The COVID-19 pandemic highlighted the critical need for vaccine strategies capable of addressing emerging viral threats. Betacoronaviruses, including severe acute respiratory syndrome coronavirus (SARS-CoV), Middle East respiratory syndrome (MERS), and SARS-CoV-2, present significant pandemic risks due to their zoonotic potential and genetic diversity. T cell-mediated immunity has demonstrated durable responses and strong cross-reactivity, offering a promising avenue for achieving broad immunity within a viral family. In this study, we combined comprehensive epitope mapping with sequence conservation analyses to identify conserved T cell epitope regions (CTERs), which constitute 12% of the complete SARS-CoV-2 proteome. We showed that SARS-CoV-2 CTER-specific T cells cross-reactively recognize sequences from multiple Betacoronavirus subgenera. Importantly, incorporating CTERs from non-spike proteins significantly enhanced T cell cross-reactivity potential and human leukocyte antigen (HLA) coverage compared with T cells targeting only spike proteins. Our findings lay the groundwork for a multi-antigen vaccine strategy that includes non-spike proteins to expand cross-reactive immunity across a broader spectrum of Betacoronaviruses.

The prime editing (PE) system consists of a Cas9 nickase fused to a reverse transcriptase, which introduces precise edits into the target genomic region guided by a PE guide RNA. However, PE efficiency is limited by mismatch repair. To overcome this limitation, transient expression of a dominant-negative MLH1 (MLH1dn) has been used to inhibit key components of mismatch repair. Here, we designed a de novo MLH1 small binder (MLH1-SB) that binds to the dimeric interface of MLH1 and PMS2 using RFdiffusion and AlphaFold 3. The compact size of MLH1-SB enabled its integration into existing PE architectures via 2A systems, creating a PE-SB platform. The PE7-SB2 system significantly improved PE efficiency, achieving an 18.8-fold increase over PEmax and a 2.5-fold increase over PE7 in HeLa cells, as well as a 3.4-fold increase over PE7 in mice. This study highlights the potential of generative AI in advancing genome editing technology.

Alzheimer's disease (AD) is a neurodegenerative disorder characterized by progressive cognitive decline, yet its epigenetic underpinnings remain elusive. Here, we generate and integrate single-cell epigenomic and transcriptomic profiles of 3.5 million cells from 384 postmortem brain samples across 6 regions in 111 AD and control individuals. We identify over 1 million candidate cis-regulatory elements (cCREs), organized into 123 regulatory modules across 67 cell subtypes. We define large-scale epigenomic compartments and single-cell epigenomic information and delineate their dynamics in AD, revealing widespread epigenome relaxation and brain-region-specific and cell-type-specific epigenomic erosion signatures during AD progression. These epigenomic stability dynamics are closely associated with cell-type proportion changes, glial cell-state transitions, and coordinated epigenomic and transcriptomic dysregulation linked to AD pathology, cognitive impairment, and cognitive resilience. This study provides critical insights into AD progression and cognitive resilience, presenting a comprehensive single-cell multiomic atlas to advance the understanding of AD.

The rational design of receptor agonists to control cell signaling is an emerging strategy for developing disease therapeutics. Creating a soluble cytokine-like agonist for the Notch receptor, which regulates cell fate in embryonic and adult development, is challenging, as receptor activation requires a mechanical force that is usually mediated by cell-associated transmembrane ligands. Here, we exploit computationally designed protein complexes with precise valencies and geometries to generate soluble cytokine-like Notch agonists. These molecules promote cell-cell bridging, cluster Notch receptors at cell synapses, and activate receptor signaling. We show that these agonists drive T cell differentiation from cord blood progenitors and human induced pluripotent stem cells (iPSCs) and in bioreactor production of T cells in liquid suspension. When delivered intravenously in mice, they stimulate cytokine production, expansion of antigen-specific CD4+ T cells, and antibody class switching. These de-novo-designed ligands can be broadly applied to optimize in vitro cell differentiation and advance immunotherapy development.

Interspecific hybridization may trigger species radiation by creating allele combinations and traits. Cultivated potato and its 107 wild relatives from the Petota lineage all share the distinctive trait of underground tubers, but the underlying mechanisms for tuberization and its relationship to extensive species diversification remain unclear. Through analyses of 128 genomes, including 88 haplotype-resolved genomes, we revealed that Petota is of ancient hybrid origin, with all members exhibiting stable mixed genomic ancestry, derived from the Etuberosum and Tomato lineages ca. 8-9 million years ago. Our functional experiments further validated the crucial roles of parental genes in tuberization, indicating that interspecific hybridization is a key driver of this innovative trait. This trait, along with the sorting and recombination of hybridization-derived polymorphisms, likely triggered the explosive species diversification of Petota by enabling occupation of broader ecological niches. These findings highlight how ancient hybridization fosters key innovation and drives subsequent species radiation.

Fermentation products released by the gut microbiota provide energy and regulatory functions to the host. Yet, little is known about the magnitude of this metabolic flux and its quantitative dependence on diet and microbiome composition. Here, we establish orthogonal approaches to consistently quantify this flux, integrating data on bacterial metabolism, digestive physiology, and metagenomics. From the nutrients fueling microbiota growth, most carbon ends up in fermentation products and is absorbed by the host. This harvest varies strongly with the amount of complex dietary carbohydrates and is largely independent of bacterial mucin and protein utilization. It covers 2%-5% of human energy demand for Western diets and up to 10% for non-Western diets. Microbiota composition has little impact on the total harvest but determines the amount of specific fermentation products. This consistent quantification of metabolic fluxes by our analysis framework is crucial to elucidate the gut microbiota's mechanistic functions in health and disease.

Despite the remarkable fidelity of eukaryotic DNA replication, nucleotide misincorporation errors occur in every replication cycle, generating mutations that drive genetic diseases and genome evolution. Here, we show that transcription factor (TF) proteins, key players in gene regulation, can increase mutagenesis from replication errors by directly competing with the recognition of DNA mismatches by MutSα, the primary initiator of eukaryotic mismatch repair (MMR). We demonstrate this TF-induced mutagenesis mechanism using a yeast genetic assay that quantifies the accumulation of mutations in TF binding sites. Analyses of human cancer mutations recapitulate the trends observed in yeast, with mutations arising from MYC-bound mismatches being enriched in MMR-proficient cells. These findings implicate TF-MMR competition as a critical determinant of somatic hypermutation at TF binding sites in cancer. Furthermore, our results provide a molecular mechanism for the higher-than-expected rate of rare genetic variants at TF binding sites, with important implications for regulatory DNA evolution.

Bacteria and archaea deploy diverse antiviral defense systems, many of which remain mechanistically uncharacterized. Here, we characterize Kiwa, a widespread two-component system composed of the transmembrane sensor KwaA and the DNA-binding effector KwaB. Cryogenic electron microscopy (cryo-EM) analysis reveals that KwaA and KwaB assemble into a large, membrane-associated supercomplex. Upon phage binding, KwaA senses infection at the membrane, leading to KwaB binding of ejected phage DNA and inhibition of replication and late transcription, without inducing host cell death. Although KwaB can bind DNA independently, its antiviral activity requires association with KwaA, suggesting spatial or conformational regulation. We show that the phage-encoded DNA-mimic protein Gam directly binds and inhibits KwaB but that co-expression with the Gam-targeted RecBCD system restores protection by Kiwa. Our findings support a model in which Kiwa coordinates membrane-associated detection of phage infection with downstream DNA binding by its effector, forming a spatially coordinated antiviral mechanism.

Secreted proteins are central mediators of intercellular communications and can serve as therapeutic targets in diverse diseases. The ∼1,903 human genes encoding secreted proteins are difficult to study through common genetic approaches. To address this hurdle and, more generally, to discover cancer therapeutics, we developed the Cancer Immunology Data Engine (CIDE, https://cide.ccr.cancer.gov), which incorporates 90 omics datasets spanning 8,575 tumor profiles with immunotherapy outcomes from 17 solid tumor types. CIDE systematically identifies all genes associated with immunotherapy outcomes. Then, we focused on secreted proteins prioritized by CIDE without known cancer roles and validated regulatory effects on immune checkpoint blockade for AOAH, CR1L, COLQ, and ADAMTS7 in mouse models. The top hit, acyloxyacyl hydrolase (AOAH), potentiates immunotherapies in multiple tumor models by sensitizing T cell receptors to weak antigens and protecting dendritic cells through depleting immunosuppressive arachidonoyl phosphatidylcholines and oxidized derivatives.

Cells interact as dynamically evolving ecosystems. While recent single-cell and spatial multi-omics technologies quantify individual cell characteristics, predicting their evolution requires mathematical modeling. We propose a conceptual framework-a cell behavior hypothesis grammar-that uses natural language statements (cell rules) to create mathematical models. This enables systematic integration of biological knowledge and multi-omics data to generate in silico models, enabling virtual "thought experiments" that test and expand our understanding of multicellular systems and generate new testable hypotheses. This paper motivates and describes the grammar, offers a reference implementation, and demonstrates its use in developing both de novo mechanistic models and those informed by multi-omics data. We show its potential through examples in cancer and its broader applicability in simulating brain development. This approach bridges biological, clinical, and systems biology research for mathematical modeling at scale, allowing the community to predict emergent multicellular behavior.

Cerebrospinal fluid (CSF) flow is essential for brain homeostasis, and its disruption is implicated in neurodegenerative and neuroinflammatory diseases. Arachnoid cuff exit (ACE) points, anatomical discontinuities in the arachnoid mater around bridging veins, serve as key sites of CSF-dura exchange. Here, we show that dural mast cells regulate CSF dynamics at ACE points. Upon degranulation, mast cells release histamine, inducing vasodilation of bridging veins and reducing perivascular spaces critical for CSF drainage. During bacterial meningitis, pathogens exploit ACE points to access the brain. However, mast cell activation redirects CSF flow, recruits neutrophils, and limits bacterial invasion. Mice lacking dural mast cells exhibit impaired immune responses and higher brain bacterial loads. These findings reveal dural mast cells as central players in modulating CSF flow and meningeal immunity. Targeting mast cells or their mediators may enhance CNS clearance and defense mechanisms, offering a potential therapeutic avenue for brain infections.

The immune environment surrounding the brain plays a fundamental role in monitoring signs of injury. Insults, including ischemic stroke, can disrupt this balance and incite an exaggerated inflammatory response, yet the underlying mechanism remains unclear. Here, we show that the mast-cell-specific receptor Mrgprb2 regulates post-stroke brain inflammation from the meninges. Mrgprb2 causes meningeal mast cell degranulation after stroke, releasing immune mediators. This process recruits skull bone marrow neutrophils into the dura and further promotes neutrophil migration from the dura into the brain by cleaving the chemorepellent semaphorin 3a. We demonstrate that the human ortholog, MRGPRX2, is expressed in human meningeal mast cells and is activated by upregulation of the neuropeptide substance P following stroke. Pharmacologically inhibiting Mrgprb2 reduces post-stroke inflammation and improves neurological outcomes in mice, providing a druggable target. Collectively, our study identifies Mrgprb2 as a critical meningeal gatekeeper for immune migration from skull bone marrow reservoirs into the brain.

Cryptosporidium is a leading cause of diarrheal disease, yet little is known regarding the infection cell biology of this intracellular intestinal parasite. To this end, we implemented an arrayed genome-wide CRISPR-Cas9 knockout screen to microscopically analyze multiple phenotypic features of a Cryptosporidium infection following individual host gene ablation. We discovered parasite survival within the host epithelial cell hinges on squalene, an intermediate metabolite in the host cholesterol biosynthesis pathway. A buildup of squalene within intestinal epithelial cells creates a reducing environment, making more reduced glutathione available for parasite uptake. Remarkably, the Cryptosporidium parasite has lost the ability to synthesize glutathione and has become dependent on this host import. This dependency can be leveraged for treatment with the abandoned drug lapaquistat, an inhibitor of host squalene synthase that shifts the redox environment, blocking Cryptosporidium growth in vitro and in vivo.

RNA-binding proteins (RBPs) regulate all stages of the mRNA life cycle, yet current methods generally map RNA targets of RBPs one protein at a time. To overcome this limitation, we developed SPIDR (split-and-pool identification of RBP targets), a highly multiplexed split-pool method that profiles the binding sites of dozens of RBPs simultaneously. SPIDR identifies precise, single-nucleotide binding sites for diverse classes of RBPs. Using SPIDR, we uncovered an interaction between LARP1 and the 18S rRNA and resolved this interaction to the mRNA entry channel of the 40S ribosome using cryoelectron microscopy (cryo-EM), providing a potential mechanistic explanation for LARP1's role in translational suppression. We explored changes in RBP binding upon mTOR inhibition and identified that 4EBP1 preferentially associates with translationally repressed mRNAs upon mTOR inhibition. SPIDR has the potential to significantly advance our understanding of RNA biology by enabling rapid, de novo discovery of RNA-protein interactions at an unprecedented scale.

Duplicated genes expanded in the human lineage likely contributed to brain evolution, yet challenges exist in their discovery due to sequence-assembly errors. We used a complete telomere-to-telomere genome sequence to identify 213 human-specific gene families. From these, 362 paralogs were found in all modern human genomes tested and brain transcriptomes, making them top candidates contributing to human-universal brain features. Choosing a subset of paralogs, long-read DNA sequencing of hundreds of modern humans revealed previously hidden signatures of selection, including for T cell marker CD8B. To understand roles in brain development, we generated zebrafish CRISPR "knockout" models of nine orthologs and introduced mRNA-encoding paralogs, effectively "humanizing" larvae. Our findings implicate two genes in possibly contributing to hallmark features of the human brain: GPR89B in dosage-mediated brain expansion and FRMPD2B in altered synapse signaling. Our holistic approach provides insights and a comprehensive resource for studying gene expansion drivers of human brain evolution.

In cancer cachexia, the presence of a tumor triggers systemic metabolic disruption that leads to involuntary body weight loss and accelerated mortality in affected patients. Here, we conducted transcriptomic and epigenomic profiling of the liver in various weight-stable cancer and cancer cachexia models. An integrative multilevel analysis approach identified a distinct gene expression signature that included hepatocyte-secreted factors and the circadian clock component REV-ERBα as key modulator of hepatic transcriptional reprogramming in cancer cachexia. Notably, hepatocyte-specific genetic reconstitution of REV-ERBα in cachexia ameliorated peripheral tissue wasting. This improvement was associated with decreased levels of specific cachexia-controlled hepatocyte-secreted factors. These hepatokines promoted catabolism in multiple cell types and were elevated in cachectic cancer patients. Our findings reveal a mechanism by which the liver contributes to peripheral tissue wasting in cancer cachexia, offering perspectives for future therapeutic interventions.

Alternating hemiplegia of childhood (AHC) is a neurodevelopmental disorder with no disease-modifying treatment. Mutations in ATP1A3, encoding an Na+/K+ ATPase subunit, cause 70% of AHC cases. Here, we present prime editing (PE) and base editing (BE) strategies to correct ATP1A3 and Atp1a3 mutations in human cells and in two AHC mouse models. We used PE and BE to correct five prevalent ATP1A3 mutations with 43%-90% efficiency. AAV9-mediated in vivo PE corrects Atp1a3 D801N and E815K in the CNS of two AHC mouse models, yielding up to 48% DNA correction and 73% mRNA correction in bulk brain cortex. In vivo PE rescued clinically relevant phenotypes, including restoration of ATPase activity; amelioration of paroxysmal spells, motor defects, and cognition deficits; and dramatic extension of animal lifespan. This work suggests a potential one-time PE treatment for AHC and establishes the ability of PE to rescue a neurological disease in animals.

Alzheimer's disease (AD) is a multifactorial neurodegenerative disorder characterized by heterogeneous molecular changes across diverse cell types, posing significant challenges for treatment development. To address this, we introduced a cell-type-specific, multi-target drug discovery strategy grounded in human data and real-world evidence. This approach integrates single-cell transcriptomics, drug perturbation databases, and clinical records. Using this framework, letrozole and irinotecan were identified as a potential combination therapy, each targeting AD-related gene expression changes in neurons and glial cells, respectively. In an AD mouse model with both Aβ and tau deposits, this combination therapy significantly improved memory performance and reduced AD-related pathologies compared with vehicle and single-drug treatments. Single-nucleus transcriptomic analysis confirmed that the therapy reversed disease-associated gene networks in a cell-type-specific manner. These results highlight the promise of cell-type-directed combination therapies in addressing multifactorial diseases like AD and lay the groundwork for precision medicine tailored to patient-specific transcriptomic and clinical profiles.

Inflammation is an essential defense response but operates at the cost of normal tissue functions. Whether and how the negative impact of inflammation is monitored remains largely unknown. Acidification of the tissue microenvironment is associated with inflammation. Here, we investigated whether macrophages sense tissue acidification to adjust inflammatory responses. We found that acidic pH restructured the inflammatory response of macrophages in a gene-specific manner. We identified mammalian BRD4 as an intracellular pH sensor. Acidic pH disrupts transcription condensates containing BRD4 and MED1 via histidine-enriched intrinsically disordered regions. Crucially, a decrease in macrophage intracellular pH is necessary and sufficient to regulate transcriptional condensates in vitro and in vivo, acting as negative feedback to regulate the inflammatory response. Collectively, these findings uncovered a pH-dependent switch in transcriptional condensates that enables environment-dependent control of inflammation, with a broader implication for calibrating the magnitude and quality of inflammation by the inflammatory cost.