The development of a multicellular organism is a highly intricate process tightly regulated by numerous genes and pathways in both spatial and temporal manners. Here, we present Flysta3D-v2, a comprehensive multi-omics atlas of the model organism Drosophila spanning its developmental lifespan from embryo to pupa. Our datasets encompass 3D single-cell spatial transcriptomic, single-cell transcriptomic, and single-cell chromatin accessibility information. Through the integration of multimodal data, we generated developmentally continuous in silico 3D models of the entire organism. We further constructed tissue development trajectories that uncover the detailed profiles of cell-type differentiation. With a focus on the midgut, we identified transcription factors involved in midgut cell-type regulation and validated exex as a key regulator of copper cell development. This extensive atlas provides a rich resource and serves as a systematic platform for studying Drosophila development with integrated single-cell data at ultra-high spatiotemporal resolution.

India has been underrepresented in genomic surveys. We generated whole-genome sequences from 2,762 individuals in India, capturing the genetic diversity across most geographic regions, linguistic groups, and historically underrepresented communities. We find most Indians harbor ancestry primarily from three ancestral groups: South Asian hunter-gatherers, Eurasian Steppe pastoralists, and Neolithic farmers related to Iranian and Central Asian cultures. The extensive homozygosity and identity-by-descent sharing among individuals reflects strong founder events due to a recent shift toward endogamy. We uncover that most of the genetic variation in Indians stems from a single major migration out of Africa that occurred around 50,000 years ago, followed by 1%-2% gene flow from Neanderthals and Denisovans. Notably, Indians exhibit the largest variation and possess the highest amount of population-specific Neanderthal ancestry segments among worldwide groups. Finally, we discuss how this complex evolutionary history has shaped the functional and disease variation on the subcontinent.

Virtual cells are an emerging frontier at the intersection of artificial intelligence and biology. A key goal of these cell state models is predicting cellular responses to perturbations. The Virtual Cell Challenge is being established to catalyze progress toward this goal. This recurring and open benchmark competition from the Arc Institute will provide an evaluation framework, purpose-built datasets, and a venue for accelerating model development.

Eukaryotic life evolved over a billion years ago when ancient cells engulfed and integrated prokaryotes to become modern mitochondria and chloroplasts. Sacoglossan "solar-powered" sea slugs possess the ability to acquire organelles within a single lifetime by selectively retaining consumed chloroplasts that remain photosynthetically active for nearly a year. The mechanism for this "animal photosynthesis" remains unknown. Here, we discovered that foreign chloroplasts are housed within novel, host-derived organelles we term "kleptosomes." Kleptosomes use ATP-sensitive ion channels to maintain a luminal environment that supports chloroplast photosynthesis and longevity. Upon slug starvation, kleptosomes digest stored chloroplasts for additional nutrients, thereby serving as a food source. We leveraged this discovery to find that organellar retention and digestion of photosynthetic cargo has convergently evolved in other photosynthetic animals, including corals and anemones. Thus, our study reveals mechanisms underlying the long-term acquisition and evolutionary incorporation of intracellular symbionts into organelles that support complex cellular function.

The Nidovirus RdRp-associated nucleotidyltransferase (NiRAN) domain initiates mRNA capping in coronaviruses through a GDP-polyribonucleotidyltransferase reaction, with RNA covalently linked to nsp9. GDP is the preferred substrate for this reaction, but the NiRAN domain can also utilize GTP to produce an authentic 5' RNA cap structure, though the GTP-mediated mechanism is unclear. Yan and colleagues claimed to have delineated the reaction mechanism from the analysis of a cryoelectron microscopy (cryo-EM) structure of a trapped catalytic intermediate of the SARS-CoV-2 NiRAN domain with a β-γ-non-hydrolyzable GTP analog (GMPPNP) and RNA-nsp9 (PDB: 8GWE). We show that the cryo-EM data used to derive PDB: 8GWE do not support the presence of GMPPNP in the NiRAN active site, and the resulting atomic model is incompatible with fundamental chemical principles. We conclude that Yan and colleagues' conclusions are not experimentally supported and the mechanism for GTP-mediated RNA capping by the SARS-CoV-2 NiRAN domain remains unresolved. This Matters Arising paper is in response to Yan et al. (2022), published in Cell. See also the response by Huang et al. (2025), published in this issue.

Sleep is known to promote tissue growth and regulate metabolism, partly by enhancing growth hormone (GH) release, but the underlying circuit mechanism is unknown. We demonstrate how GH release, which is enhanced during both rapid eye movement (REM) and non-REM (NREM) sleep, is regulated by sleep-wake-dependent activity of distinct hypothalamic neurons expressing GH-releasing hormone (GHRH) and somatostatin (SST). SST neurons in the arcuate nucleus suppress GH release by inhibiting nearby GHRH neurons that stimulate GH release, whereas periventricular SST neurons inhibit GH release by projecting to the median eminence. GH release is associated with strong surges of both GHRH and SST activity during REM sleep but moderately increased GHRH and decreased SST activity during NREM sleep. Furthermore, we identified a negative feedback pathway in which GH enhances the excitability of locus coeruleus neurons and increases wakefulness. These results elucidate a circuit mechanism underlying bidirectional interactions between sleep and hormone regulation.

Biased agonism of G protein-coupled receptors (GPCRs) offers potential for safer medications. Current efforts have explored the balance between G proteins and β-arrestin; however, other transducers like GPCR kinases (GRKs) remain understudied. GRK2 is essential for β2 adrenergic receptor (β2AR)-mediated glucose uptake, but β2AR agonists are considered poor clinical candidates for glycemic management due to Gs/cyclic AMP (cAMP)-induced cardiac side effects and β-arrestin-dependent desensitization. Using ligand-based virtual screening and chemical evolution, we developed pathway-selective agonists of β2AR that prefer GRK coupling. These compounds perform well in preclinical models of hyperglycemia and obesity and demonstrate a lower potential for cardiac and muscular side effects compared with standard β2-receptor agonists and incretin mimetics, respectively. Furthermore, the lead candidate showed favorable pharmacokinetics and was well tolerated in a placebo-controlled clinical trial. GRK-biased β2AR partial agonists are thus promising oral alternatives to injectable incretin mimetics used in the treatment of type 2 diabetes and obesity.

Next-generation sequencing is pivotal for diagnosing inborn errors of immunity (IEI) but predominantly yields variants of uncertain significance (VUS), creating clinical ambiguity. Activated PI3Kδ syndrome (APDS) is caused by gain-of-function (GOF) variants in PIK3CD or PIK3R1, which encode the PI3Kδ heterodimer. We performed massively parallel base editing of PIK3CD/PIK3R1 in human T cells and mapped thousands of variants to a clinically important readout (phospho-AKT/S6), nominating >100 VUS and unannotated variants for functional classification and validating 27 hits. Leniolisib, an FDA-approved PI3Kδ inhibitor, rescued aberrant signaling and dysfunction in GOF-harboring T cells and revealed partially drug-resistant PIK3R1 hotspots that responded to novel combination therapies of leniolisib with mTORC1/2 inhibition. We confirmed these findings in T cells from APDS patients spanning the functional spectrum discovered in the screen. Integrating our screens with population-level genomic studies revealed that APDS may be more prevalent than previously estimated. This work exemplifies a broadly applicable framework for removing ambiguity from sequencing in IEI.

Glutamatergic neuronal activity promotes proliferation of both oligodendrocyte precursor cells (OPCs) and gliomas, including diffuse midline glioma (DMG). However, the role of neuromodulatory brainstem neurons projecting to midline structures where DMGs arise remains unexplored. Here, we demonstrate that midbrain cholinergic neuronal activity modulates OPC and DMG proliferation in a circuit-dependent manner. Optogenetic stimulation of the cholinergic pedunculopontine nucleus (PPN) promotes glioma growth in pons, while stimulation of the laterodorsal tegmentum nucleus (LDT) drives proliferation in thalamus. DMG-bearing mice exhibit higher acetylcholine release and increased cholinergic neuronal activity over the disease course. In co-culture, cholinergic neurons enhance DMG proliferation, and acetylcholine directly acts on DMG cells. Single-cell RNA sequencing revealed high CHRM1 and CHRM3 expression in primary DMG samples. Pharmacological or genetic blockade of M1/M3 receptors abolished cholinergic activity-driven DMG proliferation. Taken together, these findings demonstrate that midbrain cholinergic long-range projections promote activity-dependent DMG growth, mirroring a parallel proliferative effect on healthy OPCs.

Inflammation, aberrant proteostasis, and energy depletion are hallmarks of neurodegenerative diseases such as multiple sclerosis (MS). However, the interplay between inflammation, proteasomal dysfunction in neurons, and its consequences for neuronal integrity remains unclear. Using transcriptional, proteomic, and functional analyses of proteasomal subunits in inflamed neurons, we found that interferon-γ-mediated induction of the immunoproteasome subunit, proteasome 20S beta 8 (PSMB8) impairs the proteasomal balance, resulting in reduced proteasome activity. This reduction causes the accumulation of phosphofructo-2-kinase/fructose-2,6-bisphosphatase 3 (PFKFB3), a key metabolic regulator, leading to enhanced neuronal glycolysis, reduced pentose phosphate pathway activity, oxidative injury, and ferroptosis. Neuron-specific genetic and systemic pharmacological targeting of PSMB8 or PFKFB3 protected neurons in vitro and in a mouse model of MS. Our findings provide a unifying explanation for proteasomal dysfunction in MS and possibly other neurodegenerative diseases, linking inflammation to metabolic disruption, and presenting an opportunity for targeted neuroprotective therapies.

Single-cell RNA sequencing has revolutionized our understanding of cellular diversity but remains constrained by scalability, high costs, and the destruction of cells during analysis. To overcome these challenges, we developed STAMP (single-cell transcriptomics analysis and multimodal profiling), a highly scalable approach for the profiling of single cells. By leveraging transcriptomics and proteomics imaging platforms, STAMP eliminates sequencing costs, enabling cost-efficient single-cell genomics of millions of cells. Immobilizing (stamping) cells in suspension onto imaging slides, STAMP supports multimodal (RNA, protein, and H&E) profiling, while retaining cellular structure and morphology. We demonstrate STAMP's versatility by profiling peripheral blood mononuclear cells, cell lines, and stem cells. We highlight the capability of STAMP to identify ultra-rare cell populations, simulate clinical applications, and show its utility for large-scale perturbation studies. In total, we present data for 10,962,092 high-quality cells/nuclei and 6,030,429,954 transcripts. STAMP makes high-resolution cellular profiling more accessible, scalable, and affordable.

Recent outbreaks of multidrug-resistant fungi infecting human skin emphasize the importance of understanding fungal pathophysiology and spread. In efforts to address health concerns with various Indigenous Peninsular Malaysians (Orang Asli [OA]), tinea imbricata-a Trichophyton concentricum fungal skin infection-emerged as a particular concern. We investigated the etiology and transmission of tinea imbricata by culturing, testing antifungal sensitivities, and sequencing T. concentricum isolates in remote OA villages. Among regionally conserved isolates, we identified the emergence of terbinafine-resistant T. concentricum microbiologically and genomically. Investigating the skin microbiomes of 82 Indigenous OA, we found unique microbiota and lower relative abundances of bacterial commensals (Cutibacterium acnes, Staphylococcus epidermidis) among OA versus Malaysian and US urban populations, emphasizing how understudied populations provide unprecedented knowledge on host-microbiome co-evolution. These findings provide valuable insights into clinical, microbiological, and genomic features of chronic fungal skin infections, offering the potential to inform strategies to address drug resistance and effective therapy.

Microbial communities coat nearly every surface in the environment and have co-existed with animals throughout evolution. Whether animals exploit omnipresent microbial cues to navigate their surroundings is not well understood. Octopuses use "taste-by-touch" chemotactile receptors (CRs) to explore the seafloor, but how they distinguish meaningful surfaces from the rocks and crevices they encounter is unknown. Here, we report that secreted signals from microbiomes of ecologically relevant surfaces activate CRs to guide octopus behavior. Distinct molecules isolated from individual bacterial strains located on prey or eggs bind single CRs in subtly different structural conformations to elicit specific mechanisms of receptor activation, ion permeation and signal transduction, and maternal care and predation behavior. Thus, microbiomes on ecological surfaces act at the level of primary sensory receptors to inform behavior. Our study demonstrates that uncovering interkingdom interactions is essential to understanding how animal sensory systems evolved in a microbe-rich world.

Ants originated over 150 million years ago through an irreversible transition to superorganismal colony life. Comparative analyses of 163 ant genomes, including newly generated whole-genome sequences of 145 ant species, reveal extensive genome rearrangements correlated with speciation rates. Meanwhile, conserved syntenic blocks are enriched with co-expressed genes involved in basal metabolism and caste differentiation. Gene families related to digestion, endocrine signaling, cuticular hydrocarbon synthesis, and chemoreception expanded in the ant ancestor, while many caste-associated genes underwent positive selection in the formicoid ancestor. Elaborations and reductions of queen-worker dimorphism and other social traits left convergent signatures of intensified or relaxed selection in conserved signaling and metabolic pathways, suggesting that a core gene set was used to diversify organizational complexity. Previously uncharacterized genetic regulators of caste development were confirmed by functional experiments. This study reconstructs the genetic underpinning of social traits and their integration within gene-regulatory networks shaping caste phenotypes.

When a material enters the body, it is immediately attacked by hundreds of proteins, organized into complex networks of binding interactions and reactions. How do such complex systems interact with a material, "deciding" whether to attack? We focus on the complement system of ∼40 blood proteins that bind microbes, nanoparticles, and medical devices, initiating inflammation. We show a sharp threshold for complement activation upon varying a fundamental material parameter, the surface density of potential complement attachment points. This sharp threshold manifests at scales spanning single nanoparticles to macroscale pathologies, shown here for diverse engineered and living materials. Computational models show these behaviors arise from a minimal subnetwork of complement, manifesting percolation-type critical transitions in the complement response. This criticality switch explains the "decision" of a complex signaling network to interact with a material.

Metazoan life requires the coordinated activities of thousands of genes in spatially organized cell types. Understanding the basis of tissue function requires approaches to dissect the genetic control of diverse cellular and tissue phenotypes in vivo. Here, we present Perturb-Multimodal (Perturb-Multi), a paired imaging and sequencing method to construct large-scale, multimodal genotype-phenotype maps in tissues with pooled genetic perturbations. Using imaging, we identify perturbations in individual cells while simultaneously measuring their gene expression profiles and subcellular morphology. Using single-cell sequencing, we measure full transcriptomic responses to the same perturbations. We apply Perturb-Multi to study hundreds of genetic perturbations in the mouse liver. Our data suggest the genetic regulators and mechanisms underlying the dynamic control of hepatocyte zonation, the unfolded protein response, and steatosis. Perturb-Multi accelerates discoveries of the genetic basis of complex cell and tissue physiology and provides critical training data for emerging machine learning models of cellular function.

Striatal dopamine plays fundamental roles in fine-tuning learned decisions. However, when learning from naive to expert, individuals often exhibit diverse learning trajectories, defying understanding of its underlying dopaminergic mechanisms. Here, we longitudinally measure and manipulate dorsal striatal dopamine signals in mice learning a decision task from naive to expert. Mice learning trajectories transitioned through sequences of strategies, showing substantial individual diversity. Remarkably, the transitions were systematic; each mouse's early strategy determined its strategy weeks later. Dopamine signals reflected strategies each animal transitioned through, encoding a subset of stimulus-choice associations. Optogenetic manipulations selectively updated these associations, leading to learning effects distinct from that of reward. A deep neural network using heterogeneous teaching signals, each updating a subset of network association weights, captured our results. Analyzing the model's fixed points explained learning diversity and systematicity. Altogether, this work provides insights into the biological and mathematical principles underlying individual long-term learning trajectories.

Cryptococcus neoformans is the most common cause of fungal meningitis and the top-ranking WHO fungal priority pathogen. Only distantly related to model fungi, C. neoformans is also a powerful experimental system for exploring conserved eukaryotic mechanisms lost from specialist model yeast lineages. To decipher its biology globally, we constructed 4,328 gene deletions and measured-with exceptional precision-the fitness of each mutant under 141 diverse growth-limiting in vitro conditions and during murine infection. We defined functional modules by clustering genes based on their phenotypic signatures. In-depth studies leveraged these data in two ways. First, we defined and investigated new components of key signaling pathways, which revealed metazoan-like cellular machinery not present in model yeasts. Second, we identified environmental adaptation mechanisms repurposed to promote mammalian virulence by C. neoformans, which lacks a known animal reservoir. Our work provides an unprecedented resource for deciphering a deadly human pathogen.

Social insects offer powerful models to investigate mechanisms of elaborate individual behaviors comprising a cooperative community. Workers of the leafcutter ant genus Atta are extreme examples of behavioral segregation among phenotypically distinct worker types. We utilize this worker system to test the molecular underpinnings of behavioral programming and the extent of plasticity to reprogramming. We identify specific neuropeptides mediating worker division of labor in A. cephalotes, finding two neuropeptides associated with characteristic behaviors of leaf cutting and of brood care. Genetic knockdown or injection of these neuropeptides led to a stark gain or loss of each behavior and to transcriptomic shifts toward gene pathways expressed in the natural castes. We also reveal global similarities between worker transcriptomes of the eusocial mammal, the naked mole-rat H. glaber, with orthologous A. cephalotes workers. This work underscores the essential function of neuropeptides in establishing complex social behavior and a remarkable plasticity among individual behavioral types.