Biology subjects

Jin, Z.

Publications and source records attributed to Jin, Z..

At least 19 recordsLinked to original sources

bioRxiv2026

Histone modifications define distinct nucleosome positions in cell-free DNA

Circulating cell-free DNA (cfDNA) fragmentation patterns reflect nucleosome positioning. We asked whether variation in nucleosome positions in cfDNA can reveal chromatin states and associated histone modifications. Using cell-free chromatin immunoprecipitation sequencing (cfChIP-seq) in plasma from patients with prostate cancer, we identified 35,120 modification-associated positions (MAPs), loci where nucleosomes bearing active (H3K4me2) and repressive (H3K9me3) histone marks occupy reproducibly offset positions. These offsets recurred across histone marks, an independent cfChIP-seq cohort, and nuclease-digested chromatin from cell lines. MAPs were enriched in transcribed genes but depleted near transcription start sites and CTCF-binding sites where nucleosome positioning is constrained. Across 2,535 cfDNA sequencing datasets, nucleosome protection at a subset of MAPs correlated with tumor fraction (TF), reflecting differences in histone modification status between cancer-derived and non-malignant chromatin. In targeted sequencing panels, a 50-MAP model using fragments from < 0.001% of the genome distinguished samples with tumor fractions [≥]3% vs 0% (AUCs = 0.91-0.96 across prostate, breast, and lung cancers) and outperformed a state-of-the-art fragmentomics-based tumor fraction predictor. MAP-derived estimates correlated with reference TFs (r = 0.89) and longitudinal changes in TF (r = 0.91). MAP protection at ASCL1 binding sites identified neuroendocrine transformation of prostate cancer from cfDNA. These findings establish histone-modification-associated nucleosome positioning as a mutation-independent readout of tumor fraction and cancer state from routine cfDNA sequencing.

cancer biology↗

bioRxiv2026

Perceptual similarity representations beyond the sensory cortex

It is commonly thought that information supporting conscious perception is primarily represented in sensory cortices, whereas association cortex encodes more abstract, task-dependent information. However, this impression may partly stem from difficulties in experimentally assessing the functions of association areas characterized by mixed selectivity and complex spatial topography. Here, we combined repetition-suppression (RS) and multi-voxel pattern analysis (MVPA) to extract richer information from human fMRI. With this approach, we asked whether association regions represent the perceptual similarity structure among color stimuli, although this perceptual similarity information was task-irrelevant in the experiment. Our analysis revealed such representations beyond the visual cortex, in lateral prefrontal, and parietal regions. We further demonstrated an electrophysiological complement to the fMRI findings by applying the same approach to local field potentials recorded in the macaque dorsomedial parietal cortex. Our findings suggest that higher-order areas beyond the visual cortex may play a key role in subjective color perception.

neuroscience↗

bioRxiv2026

Biologically inspired alignment reveals distributed and directionally asymmetric correspondence between rat and human cortices

Rodent models enable causal interrogation of brain circuits, but translating their systems-level organization to humans requires correspondence beyond one-to-one anatomical homology. Guided by the view that cortical areas are characterized by their relationships within distributed functional networks, we developed BrainMapping, a biologically inspired framework for aligning rat and human cortex using resting-state functional MRI. The framework combined a shared representation with optimal transport to derive probabilistic, bidirectional maps. These alignments revealed distributed, many-to-many correspondences that generalized to held-out subjects and preserved functional connectivity architecture, cortical gradients, and graph topology. Organizational preservation was directionally asymmetric. Human-to-rat mapping preserved organization more uniformly across rat cortical systems, whereas rat-to-human mapping showed stronger preservation in human association-related networks than in primary sensory and motor networks. The maps recovered literature-consistent default-mode and salience-system correspondences and generated testable non-canonical predictions. These findings provide a framework for expressing rat functional organization in human functional-network coordinates.

neuroscience↗

bioRxiv2026

scGSCA: gene-set differential co-expression analysis for single-cell RNA sequencing data

Understanding disease-associated pathway coordination requires distinguishing phenotype-related co-expression changes from differences across cellular contexts while accounting for cells sampled from the same subject. Bulk gene-set co-expression methods do not directly address the sparse counts, single-cell distributional noise, subject-level dependence, and cell-type heterogeneity of single-cell RNA sequencing (scRNA-seq) data. We developed single-cell gene-set co-expression analysis (scGSCA), a framework for pathway-level differential co-expression analysis in scRNA-seq data. scGSCA fits gene-wise zero-inflated negative binomial mixed models with subject-level random effects and computes gene-set co-expression statistics from quantile residual correlations. It provides an overall differential gene-set co-expression analysis and an interaction test to assess whether the co-expression pattern between two cell types varies by sample phenotype. We applied scGSCA to tumor-normal gastric, breast-subtype, and lung-skin comparisons with matched bulk and scRNA-seq data. The overall test identified signals not captured in bulk analysis, including Axon guidance in gastric cancer and estrogen-response, IL6-JAK-STAT3, and TNF/NF-{kappa}B pathways in breast cancer. The interaction test further identified co-expression contrasts across cell types. scGSCA extends gene-set co-expression analysis to single-cell data while retaining subject-level structure and cell-type-specific context. scGSCA is freely available as an open-source R package.

bioinformatics↗

bioRxiv2026

Longitudinal imaging of single cells in opaque tissue with cell chirp ultrasound

Small numbers of cells can determine the fate of an entire organism. For example, metastatic cancer cells seed distant organs, therapy-resistant clones repopulate tumors, and T cells infiltrate and expand in tissues with matching antigens. Visualizing the activity of such cells in living organisms requires highly sensitive, specific and repeatable imaging in optically opaque tissues. Here we introduce cell chirp, an ultrasound imaging method for real-time imaging of single cells in living organs inaccessible to light. Cell chirp exploits the harmonic response of genetically encoded gas vesicles to frequency-coded ultrasound to sensitively and specifically visualize single cells in scattering background. We first develop this method in tissue-mimicking phantoms, demonstrating the ability to quantitatively detect single cells as validated by optical cell counts. We then establish the ability of cell chirp to image thousands of genetically labeled cells within a million-cell background tissue, track reporter gene expression over days, and suppress background signals by more than two orders of magnitude. Finally, we use cell chirp to track the fate of antigen-positive or antigen-negative tumor-cell minorities during weeks-long T-cell engager treatments. Cell chirp reveals the dynamics of sparsely distributed, genetically defined cells in opaque tissues.

bioengineering↗

bioRxiv2026

Longitudinal, Non-Invasive Imaging of the Developing Chick Heart, Vasculature, and Chorioallantoic Membrane (CAM)

The chick embryo is a widely used vertebrate model for developmental biology, cardiovascular, and bioengineering research. We present an automated laser speckle contrast imaging (LSCI) platform for non-invasive, longitudinal, label-free imaging of the developing heart and extraembryonic vasculature of the chick embryo through the intact eggshell. The platform can detect blood vessels as small as 70 +/- 17 um in diameter and enable repeated imaging from day 0 to day 8 of incubation without disturbing normal embryonic development. It provides both structural (a map of growing extraembryonic blood vessels) and functional (blood flow dynamics and heart rate) information. Using this system, we generated the first continuous, non-invasive, time-lapse recordings of the early functioning chick heart and its extraembryonic vessels. Longitudinal imaging was performed on 15 embryos from different chicken breeds with eggshell colors white, brown and green. Analysis revealed slight variability in early cardiac and vascular morphogenesis across breeds and shell types and shows its potential for automated developmental staging. Finally, for the first time, the growing vasculature of the yolk sac and the chorioallantoic (CAM) membrane was imaged from day 4 to 8. The heart rate and growth of the extraembryonic blood vessels were quantified automatically during imaging.

developmental biology↗

bioRxiv2026

A physics-informed hybrid deep learning model for spatiotemporal rice disease prediction using multi-source data

Accurate, reliable, large-scale disease predictions are essential to ensure rice production. Existing disease prediction models often face a trade-off between interpretability and predictive capability, necessitating the integration of mechanistic knowledge and data-driven learning within a modelling framework. Accordingly, we propose a physics-informed hybrid gated recurrent unit (PI-HGRU) model for spatiotemporal dynamic prediction of rice sheath blight disease, caused by a fungus. Our model embeds differential equations describing disease transmission dynamics into a hybrid gated recurrent unit (HGRU) framework as mechanistic constraints, thereby enabling collaborative modelling between epidemiological processes and data-driven learning. We conducted model training and evaluation using a long-term, multi-source dataset spanning 17 years (2000-2016) and covering 16 major rice-producing provinces in southern China. These rich data include spatiotemporally aligned field disease observations, remote sensing data, meteorological data, and soil property data. In addition, to address the challenges of irregular sampling intervals and inconsistent sequence lengths in disease survey data, we adopted a sliding time-window-based prediction framework. We further conducted a time-window sensitivity analysis to determine appropriate configurations of the input time window and lag time, enabling the model to represent the cumulative and delayed effects of environmental factors. Our PI-HGRU framework substantially outperforms the purely data-driven HGRU baseline model, improving the squared Pearson correlation coefficient (r2) by 22.8% while reducing the root mean square error (RMSE) and mean absolute error (MAE) by 10.2% and 18.0%, respectively. Furthermore, analysis of the models intermediate variables showed that the transmission rate {beta}(t) exhibited interpretable relationships with environmental conditions within the input time window, providing a process-related link between environmental drivers and modeled disease transmission dynamics. Overall, our work demonstrates that integrating epidemiological mechanisms into deep learning models in a physics-informed manner can improve predictive accuracy and stability while enhancing model interpretability, highlighting its potential for large-scale disease forecasting and precision disease management.

bioinformatics↗

bioRxiv2026

Decoding the Transcriptome Dark Matter: Construction of Single-Cell Whole-Transcriptome Regulatory Atlas by dropTotal

To profile unknown ncRNAs-"dark matter" in single cells, we developed dropTotal, a high-throughput droplet-based total RNA-seq method that uses dU-modified GAT primer with temperature-ramp hybridization and droplet merge barcoding to co-detect coding and non-coding transcripts with record sensitivity (>13,500 genes/cell, including >2,000 lncRNAs and >500 sncRNAs), compatible with fresh, frozen, fixed, and FFPE tissues. Applied to ~75,000 human glioma nuclei, it captured 60,313 genes (18,681 lncRNA, 19,859 mRNAs and 6,753 sncRNAs), enabling ncRNA-driven regulatory landscape construction. In oligodendroglioma, module analysis identified recurrence-associated ncRNA-centered modules linked to therapy resistance and invasion; in glioblastoma, six cellular states showed hundreds of state-specific unannotated ncRNAs with divergent functions, from MIR222HG-mediated immune modulation to SCIRT-driven hypoxia adaptation. Alternative splicing analysis identified 428 state-specific junction markers and mapped cell-state-specific alternative splicing regulation. dropTotal offers broad application for decoding the underlying ncRNA biology and single-cell whole transcriptome regulatory mechanisms in cellular identity and disease progression.

genomics↗

bioRxiv2026

LncRNA-mediated organization of oncogenic chromatin state is a targetable vulnerability in leukemia

Long non-coding RNAs (lncRNAs) are increasingly recognized as critical regulators of gene expression underlying various cellular functions, however, the functional and mechanistic contributions of most lncRNAs to tumorigenesis remain poorly defined, and targeting of lncRNAs is challenging with conventional therapeutic approaches. Here, we uncover human PAN3-AS1 and its murine ortholog Lnc35682, previously uncharacterized lncRNAs embedded within a conserved syntenic genomic locus, as highly expressed in acute myeloid leukemia (AML). Using genetic mouse models, human cell lines and primary patient samples, we show that PAN3-AS1 is essential for leukemia maintenance but dispensable for normal hematopoiesis. Mechanistically, we find that elevated PAN3-AS1 influences chromatin accessibility, thus promoting leukemia gene expression programs. This is mediated, at least in part, by PAN3-AS1s association with the nuclear lamina through a defined functional region that is required for its leukemogenic function. We further characterize a feed-forward regulatory circuit between PAN3-AS1 and its neighboring gene FLT3 that directly links the aberrant lncRNA functions to the FLT3-mutant AML subtype. To therapeutically exploit the regulatory node, we engineer a myeloid leukemia-preferentially targeted lipid nanoparticle (LNP) formulation and demonstrate effective delivery of siRNAs against endogenous targets into leukemia cells in experimental animals. LNP-siPAN3-AS1 alone or in combination with a clinically used FLT3 inhibitor, Gilteritinib, reduces leukemia burden and significantly delay leukemogenesis in vivo. Overall, our study uncovers a therapeutic vulnerable lncRNA-centric circuitry and provides compelling preclinical evidence for the development and application of a novel RNA targeting-LNP based therapy for treatment of myeloid leukemia. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=200 SRC="FIGDIR/small/744058v1_ufig1.gif" ALT="Figure 1"> View larger version (52K): org.highwire.dtl.DTLVardef@10c9d42org.highwire.dtl.DTLVardef@12864e7org.highwire.dtl.DTLVardef@f87f6aorg.highwire.dtl.DTLVardef@750cbf_HPS_FORMAT_FIGEXP M_FIG C_FIG

cancer biology↗

bioRxiv2026

Telomerase RNA regulates the epigenome primed for human lineage commitment

Telomerase RNA (TERC) is known as the essential template for telomere elongation. Here, we report an unexpected role for TERC in regulating chromatin accessibility, which is primed for determining the cell fate of human embryonic stem cells (hESCs). TERC-deficient hESCs retain critical markers for pluripotency but fail to undergo lineage differentiation as shown by standard in vivo teratoma formation as well as in vitro differentiation assays, which is consistent with repressed transcription during differentiation into the three germ lineages. Notably, transient re-introduction of TERC into TERC-deficient hESCs rescued lineage differentiation capacity without restoring telomere length. TERC binds to the promoters and enhancers of developmental genes marked by H3K27ac to maintain an open chromatin state. Loss of TERC reduces H3K27ac deposition and decreases chromatin accessibility through the remodelling of three-dimensional genome organization, including TAD boundary insulation and compartment switching. Collectively, our findings reveal that TERC is a chromatin-associated noncoding RNA that regulates the epigenomic architecture that governs cell fate for lineage commitment during development.

cell biology↗

bioRxiv2026

Phylogenetic Mosaic of an Arms Race with Asymmetrical Sexual Conflict and Its Macroevolutionary Consequences in a Lineage of Small Water Striders

Sexual conflict has been hypothesized as a driver of speciation, though its effects are likely heterogeneous across phylogenies and between sexes. The Gerromorpha (semi-aquatic bugs), which inhabits water surfaces across diverse aquatic environments, long served as a model for studying sexual conflict. While previous studies have focused on rapid antagonistic coevolution and the genetic basis of sexually antagonistic traits, the macroevolutionary consequences of asymmetrical sexual conflict-particularly male-dominated grasping traits versus female resistance-remain largely unexplored. Within the subgenus Pseudovelia, males exhibit pronounced phenotypic diversification in grasping structures, whereas females show modest, clade-specific resistance traits, suggesting male-biased asymmetric conflict. This system presents a valuable opportunity to examine how sexual conflict influences diversification and asymmetrical trait evolution across lineages. Using 204 individuals, representing over half of the subgenus's species diversity, we reconstructed a time-calibrated phylogeny, quantified diversification rates, assessed sexual conflict intensity across clades, and analyzed correlations between sexual trait evolution and diversification. Our results reveal extensive phylogenetic conflict, particularly within the East Asian clade, driven by introgression and incomplete lineage sorting (ILS). Furthermore, we observe significant phylogenetic heterogeneity in both phenotypic evolution and diversification rates. Notably, a male "trait package" enhancing grasping ability likely drives rapid diversification in the recently radiated "South China" lineage. In contrast, grasping traits involving abdominal segment VIII are associated with lower conflict intensity, facilitating greater evolutionary flexibility in female resistance and resulting in lineage-specific counter-adaptations. These findings highlight the heterogeneous dynamics of asymmetrical sexual conflict in shaping diversification and speciation.

evolutionary biology↗

bioRxiv2026

Homeobox transcription factor MSX2 down-regulates ERα action to facilitate anti-estrogensensitivity in ERα+ breast cancer

Breast cancer is the most common malignancy among women worldwide. Estrogen receptor (ER)-positive breast cancer is about 70% in the total breast cancer. It has variable prognosis and high recurrent risk, frequently developing resistance to endocrine therapies. Herein, we have identified that a homeobox transcription factor MSX2 downregulated in ER-positive breast cancer is correlated with the advanced grade and poor survival outcomes. Our results have demonstrated that MSX2 interacts with ER to inhibit ER-mediated transactivation. Mechanistically, MSX2 associates with HDAC1/HDAC2 to form a protein complex. MSX2 is required for recruitment of HDAC1/HDAC2 complex to estrogen response elements (EREs) region on ER downstream target genes, reducing histone H3K9ac and H3K27ac levels to inactivate gene transcription. Functionally, ectopic expression of MSX2 suppresses cell growth and enhances the sensitivity to anti-estrogen treatment in ER-positive breast cancer cells. Our results indicate that MSX2 as a novel co-repressor of ER is involved in suppression of ER-positive breast cancer progression. Restoring MSX2 protein may provide a promising strategy to overcome endocrine resistance in ER-positive breast cancer.

Molecular Biology↗

bioRxiv2026

Interference-Free Propagation: Achieving Reliable Signal Propagation in Cortical Networks with Areal-Specific Local Dynamics

In cortical networks, how to simultaneously achieve both reliable inter-areal signal propagation and areal-specific local dynamics remains largely unclear. In general, strong connections between areas enhance signal propagation, but blend timescales of area-specific neuronal activity, whereas weak connections have the opposite effect. Here we identify a novel dynamical regime termed "interference-free propagation" (IFP) that reconciles the two contrasting demands in the cortex. In the IFP regime, mean signals from upstream areas can propagate reliably, but fluctuations indicative of upstream areas timescales are filtered out. This result provides new insights into the operational regime of the cortex, leading to the coexistence of reliable signal propagation and the distinct property of local temporal integration of information in the cortical network.

neuroscience↗

bioRxiv2026

Estimating Daily Taxon-specific Tree Pollen at a 1-km Resolution in Atlanta, GA from 2020 to 2024

While tree pollen is a major trigger of allergic respiratory conditions and different taxa exhibit varying allergenic potentials, the lack of high-resolution, taxon-specific exposure metrics have limited our ability to identify which local pollen taxa are primarily responsible for respiratory illness. Traditional pollen monitoring networks, which have an intermittent sampling schedule, are not ideal for examining the delayed effects of pollen exposure due to the missing days. In this study, we developed a modeling framework integrating atmospheric dispersion effects, taxa-specific phenology, and machine learning to predict daily counts of 13 tree taxa in the five-county Metro Atlanta area, Georgia at a 1-km resolution from 2020 to 2024. Machine learning model performance was validated with daily pollen counts collected by a multi-site monitoring network equipped with automated pollen sensors. Findings showed that Betula and Quercus pollens exhibited higher predictive performance than other taxa, with R2 values ranging from 0.69 to 0.92 and from 0.71 to 0.89, respectively. Our 1-kilometer prediction data provides gapless exposure metrics to understand the spatial and temporal variability in pollen exposure, can facilitate investigation of urban pollen hotspots and support epidemiologic studies of pollen-related respiratory outcomes.

plant biology↗

bioRxiv2026

piRNA direct the chromatin reader to its genomic targets

The chromatin reader Rhino (Rhi) is an HP1-paralog and master regulator of piRNA biogenesis in Drosophila that drives the transcription of piRNA precursors. While Rhi binds the heterochromatic mark H3K9me3, this interaction is insufficient to explain its specific occupancy, as Rhi is excluded from the majority of H3K9me3-enriched loci. Instead, we find that Rhi recruitment is orchestrated by several competing pathways, including the piRNA-guided protein Panoramix (Panx) and the DNA-binding protein Kipferl (Kipf). We demonstrate that Panx functions as a piRNA-guided modular scaffold that directs Rhi to its targets through a dual-mode mechanism: its N-terminus recruits the H3K9 methyltransferase machinery, while its C-terminus directly binds the Rhi chromodomain. While H3K9me3 deposition provides a necessary foundation, it acts in synergy with the direct Panx-Rhi physical bridge to drive robust Rhi occupancy. Furthermore, Rhi recruitment is amplified by the cytoplasmic inheritance of maternal piRNAs, forming a transgenerational feed-forward loop. Our results reveal that the piRNA pathway imparts sequence-specificity to the H3K9me3 code, utilizing a direct physical bridge to program the genomic distribution of the chromatin reader Rhi.

molecular biology↗

bioRxiv2026

Microglial pruning of extinction-ensemble synapses preserves fear memory

Fear extinction suppresses learned fear without erasing the original memory, yet how competing fear and extinction ensembles are selectively updated remains unknown. Here, we show that microglia preserve fear memory by selectively editing extinction-ensemble synapses during retrieval. In medial prefrontal cortex, microglial processes, but not somata, expand, ramify, and tighten their engagement with extinction-ensemble dendrites and spines, where they preferentially engulf excitatory postsynaptic material and bias spine remodeling toward elimination. This selectivity is instructed by local find-me, eat-me, and dont-eat-me cues: purinergic signaling recruits microglial processes, phosphatidylserine exposure licenses engulfment of extinction-ensemble synapses, and CD47-SIRP protects fear ensembles from removal. Weakening microglial recruitment or engulfment, or removing this protection, accelerates extinction without impairing fear acquisition. These findings identify microglial processes as active gatekeepers of ensemble competition and reveal a neuroimmune mechanism that preserves fear memory by limiting extinction. In BriefDuring memory updating, microglial processes selectively engage extinction-ensemble synapses rather than globally pruning active circuits. Local recruitment, engulfment, and protection cues determine this choice, allowing microglia to preserve fear memory by limiting extinction. HighlightsO_LIExtinction retrieval selectively recruits microglial processes to extinction ensembles. C_LIO_LIMicroglia preferentially engulf excitatory postsynaptic material from extinction ensembles. C_LIO_LILocal "find-me," "eat-me," and "dont-eat-me" cues determine synapse selection. C_LIO_LIDisrupting microglial pruning facilitates extinction without impairing fear learning. C_LI

neuroscience↗

bioRxiv2026

Transcription Factor Subtype Governs Response and Resistance to DLL3-Directed T-Cell Engagement in Small Cell Lung Cancer

Although small cell lung cancer (SCLC) comprises transcription factor (TF)-defined molecular subtypes (ASCL1, NEUROD1, POU2F3), the extent to which these subtypes predict response to clinically effective therapy in patients--and whether therapy can select for subtype switching--remains unknown. The recent approval of the DLL3xCD3 bispecific T-cell engager tarlatamab represents one of the first meaningful advances in relapsed small cell lung cancer (SCLC) in decades, yet responses remain heterogeneous and resistance is inevitable. Here, we inferred SCLC gene expression from circulating chromatin in prospectively collected patient plasma (46 patients; 167 samples), enabling interrogation of response and acquired resistance to tarlatamab. Parallel development of the first immunocompetent syngeneic mouse model to study tarlatamab response and resistance enabled functional validation. Across species, findings converged on a central principle: TF subtype governs both initial response and acquired resistance. Therapeutic response was significantly associated with ASCL1-subtype tumors, whereas NEUROD1-subtype tumors exhibited inferior responses and POU2F3-subtype tumors were uniformly resistant, consistent with DLL3 being a direct ASCL1 transcriptional target and most highly expressed in ASCL1-positive tumors. Strikingly, one mode of acquired resistance revealed therapeutic selection for a NEUROD1-high state with concomitant DLL3 downregulation. Other resistant tumors exhibited enrichment of regulatory and exhausted T-cell programs, highlighting tarlatamabs dual-targeting mechanism of action. Together, these results reveal that tarlatamab exerts selective pressure against ASCL1-driven lineages, facilitating resistance through loss of an antigen intrinsically linked to that state. These findings underscore the clinical relevance of TF-defined molecular subtypes in human SCLC. More broadly, they highlight the power of integrating longitudinal in vivo plasma transcriptional profiling from patient plasma with functional mouse modeling to uncover clinical and biological mechanisms of response and resistance to cell-surface-targeted therapies.

cancer biology↗

bioRxiv2026

Peripheral Metabolic Reprogramming Links TDP-43 Proteinopathy to Sleep Disruption

Sleep disruption is an early and prevalent feature of neurodegenerative disease, commonly attributed to neuronal circuit dysfunction or cell loss. However, sleep is tightly coupled to metabolic state, raising the possibility that systemic metabolic abnormalities contribute to disease-associated sleep phenotypes. Using Drosophila models of TDP-43 proteinopathy, we investigated whether peripheral metabolic dysfunction plays a causal role in sleep disruption. We show that TDP-43 expression induces a chronic, starvation-like metabolic state characterized by depletion of peripheral carbohydrate stores despite normal feeding. Restoration of sleep fails to correct these metabolic defects, whereas improving peripheral metabolic state robustly rescues sleep. A modifier screen of [~]650 RNAi lines identified Salt-inducible kinase 3 (SIK3) as a potent suppressor of both sleep loss and starvation sensitivity. Transcriptomic and spatial metabolomic analyses reveal that SIK3 selectively remodels a peripheral metabolic program centered on the pentose phosphate pathway and redox-associated metabolites without globally restoring energy stores. Together, these findings identify systemic metabolic dysfunction as a key driver of sleep disruption in TDP-43 proteinopathy and highlight peripheral metabolism as a potential therapeutic entry point for sleep dysfunction in neurodegenerative disease.

neuroscience↗