separate windowFig 1Medical interventions required to end the epidemic of HIV.Image credit: Glenda Gray.     

Walk on the Wild Side: Estimating the Global Magnitude of Visits to Protected Areas

How often do people visit the world’s protected areas (PAs)? Despite PAs covering one-eighth of the land and being a major focus of nature-based recreation and tourism, we don’t know. To address this, we compiled a globally-representative database of visits to PAs and built region-specific models predicting visit rates from PA size, local population size, remoteness, natural attractiveness, and national income. Applying these models to all but the very smallest of the world’s terrestrial PAs suggests that together they receive roughly 8 billion (8 x 109) visits/y—of which more than 80% are in Europe and North America. Linking our region-specific visit estimates to valuation studies indicates that these visits generate approximately US $600 billion/y in direct in-country expenditure and US $250 billion/y in consumer surplus. These figures dwarf current, typically inadequate spending on conserving PAs. Thus, even without considering the many other ecosystem services that PAs provide to people, our findings underscore calls for greatly increased investment in their conservation.Enjoyment of nature, much of it in protected areas (PAs), is recognised as the most prominent cultural ecosystem service [1–3], yet we still lack even a rough understanding of its global magnitude and economic significance. Large-scale assessments have been restricted to regional or biome-specific investigations [4–8] (but see [9]). There are good reasons for this. Information on visit rates is limited, widely scattered, and confounded by variation in methods [10,11]. Likewise, estimates of the value of visits vary greatly—geographically, among methods, and depending on the component of value being measured [12–14]. Until now, these problems have prevented data-driven analysis of the worldwide scale of nature-based recreation and tourism. But with almost all the world’s governments committed (through the Aichi Biodiversity Targets [15]) to integrating biodiversity into national accounts, policymakers require such gaps in our knowledge of natural capital to be filled.We tackled this shortfall in our understanding of a major ecosystem service by focusing on terrestrial PAs, which cover one-eighth of the land [16] and are a major focus of nature-based recreation and tourism. We compiled data on visit rates to over 500 PAs and built region-specific models, which predicted variation in visitation in relation to the properties of PAs and to local socioeconomic conditions. Next, we used these models to estimate visit rates to all but the smallest of the world’s terrestrial PAs. Last, by summing these estimates by region and combining the totals with region-specific medians for the value of nature visits obtained from the literature, we derived approximate estimates of the global extent and economic significance of PA visitation.Given the scarcity of data on visits to PAs, our approach was to use all available information (although we excluded marine and Antarctic sites, and International Union for Conservation of Nature (IUCN) Category I PAs where tourism is typically discouraged; for further details of data collection and analysis see Materials and Methods). This generated a database of visitor records for 556 PAs spread across 51 countries and included 2,663 records of annual visit numbers over our best-sampled ten-year period (1998–2007) (S1 Table). Mean annual visit rates for individual PAs in this sample ranged from zero to over 10 million visits/y, with a median across all sampled PAs of 20,333 visits/y.We explored this variation by modelling it in relation to a series of biophysical and socioeconomic variables that might plausibly predict visit rates (after refs [6,7,17]): PA size, local population size, PA remoteness, a simple measure of the attractiveness of the PA’s natural features, and national income (see Materials and Methods for a priori predictions). For each of five major regions, we performed univariate regressions (S2 Table) and then built generalised linear models (GLMs) in an effort to predict variation in observed visit rates. While the GLMs had modest explanatory power within regions (S3 Table), together they accounted for 52.9% of observed global variation in visit rates. Associations with individual GLM variables—controlling for the effects of other variables—differed regionally in their strength but broadly matched our predictions (S1 Fig.). Visit rates increased with local population size (in Europe), decreased with remoteness (everywhere apart from Asia/Australasia), increased with natural attractiveness (in North and Latin America), and increased with national income (everywhere else). Controlling for these variables, visit rates were highest in North America, lower in Asia/Australasia and Europe, and lowest in Africa and Latin America.To quantify how often people visit PAs as a whole, we used our region-specific GLMs to estimate visit rates to 94,238 sites listed in the World Database on Protected Areas (WDPA) [18]). We again excluded marine, Antarctic, and Category I PAs, as well as almost 40,000 extremely small sites which were below the size (10 ha) of the smallest PA in our sample (S2 Fig.). The limited power of our GLMs and significant errors in the WDPA mean our estimates of visit rates should be treated with caution for individual sites or (when aggregated to national level) for smaller countries. However, the larger-scale patterns they reveal are marked. Estimated median visit rates per PA (averaged within countries) are lowest in Africa (at around 3,000/y) and Latin America (4,000/y), and greatest in North America (350,000/y) (S3 Table). When visit rates are aggregated across all PAs within a country, pronounced regional differences in the numbers of PAs (with relatively few in Africa and Latin America) magnify these patterns and indicate that while many African countries have <100,000 PA visits/y, PAs in the United States receive a combined total of over 3 billion visits/y (Fig. 1). This variation is underscored when aggregate PA visit rates are standardised by the annual number of non-workdays and total population size of each region: across Europe we reckon there are ~5 PA visits/100 non-work person-days; for North America, the figure is ~10 visits/100 non-work person-days respectively, while for each other region our estimates are <0.3 visits/100 non-work person-days.Open in a separate windowFig 1Estimated total PA visit rates for each country.Totals (which are log₁₀-transformed) were derived by applying the relevant regional GLM (S3 Table) to all of a country’s terrestrial PAs (excluding those <10 ha, and marine and IUCN Category I PAs) listed in the WDPA [18]. Asterisks show countries for which we had visit rate observations.Summing our aggregate estimates of PA visits suggests that between them, the world’s terrestrial PAs receive approximately 8 billion visits/y. Of these, we estimate 3.8 billion visits/y are in Europe (where more than half of the PAs in the WDPA are located) and 3.3 billion visits/y are in North America (S3 Table). These numbers are strikingly large. However, given our confidence intervals (95% CIs for the global total: 5.4–18.5 billion/y) and considering several conservative aspects of our calculations (e.g., the exclusion of ~40,000 very small sites and the incomplete nature of the WDPA), we consider it implausible that there are fewer than 5 billion PA visits worldwide each year. Three national estimates support this view: 2.5 billion visitdays/y to US PAs in 1996 [4], >1 billion visits/y (albeit many of them cultural rather than nature-based) to China’s National Parks in 2006 [19], and 3.2–3.9 billion visits/y to all British “ecosystems” (most of which are not in PAs) in 2010 [7].Finally, what can be inferred about the economic significance of visits on this scale? Economists working on tourism distinguish two main, non-overlapping components of value [12]: direct expenditure by visitors (an element of economic impact, calculated from spending on fees, travel, accommodation, etc.); and consumer surplus (a measure of economic value which arises because many visitors would be prepared to pay more for their visit than they actually have to, and which is defined as the difference between what visitors would be prepared to pay for a visit and what they actually spend; consumer surplus is typically quantified using travel cost or contingent valuation methods). We conducted an extensive literature search to derive median (but conservative) figures for each type of value for each region (S4 Table). Applying these to our corresponding estimates of visit rates and summing across regions yields an estimate of global gross direct expenditure associated with PA visits (within-country only, and excluding indirect and induced expenditure) of ~US $600 billion/y worldwide (at 2014 prices). The corresponding figure for global consumer surplus is ~US $250 billion/y.Such numbers are unavoidably imprecise. Uncertainty in our modelled visit rates and the wide variation in published estimates of expenditure and consumer surplus mean that they could be out by a factor of two or more. However, comparison with calculations that visits to North American PAs alone have an economic impact of $350–550 billion/y [4] and that direct expenditure on all travel and tourism worldwide runs at $2,000 billion/y [20] suggests our figures are of the correct order of magnitude, and that the value of PA visitation runs into hundreds of billions of dollars annually.These results quantify, we believe for the first time, the scale of visits to the world’s PAs and their approximate economic significance. We currently spend <$10 billion/y in safeguarding PAs [21]—a figure which is widely regarded as grossly insufficient [21–25]. Even without considering the many other benefits which PAs provide [22], our estimates of the economic impact and value of PA visitation dwarf current expenditure—highlighting the risks of underinvestment in conservation, and suggesting substantially increased investments in protected area maintenance and expansion would yield substantial returns.     

Bacteria can be selected to help beneficial plasmids spread

A recent commentary raised concerns about aspects of the model and assumptions used in a previous study which demonstrated that selection can favor chromosomal alleles that confer higher plasmid donation rates. Here, the authors of that previous study respond to the concerns raised.

In our original work [1], we demonstrated experimentally that selection can favor chromosomal alleles that confer higher plasmid donation rates, given the plasmid is beneficial and the recipient has an elevated chance of carrying the donor allele (i.e., preferential donation to kin). Our experiments demonstrated this effect via 2 mechanisms of preferential donation: biased conjugation rates and structured populations. We interpreted these results through the lens of kin selection theory (benefits via horizontal gene transfer to kin), supported by simulations and an analytical fitness function model. These results hold importance by outlining that the evolution of plasmid transfer rates (a key aspect of the antibiotic resistance crisis) is not necessarily the sole product of selection on the plasmid itself and forms part of a broader series of papers from our labs investigating the sociomicrobiology of plasmids [2–4].A new commentary raises concerns over our fitness function model, flagging issues with both the structure of the model and assumptions made in our analysis [5]. We stand by the general conclusions of our work but accept that our fitness function and stated analysis assumptions could be better formulated. Our initial fitness function is heuristic in the sense it was designed to capture general processes acting on the fitness of individuals, dependent on the plasmid and donor allele status—without explicitly modeling the myriad demographic events of dispersal, reproduction, conjugation, and death that result in selective shifts across a metapopulation of cells. Specifically, we captured the “force of infection” faced by an uninfected cell as the product of average plasmid prevalence and average donor allele prevalence in the local patch (p_jq_j; see commentary for notation details). We agree with the authors that this force of infection is better phrased as the average of the product ((1/N)∑p_ij q_ij), in part because this avoids the potential pathology under limit conditions described by the authors, but also because this approach better highlights that the particular social trait in question is an “other only” cooperative trait [6], illustrated by commentary equation [2], where transmission to self and transmission to others are separated. This separation has the important consequence of highlighting that unlike many microbial social traits where benefits accrue to a group (including self), a cooperative plasmid donor trait can only benefit other cells that lack the plasmid. Given established costs of donation (e.g., see figure S2 in our original article), this defines our “donor” behavior as an altruistic trait, which can, therefore, only be favored by selection given nonrandom interactions among individuals (e.g., [7]).Our experimental results outline 2 mechanisms of nonrandom interactions: preferential donation to kin and population structure. Each of these mechanisms will generate positive covariances between focal individual q_ij and non-self-recipient q_j donor allele states (cov(q_j, q_ij) > 0). The pathway via preferential donation to kin (order-of-magnitude differences according to our analyses and more recent measurements among lineages coexisting within natural populations [8]) will also likely generate positive covariances between donor and recipient abilities (cov(s_ij, q_ij) > 0). In contrast, to arrive at the result that selection always works against plasmid donor alleles (equation [4]), the commentary makes the assumption that both of the above covariances are zero. We suggest that the additional analyses begun by the authors are an exciting starting point to better map selection on donor alleles, under a broader array of defined assumptions on cell–cell and gene–gene structure, ideally informed by data on structures found in natural bacterial populations.     

Origin of the Yeast Whole-Genome Duplication

Whole-genome duplications (WGDs) are rare evolutionary events with profound consequences. They double an organism’s genetic content, immediately creating a reproductive barrier between it and its ancestors and providing raw material for the divergence of gene functions between paralogs. Almost all eukaryotic genome sequences bear evidence of ancient WGDs, but the causes of these events and the timing of intermediate steps have been difficult to discern. One of the best-characterized WGDs occurred in the lineage leading to the baker’s yeast Saccharomyces cerevisiae. Marcet-Houben and Gabaldón now show that, rather than simply doubling the DNA of a single ancestor, the yeast WGD likely involved mating between two different ancestral species followed by a doubling of the genome to restore fertility.The unicellular baker’s yeast Saccharomyces cerevisiae was the first eukaryote to have its genome sequenced, using the first generation of automated sequencing machines and before the advent of the whole-genome shotgun approach. The sequencing was done during the period between 1990 and 1996 by an international consortium that included many small European laboratories, one of which was mine. Each laboratory was given a “tranche” of about 30 kb to sequence, and when you had completed that chunk, you could apply for another one. We were paid €2 per base pair. Progress meetings, chaired energetically by André Goffeau [1], were held every six months to ensure that the project remained on track. At these meetings, each group would make a 5-minute presentation about the genes they had found in their current chunk. The presentations were often tedious, enlivened only by the occasional exigency for André to reassign pieces of DNA from the sequencing tortoises to the hares. But as the project progressed, a pattern began to emerge: many of the chunks were similar to other chunks. The first clone that I sequenced happened to contain the centromere of chromosome II, and I noticed that a gene beside it had a paralog beside the centromere of chromosome IV [2]. My second chunk, from chromosome XV, contained four genes that had four paralogs, in the same order, on chromosome I [3].When the complete genome was released in April 1996, we were able to identify 55 large duplicated blocks of this type, ranging in size from three to 18 duplicated genes (Fig 1) [4]. Two observations indicated that the duplications were quite old: the average amino acid sequence identity between the gene pairs was only 63%, and within each block only about 25% of the genes were actually duplicated, the others being single copy. This pattern suggested that the whole block was initially duplicated, and then many individual genes were deleted. Two other observations suggested that the blocks were remnants of duplicated chromosomes that had become rearranged during evolution: there were almost no overlaps between the blocks, and the orientation of each pair of blocks was conserved relative to the centromeres and telomeres. This layout of blocks was consistent with duplication of the whole genome followed by both extensive deletion of single genes and genome rearrangement solely by the process of reciprocal translocation between chromosomes [4]. Under this hypothesis, there had been an ancient whole-genome duplication (WGD), and the 55 blocks that we could identify were simply the most duplicate-dense regions that still survived without evolutionary rearrangement.Open in a separate windowFig 1A simple model of WGD, gene loss, and synteny relationships.The upper panel shows how duplicated blocks were initially identified using only genes that remain in duplicate in S. cerevisiae [4]. The lower panel shows how additional data from non-WGD yeasts such as Lachancea waltii [5] allowed the parts of the genome that were not initially allocated to blocks to be placed into pairs, providing a duplication map that covered the whole S. cerevisiae genome. Letters A–W represent genes, and dots represent centromeres. Only two chromosomes (yellow and brown) are shown.The hypothesis of a WGD in S. cerevisiae was confirmed in 2004 when three groups sequenced the genomes of species that had branched off from this lineage before the WGD occurred [5–7]. These non-WGD genomes had a “double conserved synteny” relationship with the S. cerevisiae genome—that is, instead of each pair of duplicated regions, they had a single region containing all the genes in a merged order (Fig 1). This discovery allowed the entire genome of S. cerevisiae to be mapped into pairs of regions via their double conserved synteny with the non-WGD species, even if the pairs retain no duplicated genes, thus filling the gaps between the initial map of 55 duplicated blocks. These analyses proved that the WGD encompassed the entire genome of S. cerevisiae and showed that its 16 centromeres fall into eight ancestral pairs that are syntenic with centromeres of the non-WGD species. It therefore appeared that the WGD turned an eight-chromosome ancestor into a 16-chromosome descendant. From this complete map, we now know that among the 5,774 protein-coding genes of S. cerevisiae, there are 551 pairs of duplicated genes (ohnologs) that were formed by the WGD and that about 144 chromosomal rearrangements scrambled the genome after the WGD [8,9]. We also know that the WGD is not confined to Saccharomyces but occurred in the common ancestor of six genera, some of which diverged from each at an early stage when more than 4,000 genes were still duplicated, leading to later losses of different gene copies in different lineages [10].What were the molecular events that caused the WGD? It is relatively easy to draw a diagram summarizing the history of each chromosomal region (Fig 2), but it is much more difficult to specify the provenance of the intermediate molecules and the timescales involved. Two alternative scenarios can describe the steps in Fig 2. In both scenarios, event 1 is a DNA replication, and cells W and Z are each capable of mating (they are respectively a non-WGD haploid and a post-WGD haploid). The key question is whether the DNA molecules labeled X and Y existed in (1) two different cells of the same species or (2) two cells of two different species. Scenario 1 is called autopolyploidization, in which case event 1 corresponds to a simple cell division and event 2 is a mating between gametes from the same species or some other form of cell fusion. Scenario 2 is called allopolyploidization or hybridization, in which case event 1 is a speciation and event 2 is an interspecies mating or cell fusion. If event 2 was a mating, then an additional step such as deletion of one allele at the MAT locus is necessary to convert cell Z from a nonmating zygote to a mating gamete—but it is not essential that this additional step occurred immediately after event 2. In fact, a long delay in which cell Z replicated mitotically for many generations could be useful because it could allow reproductive isolation from cells of type W to build up. Eventually (event 3), mating between two post-WGD haploid cells of type Z can produce a post-WGD diploid like cell ZZ, which is the state in which S. cerevisiae is normally found in nature.Open in a separate windowFig 2Tracing the history of a single chromosomal region.See text for details. In an allopolyploidization, the red and blue chromosomes are called homeologs.The major difference between these two scenarios is the amount of time (T) that elapsed between events 1 and 2: was it a few generations or millions of years? In scenario 1, molecules X and Y must be identical, whereas in scenario 2 they could have any level of sequence divergence from minimal to extensive, and they could also differ by chromosomal rearrangements. It has been difficult to design tests that could differentiate between these scenarios, but an analysis of the inferred order of genes along molecules X and Y did not find any rearrangements and so did not rule out scenario 1 [9]. However, it has been frustrating that we could not pin down the details of this crucial phase of yeast evolution, which gave birth to many pairs of genes with substantially divergent functions [11–15].In this issue of PLOS Biology, Marcet-Houben and Gabaldón now report strong evidence in support of interspecies hybridization (scenario 2) as the source of the two subgenomes in post-WGD species [16]. By phylogenetic analysis using state-of-the-art methods, they show that molecules X and Y have phylogenetic affinities to two different non-WGD lineages that they call the KLE and ZT clades. The KLE clade (Kluyveromyces, Lachancea, and Eremothecium) is the group of non-WGD species that was sequenced in 2004 [5–7]. The ZT clade (Zygosaccharomyces and Torulaspora) is a separate, more recently studied non-WGD lineage [17,18]. Previous phylogenetic studies using supertrees or concatenated data suggested that the ZT clade is sister to the post-WGD clade, with the KLE clade being an out-group to them both [17,19,20]. The new analysis [16] made trees for each gene individually and found that, although the majority of genes in post-WGD species do cluster phylogenetically with the ZT clade as expected, a significant minority (about 30%) instead either cluster with the KLE clade or form an outgroup to a KLE + ZT clade. This phylogenetic heterogeneity was not noticed before because the KLE signal is only present in a minority of genes, and it is swamped by the ZT signal in methods that try to place the post-WGD clade at a single point on the tree.Marcet-Houben and Gabaldón interpret this phylogenetic heterogeneity as evidence that the two post-WGD subgenomes have separate origins, one from the ZT clade and the other from an unidentified lineage that is an outgroup to KLE + ZT. Under the simplest hypothesis of hybridization, we might then expect that phylogenetic trees constructed from ohnolog pairs should show one S. cerevisiae gene grouping with the ZT clade and the other grouping with the KLE clade, but in fact, most ohnolog pairs group with each other, with the ZT clade as their closest relative [16]. The authors’ explanation for these two results—an excess of ZT-like ohnolog pairs, and an excess of ZT-like genes in the whole genome (which is mostly singletons)—is that the post-WGD genomes have been affected by biased gene conversion that preferentially replaced some KLE-derived sequences with copies of the homeologous ZT-derived sequences, homogenizing these regions and obliterating their signal of KLE ancestry.The hybridization proposed by Marcet-Houben and Gabaldón makes a lot of sense in terms of what we know about the biology of yeast interspecies hybrids. Many yeast strains, most notably those used in commercial settings where stress tolerance is important, have turned out to be interspecies hybrids. For instance, the yeast used to brew lager (S. pastorianus) is a hybrid between S. cerevisiae and S. eubayanus [21,22], and many other combinations of genomes from different species of Saccharomyces have been found in nature [23]. These interspecies hybrids are usually infertile (unable to sporulate) because the two copies (homeologs) of each chromosome that they contain are too dissimilar to pair properly during meiosis [24–26]. One simple way to restore fertility is to double the genome, allowing each chromosome to pair with an identical partner instead of trying to pair with the homeolog. In this model, cell Z changes from being a nonmater (effectively diploid) to a mater (effectively haploid—perhaps by deletion of a MAT allele), then two cells of type Z mate to produce cell ZZ (diploid), and cell ZZ is able to go through meiosis and make spores with twice the DNA content of cell W. Thus, one hypothesis that Marcet-Houben and Gabaldón propose is that event 2 was an interspecies mating and event 3 was a restoration of fertility by genome doubling, with a possible interval of many mitotic generations between these two events. Alternatively, they hypothesize that event 2 may have been an interspecies fusion of diploid cells, obviating the need for a separate event 3.The obscuring of the phylogenetic signal of hybridization by subsequent gene conversions [16] is consistent with the known genome structures of some interspecies hybrids. The yeasts Pichia sorbitophila [27] and Candida orthopsilosis [28] are both interspecies hybrids, but in each case extensive homogenization of parts of the genome has occurred. This process of homogenization has been called overwriting, loss of heterozygosity, or gene conversion by different groups. It leaves the number of chromosomes unchanged (equal to the sum of the numbers of chromosomes in the two incoming subgenomes) but involves the replacement of sequences in one subgenome by sequences copied from the other subgenome (cell H in Fig 2). Homogenization could occur on scales as small as a few hundred base pairs (gene conversion) or as large as whole chromosome arms (break-induced replication). In the latter case, even differences in gene order such as inversions between the parental species could be ironed out.The discovery that the yeast WGD was an allopolyploidization adds complexity to what initially seemed to be a simple story of duplication. If an interspecies hybrid such as P. sorbitophila with a partly homogenized genome developed two mating types and these could mate to form a diploid that could sporulate efficiently, the result would be a species with a genome resembling the inferred progenitor of the post-WGD clade (cell HH in Fig 2). Allopolyploidy answers some old questions about why genes were retained in duplicate if their sequences were identical (answer: they weren’t identical), what the immediate selective advantage of the post-WGD cell was (answer: hybrid vigor), and how the post-WGD lineage became reproductively isolated from the pre-WGD lineage (answer: delay between events 2 and 3). But it also raises new questions about homogenization (how much of the genome? how often? why is it biased?) and about the mechanism of restoration of fertility (why is event 3 so rare, apparently happening only once in the budding yeast family even though event 2 happened quite often?).Ancient WGDs have been detected right across the eukaryotic tree of life, including in animals, ciliates, fungi, and, most prominently, plants [29–32]. If extensive gene conversion can obscure the traces of allopolyploidization in yeast genomes, one might wonder how many of these other ancient WGDs also began as interspecies hybridizations. In fact, there is evidence from plants that gene conversion acts continually to homogenize ohnolog pairs [32,33] and that hybrid plants can show preferential retention of DNA from one parent over the other [34] similar to the situation in P. sorbitophila [27]. Detecting the yeast hybridization in the presence of these obscuring factors required both good luck and good timing: good luck that a reference species closer to one parent than to the other had been sequenced and good timing that the hybrid was sampled before all traces of its hybrid origin had faded away. These fortunate circumstances may not hold for ancient hybridizations in other eukaryotes, but as a famous golfer once said, “The harder I practice, the luckier I get.” Detecting that they are hybridizations may become possible with exhaustive sampling of possible parental lineages and the use of sensitive phylogenomic methods of the type introduced by the authors [16].     

Whisking,Sniffing, and the Hippocampal θ-Rhythm: A Tale of Two Oscillators

The hippocampus has unique access to neuronal activity across all of the neocortex. Yet an unanswered question is how the transfer of information between these structures is gated. One hypothesis involves temporal-locking of activity in the neocortex with that in the hippocampus. New data from the Matthew E. Diamond laboratory shows that the rhythmic neuronal activity that accompanies vibrissa-based sensation, in rats, transiently locks to ongoing hippocampal θ-rhythmic activity during the sensory-gathering epoch of a discrimination task. This result complements past studies on the locking of sniffing and the θ-rhythm as well as the relation of sniffing and whisking. An overarching possibility is that the preBötzinger inspiration oscillator, which paces whisking, can selectively lock with the θ-rhythm to traffic sensorimotor information between the rat’s neocortex and hippocampus.The hippocampus lies along the margins of the cortical mantle and has unique access to neuronal activity across all of the neocortex. From a functional perspective, the hippocampus forms the apex of neuronal processing in mammals and is a key element in the short-term working memory, where neuronal signals persist for tens of seconds, that is independent of the frontal cortex (reviewed in [1,2]). Sensory information from multiple modalities is highly transformed as it passes from primary and higher-order sensory areas to the hippocampus. Several anatomically defined regions that lie within the temporal lobe take part in this transformation, all of which involve circuits with extensive recurrent feedback connections (reviewed in [3]) (Fig 1). This circuit motif is reminiscent of the pattern of connectivity within models of associative neuronal networks, whose dynamics lead to the clustering of neuronal inputs to form a reduced set of abstract representations [4] (reviewed in [5]). The first way station in the temporal lobe contains the postrhinal and perirhinal cortices, followed by the medial and lateral entorhinal cortices. Of note, olfactory input—which, unlike other senses, has no spatial component to its representation—has direct input to the lateral entorhinal cortex [6]. The third structure is the hippocampus, which contains multiple substructures (Fig 1).Open in a separate windowFig 1Schematic view of the circuitry of the temporal lobe and its connections to other brain areas of relevance.Figure abstracted from published results [7–15]. Composite illustration by Julia Kuhl.The specific nature of signal transformation and neuronal computations within the hippocampus is largely an open issue that defines the agenda of a great many laboratories. Equally vexing is the nature of signal transformation as the output leaves the hippocampus and propagates back to regions in the neocortex (Fig 1)—including the medial prefrontal cortex, a site of sensory integration and decision-making—in order to influence perception and motor action. The current experimental data suggest that only some signals within the sensory stream propagate into and out of the hippocampus. What regulates communication with the hippocampus or, more generally, with structures within the temporal lobe? The results from studies in rats and mice suggest that the most parsimonious hypothesis, at least for rodents, involves the rhythmic nature of neuronal activity at the so-called θ-rhythm [16], a 5–10 Hz oscillation (reviewed in [17]). The origin of the rhythm is not readily localized to a single locus [10], but certainly involves input from the medial septum [17] (a member of the forebrain cholinergic system) as well as from the supramammillary nucleus [10,18] (a member of the hypothalamus). The medial septum projects broadly to targets in the hippocampus and entorhinal cortex (Fig 1) [10]. Many motor actions, such as the orofacial actions of sniffing, whisking, and licking, occur within the frequency range of the θ-rhythm [19,20]. Thus, sensory input that is modulated by rhythmic self-motion can, in principle, phase-lock with hippocampal activity at the θ-rhythm to ensure the coherent trafficking of information between the relevant neocortical regions and temporal lobe structures [21–23].We now shift to the nature of orofacial sensory inputs, specifically whisking and sniffing, which are believed to dominate the world view of rodents [19]. Recent work identified a premotor nucleus in the ventral medulla, named the vibrissa region of the intermediate reticular zone, whose oscillatory output is necessary and sufficient to drive rhythmic whisking [24]. While whisking can occur independently of breathing, sniffing and whisking are synchronized in the curious and aroused animal [24,25], as the preBötzinger complex in the medulla [26]—the oscillator for inspiration—paces whisking at nominally 5–10 Hz through collateral projections [27]. Thus, for the purposes of reviewing evidence for the locking of orofacial sensory inputs to the hippocampal θ-rhythm, we confine our analysis to aroused animals that function with effectively a single sniff/whisk oscillator [28].What is the evidence for the locking of somatosensory signaling by the vibrissae to the hippocampal θ-rhythm? The first suggestion of phase locking between whisking and the θ-rhythm was based on a small sample size [29,30], which allowed for the possibility of spurious correlations. Phase locking was subsequently reexamined, using a relatively large dataset of 2 s whisking epochs, across many animals, as animals whisked in air [31]. The authors concluded that while whisking and the θ-rhythm share the same spectral band, their phases drift incoherently. Yet the possibility remained that phase locking could occur during special intervals, such as when a rat learns to discriminate an object with its vibrissae or when it performs a memory-based task. This set the stage for a further reexamination of this issue across different epochs in a rewarded task. Work from Diamond''s laboratory that is published in the current issue of PLOS Biology addresses just this point in a well-crafted experiment that involves rats trained to perform a discrimination task.Grion, Akrami, Zuo, Stella, and Diamond [32] trained rats to discriminate between two different textures with their vibrissae. The animals were rewarded if they turned to a water port on the side that was paired with a particular texture. Concurrent with this task, the investigators also recorded the local field potential in the hippocampus (from which they extracted the θ-rhythm), the position of the vibrissae (from which they extracted the evolution of phase in the whisk cycle), and the spiking of units in the vibrissa primary sensory cortex. Their first new finding is a substantial increase in the amplitude of the hippocampal field potential at the θ-rhythm frequency—approximately 10 Hz for the data of Fig 2A—during the two, approximately 0.5 s epochs when the animal approaches the textures and whisks against it. There is significant phase locking between whisking and the hippocampal θ-rhythm during both of these epochs (Fig 2B), as compared to a null hypothesis of whisking while the animal whisked in air outside the discrimination zone. Unfortunately, the coherence between whisking and the hippocampal θ-rhythm could not be ascertained during the decision, i.e., turn and reward epochs. Nonetheless, these data show that the coherence between whisking and the hippocampal θ-rhythm is closely aligned to epochs of active information gathering.Open in a separate windowFig 2Summary of findings on the θ-rhythm in a rat during a texture discrimination task, derived from reference [32]. (A) Spectrogram showing the change in spectral power of the local field potential in the hippocampal area CA1 before, during, and after a whisking-based discrimination task. (B) Summary index of the increase in coherence between the band-limited hippocampal θ-rhythm and whisking signals during approach of the rat to the stimulus and subsequent touch. The index reports 〈sin(ϕH−ϕW)〉2+〈cos(ϕH−ϕW)〉2, where ɸ_H and ɸ_W are the instantaneous phase of the hippocampal and whisking signals, respectively, and averaging is over all trials and animals. (C) Summary indices of the increase in coherence between the band-limited hippocampal θ-rhythm and the spiking signal in the vibrissa primary sensory cortex (“barrel cortex”). The magnitude of the index for each neuron is plotted versus phase in the θ-rhythm. The arrows show the concentration of units around the mean phase—black arrows for the vector average across only neurons with significant phase locking (solid circles) and gray arrows for the vector average across all neurons (open and closed circles). The concurrent positions of the vibrissae are indicated. The vector average is statistically significant only for the approach (p < 0.0001) and touch (p = 0.04) epochs.The second finding by Grion, Akrami, Zuo, Stella, and Diamond [32] addresses the relationship between spiking activity in the vibrissa primary sensory cortex and the hippocampal θ-rhythm. The authors find that spiking is essentially independent of the θ-rhythm outside of the task (foraging in Fig 2C), similar to the result for whisking and the θ-rhythm (Fig 2B). They observe strong coherence between spiking and the θ-rhythm during the 0.5 s epoch when the animal approaches the textures (approach in Fig 2C), yet reduced (but still significant) coherence during the touch epoch (touch in Fig 2C). The latter result is somewhat surprising, given past work from a number of laboratories that observe spiking in the primary sensory cortex and whisking to be weakly yet significantly phase-locked during exploratory whisking [33–37]. Perhaps overtraining leads to only a modest need for the transfer of sensory information to the hippocampus. Nonetheless, these data establish that phase locking of hippocampal and sensory cortical activity is essentially confined to the epoch of sensory gathering.Given the recent finding of a one-to-one locking of whisking and sniffing [24], we expect to find direct evidence for the phase locking of sniffing and the θ-rhythm. Early work indeed reported such phase locking [38] but, as in the case of whisking [29], this may have been a consequence of too small a sample and, thus, inadequate statistical power. However, Macrides, Eichenbaum, and Forbes [39] reexamined the relationship between sniffing and the hippocampal θ-rhythm before, during, and after animals sampled an odorant in a forced-choice task. They found evidence that the two rhythms phase-lock within approximately one second of the sampling epoch. We interpret this locking to be similar to that seen in the study by Diamond and colleagues (Fig 2B) [32]. All told, the combined data for sniffing and whisking by the aroused rodent, as accumulated across multiple laboratories, suggest that two oscillatory circuits—the supramammillary nucleus and medial septum complex that drives the hippocampal θ-rhythm and the preBötzinger complex that drives inspiration and paces the whisking oscillator during sniffing (Fig 1)—can phase-lock during epochs of gathering sensory information and likely sustain working memory.What anatomical pathway can lead to phase locking of these two oscillators? The electrophysiological study of Tsanov, Chah, Reilly, and O’Mara [9] supports a pathway from the medial septum, which is driven by the supramammillary nucleus, to dorsal pontine nuclei in the brainstem. The pontine nucleus projects to respiratory nuclei and, ultimately, the preBötzinger oscillator (Fig 1). This unidirectional pathway can, in principle, entrain breathing and whisking. Phase locking is not expected to occur during periods of basal breathing, when the breathing rate and θ-rhythm occur at highly incommensurate frequencies. However, it remains unclear why phase locking occurs only during a selected epoch of a discrimination task, whereas breathing and the θ-rhythm occupy the same frequency band during the epochs of approach, as well as touch-based target selection (Fig 2A). While a reafferent pathway provides the rat with information on self-motion of the vibrissae (Fig 1), it is currently unknown whether that information provides feedback for phase locking.A seeming requirement for effective communication between neocortical and hippocampal processing is that phase locking must be achieved at all possible phases of the θ-rhythm. Can multiple phase differences between sensory signals and the hippocampal θ-rhythm be accommodated? Two studies report that the θ-rhythm undergoes a systematic phase-shift along the dorsal–ventral axis of the hippocampus [40,41], although the full extent of this shift is only π radians [41]. In addition, past work shows that vibrissa input during whisking is represented among all phases of the sniff/whisk cycle, at levels from primary sensory neurons [42,43] through thalamus [44,45] and neocortex [33–37], with a bias toward retraction from the protracted position. A similar spread in phase occurs for olfactory input, as observed at the levels of the olfactory bulb [46] and cortex [47]. Thus, in principle, the hippocampus can receive, transform, and output sensory signals that arise over all possible phases in the sniff/whisk cycle. In this regard, two signals that are exactly out-of-phase by π radians can phase-lock as readily as signals that are in-phase.What are the constraints for phase locking to occur within the observed texture identification epochs? For a linear system, the time to lock between an external input and hippocampal theta depends on the observed spread in the spectrum of the θ-rhythm. This is estimated as Δf ~3 Hz (half-width at half-maximum amplitude), implying a locking time on the order of 1/Δf ~0.3 s. This is consistent with the approximate one second of enhanced θ-rhythm activity observed in the study by Diamond and colleagues (Fig 2A) [32] and in prior work [39,48] during a forced-choice task with rodents.Does the θ-rhythm also play a role in the gating of output from the hippocampus to areas of the neocortex? Siapas, Lubenov, and Wilson [48] provided evidence that hippocampal θ-rhythm phase-locks to electrical activity in the medial prefrontal cortex, a site of sensory integration as well as decision-making. Subsequent work [49–51] showed that the hippocampus drives the prefrontal cortex, consistent with the known unidirectional connectivity between Cornu Ammonis area 1 (CA1) of the hippocampus and the prefrontal cortex [11] (Fig 1). Further, phase locking of hippocampal and prefrontal cortical activity is largely confined to the epoch of decision-making, as opposed to the epoch of sensory gathering. Thus, over the course of approximately one second, sensory information flows into and then out of the hippocampus, gated by phase coherence between rhythmic neocortical and hippocampal neuronal activity.It is of interest that the medial prefrontal cortex receives input signals from sensory areas in the neocortex [52] as well as a transformed version of these input signals via the hippocampus (Fig 1). Yet it remains to be determined if this constitutes a viable hub for the comparison of the original and transformed signals. In particular, projections to the medial prefrontal cortex arise from the ventral hippocampus [2], while studies on the phase locking of hippocampal θ-rhythm to prefrontal neocortical activity were conducted in dorsal hippocampus, where the strength of the θ-rhythm is strong compared to the ventral end [53]. Therefore, similar recordings need to be performed in the ventral hippocampus. An intriguing possibility is that the continuous phase-shift of the θ-rhythm along the dorsal to the ventral axis of the hippocampus [40,41] provides a means to encode the arrival of novel inputs from multiple sensory modalities relative to a common clock.A final issue concerns the locking between sensory signals and hippocampal neuronal activity in species that do not exhibit a continuous θ-rhythm, with particular reference to bats [54–56] and primates [57–60]. One possibility is that only the up and down swings of neuronal activity about a mean are important, as opposed to the rhythm per se. In fact, for animals in which orofacial input plays a relatively minor role compared to rodents, such a scheme of clocked yet arrhythmic input may be a necessity. In this case, the window of processing is set by a stochastic interval between transitions, as opposed to the periodicity of the θ-rhythm. This may imply that up/down swings of neuronal activity may drive hippocampal–neocortical communications in all species, with communication mediated via phase-locked oscillators in rodents and via synchronous fluctuations in bats and primates. The validity of this scheme and its potential consequence on neuronal computation remains an open issue and a focus of ongoing research.     

The Hologenome Concept: Helpful or Hollow?

With the increasing appreciation for the crucial roles that microbial symbionts play in the development and fitness of plant and animal hosts, there has been a recent push to interpret evolution through the lens of the “hologenome”—the collective genomic content of a host and its microbiome. But how symbionts evolve and, particularly, whether they undergo natural selection to benefit hosts are complex issues that are associated with several misconceptions about evolutionary processes in host-associated microbial communities. Microorganisms can have intimate, ancient, and/or mutualistic associations with hosts without having undergone natural selection to benefit hosts. Likewise, observing host-specific microbial community composition or greater community similarity among more closely related hosts does not imply that symbionts have coevolved with hosts, let alone that they have evolved for the benefit of the host. Although selection at the level of the symbiotic community, or hologenome, occurs in some cases, it should not be accepted as the null hypothesis for explaining features of host–symbiont associations.The ubiquity and importance of microorganisms in the lives of plants and animals are ever more apparent, and increasingly investigated by biologists. Suddenly, we have the aspiration and tools to open up a new, complicated world, and we must confront the realization that almost everything about larger organisms has been shaped by their history of evolving from, then with, microorganisms [1]. This development represents a dramatic shift in perspective—arguably a revolution—in modern biology.Do we need to revamp basic tenets of evolutionary theory to understand how hosts evolve with associated microorganisms? Some scientists have suggested that we do [2], and the recently introduced terms “holobiont” and “hologenome” encapsulate what has been described as an “emerging postmodern synthesis” [3]. Holobiont was initially used to refer to a host and a single inherited symbiont [4] but was later extended to a host and its community of associated microorganisms, specifically for the case of corals [5]. The idea of the holobiont is that a host and its associated microorganisms must be considered as an integrated unit in order to understand many biological and ecological features.The later introduction of the term hologenome [2,6,7] sought to describe a holobiont by its genetic composition. The term has been used in different ways by different authors, but in most contexts a hologenome is considered a genetic unit that represents the combined genomes of a host and its associated microorganisms [8]. This non-controversial definition of hologenome is linked to the idea that this entity has a role in evolution. For example, Gordon et al. [1,9] state, "The genome of a holobiont, termed the hologenome, is the sum of the genomes of all constituents, all of which can evolve within that context." That last phrase is sufficiently general that it can be interpreted in any number of ways. Like physical conditions, associated organisms can be considered as part of the environment and thus can be sources of natural selection, affecting evolution in each lineage.But a more sweeping and problematic proposal is given by originators of the term, which is that "the holobiont with its hologenome should be considered as the unit of natural selection in evolution" [2,7] or by others, that “an organism’s genetics and fitness are inclusive of its microbiome” [3,4]. The implication is that differential success of holobionts influences evolution of participating organisms, such that their observed features cannot be fully understood without considering selection at the holobiont level. Another formulation of this concept is the proposal that the evolution of host–microbe systems is “most easily understood by equating a gene in the nuclear genome to a microbe in the microbiome” [8]. Under this view, interactions between host and microbial genotypes should be considered as genetic epistasis (interactions among alleles at different loci in a genome) rather than as interactions between the host’s genotype and its environment.While biologists would agree that microorganisms have important roles in host evolution, this statement is a far cry from the claim that they are fused with hosts to form the primary units of selection, or that hosts and microorganisms provide different portions of a unified genome. Broadly, the hologenome concept contends, first, that participating lineages within a holobiont affect each other’s evolution, and, second, that that the holobiont is a primary unit of selection. Our aim in this essay is to clarify what kinds of evidence are needed for each of these claims and to argue that neither should be assumed without evidence. We point out that some observations that superficially appear to support the concept of the hologenome have spawned confusion about real biological issues (Box 1).

Box 1. Misconceptions Related to the Hologenome Concept

Misconception #1: Similarities in microbiomes between related host species result from codiversification. Reality: Related species tend to be similar in most traits. Because microbiome composition is a trait that involves living organisms, it is tempting to assume that these similarities reflect a shared evolutionary history of host and symbionts. This has been shown to be the case for some symbioses (e.g., ancient maternally inherited endosymbionts in insects). But for many interactions (e.g., gut microbiota), related hosts may have similar effects on community assembly without any history of codiversification between the host and individual microbial species (Fig 1B).Open in a separate windowFig 1Alternative evolutionary processes can result in related host species harboring similar symbiont communities.Left panel: Individual symbiont lineages retain fidelity to evolving host lineages, through co-inheritance or other mechanisms, with some gain and loss of symbiont lineages over evolutionary time. Right panel: As host lineages evolve, they shift their selectivity of environmental microbes, which are not evolving in response and which may not even have been present during host diversification. In both cases, measures of community divergence will likely be smaller for more closely related hosts, but they reflect processes with very different implications for hologenome evolution. Image credit: Nancy Moran and Kim Hammond, University of Texas at Austin. Misconception #2: Parallel phylogenies of host and symbiont, or intimacy of host and symbiont associations, reflect coevolution. Reality: Coevolution is defined by a history of reciprocal selection between parties. While coevolution can generate parallel phylogenies or intimate associations, these can also result from many other mechanisms. Misconception #3: Highly intimate associations of host and symbionts, involving exchange of cellular metabolites and specific patterns of colonization, result from a history of selection favoring mutualistic traits. Reality: The adaptive basis of a specific trait is difficult to infer even when the trait involves a single lineage, and it is even more daunting when multiple lineages contribute. But complexity or intimacy of an interaction does not always imply a long history of coevolution nor does it imply that the nature of the interaction involves mutual benefit. Misconception #4: The essential roles that microbial species/communities play in host development are adaptations resulting from selection on the symbionts to contribute to holobiont function. Reality: Hosts may adapt to the reliable presence of symbionts in the same way that they adapt to abiotic components of the environment, and little or no selection on symbiont populations need be involved. Misconception #5: Because of the extreme importance of symbionts in essential functions of their hosts, the integrated holobiont represents the primary unit of selection. Reality: The strength of natural selection at different levels of biological organization is a central issue in evolutionary biology and the focus of much empirical and theoretical research. But insofar as there is a primary unit of selection common to diverse biological systems, it is unlikely to be at the level of the holobiont. In particular cases, evolutionary interests of host and symbionts can be sufficiently aligned such that the predominant effect of natural selection on genetic variation in each party is to increase the reproductive success of the holobiont. But in most host–symbiont relationships, contrasting modes of genetic transmission will decouple selection pressures.     

Peer-Led Team Learning Helps Minority Students Succeed

Active learning methods have been shown to be superior to traditional lecture in terms of student achievement, and our findings on the use of Peer-Led Team Learning (PLTL) concur. Students in our introductory biology course performed significantly better if they engaged in PLTL. There was also a drastic reduction in the failure rate for underrepresented minority (URM) students with PLTL, which further resulted in closing the achievement gap between URM and non-URM students. With such compelling findings, we strongly encourage the adoption of Peer-Led Team Learning in undergraduate Science, Technology, Engineering, and Mathematics (STEM) courses.Recent, extensive meta-analysis of over a decade of education research has revealed an overwhelming consensus that active learning methods are superior to traditional, passive lecture, in terms of student achievement in post-secondary Science, Technology, Engineering, and Mathematics (STEM) courses [1]. In light of such clear evidence that traditional lecture is among the least effective modes of instruction, many institutions have been abandoning lecture in favor of “flipped” classrooms and active learning strategies. Regrettably, however, STEM courses at most universities continue to feature traditional lecture as the primary mode of instruction.Although next-generation active learning classrooms are becoming more common, large instructor-focused lecture halls with fixed seating are still the norm on most campuses—including ours, for the time being. While there are certainly ways to make learning more active in an amphitheater, peer-interactive instruction is limited in such settings. Of course, laboratories accompanying lectures often provide more active learning opportunities. But in the wake of commendable efforts to increase rigorous laboratory experiences at the sophomore and junior levels at Syracuse University, a difficult decision was made for the two-semester, mixed-majors introductory biology sequence: the lecture sections of the second semester course were decoupled from the laboratory component, which was made optional. There were good reasons for this change, from both departmental and institutional perspectives. However, although STEM students not enrolling in the lab course would arguably be exposed to techniques and develop foundational process skills in the new upper division labs, we were concerned about the implications for achievement among those students who would opt out of the introductory labs. Our concerns were apparently warranted, as students who did not take the optional lab course, regardless of prior achievement, earned scores averaging a letter grade lower than those students who enrolled in the lab. However, students who opted out of the lab but engaged in Peer-Led Team Learning (PLTL) performed at levels equivalent to students who also took the lab course [2].Peer-Led Team Learning is a well-defined active learning model involving small group interactions between students, and it can be used along with or in place of the traditional lecture format that has become so deeply entrenched in university systems (Fig 1, adapted from [3]). PLTL was originally designed and implemented in undergraduate chemistry courses [4,5], and it has since been implemented in other undergraduate science courses, such as general biology and anatomy and physiology [6,7]. Studies on the efficacy of PLTL have shown improvements in students’ grade performance, attitudes, retention in the course [6–11], conceptual reasoning [12], and critical thinking [13], though findings related to the critical thinking benefits for peer leaders have not been consistent [14].Open in a separate windowFig 1The PLTL model.In the PLTL workshop model, students work in small groups of six to eight students, led by an undergraduate peer leader who has successfully completed the same course in which their peer-team students are currently enrolled. After being trained in group leadership methods, relevant learning theory, and the conceptual content of the course, peer leaders (who serve as role models) work collaboratively with an education specialist and the course instructor to facilitate small group problem-solving. Leaders are not teachers. They are not tutors. They are not considered to be experts in the content, and they are not expected to provide answers to the students in the workshop groups. Rather, they help mentor students to actively construct their own understanding of concepts.     

Harnessing Evolution to Elucidate the Consequences of Symbiosis

Many organisms harbor microbial associates that have profound impacts on host traits. The phenotypic effect of symbionts on their hosts may include changes in development, reproduction, longevity, and defense against natural enemies. Determining the consequences of associating with a microbial symbiont requires experimental comparison of hosts with and without symbionts. Then, determining the mechanism by which symbionts alter these phenotypes can involve genomic, genetic, and evolutionary approaches; however, many host-associated symbionts are not amenable to genetic approaches that require cultivation of the microbe outside the host. In the current issue of PLOS Biology, Chrostek and Teixeira highlight an elegant approach to studying functional mechanisms of symbiont-conferred traits. They used directed experimental evolution to select for strains of Wolbachia wMelPop (a bacterial symbiont of fruit flies) that differed in copy number of a region of the genome suspected to underlie virulence. Copy number evolved rapidly when under selection, and wMelPop strains with more copies of the region shortened the lives of their Drosophila hosts more than symbionts with fewer copies. Interestingly, the wMelPop strains with more copies also increase host resistance to viruses compared to symbionts with fewer copies. Their study highlights the power of exploiting alternative approaches when elucidating the functional impacts of symbiotic associations.Symbioses, long-term and physically close interactions between two or more species, are central to the ecology and evolution of many organisms. Though “Symbiosis” is more often used to define interactions that are presumed to be mutually beneficial to a host and its microbial partner, a broader definition including both parasitic and mutualistic interactions recognizes that the fitness effects of many symbioses are complex and often context dependent. Whether an association is beneficial can depend on ecological conditions, and mutation and other evolutionary processes can result in symbiont strains that differ in terms of costs and benefits to hosts (Fig. 1).Open in a separate windowFig 1The symbiosis spectrum.The costs and benefits of symbiosis for hosts are not bimodal but span a continuum. The benefit to cost ratio is mediated both by environmental conditions and by the strain of symbiont. For example, the bacteria Hamiltonella defensa increases aphid resistance to parasitoid wasps. When Hamiltonella loses an associated bacteriophage, protection is lost. Also, in aphids, Buchnera aphidicola is a bacterial symbiont that provisions its hosts with critical nutritional resources. However, alterations of the heat shock promoter in Buchnera lessen the fitness benefit of symbiosis for the hosts under elevated temperatures. Amplification of a region of the Wolbachia genome known as Octomom causes the bacteria to shorten the lifespan of its Drosophila fly hosts.Elucidating the effects of host-associated microbes includes, when possible, experiments designed to assay host phenotypes when they do and do not have a particular symbiont of interest (Fig. 2). In systems in which hosts acquire symbionts from the environment, hosts can be reared in sterile conditions to prevent acquisition [1]. If symbionts are passed internally from mother to offspring, antibiotic treatments can sometimes be utilized to obtain lineages of hosts without symbionts [2]. The impacts of symbiont presence on survival, development, reproduction, and defense can be quantified, with the caveat that these impacts may be quite different under alternative environmental conditions. While such experiments are sometimes more tractable in systems with simple microbial consortia, the same experimental processes can be utilized in systems with more complex microbial communities [3,4].Open in a separate windowFig 2Approaches to functionally characterize symbiont effects.The first step in functionally characterizing the phenotypic impacts of a symbiont on its host is to measure phenotypes of hosts with and without symbionts. Any effects need to be considered in the light of how they are modified by environmental conditions. Understanding the mechanisms underlying symbiont alteration of host phenotype can involve, and often combines, genomic, genetic, and evolutionary approaches. Solid arrows indicate the path leading to results highlighted in Chrostek and Teixeira’s investigation of Wolbachia virulence in this issue of PLoS Biology.Once a fitness effect of symbiosis is ascertained, determining the mechanistic basis of this effect can be challenging. A genomics approach sometimes provides informative insight into microbial function. Sequencing of many insect-associated symbionts, for example, has confirmed the presence of genes necessary for amino acid and vitamin synthesis [5–8]. These genomic revelations, in some cases, can be linked to phenotypic effects of symbiosis for the hosts. For example, aphids reared in the absence of their obligate symbiotic bacteria, Buchnera aphidicola, can survive when provisioned with supplemental amino acids but cannot survive without supplementation, suggesting that Buchnera’s provisioning of amino acids is critical for host survival [9,10]. The Buchnera genome contains many of the genes necessary for amino acid synthesis [5].Linking genotype to phenotype, however, can be complicated. Experiments are necessary to functionally test the insights garnered from genome sequencing. For example, just because a symbiont has genes necessary for synthesis of a particular nutrient does not mean that the nutrient is being provisioned to its host. Furthermore, in many systems we do not know what genetic mechanisms are most likely to influence a symbiont-conferred phenotype. For example, if hosts associated with a given microbe have lower fitness than those without the microbe, what mechanism mediates this phenotype? Is it producing a toxin? Is it using too many host resources? In these cases, a single genome provides even less insight.Comparative genomics can be another approach. This requires collection of hosts with alternative symbiont strains and then testing these strains in a common host background to demonstrate that they have different phenotypic effects. Symbiont genomes can then be sequenced and compared to identify differences. This approach was utilized to compare genomes of strains of the aphid bacterial symbiont Regiella insecticola that confer different levels of resistance to parasitoid wasps [11]; the protective and nonprotective Regiella genome differed in many respects. Comparing the genomes of Wolbachia strains with differential impacts on fly host fitness [12,13] revealed fewer differences, though none involved a gene with a function known to impact host fitness. Comparative genomics rarely uncovers a holy grail as the genomes of symbiont strains with alternative phenotypic effects rarely differ at a single locus of known function.Another approach, which is at the heart of studies of microbial pathogens, is to use genetic tools to manipulate symbionts at candidate loci (or randomly through mutagenesis) and compare the phenotypic effects of genetically-manipulated and unmanipulated symbionts. Indeed, this approach has provided insights into genes underlying traits of both pathogenic [14] and beneficial [15,16] microbes. There is one challenge. Many host-associated symbionts are not cultivable outside of their hosts, which precludes utilization of most traditional genetic techniques used to modify microbial genomes.An alternative approach to studying symbiont function leverages evolution. Occasionally, lineages that once conferred some phenotypic effect, when tested later, no longer do. If symbiont samples were saved along the way, researchers can then determine what in the genome changed. For example, pea aphids (Acyrthosiphon pisum) harboring the bacteria Hamiltonella defensa are more resistant to parasitoid wasps than those without the bacteria [17,18]. Toxin-encoding genes identified in the genome of a Hamiltonella-associated bacteriophage were hypothesized to be central to this defense [18,19]. However, confirmation of the bacteriophage’s role required comparing the insects’ resistance to wasps when they harbored the same Hamiltonella with and without the phage. No Hamiltonella isolates were found in nature without the phage, but bottleneck passaging of the insects and symbionts generation after generation in the laboratory led to the loss of phage in multiple host lineages. Experimental assays confirmed that in the absence of phage, there was no protection [20]. Similarly, laboratory passaging of aphids and symbionts serendipitously led to spread of a mutation in the genome of Buchnera aphidicola, the primary, amino acid-synthesizing symbiont of pea aphids. The mutation, a single nucleotide deletion in the promoter for ibpA, a gene encoding for a heat-shock protein, lowers aphid fitness under elevated temperature conditions [21]. The mutation is found at low levels in natural aphid populations, suggesting that laboratory conditions facilitate maintenance of the genotype.In the above cases, evolution was a fortunate coincidence. In this issue of PLoS Biology, Chrostek and Teixeira (2014) illustrate another alternative, directed experimental evolution. Previous work demonstrated that a strain of the symbiotic bacterium Wolbachia, wMelPop, is virulent to its Drosophila melanogaster hosts, considerably shortening lifespan while overproliferating inside the flies [22]. To investigate the mechanism of virulence, researchers compared the genomic content of an avirulent Wolbachia strain to that of the virulent wMelPop [12,13]. These comparisons revealed that the wMelPop genome contains a region with eight genes that is amplified multiple times; in avirulent strains there is only a single copy. This eight gene region was nicknamed “Octomom.” To functionally test whether Octomom mediates Wolbachia virulence, over successive generations, Chrostek and Teixeira selected for females with either high or low Octomom copy numbers to start the next generations. They found that copy number could evolve rapidly and was correlated with virulence. Flies harboring wMelPop with more copies of Octomom had shorter lifespans. This cost was reversed in the presence of natural enemies; flies harboring wMelPop with more copies of Octomom had higher resistance to viral pathogens. Thus, selection provided a functional link between genotype and phenotype in a symbiont recalcitrant to traditional microbial genetics approaches.In many respects, this is similar to the research on aphids and their symbionts, where protective phenotypes were lost through passaging of aphids and symbionts generation after generation, as part of standard laboratory maintenance. Chrostek and Teixeira simply used the tools of experimental evolution to select for altered symbionts in a controlled fashion. Comparison of the studies also highlights two potential approaches—select for a phenotype and determine the genotypic change, or select for a genotype of interest and determine the phenotypic effect.Why do we need to know the genetic mechanisms underlying symbiont-conferred traits? In terms of evolutionary dynamics, the maintenance of a symbiont’s effect in a population is predicated on the likelihood of it being maintained in the presence of mutation, drift, and selection. Symbiosis research often considers how ecological conditions influence symbiont-conferred traits but less often considers the instability of those influences due to evolutionary change. From the perspective of applied applications to human concerns, symbiont alteration of insect phenotypes are potential mechanisms to reduce vectoring of human and agricultural pathogens, either through directly reducing insect fitness or reducing the capacity of vectors to serve as pathogen reservoirs [23–28]. Short term field trials, for example, have demonstrated spread and persistence of Wolbachia in mosquito populations [29,30]. Because Wolbachia reduce persistence of viruses, including human pathogens, in insects [26,31–33], this is a promising pesticide-free and drug-free control strategy for insect-vectored diseases. Can we assume that Wolbachia and other symbionts will always confer the same phenotypes to their hosts? If the conferred phenotype is based on a region of the genome where mutation is likely (e.g., the homopolymeric track within the heat shock promoter of aphid Buchnera, the Octomom region in Drosophila wMelPop), then we have clear reason to suspect that the genotypic and phenotypic makeup of the symbiont population could change over time. We need to investigate how populations of bacterial symbionts evolve in host populations under natural ecological conditions, carefully screening for both changes in phenotype and changes in genotype over the course of such experimental observations. We then need to incorporate evolutionary changes when modeling symbiont maintenance and when considering the use of symbionts in applied applications.