De novo and salvage purine synthesis pathways across tissues and tumors.

Purine nucleotides are vital for RNA and DNA synthesis, signaling, metabolism, and energy homeostasis. To synthesize purines, cells use two principal routes: the de novo and salvage pathways. Traditionally, it is believed that proliferating cells predominantly rely on de novo synthesis, whereas differentiated tissues favor the salvage pathway. Unexpectedly, we find that adenine and inosine are the most effective circulating precursors for supplying purine nucleotides to tissues and tumors, while hypoxanthine is rapidly catabolized and poorly salvaged in vivo. Quantitative metabolic analysis demonstrates comparative contribution from de novo synthesis and salvage pathways in maintaining purine nucleotide pools in tumors. Notably, feeding mice nucleotides accelerates tumor growth, while inhibiting purine salvage slows down tumor progression, revealing a crucial role of the salvage pathway in tumor metabolism. These findings provide fundamental insights into how normal tissues and tumors maintain purine nucleotides and highlight the significance of purine salvage in cancer.

Osteoclasts recycle via osteomorphs during RANKL-stimulated bone resorption.

Osteoclasts are large multinucleated bone-resorbing cells formed by the fusion of monocyte/macrophage-derived precursors that are thought to undergo apoptosis once resorption is complete. Here, by intravital imaging, we reveal that RANKL-stimulated osteoclasts have an alternative cell fate in which they fission into daughter cells called osteomorphs. Inhibiting RANKL blocked this cellular recycling and resulted in osteomorph accumulation. Single-cell RNA sequencing showed that osteomorphs are transcriptionally distinct from osteoclasts and macrophages and express a number of non-canonical osteoclast genes that are associated with structural and functional bone phenotypes when deleted in mice. Furthermore, genetic variation in human orthologs of osteomorph genes causes monogenic skeletal disorders and associates with bone mineral density, a polygenetic skeletal trait. Thus, osteoclasts recycle via osteomorphs, a cell type involved in the regulation of bone resorption that may be targeted for the treatment of skeletal diseases.

Crystal Structure of the Human Cannabinoid Receptor CB2.

The cannabinoid receptor CB2 is predominately expressed in the immune system, and selective modulation of CB2 without the psychoactivity of CB1 has therapeutic potential in inflammatory, fibrotic, and neurodegenerative diseases. Here, we report the crystal structure of human CB2 in complex with a rationally designed antagonist, AM10257, at 2.8 Å resolution. The CB2-AM10257 structure reveals a distinctly different binding pose compared with CB1. However, the extracellular portion of the antagonist-bound CB2 shares a high degree of conformational similarity with the agonist-bound CB1, which led to the discovery of AM10257's unexpected opposing functional profile of CB2 antagonism versus CB1 agonism. Further structural analysis using mutagenesis studies and molecular docking revealed the molecular basis of their function and selectivity for CB2 and CB1. Additional analyses of our designed antagonist and agonist pairs provide important insight into the activation mechanism of CB2. The present findings should facilitate rational drug design toward precise modulation of the endocannabinoid system.

Antibody agonists trigger immune receptor signaling through local exclusion of receptor-type protein tyrosine phosphatases.

Antibodies can block immune receptor engagement or trigger the receptor machinery to initiate signaling. We hypothesized that antibody agonists trigger signaling by sterically excluding large receptor-type protein tyrosine phosphatases (RPTPs) such as CD45 from sites of receptor engagement. An agonist targeting the costimulatory receptor CD28 produced signals that depended on antibody immobilization and were sensitive to the sizes of the receptor, the RPTPs, and the antibody itself. Although both the agonist and a non-agonistic anti-CD28 antibody locally excluded CD45, the agonistic antibody was more effective. An anti-PD-1 antibody that bound membrane proximally excluded CD45, triggered Src homology 2 domain-containing phosphatase 2 recruitment, and suppressed systemic lupus erythematosus and delayed-type hypersensitivity in experimental models. Paradoxically, nivolumab and pembrolizumab, anti-PD-1-blocking antibodies used clinically, also excluded CD45 and were agonistic in certain settings. Reducing these agonistic effects using antibody engineering improved PD-1 blockade. These findings establish a framework for developing new and improved therapies for autoimmunity and cancer.

BMAL1 drives muscle repair through control of hypoxic NAD+ regeneration in satellite cells.

The process of tissue regeneration occurs in a developmentally timed manner, yet the role of circadian timing is not understood. Here, we identify a role for the adult muscle stem cell (MuSC)-autonomous clock in the control of muscle regeneration following acute ischemic injury. We observed greater muscle repair capacity following injury during the active/wake period as compared with the inactive/rest period in mice, and loss of Bmal1 within MuSCs leads to impaired muscle regeneration. We demonstrate that Bmal1 loss in MuSCs leads to reduced activated MuSC number at day 3 postinjury, indicating a failure to properly expand the myogenic precursor pool. In cultured primary myoblasts, we observed that loss of Bmal1 impairs cell proliferation in hypoxia (a condition that occurs in the first 1-3 d following tissue injury in vivo), as well as subsequent myofiber differentiation. Loss of Bmal1 in both cultured myoblasts and in vivo activated MuSCs leads to reduced glycolysis and premature activation of prodifferentiation gene transcription and epigenetic remodeling. Finally, hypoxic cell proliferation and myofiber formation in Bmal1-deficient myoblasts are restored by increasing cytosolic NAD+ Together, we identify the MuSC clock as a pivotal regulator of oxygen-dependent myoblast cell fate and muscle repair through the control of the NAD+-driven response to injury.

Proliferation at the heart of preadolescence.

Cardiomyocytes, the cells of the heart muscle, lose nearly all of their proliferative capacity after birth, limiting the heart's ability to regenerate. Naqvi et al. now identify a transient burst of cardiomyocyte proliferation during preadolescence, driven by a thyroid hormone surge, with therapeutic implications for congenital and acquired heart diseases.

Principles of mitoribosomal small subunit assembly in eukaryotes.

Mitochondrial ribosomes (mitoribosomes) synthesize proteins encoded within the mitochondrial genome that are assembled into oxidative phosphorylation complexes. Thus, mitoribosome biogenesis is essential for ATP production and cellular metabolism1. Here we used cryo-electron microscopy to determine nine structures of native yeast and human mitoribosomal small subunit assembly intermediates, illuminating the mechanistic basis for how GTPases are used to control early steps of decoding centre formation, how initial rRNA folding and processing events are mediated, and how mitoribosomal proteins have active roles during assembly. Furthermore, this series of intermediates from two species with divergent mitoribosomal architecture uncovers both conserved principles and species-specific adaptations that govern the maturation of mitoribosomal small subunits in eukaryotes. By revealing the dynamic interplay between assembly factors, mitoribosomal proteins and rRNA that are required to generate functional subunits, our structural analysis provides a vignette for how molecular complexity and diversity can evolve in large ribonucleoprotein assemblies.

Learning from prepandemic data to forecast viral escape.

Effective pandemic preparedness relies on anticipating viral mutations that are able to evade host immune responses to facilitate vaccine and therapeutic design. However, current strategies for viral evolution prediction are not available early in a pandemic-experimental approaches require host polyclonal antibodies to test against1-16, and existing computational methods draw heavily from current strain prevalence to make reliable predictions of variants of concern17-19. To address this, we developed EVEscape, a generalizable modular framework that combines fitness predictions from a deep learning model of historical sequences with biophysical and structural information. EVEscape quantifies the viral escape potential of mutations at scale and has the advantage of being applicable before surveillance sequencing, experimental scans or three-dimensional structures of antibody complexes are available. We demonstrate that EVEscape, trained on sequences available before 2020, is as accurate as high-throughput experimental scans at anticipating pandemic variation for SARS-CoV-2 and is generalizable to other viruses including influenza, HIV and understudied viruses with pandemic potential such as Lassa and Nipah. We provide continually revised escape scores for all current strains of SARS-CoV-2 and predict probable further mutations to forecast emerging strains as a tool for continuing vaccine development ( evescape.org ).

An autonomous laboratory for the accelerated synthesis of novel materials.

To close the gap between the rates of computational screening and experimental realization of novel materials1,2, we introduce the A-Lab, an autonomous laboratory for the solid-state synthesis of inorganic powders. This platform uses computations, historical data from the literature, machine learning (ML) and active learning to plan and interpret the outcomes of experiments performed using robotics. Over 17 days of continuous operation, the A-Lab realized 41 novel compounds from a set of 58 targets including a variety of oxides and phosphates that were identified using large-scale ab initio phase-stability data from the Materials Project and Google DeepMind. Synthesis recipes were proposed by natural-language models trained on the literature and optimized using an active-learning approach grounded in thermodynamics. Analysis of the failed syntheses provides direct and actionable suggestions to improve current techniques for materials screening and synthesis design. The high success rate demonstrates the effectiveness of artificial-intelligence-driven platforms for autonomous materials discovery and motivates further integration of computations, historical knowledge and robotics.

The recovery of European freshwater biodiversity has come to a halt.

Owing to a long history of anthropogenic pressures, freshwater ecosystems are among the most vulnerable to biodiversity loss1. Mitigation measures, including wastewater treatment and hydromorphological restoration, have aimed to improve environmental quality and foster the recovery of freshwater biodiversity2. Here, using 1,816 time series of freshwater invertebrate communities collected across 22 European countries between 1968 and 2020, we quantified temporal trends in taxonomic and functional diversity and their responses to environmental pressures and gradients. We observed overall increases in taxon richness (0.73% per year), functional richness (2.4% per year) and abundance (1.17% per year). However, these increases primarily occurred before the 2010s, and have since plateaued. Freshwater communities downstream of dams, urban areas and cropland were less likely to experience recovery. Communities at sites with faster rates of warming had fewer gains in taxon richness, functional richness and abundance. Although biodiversity gains in the 1990s and 2000s probably reflect the effectiveness of water-quality improvements and restoration projects, the decelerating trajectory in the 2010s suggests that the current measures offer diminishing returns. Given new and persistent pressures on freshwater ecosystems, including emerging pollutants, climate change and the spread of invasive species, we call for additional mitigation to revive the recovery of freshwater biodiversity.

Small rainfall changes drive substantial changes in plant coexistence.

Although precipitation patterns have long been known to shape plant distributions1, the effect of changing climate on the interactions of species and therefore community composition is far less understood2,3. Here, we explored how changes in precipitation alter competitive dynamics via direct effects on individual species, as well as by the changing strength of competitive interactions between species, using an annual grassland community in California. We grew plants under ambient and reduced precipitation in the field to parameterize a competition model4 with which we quantified the stabilizing niche and fitness differences that determine species coexistence in each rainfall regime. We show that reduced precipitation had little direct effect on species grown alone, but it qualitatively shifted predicted competitive outcomes for 10 of 15 species pairs. In addition, species pairs that were functionally more similar were less likely to experience altered outcomes, indicating that functionally diverse communities may be most threatened by changing interactions. Our results highlight how important it is to account for changes to species interactions when predicting species and community response to global change.

Hemispheric black carbon increase after the 13th-century Maori arrival in New Zealand.

New Zealand was among the last habitable places on earth to be colonized by humans1. Charcoal records indicate that wildfires were rare prior to colonization and widespread following the 13th- to 14th-century Maori settlement2, but the precise timing and magnitude of associated biomass-burning emissions are unknown1,3, as are effects on light-absorbing black carbon aerosol concentrations over the pristine Southern Ocean and Antarctica4. Here we used an array of well-dated Antarctic ice-core records to show that while black carbon deposition rates were stable over continental Antarctica during the past two millennia, they were approximately threefold higher over the northern Antarctic Peninsula during the past 700 years. Aerosol modelling5 demonstrates that the observed deposition could result only from increased emissions poleward of 40° S-implicating fires in Tasmania, New Zealand and Patagonia-but only New Zealand palaeofire records indicate coincident increases. Rapid deposition increases started in 1297 (±30 s.d.) in the northern Antarctic Peninsula, consistent with the late 13th-century Maori settlement and New Zealand black carbon emissions of 36 (±21 2 s.d.) Gg y-1 during peak deposition in the 16th century. While charcoal and pollen records suggest earlier, climate-modulated burning in Tasmania and southern Patagonia6,7, deposition in Antarctica shows that black carbon emissions from burning in New Zealand dwarfed other preindustrial emissions in these regions during the past 2,000 years, providing clear evidence of large-scale environmental effects associated with early human activities across the remote Southern Hemisphere.

Mycobacterium tuberculosis response to cholesterol is integrated with environmental pH and potassium levels via a lipid metabolism regulator.

Successful colonization of the host requires Mycobacterium tuberculosis (Mtb) to sense and respond coordinately to disparate environmental cues during infection and adapt its physiology. However, how Mtb response to environmental cues and the availability of key carbon sources may be integrated is poorly understood. Here, by exploiting a reporter-based genetic screen, we have unexpectedly found that overexpression of transcription factors involved in Mtb lipid metabolism altered the dampening effect of low environmental potassium concentrations ([K+]) on the pH response of Mtb. Cholesterol is a major carbon source for Mtb during infection, and transcriptional analyses revealed that Mtb response to acidic pH was augmented in the presence of cholesterol and vice versa. Strikingly, deletion of the putative lipid regulator mce3R had little effect on Mtb transcriptional response to acidic pH or cholesterol individually, but resulted specifically in loss of cholesterol response augmentation in the simultaneous presence of acidic pH. Similarly, while mce3R deletion had little effect on Mtb response to low environmental [K+] alone, augmentation of the low [K+] response by the simultaneous presence of cholesterol was lost in the mutant. Finally, a mce3R deletion mutant was attenuated for growth in foamy macrophages and for colonization in a murine infection model that recapitulates caseous necrotic lesions and the presence of foamy macrophages. These findings reveal the critical coordination between Mtb response to environmental cues and cholesterol, a vital carbon source, and establishes Mce3R as a transcription factor that crucially serves to integrate these signals.

Torsional force microscopy of van der Waals moirés and atomic lattices.

In a stack of atomically thin van der Waals layers, introducing interlayer twist creates a moiré superlattice whose period is a function of twist angle. Changes in that twist angle of even hundredths of a degree can dramatically transform the system's electronic properties. Setting a precise and uniform twist angle for a stack remains difficult; hence, determining that twist angle and mapping its spatial variation is very important. Techniques have emerged to do this by imaging the moiré, but most of these require sophisticated infrastructure, time-consuming sample preparation beyond stack synthesis, or both. In this work, we show that torsional force microscopy (TFM), a scanning probe technique sensitive to dynamic friction, can reveal surface and shallow subsurface structure of van der Waals stacks on multiple length scales: the moirés formed between bi-layers of graphene and between graphene and hexagonal boron nitride (hBN) and also the atomic crystal lattices of graphene and hBN. In TFM, torsional motion of an Atomic Force Microscope (AFM) cantilever is monitored as it is actively driven at a torsional resonance while a feedback loop maintains contact at a set force with the sample surface. TFM works at room temperature in air, with no need for an electrical bias between the tip and the sample, making it applicable to a wide array of samples. It should enable determination of precise structural information including twist angles and strain in moiré superlattices and crystallographic orientation of van der Waals flakes to support predictable moiré heterostructure fabrication.

Assembly of lamina-specific neuronal connections by slit bound to type IV collagen.

The mechanisms that generate specific neuronal connections in the brain are under intense investigation. In zebrafish, retinal ganglion cells project their axons into at least six layers within the neuropil of the midbrain tectum. Each axon elaborates a single, planar arbor in one of the target layers and forms synapses onto the dendrites of tectal neurons. We show that the laminar specificity of retinotectal connections does not depend on self-sorting interactions among RGC axons. Rather, tectum-derived Slit1, signaling through axonal Robo2, guides neurites to their target layer. Genetic and biochemical studies indicate that Slit binds to Dragnet (Col4a5), a type IV Collagen, which forms the basement membrane on the surface of the tectum. We further show that radial glial endfeet are required for the basement-membrane anchoring of Slit. We propose that Slit1 signaling, perhaps in the form of a superficial-to-deep gradient, presents laminar positional cues to ingrowing retinal axons.

Engineered calprotectin-sensing probiotics for IBD surveillance in humans.

Inflammatory bowel disease (IBD) is a spectrum of autoimmune diseases affecting the gastrointestinal tract characterized by a relapsing and remitting course of gut mucosal inflammation. Disease flares can be difficult to predict, and the current practice of IBD disease activity surveillance through endoscopy is invasive and requires medical expertise. Recent advancements in synthetic biology raise the possibility that symbiotic microbes can be engineered to selectively detect disease biomarkers used in current clinical practice. Here, we introduce an engineered probiotic capable of detecting the clinical gold standard IBD biomarker, calprotectin, with sensitivity and specificity in IBD patients. Specifically, we identified a bacterial promoter in the probiotic strain Escherichia coli Nissle 1917 (EcN) which exhibits a specific expression increase in the presence of calprotectin. Using murine models of colitis, we show that the reporter signal is activated in vivo during transit of the GI tract following oral delivery. Furthermore, our engineered probiotic can successfully discriminate human patients with active IBD from those in remission and without IBD using patient stool samples, where the intensity of reporter signal quantitatively tracks with clinical laboratory-measured levels of calprotectin. Our pilot study sets the stage for probiotics that can be engineered to detect fecal calprotectin for precise noninvasive disease activity monitoring in IBD patients.

Symmetry in frontal but not motor and somatosensory cortical projections.

Neocortex and striatum are topographically organized for sensory and motor functions. While sensory and motor areas are lateralized for touch and motor control, respectively, frontal areas are involved in decision making, where lateralization of function may be less important. This study contrasted the topographic precision of cell type-specific ipsilateral and contralateral cortical projections while varying the injection site location in transgenic mice of both sexes. While sensory cortical areas had strongly topographic outputs to ipsilateral cortex and striatum, they were weaker and not as topographically precise to contralateral targets. Motor cortex had somewhat stronger projections, but still relatively weak contralateral topography. In contrast, frontal cortical areas had high degrees of topographic similarity for both ipsilateral and contralateral projections to cortex and striatum. Corticothalamic organization is mainly ipsilateral, with weaker, more medial contralateral projections. Corticostriatal computations might integrate input outside closed basal ganglia loops using contralateral projections, enabling the two hemispheres to act as a unit to converge on one result in motor planning and decision making.Significance Statement Each cerebral hemisphere is responsible for sensation and movement of the opposite side of the body. Many axonal projections cross the midline to target contralateral areas. Crossed corticocortical, corticostriatal, and corticothalamic projections originate from much of neocortex, but how these projections vary across cortical regions and cell types is unknown. We quantify differences in the strength and targeting of ipsilateral and contralateral projections from frontal, motor, and somatosensory areas. The contralateral corticocortical and corticostriatal projections are proposed to play a larger role in frontal areas than in sensory or motor ones as a circuit basis for unifying computation across hemispheres in motor planning, while contralateral connectivity plays a smaller role in sensory and motor processing.

Restoration of the ER stress response protein TDAG51 in hepatocytes mitigates NAFLD in mice.

Endoplasmic reticulum stress is associated with insulin resistance and the development of nonalcoholic fatty liver disease. Deficiency of the endoplasmic reticulum stress response T-cell death-associated gene 51 (TDAG51) (TDAG51-/-) in mice promotes the development of high-fat diet (HFD)-induced obesity, fatty liver, and hepatic insulin resistance. However, whether this effect is due specifically to hepatic TDAG51 deficiency is unknown. Here, we report that hepatic TDAG51 protein levels are consistently reduced in multiple mouse models of liver steatosis and injury as well as in liver biopsies from patients with liver disease compared to normal controls. Delivery of a liver-specific adeno-associated virus (AAV) increased hepatic expression of a TDAG51-GFP fusion protein in WT, TDAG51-/-, and leptin-deficient (ob/ob) mice. Restoration of hepatic TDAG51 protein was sufficient to increase insulin sensitivity while reducing body weight and fatty liver in HFD fed TDAG51-/- mice and in ob/ob mice. TDAG51-/- mice expressing ectopic TDAG51 display improved Akt (Ser473) phosphorylation, post-insulin stimulation. HFD-fed TDAG51-/- mice treated with AAV-TDAG51-GFP displayed reduced lipogenic gene expression, increased beta-oxidation and lowered hepatic and serum triglycerides, findings consistent with reduced liver weight. Further, AAV-TDAG51-GFP-treated TDAG51-/- mice exhibited reduced hepatic precursor and cleaved sterol regulatory-element binding proteins (SREBP-1 and SREBP-2). In vitro studies confirmed the lipid-lowering effect of TDAG51 overexpression in oleic acid-treated Huh7 cells. These studies suggest that maintaining hepatic TDAG51 protein levels represents a viable therapeutic approach for the treatment of obesity and insulin resistance associated with nonalcoholic fatty liver disease.

DeepGSEA: explainable deep gene set enrichment analysis for single-cell transcriptomic data.

MOTIVATION: Gene set enrichment (GSE) analysis allows for an interpretation of gene expression through pre-defined gene set databases and is a critical step in understanding different phenotypes. With the rapid development of single-cell RNA sequencing (scRNA-seq) technology, GSE analysis can be performed on fine-grained gene expression data to gain a nuanced understanding of phenotypes of interest. However, with the cellular heterogeneity in single-cell gene profiles, current statistical GSE analysis methods sometimes fail to identify enriched gene sets. Meanwhile, deep learning has gained traction in applications like clustering and trajectory inference in single-cell studies due to its prowess in capturing complex data patterns. However, its use in GSE analysis remains limited, due to interpretability challenges. RESULTS: In this paper, we present DeepGSEA, an explainable deep gene set enrichment analysis approach which leverages the expressiveness of interpretable, prototype-based neural networks to provide an in-depth analysis of GSE. DeepGSEA learns the ability to capture GSE information through our designed classification tasks, and significance tests can be performed on each gene set, enabling the identification of enriched sets. The underlying distribution of a gene set learned by DeepGSEA can be explicitly visualized using the encoded cell and cellular prototype embeddings. We demonstrate the performance of DeepGSEA over commonly used GSE analysis methods by examining their sensitivity and specificity with four simulation studies. In addition, we test our model on three real scRNA-seq datasets and illustrate the interpretability of DeepGSEA by showing how its results can be explained. AVAILABILITY AND IMPLEMENTATION: https://github.com/Teddy-XiongGZ/DeepGSEA.