Foraging trade-offs,flagellar arrangements,and flow architecture of planktonic protists

Unicellular flagellated protists are a key element in aquatic microbial food webs. They all use flagella to swim and to generate feeding currents to encounter prey and enhance nutrient uptake. At the same time, the beating flagella create flow disturbances that attract flow-sensing predators. Protists have highly diverse flagellar arrangements in terms of number of flagella and their position, beat pattern, and kinematics, but it is unclear how the various arrangements optimize the fundamental trade-off between resource acquisition and predation risk. Here we describe the near-cell flow fields produced by 15 species and demonstrate consistent relationships between flagellar arrangement and swimming speed and between flagellar arrangement and flow architecture, and a trade-off between resource acquisition and predation risk. The flow fields fall in categories that are qualitatively described by simple point force models that include the drag force of the moving cell body and the propulsive forces of the flagella. The trade-off between resource acquisition and predation risk varies characteristically between flow architectures: Flagellates with multiple flagella have higher predation risk relative to their clearance rate compared to species with only one active flagellum, with the exception of the highly successful dinoflagellates that have simultaneously achieved high clearance rates and stealth behavior due to a unique flagellar arrangement. Microbial communities are shaped by trade-offs and environmental constraints, and a mechanistic explanation of foraging trade-offs is a vital part of understanding the eukaryotic communities that form the basis of pelagic food webs.

Unicellular flagellated protists play a key role in the biogeochemical cycles of the global ocean. Their photosynthetic activity and grazing on microbes are major processes in the microbial food web, and they may control the populations of bacteria and cyanobacteria (1). By being grazed, they transfer primary production to higher trophic levels (2–4). Thus, flagellates are both consumers and prey, but we do not understand how their resource acquisition trades off against predation mortality, or how this trade-off shapes their foraging behavior.In the low Reynolds number (Re) world of protists, viscosity impedes predator-prey contact. The physical mechanisms that nevertheless allow flagellates to daily clear a volume of water for prey that corresponds to approximately 10⁶ times their own cell volume (5, 6) are not well understood. Many marine flagellates are mixotrophic and can acquire resources both through photosynthesis and by eating other organisms (7). Their demand for inorganic mineral nutrients is also constrained by viscosity that retards the advective enhancement of diffusive uptake (8).To encounter prey and enhance advective transport of nutrients, protists may swim or create a feeding current through the beating of one or several flagella (9, 10). However, the beating of flagella produces fluid disturbances that exposes the flagellate to its rheotactic (flow-sensing) predators (11). Small flagellates are grazed by microzooplankton, many of which perceive their prey from the fluid disturbance that the prey generates (12, 13). Thus, there are fundamental foraging trade-offs. Such trade-offs are largely unexplored among the eukaryotic microbes that form the basis of aquatic food webs. This is crucial, because the diversity of microbial communities is determined by such trade-offs in concert with environmental constraints (14–17). Microbial diversity in turn governs the functionality and “services” of microbial communities, and hence also their role in ocean biogeochemistry (18, 19).Here we explore the trade-off between resource acquisition and predation risk in marine nanoflagellates and microflagellates by describing the flow fields produced by the action of their flagella. The quantification of near-cell feeding currents has been reported in only a few species of free-swimming protists (10, 20). The kinematics, wave patterns, and arrangement and number of flagella are highly diverse among flagellated protists (Fig. 1). Theoretical models suggest that the feeding currents and fluid signal generated by a swimming cell depends on the arrangement of the flagella (11, 13, 21, 22). We use microparticle image velocimetry (µPIV) to visualize and quantify the flow fields generated by free-swimming planktonic protists with diverse flagellar arrangements and beat patterns. We show how the different modes of swimming produce very different flow architectures and demonstrate a trade-off between resource acquisition and predation risk in flagellated protists.Open in a separate windowFig. 1.Schematic overview of the diverse flagellar arrangements and beat patterns represented in this study. Latin names below each taxonomic group indicate the species (or other taxonomic unit) examined. Flagellar hairs are drawn when feasible, but some flagellar morphologies (e.g., the dinoflagellates) are deliberately simplified (25, 63). Redrawn from several sources; not to scale.     

Wolves make roadways safer,generating large economic returns to predator conservation

Recent studies uncover cascading ecological effects resulting from removing and reintroducing predators into a landscape, but little is known about effects on human lives and property. We quantify the effects of restoring wolf populations by evaluating their influence on deer–vehicle collisions (DVCs) in Wisconsin. We show that, for the average county, wolf entry reduced DVCs by 24%, yielding an economic benefit that is 63 times greater than the costs of verified wolf predation on livestock. Most of the reduction is due to a behavioral response of deer to wolves rather than through a deer population decline from wolf predation. This finding supports ecological research emphasizing the role of predators in creating a “landscape of fear.” It suggests wolves control economic damages from overabundant deer in ways that human deer hunters cannot.

Populations of apex predators have declined across the world’s landscapes over the past 200 y due to government bounty programs, hunting pressure, habitat loss, and declines in prey populations (1, 2). Ecologists are beginning to unravel the far-reaching ecological effects of these changes (1–5), but little is known about the economic effects. While many of the costs attributable to predators are salient and quantifiable, such as predation on livestock and pets, estimating and valuing the often subtle and indirect beneficial effects of predators is more difficult (6, 7).^*The recent expansion of the gray wolf (Canis lupus) offers a unique opportunity to concretely measure the cascading benefits of a predator whose reintroduction is controversial. Wolves once ranged over most of the Northern Hemisphere, but humans nearly eradicated the species from the continental United States and Europe by the 1960s (10). Legal protections strengthened during the latter half of the 20th century, and wolf populations returned to 10 coterminous US states and 28 European countries (11, 12). As of 2019, there are about 5,500 wolves in the United States and 11,000 in Europe. More jurisdictions, such as the state of Colorado, are proposing or already planning reintroductions (13).Restoring wolves could benefit humans who enjoy seeing wolves in their natural habitat or who value knowing of their existence (14, 15), but in this study we focus on the potential for wolves to generate indirect benefits by controlling overabundant deer populations. Deer populations have surged in the United States, increasing from about 2 to 4 deer per km² in the precolonial era (16) to 15 to 50 deer per km² in some areas today (17). Overabundant deer populations affect ecosystems by suppressing forest regeneration, altering the composition of tree and herbaceous plant species, and contributing to the spread of invasive species (18–20). Deer also generate economic costs for humans through deer–vehicle collisions (DVCs), Lyme disease (which is transmitted through deer ticks), and damage to agriculture, timber products, and landscaping (21).This study focuses on DVCs, which are the largest known economic cost of deer (SI Appendix, Table S1). About 1 million DVCs occur every year in the United States, causing 29,000 human injuries, 200 human fatalities, and nearly $10 billion in total economic losses (21, 22).^† Europe experiences similar problems, with a lower frequency of collisions with ungulates (such as deer and moose) but a higher rate of fatalities and injuries (23). The problem has worsened over time, with DVCs rapidly increasing since around 1990 (22, 23). If wolves reduce DVCs even modestly, the social and economic benefits could be sizable.We focus on two channels through which wolves could affect DVCs. The first is changes to deer abundance. We hypothesize that larger wolf populations reduce deer abundance directly through predation (18, 24, 25), which in turn reduces DVCs (26–28). The second channel is through changes to deer behavior because wolves create a “landscape of fear” for deer (29–31). Wolves use roads, pipelines, and other linear features as travel corridors, which increases wolves’ travel efficiency and the kill rate of prey near these features (32–36). We hypothesize that wolf presence affects deer movement near these features (34, 37, 38), thereby reducing collision risk for a given number of deer on the landscape. The behavioral effect is important because, through it, wolves can suppress economic damage from deer in ways seasonal human deer hunters cannot.Our empirical analysis focuses on Wisconsin, where wolves began to recolonize naturally around 1975 (Fig. 1) (39). Wisconsin provides an interesting, if not ideal, case study for several reasons. Foremost, the results from Wisconsin should generalize to other settings where wolves are (or could be) allowed to spread naturally into areas of human communities rather than only into wilderness. Much of the prior research on the effects of wolves in the United States focuses on Isle Royale and Yellowstone National Parks; however, the effect of wolves in national parks “would have little relevance to most of wolf range because of overriding anthropogenic influences there on wolves, prey, vegetation, and other parts of the food web” (40). By contrast, the spread of wolves across Wisconsin was natural and unimpeded by wildlife managers. As a result, contiguous wolf range in Wisconsin spans a human-dominated landscape more than 6 times the size of Isle Royale and Yellowstone combined (41). Second, the wolf population in Wisconsin is likely close to ecological carrying capacity (42, 43), which suggests the wolf effects we measure represent a long-term steady state rather than only transitional effects. Finally, if the benefits of a reduction in DVCs outweigh the costs of wolf predation in Wisconsin, then there may be economic justification for allowing wolves to expand not just in the state but also potentially in other states that have suitable wolf habitat and high DVCs (e.g., the northeastern United States) (44). Although verified predation on livestock and pets in Wisconsin is costly (recently, about $174,000 per year, on average) (45), DVC losses are orders of magnitude larger (almost $200 million per year, based on the national average cost per DVC) (22, 46).Open in a separate windowFig. 1.Wolf packs spread across Wisconsin between 1980 and 2010. Wolf packs are concentrated in the forested areas in the northern and central parts of the state. The rest of the state is predominantly nonforested agricultural or urban areas.     

Designed nanomolar small-molecule inhibitors of Ena/VASP EVH1 interaction impair invasion and extravasation of breast cancer cells

Battling metastasis through inhibition of cell motility is considered a promising approach to support cancer therapies. In this context, Ena/VASP-depending signaling pathways, in particular interactions with their EVH1 domains, are promising targets for pharmaceutical intervention. However, protein–protein interactions involving proline-rich segments are notoriously difficult to address by small molecules. Hence, structure-based design efforts in combination with the chemical synthesis of additional molecular entities are required. Building on a previously developed nonpeptidic micromolar inhibitor, we determined 22 crystal structures of ENAH EVH1 in complex with inhibitors and rationally extended our library of conformationally defined proline-derived modules (ProMs) to succeed in developing a nanomolar inhibitor (Kd=120 nM,MW=734 Da). In contrast to the previous inhibitor, the optimized compounds reduced extravasation of invasive breast cancer cells in a zebrafish model. This study represents an example of successful, structure-guided development of low molecular weight inhibitors specifically and selectively addressing a proline-rich sequence-recognizing domain that is characterized by a shallow epitope lacking defined binding pockets. The evolved high-affinity inhibitor may now serve as a tool in validating the basic therapeutic concept, i.e., the suppression of cancer metastasis by inhibiting a crucial protein–protein interaction involved in actin filament processing and cell migration.

Metastasis is a complex multistep process (1, 2) employing, among others, mechanisms governing actin cytoskeleton dynamics involving integrin signaling and actin regulatory proteins (3–5). So far, all approved antimetastatic drugs antagonize integrins (6) or inhibit downstream kinases (7, 8) (SI Appendix, Fig. S1). In the metastatic setting however, these drugs appear to have only limited success (9–13) and 5-y survival is not increasing satisfactorily (14, 15), making new approaches in antimetastatic drug development essential to meet this urgent medical need.The enabled/vasodilator stimulated phosphoprotein protein family (Ena/VASP) acts as a crucial hub in cell migration by linking actin filaments to invadopodia and focal adhesions (16–22). Due to their role in the transformation of benign lesions into invasive and metastatic cancer, Ena/VASP proteins are discussed as part of the invasive signature and as a marker of breast carcinogenesis (23–25). At the advanced tumor stage, the protein family is overexpressed (26–28), which has been shown to increase migration speed in vivo (29) and to potentiate invasiveness (30). Yet, no sufficiently potent probes to interfere with Ena/VASP in vivo have been reported.The three vertebrate Ena/VASP family members, enabled homolog (ENAH), VASP, and Ena-VASP-like (EVL), share a tripartite structural organization in which two Ena/VASP homology domains (EVH1 and EVH2) are separated by a more divergent proline-rich central part. Interactions of the EVH2 domain are involved in the elongation and protection of barbed-end actin filaments from capping proteins and tetramerization (31, 32). EVH1 folds into a structured globular domain that interacts with proteins at focal adhesions (33), the leading edge (34, 35), and invadopodia (36, 37) by recognizing the motif [F/W/L/Y]PxϕP (35, 38) (ϕ hydrophobic, x any; SI Appendix, Fig. S3) in poly-L-proline type II helix (PPII) conformation.In the course of our research into small molecules as potential inhibitors of protein–protein interactions (39) we recently in silico designed and stereo-selectively synthesized scaffolds, coined ProMs, which mimic pairs of prolines in PPII conformation (40). The modular combination of different ProMs thereby allowed us to generate nonpeptidic secondary-structure mimetics that fulfill the steric requirements of the addressed proline-rich motif-recognizing domain (41–47). For the EVH1 domain, our proof-of-concept study yielded a canonically binding, nontoxic, cell-membrane-permeable, 706-Da inhibitor 1 (Fig. 1A) composed of two different ProM scaffolds and 2-chloro-(L)-phenylalanine (2-Cl-Phe) (40). While the synthetic inhibitor 1 represents the compound with the highest reported affinity toward Ena/VASP EVH1 domains, a further improvement was required for in vivo experiments. Here we report successful structure-based optimization of inhibitor 1 based on 22 high-resolution crystal structures of ENAH EVH1 in complex with different inhibitors (SI Appendix, Tables S1–S6), including the well-resolved C-terminal binding epitope TEDEL of ActA from Listeria monocytogenes (48). Newly identified interaction sites adjacent to the C terminus of 1 were addressed by in silico designed and stereo-selectively synthesized modifications of the ProM-1 scaffold (Fig. 1A). While drastically increasing the affinity against a rather flat protein surface we conserved structural simplicity, low molecular weight, nontoxicity, and cell-membrane permeability. Potent compounds against Ena/VASP were shown to also act in vivo, i.e., by inhibiting cancer cell extravasation in zebrafish at only 1 μM, thereby paving the way for future preclinical studies.Open in a separate windowFig. 1.(A) Structure of the first-generation Ena/VASP EVH1 inhibitor 1. All compositions share the N-acetylated 2-chloro-phenylalanine unit (blue) attached to a central ProM-2 scaffold (red). Esterification of the C terminus renders the inhibitors cell-membrane permeable (40). (B) General (modular) architecture of nonpeptidic, conformationally preorganized inhibitors used in this study. Structural variation (pink) was achieved by replacing the C-terminal ProM-1 unit (green) by ProM-9, ProM-13, ProM-12, ProM-15, or ProM-17 (Table 1).     

From the Cover: Cardenolides,toxicity, and the costs of sequestration in the coevolutionary interaction between monarchs and milkweeds

For highly specialized insect herbivores, plant chemical defenses are often co-opted as cues for oviposition and sequestration. In such interactions, can plants evolve novel defenses, pushing herbivores to trade off benefits of specialization with costs of coping with toxins? We tested how variation in milkweed toxins (cardenolides) impacted monarch butterfly (Danaus plexippus) growth, sequestration, and oviposition when consuming tropical milkweed (Asclepias curassavica), one of two critical host plants worldwide. The most abundant leaf toxin, highly apolar and thiazolidine ring–containing voruscharin, accounted for 40% of leaf cardenolides, negatively predicted caterpillar growth, and was not sequestered. Using whole plants and purified voruscharin, we show that monarch caterpillars convert voruscharin to calotropin and calactin in vivo, imposing a burden on growth. As shown by in vitro experiments, this conversion is facilitated by temperature and alkaline pH. We next employed toxin-target site experiments with isolated cardenolides and the monarch’s neural Na⁺/K⁺-ATPase, revealing that voruscharin is highly inhibitory compared with several standards and sequestered cardenolides. The monarch’s typical >50-fold enhanced resistance to cardenolides compared with sensitive animals was absent for voruscharin, suggesting highly specific plant defense. Finally, oviposition was greatest on intermediate cardenolide plants, supporting the notion of a trade-off between benefits and costs of sequestration for this highly specialized herbivore. There is apparently ample opportunity for continued coevolution between monarchs and milkweeds, although the diffuse nature of the interaction, due to migration and interaction with multiple milkweeds, may limit the ability of monarchs to counteradapt.

Although coevolutionary interactions are often portrayed as simplified arms races of reciprocal defense and offense evolution, the dynamics are decidedly more complex. For example, how do plants respond to highly specialized herbivores, and are such adapted consumers immune to plant defenses? On average, specialists are less impacted by particular plant defense compounds than generalists (1, 2), but does this mean that further coevolution is not possible? Even highly specialized herbivores must contend with plant defenses if coevolutionary interactions are proceeding (3). For any herbivorous insect, larval feeding, protection from enemies, and adult oviposition are each key points in the life cycle where plant chemistry plays a role in the outcome. Thus, the typical cornucopia of chemical compounds in an individual plant presents opportunities for both plant resistance and co-option of this defense by specialist herbivores (4–6).Thus, it is unclear how often coevolutionary interactions reach equilibrium or “stalemate,” as it were (7). Nonetheless, several conditions are predicted to slow or suppress the endless arms race. First, the more specialized an interaction, the greater the investments required and potential challenges to innovation. Second, when different life stages of herbivores are subject to distinct selection pressures (8–10), continued coevolution may be restricted because of conflicting selection. Finally, when aspects of the population biology of the species involved reduce local adaptation, such as gene flow and the presence of alternate hosts, asymmetry may emerge in the coevolutionary match between plants and herbivores (11, 12). In the interaction between milkweed plants and monarch butterflies, cardenolides have played a central role in our understanding of coevolutionary specialization, larval feeding, sequestration, and, to a lesser extent, oviposition (13). Although monarchs are abundant across a broad geographical range, substantial phenotypic and genetic analyses have failed to reveal population differentiation (14, 15). A lack of local adaptation is likely due to the four-generation annual cycle where butterflies feed on diverse milkweed species and yet intermix during migration and overwintering (13).There is some evidence that cardenolides can be a burden for monarch caterpillars (16–20), although costs of sequestration have not been demonstrated. Nonetheless, many assays, even across >10-fold concentrations of cardenolides, fail to show negative effects of cardenolides on monarchs (21). More mechanistic in vitro work with the monarch’s highly resistant sodium-potassium pump (Na⁺/K⁺-ATPase), the cellular target of cardenolides, demonstrated that some milkweed cardenolides are strong inhibitors of monarch neural physiology (22). Thus, work with specific compounds that are variable in plants is needed to pinpoint agents of resistance. For sequestration of cardenolides, a model proposed by Nelson (23) and supported in a review of early work (24) and new research (25) suggests that monarchs selectively sequester more polar cardenolides, some compounds are metabolized (modification or detoxification), and others are transported via carriers (20, 26–28). Finally, observational work indicated that monarchs tend to oviposit on intermediate cardenolide concentration plants (29, 30), suggesting the hypothesis that adult butterflies minimize toxic exposure to larvae while optimizing sequestration of plant poisons.Asclepias curassavica is surprisingly understudied in its interactions with monarch butterflies, despite being a critical hostplant worldwide (second only to Asclepias syriaca) (13). Attack of A. curassavica by monarchs can be strong and therefore a likely source of selection for plant defense. The species is weedy throughout the tropics and has a plethora of cardenolides, including relatively uncommon compounds, some of which may be detrimental to monarch performance (20, 28, 31–34). In particular, voruscharin is a long-known cardenolide containing a thiazolidine heterocycle (having both nitrogen and sulfur; Fig. 1), yet its previous study was hampered by solubility issues and the inability of thin layer chromatography to separate it from related compounds (20, 28, 31, 35). In terms of sequestration, it was demonstrated decades ago that monarchs preferentially sequester two cardenolides, calotropin and calactin, especially when feeding on A. curassavica (20, 31, 33, 36). For oviposition, two flavonol glycosides were isolated from A. curassavica leaves that stimulate egg laying (37). Nonetheless, the relative importance of quercetin glycosides versus cardenolides in oviposition is unknown, and specific cardenolides that impact larval growth and sequestration have not been well-studied. If A. curassavica defends itself against this specialized herbivore in a coevolutionary interaction mediated by plant chemistry, connecting specific toxins to their target site in the context of sequestration and oviposition is critical. In particular, we hypothesized that specific cardenolides modulate a trade-off between benefits of specialization and costs of coping with toxicity.Open in a separate windowFig. 1.Chemical conversion of milkweed cardenolides by monarch caterpillars. (A) A visualization of metabolomic data showing the differences in the chemical composition across sample groups (n = 4 per group; significance tested by PERMANOVA). After data curation, over 7,000 chemical features (m/z) were generated with MS data collected in positive ionization mode and visualized with a Bray–Curtis distance matrix. Ellipses represent the region of 95% confidence. (B) Voruscharin was converted to calactin and calotropin when fed to monarch caterpillars. Shown are means ± SE concentrations as determined by UV-HPLC (n = 3 to 9). Data bars very close to zero had no detectable cardenolides. Note that the caterpillars fed A. curassavica were reared on this diet from hatching and had an order of magnitude higher cardenolides than other treatments which were dosed only during the fourth instar. (C) The basic skeleton of cardenolides and the chemical structures of calactin, calotropin, and voruscharin.Here, we identify cardenolides produced by A. curassavica and address which compounds are sequestered by monarchs, followed by asking four questions: 1) Do specific cardenolides reduce monarch larval growth, or does sequestration impose a burden for larvae? 2) Using in vivo and in vitro assays, do monarchs detoxify or convert particular cardenolides to less toxic forms? 3) What is the relative toxicity (measured as in vitro inhibition of the cellular target, the monarch’s Na⁺/K⁺-ATPase) of nonsequestered cardenolides, those sequestered intact, and those modified during sequestration? And, finally, 4) do monarch oviposition decisions minimize toxicity and optimize sequestration of cardenolides, or are oviposition stimulants (flavonol glycosides) drivers of oviposition?     

Growth,death, and resource competition in sessile organisms

Population-level scaling in ecological systems arises from individual growth and death with competitive constraints. We build on a minimal dynamical model of metabolic growth where the tension between individual growth and mortality determines population size distribution. We then separately include resource competition based on shared capture area. By varying rates of growth, death, and competitive attrition, we connect regular and random spatial patterns across sessile organisms from forests to ants, termites, and fairy circles. Then, we consider transient temporal dynamics in the context of asymmetric competition, such as canopy shading or large colony dominance, whose effects primarily weaken the smaller of two competitors. When such competition couples slow timescales of growth to fast competitive death, it generates population shocks and demographic oscillations similar to those observed in forest data. Our minimal quantitative theory unifies spatiotemporal patterns across sessile organisms through local competition mediated by the laws of metabolic growth, which in turn, are the result of long-term evolutionary dynamics.

Ecological niches display a wide variety of spatial and temporal patterns ranging from random to regular and from transient to long lived. In Fig. 1, we show a small sample from such diversity, including fairy circles in semiarid environments (1), regular and random tiling of termite mounds (2, 3), and more randomly spaced ant nests and trees (4, 5). This variation is not limited to between taxa but also varies between different plots in the same region. These systems also operate on different timescales, where fairy circles have estimated lifetimes of around half of a century compared with days or weeks for nascent ant nests and centuries for trees in unperturbed forests. In the extreme, transient growth is maximized for agricultural crops, which are then razed at maturity before demographic stability (6, 7). Overall, fast and slow dynamics of sessile organisms are characterized by a range of spatial distributions, from the random to the regular, that reflect underlying forces of growth, death, and competition.Open in a separate windowFig. 1.Regular to random spatial distributions and transient to slow temporal evolution in sessile organisms. (Upper) Trees in Alaskan rainforest (circles indicate basal stem diameter of >2.5 cm increased by a factor of five) (5), view of the Panamian rainforest canopy, semiregularly packed termite mounds reprinted from ref. 3 (empty circles are inactive mounds), and hexagonally packed fairy circles reprinted from ref. 1. (Lower) Newly built ant nests (4), termite mounds with size shown by circles (2), and perennial agricultural crops. Dynamics range from transience dominated, in the case of crops razed at the end of the season or newly built ant nests that die within days as indicated by open circles, to long-lasting structures such as fairy circles, which can live individually for decades or forests at demographic equilibrium lasting millennia. Scale is unavailable for fairy circles, but they range from 2 to 12 m in diameter, meaning that the shown plot covers some hundreds of meters on a side (1). Panamanian rainforest image credit: Christian Ziegler (photographer). Termite mounds image reprinted from ref. 3, which is licensed under CC BY 4.0. Fairy circles image reprinted from ref. 1, which is licensed under CC BY 4.0. Solenopsis invicta nests image reprinted by permission of ref. 4: Springer Nature, Oecologia, copyright 1995. M. michaelseni mounds image reprinted by permission of ref. 2: Springer Nature, Insectes Sociaux, copyright 2010. Crops image credit: Pxhere.The mechanisms underlying such pattern formation have been a source of robust debate, especially in the context of vegetation (8, 9). Following Turing’s seminal work on scale-dependent feedback, namely local activation and long-range inhibition, similar principles of pattern formation with local density dependence have been considered (10–13), touching on the more general question of how multiple scales of time and space emerge (14–16). More recent work has connected these principles with mechanisms of biological interaction and environmental feedback (17–19). For spatial patterning, approaches to mechanism range from using perturbations like cascades of tree death to explore self-organized criticality in forests (20–22) to applying Turing-like activation-inhibition concepts to scale-dependent plant processes (15, 16), which could be modulated by environmental conditions (23), to considering how ecosystem engineers modify the local environment to generate bare and densely vegetated patches (18, 24). Demographic theories, in contrast, focus on variables that aggregate across species and space such as age and size (25–27) and build on allometric dependence of growth, mortality, and resource acquisition (28–36). In an alternative set of approaches, mechanism-free maximum entropy principles can capture demographic patterns by fixing a few population “state variables” to predict measured properties (37). Across these examples, forests are particularly well-studied empirically across diverse species, sizes, and environments (38, 39) and grounded on predicted theoretical regularities in space and demography such as in the context of metabolic scaling (40–43) and mechanical or hydraulic limits (44–47).Here, we build on previous work on forest growth and structure to consider sessile organisms more broadly in the context of both spatial structure and demographic dynamics. We propose a minimal dynamical model that integrates timescales of individual growth and mortality with competitive attrition on a background of fluctuating resources. With the model, we study the emergence and erasure of spatiotemporal order in ecological systems. We show how competition alone is insufficient to generate strong spatial regularity and that growth and death must flatline for the largest organisms to stabilize spatial order. Since most ecological systems are out of equilibrium, we extend our model to consider transient phenomena and predict population shock waves from competitive interactions when there is metabolic growth. This minimal framework serves to unify at a conceptual level the role of various timescales for pattern formation in distinct ecological settings.As the starting point, we consider how metabolism determines individual growth and death. Metabolic scaling theory describes the origins of scaling laws in organism growth across a large range of body sizes derived from energetic constraints (40, 48, 49). Given constraints on average resource consumption per unit area, individual growth follows power law, allometric scaling relations connecting accumulation of biomass m, or the organism’s physical dimensions such as the stem radius r with age. In the context of forests where individuals are fixed in location, metabolic scaling can be connected with population-level statistics such as spatial density, biomass production, and stand energetics determined by the balance of individual growth and mortality (34, 43). Such predictions have been verified for individual organisms (41, 50) and have highlighted ecosystem-level regularities such as total population density and predator–prey relations (51, 52). The presence of universal patterns suggests that unifying principles act across systems (53, 54) such as from energetic constraints (34, 43, 55, 56). Such observations form the basis of using power law, allometric relationships to describe the rates of processes, but this is not essential. Any number of assumptions or mathematical relationships could replace these in our overall framework.One surprising prediction of metabolic scaling theory is that it is not necessary to explicitly include local competitive interactions to explain steady-state population distributions (33, 34), even if local competition is one of the major factors that drives long-term evolutionary dynamics to optimize fundamental energetic constraints (57). However, competition coupled with other timescales can introduce complex dynamics (58, 59) such as in response to exogenous perturbations (60, 61), which goes beyond steady-state assumptions. Other than mechanistic additions to metabolic scaling theory (44), competition, perturbation, and other dynamics present potential explanations for significant and sometimes substantial deviations from predictions (39, 42). Here, we present a minimal model to account for these missing factors.We start with allometric scaling theory of forest growth in section 1 and connect deviations from metabolic scaling theory to organism density, resource variability, and competitive interactions in section 2. We explore the implications of competition through space in section 3 and time in section 4, concluding with section 5. Although we explicitly develop our framework using the language of forests, referring, for instance, to individuals as trees and dimensions as stem radii, our formulation is straightforwardly generalizable to other sessile organisms (62). As an example, we extend our model beyond allometric assumptions to consider the emergence of spatial order (SI Appendix, section D).     

Network motifs involving both competition and facilitation predict biodiversity in alpine plant communities

Biological diversity depends on multiple, cooccurring ecological interactions. However, most studies focus on one interaction type at a time, leaving community ecologists unsure of how positive and negative associations among species combine to influence biodiversity patterns. Using surveys of plant populations in alpine communities worldwide, we explore patterns of positive and negative associations among triads of species (modules) and their relationship to local biodiversity. Three modules, each incorporating both positive and negative associations, were overrepresented, thus acting as "network motifs." Furthermore, the overrepresentation of these network motifs is positively linked to species diversity globally. A theoretical model illustrates that these network motifs, based on competition between facilitated species or facilitation between inferior competitors, increase local persistence. Our findings suggest that the interplay of competition and facilitation is crucial for maintaining biodiversity.

Identifying the processes that maintain natural biodiversity is a longstanding goal of ecology (1–4). Theoretical and empirical explanations of coexistence in plant communities have largely proceeded along two parallel lines: one focused on competition (5–7) and the other on facilitation (8–10). Regarding the former, recent theoretical models highlight the role of intransitive competition in preventing individual plant species from excluding inferior competitors (7, 11). Regarding the latter, studies have shown that key plant species (ecosystem engineers) can support many other species through the amelioration of local environmental conditions, a process widely referred to as direct facilitation (12–15). However, focusing on either competition or facilitation independently may be inadequate for fully understanding species coexistence. In fact, the balance between positive and negative effects plays a crucial role in regulating nutrient flow and driving population and community response to environmental change (2, 13).There is substantial evidence indicating that both competition and facilitation occur simultaneously within the same communities (16, 17). For instance, facilitated species may compete against one another (18), or species can facilitate each other in ways that outcompete other species (19, 20). Yet, because facilitation and competition are rarely considered together at the community level, we have little understanding of the degree to which the interplay of competition and facilitation affects biodiversity. A recent empirical study found that the overall frequency of positive and negative associations between plant species was only weakly correlated to plant diversity in drylands (21). It is unknown, however, whether it is the combination of positive and negative associations at fine spatial scales (orders of centimeters) that matters for biodiversity maintenance. This expectation is consistent with theoretical evidence on the impact of network modules on community dynamics (22).Here, we explore the prevalence and importance of community-level positive and negative associations among species in a global set of alpine plant communities. We analyzed whole-community population data (abundance of individuals per species) for 166 alpine plant communities at 83 sites worldwide (10) (Fig. 1). The dataset includes 2,252 plant species and more than 13,000 observations. Within the dataset, microhabitats with and without ecosystem engineers (an average of 81 paired plots per site) are treated separately (10, 14). We inferred positive and negative associations among all plant species using a Bayesian model in which the expected population size of a species is the sum of proportional changes in the population size of all other species (ref. 23; see Materials and Methods).Open in a separate windowFig. 1.Global map of alpine plant networks studied here. Red dots on the map indicate the spatial location of the networks, with a few networks plotted for reference. In the networks, green dots represent plant species, and blue and red arrows represent negative- and positive species associations, respectively. Dot size is proportional to species abundance. The four network modules analyzed here are represented at the bottom of the figure, from left to right: intransitive competition, facilitation-driven competition, and competition-driven facilitation 1 and 2.According to Abrams (24) and Wootton (25), and following the plant ecology literature (12, 15), network interactions derived from species associations are defined according to long-term effects measured on population size. In general, it is hard to infer interactions from association data alone (20, 26). Still, we have confidence that inferred categorical associations are indicative of the long-term outcome of species interactions to a large extent because: 1) alpine plant communities are relatively simple and spatial patterns closely reflect the net effects of plant–plant interactions (8, 12, 15, 27); 2) population data (number of plants per species) were collected at a fine spatial scale on the order of centimeters, where direct interactions take place (4, 8, 12), minimizing the influence of environmental heterogeneity and maximizing the imprint of direct neighbor effects (17, 27); 3) each network was built for each microhabitat at each site, with species growing in the same homogeneous environmental conditions (temperature, soil, aridity, etc.) (10), thus excluding spatial gradients that might mask or confound the correct inference of interactions from plant–plant associations (26); 4) we used high-resolution community data (as opposed to presence/absence data) that allow us to derive robust estimates of plant associations (28), as demonstrated in the sensitivity analysis (SI Appendix, Data and Code); 5) in addition to having highly resolved local communities, the survey was also replicated on a global scale, which allows us to generalize our findings since patterns are observed over a broad range of environmental and biogeographic contexts, from tropical to arctic latitudes (Fig. 1); and 6) inference was carried out with a Bayesian model that describes association strengths among plants with a similar power to existing models of plant fecundity and growth (5). This includes joint-posterior distributions of parameters, which allows us to infer associations among many species at the community level (23, 28).     

Structure–function subsystem models of female and male forebrain networks integrating cognition,affect, behavior,and bodily functions

The forebrain is the first of three primary vertebrate brain subdivisions. Macrolevel network analysis in a mammal (rat) revealed that the 466 gray matter regions composing the right and left sides of the forebrain are interconnected by 35,738 axonal connections forming a large set of overlapping, hierarchically arranged subsystems. This hierarchy is bilaterally symmetrical and sexually dimorphic, and it was used to create a structure–function conceptual model of intraforebrain network organization. Two mirror image top-level subsystems are presumably the most fundamental ontogenetically and phylogenetically. They essentially form the right and left forebrain halves and are relatively weakly interconnected. Each top-level subsystem in turn has two second-level subsystems. A ventromedial subsystem includes the medial forebrain bundle, functionally coordinating instinctive survival behaviors with appropriate physiological responses and affect. This subsystem has 26/24 (female/male) lowest-level subsystems, all using a combination of glutamate and GABA as neurotransmitters. In contrast, a dorsolateral subsystem includes the lateral forebrain bundle, functionally mediating voluntary behavior and cognition. This subsystem has 20 lowest-level subsystems, and all but 4 use glutamate exclusively for their macroconnections; no forebrain subsystems are exclusively GABAergic. Bottom-up subsystem analysis is a powerful engine for generating testable hypotheses about mechanistic explanations of brain function, behavior, and mind based on underlying circuit organization. Targeted computational (virtual) lesioning of specific regions of interest associated with Alzheimer’s disease, clinical depression, and other disorders may begin to clarify how the effects spread through the entire forebrain network model.

Developmentally, the vertebrate nervous system’s central division, the neural tube, has four primary subdivisions: forebrain (FB), midbrain, hindbrain, and spinal cord (1, 2). Functionally, the mammalian FB is critical for survival of individuals and of species because it is required for the spontaneous expression of goal-directed homeostatic and reproductive behaviors (3, 4) and for coordinating specific behaviors with physiologically appropriate autonomic and neuroendocrine visceral responses (5–7). The FB may thus be viewed broadly as a biological network controlling voluntary behavior, generating associated conscious experience (cognition and affect) (8), and coordinating behavior and conscious experience with bodily functions.Based on its diverse and critical functional roles, it is not surprising that the FB is the most differentiated mammalian nervous system part, with four traditional subdivisions (cerebral cortex [CTX], cerebral nuclei [CNU], thalamus [TH], and hypothalamus [HY]), together parceled into about half of all recognized nervous system gray matter regions (466/920 bilaterally in rat) (9). A vast literature addresses the structure–function properties of many FB regions and their axonal connections with other regions, but no conceptual model of global FB structure–function architecture has emerged to provide a basic plan and first principles for generating data-driven testable hypotheses from bottom-up and/or top-down approaches.Network neuroscience provides tools for systematically constructing and deconstructing global models of systems architecture, most recently in terms of subsystem (module) hierarchies (10–12). For systems analysis generally, basic requirements include a parts list, an understanding of how each part works, and an account of how the parts interconnect and function as a whole. In neuroscience, the most complete analysis of the whole adult nervous system is for the two sexes of the nematode, Caenorhabditis elegans, with fewer than 400 neurons (parts) and on the order of 6,000 to 7,000 synapses (connections) (13, 14). Brenner and colleagues rationalized the whole nervous system approach by noting that less than a complete solution at any analysis level is modifiable by additional data at that level and by suggesting that solutions help answer two fundamental questions in neurobiology: 1) how do neurons in the embryo organize themselves into specifically interconnected structural networks and then 2) how do such networks function in the adult (13, 15)?We have approached constructing a global adult mammalian nervous system wiring diagram—as a necessary prelude to examining how it develops and understanding how it constrains the range of adult functional dynamics—by starting with a macroconnectome, a matrix of directed and weighted axonal connections between all gray matter regions (parts) in rat, a granularity level and species where by far the most data currently exist. Because a 920 × 920 matrix of rat nervous system regions has 846,400 possible monosynaptic macroconnections (referred to below simply as connections), for practical reasons we decided initially to create separate subconnectomes for each of the central nervous system’s 10 subdivisions (Fig. 1B), to progress from rostral to caudal, and then to add the peripheral nervous system and its interactions with the rest of the body—a neurome (16). This practical strategy also yields conceptual results because the intrinsic circuitry of each subdivision, considered as an aggregate part, can be analyzed, along with the organization of intersubdivisional connections. A top-level macroneuroscience approach is meant to provide boundary conditions (total interregional connectivity pattern) and a theoretical framework for understanding rodent nervous system organization at finer, nested levels of granularity: the set of neuron types forming a region (mesolevel), the set of individual neurons forming a type (microlevel), and the set of synapses for individual neurons (nanolevel) (17).Open in a separate windowFig. 1.Analysis strategy overview. (A) The right and left FB, consisting of CTX, CNU, TH, and HY (with retina) shown on a rat central nervous system flat map (28). (B) Hierarchy of major central nervous system subdivisions common to adult vertebrates (1, 2). (C) The 64 subdivision subconnectomes assembled in topographic order to create the whole FB subconnectome. Numbers indicate region number in a subconnectome or subdivision (B). The main diagonal (darker dashed line, upper left to lower right) indicates the connection of a region to itself, with no value in a macroconnectome where regions are black boxes. The two shorter diagonals (lighter dashed lines) parallel to the main diagonal represent homotopic crossed connections: from a region on one side of the brain to the corresponding region on the other side.Network analysis now has been applied to the internal connections of CTX, CNU, TH, and HY and to connections between CTX and CNU (endbrain [EB]) and between TH and HY (interbrain [IB]) (12, 16, 18–22). Here a systematic, comprehensive database of all possible intra-FB connections was generated (by including those between EB and IB) and subjected to network analysis, preparatory to adding more caudal central nervous system parts, and the peripheral nervous system.     

From the Cover: Evidence from South Africa for a protracted end-Permian extinction on land

Earth’s largest biotic crisis occurred during the Permo–Triassic Transition (PTT). On land, this event witnessed a turnover from synapsid- to archosauromorph-dominated assemblages and a restructuring of terrestrial ecosystems. However, understanding extinction patterns has been limited by a lack of high-precision fossil occurrence data to resolve events on submillion-year timescales. We analyzed a unique database of 588 fossil tetrapod specimens from South Africa’s Karoo Basin, spanning ∼4 My, and 13 stratigraphic bin intervals averaging 300,000 y each. Using sample-standardized methods, we characterized faunal assemblage dynamics during the PTT. High regional extinction rates occurred through a protracted interval of ∼1 Ma, initially co-occurring with low origination rates. This resulted in declining diversity up to the acme of extinction near the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary. Regional origination rates increased abruptly above this boundary, co-occurring with high extinction rates to drive rapid turnover and an assemblage of short-lived species symptomatic of ecosystem instability. The “disaster taxon” Lystrosaurus shows a long-term trend of increasing abundance initiated in the latest Permian. Lystrosaurus comprised 54% of all specimens by the onset of mass extinction and 70% in the extinction aftermath. This early Lystrosaurus abundance suggests its expansion was facilitated by environmental changes rather than by ecological opportunity following the extinctions of other species as commonly assumed for disaster taxa. Our findings conservatively place the Karoo extinction interval closer in time, but not coeval with, the more rapid marine event and reveal key differences between the PTT extinctions on land and in the oceans.

Mass extinctions are major perturbations of the biosphere resulting from a wide range of different causes including glaciations and sea level fall (1), large igneous provinces (2), and bolide impacts (3, 4). These events caused permanent changes to Earth’s ecosystems, altering the evolutionary trajectory of life (5). However, links between the broad causal factors of mass extinctions and the biological and ecological disturbances that lead to species extinctions have been difficult to characterize. This is because ecological disturbances unfold on timescales much shorter than the typical resolution of paleontological studies (6), particularly in the terrestrial record (6–8). Coarse-resolution studies have demonstrated key mass extinction phenomena including high extinction rates and lineage turnover (7, 9), changes in species richness (10), ecosystem instability (11), and the occurrence of disaster taxa (12). However, finer time resolutions are central to determining the association and relative timings of these effects, their potential causal factors, and their interrelationships. Achieving these goals represents a key advance in understanding the ecological mechanisms of mass extinctions.The end-Permian mass extinction (ca. 251.9 Ma) was Earth’s largest biotic crisis as measured by taxon last occurrences (13–15). Large outpourings from Siberian Trap volcanism (2) are the likely trigger of calamitous climatic changes, including a runaway greenhouse effect and ocean acidification, which had profound consequences for life on land and in the oceans (16–18). An estimated 81% of marine species (19) and 89% of tetrapod genera became extinct as established Permian ecosystems gave way to those of the Triassic. In the ocean, this included the complete extinction of reef-forming tabulate and rugose corals (20, 21) and significant losses in previously diverse ammonoid, brachiopod, and crinoid families (22). On land, many nonmammalian synapsids became extinct (16), and the glossopterid-dominated floras of Gondwana also disappeared (23). Stratigraphic sequences document a global “coral gap” and “coal gap” (24, 25), suggesting reef and forest ecosystems were rare or absent for up to 5 My after the event (26). Continuous fossil-bearing deposits documenting patterns of turnover across the Permian–Triassic transition (PTT) on land (27) and in the oceans (28) are geographically widespread (29, 30), including marine and continental successions that are known from China (31, 32) and India (33). Continental successions are known from Russia (34), Australia (35), Antarctica (36), and South Africa’s Karoo Basin (Fig. 1 and 37–40), the latter providing arguably the most densely sampled and taxonomically scrutinized (41–43) continental record of the PTT. The main extinction has been proposed to occur at the boundary between two biostratigraphic zones with distinctive faunal assemblages, the Daptocephalus and Lystrosaurus declivis assemblage zones (Fig. 1), which marks the traditional placement of the Permian–Triassic geologic boundary [(37) but see ref. 44]. Considerable research has attempted to understand the anatomy of the PTT in South Africa (38, 39, 45–52) and to place it in the context of biodiversity changes across southern Gondwana (53, 54) and globally (29, 31, 32, 44, 47, 55).Open in a separate windowFig. 1.Map of South Africa depicting the distribution of the four tetrapod fossil assemblage zones (Cistecephalus, Daptocephalus, Lystrosaurus declivis, Cynognathus) and our two study sites where fossils were collected in this study (sites A and B). Regional lithostratigraphy and biostratigraphy within the study interval are shown alongside isotope dilution–thermal ionization mass spectrometry dates retrieved by Rubidge et al., Botha et al., and Gastaldo et al. (37, 44, 80). The traditional (dashed red line) and associated PTB hypotheses for the Karoo Basin (37, 44) are also shown. Although traditionally associated with the PTB, the Daptocephalus–Lystrosaurus declivis Assemblage Zone boundary is defined by first appearances of co-occurring tetrapod assemblages, so its position relative to the three PTB hypotheses is unchanged. The Ripplemead member (*) has yet to be formalized by the South African Committee for Stratigraphy.Decades of research have demonstrated the richness of South Africa’s Karoo Basin fossil record, resulting in hundreds of stratigraphically well-documented tetrapod fossils across the PTT (37, 39, 56). This wealth of data has been used qualitatively to identify three extinction phases and an apparent early postextinction recovery phase (39, 45, 51). Furthermore, studies of Karoo community structure and function have elucidated the potential role of the extinction and subsequent recovery in breaking the incumbency of previously dominant clades, including synapsids (11, 57). Nevertheless, understanding patterns of faunal turnover and recovery during the PTT has been limited by the scarcity of quantitative investigations. Previous quantitative studies used coarsely sampled data (i.e., assemblage zone scale, 2 to 3 Ma time intervals) to identify low species richness immediately after the main extinction, potentially associated with multiple “boom and bust” cycles of primary productivity based on δ¹³C variation during the first 5 My of the Triassic (41, 58). However, many details of faunal dynamics in this interval remain unknown. Here, we investigate the dynamics of this major tetrapod extinction at an unprecedented time resolution (on the order of hundreds of thousands of years), using sample-standardized methods to quantify multiple aspects of regional change across the Cistecephalus, Daptocephalus, and Lystrosaurus declivis assemblage zones.     

The impact of identity by descent on fitness and disease in dogs

Domestic dogs have experienced population bottlenecks, recent inbreeding, and strong artificial selection. These processes have simplified the genetic architecture of complex traits, allowed deleterious variation to persist, and increased both identity-by-descent (IBD) segments and runs of homozygosity (ROH). As such, dogs provide an excellent model for examining how these evolutionary processes influence disease. We assembled a dataset containing 4,414 breed dogs, 327 village dogs, and 380 wolves genotyped at 117,288 markers and data for clinical and morphological phenotypes. Breed dogs have an enrichment of IBD and ROH, relative to both village dogs and wolves, and we use these patterns to show that breed dogs have experienced differing severities of bottlenecks in their recent past. We then found that ROH burden is associated with phenotypes in breed dogs, such as lymphoma. We next test the prediction that breeds with greater ROH have more disease alleles reported in the Online Mendelian Inheritance in Animals (OMIA). Surprisingly, the number of causal variants identified correlates with the popularity of that breed rather than the ROH or IBD burden, suggesting an ascertainment bias in OMIA. Lastly, we use the distribution of ROH across the genome to identify genes with depletions of ROH as potential hotspots for inbreeding depression and find multiple exons where ROH are never observed. Our results suggest that inbreeding has played a large role in shaping genetic and phenotypic variation in dogs and that future work on understudied breeds may reveal new disease-causing variation.

The unique demographic and selective history of dogs has enabled the persistence of deleterious variation, simplified genetic architecture of complex traits, and caused an increase in both runs of homozygosity (ROH) and identity-by-descent (IBD) segments within breeds (1–6). Specifically, the average F_ROH was ∼0.3 in dogs (7), compared to 0.005 in humans, computed from the 1000 Genomes populations (8). The large amount of the genome in ROH in dogs, combined with a wealth of genetic variation and phenotypic data (2, 5, 7, 9–11), allow us to test how ROH and IBD influence complex traits and fitness (Fig. 1). Furthermore, many of the deleterious alleles within dogs likely arose relatively recently within a breed, and dogs tend to share similar disease pathways and genes with humans (4, 12, 13), increasing their relevance for complex traits in humans.Open in a separate windowFig. 1.Potential mechanisms for associations between ROH and phenotypes that depend on recessive mutations. If a recessive deleterious mutation is nonlethal (blue), it may lead to ROH correlating with disease, while lethal (red) recessive mutations will cause a depletion of ROH.Despite IBD segments and ROH being ubiquitous in genomes, the extent to which they affect the architecture of complex traits as well as reproductive fitness has remained elusive. Given that ROH are formed by inheritance of the same ancestral chromosome from both parents, there is a much higher probability of the individual to become homozygous for a deleterious recessive variant (8, 14), leading to a reduction in fitness. This prediction was verified in recent work in nonhuman mammals that has shown that populations suffering from inbreeding depression tend to have an increase in ROH (15, 16). ROH in human populations are enriched for deleterious variants (8, 14, 17). However, the extent to which ROH impact phenotypes remains unclear. For example, several studies have associated an increase in ROH with complex traits in humans (18–23), though some associations remain controversial (24–28). Determining how ROH and IBD influence complex traits and fitness could provide a mechanism for differences in complex-trait architecture across populations that vary in their burden of IBD and ROH.Here, we use IBD segments and ROH from 4,741 breed dogs and village dogs, and 380 wolves to determine the recent demographic history of dogs and wolves and establish a connection between recent inbreeding and deleterious variation associated with both disease and inbreeding depression. This comprehensive dataset contains genotype data from 172 breeds of dog, village dogs from 30 countries, and gray wolves from British Colombia, North America, and Europe. We test for an association with the burden of ROH and case-control status for a variety of complex traits. Remarkably, we also find that the number of disease-associated causal variants identified in a breed is positively correlated with breed popularity rather than burden of IBD or ROH in the genome, suggesting ascertainment biases also exist in databases of dog disease mutations and that many breeds of dog are understudied. Lastly, we identify multiple loci that may be associated with inbreeding depression by examining localized depletions of ROH across dog genomes.     

Rapid reductions and millennial-scale variability in Nordic Seas sea ice cover during abrupt glacial climate changes

Constraining the past sea ice variability in the Nordic Seas is critical for a comprehensive understanding of the abrupt Dansgaard-Oeschger (D-O) climate changes during the last glacial. Here we present unprecedentedly detailed sea ice proxy evidence from two Norwegian Sea sediment cores and an East Greenland ice core to resolve and constrain sea ice variations during four D-O events between 32 and 41 ka. Our independent sea ice records consistently reveal a millennial-scale variability and threshold response between an extensive seasonal sea ice cover in the Nordic Seas during cold stadials and reduced seasonal sea ice conditions during warmer interstadials. They document substantial and rapid sea ice reductions that may have happened within 250 y or less, concomitant with reinvigoration of deep convection in the Nordic Seas and the abrupt warming transitions in Greenland. Our empirical evidence thus underpins the cardinal role of rapid sea ice decline and related feedbacks to trigger abrupt and large-amplitude climate change of the glacial D-O events.

Sea ice is a critical component of the global climate system as it affects Earth’s albedo, phytoplankton productivity, ocean-atmosphere heat and gas exchange, and ocean circulation (1). Rapid sea ice retreat, as observed in the modern Arctic Ocean, exerts important climate feedbacks that may lead to an accelerated climate warming at northern high latitudes (2). While many climate models have difficulties in reproducing the currently observed Arctic sea ice decline (3), the rates of ongoing atmospheric warming in some Arctic regions are already comparable with those of prominent abrupt climate changes that occurred during the last glacial period (4). The latter are referred to as Dansgaard–Oeschger (D-O) climate events and known from Greenland ice core records as abrupt shifts between cold Greenland stadials (GS) and warmer Greenland interstadials (GI) occurring repeatedly ∼10–110 ka (5, 6). The millennial-scale glacial climate variability was a global phenomenon with different characteristics in the northern and southern hemispheres, but the most striking feature of the D-O events is an extremely abrupt climate transition that includes an atmospheric warming of 5–16.5 °C over the Greenland ice sheet happening in just a few decades (7). Analogous to the modern and future sea ice retreat and resulting warming in the Arctic, the abrupt D-O climate transitions are widely believed to have been amplified by rapid sea ice retreat in the Nordic Seas (8–15).Today, the Nordic Seas are largely ice-free, and warm Atlantic surface waters flow into the Norwegian Sea as far north as Svalbard at ∼80°N (Fig. 1), where the Arctic sea ice cover is being eroded, in particular in the Barents Sea. The warm Atlantic surface waters release heat to the atmosphere as it flows northward, which is accompanied by convective intermediate and deep-water formation between Norway and Greenland, feeding the lower limb of the Atlantic Meridional Overturning Circulation (AMOC) (16). A portion of the Atlantic waters continues flowing into the stratified Arctic Ocean as subsurface waters (17). While the pattern of ocean circulation during GI was fairly comparable to that today, proxy data indicate that the glacial Nordic Seas exhibited a stable surface stratification during GS, similar to the modern Arctic Ocean (13, 18). The AMOC and associated northward surface heat transport into the Nordic Seas were weakened during GS, with most extreme weakening related to Heinrich events signified by massive iceberg discharges to the North Atlantic (19, 20). Intermediate and deep waters in the stadial Nordic Seas were 2–4 °C warmer as compared with GI or modern conditions, resulting from a stable halocline and reduced open-ocean convection (21, 22). Contemporaneously, an extended sea ice cover reaching at least as far south as the Greenland–Scotland Ridge at ∼60°N insulated the high-latitude atmosphere from the deep oceanic heat reservoir (23, 24). Model simulations support a subsurface warming scenario under extended sea ice during GS (22, 25, 26) and suggest that a rapid removal of the sea ice cover might have caused the abrupt and high-amplitude D-O climate warming (11, 12, 14, 15).Open in a separate windowFig. 1.Core sites and regional context of the study area. Yellow diamonds mark the core sites investigated in this study. The map shows the core-top P_BIP₂₅ distribution (42, 43, 63), illustrating the great potential of the biomarker approach for sea ice reconstruction. Orange, yellow, and green dots mark core-top sites north, east, and south of Greenland, respectively, data of which are investigated in this study. Small black dots indicate locations of published core-top data. Purple lines mark the modern sea ice extent during September (dashed) and March (solid), averaged between A.D. 1981 and 2010 (https://nsidc.org/; ref. 64). The thin blue line shows the P_BIP₂₅ = 0.2 isoline, representing best the modern winter/spring sea ice extent. Red arrows illustrate the warm and saline North Atlantic Current (NAC). The map was produced with Ocean Data View software (65).Although there is some evidence of millennial-scale sea ice fluctuations during the last glacial, the few available sea ice proxy records (23, 24, 27–31) are mostly restricted to the southern Norwegian Sea and the Arctic Ocean, often have a limited temporal resolution, and partly reflect opposing trends regarding stadial–interstadial sea ice changes depending on the proxies used. Here we present high-resolution sea ice biomarker records from two key sites that form a North–South transect within the Atlantic inflow region in the Norwegian Sea and are thus ideally suited to record spatiotemporal shifts in sea ice cover in both the entrance and the interior of the ocean basin, oceanic fronts, and Atlantic water inflow during the last glacial (Fig. 1). Furthermore, we combine these marine sea ice proxy records with an independent sea ice record based on bromine-enrichment (Br_enr) values from an East Greenland ice core, which significantly enhances the spatial coverage, the robustness of results, and temporal constraint of the sea ice reconstruction. We focus on five representative glacial D-O cycles between 32 and 41 ka, which comprise long- and short-lasting GI as well as several GS, one of which includes Heinrich Event 4. The application of the cryptotephra-based chronological constraints provides a level of robustness as to the timing, duration, and nature of the events unfolding during abrupt climate changes. Our study provides robust empirical evidence that resolves rapid and widespread sea ice retreat in the Nordic Seas and its role in initiating and amplifying the abrupt climate change of the glacial D-O events.     

A solution to a sex ratio puzzle in Melittobia wasps

The puzzling sex ratio behavior of Melittobia wasps has long posed one of the greatest questions in the field of sex allocation. Laboratory experiments have found that, in contrast to the predictions of theory and the behavior of numerous other organisms, Melittobia females do not produce fewer female-biased offspring sex ratios when more females lay eggs on a patch. We solve this puzzle by showing that, in nature, females of Melittobia australica have a sophisticated sex ratio behavior, in which their strategy also depends on whether they have dispersed from the patch where they emerged. When females have not dispersed, they lay eggs with close relatives, which keeps local mate competition high even with multiple females, and therefore, they are selected to produce consistently female-biased sex ratios. Laboratory experiments mimic these conditions. In contrast, when females disperse, they interact with nonrelatives, and thus adjust their sex ratio depending on the number of females laying eggs. Consequently, females appear to use dispersal status as an indirect cue of relatedness and whether they should adjust their sex ratio in response to the number of females laying eggs on the patch.

Sex allocation has produced many of the greatest success stories in the study of social behaviors (1–4). Time and time again, relatively simple theory has explained variation in how individuals allocate resources to male and female reproduction. Hamilton’s local mate competition (LMC) theory predicts that when n diploid females lay eggs on a patch and the offspring mate before the females disperse, the evolutionary stable proportion of male offspring (sex ratio) is (n − 1)/2n (Fig. 1) (5). A female-biased sex ratio is favored to reduce competition between sons (brothers) for mates and to provide more mates (daughters) for those sons (6–8). Consistent with this prediction, females of >40 species produce female-biased sex ratios and reduce this female bias when multiple females lay eggs on the same patch (higher n; Fig. 1) (9). The fit of data to theory is so good that the sex ratio under LMC has been exploited as a “model trait” to study the factors that can constrain “perfect adaptation” (4, 10–13).Open in a separate windowFig. 1.LMC. The sex ratio (proportion of sons) is plotted versus the number of females laying eggs on a patch. The bright green dashed line shows the LMC theory prediction for the haplodiploid species (5, 39). A more female-biased sex ratio is favored in haplodiploids because inbreeding increases the relative relatedness of mothers to their daughters (7, 32). Females of many species adjust their offspring sex ratio as predicted by theory, such as the parasitoid Nasonia vitripennis (green diamonds) (82). In contrast, the females of several Melittobia species, such as M. australica, continue to produce extremely female-biased sex ratios, irrespective of the number of females laying eggs on a patch (blue squares) (15).In stark contrast, the sex ratio behavior of Melittobia wasps has long been seen as one of the greatest problems for the field of sex allocation (3, 4, 14–21). The life cycle of Melittobia wasps matches the assumptions of Hamilton’s LMC theory (5, 15, 19, 21). Females lay eggs in the larvae or pupae of solitary wasps and bees, and then after emergence, female offspring mate with the short-winged males, who do not disperse. However, laboratory experiments on four Melittobia species have found that females lay extremely female-biased sex ratios (1 to 5% males) and that these extremely female-biased sex ratios change little with increasing number of females laying eggs on a patch (higher n; Fig. 1) (15, 17–20, 22). A number of hypotheses to explain this lack of sex ratio adjustment have been investigated and rejected, including sex ratio distorters, sex differential mortality, asymmetrical male competition, and reciprocal cooperation (15–18, 20, 22–26).We tested whether Melittobia’s unusual sex ratio behavior can be explained by females being related to the other females laying eggs on the same patch. After mating, some females disperse to find new patches, while some may stay at the natal patch to lay eggs on previously unexploited hosts (Fig. 2). If females do not disperse, they can be related to the other females laying eggs on the same host (27–31). If females laying eggs on a host are related, this increases the extent to which relatives are competing for mates and so can favor an even more female-biased sex ratio (28, 32–35). Although most parasitoid species appear unable to directly assess relatedness, dispersal behavior could provide an indirect cue of whether females are with close relatives (36–38). Consequently, we predict that when females do not disperse and so are more likely to be with closer relatives, they should maintain extremely female-biased sex ratios, even when multiple females lay eggs on a patch (28, 35).Open in a separate windowFig. 2.Host nest and dispersal manners of Melittobia. (A) Photograph of the prepupae of the leaf-cutter bee C. sculpturalis nested in a bamboo cane and (B) a diagram showing two ways that Melittobia females find new hosts. The mothers of C. sculpturalis build nursing nests with pine resin consisting of individual cells in which their offspring develop. If Melittobia wasps parasitize a host in a cell, female offspring that mate with males inside the cell find a different host on the same patch (bamboo cane) or disperse by flying to other patches.We tested whether the sex ratio of Melittobia australica can be explained by dispersal status in a natural population. We examined how the sex ratio produced by females varies with the number of females laying eggs on a patch and whether or not they have dispersed before laying eggs. To match our data to the predictions of theory, we developed a mathematical model tailored to the unique population structure of Melittobia, where dispersal can be a cue of relatedness. We then conducted a laboratory experiment to test whether Melittobia females are able to directly access the relatedness to other females and adjust their sex ratio behavior accordingly. Our results suggest that females are adjusting their sex ratio in response to both the number of females laying eggs on a patch and their relatedness to the other females. However, relatedness is assessed indirectly by whether or not they have dispersed. Consequently, the solution to the puzzling behavior reflects a more-refined sex ratio strategy.     

Stable metal anodes enabled by a labile organic molecule bonded to a reduced graphene oxide aerogel

Metallic anodes (lithium, sodium, and zinc) are attractive for rechargeable battery technologies but are plagued by an unfavorable metal–electrolyte interface that leads to nonuniform metal deposition and an unstable solid–electrolyte interphase (SEI). Here we report the use of electrochemically labile molecules to regulate the electrochemical interface and guide even lithium deposition and a stable SEI. The molecule, benzenesulfonyl fluoride, was bonded to the surface of a reduced graphene oxide aerogel. During metal deposition, this labile molecule not only generates a metal-coordinating benzenesulfonate anion that guides homogeneous metal deposition but also contributes lithium fluoride to the SEI to improve Li surface passivation. Consequently, high-efficiency lithium deposition with a low nucleation overpotential was achieved at a high current density of 6.0 mA cm⁻². A Li|LiCoO₂ cell had a capacity retention of 85.3% after 400 cycles, and the cell also tolerated low-temperature (−10 °C) operation without additional capacity fading. This strategy was applied to sodium and zinc anodes as well.

Rechargeable batteries based on metal anodes including lithium (Li), sodium (Na), and zinc (Zn) show great promise in achieving high energy density (1–3). Unfortunately, the electrochemical interface of the metal anodes is not favorable for metal deposition. Metal nucleation is inhomogeneous at the surface, leading to the growth of metal dendrites (4–7) and the formation of an unstable solid–electrolyte interphase (SEI) that is incapable of protecting metals from the side reactions with the electrolyte (8–12).Substantial efforts have been devoted to stabilizing the interface of metal anodes, especially for Li metal. These include the design of artificial protective layers (13–17), alternative electrolytes (18–24), and sacrificial additives (25–30) to stabilize the metal–electrolyte interface, the development of mechanically robust coatings (31–34) to block Li dendrite growth, and the use of structured scaffolds to host dendrite-free Li deposition by reducing local current densities (35–43). However, the performance of metal anodes remains poor under high-current or low-temperature conditions. This is because the inhomogeneous Li nucleation and unstable SEI problems have not been well addressed, and these problems at the interface are even exacerbated under critical operating conditions, especially high-current densities and low temperatures (5, 6, 44).Toward this end, we report a simple molecular approach for regulating the electrochemical interface of metal anodes, which enables even Li deposition and stable SEI formation in a conventional electrolyte. This was realized by bonding a labile organic molecule, benzenesulfonyl fluoride (BSF), to a reduced graphene oxide (rGO) aerogel surface as the Li anode host (Fig. 1A). During Li deposition, BSF molecules electrochemically decompose at the interface and generate benzenesulfonate anions bonded to the rGO aerogel (Fig. 1B). The conjugated anions have a strong binding affinity for Li, serving as lithiophilic sites on the rGO surface to synergistically induce homogeneous Li nucleation of Li on the rGO surface. At the same time, BSF molecules contribute LiF to the SEI layer, which facilitates Li surface passivation (Fig. 1C). As a result, high-efficiency (99.2%) Li deposition was achieved at a Li deposition amount of 6.0 mAh cm⁻² and a current density of 6.0 mA cm⁻²; the barrier to Li nucleation was markedly reduced, as evidenced by the low nucleation overpotentials at high-current density (6.0 mA cm⁻²) or at a low temperature (−10 °C). A 400-cycle life with a capacity retention of 83.6% was achieved for a Li|LiCoO₂ (LCO) cell in a conventional carbonate electrolyte. Moreover, with the organic molecule-tuned interface, the Li|LCO cell can be stably cycled at a low operating temperature (−10 °C). This approach was applied to Na and Zn metal anodes as well.Open in a separate windowFig. 1.Illustration of a stable interface for Li deposition using a labile organic molecule, benzenesulfonyl fluoride (BSF). (A) Covalently bonded BSF on the rGO aerogel surface. (B) In situ generation of a lithiophilic conjugated anion (benzenesulfonate) and LiF on the surface during Li deposition. (C) Li nucleation preferentially occurs at the conjugated anion sites owing to the strong Li binding affinity, which leads to uniform Li deposition. In addition, the LiF that is formed is in the SEI layer and passivates the Li surface.     

P7C3-A20 treatment one year after TBI in mice repairs the blood–brain barrier,arrests chronic neurodegeneration,and restores cognition

Chronic neurodegeneration in survivors of traumatic brain injury (TBI) is a major cause of morbidity, with no effective therapies to mitigate this progressive and debilitating form of nerve cell death. Here, we report that pharmacologic restoration of the blood–brain barrier (BBB), 12 mo after murine TBI, is associated with arrested axonal neurodegeneration and cognitive recovery, benefits that persisted for months after treatment cessation. Recovery was achieved by 30 d of once-daily administration of P7C3-A20, a compound that stabilizes cellular energy levels. Four months after P7C3-A20, electron microscopy revealed full repair of TBI-induced breaks in cortical and hippocampal BBB endothelium. Immunohistochemical staining identified additional benefits of P7C3-A20, including restoration of normal BBB endothelium length, increased brain capillary pericyte density, increased expression of BBB tight junction proteins, reduced brain infiltration of immunoglobulin, and attenuated neuroinflammation. These changes were accompanied by cessation of TBI-induced chronic axonal degeneration. Specificity for P7C3-A20 action on the endothelium was confirmed by protection of cultured human brain microvascular endothelial cells from hydrogen peroxide-induced cell death, as well as preservation of BBB integrity in mice after exposure to toxic levels of lipopolysaccharide. P7C3-A20 also protected mice from BBB degradation after acute TBI. Collectively, our results provide insights into the pathophysiologic mechanisms behind chronic neurodegeneration after TBI, along with a putative treatment strategy. Because TBI increases the risks of other forms of neurodegeneration involving BBB deterioration (e.g., Alzheimer’s disease, Parkinson’s disease, vascular dementia, chronic traumatic encephalopathy), P7C3-A20 may have widespread clinical utility in the setting of neurodegenerative conditions.

Traumatic brain injury (TBI) is commonly caused by motor vehicle accidents, falls, contact sports, explosions, or assaults, with an estimated 70 million people worldwide sustaining a TBI every year (1). In the United States alone, there are almost 3 million annual emergency department visits for TBI treatment (2) and ∼5 million people living with TBI-related disabilities, translating to an annual cost of ∼$80 billion (3–5). Many TBI survivors experience chronic diffuse axonal degradation and nerve cell death (6–8) associated with sensorimotor impairment, cognitive dysfunction, and emotional dysregulation, as well as increased risk of developing Alzheimer’s disease (AD), Parkinson’s disease (PD), vascular dementia, and chronic traumatic encephalopathy (CTE) (9, 10).The initial clinical management of TBI is confined to acute measures, such as reducing intracranial pressure and edema (11), while maintaining oxygenation and meeting metabolic demand of the injured brain (12, 13). For survivors, the only chronic treatment options are prolonged physical and cognitive rehabilitation accompanied by symptom-driven medication. Unfortunately, such approaches rarely slow the long-term deterioration in neurologic function (14). In essence, TBI produces a chronic pathology that is triggered by injury-initiated persistent neurodegeneration and leads to life-long detrimental effects on multiple health outcomes (6, 15).Despite decades of research, there remains a tremendous unmet need for new disease-modifying therapies that can mitigate post-TBI chronic neurodegeneration (16). Recent work elegantly summarized by Sandsmark et al. (17) has identified injury to the neurovascular unit (NVU) as a potential driving force for chronic neurodegeneration after TBI. Damage to the endothelial lining of the brain microvessels is observed in both human patients and mouse TBI models (18), resulting in persistent deterioration of the blood–brain barrier (BBB) and chronic brain inflammation (19, 20). Here, we have studied this chronic condition in a murine model of multimodal TBI (mmTBI) that entails jet-flow exposure in an overpressure chamber to produce globally compressive forces along with a variable amount of acceleration–deceleration and early blast wave exposure. This laboratory model produces neurodegeneration and neurobehavioral deficits reminiscent of TBI in people (21–24). We treated and analyzed mice beginning 1 y after a single injury, as outlined in Fig. 1A. This late time point was selected because it represents approximately the midpoint of a typical mouse’s lifespan and thus can be considered a model of delaying initiation of treatment in people until decades after their TBI. This is important because of the great many people living today who are suffering from the chronic deficits of TBI.Open in a separate windowFig. 1.P7C3-A20 restores cognition in chronic TBI. (A) Experimental schematic. (B) All groups showed equal learning at 15 mo. At 19 mo, TBI-Veh exhibited learning deficits on day 4 compared to Sham-Veh. (C) Platform crossings in the memory probe test show expected aging-related decline in Sham-Veh mice, and TBI-Veh showed significant impairment relative to Sham-Veh. Memory function was fully restored in TBI-P7C3-A20 at both time points. Values are mean ± SEM. Individual data points represent individual animals. Significance was determined by repeated-measure two-way ANOVA for learning, one-way ANOVA for memory, and Dunnett’s post hoc analysis. *P < 0.05, **P < 0.01, ***P < 0.001, relative to TBI-Veh.     

Structure,self-assembly,and properties of a truncated reflectin variant

Naturally occurring and recombinant protein-based materials are frequently employed for the study of fundamental biological processes and are often leveraged for applications in areas as diverse as electronics, optics, bioengineering, medicine, and even fashion. Within this context, unique structural proteins known as reflectins have recently attracted substantial attention due to their key roles in the fascinating color-changing capabilities of cephalopods and their technological potential as biophotonic and bioelectronic materials. However, progress toward understanding reflectins has been hindered by their atypical aromatic and charged residue-enriched sequences, extreme sensitivities to subtle changes in environmental conditions, and well-known propensities for aggregation. Herein, we elucidate the structure of a reflectin variant at the molecular level, demonstrate a straightforward mechanical agitation-based methodology for controlling this variant’s hierarchical assembly, and establish a direct correlation between the protein’s structural characteristics and intrinsic optical properties. Altogether, our findings address multiple challenges associated with the development of reflectins as materials, furnish molecular-level insight into the mechanistic underpinnings of cephalopod skin cells’ color-changing functionalities, and may inform new research directions across biochemistry, cellular biology, bioengineering, and optics.

Materials from naturally occurring and recombinant proteins are frequently employed for the study of fundamental biological processes and leveraged for applications in fields as diverse as electronics, optics, bioengineering, medicine, and fashion (1–13). Such broad utility is enabled by the numerous advantageous characteristics of protein-based materials, which include sequence modularity, controllable self-assembly, stimuli-responsiveness, straightforward processability, inherent biological compatibility, and customizable functionality (1–13). Within this context, unique structural proteins known as reflectins have recently attracted substantial attention because of their key roles in the fascinating color-changing capabilities of cephalopods, such as the squid shown in Fig. 1A, and have furthermore demonstrated their utility for unconventional biophotonic and bioelectronic technologies (11–40). For example, in vivo, Bragg stack-like ultrastructures from reflectin-based high refractive index lamellae (membrane-enclosed platelets) are responsible for the angle-dependent narrowband reflectance (iridescence) of squid iridophores, as shown in Fig. 1B (15–20). Analogously, folded membranes containing distributed reflectin-based particle arrangements within sheath cells lead to the mechanically actuated iridescence of squid chromatophore organs, as shown in Fig. 1C (15, 16, 21, 22). Moreover, in vitro, films processed from squid reflectins not only exhibit proton conductivities on par with some state-of-the-art artificial materials (23–27) but also support the growth of murine and human neural stem cells (28, 29). Additionally, morphologically variable coatings assembled from different reflectin isoforms can enable the functionality of chemically and electrically actuated color-changing devices, dynamic near-infrared camouflage platforms, and stimuli-responsive photonic architectures (27, 30–34). When considered together, these discoveries and demonstrations constitute compelling motivation for the continued exploration of reflectins as model biomaterials.Open in a separate windowFig. 1.(A) A camera image of a D. pealeii squid for which the skin contains light-reflecting cells called iridophores (bright spots) and pigmented organs called chromatophores (colored spots). Image credit: Roger T. Hanlon (photographer). (B) An illustration of an iridophore (Left), which shows internal Bragg stack-like ultrastructures from reflectin-based lamellae (i.e., membrane-enclosed platelets) (Inset). (C) An illustration of a chromatophore organ (Left), which shows arrangements of reflectin-based particles within the sheath cells (Inset). (D) The logo of the 28-residue-long N-terminal motif (RMN), which depicts the constituent amino acids (Upper) and their predicted secondary structures (Lower). (E) The logo of the 28-residue-long internal motif (RMI), which depicts the constituent amino acids (Upper) and their predicted secondary structures (Lower). (F) The logo of the 21-residue-long C-terminal motif (RMC), which depicts the constituent amino acids (Upper) and their predicted secondary structures (Lower). (G) The amino acid sequence of full-length D. pealeii reflectin A1, which contains a single RMN motif (gray oval) and five RMI motifs (orange ovals). (H) An illustration of the selection of the prototypical truncated reflectin variant (denoted as RfA1TV) from full-length D. pealeii reflectin A1.Given reflectins’ demonstrated significance from both fundamental biology and applications perspectives, some research effort has been devoted to resolving their three-dimensional (3D) structures (30, 31, 35–39). For example, fibers drawn from full-length Euprymna scolopes reflectin 1a and films processed from truncated E. scolopes reflectin 1a were shown to possess secondary structural elements (i.e., α-helices or β-sheets) (30, 31). In addition, precipitated nanoparticles and drop-cast films from full-length Doryteuthis pealeii reflectin A1 have exhibited β-character, which was seemingly associated with their conserved motifs (35, 36). Moreover, nanoparticles assembled from both full-length and truncated Sepia officinalis reflectin 2 variants have demonstrated signatures consistent with β-sheet or α-helical secondary structure, albeit in the presence of surfactants (38). However, such studies were made exceedingly challenging by reflectins’ atypical primary sequences enriched in aromatic and charged residues, documented extreme sensitivities to subtle changes in environmental conditions, and well-known propensities for poorly controlled aggregation (12, 14, 15, 30–32, 34–39). Consequently, the reported efforts have all suffered from multiple drawbacks, including the need for organic solvents or denaturants, the evaluation of only polydisperse or aggregated (rather than monomeric) proteins, a lack of consensus among different experimental techniques, inadequate resolution that precluded molecular-level insight, imperfect agreement between computational predictions and experimental observations, and/or the absence of conclusive correlations between structure and optical functionality. As such, there has emerged an exciting opportunity for investigating reflectins’ molecular structures, which remain poorly understood and the subject of some debate.Herein, we elucidate the structure of a reflectin variant at the molecular level, demonstrate a robust methodology for controlling this variant’s hierarchical assembly, and establish a direct correlation between its structural characteristics and optical properties. We first rationally select a prototypical reflectin variant expected to recapitulate the behavior of its parent protein by using a bioinformatics-guided approach. We next map the conformational and energetic landscape accessible to our selected protein by means of all-atom molecular dynamics (MD) simulations. We in turn produce our truncated reflectin variant with and without isotopic labeling, develop solution conditions that maintain the protein in a monomeric state, and characterize the variant’s size and shape with small-angle X-ray scattering (SAXS). We subsequently resolve our protein’s dynamic secondary and tertiary structures and evaluate its backbone conformational fluctuations with NMR spectroscopy. Finally, we demonstrate a straightforward mechanical agitation-based approach to controlling our truncated reflectin variant’s secondary structure, hierarchical self-assembly, and bulk refractive index distribution. Overall, our findings address multiple challenges associated with the development of reflectins as materials, furnish molecular-level insight into the mechanistic underpinnings of cephalopod skin cells’ color-changing functionalities, and appear poised to inform new directions across biochemistry, cellular biology, bioengineering, and optics.     

Widespread occurrence of the droplet state of proteins in the human proteome

A wide range of proteins have been reported to condensate into a dense liquid phase, forming a reversible droplet state. Failure in the control of the droplet state can lead to the formation of the more stable amyloid state, which is often disease-related. These observations prompt the question of how many proteins can undergo liquid–liquid phase separation. Here, in order to address this problem, we discuss the biophysical principles underlying the droplet state of proteins by analyzing current evidence for droplet-driver and droplet-client proteins. Based on the concept that the droplet state is stabilized by the large conformational entropy associated with nonspecific side-chain interactions, we develop the FuzDrop method to predict droplet-promoting regions and proteins, which can spontaneously phase separate. We use this approach to carry out a proteome-level study to rank proteins according to their propensity to form the droplet state, spontaneously or via partner interactions. Our results lead to the conclusion that the droplet state could be, at least transiently, accessible to most proteins under conditions found in the cellular environment.

It has been recently observed that proteins can self-assemble through a liquid–liquid phase separation (LLPS) process into a dense liquid phase, while maintaining at least in part their functional native states (1–4). These liquid-like assemblies of complex compositions are often referred to as biomolecular condensates or membraneless organelles (1–4). Here, we refer to these dynamic and reversible condensates as droplets, in order to distinguish them from irreversible amyloids. Droplets can concentrate cellular components to perform efficiently a variety of different functions, with an increasing number of biological roles being discovered (1–4).In this work, we investigate whether liquid–liquid phase separation can be expected to be a proteome-wide phenomenon. In this view, the condensation of proteins from the native state to the amyloid state may quite generally proceed through an intermediate dense liquid phase, which is typically metastable (5) (Fig. 1). Different proteins may have different propensities to remain in this metastable phase, depending in particular on the free energy barrier between the droplet and amyloid states (Fig. 1). This type of liquid–liquid phase separation is indeed typical of condensation phenomena (1, 6), and sometimes is referred to as the Ostwald step rule (7). One may think that for most proteins the free energy barrier between the droplet and fibrillar states is low, and therefore the droplet state cannot be readily observed (Fig. 1). Indeed, this state may be difficult to detect due to a variety of reasons, including because experimental methods to probe its formation, in particular high-throughput ones, are still under development (8). Furthermore, our current understanding of the interactions that stabilize the metastable dense liquid phase is still incomplete.Open in a separate windowFig. 1.Liquid–liquid phase separation could be expected to be a proteome-wide phenomenon. Proteins that undergo condensation convert from the native state to the amyloid state through a dense liquid state (the droplet state). The stability of these different states (the minima in the free energy), as well as the conversion rates between them (the barriers in the free energy), is different for different proteins. For most proteins under cellular conditions, the native and droplet states could be expected to be metastable (56), being kinetically trapped by a free energy barrier (ΔG) between the droplet and fibrillar states. Proteins that can be observed in the droplet state tend to have a high free energy barrier (LLPS; green) while the other ones tend to have a low free energy barrier compared with the thermal energy (non-LLPS; orange). For certain proteins the droplet state is functional, and it is stabilized by extrinsic factors, such as RNA and posttranslational modifications.Native and amyloid states are stabilized by specific interactions including hydrogen bonds, ionic interactions, and van der Waals contacts typical of ordered states and enthalpic in nature (9, 10). By contrast, in droplets, transient short-range aromatic cation–π and π–π, dipole–dipole, and electrostatic and hydrophobic interactions have been observed, providing low-specificity, weak-affinity contacts characteristic of disordered states (11–16). These observations have led to a series of prediction methods (11, 13, 17–19), which focused on specific side-chain interactions. The redundancy and multivalency of the interacting elements (20) suggest that conformational entropy is a driving force of the condensation (21), also including main-chain contributions. Indeed, proteins exhibiting many binding configurations with a specific partner are often capable of forming droplets (22).Here, we exploit the observation that many proteins exhibit high conformational entropy upon binding, which can be predicted from their amino acid sequences (23). Based on this result, we develop the FuzDrop method to predict the droplet-promoting propensity of proteins and their droplet-promoting profiles based on the conformational entropy of their free states and the binding entropy. Using this method, we identify a list of “droplet-driving” proteins, which are predicted to undergo spontaneous liquid–liquid phase separation under physiological conditions, and estimate that they comprise about 40% of the human proteome. In addition, we also predict that about 80% of the proteins are “droplet clients,” characterized by short droplet-promoting regions in their sequences, which facilitate condensation via interactions with suitable partners. Taken together, our results indicate that protein phase separation is a proteome-wide phenomenon.     

Plant species richness at archaeological sites suggests ecological legacy of Indigenous subsistence on the Colorado Plateau

Humans have both intentional and unintentional impacts on their environment, yet identifying the enduring ecological legacies of past small-scale societies remains difficult, and as such, evidence is sparse. The present study found evidence of an ecological legacy that persists today within an semiarid ecosystem of western North America. Specifically, the richness of ethnographically important plant species is strongly associated with archaeological complexity and ecological diversity at Puebloan sites in a region known as Bears Ears on the Colorado Plateau. A multivariate model including both environmental and archaeological predictors explains 88% of the variation in ethnographic species richness (ESR), with growing degree days and archaeological site complexity having the strongest effects. At least 31 plant species important to five tribal groups (Navajo, Hopi, Zuni, Ute Mountain Ute, and Apache), including the Four Corners potato (Solanum jamesii), goosefoot (Chenopodium sp.), wolfberry (Lycium pallidum), and sumac (Rhus trilobata), occurred at archaeological sites, despite being uncommon across the wider landscape. Our results reveal a clear ecological legacy of past human behavior: even when holding environmental variables constant, ESR increases significantly as a function of past investment in habitation and subsistence. Consequently, we suggest that propagules of some species were transported and cultivated, intentionally or not, establishing populations that persist to this day. Ensuring persistence will require tribal input for conserving and restoring archaeo-ecosystems containing “high-priority” plant species, especially those held sacred as lifeway medicines. This transdisciplinary approach has important implications for resource management planning, especially in areas such as Bears Ears that will experience greater visitation and associated impacts in the near future.

Local resource abundance is important for determining where in a given landscape humans decide to live. Nearby water, game, soil, and plants provide readily available wild resources for foraging and conditions that allow for cultivation (1–5). However, humans also modify their surrounding environments in order to increase the abundance and diversity of local plant (6–11) and animal (12–15) resources. Such “human niche construction” is a hallmark of ancient and modern societies (16, 17), having positive and negative impacts on global biodiversity while possibly creating enduring ecological legacies (18–21). This may be especially true for more sedentary and dense populations (22, 4) that are more likely to find investment worthwhile (23) and to produce unintentional impacts. Thus, variation in contemporary ecological diversity may in part reflect past land use dynamics and, therefore, be revealed through coupled archaeological and ecological research (24–33).Coupled ecological and archaeological research has led to the discovery of altered patterns of succession resulting from 1) forest clearing and changes in canopy light regime (34, 35), 2) alterations of soil especially linked to food refuse (36, 37), 3) changes in fire regimes (38, 39), and, more rarely, 4) the importation of plant propagules from distant sites of collection (40, 41). Identifying such long-lost dynamics between humans and landscapes can inform conservation aimed at restoring site-specific artifacts, features, and the associated resource base past and present, here termed “archaeo-ecosystems” (42, 43). This would greatly facilitate cross-cultural management of public lands (44) in ways that promote Indigenous health, cultural reclamation, and sovereignty (7, 45). The linkages, however, between ecological legacies, archaeo-ecosystem restoration and cross-cultural management have yet to be systematically tested or practically applied.Here, we offer a formal evaluation of this archaeo-ecosystem approach by using paired archaeological and ecological survey data focused on Puebloan occupation of a region known as Bears Ears on the Colorado Plateau in southeastern Utah (Fig. 1). Puebloan populations modified their environment by constructing terraces and check dams, developing blinds and wing traps, importing exogenous species, and setting fires (4, 22, 46), but investments were not uniform across the region. We test the hypothesis that locations with greater investment indicated by larger and more complex archaeological sites should today have higher richness of culturally significant plant species, here termed ethnographic species richness (ESR), as an enduring legacy of past investment. Our study expands previous work on ecological legacies by using field surveys to develop an explanatory model applied to 265 sites across one million acres of semiarid public lands. It documents the occurrence of uncommon and ethnographically significant plant species associated with those sites and infuses traditional ecological knowledge into proposed management actions for conserving these archaeo-ecosystems. Controlling for underlying environmental variation, our results indicate that past human habitation increases the diversity of plant species important for Indigenous subsistence.Open in a separate windowFig. 1.Location of Bears Ears National Monument in southeastern Utah. The predicted ESR at 265 known archaeological sites across the original and reduced monument boundaries and surrounding region are shown.     

Developmental influence on evolutionary rates and the origin of placental mammal tooth complexity

Development has often been viewed as a constraining force on morphological adaptation, but its precise influence, especially on evolutionary rates, is poorly understood. Placental mammals provide a classic example of adaptive radiation, but the debate around rate and drivers of early placental evolution remains contentious. A hallmark of early dental evolution in many placental lineages was a transition from a triangular upper molar to a more complex upper molar with a rectangular cusp pattern better specialized for crushing. To examine how development influenced this transition, we simulated dental evolution on “landscapes” built from different parameters of a computational model of tooth morphogenesis. Among the parameters examined, we find that increases in the number of enamel knots, the developmental precursors of the tooth cusps, were primarily influenced by increased self-regulation of the molecular activator (activation), whereas the pattern of knots resulted from changes in both activation and biases in tooth bud growth. In simulations, increased activation facilitated accelerated evolutionary increases in knot number, creating a lateral knot arrangement that evolved at least ten times on placental upper molars. Relatively small increases in activation, superimposed on an ancestral tritubercular molar growth pattern, could recreate key changes leading to a rectangular upper molar cusp pattern. Tinkering with tooth bud geometry varied the way cusps initiated along the posterolingual molar margin, suggesting that small spatial variations in ancestral molar growth may have influenced how placental lineages acquired a hypocone cusp. We suggest that development could have enabled relatively fast higher-level divergence of the placental molar dentition.

Whether developmental processes bias or constrain morphological adaptation is a long-standing question in evolutionary biology (1–4). Many of the distinctive features of a species derive from pattern formation processes that establish the position and number of anatomical structures (5). If developmental processes like pattern formation are biased toward generating only particular kinds of variation, adaptive radiations may often be directed along developmental–genetic “lines of least resistance” (2, 4, 6, 7). Generally, the evolutionary consequences of this developmental bias have been considered largely in terms of how it might influence the pattern of character evolution (e.g., refs. 1, 2, 8–10). But development could also influence evolutionary rates by controlling how much variation is accessible to natural selection in a given generation (11).For mammals, the dentition is often the only morphological system linking living and extinct species (12). Correspondingly, tooth morphology plays a crucial role in elucidating evolutionary relationships, time calibrating phylogenetic trees, and reconstructing adaptive responses to past environmental change (e.g., refs. 13–15). One of the most pervasive features of dental evolution among mammals is an increase in the complexity of the tooth occlusal surface, primarily through the addition of new tooth cusps (16, 17). These increases in tooth complexity are functionally and ecologically significant because they enable more efficient mechanical breakdown of lower-quality foods like plant leaves (18).Placental mammals are the most diverse extant mammalian group, comprising more than 6,000 living species spread across 19 extant orders, and this taxonomic diversity is reflected in their range of tooth shapes and dietary ecologies (12). Many extant placental orders, especially those with omnivorous or herbivorous ecologies (e.g., artiodactyls, proboscideans, rodents, and primates), convergently evolved a rectangular upper molar cusp pattern from a placental ancestor with a more triangular cusp pattern (19–21). This resulted from separate additions in each lineage of a novel posterolingual cusp, the "hypocone'''' [sensu (19)], to the tritubercular upper molar (Fig. 1), either through modification of a posterolingual cingulum (“true” hypocone) or another posterolingual structure, like a metaconule (pseudohypocone) (19). The fossil record suggests that many of the basic steps in the origin of this rectangular cusp pattern occurred during an enigmatic early diversification window associated with the divergence and early radiation of several placental orders (20, 21; Fig. 1). However, there remains debate about the rate and pattern of early placental divergence (22–24). On the one hand, most molecular phylogenies suggest that higher-level placental divergence occurred largely during the Late Cretaceous (25, 26), whereas other molecular phylogenies and paleontological analyses suggest more rapid divergence near the Cretaceous–Paleogene (K–Pg) boundary (21, 24, 27–29). Most studies agree that ecological opportunity created in the aftermath of the K–Pg extinction probably played an important role in ecomorphological diversification within the placental orders (30, 31). But exactly how early placentals acquired the innovations needed to capitalize on ecological opportunity remains unclear. Dental innovations, especially those which facilitated increases in tooth complexity, may have been important because they would have promoted expansion into plant-based dietary ecologies left largely vacant after the K–Pg extinction event (32).Open in a separate windowFig. 1.Placental mammal lineages separately evolved complex upper molar teeth with a rectangular cusp pattern composed of two lateral pairs of cusps from a common ancestor with a simpler, triangular cusp pattern. Many early relatives of the extant placental orders, such as Eritherium, possessed a hypocone cusp and a more rectangular primary cusp pattern. Examples of complex upper molars are the following: Proboscidea, the gomphothere Anancus; Rodentia, the wood mouse Apodemus; and Artiodactyla, the suid Nyanzachoerus.Mammalian tooth cusps form primarily during the “cap” and “bell” stage of dental development, when signaling centers called enamel knots establish the future sites of cusp formation within the inner dental epithelium (33, 34). The enamel knots secrete molecules that promote proliferation and changes in cell–cell adhesion, which facilitates invagination of the dental epithelium into an underlying layer of mesenchymal cells (34, 35). Although a range of genes are involved in tooth cusp patterning (36–38), the basic dynamics can be effectively modeled using reaction–diffusion models with just three diffusible morphogens: an activator, an inhibitor, and a growth factor (39–41). Candidate activator genes in mammalian tooth development include Bmp4, Activin A, Fgf20, and Wnt genes, whereas potential inhibitors include Shh and Sostdc, and Fgf4 and Bmp2 have been hypothesized to act as growth factors (38, 40–43). In computer models of tooth development, activator molecules up-regulated in the underlying mesenchyme stimulate differentiation of overlying epithelium into nondividing enamel knot cells. These in turn secrete molecules that inhibit further differentiation of epithelium into knot cells, while also promoting cell proliferation that creates the topographic relief of the cusp (40). Although many molecular, cellular, and physical processes have the potential to influence cusp formation, and thereby tooth complexity (35, 37), parameters that control the strength and conductance of the activator and inhibitor signals, the core components of the reaction–diffusion cusp patterning mechanism (39, 40) are likely to be especially important.Here, we integrate a previous computer model of tooth morphogenesis called ToothMaker (41), with simulations of trait evolution and data from the fossil record (Fig. 2), to examine the developmental origins of tooth complexity in placental mammals. Specifically, we ask the following: 1) What developmental processes can influence how many cusps form? 2) How might these developmental processes influence the evolution of tooth cusp number, especially rates? And 3) what developmental changes may have been important in the origins of the fourth upper molar cusp, the hypocone, in placental mammal evolution?Open in a separate windowFig. 2.Workflow for simulations of tooth complexity evolution. (A) Tooth shape is varied for five signaling and growth parameters in ToothMaker. (B) From an ancestral state, each parameter is varied in 2.5% increments up to a maximum of ± 50% of the ancestral state. (C) Tooth complexity and enamel knot (EK) pattern were quantified for each parameter combination. Tooth complexity was measured using cusp number/EK number and OPC. ToothMaker and placental upper second molars were classified into categories based on EK/cusp pattern. (D) The parameter space was populated with pattern and tooth complexity datums to build a developmental landscape. (E) Tooth complexity evolution was simulated on each developmental landscape. (F) Resulting diversity and pattern of tooth complexity was compared with placental mammal molar diversity.