bioRxiv : the preprint server for biology最新文献

CD8+ T cells differentiate into diverse states that shape immune outcomes in cancer and chronic infection. To systematically define the transcription factors (TFs) driving these states, we built a comprehensive atlas integrating transcriptional and epigenetic data across nine CD8+ T cell states and inferred TF activity profiles. Our analysis catalogued TF activity fingerprints, uncovering regulatory mechanisms governing selective cell state differentiation. Leveraging this platform, we focused on two transcriptionally similar but functionally opposing states critical in tumor and viral contexts: terminally exhausted T cells (TEXterm), which are dysfunctional, and tissue-resident memory T cells (TRM), which are protective. Global TF community analysis revealed distinct biological pathways and TF-driven networks underlying protective versus dysfunctional states. Through in vivo CRISPR screening integrated with single-cell RNA sequencing (in vivo Perturb-seq), we delineated that TFs selectively govern TEXterm. We identified HIC1 and GFI1 as shared regulators of TEXterm and TRM differentiation and KLF6 as a unique regulator of TRM. Importantly, we discovered novel TEXterm single-state TFs, including ZSCAN20 and JDP2 with no prior known function in T cells. Targeted deletion of these TFs enhanced tumor control and synergized with immune checkpoint blockade. Consistently, their depletion in human T cells reduces the expression of inhibitory receptors and improves effector function. By decoupling exhaustion-selective from protective TRM programs, our platform enables more precise engineering of T cell states, advancing rational design of effective immunotherapies.

A key problem in learning is credit assignment. Biological systems lack a plausible mechanism to implement the backpropagation approach, a method that underlies much of the dramatic progress in artificial intelligence. Here, we use automated connectomic analysis to show that the synaptic architecture of songbird basal ganglia (Area X) supports local credit assignment using a variant of a node perturbation algorithm proposed in a model of reinforcement learning. Using two volume electron microscopy (vEM) datasets, we find that key predictions of the model hold true: axons that encode exploratory variability terminate predominantly on dendritic shafts, while axons that encode song timing (context) terminate predominantly on spines. Based on the detailed EM data, we then built a biophysical model of reinforcement learning that suggests that the synaptic dichotomy between variability and context encoding axons facilitates efficient learning. In combination, these findings provide strong evidence for a general, biologically plausible credit assignment model in vertebrate basal ganglia learning.

Neurons have an outsized metabolic demand, requiring continuous metabolic support from non-neuronal cells called glia. When this support fails, toxic metabolic byproducts accumulate, ultimately leading to excitotoxicity and neurodegeneration. Astrocytes, the primary synapse-associated glial cell type, are known to provide essential metabolites ( e.g. lactate) to sustain neuronal function. Here, we leverage the well-characterized Drosophila motor circuit to investigate another means of astrocyte-to-neuron metabolic support: activity-dependent trafficking of astrocyte mitochondria. Following optogenetic activation, motor neuron mitochondria migrate away from synapses. By contrast, astrocytic mitochondria accumulated peri-synaptically, and at times, were transferred into neighboring neurons. A genetic screen identified the mitochondrial adaptor protein Milton as a key regulator of this process. Astrocyte-specific milton knockdown disrupted regular mitochondrial trafficking, resulting in locomotor deficits, dysfunctional motor activity, and altered synapse number at the neuromuscular junction. These findings suggest that astrocytes dynamically redistribute mitochondria to buffer metabolic demand at synapses, highlighting a potential mechanism by which glia protect neural circuits from metabolic failure and neurodegeneration.

To understand why people avoid mental effort, it is crucial to reveal the mechanisms by which we learn and decide about mental effort costs. This study investigated whether mental effort cost learning aligns with temporal-difference (TD) learning or alternative mechanisms. Model-based fMRI analyses showed no correlation between cost prediction errors (CPEs) and activity in the dorsomedial frontal cortex/dorsal anterior cingulate cortex (dmFC/dACC) or striatum at the time of a fully informative effort cue about upcoming effort demands, contradicting the TD hypothesis. Instead, CPEs correlate with dmFC/dACC (positively) and caudate (negatively) activity at effort completion. Furthermore, only activity patterns at effort completion predict subsequent choices. These results show that decision policies are updated retrospectively at effort completion, updating expected costs with prediction error between experienced effort and prior expectations, demonstrating mental effort cost learning is retrospective, and imply that adaptive learning of mental effort cost does not follow canonical TD learning.

Proper brain function requires the assembly and function of diverse populations of neurons and glia. Single cell gene expression studies have mostly focused on characterization of neuronal cell diversity; however, recent studies have also revealed substantial diversity of glial cells, particularly astrocytes. To better understand glial cell types and their roles in neurobiology, we built a new suite of adeno-associated viral (AAV)-based genetic tools to enable genetic access to astrocytes and oligodendrocytes. These oligodendrocyte and astrocyte enhancer-AAVs are highly specific (usually > 95% cell type specificity) with variable expression levels, and the astrocyte enhancer-AAVs show multiple distinct expression patterns reflecting the spatial distribution of astrocyte cell types. To provide the best glial-specific functional tools, several enhancer-AAVs were: optimized for higher expression levels, shown to be functional and specific in rat and macaque, shown to maintain specific activity across transgenes and in epilepsy where traditional promoters changed activity, and used to drive functional transgenes in astrocytes including Cre recombinase and acetylcholine-responsive sensor iAChSnFR. The astrocyte-specific iAChSnFR revealed a clear reward-dependent acetylcholine response in astrocytes of the nucleus accumbens during reinforcement learning. Together, this collection of glial enhancer-AAVs will enable characterization of astrocyte and oligodendrocyte populations and their roles across species, disease states, and behavioral epochs.

The growth and division of cells in plant leaves is highly dynamic in time and space, even though cells cannot move relative to their neighbors. Thus, organ shape must emerge from carefully coordinated growth, especially in leaves that remain relatively flat as they grow. Here we explored the phenotype of the jagged and wavy (jaw-D) mutant in Arabidopsis thaliana, in which the leaves do not remain flat. It has previously been shown that the jaw-D mutant phenotype is caused by the overexpression of miR319, which represses TCP transcription factors, thus delaying maturation of the leaf. We analyzed cell dynamics in wild type and jaw-D by performing time lapse live imaging of developing leaves. We found that the progression of maturation from the tip of the leaf downward was delayed in jaw-D relative to wild type based on several markers of maturation, in agreement with the role of TCP transcription factors in promoting maturation. We further found that these changes in maturation were accompanied by differences in the coordination of growth across the leaf, particularly across the medial-lateral axis, causing growth conflicts that prevent the leaf from remaining flat. Although leaf flatness is often framed as a problem that requires the local synchronization of growth on the abaxial vs adaxial sides of the leaf, our results based on the jaw-D phenotype suggest that wild-type plants also need to coordinate growth more globally across the leaf blade to maintain flatness.

Genetically encoded sensors and actuators have advanced the ability to observe and manipulate cellular activity, yet few non-invasive strategies enable cells to directly couple their intracellular states to user-defined outputs. We developed a bioluminescent activity-dependent (BLADe) platform that facilitates programmable feedback through genetically encoded light generation. Using calcium (Ca²⁺) flux as a model, we engineered a Ca²⁺-dependent luciferase that functions as both a reporter and an activity-gated light source capable of photoactivating light-sensing actuators. In neurons, the presence of luciferin triggers Ca²⁺ dependent local illumination that provides activity dependent gene expression by activating a light-sensitive transcription factor and control of neural dynamics through opsin activation in single cells, populations and intact tissue. BLADe can be expanded to couple any signal that bioluminescent enzymes can be engineered to detect with the wide variety of photosensing actuators. This modular strategy of coupling an activity dependent light emitter to a light sensing actuator offers a generalizable framework for state dependent cell-autonomous control across biological systems.

As epithelial cells polarize in the tissue plane, the Planar Cell Polarity (PCP) signaling module segregates two distinct molecular subcomplexes to opposite sides of cells. Homodimers of the atypical cadherin Flamingo form bridges linking opposite complexes in neighboring cells, coordinating their direction of polarization. Feedback is required for cell polarization, but whether feedback requires intercellular and/or intracellular pathways is unknown. Using novel tools, we show that cells lacking Flamingo, or bearing a homodimerization-deficient Flamingo, polarize autonomously, indicating that functional PCP subcomplexes form and segregate cell-autonomously. Furthermore, we identify feedback pathways and propose an asymmetry amplifying mechanism that operate cell-autonomously. The intrinsic logic of PCP signaling is therefore more similar to that in single cell systems than was previously recognized.

Rett syndrome (RTT) is a severe X-linked neurodevelopmental disorder caused by mutations in MECP2. Elevated circulating levels of the adipocyte hormone leptin are consistently observed in patients and in mouse models, yet their contribution to disease progression has remained unclear. Here, we show that reducing leptin signaling, either pharmacologically or genetically, significantly alleviates RTT-like phenotypes in Mecp2-deficient mice. In males, these interventions preserved general health, prevented weight loss, and improved breathing and locomotor functions. At the neuronal level, they restored excitatory/inhibitory balance in the hippocampus and somatosensory cortex and rescued hippocampal synaptic plasticity. In females, delaying the pathological rise of leptin levels postponed symptom progression. These findings uncover leptin as a key contributor to RTT pathophysiology and position leptin-targeted interventions as a promising therapeutic strategy for this currently untreatable disorder.

The aryl hydrocarbon receptor (AHR) is a ligand-dependent transcription factor activated by environmental toxicants like halogenated and polycyclic aromatic hydrocarbons, which then binds to DNA and regulates gene expression. AHR is implicated in numerous physiological processes, including liver and immune function, cell cycle control, oncogenesis, and metabolism. Traditionally, AHR binds a consensus DNA sequence (GCGTG), the xenobiotic response element (XRE), recruits coregulators, and modulates gene expression. Yet, recent evidence suggests AHR can also regulate gene expression via a non-consensus sequence (GGGA), termed the non-consensus XRE (NC-XRE). The prevalence and functional significance of NC-XRE motifs in the genome have remained unclear. While ChIP and reporter studies hinted at AHR-NC-XRE interactions, direct evidence for transcriptional regulation in a native context was lacking. In this study, we analyzed AHR binding to NC-XRE sequences genome-wide in mouse liver, integrating ChIP-seq and RNA-seq data to identify candidate AHR target genes containing NC-XRE motifs in their regulatory regions. We found NC-XRE motifs in 82% of AHR-bound DNA, significantly enriched compared to random regions, and present in promoters and enhancers of AHR targets. Functional genomics on the Serpine1 gene revealed that deleting NC-XRE motifs reduced TCDD-induced Serpine1 upregulation, demonstrating direct regulation. These findings provide the first direct evidence for AHR-mediated regulation via NC-XRE in a natural genomic context, advancing our understanding of AHR-bound DNA and its impact on gene expression and physiological relevance.