From the Cover: Magmatic thickening of crust in non–plate tectonic settings initiated the subaerial rise of Earth’s first continents 3.3 to 3.2 billion years ago

When and how Earth''s earliest continents—the cratons—first emerged above the oceans (i.e., emersion) remain uncertain. Here, we analyze a craton-wide record of Paleo-to-Mesoarchean granitoid magmatism and terrestrial to shallow-marine sedimentation preserved in the Singhbhum Craton (India) and combine the results with isostatic modeling to examine the timing and mechanism of one of the earliest episodes of large-scale continental emersion on Earth. Detrital zircon U-Pb(-Hf) data constrain the timing of terrestrial to shallow-marine sedimentation on the Singhbhum Craton, which resolves the timing of craton-wide emersion. Time-integrated petrogenetic modeling of the granitoids quantifies the progressive changes in the cratonic crustal thickness and composition and the pressure–temperature conditions of granitoid magmatism, which elucidates the underlying mechanism and tectonic setting of emersion. The results show that the entire Singhbhum Craton became subaerial ∼3.3 to 3.2 billion years ago (Ga) due to progressive crustal maturation and thickening driven by voluminous granitoid magmatism within a plateau-like setting. A similar sedimentary–magmatic evolution also accompanied the early (>3 Ga) emersion of other cratons (e.g., Kaapvaal Craton). Therefore, we propose that the emersion of Earth’s earliest continents began during the late Paleoarchean to early Mesoarchean and was driven by the isostatic rise of their magmatically thickened (∼50 km thick), buoyant, silica-rich crust. The inferred plateau-like tectonic settings suggest that subduction collision–driven compressional orogenesis was not essential in driving continental emersion, at least before the Neoarchean. We further surmise that this early emersion of cratons could be responsible for the transient and localized episodes of atmospheric–oceanic oxygenation (O₂-whiffs) and glaciation on Archean Earth.

The emergence of continental crust above sea level (called continental emersion) critically influences atmospheric and ocean chemistry, climate, and the supply of nutrients to the oceans via weathering and fluvial runoff (1, 2). However, it remains unclear when large areas of subaerial continental crust first appeared on Earth (1–13). A rapid and extensive emersion of continental crust at the Archean–Proterozoic transition (2.5 billion years ago [Ga]) is inferred from abrupt shifts in the oxygen isotope compositions of shales and magmatic zircons, zinc isotope composition of iron formations, and an increase in subaerial continental volcanism at that time (1, 3–5, 7). However, >3.0 to 2.7-Ga-old paleosols (ancient horizons of subaerial weathering) and terrestrial sedimentary rocks that formed atop Earth''s earliest stable continental nuclei, the cratons (14–17), provide direct evidence for earlier episodes of continental emersion. This inference is further corroborated by an increase in the diversity of detrital zircon ages in clastic sedimentary rocks from ∼2.8 Ga onwards, representing the development of regionally extensive watersheds at that time (13). Thus, subaerial exposure of continental crust before 2.5 Ga seems evident. However, the exact timing and spatial extent of these emersion events are poorly constrained, and their global significance remains unclear. Moreover, the mechanisms and tectonic settings that drove continental emersion during the Archean also remain ambiguous. A uniformitarian view posits that Archean continental emersion (whether at ∼2.5 Ga or earlier) was driven by plate tectonics (1, 7, 9) with subduction-collision processes forming thick continental crust with high-standing topography via magmatism and compressional deformation, as is observed on modern Earth (2). However, the operation of plate tectonics in the Archean is disputed (9, 10, 18, 19), and a growing body of evidence suggests that subduction-collision processes were not globally prevalent until ∼2.5 to 2.0 Ga (10, 20–25), warranting the consideration of alternative mechanisms for producing subaerial continental landmasses on early Earth.Here, we integrate the Paleoarchean (3.6 to 3.2 Ga) to Mesoarchean (3.2 to 2.8 Ga) magmatic and sedimentary records of the Singhbhum Craton of India to elucidate the timing and underlying geodynamics of craton-wide emersion of continental crust in the Archean. This craton is ideal for studying Archean continental emersion as it hosts widespread Mesoarchean terrestrial to shallow-marine siliciclastic strata (26–29) and one of the oldest paleosols on Earth (the ∼3.29- to 3.08-Ga Keonjhar paleosol) (30) (Fig. 1A), providing an unambiguous record of early subaerial continental crust. We first synthesize detrital zircon data (SI Appendix, Methods and Datasets S1 and S2) from these Mesoarchean strata to determine the timing of emersion of the Singhbhum Craton. Then, we analyze the published compositional data of the craton’s Paleo-to-Mesoarchean granitoids (SI Appendix, Methods and Dataset S3) to reconstruct the history of crustal thickening and chemical maturation before and during the emersion. This allows us to link the physicochemical evolution of Archean cratonic crust to its emersion as the long-term topography of subaerial continents is critically controlled by their thick, silica-rich (less-dense) crust, which experiences large positive buoyancy and thereby a greater isostatic uplift relative to the surrounding thin and mafic (more-dense) oceanic crust (2). In particular, we determine the pressure–temperature (P-T) conditions of formation of the tonalite–trondhjemite–granodiorite (TTG) suite of granitoids—the principal crustal component of the Singhbhum Craton. The P-T data provide a time-integrated estimate of crustal thicknesses and elucidate the tectonic process controlling the craton’s emersion. These crustal thickness values are cross checked against the independent thickness estimates provided by the La-Yb systematics of the TTGs. Finally, a link between crustal thickening, maturation, and emersion is demonstrated via isostatic modeling.Open in a separate windowFig. 1.Spatial distribution and detrital zircon U-Pb ages of the Singhbhum cover sequence. (A) Simplified geological map of the Singhbhum Craton (29, 31) showing the outliers of the Singhbhum cover sequence and their granite–greenstone basement (SI Appendix, SI Text). The orange area in the Inset shows the location of the Singhbhum Craton within the Indian Peninsula. The younger (∼3.0 to 2.8 Ga) granitoids (including those of the Rengali Province) that intruded the outliers of the cover sequence are also shown. The formations comprising the outliers include: Mahagiri (Mhg), Pallahara-Mankaharchua (PM), Simlipal (Smp), Keonjhar (Kj), Birtola (Bir), Achu (Ac), Bisrampur (Brm), and Dhanjori (Dj). (B) Kernel density estimate (KDE) of <±10% discordant detrital zircon (²⁰⁷Pb/²⁰⁶Pb) ages from different outliers of the cover sequence (SI Appendix, Fig. S1). For each outlier, the white arrow shows the weighted mean ²⁰⁷Pb/²⁰⁶Pb age of the youngest detrital zircon population, which represents its maximum depositional age (SI Appendix, Fig. S1). The minimum depositional age (dashed gray line) of ∼2.94 Ga is constrained from a metamorphic event that affected the outliers. The colored bands show the age brackets of the different phases of granitoid magmatism and greenstone belt formation. Data are in Dataset S1. Refer to SI Appendix, Methods and SI Text for details.     

Global urban population exposure to extreme heat

Increased exposure to extreme heat from both climate change and the urban heat island effect—total urban warming—threatens the sustainability of rapidly growing urban settlements worldwide. Extreme heat exposure is highly unequal and severely impacts the urban poor. While previous studies have quantified global exposure to extreme heat, the lack of a globally accurate, fine-resolution temporal analysis of urban exposure crucially limits our ability to deploy adaptations. Here, we estimate daily urban population exposure to extreme heat for 13,115 urban settlements from 1983 to 2016. We harmonize global, fine-resolution (0.05°), daily temperature maxima and relative humidity estimates with geolocated and longitudinal global urban population data. We measure the average annual rate of increase in exposure (person-days/year⁻¹) at the global, regional, national, and municipality levels, separating the contribution to exposure trajectories from urban population growth versus total urban warming. Using a daily maximum wet bulb globe temperature threshold of 30 °C, global exposure increased nearly 200% from 1983 to 2016. Total urban warming elevated the annual increase in exposure by 52% compared to urban population growth alone. Exposure trajectories increased for 46% of urban settlements, which together in 2016 comprised 23% of the planet’s population (1.7 billion people). However, how total urban warming and population growth drove exposure trajectories is spatially heterogeneous. This study reinforces the importance of employing multiple extreme heat exposure metrics to identify local patterns and compare exposure trends across geographies. Our results suggest that previous research underestimates extreme heat exposure, highlighting the urgency for targeted adaptations and early warning systems to reduce harm from urban extreme heat exposure.

Increased exposure to extreme heat from both climate change (1–5) and the urban heat island (UHI) effect (6–9) threaten the sustainability of rapidly growing urban settlements worldwide. Exposure to dangerously high temperatures endangers urban health and development, driving reductions in labor productivity and economic output (10, 11) and increases in morbidity (1) and mortality (2, 3, 12). Within urban settlements, extreme heat exposure is highly unequal and most severely impacts the urban poor (13, 14). Despite the harmful and inequitable risks, we presently lack a globally comprehensive, fine-resolution understanding of where urban population growth intersects with increases in extreme heat (2, 6, 15). Without this knowledge, we have limited ability to tailor adaptations to reduce extreme heat exposure across the planet’s diverse urban settlements (6, 15, 16).Reducing the impacts of extreme heat exposure to urban populations requires globally consistent, accurate, and high-resolution measurement of both climate and demographic conditions that drive exposure (5, 15, 17). Such analysis provides decision makers with information to develop locally tailored interventions (7, 18, 19) and is also sufficiently broad in spatial coverage to transfer knowledge across urban geographies and climates (6). Information about exposures and interventions from diverse contexts is vital for the development of functional early warning systems (20) and can help guide risk assessments and inform future scenario planning (21). Existing global extreme heat exposure assessments (1, 2), however, do not meet these criteria (SI Appendix, Table S1) and are insufficient for decision makers. These studies are coarse grained (>0.5° spatial resolution), employ disparate or single metrics that do not capture the complexities of heat-health outcomes (22), do not separate urban from rural exposure (19), and rely on climate reanalysis products that can be substantially (∼1 to 3 °C) cooler than in situ data observations (5, 23, 24). In fact, widely cited benchmarks (25) that estimate extreme heat with the version 5 of the European Centre for Medium-Range Weather Forecasts Reanalysis (ERA5) (26) may greatly underestimate total global exposure to extreme heat (5, 23, 24). Using a 40.6 °C daily maximum 2-m air temperature threshold (T_max), recent analysis found that ERA5 T_max drastically underestimated the number of extreme heat days per year compared to in situ observations (23). Finally, few studies (2, 18) have assessed urban extreme heat exposure across data-sparse (23) rapidly urbanizing regions, such as sub-Saharan Africa, the Middle East, and Southern Asia (27), that may be most impacted by increased extreme heat events due to climate change (3, 5, 28).Here, we present a globally comprehensive, fine-resolution, and longitudinal estimate of urban population exposure to extreme heat––referred to henceforth as exposure––for 13,115 urban settlements from 1983 to 2016. To accomplish this, we harmonize global, fine-grained (0.05° spatial resolution) T_max estimates (23) with global urban population and spatial extent data (29). For each urban settlement, we calculate area-averaged daily wet bulb globe temperature (WBGT_max) (30) and heat index (HI_max) (31) maxima using Climate Hazards Center InfraRed Temperature with Stations Daily (CHIRTS-daily) T_max (23) and down-scaled daily minimum relative humidity (RH_min) estimates (32). CHIRTS-daily is better suited to measure urban extreme heat exposure than other gridded temperature datasets used in recent global extreme heat studies (SI Appendix, Table S1) for two reasons. First, it is more accurate, especially at long distances (refer to figure 3 in ref. 23), than widely used gridded temperature datasets to estimate urban temperature signals worldwide (SI Appendix, Figs. S1 and S2). Second, it better captures the spatial heterogeneity of T_max across diverse urban contexts (SI Appendix, Fig. S3). These factors are key for measuring extreme heat exposure in rapidly urbanizing, data-sparse regions.As discussed in refs. 23 and 24, the number of in situ temperature observations is far too low across rapidly urbanizing (27) regions to resolve spatial and temporal urban extreme heat fluctuations, which can vary dramatically over small distances and time periods. For example, of the more than 3,000 urban settlements in India (29), only 111 have reliable station observations (SI Appendix, Fig. S3). While climate reanalyses can help overcome these limitations, they are coarse grained (SI Appendix, Table S1) and suffer from mean bias, and, to a lesser degree, temporal fidelity. ERA5 has been shown to substantially underestimate the increasing frequencies of heat extremes (figure 4 in ref. 23), while Modern-Era Retrospective analysis for Research and Applications Version 2 (MERRA2) fails to represent the substantial increase in recent monthly T_max values (figure 8 in ref. 24). These datasets dramatically underestimate increases in warming. CHIRTS-daily overcomes these limitations by coherently stacking information from a high-resolution (0.05°) climatology-derived surface emission temperature (24), interpolated in situ observations, and ERA5 reanalysis to produce a product that has been explicitly developed to monitor and assess temperature related hazards (23). As such, CHIRTS-daily is best suited to capture variation in exposure across urban settlements in rapidly urbanizing (27), data-sparse regions such as sub-Saharan Africa, the Middle East, and Southern Asia (SI Appendix, Fig. S3) (24).We measure exposure in person-days/year⁻¹—the number of days per year that exceed a heat exposure threshold multiplied by the total urban population exposed (5). We then estimate annual rates of increase in exposure at the global (Fig. 1), regional (SI Appendix, Table S2), national (SI Appendix, Table S3), and municipality levels from 1983 to 2016 (SI Appendix, Table S4). At each spatial scale, we separate the contribution to exposure trajectories from total urban warming and population growth (5). For clarity, total urban warming refers to the combined increase of extreme heat in urban settlements from both the UHI effect and anthropogenic climate change. We do not decouple these two forcing agents (33, 34). However, we identify which urban settlements have warmed the fastest by measuring the rate of increase in the number of days per year that exceed the two extreme heat thresholds described below (15). Our main findings use an extreme heat exposure threshold defined as WBGT_max > 30 °C, the International Standards Organization (ISO) occupational heat stress threshold for risk of heat-related illness among acclimated persons at low metabolic rates (100 to 115 W) (30). WBGT_max is a widely used heat stress metric (35) that captures the biophysical response (36) of hot temperature–humidity combinations (3, 17) that reduce labor output (36), lead to heat-related illness (36), and can cause death (23). In using a threshold WBGT_max > 30 °C, which has been associated with higher mortality rates among vulnerable populations (37), we aim to identify truly extremely hot temperature–humidity combinations (17) that can harm human health and well-being. We recognize, however, that strict exposure thresholds do not account for individual-level risks and vulnerabilities related to acclimatization, socio-economic, or health status or local infrastructure (18, 19, 38). We also note that there are a range of definitions of exposure, and we provide further analysis identifying 2-d or longer periods during which the maximum heat index (HI_max) (31) exceeded 40.6 °C (SI Appendix, Figs. S4–S6) following the US National Weather Service’s definition for an excessive heat warning (39).Open in a separate windowFig. 1.Global urban population exposure to extreme heat, defined by 1-d or longer periods when WBGT_max > 30 °C, from 1983 to 2016 (A), with the contribution from population growth (B), and total urban warming (C) decoupled.     

Accounting for a mirror-image conformation as a subtle effect in protein folding

By using local (free-energy profiles along the amino acid sequence and ¹³C^α chemical shifts) and global (principal component) analyses to examine the molecular dynamics of protein-folding trajectories, generated with the coarse-grained united-residue force field, for the B domain of staphylococcal protein A, we are able to (i) provide the main reason for formation of the mirror-image conformation of this protein, namely, a slow formation of the second loop and part of the third helix (Asp29–Asn35), caused by the presence of multiple local conformational states in this portion of the protein; (ii) show that formation of the mirror-image topology is a subtle effect resulting from local interactions; (iii) provide a mechanism for how protein A overcomes the barrier between the metastable mirror-image state and the native state; and (iv) offer a plausible reason to explain why protein A does not remain in the metastable mirror-image state even though the mirror-image and native conformations are at least energetically compatible.To perform their functions in living organisms, most proteins must fold from unfolded polypeptides into their functional, unique 3D structures. Understanding protein-folding mechanisms is crucial because misfolded proteins can cause many diseases, including neurodegenerative diseases (1) such as Alzheimer’s, Parkinson, and Huntington diseases. From theoretical and conceptual points of view, it has been suggested that a native protein exists in a thermodynamically stable state with its surroundings (2) and that a study of free-energy landscapes (FELs) holds the key to understanding how proteins fold and function (3, 4).The native structures of some proteins contain a high degree of symmetry that, in addition to the native structure, allows the existence of another, energetically very close to the native conformation, a native-like “mirror-image” structure. One of the representatives of such symmetrical proteins is the 10- to 55-residue fragment of the B domain of staphylococcal protein A [Protein Data Bank (PDB) ID: 1BDD, a three-α-helix bundle] (5). Protein A has been the subject of extensive theoretical (6–18) and experimental (19–23) studies because of its small size, fast folding kinetics, and biological importance. However, the mirror-image topology has never been a subject for discussion except for the earlier work by Olszewski et al. (7) and recent work by Noel et al. (24). The reason for this might be that it has never been detected experimentally and it was observed only in some theoretical studies (7–9, 12, 13, 15, 17, 18, 24) with different force fields. It is of interest to determine how realistic the mirror-image conformation is. Is it an artifact of the simulations or is it a conformation difficult to observe experimentally? Noel et al. (24) showed that the native and mirror-image structures have a similar enthalpic stability and are thermodynamically competitive and that the mirror image can be considered not just a computational annoyance, but as a real conformation competing with the native structure. Moreover, the mirror-image conformation is more entropically favorable than the native conformation (24). By making multiple mutations in the hydrophobic core and the first loop region, Olszewski et al. (7) found that the change in the handedness of the first loop induced by the mutations, the burial of the N cap of the second helix, and repacking of the hydrophobic core are responsible for formation of the mirror-image conformation. However, at the end, the authors stated: “… Whether the conclusion about the possible importance of turns in defining the global topology holds in general or is just specific to the three-helix bundles analyzed here requires additional investigation....” (ref. 7, p. 298).The difficulties for experiments to detect the mirror-image topology arise because the secondary structures of the mirror-image and the native conformation are identical and the native-contact interactions are similar in both conformations (details in Fig. S1 and SI Native and Mirror-Image Structures of Protein A). Hence, with an experimental technique such as circular dichroism, used to estimate the fraction of secondary-structure content, it is almost impossible to distinguish the mirror-image structure from the native structure. It would have been desirable if the mirror-image conformation and its evolution to the native structure could be detected by NMR spectroscopy. Nevertheless, by using local [¹³C^α chemical shift (25) and free-energy profiles (FEPs) along the amino acid sequence (26–28)] and global [principal component (PC) (29)] analyses (SI Materials and Methods), we examined molecular dynamics (MD) trajectories of protein A, generated with the coarse-grained united-residue (UNRES) force field (27, 30–32) (Fig. S2 and SI Materials and Methods). These analyses of the MD trajectories, in which folding from a fully unfolded conformation occurs either almost instantly or through a metastable state formed by the mirror-image topology, enabled us to elucidate the origin of the formation of a mirror-image topology and how the protein emerges from the kinetic trap and folds to the native state.The results presented in this work are based on the analysis of four pairs of MD trajectories at 270 K (in each pair, one trajectory folds directly to the native state and the other folds through the metastable mirror-image state) selected from 96 MD simulations, which we carried out in a broad range of temperatures (details in Materials and Methods). The mirror-image conformation is energetically competitive with the native conformation in the studied trajectories (an illustrative example of two trajectories is in Fig. S3), and these results are in agreement with those of earlier studies (12, 24).     

SARS-CoV-2 evolution in animals suggests mechanisms for rapid variant selection

SARS-CoV-2 spillback from humans into domestic and wild animals has been well documented, and an accumulating number of studies illustrate that human-to-animal transmission is widespread in cats, mink, deer, and other species. Experimental inoculations of cats, mink, and ferrets have perpetuated transmission cycles. We sequenced full genomes of Vero cell–expanded SARS-CoV-2 inoculum and viruses recovered from cats (n = 6), dogs (n = 3), hamsters (n = 3), and a ferret (n = 1) following experimental exposure. Five nonsynonymous changes relative to the USA-WA1/2020 prototype strain were near fixation in the stock used for inoculation but had reverted to wild-type sequences at these sites in dogs, cats, and hamsters within 1- to 3-d postexposure. A total of 14 emergent variants (six in nonstructural genes, six in spike, and one each in orf8 and nucleocapsid) were detected in viruses recovered from animals. This included substitutions in spike residues H69, N501, and D614, which also vary in human lineages of concern. Even though a live virus was not cultured from dogs, substitutions in replicase genes were detected in amplified sequences. The rapid selection of SARS-CoV-2 variants in vitro and in vivo reveals residues with functional significance during host switching. These observations also illustrate the potential for spillback from animal hosts to accelerate the evolution of new viral lineages, findings of particular concern for dogs and cats living in households with COVID-19 patients. More generally, this glimpse into viral host switching reveals the unrealized rapidity and plasticity of viral evolution in experimental animal model systems.

Cross-species transmission events, which challenge pathogens to survive in new host environments, typically result in species-specific adaptations (1). These evolutionary changes can determine the pathogenicity and transmissibility of the virus in novel host species (2). Pathogen host switching resulting in epidemic disease is a rare event that is constrained by the interaction between species (3). In contrast to most species, humans move globally and regularly come into contact with domestic and peridomestic animals. Thus, when a novel virus spreads through human populations, there is an incidental risk of exposure to potentially susceptible nonhuman species.This scenario has become evident with the SARS-CoV-2 pandemic (SI Appendix, Table S1). Originally resulting from viral spillover into humans (4, 5), likely from an animal reservoir, spillback into a wide range of companion and wild animals has occurred or been shown to be plausible (6–10), and an increasing number of studies have indicated a high frequency of human-to-animal SARS-CoV-2 spillback transmission (11–18). Given the short duration of viral shedding, serologic analyses present a more accurate characterization of actual animal exposures to SARS-CoV-2. Such studies conducted in a variety of animal species have illustrated surprisingly high levels of seroconversion in cats and dogs and more recently free-ranging deer (SI Appendix, Table S1) (73–87). Other well-documented spillback events include numerous mink farms (SI Appendix, Table S1). In one of these reports, multiple feral cats living on a mink farm in the Netherlands during a SARS-CoV-2 outbreak were seropositive, likely from the direct transmission of the virus from mink to cats, as owned cats on the same farm were seronegative (19). This further illustrates that cross-species transmission chains are readily achieved. Recent surveys of free-ranging white-tailed deer in Illinois, Michigan, New York, and Pennsylvania revealed 33% seropositivity in free-ranging animals (20). Active SARS-CoV-2 infection was subsequently confirmed by PCR in a deer in Ohio (21). Together, these findings suggest the likely establishment of multiple domestic animal and wildlife reservoirs of SARS-CoV-2.The repeated interspecies transmission of a virus presents the potential for the acceleration of viral evolution and a possible source of novel strain emergence. This was demonstrated by reverse zoonosis of SARS-CoV-2 from humans to mink, followed by a selection in mink and zoonotic transmission back to humans (8). Given that reverse zoonosis has been reported repeatedly in dogs and cats from households where COVID-19 patients reside, and the fact that up to 50% of households worldwide are inhabited by these companion animals, there is potential for similar transmission chains to arise via humans and their pets (22, 23). Elucidating the viral selection and species-specific adaptation of SARS-CoV-2 in common companion animals is therefore of high interest. Furthermore, understanding viral evolutionary patterns in both companion animals and experimental animal models provides a valuable appraisal of species-specific viral variants that spotlight genomic regions for host–virus interaction.Significant attention has been directed at substrains evolving from the initial SARS-CoV-2 isolate (24), and an accumulating number of variant lineages have demonstrated increased transmission potential in humans (25, 26). The role, if any, that reverse zoonotic infections of nonhuman species and spillback may have played in the emergence of these novel variants of SARS-CoV-2 remains unknown. Documenting viral evolution following the spillover of SARS-COV-2 into new species is difficult given the unpredictability of timing of these events; therefore, experimental studies can greatly aid the understanding of SARS-CoV-2 evolution in animal species. Laboratory-based studies also provide the opportunity to determine how changes that occur during viral expansion in cell culture may influence in vivo infections. This information is highly relevant for the interpretation of in vivo and in vitro experiments using inoculum propagated in culture.We therefore assessed the evolution of SARS-CoV-2 during the three rounds of expansion of strain USA-WA1/2020 in Vero E6 cells (27), followed by measuring the variant emergence occurring during primary experimental infection in four mammalian hosts. Specifically, we compared variant proportions, insertions, and deletions occurring in genomes of SARS-CoV-2 recovered from dogs (n = 3), cats (n = 6), hamsters (n = 3), and a ferret (n = 1).     

Spin crossover in ferropericlase and velocity heterogeneities in the lower mantle

Deciphering the origin of seismic velocity heterogeneities in the mantle is crucial to understanding internal structures and processes at work in the Earth. The spin crossover in iron in ferropericlase (Fp), the second most abundant phase in the lower mantle, introduces unfamiliar effects on seismic velocities. First-principles calculations indicate that anticorrelation between shear velocity (V_S) and bulk sound velocity (V_φ) in the mantle, usually interpreted as compositional heterogeneity, can also be produced in homogeneous aggregates containing Fp. The spin crossover also suppresses thermally induced heterogeneity in longitudinal velocity (V_P) at certain depths but not in V_S. This effect is observed in tomography models at conditions where the spin crossover in Fp is expected in the lower mantle. In addition, the one-of-a-kind signature of this spin crossover in the R_S/P (??ln?V_S/??ln?V_P) heterogeneity ratio might be a useful fingerprint to detect the presence of Fp in the lower mantle.Ferropericlase (Fp) is believed to be the second most abundant phase in the lower mantle (1, 2). Since the discovery of the high-spin (HS) to low-spin (LS) crossover in iron in Fp (3), this phenomenon has been investigated extensively experimentally and theoretically (4–14). Most of its properties are affected by the spin crossover. In particular, thermodynamics (14) and thermal elastic properties (15–20) are modified in unusual ways that can change profoundly our understanding of the Earth’s mantle. However, this is a broad and smooth crossover that takes place throughout most of the lower mantle and might not produce obvious signatures in radial velocity or density profiles (20, 21) (see Figs. S1 and S2). Therefore, its effects on aggregates are more elusive and indirect. For instance, the associated density anomaly can invigorate convection, as demonstrated by geodynamics simulations in a homogeneous mantle (22–24). The bulk modulus anomaly may decrease creep activation parameters and lower mantle viscosity (10, 24, 25) promoting mantle homogenization in the spin crossover region (24), and anomalies in elastic coefficients can enhance anisotropy in the lower mantle (16). Less understood are its effects on seismic velocities produced by lateral temperature variations.The present analysis is based on our understanding of thermal elastic anomalies caused by the spin crossover. It has been challenging for both experiments (15–19) and theory (20) to reach a consensus on this topic. Measurements often seemed to include extrinsic effects, making it difficult to confirm the spin crossover signature by different techniques and across laboratories. A theoretical framework had to be developed to address these effects. However, an agreeable interpretation of data and results has emerged recently (20). With increasing pressure, nontrivial behavior is observed in all elastic coefficients, aggregate moduli, and density throughout the spin crossover—the mixed spin (MS) state. In an ideal crystal or aggregate, bulk modulus (K_S), C₁₁, and C₁₂ are considerably reduced in the MS state, whereas shear modulus (G), C₄₄, and density (ρ) are enhanced. The pressure range of these anomalies broadens with increasing temperature whereas the magnitude decreases. With respect to the HS state, all these properties are enhanced in the LS state.     

Regulation of beta-amyloid production in neurons by astrocyte-derived cholesterol

Alzheimer’s disease (AD) is characterized by the presence of amyloid β (Aβ) plaques, tau tangles, inflammation, and loss of cognitive function. Genetic variation in a cholesterol transport protein, apolipoprotein E (apoE), is the most common genetic risk factor for sporadic AD. In vitro evidence suggests that apoE links to Aβ production through nanoscale lipid compartments (lipid clusters), but its regulation in vivo is unclear. Here, we use superresolution imaging in the mouse brain to show that apoE utilizes astrocyte-derived cholesterol to specifically traffic neuronal amyloid precursor protein (APP) in and out of lipid clusters, where it interacts with β- and γ-secretases to generate Aβ-peptide. We find that the targeted deletion of astrocyte cholesterol synthesis robustly reduces amyloid and tau burden in a mouse model of AD. Treatment with cholesterol-free apoE or knockdown of cholesterol synthesis in astrocytes decreases cholesterol levels in cultured neurons and causes APP to traffic out of lipid clusters, where it interacts with α-secretase and gives rise to soluble APP-α (sAPP-α), a neuronal protective product of APP. Changes in cellular cholesterol have no effect on α-, β-, and γ-secretase trafficking, suggesting that the ratio of Aβ to sAPP-α is regulated by the trafficking of the substrate, not the enzymes. We conclude that cholesterol is kept low in neurons, which inhibits Aβ accumulation and enables the astrocyte regulation of Aβ accumulation by cholesterol signaling.

Alzheimer’s disease (AD), the most prevalent neurodegenerative disorder, is characterized by the progressive loss of cognitive function and the accumulation of amyloid β (Aβ) peptide and phosphorylated tau (1). Amyloid plaques are composed of aggregates of Aβ peptide, a small hydrophobic protein excised from the transmembrane domain of amyloid precursor protein (APP) by proteases known as beta- (β-) and gamma- (γ-) secretases (SI Appendix, Fig. S1A). In high concentrations, Aβ peptide can aggregate to form Aβ plaques (2–4). The nonamyloidogenic pathway involves a third enzyme, alpha- (α-) secretase, which generates a soluble APP fragment (sAPP-α), helps set neuronal excitability in healthy individuals (5), and does not contribute to the generation of amyloid plaques. Therefore, by preventing Aβ production, α-secretase–mediated APP cleavage reduces plaque formation. Strikingly, both pathways are finely regulated by cholesterol (6) (SI Appendix, Fig. S1B).In cellular membranes, cholesterol regulates the formation of lipid clusters (also known as lipid rafts) and the affinity of proteins to lipid clusters (7), including β-secretase and γ-secretase (8–10). α-secretase does not reside in lipid clusters; rather, α-secretase is thought to reside in a region made up of disordered polyunsaturated lipids (11). The location of APP is less clear. In detergent-resistant membrane (DRM) studies, it primarily associates with lipid from the disordered region, although not exclusively (8, 10, 12–14). Endocytosis is thought to bring APP in proximity to β-secretase and γ-secretase, and this correlates with Aβ production. Cross-linking of APP with β-secretase on the plasma membrane also increases Aβ production, leading to a hypothesis that lipid clustering in the membrane contributes to APP processing (11, 14, 15) (SI Appendix, Fig. S1A). Testing this hypothesis in vivo has been hampered by the small size and transient nature of lipid clusters (often <100 nm), which is below the resolution of light microscopy.Superresolution imaging has emerged as a complimentary technique to DRMs, with the potential to interrogate cluster affinity more directly in a native cellular environment (16). We recently employed superresolution imaging to establish a membrane-mediated mechanism of general anesthesia (17). In that mechanism, cholesterol causes lipid clusters to sequester an enzyme away from its substrate. Removal of cholesterol then releases and activates the enzyme by giving it access to its substrate (SI Appendix, Fig. S1C) (7, 18). A similar mechanism has been proposed to regulate the exposure of APP to its cutting enzymes (11, 15, 19–21).Neurons are believed to be the major source of Aβ in normal and AD brains (22, 23). In the adult brain, the ability of neurons to produce cholesterol is impaired (24). Instead, astrocytes make cholesterol and transport it to neurons with apolipoprotein E (apoE) (25–27). Interestingly, apoE, specifically the e4 subtype (apoE4), is the strongest genetic risk factor associated with sporadic AD (28, 29). This led to the theory that astrocytes may be controlling Aβ accumulation through regulation of the lipid cluster function (11, 15, 19), but this has not yet been shown in the brain of an animal. Here, we show that astrocyte-derived cholesterol controls Aβ accumulation in vivo and links apoE, Aβ, and plaque formation to a single molecular pathway.     

Structural and functional insights into caseinolytic proteases reveal an unprecedented regulation principle of their catalytic triad

Caseinolytic proteases (ClpPs) are large oligomeric protein complexes that contribute to cell homeostasis as well as virulence regulation in bacteria. Although most organisms possess a single ClpP protein, some organisms encode two or more ClpP isoforms. Here, we elucidated the crystal structures of ClpP1 and ClpP2 from pathogenic Listeria monocytogenes and observe an unprecedented regulation principle by the catalytic triad. Whereas L. monocytogenes (Lm)ClpP2 is both structurally and functionally similar to previously studied tetradecameric ClpP proteins from Escherichia coli and Staphylococcus aureus, heptameric LmClpP1 features an asparagine in its catalytic triad. Mutation of this asparagine to aspartate increased the reactivity of the active site and led to the assembly of a tetradecameric complex. We analyzed the heterooligomeric complex of LmClpP1 and LmClpP2 via coexpression and subsequent labeling studies with natural product-derived probes. Notably, the LmClpP1 peptidase activity is stimulated 75-fold in the complex providing insights into heterooligomerization as a regulatory mechanism. Collectively, our data point toward different preferences for substrates and inhibitors of the two ClpP enzymes and highlight their structural and functional characteristics.The caseinolytic protease P (ClpP) is a highly conserved enzyme present in bacteria and higher organisms (1–3). ClpP is responsible for cell homeostasis and among other duties for the regulation of bacterial virulence in several pathogens including Staphylococcus aureus and Listeria monocytogenes (4, 5). Early structural studies revealed the topology of the Escherichia coli ClpP complex that consists of two heptameric rings building up a 300 kDa cylinder (Fig. 1A) (6). The interior of this proteolytic machinery exhibits 14 active sites flanked by axial pores that allow protein substrates to enter the hydrolytic chamber. ClpP gains its catalytic activity in complex with AAA⁺-chaperones (such as ClpC, ClpE, and ClpX in the case of L. monocytogenes). These ATP-dependent enzymes bind to the axial pores of ClpP, unfold the protein prone to degradation, and direct it into the proteolytic chamber (7–9).Open in a separate windowFig. 1.Main structural elements of ClpP. (A) Top and side view of the tetradecameric ClpP complex from E. coli (10) (EcClpP, PDB ID code 1TYF, surface representation) with one subunit highlighted in dark gray. Each subunit (close-up, ribbon diagram) is made up of seven α-helices (denoted with letters) and 11 β-strands (denoted with numbers) and contains a catalytic triad (highlighted with red circles). Relevant secondary structures (α-helices E and F, β-strand 9) are highlighted in gold. (B) Sequence alignment of EcClpP with LmClpP1 and LmClpP2. The secondary structure elements are depicted for EcClpP. The catalytic triad is framed in red, the residues forming the E-helix are underlined in orange, the conserved proline and the glycins in the Gly-rich loop are colored blue, and the Asp/Arg sensor is shown in green.A close-up view of a single ClpP monomer reveals several characteristic structural features that are conserved among this class of proteases. To harmonize the ClpP nomenclature for all subsequent discussions, we use a general sequence numbering based on the first determined crystal structure of ClpP from E. coli [EcClpP, Protein Data Bank (PDB) ID code 1TYF] (10) (Fig. 1B). According to this nomenclature, a catalytic triad (Ser98, His123, Asp172) essential for proteolysis, a central E-helix with a Gly-rich loop region essential for interring contacts between the two heptamers, and a N-terminal region essential for interaction with a AAA⁺-chaperone can be observed in all published X-ray structures to date (Fig. 1A, Fig. S1B) (10–18). Cocrystallization of E. coli ClpP with an irreversible dipeptide chloromethylketone inhibitor confirmed the reactivity of the catalytic triad residues Ser98 and His123 and illustrate a binding site for the dipeptide within the Gly-rich loop region that adopts an antiparallel beta-strand (19) (Fig. 2). Recently, two conformations of ClpP from S. aureus have been reported that are thought to represent physiologically important states with an active and an inactive catalytic triad corresponding to an extended and a bent E-helix, respectively (Fig. S2) (11, 12). In addition, a highly conserved aspartate/arginine sensor (Asp170/Arg171) links oligomerization to the catalytic activity and exhibits characteristic conformations in both states (Fig. S2) (12). In agreement with this model, ClpP heptamers lack the interaction of the sensor residues with their counterparts on the adjacent ring and thus have an inactive triad. In the tetradacameric state, the senor feedbacks the correct assembly to the active sites, thereby ensuring controlled proteolysis.Open in a separate windowFig. 2.Stereo-representation of ClpP monomers. Structural superposition of LmClpP1 (gold), LmClpP2 (green), SaClpP (PDB ID code 3V5E, pale red), and EcClpP (PDB ID code 2FZS, gray) with covalently bound CMK inhibitor.Although most organisms possess a single ClpP protein with a conserved fold (6, 11, 13–16, 18, 20), the genomes of some organisms encode two or more ClpP isoforms (21–24). For a cyanobacterial system, heptameric rings of mixed composition have been reported that interact with different chaperones (22). In contrast, ClpP proteins from L. monocytogenes (LmClpP1 and LmClpP2) as well as from Mycobacterium tuberculosis have been found to assemble into heterooligomeric complexes composed of two homoheptamers (25, 26). Inhibition of LmClpP2 with lactone-based inhibitors led to down-regulation of virulence without affecting viability (27). In contrast, both mycobacterial ClpP subunits are essential for bacterial survival, emphasizing defined functional roles of ClpP proteins among species (26, 28).Interestingly, LmClpP2 shares a high-sequence homology with ClpP enzymes of various organisms that feature one ClpP (Fig. S1 A and C). LmClpP1 exhibits only 41% sequence identity with LmClpP2, raising the question of how these two distinct isoforms interact and how they differ functionally. Furthermore, there is a distinct difference between the two ClpP homologs in the composition of their catalytic triad: Asp172 of LmClpP2 is replaced by an asparagine in LmClpP1, an unusual observation within serine proteases that is, however, conserved in several uncharacterized homologs (Fig. S1 A and C). Although the replacement of an aspartate with an asparagine represents only a moderate structural alteration, it significantly influences the strength of the catalytic triad charge-relay system. The nucleophilicity of the active site Ser98 in LmClpP1 and LmClpP2 was previously monitored and compared by β-lactone activity-based probes (25, 29). Although all monocyclic β-lactones selectively labeled LmClpP2 either as a homooligomer or as part of the heterooligomeric complex, a probe derived from the bicyclic natural product vibralactone (VLP) was able to interact with both LmClpP1 and LmClpP2 catalytic sites. Importantly, binding of the ligand to LmClpP1 was only observed in the presence of LmClpP2 (25).     

Oxidative regulation of chloroplast enzymes by thioredoxin and thioredoxin-like proteins in Arabidopsis thaliana

Thioredoxin (Trx) is a protein that mediates the reducing power transfer from the photosynthetic electron transport system to target enzymes in chloroplasts and regulates their activities. Redox regulation governed by Trx is a system that is central to the adaptation of various chloroplast functions to the ever-changing light environment. However, the factors involved in the opposite reaction (i.e., the oxidation of various enzymes) have yet to be revealed. Recently, it has been suggested that Trx and Trx-like proteins could oxidize Trx-targeted proteins in vitro. To elucidate the in vivo function of these proteins as oxidation factors, we generated mutant plant lines deficient in Trx or Trx-like proteins and studied how the proteins are involved in oxidative regulation in chloroplasts. We found that f-type Trx and two types of Trx-like proteins, Trx-like 2 and atypical Cys His-rich Trx (ACHT), seemed to serve as oxidation factors for Trx-targeted proteins, such as fructose-1,6-bisphosphatase, Rubisco activase, and the γ-subunit of ATP synthase. In addition, ACHT was found to be involved in regulating nonphotochemical quenching, which is the mechanism underlying the thermal dissipation of excess light energy. Overall, these results indicate that Trx and Trx-like proteins regulate chloroplast functions in concert by controlling the redox state of various photosynthesis-related proteins in vivo.

Plant chloroplasts have evolved multiple strategies with which to adapt photosynthesis to fluctuating light environments. One such strategy involves the redox regulation of various enzymes that function in photosynthesis reactions. Multiple photosynthesis-related proteins, such as the four Calvin–Benson cycle enzymes (glyceraldehyde-3-phosphate dehydrogenase, fructose-1,6-bisphosphatase [FBPase], sedoheptulose-1,7-bisphosphatase [SBPase], and phosphoribulokinase [PRK]), possess redox-active Cys residues (1, 2). In addition, the γ-subunit of ATP synthase (CF₁-γ) and two regulatory proteins associated with Calvin–Benson cycle enzymes, CP12 and ribulose-1,5-bisphosphate carboxylase/oxygenase (Rubisco) activase (RCA), are also redox-regulated (2–4). In the 1970s thioredoxin (Trx) was identified as a reducing power mediator for FBPase and SBPase in chloroplasts (5, 6). In a light-containing environment, reducing power is transferred from the photosynthetic electron transport system to Trx via ferredoxin and ferredoxin-Trx reductase (6). Trx then achieves light-dependent activation of its target enzymes by reducing the disulfide bond on these enzymes.In chloroplasts, NADPH-Trx reductase C (NTRC) works in parallel with the Trx-dependent system as another redox pathway. NTRC is also a redox-responsive protein containing both NADPH-dependent Trx reductase and Trx domains; these enable NTRC to reduce its target proteins using the reducing power of NADPH (7). NTRC can reduce 2-Cys peroxiredoxin (2-Cys Prx) in addition to several Trx-targeted proteins (8–12). 2-Cys Prx utilizes reducing power to reduce reactive oxygen species such as H₂O₂ (13). In chloroplasts, NTRC is thought to be a major electron donor for 2-Cys Prx (14) because the reducing power transfer efficiency from NTRC is extremely high compared with that from typical chloroplast Trx proteins (12). Plants deficient in NTRC show severe phenotypes, such as stunted growth, low chlorophyll content, and very high nonphotochemical quenching (NPQ) (7, 11, 12, 14–17). Thus, it is clear that NTRC plays important physiological roles in chloroplasts.Redox-regulated proteins in the stroma are reduced in the light and then reoxidized in the dark (18, 19). Reoxidation is an important process in plants; for example, we recently showed that the reoxidation of chloroplast NADP-malate dehydrogenase is important for maintaining NADPH homeostasis in chloroplasts, particularly in an environment with fluctuating light (20). Despite the importance of the oxidation process, the proteins involved in target oxidation have yet to be clarified. Recently, Trx-like proteins, such as Trx-like 2 (TrxL2) and atypical Cys His-rich Trx (ACHT), have been suggested as oxidation factors (21–27). These reports were mainly based on the results of in vitro experiments, suggesting that Trx-like proteins transfer the reducing power of Trx-targeted proteins to H₂O₂ via 2-Cys Prx. However, the functions of these proteins in vivo are not known very well. The so-called common Trxs belonging to f-, m-, x-, y- (or z-?) types were also thought to be the candidate of the oxidation factor. Because it is known that, particularly, Trx-f can oxidize its target proteins under certain conditions in vitro (25, 28), we focused this work on Trx-f.Target oxidation by ACHT1 and ACHT2, among five ACHT isoforms in Arabidopsis thaliana (29), has been demonstrated in vitro (25). ACHT1 and ACHT2 are broadly conserved in photosynthetic organisms, including green algae, moss, and seed plants (30). Their amino acid sequences and biochemical properties are similar (SI Appendix, Fig. S1A) (25, 29). In addition, ACHT1 and ACHT2 (designated also as Lilium5 and Lilium2, respectively) are predicted to originate from the same ancestral gene (31). Comparison of the expression patterns of ACHT1 and ACHT2 in the database shows that ACHT2 is expressed more than ACHT1, especially in leaves (SI Appendix, Fig. S1B) (32), suggesting that ACHT2 may play a dominant role in A. thaliana leaves.Oxidation of target proteins by the TrxL2 isoforms from A. thaliana, namely TrxL2.1 and TrxL2.2, has been demonstrated in vitro (22). TrxL2 genes are also conserved in photosynthetic organisms, such as seed plants, moss, and some green algae, but not in Chlamydomonas reinhardtii (30). Although the amino acid sequences and biochemical properties of TrxL2.1 and TrxL2.2 are similar (SI Appendix, Fig. S2A) (22), their expression patterns are different, and TrxL2.1 is reported to be more expressed than TrxL2.2, particularly in leaves (SI Appendix, Fig. S2B) (32). In addition, TrxL2.1 expression seems to be regulated by the circadian rhythm and the rhythm of temperature change (SI Appendix, Fig. S2C). The expression of TrxL2.1 is more strongly induced before and during light-to-dark transitions than TrxL2.2, suggesting that TrxL2.1 plays a predominant role during these periods.In the present study, we generated A. thaliana mutant plant lines deficient in Trx-f1 and Trx-f2, TrxL2.1, or ACHT1 and ACHT2, whose target oxidation activities are well studied in vitro, and used these plants to investigate redox state changes in chloroplasts. We found that Trx-f, TrxL2.1, ACHT1, and ACHT2 are involved in the oxidation of FBPase, CF₁-γ, and RCA. ACHT2 also seemed to be involved in the regulation of NPQ. Furthermore, the knockout of Trx-like proteins suppressed the impact of NTRC deficiency in plants, suggesting that a connection existed between the NTRC system and Trx-like protein-involving system.     

Structural basis for isoform-specific inhibition of human CTPS1

Cytidine triphosphate synthase 1 (CTPS1) is necessary for an effective immune response, as revealed by severe immunodeficiency in CTPS1-deficient individuals [E. Martin et al.], [Nature] [510], [288–292] ([2014]). CTPS1 expression is up-regulated in activated lymphocytes to expand CTP pools [E. Martin et al.], [Nature] [510], [288–292] ([2014]), satisfying increased demand for nucleic acid and lipid synthesis [L. D. Fairbanks, M. Bofill, K. Ruckemann, H. A. Simmonds], [J. Biol. Chem. ] [270], [29682–29689] ([1995]). Demand for CTP in other tissues is met by the CTPS2 isoform and nucleoside salvage pathways [E. Martin et al.], [Nature] [510], [288–292] ([2014]). Selective inhibition of the proliferative CTPS1 isoform is therefore desirable in the treatment of immune disorders and lymphocyte cancers, but little is known about differences in regulation of the isoforms or mechanisms of known inhibitors. We show that CTP regulates both isoforms by binding in two sites that clash with substrates. CTPS1 is less sensitive to CTP feedback inhibition, consistent with its role in increasing CTP levels in proliferation. We also characterize recently reported small-molecule inhibitors, both CTPS1 selective and nonselective. Cryo-electron microscopy (cryo-EM) structures reveal these inhibitors mimic CTP binding in one inhibitory site, where a single amino acid substitution explains selectivity for CTPS1. The inhibitors bind to CTPS assembled into large-scale filaments, which for CTPS1 normally represents a hyperactive form of the enzyme [E. M. Lynch et al.], [Nat. Struct. Mol. Biol.] [24], [507–514] ([2017]). This highlights the utility of cryo-EM in drug discovery, particularly for cases in which targets form large multimeric assemblies not amenable to structure determination by other techniques. Both inhibitors also inhibit the proliferation of human primary T cells. The mechanisms of selective inhibition of CTPS1 lay the foundation for the design of immunosuppressive therapies.

CTP synthase (CTPS) is a critical regulatory enzyme in nucleotide metabolism, catalyzing the rate-limiting step in de novo CTP synthesis. The two human CTPS isoforms, CTPS1 and CTPS2, share 75% sequence identity but have distinct physiological roles. While CTPS2 is uniformly expressed across various tissue types, CTPS1 expression is generally low but is up-regulated in activated T cells (1). Individuals deficient in CTPS1—owing to a deleterious homozygous mutation—are severely immunocompromised (1, 2). These individuals have T cells that fail to proliferate upon activation but lack other major clinical consequences, with demand for CTP in resting T cells and other tissues likely maintained by CTPS2 and the nucleoside salvage pathway (1). The proliferation of T cells from CTPS1-deficient individuals can be rescued by the addition of exogenous CTP (1). CTPS1 thus plays an essential role in expanding CTP pools in proliferating lymphocytes, where additional CTP is likely required to meet an increased demand for DNA, RNA, and membrane lipid biosynthesis (3). Selective inhibition of CTPS1 is therefore an attractive target for immunosuppressive therapies as well as the treatment of lymphocyte cancers, with potentially limited off-target effects. Existing CTPS inhibitors exhibit substantial toxicity (4, 5), and whether they have selectivity for CTPS isoforms is unknown.CTPS is a homotetramer, with each monomer comprising a glutaminase domain and an amidoligase domain connected by an α-helical linker (6) (SI Appendix, Fig. S2A). The glutaminase domain hydrolyzes glutamine to produce ammonia, which is transferred to the amidoligase domain, where it is ligated to UTP to form CTP in an ATP-dependent process (SI Appendix, Fig. S2A). CTPS experiences feedback inhibition by CTP, which binds a site overlapping the UTP binding site and is allosterically regulated by GTP (7, 8) (SI Appendix, Fig. S2A). CTPS thus has the capacity to integrate information about the levels of all four major ribonucleotides. Substrate and product binding control a conserved conformational cycle in CTPS; the tetramer interface adopts a compressed or extended conformation in order to accommodate CTP or UTP binding, respectively (9, 10) (SI Appendix, Fig. S2 B and C). Furthermore, upon substrate binding, the glutaminase domain rotates relative to the amidoligase domain (SI Appendix, Fig. S2 D and E), opening a tunnel that likely facilitates ammonia transfer between the two active sites (6, 9, 10, 11). Polymerization into filaments adds another layer to CTPS regulation, which varies among species and between the human isoforms (9, 10, 12, 13). Escherichia coli CTPS polymerizes into inactive filaments in the presence of CTP (12). Both human isoforms assemble filaments of stacked tetramers through conserved intertetramer interactions but with different functional consequences: CTPS1 polymerizes into filaments with increased activity upon substrate binding (9), whereas CTPS2 filaments dynamically switch between substrate- and product-bound conformations to produce highly cooperative regulation (10). CTPS filaments are observed under conditions of cellular stress, at particular stages of development, and in cancer cells, suggesting they are involved in adapting to changes in metabolic requirements (14–18).The biochemical basis for the different physiological roles of CTPS1 and CTPS2 remains unclear. Here, we investigate the differential regulation of CTPS1 and CTPS2 by CTP and find that CTPS1 is active at higher CTP concentrations, consistent with its critical role in expanding nucleotide pools in proliferating cells. We also identify a second inhibitory CTP binding site that overlaps the CTPS ATP binding site. Furthermore, we show that a family of recently described small-molecule CTPS inhibitors binds in a site adjacent to the second CTP site and selectively targets CTPS1 through a mechanism dependent on a single amino acid substitution.     

From the Cover: Late Pleistocene shrub expansion preceded megafauna turnover and extinctions in eastern Beringia

The collapse of the steppe-tundra biome (mammoth steppe) at the end of the Pleistocene is used as an important example of top-down ecosystem cascades, where human hunting of keystone species led to profound changes in vegetation across high latitudes in the Northern Hemisphere. Alternatively, it is argued that this biome transformation occurred through a bottom-up process, where climate-driven expansion of shrub tundra (Betula, Salix spp.) replaced the steppe-tundra vegetation that grazing megafauna taxa relied on. In eastern Beringia, these differing hypotheses remain largely untested, in part because the precise timing and spatial pattern of Late Pleistocene shrub expansion remains poorly resolved. This uncertainty is caused by chronological ambiguity in many lake sediment records, which typically rely on radiocarbon (¹⁴C) dates from bulk sediment or aquatic macrofossils—materials that are known to overestimate the age of sediment layers. Here, we reexamine Late Pleistocene pollen records for which ¹⁴C dating of terrestrial macrofossils is available and augment these data with ¹⁴C dates from arctic ground-squirrel middens and plant macrofossils. Comparing these paleovegetation data with a database of published ¹⁴C dates from megafauna remains, we find the postglacial expansion of shrub tundra preceded the regional extinctions of horse (Equus spp.) and mammoth (Mammuthus primigenius) and began during a period when the frequency of ¹⁴C dates indicates large grazers were abundant. These results are not consistent with a model of top-down ecosystem cascades and support the hypothesis that climate-driven habitat loss preceded and contributed to turnover in mammal communities.

In northern high latitudes, the widespread extinction of Quaternary megafauna (animals weighing >44 kg) and disappearance of the steppe-tundra biome they inhabited is used as an important example of top-down ecosystem cascades, where human hunting of keystone species led to profound changes in vegetation structure at the end of the Pleistocene (15 thousand years before 1950 [15 ka] to 11.7 ka) (1–5). This hypothesis, however, is not well tested, and it is unclear whether the relative timing of megafauna extinctions and vegetation change is consistent with a top-down model. Resolving this question is an important part of understanding how past ecosystems functioned and may help predict how modern high-latitude ecosystems will respond to climate-driven vegetation change, current declines in large mammal species, or their deliberate reintroduction.In eastern Beringia (modern-day Alaska and the Yukon interior) (Fig. 1), Late Pleistocene megafauna extinctions broadly coincided with an expansion of shrub tundra vegetation including dwarf and tall-shrub species of birch (Betula nana and Betula glandulosa) and willow (Salix spp.) (6). Prior to these events, herds of grazing megafauna occupied a biome termed the mammoth steppe (7–9) or steppe-tundra (10, 11), which has no widespread modern analog. This novel, dry environment supported diverse plant communities, dominated by grasses, sedges, Artemisia spp., and a range of other forbs (8, 12–16). Sometime between 16 ka and 13 ka, woody shrub species began to expand across eastern Beringia, coupled with the development of peatlands and organic soil horizons (14, 17, 18). Lake sediment records show that the expansion of shrubs was rapid in many cases, and, although pollen influx data suggest herbaceous plant taxa continued to form an important part of the vegetation community, the abundance of Betula and Salix pollen (often >50% of the pollen sum) indicates that eastern Beringia became increasingly dominated by woody vegetation during this period (19–22).Open in a separate windowFig. 1.Eastern Beringia during the Late Pleistocene. Ice limits (14.2 and 15.5 ka) are redrawn from Dalton et al. (80). Lake sediment records reanalyzed in this study are numbered and include the following: 1, Burial Lake (81); 2, Tukuto Lake (82); 3, Lake of the Pleistocene (18); 4, Okpilak Lake (44); 5, Trout Lake (55); 6, Hanging Lake (54); 7, Ruppert Lake (83); 8, Xindi Lake (84); 9, Harding Lake (45); 10, Birch Lake (19); 11, Lost Lake (21); 12, Jan Lake (47); 13, Idavain Lake (20); 14, Beaver Lake (46); and 15, Discovery Pond (85).During the same time period, mammal communities in eastern Beringia underwent some of the most profound changes to occur in the region since at least the end of the last interglacial (Marine Isotope Stage 5e), 115 ka. Of the 13 megafauna taxa present in eastern Beringia immediately prior to 15 ka, only seven survived in situ beyond the Pleistocene (steppe bison, Bison priscus; caribou, Rangifer tarandus; wapiti, Cervus canadensis; muskox, Ovibos moschatus; wolf, Canis lupus; grizzly bear, Ursus arctos; and sheep, Ovis). The remaining taxa (caballine/stout-legged horses, Equus; stilt-legged horses, Haringtonhippus; woolly mammoth, Mammuthus primigenius; saiga antelope, Saiga tatarica; lion, Panthera spelaea; and short-faced bear, Arctodus simus), along with smaller mammals such as the arctic ground squirrel (Urocitellus parryii), became regionally extinct throughout large areas between 15.0 ka and 11.7 ka, leaving behind a comparatively impoverished mammal community (6, 23). The arrival of moose (Alces alces), an obligate browser, in eastern Beringia shortly after 15 ka (24) marks the beginning of a shift from the grazer community of the steppe-tundra toward a community of mixed-feeding megafauna species better adapted to a shrub tundra environment.The broad chronological overlap between the timing of shrub expansion and turnover in mammal populations has led numerous authors to hypothesize that habitat loss was a key driver of Late Pleistocene extinctions in eastern Beringia (8, 25–27). These authors argue that the Betula- and Salix-dominated shrub tundra was inhospitable to grazing megafauna because low-growing shrubs develop strong antiherbivory compounds, making them inedible or toxic to many mammals that lack a rumen to aid digestion (28). Other researchers have suggested that the decline in populations of grazing megafauna preceded shrub expansion, and that the spread of shrub tundra was caused by the resulting reduction in browsing pressure, vegetation trampling, and snow clearance (2, 29). These studies argue that grazers, and particularly megaherbivores (mammals of >1,000 kg), such as mammoth, acted as keystone species and were essential to the continuation of the steppe-tundra (1). In this case, human-caused “overkill” (30) or the compounded impacts of humans (e.g., burning, hunting, or simply their presence) in a dynamic ecosystem are advanced as the causes of megafauna extinctions. Finally, it is also possible that both of these processes reinforced one another, and the disappearance of the steppe-tundra was caused by both bottom-up and top-down pressures, or even that there was no causal relationship between the megafauna declines and shrub expansion. All of these hypotheses remain largely untested and continue to be controversial, in part because human arrival patterns, hunting preferences, and population size are largely unknown (31).In eastern Beringia, it is difficult to distinguish between these alternative hypotheses because the regional timing and spatial pattern of Late Pleistocene shrub expansion is poorly resolved, despite more than 50 y of detailed paleoecological study (14, 32–35). This uncertainty is principally due to the difficulty in accurately dating lake sediments from high latitudes (36–38). Terrestrial plant macrofossil remains are often rare in these depositional environments, and many pioneering paleoenvironmental studies are founded on chronologies based on radiocarbon (¹⁴C) dates derived from bulk sediment or aquatic macrofossils. This is particularly common for lake records obtained before the routine availability of accelerator mass spectrometer radiocarbon (AMS ¹⁴C) dating, when larger samples were required. Radiocarbon dates from bulk sediment or aquatic macrofossils are often imprecise or contaminated by old carbon (SI Appendix, Text), and, as a result, chronologies developed in this way are unreliable.To assess the chronology of shrub expansion and megafauna community turnover in eastern Beringia, we reanalyzed 15 lake sediment records for which AMS ¹⁴C dating of terrestrial macrofossils is available (SI Appendix, Figs. S1 and S6–S9). We developed Bayesian age–depth models for each study site, and compared the results with a new database of published ¹⁴C dates from plant macrofossils, megafauna remains, and arctic ground squirrel middens (Materials and Methods and SI Appendix, Text). In each pollen record, we define the beginning of shrub tundra expansion as the first sustained increase (replicated in three or more consecutive pollen samples) in Betula pollen above pre-15-ka background values, which are typically <5% of the pollen sum (SI Appendix, Fig. S2 and Text). In most cases, this expansion represents an increase to >20% of the pollen sum, and, where they are available, we use pollen influx data to support this timing (SI Appendix, Fig. S3). In some records, Salix pollen increases in abundance before Betula by as much as 1,200 y, and, in these cases, we consider the taxa separately (Fig. 2 and SI Appendix, Figs. S2 and S3). We define the timing of Salix expansion as the first sustained increase in Salix pollen above background values (see above). In most cases, this expansion represents an increase to >15% of the pollen sum. This approach is conservative. It provides minimum ages for the beginning of shrub expansion, as the true increase in shrub pollen above these thresholds is likely to lie between sampling points (i.e., would have an older assigned age). In records with high-resolution sampling [e.g., Birch Lake (19)], this difference is small; however, in most records, sampling resolution is ≤1 pollen spectrum every 10 cm, which may represent >500 y of sediment accumulation (SI Appendix, Table S1). With this approach, we aim to establish whether shrub expansion began prior to turnover in megafauna communities, as predicted by Guthrie (6, 8), or after populations of keystone species collapsed, as suggested by Zimov et al. (2, 29). As these hypotheses predict events in the opposite order, it allows us to assess whether the Late Pleistocene extinction of grazing megafauna species was a response to, or the cause of, steppe-tundra decline.Open in a separate windowFig. 2.(A) North Greenland ice core project (NGRIP) δ¹⁸O record (86). (B) Modeled, calibrated age ranges (shown as probability density functions) for the beginning of Salix (shown in blue when clearly defined) and Betula (shown in gray) expansion from lake sediment records reanalyzed in this study. The medians of calibrated modeled dates are indicated by black crosses. (C) The median of calibrated ¹⁴C age ranges from shrub macrofossils in eastern Beringia. (D) Kernel Density Estimation modeled distributions (mean and 1σ uncertainty) for calibrated ¹⁴C dates from moose in eastern Beringia (sum probability distributions shown in SI Appendix, Fig. S3). (E) Kernel Density Estimation modeled distributions (mean and 1σ uncertainty) for calibrated ¹⁴C dates from horse, bison, and mammoth in eastern Beringia (sum probability distributions shown in SI Appendix, Fig. S3). (F) The median of calibrated ¹⁴C age ranges from arctic ground squirrel middens in eastern Beringia. (G) Periods of human occupation at archaeological sites in the Tanana River Valley, Alaska (70).     

From the Cover: Sea surface height evidence for long-term warming effects of tropical cyclones on the ocean

Tropical cyclones have been hypothesized to influence climate by pumping heat into the ocean, but a direct measure of this warming effect is still lacking. We quantified cyclone-induced ocean warming by directly monitoring the thermal expansion of water in the wake of cyclones, using satellite-based sea surface height data that provide a unique way of tracking the changes in ocean heat content on seasonal and longer timescales. We find that the long-term effect of cyclones is to warm the ocean at a rate of 0.32 ± 0.15 PW between 1993 and 2009, i.e., ∼23 times more efficiently per unit area than the background equatorial warming, making cyclones potentially important modulators of the climate by affecting heat transport in the ocean–atmosphere system. Furthermore, our analysis reveals that the rate of warming increases with cyclone intensity. This, together with a predicted shift in the distribution of cyclones toward higher intensities as climate warms, suggests the ocean will get even warmer, possibly leading to a positive feedback.Strong winds associated with tropical cyclones (TCs) increase air–sea heat fluxes, favoring the intensification of storms, and generate vigorous vertical mixing in the upper ocean, stirring warm surface waters with colder waters below (1–6). The wake produced by the passage of TCs is thus characterized by a surface cold anomaly and a subsurface warm anomaly (1–3, 6, 7). After the TC passage, the sea surface cold anomaly dissipates quickly (8–10), due in part to anomalous air–sea heat fluxes (9, 11), whereas the subsurface warm anomaly is believed to persist over a much longer period (12). This has led to the suggestion that the net long-term effect of TCs is to pump heat into the ocean (13–16). Such a flux of heat into the low-latitude ocean has been proposed to be an important modulator of local and remote climate (12, 17–22).During the past decade or so, several studies have been devoted to estimating the magnitude of this heating effect, using sea surface temperature (SST) data (13–16). However, owing to a lack of subsurface temperature observations, these studies relied upon many assumptions that led to large and poorly quantified uncertainties (SI Appendix, SI Results). Furthermore, it is currently highly debated how much (if any) of the estimated warming survives beyond winter season when the deepening of the mixed layer cools the upper ocean. To avoid the ideological and methodological challenges inherent in the previous work, we take a more straightforward approach that was first proposed by Emanuel (13, 23) and quantify the TC-induced warming effect on the ocean by estimating the thermal expansion of water in the wake of Northern Hemisphere TCs, using satellite-derived sea surface height (SSH) data (24) together with tropical cyclone best-track data (25, 26). Combining these two datasets allows us to track the SSH anomalies (SSHAs) around the TC-generated wake beyond the winter season and thus provides a clear picture of the temporal evolution of the TC-induced changes in the ocean heat content. Details on the data and methods are given in SI Appendix, SI Data and Methods.     

Tooth wear and dentoalveolar remodeling are key factors of morphological variation in the Dmanisi mandibles

The Plio-Pleistocene hominin sample from Dmanisi (Georgia), dated to 1.77 million years ago, is unique in offering detailed insights into patterns of morphological variation within a paleodeme of early Homo. Cranial and dentoalveolar morphologies exhibit a high degree of diversity, but the causes of variation are still relatively unexplored. Here we show that wear-related dentoalveolar remodeling is one of the principal mechanisms causing mandibular shape variation in fossil Homo and in modern human hunter–gatherer populations. We identify a consistent pattern of mandibular morphological alteration, suggesting that dental wear and compensatory remodeling mechanisms remained fairly constant throughout the evolution of the genus Homo. With increasing occlusal and interproximal tooth wear, the teeth continue to erupt, the posterior dentition tends to drift in a mesial direction, and the front teeth become more upright. The resulting changes in dentognathic size and shape are substantial and need to be taken into account in comparative taxonomic analyses of isolated hominin mandibles. Our data further show that excessive tooth wear eventually leads to a breakdown of the normal remodeling mechanisms, resulting in dentognathic pathologies, tooth loss, and loss of masticatory function. Complete breakdown of dentognathic homeostasis, however, is unlikely to have limited the life span of early Homo because this effect was likely mediated by the preparation of soft foods.Although patterns of dental micro- and macrowear and wear-related pathologies are amply documented in the hominin fossil record (1–5), processes of in vivo dentoalveolar remodeling (3, 6, 7) and their potential influence on dentognathic morphology are only beginning to be studied in fossil hominins (8). In modern human hunter–gatherer populations, remodeling of dentoalveolar hard tissue is triggered mainly by dental wear, aging, pathologies, and trauma. Wear-related remodeling can be understood as a mechanism of in vivo modification that maintains masticatory function (3, 7, 9–14). Three main processes are typically identified (Fig. 1):

• i)Wear-induced reduction of dental crown height leads to alterations in masticatory biomechanics. This triggers alveolar bone remodeling, yielding dislocation of dental structures and eventual continuous eruption of all teeth. As an effect, occlusal contact between upper and lower teeth is maintained (15–17), and the position and orientation of the occlusal plane relative to the temporomandibular joints (TMJs) is held approximately constant, thus preventing the “wear-out” (18) of the TMJs.
• ii)The reduction of mesiodistal crown dimensions through interproximal dental wear triggers alveolar bone remodeling in the mesiodistal direction. This leads to mesial drift of the postcanine dentition and shortening of the dental arcade (19).
• iii)In the anterior dentition, remodeling induced by interproximal wear results in increased lingual tipping; that is, teeth become more upright relative to the alveolar plane (7).

As an effect of mesial drift, interproximal contacts between adjacent postcanine teeth are preserved. Similarly, as an effect of lingual tipping, interproximal contacts between incisors are preserved. During an individual’s lifetime, the combined, accumulated effects of continuous eruption, mesial drift, and lingual tipping tend to result in an edge-to-edge bite in the front dentition (7) and in significant changes in mandibular morphology (13, 20).Open in a separate windowFig. 1.Mechanisms of in vivo dentoalveolar remodeling. Continuous eruption (CE) is tracked by the distance between the mandibular canal and root apices. Mesial drift (MD) is tracked by the length of the posterior dental arcade from M2 to P3. Lingual tipping (LT) is tracked by the angle of inclination of the anterior teeth (incisors and canines) relative to the mandibular canal.The site of Dmanisi, Georgia, has yielded a crucial sample of early Pleistocene hominin fossils along with a rich vertebrate fauna and mode I (Oldowan) lithic implements (21, 22). Site occupation began shortly after 1.85 Ma (million years ago) (23); the fossils are dated to 1.77 Ma (21, 23–26). The Dmanisi hominin sample comprises five individuals that document dentognathic development from adolescence to old age, thus providing a unique opportunity to study wear-related dentognathic variation in a sample that comes from a single point in space and geological time (26–29). Various hypotheses have been proposed to explain the high degree of variation seen in the Dmanisi mandibles, ranging from intrataxon sexual dimorphism to intertaxon variation (25, 27–31). Here we focus on in vivo dentognathic remodeling as a potential mechanism contributing to the remarkable dentognathic variation in Dmanisi and differentiate normal remodeling processes from pathologic alterations. Using direct observations and data derived from computed tomography (CT) and scanning electron microscopy (SEM), we quantify dental wear (DW), continuous eruption (CE), mesial drift (MD), and lingual tipping (LT) in the following groups: the Dmanisi mandibles [specimens D2735, D211, D2600, D3900 (Fig. 2 and Fig. S1) and KNM-WT 15000 (grouped as early Pleistocene Homo)]; the middle Pleistocene mandibles from Tighenif (n = 3) and Atapuerca Sima de los Huesos (SH) (n = 4); and mandibles of modern hunter–gatherer populations from Australia (n = 26) and Greenland (n = 15) (Table S1), which all show substantial intragroup variation in dental wear. Measurement protocols are specified in Materials and Methods and in Table S2; abbreviations are listed in Table S3. It is well known that dental wear rates (amount of wear per year of life) vary substantially between populations as an effect of differences in food properties (e.g., abrasiveness) and paramasticatory tooth use (32, 33). To permit comparisons between different populations, remodeling rates are thus calculated per wear stage.Open in a separate windowFig. 2.Dmanisi mandibles. Right lateral and occlusal views are photographs taken from original specimens; left lateral views are CT-based 3D reconstructions highlighting internal structures. The canines and incisors of D2735 were found in isolation and digitally reinserted into their sockets. Arrow indicates toothpick lesion.     

C1q binding to surface-bound IgG is stabilized by C1r2s2 proteases

Complement is an important effector mechanism for antibody-mediated clearance of infections and tumor cells. Upon binding to target cells, the antibody’s constant (Fc) domain recruits complement component C1 to initiate a proteolytic cascade that generates lytic pores and stimulates phagocytosis. The C1 complex (C1qr₂s₂) consists of the large recognition protein C1q and a heterotetramer of proteases C1r and C1s (C1r₂s₂). While interactions between C1 and IgG-Fc are believed to be mediated by the globular heads of C1q, we here find that C1r₂s₂ proteases affect the capacity of C1q to form an avid complex with surface-bound IgG molecules (on various 2,4-dinitrophenol [DNP]-coated surfaces and pathogenic Staphylococcus aureus). The extent to which C1r₂s₂ contributes to C1q–IgG stability strongly differs between human IgG subclasses. Using antibody engineering of monoclonal IgG, we reveal that hexamer-enhancing mutations improve C1q–IgG stability, both in the absence and presence of C1r₂s₂. In addition, hexamer-enhanced IgGs targeting S. aureus mediate improved complement-dependent phagocytosis by human neutrophils. Altogether, these molecular insights into complement binding to surface-bound IgGs could be important for optimal design of antibody therapies.

Antibodies are important mediators of the human complement response, which offers critical protection against microbial infections and damaged host cells (1). In order to initiate a complement response, an antibody molecule first needs to bind antigens on the target cell via its antigen-binding (Fab) domains (2–5). Subsequently, the antibody’s constant (Fc) domain recruits the first complement protein complex, C1, to the cell surface (SI Appendix, Fig. S1A). The large C1 complex (also denoted as C1qr₂s₂, 766 kDa) consists of the recognition protein C1q (410 kDa) and a heterotetramer of serine proteases C1r and C1s (denoted C1r₂s₂, 356 kDa) (SI Appendix, Fig. S1B). While C1q is responsible for antibody recognition, its attached proteases C1r₂s₂ induce the activation of downstream enzymatic complexes (i.e., C3 convertases [C4b2b (6)]) that catalyze the covalent deposition of C3-derived molecules (e.g., C3b and its degradation product iC3b) onto the target cell surface (SI Appendix, Fig. S1A) (7, 8). C3b opsonizes the target cell surface and can induce formation of lytic pores (membrane attack complex [MAC]) in the target cell membrane (9–11). In contrast to human cells and gram-negative bacteria, gram-positive bacteria are not susceptible to the MAC due to their thick cell wall (12). On these bacteria, efficient decoration with C3b and iC3b is essential for triggering effective phagocytic uptake of target cells via complement receptors (CR) expressed on phagocytes of which the integrin CR3 (also denoted CD11b/CD18) is considered most important (13, 14).In recent years, our insights into IgG-dependent complement activation have increased significantly. A combination of structural, biophysical, and functional studies revealed that surface-bound IgG molecules (after Fab-mediated antigen binding) require organization into higher-ordered structures, namely hexamers, to induce complement activation most effectively (15–19). Hexamerized IgGs are being held together by noncovalent Fc–Fc interactions and form an optimal platform for C1q docking (SI Appendix, Fig. S1A). C1q has a “bunch of tulips–” like structure, consisting of six collagen arms that each end in a globular (gC1q) domain (SI Appendix, Fig. S1B) that binds the Fc region of an IgG. As the affinity of C1q for a single IgG is very weak (20, 21), avidity achieved through simultaneous binding of its globular domains to six oligomerized IgG molecules is paramount for a strong response (15, 17–19). Furthermore, it was found that IgG hexamerization could be manipulated by specific point mutations in the Fc–Fc contact region that enhance such oligomerization (15, 18, 22). While these hexamer-enhancing mutations in IgG potentiate the efficacy of MAC-dependent cytotoxicity on tumor cells and gram-negative bacteria (15, 23), their effect on complement-dependent phagocytosis is not known.Because complement is an important effector mechanism to kill bacteria and tumor cells, development of complement-enhancing antibodies represents an attractive strategy for immune therapies (1, 24). Immunotherapy based on human monoclonal antibodies is not yet available for bacterial infections (25–28). Such developments are mainly hampered by the fact that little is known about the basic mechanisms of complement activation on bacterial cells. For instance, we do not understand why certain antibodies induce complement activation on bacteria and others do not. In this study, we set out to investigate how antibacterial IgGs induce an effective complement response. By surprise, we noticed that C1q–IgG stability differs between human IgG subclasses. More detailed molecular investigations revealed that C1r₂s₂ proteases are important for generating stable C1q–IgG complexes on various target surfaces. Furthermore, we demonstrate that C1q–IgG stability is influenced by antibody oligomerization. These molecular insights into C1q binding to surface-bound IgGs may pave the way for optimal design of antibody therapies.     

Selective treatment and monitoring of disseminated cancer micrometastases in vivo using dual-function,activatable immunoconjugates

Drug-resistant micrometastases that escape standard therapies often go undetected until the emergence of lethal recurrent disease. Here, we show that it is possible to treat microscopic tumors selectively using an activatable immunoconjugate. The immunoconjugate is composed of self-quenching, near-infrared chromophores loaded onto a cancer cell-targeting antibody. Chromophore phototoxicity and fluorescence are activated by lysosomal proteolysis, and light, after cancer cell internalization, enabling tumor-confined photocytotoxicity and resolution of individual micrometastases. This unique approach not only introduces a therapeutic strategy to help destroy residual drug-resistant cells but also provides a sensitive imaging method to monitor micrometastatic disease in common sites of recurrence. Using fluorescence microendoscopy to monitor immunoconjugate activation and micrometastatic disease, we demonstrate these concepts of “tumor-targeted, activatable photoimmunotherapy” in a mouse model of peritoneal carcinomatosis. By introducing targeted activation to enhance tumor selectively in complex anatomical sites, this study offers prospects for catching early recurrent micrometastases and for treating occult disease.Metastatic disease remains the main cause of cancer-related death despite advances in cytoreductive surgery and chemotherapy (1–4). An ongoing dilemma is the lack of options to address residual micrometastases that escape standard treatments and detection by current imaging technologies (3). In addition to spread via hematogenous and lymphatic routes (5), diffuse micrometastatic spread throughout anatomical cavities is also problematic, including peritoneal dissemination resulting from cancers of the colon (6), pancreas (7), and ovary (1, 2, 4). These obstacles are pronounced in the treatment of epithelial ovarian cancer (EOC), a prime example of a frequently recurrent disease characterized by residual micrometastases. Due to the lack of screening methods or distinct symptoms during early progression, the vast majority of EOC cases are diagnosed once the disease has metastasized and formed numerous nodules studding the peritoneal cavity (1, 2, 4). Although a significant fraction of patients (∼35%) appear to achieve a complete response after cytoreductive surgery and follow-up chemotherapy, a small number of cells with intrinsic or acquired resistance are responsible for recurrence and poor survival (1, 2, 4, 8). These residual micrometastases are clinically occult until gross recurrence, which is often refractory to standard treatments (1, 2, 4). Laparotomy, an invasive surgical reassessment, frequently fails to detect residual disease (9) while noninvasive clinical imaging modalities also have poor sensitivity for subcentimeter tumors (10, 11).To address the challenges associated with treating and detecting occult, residual, and drug-resistant micrometastases before gross recurrence, it is necessary to develop (i) targeted treatments with high tumor selectivity and distinct mechanisms of cell death (12–14) to overcome dose-limiting toxicities and chemoresistance; and (ii) high-resolution approaches with sufficient contrast to monitor microscopic disease. Here, we address both of these needs by developing an activatable construct targeted to markers overexpressed by cancer cells with dual functionality for both therapy and imaging, and integrate this into a quantitative fluorescence microendoscopy platform for longitudinal monitoring of micrometastases. This approach realizes treatment selectivity and imaging fidelity at the microscale.Targeted agents carrying “always-on,” unquenched chromophores have emerged for targeted therapy and imaging at the macroscale. In a promising clinical study, intraoperative visualization of EOC nodules labeled with a targeted, always-on fluorescent probe facilitated the identification of more tumor deposits by surgeons compared with conventional bright-field illumination (15). This development may ultimately translate to fluorescence-guided resection for more radical cytoreductive surgery, leaving less disease behind (15–17). Photoimmunotherapy (PIT) using always-on immunoconjugates is a targeted form of photodynamic therapy—first reported in the seminal works of Levy and colleagues (18)—that has been shown to hold promise by us (19–23) and by others (18, 24, 25). Because photodynamic agents are mechanistically distinct from traditional treatment modalities (13, 14), are effective against radioresistant and chemoresistant cells (19, 20, 26), and can also resensitize resistant cells to chemotherapy (20, 23), the development of PIT is of importance for overcoming drug resistance. In fact, photodynamic therapy has been used in the treatment of disseminated peritoneal disease with some success intraoperatively (27) and endoscopically in the lung, bladder, and esophagus (SI Text, Note S1).Integrating the concepts of targeted therapy and imaging, a recent proof-of-concept study performed dual epidermal growth factor receptor (EGFR)-targeted PIT and imaging of localized, macroscopic tumors using always-on immunoconjugates (25). This study used a mouse model derived from s.c. implantation of A431 squamous-cell carcinoma cells that express abnormally high levels of EGFR (25). A limitation of PIT is persistent phototoxicity and background signal in nontarget tissues due to unbound and circulating always-on immunoconjugates, which compromise treatment and imaging selectivity at the microscale. It therefore remains uncertain whether PIT is safe and effective for treatment of micrometastases—the ultimate test of treatment selectivity. It is also unknown whether always-on immunoconjugates have sufficient tumor selectivity for treatment and imaging of tumors that express more realistic levels of the target molecule. Given these limitations, we sought to develop a more selective type of PIT—termed tumor-targeted, activatable PIT (taPIT)—and tumor imaging based on dual-function immunoconjugates that enable activatable, near-infrared (NIR)-mediated PIT as well as activatable fluorescence imaging (Fig. 1). This approach—building on the concept of lysosome-activated imaging probes suggested by Achilefu, Urano, Kobayashi, and coworkers (28, 29)—not only achieves greater treatment selectivity than always-on PIT but also enables resolution of microscopic tumor deposits.Open in a separate windowFig. 1.Concepts of tumor-targeted, activatable photoimmunotherapy (taPIT) and longitudinal monitoring of micrometastases in vivo. (A) Cet-BPD—a dual-function, activatable immunoconjugate for both taPIT and monitoring of micrometastases—consists of multiple BPD molecules conjugated to each cetuximab molecule. The BPD molecules remain self-quenched until EGFR binding and cellular internalization. (B) Schematic of Cet-BPD intracellular activation. (C) taPIT enables tumor-confined phototoxicity, whereas always-on agents and immunoconjugates result in nonspecific damage to normal tissues. (D) Mouse model of micrometastatic epithelial ovarian cancer (EOC) and fluorescence microendoscopy schematics. (E) (Left) In vivo fluorescence microendoscopy of control no-tumor and EOC mice on days 5 and 14 posttumor inoculation. (Right) Corresponding ex vivo immunofluorescence images show human EOC and mouse endothelial cells (ECs) stained with anti-CK8 and -CD31 antibodies, respectively. (Scale bars: 100 μm.) Note that all images in this report are displayed on a linear scale deliberately without saturation. Nonlinear, saturated image display appears to show higher contrast, but such a representation is not quantitative (Fig. S1). (F) Schematic of i.p. Cet-BPD photoactivation using a diffusing tip fiber and scattering media to enable efficient, targeted wide-field treatment of micrometastatic disease spread throughout the abdominal cavity by stepwise irradiation of each quadrant within the cavity.Here, we demonstrate these concepts of dual-function, tumor-targeted activatable immunoconjugates for selective treatment and quantitative, longitudinal imaging of micrometastases in vivo using a clinically motivated model of advanced-stage ovarian carcinomatosis (30). In this model, peritoneal micrometastases are derived from human EOC cells (OVCAR5) that possess intrinsic resistance to chemotherapy (8, 31). Using activatable immunoconjugates, a custom-built microendoscope (32) and a newly developed image analysis workflow (Figs. S2 and S3), we present minimally invasive, quantitative, and repeated measurements of micrometastases during therapy. Using fluorescence microendoscopy to characterize immunoconjugate pharmacokinetics and to monitor micrometastatic burden reduction in vivo, we demonstrate tumor-selective immunoconjugate activation and taPIT efficacy. This targeted activation significantly reduces nonspecific phototoxicity and fluorescence to provide therapeutic response monitoring of microscopic tumor nodules in a complex model of disseminated disease.     

Negative effects of nitrogen override positive effects of phosphorus on grassland legumes worldwide

Anthropogenic nutrient enrichment is driving global biodiversity decline and modifying ecosystem functions. Theory suggests that plant functional types that fix atmospheric nitrogen have a competitive advantage in nitrogen-poor soils, but lose this advantage with increasing nitrogen supply. By contrast, the addition of phosphorus, potassium, and other nutrients may benefit such species in low-nutrient environments by enhancing their nitrogen-fixing capacity. We present a global-scale experiment confirming these predictions for nitrogen-fixing legumes (Fabaceae) across 45 grasslands on six continents. Nitrogen addition reduced legume cover, richness, and biomass, particularly in nitrogen-poor soils, while cover of non–nitrogen-fixing plants increased. The addition of phosphorous, potassium, and other nutrients enhanced legume abundance, but did not mitigate the negative effects of nitrogen addition. Increasing nitrogen supply thus has the potential to decrease the diversity and abundance of grassland legumes worldwide regardless of the availability of other nutrients, with consequences for biodiversity, food webs, ecosystem resilience, and genetic improvement of protein-rich agricultural plant species.

Anthropogenic enrichment of nitrogen (N), phosphorus (P), and other nutrients from fertilizers and fossil fuel combustion is transforming natural ecosystems worldwide (1–5), leading to increased terrestrial plant productivity (6, 7) and loss of biodiversity (8, 9). Resource competition theory proposes that the capacity of species to persist at low levels of a limiting resource is a key mechanism underpinning competitive success. Consequently, plant functional types with specialized nutrient acquisition strategies are expected to have a competitive advantage in nutrient-limited environments but also to be especially vulnerable to nutrient enrichment (10–13).Legumes (Fabaceae) are one of the largest families of flowering plants, contributing over 650 genera and 19,000 taxa to global plant diversity (14). This diversity is important for biodiversity conservation and for genetic improvement of protein-rich crops and forage species for sustainable livestock production (15–17). Furthermore, the ability to fix atmospheric N₂ is one of the most important plant functional traits for influencing ecosystem processes, conferring N-fixing legumes with a disproportionately important role in ecosystem functioning (18, 19). For example, litter produced by legumes is nitrogen-rich and more easily decomposed by soil microorganisms, leading to flow on effects to higher trophic levels, including increased complexity of food webs and resistance of soil biophysical and chemical properties to ecosystem disturbance (20). As the success of legumes often arises from this capacity for symbiotic fixation of atmospheric N₂ in N-limited environments (21, 22), atmospheric N-deposition and other pathways of anthropogenic N supply are expected to drastically reduce their competitive advantage in plant communities (1, 5, 11, 23). This is especially the case for obligate-N-fixers that cannot down-regulate N-fixation (24, 25) and hence at higher soil N are disadvantaged by the high energetic cost of N-fixation (26).While concerns about global nutrient enrichment are focused on impacts of N on biodiversity and ecosystem productivity (1, 2, 27), changes in P and potassium (K) cycles (3, 4) or altered concentrations of other nutrients, can also influence the abundance and diversity of legumes in accordance with resource competition theory (10–13). Owing to the physiological demands of N-fixation, N-fixing legumes often have higher requirements for P, K, and other nutrients [e.g., molybdenum (Mo), iron (Fe), and calcium (Ca)] than non–N-fixing plants (28–31), and increases in these nutrients can favor N-fixing over non–N-fixing species, particularly in nutrient poor soils (21, 22). However, added nutrients may have synergistic effects (6, 32), leading to uncertainties in the expected net effect of P addition on the abundance of N-fixing legumes (26). For example, the phosphatases required for P acquisition from soils are rich in N; N addition may increase phosphatase investment, conferring legumes a superior phosphorus acquisition capacity in P- and N-limited environments (25, 29). Conversely, multiple nutrient addition is expected to allow nonlegumes to compete more effectively with legume species. Resulting light limitation may suppress legume growth and reduce the survival and establishment of new legume individuals (8, 9), especially of those legumes that are unable to reduce the costs of N fixation through down-regulation (10, 11, 15, 33–35).Despite these theoretical predictions, empirical evidence for the individual and interactive effects of changes in nutrient availability on legumes in natural ecosystems is limited (29, 36–39). Some experimental studies have shown decreased legume abundance with N addition and increased with P addition, but these studies are typically conducted at a single site and show both positive and negative interactive effects among nutrients (e.g., refs. 37, 40, and 41). Furthermore, minimal evidence is available regarding the influence of K or micronutrient enrichment on legume responses (29), and the underlying mechanisms of legume responses to nutrient addition, such as soil and climatic conditions, have not been investigated at global scales (but see ref. 26 for forest ecosystems).Using data from the Nutrient Network global collaborative experiment [https://nutnet.org/ (42)], we measured the cover, richness, and biomass responses of N-fixing legumes (hereafter legumes) to standardized experimental nutrient additions in 45 grasslands across six continents (SI Appendix, Fig. S1 and Table S1). Grasslands are a globally significant biome, covering more than one-third of the Earth’s ice-free land surface, accounting for a third of terrestrial net primary production (43), and supporting the livelihoods of more than 1.3 billion people. They are subject to chronic atmospheric nitrogen deposition due to fossil fuel combustion and are likely candidates for direct nitrogen fertilization (44). While N emissions in many regions of Europe have declined leading to plateaus or reductions in deposition (45), deposition in other world grasslands, such as the Mongolian Steppe, have increased in recent decades (e.g., ref. 46). Experimental sites included temperate and anthropic grasslands that spanned a broad range of geographical locations and ecological conditions, although were mostly from temperate latitudes (39) (SI Appendix, Table S1 and Fig. S1; see Methods for details).Three nutrients (N, P, K⁺) were applied in factorial combinations, resulting in eight treatments enabling evaluation of the interactive effects of N, P, and K addition (6, 8) on legumes. Over 3 to 6 y, 10 g⋅m⁻² N, P, and K were added annually to their respective treatment plots at the beginning of each site’s growing season; other nutrients in the K⁺ treatment [sulfur (S), magnesium (Mg), and micronutrients] were applied only in the first year to avoid toxicity (42). These nutrient levels were selected to ensure they were high enough to reduce nutrient limitation at a wide diversity of sites. They are at the higher end of the range for agricultural fertilizer application rates globally (5), and higher than atmospheric nutrient deposition rates (1, 3, 41, 43). In particular, our N-addition rate was about three times maximum current N-deposition rates in European grasslands and more generally across the globe (1, 47, 48).We used a standardized protocol (6, 42) to annually measure cover, richness, and biomass of legumes, forbs, and grasses in 1-m² permanent plots (Methods), starting in the year prior to the first nutrient application (Y_initial). Across all years and sites, we recorded 170 species of N-fixing grassland legumes, comprising 50 genera (SI Appendix, Table S2). The most species-rich genera were Trifolium (25 spp.), Astragalus (12 spp.), Vicia (11 spp.), and Lupinus (11 spp.). Vicia sativa, Trifolium repens, and Vicia hirsuta were the most frequent species across our sites (9.1%, 5.1%, and 4.9% of total occurrences, respectively). Each site contained one to eight legume species (Methods and SI Appendix, Table S1). Most legume species were perennials (∼60%), including 10 woody or shrub species (∼6% of species). On average, ∼3% and 4% of total live cover comprised annual and perennial legumes, respectively.We present results of nutrient addition for the third and the last available sampling year (years 3 to 6) after starting nutrient application in each site [noting sites started applying experimental treatments in different calendar years and ran for different lengths of time (SI Appendix, Table S1)]. To measure the relative impact of N, P, and K⁺ addition on legumes, we calculated the log ratio (LR) of legume abundance and richness in the third or last year in each plot versus the initial (pretreatment) value [LR = ln (Y_final/Y_initial)]. We used the pretreatment legume abundance in the LR instead of control plots (49) to control for initial legume abundance and spatial variability among plots (8, 50). We also calculated measures of legume colonization and extinction in each plot, and evaluated the effect of initial soil nutrient concentrations, community structure, and climatic conditions as contingencies for nutrient addition effects (see Methods for details). We analyzed the data using linear mixed-effects models (51–53), with nutrient treatments (i.e., N, P, K⁺, and their interactions) as fixed effects, and blocks nested within sites as random effects. Confidence intervals for model parameters were bootstrapped as a conservative method for hypothesis testing (51, 52) (see Methods for details).     

Subtropical High predictability establishes a promising way for monsoon and tropical storm predictions

Monsoon rainfall and tropical storms (TSs) impose great impacts on society, yet their seasonal predictions are far from successful. The western Pacific Subtropical High (WPSH) is a prime circulation system affecting East Asian summer monsoon (EASM) and western North Pacific TS activities, but the sources of its variability and predictability have not been established. Here we show that the WPSH variation faithfully represents fluctuations of EASM strength (r = –0.92), the total TS days over the subtropical western North Pacific (r = –0.81), and the total number of TSs impacting East Asian coasts (r = –0.76) during 1979–2009. Our numerical experiment results establish that the WPSH variation is primarily controlled by central Pacific cooling/warming and a positive atmosphere-ocean feedback between the WPSH and the Indo-Pacific warm pool oceans. With a physically based empirical model and the state-of-the-art dynamical models, we demonstrate that the WPSH is highly predictable; this predictability creates a promising way for prediction of monsoon and TS. The predictions using the WPSH predictability not only yields substantially improved skills in prediction of the EASM rainfall, but also enables skillful prediction of the TS activities that the current dynamical models fail. Our findings reveal that positive WPSH–ocean interaction can provide a source of climate predictability and highlight the importance of subtropical dynamics in understanding monsoon and TS predictability.Summer monsoons and tropical storms (TSs) affect billions of people’s livelihoods over East Asia including China, Japan, Korea, Indo-China peninsula, and Philippines. Prediction of the East Asian summer monsoon (EASM) rainfall and the TS in the western North Pacific (WNP) is a forefront scientific challenge of great societal importance and economic value. The latest assessment of the world-class climate models’ performance clearly demonstrates the models’ poor skills in prediction of the monsoon rainfall (1) and their inability to predict WNP TS variations.The western Pacific Subtropical High (WPSH) has profound effects on (and interact with) EASM and WNP TS activities (2–6); it also has far reaching influence on the summer rainfall over the Great Plains of the United States through atmospheric teleconnection (7, 8). Understanding the mechanism and predictability of the WPSH is a prerequisite for better prediction of the EASM and WNP TS.It has been noticed decades ago that an enhanced WPSH occurs during El Niño decaying summer, but the physical interpretation was not offered until the turn of 21st century (9–11). Recently, the influence of the Indian Ocean (IO) warming (12) has been revived to explain why the WPSH is abnormally strong after a peak El Niño (13–17). Note, however, approximately one-half of the strong anomalous WPSH years do not concur with decaying El Niño (Fig. S1) or IO warming (Fig. S2). Thus, it is necessary to reshape the conventional thinking on the causes of the interannual variation of the WPSH.Here, we reveal two fundamental mechanisms controlling the year-to-year variability of the WPSH, and demonstrate the high predictability of the WPSH, which paves a promising way to predict the monsoon and TS activities.     

From the Cover: Evidence of Lévy walk foraging patterns in human hunter–gatherers

When searching for food, many organisms adopt a superdiffusive, scale-free movement pattern called a Lévy walk, which is considered optimal when foraging for heterogeneously located resources with little prior knowledge of distribution patterns [Viswanathan GM, da Luz MGE, Raposo EP, Stanley HE (2011) The Physics of Foraging: An Introduction to Random Searches and Biological Encounters]. Although memory of food locations and higher cognition may limit the benefits of random walk strategies, no studies to date have fully explored search patterns in human foraging. Here, we show that human hunter–gatherers, the Hadza of northern Tanzania, perform Lévy walks in nearly one-half of all foraging bouts. Lévy walks occur when searching for a wide variety of foods from animal prey to underground tubers, suggesting that, even in the most cognitively complex forager on Earth, such patterns are essential to understanding elementary foraging mechanisms. This movement pattern may be fundamental to how humans experience and interact with the world across a wide range of ecological contexts, and it may be adaptive to food distribution patterns on the landscape, which previous studies suggested for organisms with more limited cognition. Additionally, Lévy walks may have become common early in our genus when hunting and gathering arose as a major foraging strategy, playing an important role in the evolution of human mobility.Over the last decade, researchers have applied sophisticated analytical techniques to explore the movement patterns of a wide variety of organisms from insects to mammals (1–8). Many of these taxa seem to use a similar movement pattern during foraging, where the length of move steps (distance traveled between two points marked by either a pause or a change in direction) is distributed according to a power law function with a heavy tail:, where l is move step length and μ is the power law exponent with 1 < μ ≤ 3 (1). In this distribution, termed a Lévy walk, groups of short step lengths are interspersed with longer movements between them, and this pattern is repeated across all scales (i.e., the distribution is scale-free) (9). Modeling studies have shown that this step length distribution is advantageous when searching for resources that are patchily distributed and can be profitably revisited (i.e., resources are not depleted after a given visit) (1, 10, 11). In these cases, the optimal Lévy strategy has μ ∼ 2, because the rare long steps minimize oversampling a given patch and take organisms to new food patches without requiring memory or high levels of cognition (1, 10, 11).When similar analytical techniques are applied to human movements, researchers have found some support for Lévy walks in our own species (12–15). In most cases, patterns found in urban-dwelling humans are attributed to the requirements of life (work, shopping, etc.) in a human-designed landscape (15) rather than an evolved search strategy as suggested for other organisms (1, 16). One previous study found evidence of Lévy walks in Ju/’hoansi hunter–gatherers of Botswana and Namibia, suggesting that random walk searches may be advantageous to humans living more traditional lifestyles (13, 17). However, this study examined the distribution of distances between residential camp locations [which are largely tied to the locations of permanent waterholes (18)] rather than the steps taken during actual foraging bouts (13). Thus, we are left with the question of whether Lévy walk patterns occur in cognitively complex foragers.In this study, we examined individual movement patterns among Hadza hunter–gatherers of northern Tanzania to determine whether the most cognitively complex foragers on Earth perform Lévy walks while foraging. The Hadza hunter–gatherers who we worked with adhered to a traditional hunting and gathering lifestyle—foraging for wild plant foods and game on foot with simple tools (bow and arrow, digging sticks, and axes) and without any modern technologies or agriculture (19). We recruited 44 Hadza subjects from two camps to wear global positioning system (GPS) units during foraging bouts (Table S1). Individuals wore GPS units on multiple days, and we collected data from camps during different seasons (SI Methods). We define a foraging bout as a round trip taken by a subject from and back to his or her residential camp. In addition to full foraging bouts, we examined the outbound leg of foraging bouts separately (from camp to the farthest point from camp in a given bout). We analyzed individual subject’s movement data from the longest foraging bout for each day separately (n = 342 total bouts) (analyses of all bouts for all individuals are in SI Methods). Step lengths are defined as the distance traveled between two points followed by either a pause or a change in direction (defined by a turning angle). The definition for a change in direction is generally arbitrary among various studies (15). Here, we ran our full dataset (Dataset S1) through multiple analyses, where the definition of directional change was altered in 10° increments from 0° to 180° (SI Methods).For each foraging bout and all step length definitions, we used maximum likelihood methods to fit six models (power law, truncated power law, exponential function, and three composite exponential models) to our data, and we used the Akaike Information Criterion (AIC) for model selection (20). Because humans and other animals are limited by physiology and time of day to some maximum step length, the truncated power law is generally thought to better represent movement patterns in nature (3) given by the following probability density function: f(l) = (μ − 1)(a^{1 − μ} − b^{1 − μ})⁻¹l^−μ, where a and b are the minimum and maximum values of l, respectively, for which a distribution is valid (21). In practice, these values are the minimum and maximum step lengths observed in a dataset. We also tested an exponential model to represent Brownian motion, a classic alternative movement strategy to Lévy walks (20): f(l) = . Finally, we tested three composite exponential models (composite Brownian walks) using information in the work by Jansen et al. (22): , where k is the number of exponential models mixed and p_j is the proportional contribution of the jth model to the overall distribution of steps. We tested models that included two, three, and four exponential functions. We performed Kolmogorov–Smirnov tests to determine the significance of model fits chosen by AIC (23). This method, which directly compares fits of power law models with the alternative exponential models, is considered the most statistically robust for determining the presence of a power law in movement data (20, 23).     

From the Cover: Modern Siberian dog ancestry was shaped by several thousand years of Eurasian-wide trade and human dispersal

Dogs have been essential to life in the Siberian Arctic for over 9,500 y, and this tight link between people and dogs continues in Siberian communities. Although Arctic Siberian groups such as the Nenets received limited gene flow from neighboring groups, archaeological evidence suggests that metallurgy and new subsistence strategies emerged in Northwest Siberia around 2,000 y ago. It is unclear if the Siberian Arctic dog population was as continuous as the people of the region or if instead admixture occurred, possibly in relation to the influx of material culture from other parts of Eurasia. To address this question, we sequenced and analyzed the genomes of 20 ancient and historical Siberian and Eurasian Steppe dogs. Our analyses indicate that while Siberian dogs were genetically homogenous between 9,500 to 7,000 y ago, later introduction of dogs from the Eurasian Steppe and Europe led to substantial admixture. This is clearly the case in the Iamal-Nenets region (Northwestern Siberia) where dogs from the Iron Age period (∼2,000 y ago) possess substantially less ancestry related to European and Steppe dogs than dogs from the medieval period (∼1,000 y ago). Combined with findings of nonlocal materials recovered from these archaeological sites, including glass beads and metal items, these results indicate that Northwest Siberian communities were connected to a larger trade network through which they acquired genetically distinctive dogs from other regions. These exchanges were part of a series of major societal changes, including the rise of large-scale reindeer pastoralism ∼800 y ago.

Early archaeological and genomic evidence from Zhokhov Island in Arctic Siberia indicates that dogs belonging to a distinct lineage were an essential component of life in the Arctic for over 9,500 y (1, 2). This tight link between people and dogs continues in Siberian communities such as the Koryaks, Itel’mens, Chukchi, and Nenets, where dogs continued to be used for hunting, herding, and sledding among other activities (3–5). Recent genomic data obtained from Samoyedic-speaking communities such as Nenets and Selkups suggest that during the Holocene they received limited gene flow from neighboring groups, including Steppe pastoralists (6, 7). Given that humans and their dogs often migrate and interact in parallel (8), it is possible that Siberian dogs also experienced limited gene flow from other populations.In contrast to the human genomic evidence, linguistic and ethnographic data suggest more dynamic processes. Specifically, these data suggest that Samoyedic-speaking peoples of Northwest Siberia migrated from southern Siberia, or neighboring regions of southeast Europe, to the Arctic as recently as ∼3,000 to 4,000 y ago (9–12). In addition, archaeological sites such as Ust’-Polui in Northwest Siberia show evidence of iron and bronze metallurgy and isolated finds such as glass beads that were likely introduced from the Steppe, Black Sea, or the Near East (13–15). The presence of this material culture suggests that these communities participated in broad-ranging trade networks (13–15). The proposed migrations and exchanges of materials and practices potentially also involved dogs, which could have led to admixture, improvement, and ultimately to the establishment of modern Siberian dog lineages such as the modern Samoyed breed.To assess whether the Northwest Siberian Arctic dogs population was continuous, or was instead marked by admixture (possibly in relation to the influx of material culture from other parts of Eurasia), we sequenced 20 ancient and historical Siberian and Eurasian Steppe dogs ranging in age from 11,000 to 60 y ago and in genomic coverage between 0.1× and 11.1× (Dataset S1). We then analyzed these genomes alongside publicly available ancient (n = 29) and modern (n = 120) canids (Fig. 1A and Dataset S2).Open in a separate windowFig. 1.(A) Map of ancient dogs included in the study with sample name and age (kya) with an Inset map of the Iamal-Nenets region of Northwest Siberia. Data from samples represented by circles were generated in this study with a mean genome coverage between 0.1 and 19.9×; triangles represent publicly available ancient dogs. The colors of the data points represent the D-statistic value of the form D (black jackal, sample; Zhokhov, ASHQ01). Red-shifted colors show a closer affinity to ASHQ01 (ancient Near Eastern dog), and blue-shifted colors indicate a closer affinity to Zhokhov (ancient Arctic dog). (B) A TreeMix phylogeny with five migration edges that are indicated by gray dotted lines. Each population contains between one and three individuals (SI Appendix, Table S1). The color of the branches correspond to average D-statistic value in A. Complete models with the outgroup and edge weights, as well as models with additional edges can be found in SI Appendix, Fig. S3.