Distinct Cellular Tropism and Immune Responses to Alphavirus Infection.

Alphaviruses are emerging and reemerging viruses that cause disease syndromes ranging from incapacitating arthritis to potentially fatal encephalitis. While infection by arthritogenic and encephalitic alphaviruses results in distinct clinical manifestations, both virus groups induce robust innate and adaptive immune responses. However, differences in cellular tropism, type I interferon induction, immune cell recruitment, and B and T cell responses result in differential disease progression and outcome. In this review, we discuss aspects of immune responses that contribute to protective or pathogenic outcomes after alphavirus infection.

Immune System Investigation Using Parasitic Helminths.

Coevolutionary adaptation between humans and helminths has developed a finely tuned balance between host immunity and chronic parasitism due to immunoregulation. Given that these reciprocal forces drive selection, experimental models of helminth infection are ideally suited for discovering how host protective immune responses adapt to the unique tissue niches inhabited by these large metazoan parasites. This review highlights the key discoveries in the immunology of helminth infection made over the last decade, from innate lymphoid cells to the emerging importance of neuroimmune connections. A particular emphasis is placed on the emerging areas within helminth immunology where the most growth is possible, including the advent of genetic manipulation of parasites to study immunology and the use of engineered T cells for therapeutic options. Lastly,we cover the status of human challenge trials with helminths as treatment for autoimmune disease, which taken together, stand to keep the study of parasitic worms at the forefront of immunology for years to come.

Empowering biomedical discovery with AI agents.

We envision "AI scientists" as systems capable of skeptical learning and reasoning that empower biomedical research through collaborative agents that integrate AI models and biomedical tools with experimental platforms. Rather than taking humans out of the discovery process, biomedical AI agents combine human creativity and expertise with AI's ability to analyze large datasets, navigate hypothesis spaces, and execute repetitive tasks. AI agents are poised to be proficient in various tasks, planning discovery workflows and performing self-assessment to identify and mitigate gaps in their knowledge. These agents use large language models and generative models to feature structured memory for continual learning and use machine learning tools to incorporate scientific knowledge, biological principles, and theories. AI agents can impact areas ranging from virtual cell simulation, programmable control of phenotypes, and the design of cellular circuits to developing new therapies.

Translational potential of mouse models of human metabolic disease.

Obesity causes significant morbidity and mortality globally. Research in the last three decades has delivered a step-change in our understanding of the fundamental mechanisms that regulate energy homeostasis, building on foundational discoveries in mouse models of metabolic disease. However, not all findings made in rodents have translated to humans, hampering drug discovery in this field. Here, we review how studies in mice and humans have informed our current framework for understanding energy homeostasis, discuss their challenges and limitations, and offer a perspective on how human studies may play an increasingly important role in the discovery of disease mechanisms and identification of therapeutic targets in the future.

Task-driven neural network models predict neural dynamics of proprioception.

Proprioception tells the brain the state of the body based on distributed sensory neurons. Yet, the principles that govern proprioceptive processing are poorly understood. Here, we employ a task-driven modeling approach to investigate the neural code of proprioceptive neurons in cuneate nucleus (CN) and somatosensory cortex area 2 (S1). We simulated muscle spindle signals through musculoskeletal modeling and generated a large-scale movement repertoire to train neural networks based on 16 hypotheses, each representing different computational goals. We found that the emerging, task-optimized internal representations generalize from synthetic data to predict neural dynamics in CN and S1 of primates. Computational tasks that aim to predict the limb position and velocity were the best at predicting the neural activity in both areas. Since task optimization develops representations that better predict neural activity during active than passive movements, we postulate that neural activity in the CN and S1 is top-down modulated during goal-directed movements.

Decoding the brain: From neural representations to mechanistic models.

A central principle in neuroscience is that neurons within the brain act in concert to produce perception, cognition, and adaptive behavior. Neurons are organized into specialized brain areas, dedicated to different functions to varying extents, and their function relies on distributed circuits to continuously encode relevant environmental and body-state features, enabling other areas to decode (interpret) these representations for computing meaningful decisions and executing precise movements. Thus, the distributed brain can be thought of as a series of computations that act to encode and decode information. In this perspective, we detail important concepts of neural encoding and decoding and highlight the mathematical tools used to measure them, including deep learning methods. We provide case studies where decoding concepts enable foundational and translational science in motor, visual, and language processing.

Functional sensory circuits built from neurons of two species.

A central question for regenerative neuroscience is whether synthetic neural circuits, such as those built from two species, can function in an intact brain. Here, we apply blastocyst complementation to selectively build and test interspecies neural circuits. Despite approximately 10-20 million years of evolution, and prominent species differences in brain size, rat pluripotent stem cells injected into mouse blastocysts develop and persist throughout the mouse brain. Unexpectedly, the mouse niche reprograms the birth dates of rat neurons in the cortex and hippocampus, supporting rat-mouse synaptic activity. When mouse olfactory neurons are genetically silenced or killed, rat neurons restore information flow to odor processing circuits. Moreover, they rescue the primal behavior of food seeking, although less well than mouse neurons. By revealing that a mouse can sense the world using neurons from another species, we establish neural blastocyst complementation as a powerful tool to identify conserved mechanisms of brain development, plasticity, and repair.

Mosaic sarbecovirus nanoparticles elicit cross-reactive responses in pre-vaccinated animals.

Immunization with mosaic-8b (nanoparticles presenting 8 SARS-like betacoronavirus [sarbecovirus] receptor-binding domains [RBDs]) elicits more broadly cross-reactive antibodies than homotypic SARS-CoV-2 RBD-only nanoparticles and protects against sarbecoviruses. To investigate original antigenic sin (OAS) effects on mosaic-8b efficacy, we evaluated the effects of prior COVID-19 vaccinations in non-human primates and mice on anti-sarbecovirus responses elicited by mosaic-8b, admix-8b (8 homotypics), or homotypic SARS-CoV-2 immunizations, finding the greatest cross-reactivity for mosaic-8b. As demonstrated by molecular fate mapping, in which antibodies from specific cohorts of B cells are differentially detected, B cells primed by WA1 spike mRNA-LNP dominated antibody responses after RBD-nanoparticle boosting. While mosaic-8b- and homotypic-nanoparticles boosted cross-reactive antibodies, de novo antibodies were predominantly induced by mosaic-8b, and these were specific for variant RBDs with increased identity to RBDs on mosaic-8b. These results inform OAS mechanisms and support using mosaic-8b to protect COVID-19-vaccinated/infected humans against as-yet-unknown SARS-CoV-2 variants and animal sarbecoviruses with human spillover potential.

Toward developing human organs via embryo models and chimeras.

Developing functional organs from stem cells remains a challenging goal in regenerative medicine. Existing methodologies, such as tissue engineering, bioprinting, and organoids, only offer partial solutions. This perspective focuses on two promising approaches emerging for engineering human organs from stem cells: stem cell-based embryo models and interspecies organogenesis. Both approaches exploit the premise of guiding stem cells to mimic natural development. We begin by summarizing what is known about early human development as a blueprint for recapitulating organogenesis in both embryo models and interspecies chimeras. The latest advances in both fields are discussed before highlighting the technological and knowledge gaps to be addressed before the goal of developing human organs could be achieved using the two approaches. We conclude by discussing challenges facing embryo modeling and interspecies organogenesis and outlining future prospects for advancing both fields toward the generation of human tissues and organs for basic research and translational applications.

Controlling organoid symmetry breaking uncovers an excitable system underlying human axial elongation.

The human embryo breaks symmetry to form the anterior-posterior axis of the body. As the embryo elongates along this axis, progenitors in the tail bud give rise to tissues that generate spinal cord, skeleton, and musculature. This raises the question of how the embryo achieves axial elongation and patterning. While ethics necessitate in vitro studies, the variability of organoid systems has hindered mechanistic insights. Here, we developed a bioengineering and machine learning framework that optimizes organoid symmetry breaking by tuning their spatial coupling. This framework enabled reproducible generation of axially elongating organoids, each possessing a tail bud and neural tube. We discovered that an excitable system composed of WNT/FGF signaling drives elongation by inducing a neuromesodermal progenitor-like signaling center. We discovered that instabilities in the excitable system are suppressed by secreted WNT inhibitors. Absence of these inhibitors led to ectopic tail buds and branches. Our results identify mechanisms governing stable human axial elongation.

An ethical framework for human embryology with embryo models.

A human embryo's legal definition and its entitlement to protection vary greatly worldwide. Recently, human pluripotent stem cells have been used to form in vitro models of early embryos that have challenged legal definitions and raised questions regarding their usage. In this light, we propose a refined legal definition of an embryo, suggest "tipping points" for when human embryo models could eventually be afforded similar protection to that of embryos, and then revisit basic ethical principles that might help to draft a roadmap for the gradual, justified usage of embryo models in a manner that aims to maximize benefits to society.

Massively parallel functional dissection of schizophrenia-associated noncoding genetic variants.

Schizophrenia (SCZ) is a highly heritable mental disorder with thousands of associated genetic variants located mostly in the noncoding space of the genome. Translating these associations into insights regarding the underlying pathomechanisms has been challenging because the causal variants, their mechanisms of action, and their target genes remain largely unknown. We implemented a massively parallel variant annotation pipeline (MVAP) to perform SCZ variant-to-function mapping at scale in disease-relevant neural cell types. This approach identified 620 functional variants (1.7%) that operate in a highly developmental context and neuronal-activity-dependent manner. Multimodal integration of epigenomic and CRISPRi screening data enabled us to link these functional variants to target genes, biological processes, and ultimately alterations of neuronal physiology. These results provide a multistage prioritization strategy to map functional single-nucleotide polymorphism (SNP)-to-gene-to-endophenotype relations and offer biological insights into the context-dependent molecular processes modulated by SCZ-associated genetic variation.

The EN-TEx resource of multi-tissue personal epigenomes & variant-impact models.

Understanding how genetic variants impact molecular phenotypes is a key goal of functional genomics, currently hindered by reliance on a single haploid reference genome. Here, we present the EN-TEx resource of 1,635 open-access datasets from four donors (∼30 tissues × âˆ¼15 assays). The datasets are mapped to matched, diploid genomes with long-read phasing and structural variants, instantiating a catalog of >1 million allele-specific loci. These loci exhibit coordinated activity along haplotypes and are less conserved than corresponding, non-allele-specific ones. Surprisingly, a deep-learning transformer model can predict the allele-specific activity based only on local nucleotide-sequence context, highlighting the importance of transcription-factor-binding motifs particularly sensitive to variants. Furthermore, combining EN-TEx with existing genome annotations reveals strong associations between allele-specific and GWAS loci. It also enables models for transferring known eQTLs to difficult-to-profile tissues (e.g., from skin to heart). Overall, EN-TEx provides rich data and generalizable models for more accurate personal functional genomics.

An antibiotic from an uncultured bacterium binds to an immutable target.

Antimicrobial resistance is a leading mortality factor worldwide. Here, we report the discovery of clovibactin, an antibiotic isolated from uncultured soil bacteria. Clovibactin efficiently kills drug-resistant Gram-positive bacterial pathogens without detectable resistance. Using biochemical assays, solid-state nuclear magnetic resonance, and atomic force microscopy, we dissect its mode of action. Clovibactin blocks cell wall synthesis by targeting pyrophosphate of multiple essential peptidoglycan precursors (C55PP, lipid II, and lipid IIIWTA). Clovibactin uses an unusual hydrophobic interface to tightly wrap around pyrophosphate but bypasses the variable structural elements of precursors, accounting for the lack of resistance. Selective and efficient target binding is achieved by the sequestration of precursors into supramolecular fibrils that only form on bacterial membranes that contain lipid-anchored pyrophosphate groups. This potent antibiotic holds the promise of enabling the design of improved therapeutics that kill bacterial pathogens without resistance development.

Respiratory mucosal delivery of next-generation COVID-19 vaccine provides robust protection against both ancestral and variant strains of SARS-CoV-2.

The emerging SARS-CoV-2 variants of concern (VOCs) threaten the effectiveness of current COVID-19 vaccines administered intramuscularly and designed to only target the spike protein. There is a pressing need to develop next-generation vaccine strategies for broader and long-lasting protection. Using adenoviral vectors (Ad) of human and chimpanzee origin, we evaluated Ad-vectored trivalent COVID-19 vaccines expressing spike-1, nucleocapsid, and RdRp antigens in murine models. We show that single-dose intranasal immunization, particularly with chimpanzee Ad-vectored vaccine, is superior to intramuscular immunization in induction of the tripartite protective immunity consisting of local and systemic antibody responses, mucosal tissue-resident memory T cells and mucosal trained innate immunity. We further show that intranasal immunization provides protection against both the ancestral SARS-CoV-2 and two VOC, B.1.1.7 and B.1.351. Our findings indicate that respiratory mucosal delivery of Ad-vectored multivalent vaccine represents an effective next-generation COVID-19 vaccine strategy to induce all-around mucosal immunity against current and future VOC.

The Unreasonable Effectiveness of Reaction Diffusion in Vertebrate Skin Color Patterning.

In 1952, Alan Turing published the reaction-diffusion (RD) mathematical framework, laying the foundations of morphogenesis as a self-organized process emerging from physicochemical first principles. Regrettably, this approach has been widely doubted in the field of developmental biology. First, we summarize Turing's line of thoughts to alleviate the misconception that RD is an artificial mathematical construct. Second, we discuss why phenomenological RD models are particularly effective for understanding skin color patterning at the meso/macroscopic scales, without the need to parameterize the profusion of variables at lower scales. More specifically, we discuss how RD models (a) recapitulate the diversity of actual skin patterns, (b) capture the underlying dynamics of cellular interactions, (c) interact with tissue size and shape, (d) can lead to ordered sequential patterning, (e) generate cellular automaton dynamics in lizards and snakes, (f) predict actual patterns beyond their statistical features, and (g) are robust to model variations. Third, we discuss the utility of linear stability analysis and perform numerical simulations to demonstrate how deterministic RD emerges from the underlying chaotic microscopic agents.

Microenvironment drives cell state, plasticity, and drug response in pancreatic cancer.

Prognostically relevant RNA expression states exist in pancreatic ductal adenocarcinoma (PDAC), but our understanding of their drivers, stability, and relationship to therapeutic response is limited. To examine these attributes systematically, we profiled metastatic biopsies and matched organoid models at single-cell resolution. In vivo, we identify a new intermediate PDAC transcriptional cell state and uncover distinct site- and state-specific tumor microenvironments (TMEs). Benchmarking models against this reference map, we reveal strong culture-specific biases in cancer cell transcriptional state representation driven by altered TME signals. We restore expression state heterogeneity by adding back in vivo-relevant factors and show plasticity in culture models. Further, we prove that non-genetic modulation of cell state can strongly influence drug responses, uncovering state-specific vulnerabilities. This work provides a broadly applicable framework for aligning cell states across in vivo and ex vivo settings, identifying drivers of transcriptional plasticity and manipulating cell state to target associated vulnerabilities.

Modularity and robustness of frontal cortical networks.

Neural activity underlying short-term memory is maintained by interconnected networks of brain regions. It remains unknown how brain regions interact to maintain persistent activity while exhibiting robustness to corrupt information in parts of the network. We simultaneously measured activity in large neuronal populations across mouse frontal hemispheres to probe interactions between brain regions. Activity across hemispheres was coordinated to maintain coherent short-term memory. Across mice, we uncovered individual variability in the organization of frontal cortical networks. A modular organization was required for the robustness of persistent activity to perturbations: each hemisphere retained persistent activity during perturbations of the other hemisphere, thus preventing local perturbations from spreading. A dynamic gating mechanism allowed hemispheres to coordinate coherent information while gating out corrupt information. Our results show that robust short-term memory is mediated by redundant modular representations across brain regions. Redundant modular representations naturally emerge in neural network models that learned robust dynamics.

High Potency of a Bivalent Human VH Domain in SARS-CoV-2 Animal Models.

Novel COVID-19 therapeutics are urgently needed. We generated a phage-displayed human antibody VH domain library from which we identified a high-affinity VH binder ab8. Bivalent VH, VH-Fc ab8, bound with high avidity to membrane-associated S glycoprotein and to mutants found in patients. It potently neutralized mouse-adapted SARS-CoV-2 in wild-type mice at a dose as low as 2 mg/kg and exhibited high prophylactic and therapeutic efficacy in a hamster model of SARS-CoV-2 infection, possibly enhanced by its relatively small size. Electron microscopy combined with scanning mutagenesis identified ab8 interactions with all three S protomers and showed how ab8 neutralized the virus by directly interfering with ACE2 binding. VH-Fc ab8 did not aggregate and did not bind to 5,300 human membrane-associated proteins. The potent neutralization activity of VH-Fc ab8 combined with good developability properties and cross-reactivity to SARS-CoV-2 mutants provide a strong rationale for its evaluation as a COVID-19 therapeutic.

A Mouse-Adapted SARS-CoV-2 Induces Acute Lung Injury and Mortality in Standard Laboratory Mice.

The SARS-CoV-2 pandemic has caused extreme human suffering and economic harm. We generated and characterized a new mouse-adapted SARS-CoV-2 virus that captures multiple aspects of severe COVID-19 disease in standard laboratory mice. This SARS-CoV-2 model exhibits the spectrum of morbidity and mortality of COVID-19 disease as well as aspects of host genetics, age, cellular tropisms, elevated Th1 cytokines, and loss of surfactant expression and pulmonary function linked to pathological features of acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). This model can rapidly access existing mouse resources to elucidate the role of host genetics, underlying molecular mechanisms governing SARS-CoV-2 pathogenesis, and the protective or pathogenic immune responses related to disease severity. The model promises to provide a robust platform for studies of ALI and ARDS to evaluate vaccine and antiviral drug performance, including in the most vulnerable populations (i.e., the aged) using standard laboratory mice.