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.     

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.     

Sleep loss leads to the withdrawal of human helping across individuals,groups, and large-scale societies

Humans help each other. This fundamental feature of homo sapiens has been one of the most powerful forces sculpting the advent of modern civilizations. But what determines whether humans choose to help one another? Across 3 replicating studies, here, we demonstrate that sleep loss represents one previously unrecognized factor dictating whether humans choose to help each other, observed at 3 different scales (within individuals, across individuals, and across societies). First, at an individual level, 1 night of sleep loss triggers the withdrawal of help from one individual to another. Moreover, fMRI findings revealed that the withdrawal of human helping is associated with deactivation of key nodes within the social cognition brain network that facilitates prosociality. Second, at a group level, ecological night-to-night reductions in sleep across several nights predict corresponding next-day reductions in the choice to help others during day-to-day interactions. Third, at a large-scale national level, we demonstrate that 1 h of lost sleep opportunity, inflicted by the transition to Daylight Saving Time, reduces real-world altruistic helping through the act of donation giving, established through the analysis of over 3 million charitable donations. Therefore, inadequate sleep represents a significant influential force determining whether humans choose to help one another, observable across micro- and macroscopic levels of civilized interaction. The implications of this effect may be non-trivial when considering the essentiality of human helping in the maintenance of cooperative, civil society, combined with the reported decline in sufficient sleep in many first-world nations.

Helping behavior between humans has been one of the most influential forces sculpting modern civilizations, but what factors influence this propensity to help? This study demonstrates that a lack of sleep dictates whether humans choose to help each other at three different scales: within individuals, across individuals, and across societies.

“Service to others is the rent you pay for your room here on earth.”― Muhammad Ali

Humans help each other. Helping is a prominent feature of homo sapiens [1], and represents a fundamental force sculpting the advent and preservation of modern civilizations [2,3].The ubiquity of helping is evident across the full spectrum of societal strata. From global government-to-government aid packages (e.g., the international aid following the 2004 Indian Ocean tsunami [4]), to country-wide pledge drives (e.g., the 2010 Haiti disaster) [5], and to individuals altruistically gifting money or donating their own blood to strangers, the expression of helping is abundant and pervasive [6]. So much so that this fundamental act has scaled into a lucent and sizable “helping economy” [7], with charitable giving in the United States amounting to $450 billion in 2019; a value representing 5.5% of the gross domestic product. In the United Kingdom, 10 billion pounds were donated to charity in 2017 and 2018. Indeed, more than 50% of individuals across the US, Europe, and Asia will have reported donating to charity or helping a stranger within the past month (The World Giving index).Human helping is therefore globally abundant, common across diverse societies, sizable in scope, substantive in financial magnitude, consequential in ramification, and frequent in occurrence.The motivated drive for humans to help each other has been linked to a range of underlying factors, from evolutionary forces (e.g., kin selection and reciprocal altruism that bias helping toward close others [2]), cultural norms and expectations (e.g., individualistic versus collectivistic cultures [8,9]), to socioeconomic factors (e.g., helping is less common in larger cities relative to rural areas [10,11]), as well as personality traits (e.g., individual empathy) [12,13].Ultimately, however, the decisional act to help others involves the human brain. Prosocial helping of varied kinds consistently engages a set of brain regions known as the social cognition network. Comprised of the medial prefrontal cortex (mPFC), mid and superior temporal sulcus, temporal-parietal junction (TPJ), and the precuneus [14,15], this network is activated when considering the mental states, needs, and perspectives of others [16–19], and the active choice to help them [20–23]. In contrast, lesions within key regions of this network result in “acquired sociopathy” [24], associated with a loss of both empathy and the withdrawal of compassionate helping [25–27].Yet the possibility that sleep loss represents another significant factor determining whether or not humans help each other, linked to underlying impairments within the social cognition brain network, remains unknown. Several lines of evidence motivate this prediction. First, insufficient sleep impairs emotional processing, including deficits in emotion recognition and expression, while conversely increasing basic emotional reactivity, further linked to antisocial behavior [28,29] (such as increased interpersonal conflict [30] and reduced trust in others [31,32]). Second, sleep loss reliably decreases activity in, and disrupts functional connectivity between, numerous regions within the social cognition brain network [33], including the mPFC [34], TPJ, and precuneus [35].Building on this overarching hypothesis, here, we test the prediction that a lack of sleep impairs human helping at a neural, individual, group, and global societal level. More specifically, we tested whether: (i) within individuals, a night of experimental sleep loss decreases the fundamental desire to help others, the underlying neural mechanism of which is linked to impaired activity within the social cognition brain network when considering other individuals (Study 1), (ii) in a micro-longitudinal study, night-to-night fluctuations in sleep result in a corresponding next-day deficit in the desire to act altruistically and helping others (Study 2), and (iii) at a large-scale national level, the loss of 1 h of sleep opportunity, using the manipulation of daylight saving time (DST), impairs the real-world behavioral act of altruistic human helping at a large-scale, societal level (Study 3).     

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.     

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.”     

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.     

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.     

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.     

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.     

Orienting the Interaction Compass: Resource Availability as a Major Driver of Context Dependence

Life on earth is enormously diverse, in part because each individual engages in countless interactions with its biotic and abiotic environment during its lifetime. Not only are there many such interactions, but any given interaction of each individual with, say, its neighbor or a nutrient could lead to a different effect on its fitness and on the dynamics of the population of which it is a member. Predicting those effects is an enduring challenge to the field of ecology. Using a simple laboratory system, Hoek and colleagues present evidence that resource availability can be a primary driver of variation between interactions. Their results suggest that a complex continuum of interaction outcomes can result from the simple combined effects of nutrient availability and density-dependent population dynamics. The future is rich with potential to integrate tractable experimental systems like theirs with hypotheses derived from studies of interactions in natural communities.The science of ecology is plagued or elevated (depending on your perspective) by the tendency for interactions between organisms and their environment to vary in space and time, with differing consequences for behavior, physiology, and/or fitness. This variation, known as context dependence, affects biotic and abiotic interactions alike and frustrates predictive efforts. For example, to determine how herbivory affects a plant population, you have to predict not only (a) how tissue loss will affect plant fitness but also (b) how much tissue will be lost (which depends on the density and identity of herbivores) and (c) how difficult that tissue will be to replace (which depends on resource availability). Herbivore communities and resource availability thus provide the “context” for plant tissue loss, such that herbivory can matter "hardly at all" or "a whole lot" depending on where you are and when you look.Mutualisms—i.e., interactions with reciprocal fitness benefits (Box 1)—were early poster children for context dependence [1], in part because it seemed difficult to reconcile cooperative behavior with the selective pressure to minimize interaction costs [2]. Such selection can destabilize mutualism by favoring the evolution of exploiters (or "cheaters"), whose effects on their interacting partners are dampened or even reversed (i.e., resulting in parasitism; Box 1). Compounding this paradox still further, some mutualisms occur within a trophic level, where substantial niche overlap between partners also renders them potential competitors. Recent work on microbes nevertheless suggests that mutualism readily evolves between partners at the same trophic level under certain environmental conditions [3]. Work on positive interactions between plants had in fact previously suggested a general "stress gradient hypothesis" for predicting these context-dependent outcomes: interactions should transition from negative to positive along gradients of increasing environmental stress [4]. Although derived from plant community ecology, the stress gradient hypothesis has recently gained traction in diverse mutualisms [5–8]. So far, this concordance is more about pattern than process; elucidating process is, however, ultimately essential to understanding context dependence.

Box 1. The Interaction Compass

Interactions are usually defined by the direction in which they affect the interactors, be they species, strains, or individuals. Even as variation in interspecific interactions first came into focus [1,9], it was clear that both the strength and the sign of interactions shifted back and forth along a continuum (Fig 1). The center of the interaction compass (see [10,11]) is sometimes called neutralism, but this box classifies any interaction where a fitness effect does not occur. Although the interaction compass is typically shown with only two species for the purposes of illustration, all species are involved in networks of interactions, and indirect interactions—defined where one species affects another by way of a third species or pathway—are ubiquitous in ecological communities and can rival direct interactions in their strength [e.g., 12]. The variety of terms and their distinct historical origins can lead to some ambiguity, as is the case with mutualism and facilitation [13]. Facilitation does not appear in the interaction compass (Fig 1), but it is associated with some of the earliest research on positive interactions across environmental gradients and with the stress gradient hypothesis in particular [4]. The term arises from 20th-century plant community ecology and refers either to any interaction where one species modifies the environment in a way that is positive for a neighboring species or specifically to positive interactions within a trophic level. Relevant here, until the recent surge of interest in microbe-microbe interactions, the term mutualism typically referred to interactions between trophic levels, where the competition outcome (––) is unlikely because the interactors do not overlap substantially in their niche requirements. It is common to speak instead of the mutualism-parasitism continuum. Although microbes fit perhaps only uncomfortably into the trophic boxes defined on the basis of macroorganism interactions, most cross-feeding mutualisms occur within a trophic level and thus could be thought of as examples of both mutualism and facilitation, with outcomes ranging around the full compass, from mutualism to competition and back to mutualism again.Open in a separate windowFig 1The interaction compass.A two-species interaction is illustrated with the terms defining each of the differently signed outcomes; the signs indicate individual fitness or population growth rate. A positive (+) sign thus indicates a positive effect of the interaction on the individual or population, a zero (0) sign indicates no effect, and a negative (–) sign indicates a negative effect. Moving away from the center increases the magnitude of the net effect of the interaction.One relatively straightforward path by which an increase in stress can lead to stronger mutualism is when the interaction involves a direct exchange of the environmentally limiting resource. In North American grasslands, grasses associate with arbuscular mycorrhizal fungi, which exchange soil nutrients for carbon fixed by the grass. The fungi can deliver both phosphorus and nitrogen, increasing grass uptake of whichever nutrient is least available in a given soil [5]. Although this seems like a good trick, we cannot characterize the outcome of the grass''s interaction with the fungi on the basis of nutrient uptake (the benefit) alone. The delivery of carbon by the grass to the fungi (the cost), and the net balance of trade (benefit−cost), is key. In this example, the grass receives a net benefit (increased biomass) from interacting with the fungi in phosphorus-poor soil but not in nitrogen-poor soil [5]. The fungi thus seem to be parasites in nitrogen-poor soil, but, interestingly, even that interaction is less negative for grasses in soils with less nitrogen [5]. This example suggests potentially broad relevance for the stress gradient hypothesis across the continuum of interaction types (Box 1) (Fig 1) but also highlights how the balance of trade determines ecological outcomes. To predict the outcome of any given interaction, therefore, we need to understand how both the benefits and the costs of interactions depend on an organism''s environment. This is a challenging task, requiring integrative understanding of organismal physiology, axes of environmental variation, and the nature of biotic interactions, as well as of the feedbacks between organismal ecology and evolution.The diversity and experimental tractability of microorganisms, as well as their fundamental role in life on earth, make them appealing systems for studying context dependence in its multiple dimensions. The potential for mutualism among microbes and between microbes and their multicellular hosts is receiving unprecedented attention as the diverse and important roles of the human gut microbiome come into sharp relief. As field-based studies of macroorganism interactions move past the recognition of context dependence to a deliberate focus on its drivers and mechanisms [14], laboratory-based studies of microbes are, in parallel, moving past debates about the "typical" nature of microbial interactions [15,16] to focus on how and why interaction outcomes vary across environmental gradients [3,17].In this issue of PLOS Biology, Hoek and colleagues show that interactions between two cross-feeding yeast strains can transition across nearly a full continuum of outcomes with simple variation in environmental nutrient concentration [18]. Cross-feeding microbes are those with similar metabolic requirements whose metabolic pathways are complementary, either because of a "leaky" byproduct system whereby some metabolites end up in the environment [15] or because of costly, cooperative exchange [19]. In the Hoek et al. study, the investigators used strains of cross-feeding yeast engineered to differ in amino acid production: one strain lacks leucine production but overproduces tryptophan (Leu⁻), and the other lacks tryptophan production but overproduces leucine (Trp⁻). By varying the quantity of leucine and tryptophan in the environment in a constant ratio, the investigators produced a continuum of interaction outcomes, from low-amino-acid environments that exhibit obligate mutualism to high-amino-acid environments that exhibit strong competition. They go on to show that many of these dynamics can be recovered with a remarkably simple model of each strain''s population growth, primarily depending only on the quantity of environmental amino acids and the population densities of the two strains. The complete range of empirically determined qualitative change in the interaction is mirrored by this simple model, which suggests that the outcomes of interactions that depend on resource exchange (including most mutualisms! [20]) can be predicted to an impressive degree by measuring the availability of that resource, the population densities of the interacting species, and their intrinsic growth rates.Returning to our grass-fungi interaction from above, however, we recall that the benefits of interacting (receiving the missing amino acid in the case of these yeasts) are only one side of the coin. The costs of interacting are what underlie the conflicts of interest that threaten mutualism stability and can lead to increasingly negative interactions over evolutionary time. In the Hoek et al. study, the costs of overproducing the amino acid that is consumed by the other strain are modeled only implicitly in the intrinsic growth rate (r), which is determined by growing each strain in monoculture with unlimited amino acids. The major discrepancy between their model and the empirical data, however, is that the model incorrectly predicts a much larger range of amino-acid concentrations at which the Trp⁻ strain is expected to outperform the Leu⁻ strain in both monoculture and co-culture. Interestingly, the Trp⁻ strain performs particularly poorly when it is co-cultured with the Leu⁻ strain, except at very high levels of environmental amino-acid availability. It is tempting to speculate that this discrepancy is caused by the model''s lack of an explicit density-dependent cost of leucine production, which would be exacerbated when the Leu⁻ strain is performing well. Going forward, it should be possible to merge population dynamic models that include such a cost [21] with an explicit term for resource availability to see how well these models predict dynamics in a variety of empirical systems.Rapid, ongoing global change presents one compelling reason to determine how resource availability underpins interactions, and the Hoek et al. study also sheds some needed light here. Using their model, they determine distinct early-warning "signatures" of imminent population collapse for co-cultures at very low levels of amino acids (think, e.g., drought), in which both strains go extinct upon the collapse of the obligate mutualism, and at very high levels of amino acids (think, e.g., nutrient pollution), in which competitive exclusion leads to the extinction of the slower growing strain. The collapse of populations engaging in obligate mutualism is predicted when the ratio of the population densities of the two strains becomes stable much more quickly than the total population size (particularly at small population sizes) and vice versa for competitive exclusion. In contrast, in healthy populations, the ratio of the strains and the total population size become stable at approximately equal speeds. As the authors note, this result suggests that we can predict how close one or both interacting species are to extinction by monitoring their comparative population dynamics.This is an exciting prospect, but how easy is it to monitor the population dynamics of interacting species outside the laboratory? Monitoring populations of long-lived species in the field is inherently difficult, and, historically, less attention has been paid to determining how the environment affects populations of interacting species than to how it affects individual traits and fitness [14]. But wait, you say, surely individual fitness is the driving force behind population dynamics. Well, yes and no. To assess individual fitness, investigators almost always use one or more proxies, including growth, survival, and reproductive biomass. Population-level studies have shown that a given interacting species can have multiple, frequently opposing effects on these different components of their partner''s fitness, such that an exclusive focus on any one component can be very misleading [22,23]. In addition, population dynamics depend on the probability of successful offspring recruitment; this probability is critical because it itself is also likely to vary along environmental gradients [14]. Population-level approaches thus deserve explicit focus despite their challenges, and this is one area where field studies can be greatly enhanced by both theory and model systems.A more serious problem, perhaps, and one that confronts all manner of approaches and systems, is how to scale up from simplified studies of two interacting species to entire ecological communities [24,25]. To use distinct dynamical signatures to predict population collapse, we need to know what other threats a species faces as well as what other opportunities are available. For example, corals exchange nutrients and protection for fixed carbon from their photosynthetic algal symbionts in the genus Symbiodinium. There are at least four major clades within Symbiodinium that associate with corals, and any given coral can associate with more than one type of algae, either simultaneously or throughout its lifetime. Temperature is an important environmental stress for corals, leading to the well known and increasingly problematic coral bleaching phenomenon, in which corals lose the carbon source provided by their algal symbionts (through loss of the symbionts themselves or of the symbionts'' photosynthetic capacity) as the oceans warm. However, some algal symbionts are more thermally tolerant than others, such that corals under temperature stress may lose their association with one symbiont (i.e., collapse of that obligate mutualism) only to gain assocation with a second, more thermally tolerant symbiont (i.e., formation of a different obligate mutualism) [26]. Various alternative responses to environmental stress can be imagined by considering interactions in a community context (Fig 2), and our understanding of these scenarios in well studied field systems should be mined to generate hypotheses about lesser known microbial interaction networks.Open in a separate windowFig 2Mutualism in a community context.Multispecies interactions can exhibit a greater variety of outcomes than two-way interactions. (A) An interaction in which the mutualism is always obligate (individuals with no mutualist have zero fitness), but some mutualists are better than others at high environmental stress (e.g., as in the coral-algae example). (B) An interaction in which there are multiple mutualists that vary in their cost to the partner. The costly mutualist is more effective, so Mutualist A increases fitness more than Mutualist B when stress is low to intermediate, but the cost of Mutualist A exceeds its benefit when stress is intermediate to high. In this mutualism, unlike in (A), the partner can exist independently of its mutualists and actually does so with higher fitness when environmental stress is very low (resource availability is very high) or stress is very high (resource availability is very low).The challenges to elucidating the drivers and mechanisms of context dependence are real, but the work of Hoek and colleagues reminds us that complex outcomes do not necessarily require complicated explanations. The emerging parallels between the burgeoning study of interactions among microbes and the research on species interactions in the macro-world should not be ignored and should, in fact, be leveraged for additional insight. For example, a functional approach is being pursued in both subfields and may increase our ability to generalize across highly diverse systems [24,27], but the context dependence of such functional types themselves [28] must be recognized and investigated in tandem. Simple systems like these cross-feeding yeasts suggest numerous possible future experiments to study what happens when we add dimensions in the environment or the species pool under high levels of experimental control. This study emphasizes the importance of resource availability for orienting the interaction compass.     

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.     

From Dinosaurs to Modern Bird Diversity: Extending the Time Scale of Adaptive Radiation

What explains why some groups of organisms, like birds, are so species rich? And what explains their extraordinary ecological diversity, ranging from large, flightless birds to small migratory species that fly thousand of kilometers every year? These and similar questions have spurred great interest in adaptive radiation, the diversification of ecological traits in a rapidly speciating group of organisms. Although the initial formulation of modern concepts of adaptive radiation arose from consideration of the fossil record, rigorous attempts to identify adaptive radiation in the fossil record are still uncommon. Moreover, most studies of adaptive radiation concern groups that are less than 50 million years old. Thus, it is unclear how important adaptive radiation is over temporal scales that span much larger portions of the history of life. In this issue, Benson et al. test the idea of a “deep-time” adaptive radiation in dinosaurs, compiling and using one of the most comprehensive phylogenetic and body-size datasets for fossils. Using recent phylogenetic statistical methods, they find that in most clades of dinosaurs there is a strong signal of an “early burst” in body-size evolution, a predicted pattern of adaptive radiation in which rapid trait evolution happens early in a group''s history and then slows down. They also find that body-size evolution did not slow down in the lineage leading to birds, hinting at why birds survived to the present day and diversified. This paper represents one of the most convincing attempts at understanding deep-time adaptive radiations.

“It is strikingly noticeable from the fossil record and from its results in the world around us that some time after a rather distinctive new adaptive type has developed it often becomes highly diversified.” – G. G. Simpson ([1], pp. 222–223)

George Gaylord Simpson was the father of modern concepts of adaptive radiation—the diversification of ecological traits in a rapidly speciating group of organisms (Figure 1; [2]). He considered adaptive radiation to be the source of much of the diversity of living organisms on planet earth, in terms of species number, ecology, and body form [1]–[3]. Yet more than 60 years after Simpson''s seminal work, the exact role of adaptive radiation in generating life''s extraordinary diversity is still an open and fundamental question in evolutionary biology [3],[4].Open in a separate windowFigure 1An example of adaptive radiation and early bursts in rates of speciation and phenotypic evolution.(a) The adaptive radiation of the modern bird clade Vanginae, which shows early rapid speciation, morphological diversity, and diversity in foraging behavior and diet [15],[32]. (b) Hypothetical curve of speciation rates through time that would be expected in adaptive radiation. The exponential decline in speciation rates shows that there was an “early burst” of speciation at the beginning of the clade''s history. (c) Hypothetical curve of rates of phenotypic evolution through time that would be expected in adaptive radiation, also showing an early burst of evolution with high initial rates. Part (a) is reproduced from [32] with permission (under CC-BY) from the Royal Society and the original authors.To address this question, researchers have looked for signatures of past adaptive radiation in the patterns of diversity in nature. In particular, it has been suggested that groups that have undergone adaptive radiation should show an “early-burst” signal in both rates of lineage diversification and phenotypic evolution through time—a pattern in which rates of speciation and phenotypic evolution are fast early in the history of groups and then decelerate over time (Figure 1; [3]–[5]). These predictions arise from the idea that clades should multiply and diversify rapidly in species number, ecology, and phenotype in an adaptive radiation and that rates of this diversification should decrease later as niches are successively occupied [2].Early bursts have been sought in both fossils and phylogenies. Few fossil studies have discussed their results in the context of adaptive radiation (but see [6]), but they often have found rapid rises in both taxonomic and morphological diversity early in the history of various groups [7], ranging from marine invertebrates [8] to terrestrial mammals [9]. However, fossils often lack the phylogeny needed to model how evolution has proceeded [7]. On the other hand, studies that test for early bursts in currently existing (extant) species typically use phylogenies, which allow us to model past evolution in groups with few or no fossils [5]. Phylogenies have most often been used to test early bursts in speciation (see, e.g., [10]). However, such tests may be misled by past extinction, which will decay the statistical signal of rapid, early diversification [11]. Furthermore, diverse evolutionary scenarios beyond adaptive radiation can give rise to early bursts in speciation [12]. By contrast, studies of phenotypic diversification may be more robust to extinction [13] and they test the distinguishing feature that separates adaptive from nonadaptive radiation [2],[12].Thus, studies of adaptive radiation in extant organisms increasingly have focused on phylogenetic tests of the early-burst model of phenotypic evolution. Some studies show strong support for this prediction in both birds [14],[15] and lizards [5],[16]. However, the most extensive study to date showed almost no support for the early-burst model. In this study, Harmon et al. [17] examined body size in 49 (and shape in 39) diverse groups of animals, including invertebrates, fishes, amphibians, reptiles, birds, and mammals. They found strong support for the early-burst model in only two of these 88 total datasets.This result raises an important question: if adaptive radiation explains most of life''s diversity [1], how is it possible that there is so little phylogenetic evidence for early bursts of phenotypic evolution? One possibility is that early bursts are hard to detect. This can be due to low statistical power in the most commonly employed tests [18]. It may also be due to a lack of precision in the way “early burst” is defined (and thus tested), as the ecological theory of adaptive radiation suggests that the rate of phenotypic evolution will decrease as species diversity increases in a group, not just over time [14],[16]. Indeed, recent studies [14],[16] detected a decline in rates with species diversity in clades that were also in the Harmon et al. [17] study, yet for which no decline over time was detected.A second possible reason for why early-burst patterns are uncommon is more fundamental: the patterns of phenotypic diversity that result from adaptive radiation may be different at large time scales. Many of the best examples of adaptive radiation are in groups that are relatively young, including Darwin''s finches (2.3 million years old [myr]; [19]) and Lake Malawi and Victoria cichlids (2.3 myr; [20]), whereas most groups that are examined for early bursts in phenotypic evolution are much older (e.g., 47 of 49 in Harmon et al. [17]; mean ± sd = 23.8±29.2 myr). So there may be an inherent difference between what unfolds over the relatively short time scales emphasized by Schluter [2] and what one sees at macroevolutionary time scales (see [21] for an in-depth discussion of this idea as it relates to speciation).The time scale over which adaptive radiations unfold has been little explored. As a result, the link between extant diversity and major extinct radiations remains unclear. Simpson [1] believed that adaptive radiation played out at the population level, but that it should manifest itself at larger scales as well—up to phyla (e.g., chordates, arthropods). He suggested that we should see signals of adaptive radiations in large, old clades because they are effectively small-scale adaptive radiation writ large [1]. Under this view, we should see the signal of adaptive radiation even in groups that diversified over vast time scales, particularly if adaptive radiation is as important for explaining life''s diversity as Simpson [1] thought it was.Part of the reason why potential adaptive radiations at deep time scales remain poorly understood is that studies either focus on fossils or phylogenies, but rarely both. In this issue, Benson et al. [22] combine these two types of data to address whether dinosaurs show signs that they adaptively radiated. Unlike most other studies, the temporal scale of the current study is very large—in this case, over 170 million years throughout the Mesozoic era, starting at 240 million years ago in the Triassic period. This characteristic allowed Benson et al. to shed light on deep-time adaptive radiation.The authors estimated body mass from fossils by using measurements of the circumference of the stylopodium shaft (the largest bone of the arm or leg, such as the femur), which shows a consistent scaling relationship with body mass in extant reptiles and mammals [23]. They then combined published phylogenies to obtain a composite phylogeny for the species in their body-size dataset. The authors finally conducted two types of tests of the rate of body-size evolution—tests of early bursts in phenotypic evolution that are the same as those of Harmon et al. [17], as well as an additional less commonly used test that estimates whether differences between estimated body size at adjacent phylogenetic nodes decreases over time.Benson et al. [22] found two striking results. First, in both of their analyses, the early-burst model was strongly supported for most clades of dinosaurs. This early burst began in the Triassic period, indicating that diversification in body size in dinosaurs began before the Triassic-Jurassic mass extinction event would have opened competition-free ecological space (as commonly hypothesized; [24],[25]). Rather, the authors [22] suggest that a key innovation led to this rise in dinosaurs, though it is not clear what this innovation was [26]. In general, though, the finding of an early burst in body-size evolution in most dinosaurs—if a consequence of adaptive evolution—suggests that adaptive radiation may play out over large evolutionary time scales, not just on the short time scales typical of the most well-studied cases of extant groups.Second, one clade—Maniraptora, which is the clade in which modern-day birds are nested—was the only part of the dinosaur phylogeny that did not show such a strong early burst in body-size evolution. Instead, this clade fit a model to a single adaptive peak—an optimum body size, if you will—but also maintained high rates of undirected body-size evolution throughout their history. Benson et al. [22] suggest that this last result connects deep-time adaptive radiation in the dinosaurs, which quickly exhausted the possibility of phenotypic space, with the current radiation in extant birds, which survived to the present day because their constant, high rate of evolution meant that they were constantly undergoing ecological innovation. This gives a glimpse into why modern birds have so many species (an order of magnitude higher than the nonavian dinosaurs) and so much ecological diversity.The use of fossils allowed Benson et al. [22] to address deep-time radiation in dinosaurs and its consequence on present-day bird diversity. Nevertheless, the promise of using fossils to understand adaptive radiation has its limits. The paleontological dataset presented here is exceptional, yet still insufficient to explore major components of adaptive radiations like actual ecological diversification. As in many paleontological studies, Benson et al. used body-size data to represent ecology because body size is one of the few variables that is available for most species. But it is unclear how important body size really is for ecological diversification and niche filling, because body size is important for nearly every aspect of organismal function. Consequently, evolutionary change in body size can result not only from the competition that drives adaptive radiation, but also from predation pressure, reproductive character displacement, and physiological advantages of particular body sizes in a given environment, among other reasons [27].Despite the broad coverage of extinct species presented in Benson et al. [22], the data were insufficient to study another major part of adaptive radiation: early bursts of lineage diversification. While new approaches are becoming available to study diversification with phylogenies containing extinct species [28],[29] or with incomplete fossil data [30], these approaches are limited when many taxa are known from only single occurrences. This is the case in the Benson et al. dataset, and more generally in most fossil datasets.Given that few fossils exist for many extant groups, a major goal for future studies will be the incorporation of incomplete fossil information into analyses primarily focused on traits and clades for which mostly neontological data are available. For example, Slater et al. [31] developed an approach to include fossil information in analyses of phenotypic evolution. They showed that adding just a few fossils (12 fossils in a study of a 135-species clade) drastically increased the power and accuracy of their analyses of extant taxa. Thus, the combination of fossil data and those based on currently living species is important for future studies, as are new approaches that allow analyzing early bursts of lineage diversification along with phenotypic evolution in fossils.So what answers do Benson et al. [22] bring to Simpson''s original question of the importance of adaptive radiation for explaining diversity on earth? The authors present an intriguing and unconventional link between adaptive radiation and the diversity of modern-day birds. They argue that bird diversification was possible because the dinosaur lineage leading to birds did not exhaust niche space, potentially thanks to small body sizes; in contrast, other dinosaur groups adaptively radiated, filled niche space, and thus could not produce the ecological innovation that may have been necessary to survive the Cretaceous-Paleogene mass extinction. This intriguing hypothesis suggests an important role for the relative starting points of successive adaptive radiations in explaining current diversity, giving a new spin to the pivotal question raised by Simpson more than 60 years ago.     

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].     

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.