Peripheral serotonergic signaling has been implicated in diverse physiological processes, yet its role in coordinating glial-immune interactions remains poorly understood. In this issue of Cell, Wen and colleagues identify enteric glial cells as critical effectors of peripheral 5-HT2AR agonism, uncovering a serotonergic neuroimmune circuit that drives cytotoxic T cell-mediated immunity against colorectal cancer.
Gustatory systems drive critical survival behaviors such as feeding, foraging, and social interactions. However, gustation remains one of the least mapped sensory modalities at the connectome level. Here, we present the first complete wiring diagram of the male Drosophila adult gustatory system, comprehensively reconstructing gustatory receptor neurons (GRNs) from peripheral organs in a contiguous electron microscopy volume spanning brain, cervical connective, and ventral nerve cord. Integrating this with existing datasets, we generated a pan-central nervous system (CNS), cross-sex connectome that reveals GRN diversity through connectivity-based clustering, molecular identity mapping, and sexual dimorphism analysis. We mapped all feeding motor neurons and traced complete sensory-to-motor pathways to feeding, foraging, endocrine, and social behavior circuits. The emerging circuit architectures reveal distinct circuits for nutrient assessment, motor control, neuroendocrine regulation, and courtship. This work defines the gustatory system's organization at synaptic resolution and provides a framework for understanding how internal states modulate sensory-driven decisions across behavioral contexts.
Iron abundance alone does not determine ferroptosis sensitivity. In this issue of Cell, Sharma and colleagues identify polyamines as endogenous metabolic buffers that reduce the chemical accessibility of labile iron, revealing an unexpected function for one of the cell's most abundant metabolite classes while raising new questions about the organization of intracellular iron metabolism.
Beginning approximately 4,000 years ago, southwest-Asian-originating domesticated crops and livestock began appearing in Gansu, a key crossroads in northwestern China, yet the population dynamics and social practices underlying these historically transformative events in the region have not been fully explored. Despite the adoption of western domesticates, genome sequences of 149 individuals from the large Mogou cemetery and ten other sites in Gansu, dating between 4,700 and 3,000 years ago, revealed migrations within East Asian regions but no detectable evidence of genetic influence from western or central Eurasia, suggesting that early agricultural dispersals may have followed a model distinct from that documented in Europe and Central Asia. The Mogou cemetery represents a continuous community that interacted with surrounding regions but does not exhibit clear matrilocal or patrilocal residential patterns. We found no strong evidence that co-buried individuals represented biological relatives. Non-local ancestry appears to be linked to lower-status burial practices.
Whether tissue injury resolves or progresses to chronic scarring is determined by regulatory choices that remain only partially understood. In this review, we propose that immune cells and fibroblasts function as dynamic interpreters of intercellular cues, integrating these signals through chromatin-regulated gene circuits that govern cell state and fate. Drawing on insights from cardiac biology and from settings where tissues regenerate or resolve injury without scarring, we outline a molecular framework in which immune-stromal crosstalk and gene regulatory networks dictate the choice between recovery and chronic fibrosis across organs, including the heart, lung, liver, and kidney. Reframing fibrosis as a reversible state shaped by disrupted regulatory logic opens therapeutic avenues that move beyond suppressing fibrotic outputs toward rewiring the regulatory programs that sustain them.
The Tabula Sapiens is a reference human cell atlas containing single-cell transcriptomic data from more than two dozen organs and tissues. Here, we report Tabula Sapiens 2.0, which includes data from nine new donors, doubles the number of cells, and adds four new tissues. These new data include four donors with multiple organs contributed, thus providing a unique dataset in which genetic background, age, and epigenetic effects are controlled for. We illustrate applications of the Tabula Sapiens data in areas as diverse as gene regulation and aging. The Tabula Sapiens contains transcripts from nearly all human transcription factors, thereby providing putative cell-type specificity for nearly every human transcription factor and insights into their potential regulatory roles. We also analyze the transcriptomes of cells expressing canonical genes relating to cellular senescence, revealing the heterogeneity and context-dependent nature of senescence and providing new hypotheses into senescence-associated pathways.
The striatum is critical for decision-making, movement, and reward processing, functions achieved through subregional cellular and molecular specialization. Striatal cell types and subregions are differentially implicated in neurodegenerative and neuropsychiatric disorders, but the mechanisms underlying these vulnerabilities are poorly understood. Using single-nucleus RNA sequencing across 109 human and 22 mouse samples spanning dorsal and ventral striatum, we provide a comprehensive atlas of subregional neuronal specialization. We define rare neuronal subpopulations and transcriptional gradients along the dorsolateral-ventromedial axis with notable differences between species, suggesting divergent pharmacological targets, connectivity, and disease mechanisms. Integration with genome-wide association and pharmacological studies identifies human-enriched sites of opioid receptor expression and ventral-biased chronic antipsychotic action. Lastly, paired single-cell transcriptomic and somatic trinucleotide repeat expansion measurements identify differences in subregion and neuronal subtype vulnerability in Huntington's disease. Our findings lay the foundation for understanding how striatal cell types and subregions contribute to brain function and neurological disorders.
Symbiotic gut bacteria must re-establish themselves in every host generation, yet the molecular strategies enabling this inheritance remain poorly understood. Here, we show that Bacteroides fragilis uses a membrane glycolipid, alpha-galactosylceramide (BfaGC), to colonize the neonatal gut. Genome-wide fitness profiling revealed that BfaGC biosynthesis is selectively required during early life, when transient oxygenation creates a physiological bottleneck for strict anaerobes. Mechanistically, BfaGC reduces membrane proton permeability, sustaining the proton-motive force that supports aerobic respiration. This oxygen-responsive adaptation simultaneously generates a host-facing immunomodulatory signal that calibrates neonatal natural killer T (NKT) cell development, linking bacterial fitness to immune maturation through a single metabolite. The same mechanism also enables niche expansion by enterotoxigenic strains, revealing context-dependent consequences. Notably, this strategy is distinct among gut Bacteroidales: other prominent members synthesize a different sphingolipid subclass supporting broader fitness, implying divergent evolutionary strategies. Our findings provide time-resolved insight into how bacterial metabolites shape host-microbiota symbiosis across development.
Fluorescent imaging in live cells is a cornerstone of life sciences. While natural fluorescent proteins have been engineered to enhance individual features, no existing tag combines ideal properties into a single system: high brightness, reversible binding, compact size, and stability across diverse conditions. Here, we achieve this through de novo design of rhodamine binders (Rhobin). To harness the broad repertoire of rhodamine fluorophores, we developed a generalizable design strategy for a pan-rhodamine binder compatible with diverse wavelengths and applications. Rhobin enables live- and fixed-cell imaging of various subcellular targets in mammalian cells, showing brightness surpassing existing tags. Its reversible fluorophore binding supports super-resolution stimulated emission depletion (STED) and live-cell single-molecule imaging for extended durations compared with HaloTag. Beyond conventional systems, Rhobin enables live imaging of the extremophile Sulfolobus acidocaldarius at 75°C, previously inaccessible with current tags. Together, these results establish Rhobin as a versatile platform for next-generation imaging and biosensor design.
While machine learning models offer potential for predicting transcriptomic effects of perturbation, they currently struggle to generalize across cellular contexts. Here, we introduce State, a machine learning model that predicts perturbation effects while accounting for cellular heterogeneity within and across experiments. State is trained using single-cell gene expression data to predict perturbation effects across sets of cells. State improved discrimination of effects on large datasets by more than 30% and identified differentially expressed genes across genetic, signaling, and chemical perturbations with significantly improved accuracy compared with baselines. Its cell embeddings trained on observational data from 167 million cells enable the identification of strong perturbations in cellular contexts where no perturbations were observed during training. We further introduce Cell-Eval, a comprehensive evaluation framework that can be used to evaluate future models. Overall, the performance and flexibility of State set the stage for scaling the development of AI models of cell state.
Ribonucleoside monophosphates (rNMPs) are the most abundant non-canonical nucleotides in DNA, yet their distribution and function in the human nuclear genome remain unclear. We present high-resolution maps of ∼1 million rNMPs per genome across diverse human cells, revealing a non-random nuclear "ribome," the genome-wide landscape of embedded rNMPs, enriched in GC-rich regions, regulatory elements, and telomeres. Ribonucleotide-enriched zones (REZs) cluster near transcription start sites (TSSs), coincide with C-phosphate-G (CpG) islands, R-loops, and G4 structures, and scale with gene expression. Ribonuclease (RNase) H2 deficiency increases rGMP levels and is associated with topoisomerase 1 (Top1)-dependent, strand-biased rNMP enrichment near TSSs, while Top1 depletion further enhances rGMP accumulation. RNase H2-mediated nicking at rNMPs alters DNA supercoiling in vitro, and RNH2A-deficient cells show altered supercoiling at rNMP-enriched TSSs. Our findings identify embedded rNMPs as epigenetic modulators of DNA supercoiling linked to DNA sequence and transcription, revealing a connection between ribonucleotide processing and transcription-associated DNA topology in human cells.
Gut bacteria affect host physiology, but the underlying mechanisms are not completely understood. We identify a pathway whereby gut microbes convert inorganic nitrate and non-heme iron into mobile bioactive dinitrosyl iron complexes (DNICs) that are distributed systemically and affect host metabolism. Electron paramagnetic resonance detected DNICs in tissues of conventional but not germ-free mice. Mouse and human feces and E. coli generated DNICs from nitrate and iron citrate, whereas a nitrate-reductase-deficient mutant did not. Dietary supplementation with nitrate+iron citrate or synthetic DNICs increased tissue DNIC levels and ameliorated cardiometabolic dysfunction in Western diet-fed mice. Additionally, in HepG2 cells and human hepatocyte spheroids, DNIC reduced fatty acid-induced steatosis. DNIC bioactivity is mediated by the Fe(NO)2 entity, rather than by free nitric oxide (NO), and involves activation of soluble guanylyl cyclase (sGC), inhibition of leucine uptake, and mTORC1 signaling normalization. Modulating DNIC formation by the gut microbiota could be a strategy to support cardiometabolic health.
Viral genomes encode regulatory RNA structures that orchestrate key steps of viral replication and gene expression. Although these structures are increasingly recognized as critical regulators of viral function, their systematic characterization in an infection context and roles in regulating viral fitness and immune recognition in vivo remain limited. Here, we systematically map and functionally interrogate structured RNA elements across the murine norovirus genome using orthogonal in-cell chemical probing, revealing conserved motifs that regulate viral function. Targeted disruption of specific structural elements reduces viral replication in cell culture, modulates translation in cis, and decreases viral RNA levels in animal infection models. These findings enabled the rational design of a genetically stable, attenuated virus that elicits protective immunity and limits viral replication upon secondary challenge. Together, this work uncovers essential roles for RNA structure in norovirus biology and establishes a generalizable framework for RNA structure-guided design of antiviral vaccines and therapeutics.
Human protein-coding genes evolved via rearrangement of domains from ancestral genes. We develop a scalable, evolutionarily guided method to assemble novel genes from constituent domains within a protein family, termed DESynR (domain engineered via synthesis and recombination) genes. In primary human T cells, DESynR activator protein-1 (AP-1) transcription factors (TFs) significantly outperform natural AP-1 TFs across in vitro and in vivo antitumor assays. DESynR AP-1 TFs induce broad transcriptional and epigenetic reprogramming and establish non-natural T cell states that optimize features of exhaustion, effector and cytotoxic function, and persistence—sometimes co-opting gene modules from disparate cell types. Reprogramming is primarily driven by differential regulation of established AP-1-bound regulatory elements rather than unique binding. Finally, we screen DESynR erythroblast transformation-specific (ETS) and forkhead box (FOX) TFs to support generalizability across protein families. Overall, we demonstrate that reconfiguring existing protein domains may uncover non-evolved genes that program therapeutically relevant cell states.
High-throughput single-cell omics of non-human primate brain tissue provides a powerful platform to investigate the molecular basis of brain aging. Here, we present a comprehensive transcriptomic and chromatin accessibility atlas of 2,955,873 nuclei from eight brain regions of 23 female cynomolgus macaques spanning the adult lifespan, including exceptionally old individuals. Our analyses reveal dynamic, cell-subtype- and region-specific age-related changes in core brain functions, including synaptic communication and axon myelination. We identify multicellular networks in the pons and medulla as a previously unrecognized hotspot of primate brain aging, highlighting white matter vulnerability as a central feature of aging. Integration with human brain aging and neurodegeneration datasets reveals both shared and divergent molecular mechanisms. We further define transcription factors and age-related chromatin remodeling programs linked to longevity and neurodegeneration. This spatiotemporal atlas establishes a foundational framework for understanding the cellular and regulatory architecture of primate brain aging and its links to disease.
Generative AI (Gen-AI) has shown a remarkable impact in several biological research areas, from protein folding and de novo design to pathogenic mutation prediction. However, it remains unclear whether these molecular-level successes can translate to cellular and multicellular insights relevant to fields ranging from immunology to cancer and neurodegeneration. This arises from the intricate nature of the molecular mechanisms that determine cellular and organismal behavior, the lack of sufficient training data, and the multicellular nature of most pathophysiologic phenotypes. Novel Gen-AI frameworks are likely needed to integrate prior biological knowledge, such as molecular interaction networks, as well as guiding principles focusing the community’s attention on solving biologically and translationally relevant problems. Drawing inspiration from Hilbert’s list of 23 mathematical problems that have focused the mathematical community’s attention for more than a century, we propose fifteen grand AI challenges to focus the biomedical community’s attention on critically relevant questions, most of which still lack effective predictive methodologies.
