Biology subjects

Wu, W.

Publications and source records attributed to Wu, W..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Off-target effects of PLX5622 revealed: mixing microglial function in anesthesia and addiction withdrawal

Microglia have gained increasing attention as important regulators in the brain. Acute microglial depletion using the colony-stimulating factor 1 receptor (CSF1R) inhibitor, PLX5622, has become a popular approach to uncover microglial function. PLX5622 treatment has been recently shown to significantly promote anesthetic emergence. In characterizing underlying mechanisms, we found that PLX5622 treatment did not change the global neuronal activity during anesthesia, but robustly enhanced anesthetic metabolism. Moreover, PLX5622 dramatically induced the expression of hepatic enzymes that extensively modify xenobiotic and endobiotic metabolism. Blocking increased enzymatic activity significantly reduced the arousal-promoting effects of PLX5622 in anesthesia, irrespective of microglial elimination. In addition, we demonstrate that enhanced drug metabolism also contributed to PLX5622-induced attenuation in nicotine-withdrawal anxiety. By revealing previously unrecognized effects of PLX5622, our findings raise caution in interpreting data generated from PLX5622 treatment and bring forward the need for designing more specific CSF1R inhibitors.

neuroscience↗

bioRxiv2025

MACGA: Multi-scale Adaptive Convolution with Graph Attention for LncRNA-Disease Association Prediction

Accurate prediction of lncRNA-disease associations (LDAs) is crucial for understanding complex disease mechanisms and advancing precision medicine. Existing computational methods based on graph neural networks (GNNs) often suffer from over-smoothing issues, limiting their predictive accuracy. To address this challenge, we propose MACGA, a novel neural network framework integrating Multi-scale Adaptive Convolution with Graph Attention networks. MACGA effectively captures both local neighborhood information and global high-order structural features by combining PCA-based dimensionality reduction, local node feature extraction via graph attention mechanisms, and multi-scale feature aggregation through adaptive convolution. Extensive experiments using five-fold cross-validation demonstrated that MACGA significantly outperformed four representative state-of-the-art methods (AUC=0.9463, AUPR=0.4119). Case studies on prostate and colon cancers further validated the reliability of MACGA, with top-ranked lncRNA predictions well-supported by existing experimental literature. Moreover, we extended the proposed framework to predict disease-drug associations via lncRNA-bridging strategy, highlighting its potential for drug repositioning. Overall, MACGA provides a powerful computational tool for accurately predicting lncRNA-disease associations and exploring novel therapeutic opportunities. The source code and dataset used in this paper are available at: https://github.com/huifeideyu518/MACGA.

bioinformatics↗

bioRxiv2025

Breaking the Salinity-Nitrogen Fixation Trade-Off: Engineering A Synthetic Nitrogen-Fixing Vibrio natriegens Strain

Inefficient nitrogen fixation in legumes under saline stress threatens food security, while conventional symbiotic nitrogen fixation is limited by host specificity and saline stress inhibition. This study engineered Vibrio natriegens with nitrogen fixation genes, creating a saline-tolerant, broad-host-range nitrogen-fixing bacteria that enhances plant-microbe interactions through reprogrammed nitrogen metabolism. We demonstrated that engineered nitrogen-fixing V. natriegen significantly enhanced soybean growth and nodulation under saline stress. It also activated nitrogenase gene (nifHDK) expression in rhizosphere bacteria and increased the abundance of rhizosphere diazotrophs. This study presents a novel approach for developing stress-resilient crop-microbe symbioses, offering a sustainable solution to improve crop growth under saline stress.

synthetic biology↗

bioRxiv2025

Respiratory syncytial virus infection confers heterologous protection against SARS-CoV-2 via induction of γδ T cell-mediated trained immunity and SARS-CoV-2 reactive mucosal T cells

The respiratory viruses can concurrently or sequentially infect a host and influence the trajectory of each other. The underlying immune mechanisms are not well understood. Here, we investigated whether respiratory syncytial virus (RSV) infection affects host vulnerability to subsequent SARS-CoV-2 infection in two murine models of SARS-CoV-2 infection. We found that prior RSV infection-induced heterologous protection against subsequent SARS-CoV-2 infection was dose and time dependent. RNA-seq and immunological analyses revealed that RSV triggered the activation of lung antigen presenting cells (APC)s and SARS-CoV-2 reactive mucosal T cells at day 9, which declined at 1 month. RSV also induced the expansion of lung {gamma}{delta} T cells and the upregulation of their cellular metabolic pathways. Furthermore, RSV infection in TCR{delta}-/- mice, which are deficient of {gamma}{delta} T cells, resulted in a reduced SARS-CoV-2 reactive mucosal T cell response and subsequent increased viral loads and higher levels of virus-induced inflammatory responses in the lung upon SARS-CoV-2 challenge compared to the wild-type mice. In summary, our findings suggest that RSV infection provides heterologous protection against the subsequent SARS-CoV-2 infection via induction of {gamma}{delta} T cell-mediated trained immunity in the lung and SARS-CoV-2 reactive mucosal T cell responses.

microbiology↗

bioRxiv2025

An expanded reference catalog of translated open reading frames for biomedical research

Non-canonical (i.e., unannotated) open reading frames (ncORFs) have until recently been omitted from reference genome annotations, despite evidence of their translation, limiting their incorporation into biomedical research. To address this, in 2022, we initiated the TransCODE consortium and built the first community-driven consensus catalog of human ncORFs, which was openly distributed to the research community via Ensembl-GENCODE. While this catalog represented a starting point for reference ncORF annotation, major technical and scientific issues remained. In particular, this initial catalogue had no standardized framework to judge the evidence of translation for individual ncORFs. Here, we present an expanded and refined catalog of the human reference annotation of ncORFs. By incorporating more datasets and by lifting constraints on ORF length and start-codon, we define a comprehensive set of 28,359 ncORFs that is nearly four times the size of the previous catalog. Furthermore, to aid users who wish to work with ncORFs with the strongest and most reproducible signals of translation, we utilized a data-driven framework (i.e. translation signature scores) to assess the accumulated evidence for any individual ncORF. Using this approach, we derive a subset of 7,888 ncORFs with translation evidence on par with canonical protein-coding genes, which we refer to as the Primary set. This set can serve as a reliable reference for downstream analyses and validation, with a particular emphasis on high quality. Overall, this update reflects continual community-driven efforts to make ncORFs accessible and actionable to the broader research public and further iterations of the catalog will continue to expand and refine this resource.

genomics↗

bioRxiv2025

Common Signatures of Neutrophils in Diverse Disease Conditions

Neutrophils are traditionally recognized for their pro-inflammatory roles. However, accumulating evidence has begun to highlight the plasticity of transcriptional states of neutrophils during pathological insults. Whether such unconventional neutrophils may share commonality across diverse disease conditions is incompletely understood. Here, we systematically profile over 500,000 neutrophils in key immune compartments and disease-inflicted tissues of the mouse models of metabolic disorder, autoimmunity, tissue damage, peripheral cancers, and intracranial gliomas. Of importance, we observe two distinct neutrophil clusters with unique immune features. The first cluster, characterized by Cd274, Vegfa, and antigen presentation, is highly enriched within the diseased tissues. In contrast, the second cluster with elevated Cd244 and type 2 immune response but reduced maturation markers primarily emerges in the peripheral blood and spleens of specific disease scenarios. These results have elucidated the common signatures of neutrophils in response to various pathological conditions, providing a valuable reference for diagnostic and therapeutic applications.

immunology↗

bioRxiv2025

Punctuated mutagenesis promotes multi-stepevolutionary adaptation in human cancers

The rate of acquisition of genomic changes in cancer has been the topic of much discussion, with several recent investigations finding evidence of punctuated evolution instead of gradual accumulation of such changes. Despite forays into the description and quantification of these punctuated events, the effects of such changes on subsequent cancer evolution remain incompletely understood. Here we investigate how non-gradual mutagenesis affects the ability of tumor cells to acquire and retain fitness-enhancing adaptations. We find that punctuated mutagenesis significantly facilitates adaptation in scenarios where adaptation requires crossing a fitness valley, i.e. when multiple mutations are required which individually are maladaptive but jointly confer a fitness advantage. By increasing the probability that multiple mutations occur in close succession, punctuation increases the chance that mutants in a fitness valley mutate further to reach a fitness peak before going extinct. Analyzing data from The Cancer Genome Atlas, we find that tumors with signatures of APOBEC mutagenesis, which has been shown to proceed in episodic bursts, exhibit patterns consistent with higher rates of crossing fitness valleys. Lastly, we characterize how the interplay between this enhanced ability to cross fitness valleys and adaptation-limiting effects of clonal interference affects overall adaptability in complex fitness landscapes.

cancer biology↗

bioRxiv2025

PROFET Predicts Continuous Gene Expression Dynamics from scRNA-seq Data to Elucidate Heterogeneity of Cancer Treatment Responses

Single-cell RNA sequencing profiles cellular heterogeneity but captures only static snapshots, limiting inference of gene expression dynamics. We developed PROFET (Particle-based Reconstruction Of generative Force-matched Expression Trajectories), a framework that reconstructs continuous, nonlinear single-cell trajectories from sparsely sampled scRNA-seq time series. PROFET combines a particle-based gradient-flow algorithm with simulation-free force matching to accurately infer cellular dynamics. Across mouse and human in vitro datasets and an in vivo axolotl regeneration dataset, PROFET achieved 2.6-12.5X lower prediction error than ten state-of-the-art trajectory inference methods. Applying PROFET to newly generated scRNA-seq data from a palbociclib-treated MCF7 cell line and three published breast cancer patient datasets, we reconstructed treatment-response trajectories and identified a resistant cell subpopulation exhibiting large phenotypic shifts and enrichment of the surface markers UNC5B, TLR3, PCDH19, PROCR, SLITRK6, and SEMA6B. PROFET provides a biologically grounded framework for reconstructing cell-state dynamics from static single-cell data across development, regeneration, and therapeutic response.

bioinformatics↗

bioRxiv2025

Single-Cell and Spatial Profiling of Tumor Microenvironment Heterogeneity in Human Osteosarcomas

Osteosarcoma, a highly heterogeneous malignant bone tumor, exhibits substantial interpatient and intratumoral heterogeneity. Utilizing integrated single-cell RNA sequencing and spatial transcriptomics, we uncovered distinct tumor microenvironment (TME) transcriptional profiles across patients, highlighting profound interpatient heterogeneity. Intratumorally, malignant cells primarily followed two differentiation trajectories, converging into osteoblastic and chondroblastic functional states, and hypoxia may be the influencer; notably, within individual patients, tumor cells exhibited greater transcriptional similarity driven by specific transcription factors, despite these divergent states. Spatial analysis revealed patient-specific TME cellular co-localization patterns, alongside conserved spatial relationships: vascular components (endothelial cells, pericytes) demonstrated strong co-localization, while immune cells (T cells, myeloid cells) clustered within shared regions. Crucially, these functional states occupied distinct microniches: osteoblastic regions were enriched with osteoclasts, vascular components, and immune cells, whereas chondroblastic regions displayed the opposite composition and were preferentially located in hypoxic, vascular-poor niches, exhibiting significant enrichment of hypoxia-related signaling pathways. Furthermore, our data suggest osteosarcoma cells may activate fibroblasts via the SPP1 signaling pathway, indicating fibroblasts act as key intermediaries in tumor-directed TME modulation. This study comprehensively delineates the intricate landscape of osteosarcoma heterogeneity, defining distinct functional cellular states, their spatially organized TME niches, and a potential SPP1-mediated tumor-fibroblast regulatory axis. This comprehensive analysis elucidates the intricate interpatient and intratumoral heterogeneity in osteosarcoma, revealing functional and spatial organization within the tumor and its microenvironment.

cancer biology↗

bioRxiv2025

Towards the Development of Isoenergetic Peptide Nucleic Acid Based Probes Targeting Double-Stranded RNAs Through Enhancing Sequence-Specific Stacking Interactions

Peptide nucleic acid (PNA), a synthetic nucleic acid analog, exhibits substantial potential in biotechnology and therapeutic applications due to its high binding affinity and nuclease/protease resistance. Chemically modified PNAs capable of forming stable triplex structures with double-stranded RNAs (dsRNAs) under near-physiological conditions further expand their utility by enabling sequence-specific precise targeting and probing of functional RNA structural motifs. However, the presence of inverted Watson-Crick pairs (C-G and U-A) may significantly weaken the triplex formation of the dsRNA-binding PNAs (dbPNAs). Our previous work demonstrated that dbPNA P3 (composed of L, T, and Q monomers for the recognition of G-C, A-U, and C-G base pairs, respectively) can stimulate ribosomal frameshifting by binding to rHP2, a model RNA hairpin structure in an mRNA, albeit with suboptimal efficiency, due to its significantly weakened Q*C-G triple formation. We hypothesize that incorporating s2U adjacent to Q may offer unique stacking and hydrogen bonding interactions facilitating the development of isoenergetic dbPNA-based probes binding toward dsRNAs with varied sequences. In this study, we investigate how incorporating s2U adjacent to Q residues in P3 influences its binding to rHP2. Bio-layer interferometry (BLI) and non-denaturing polyacrylamide gel electrophoresis (PAGE) analyses demonstrate that substituting T with s2U at the N-terminal position adjacent to Q (P3-2QT) enhances binding affinity by [~]10-fold compared to unmodified P3, whereas C-terminal substitution (P3-TQ2) yields only a 2-fold improvement. Consistent with these findings, a cell-free dual-luciferase reporter assay reveals that P3-2QT significantly increases ribosomal frameshifting efficiency compared to P3 and P3-TQ2. Molecular dynamics simulations further indicate that P3-2QT maintains enhanced PNA-PNA stacking stability, particularly between s2U3 and Q4, suggesting a structural basis for its superior activity. Intriguingly, analogous s2U substitution in the P5 oligomer with the Q replaced by L does not confer a comparable enhancement in binding to the target RNA (rHP1) and frameshifting stimulation, highlighting the context-dependent nature of this modification. To assess the broader applicability of the s2U-Q motif, we examined its effect in dbPNAs targeting the RNA panhandle structure of influenza virus A and precursor microRNA-21, respectively. Both PAGE and BLI data confirm that s2U incorporation improves binding affinity, reinforcing the generality of this strategy. These findings underscore the potential of sequence-dependent uracil thiolation in optimizing triplex-forming dsRNA-binding PNAs, warranting further exploration of modified nucleobase designs to enhance their binding and functional properties. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/662161v1_ufig1.gif" ALT="Figure 1"> View larger version (32K): org.highwire.dtl.DTLVardef@15d86aborg.highwire.dtl.DTLVardef@1347369org.highwire.dtl.DTLVardef@852040org.highwire.dtl.DTLVardef@84b0a_HPS_FORMAT_FIGEXP M_FIG C_FIG HighlightsO_LIThiolation of uracil upstream of Q base in PNA markedly enhances triplex binding affinity and enables isoenergetic and orthogonal targeting/activation. C_LIO_LIN-terminal s2U modification adjacent to Q residues increases PNA-dsRNA binding by [~]10-fold and significantly boosts ribosomal frameshifting efficiency. C_LIO_LIBiophysical assays and molecular dynamics simulations reveal that thiolation improves PNA stacking stability and slows dissociation, thereby enhancing functional activity toward structured RNA targets. C_LIO_LIThe general applicability of s2U modification is demonstrated with influenza A virus RNA panhandle structure and precursor micoRNA-21 targets, underscoring its broad potential for optimizing PNA-based therapeutics and biotechnological tools. C_LI

biochemistry↗

bioRxiv2025

Pollinate to Suppress: Sterile Pollen and Certation Effects in Palmer amaranth (Amaranthus palmeri)

The sterile pollen technique, which involves applying X-ray irradiated pollen to female plants, has shown promising results in reducing seed production in dioecious Palmer amaranth (Amaranthus palmeri S. Wats.). However, field-scale implementation of this method requires a carrier for pollen delivery, as applying pure pollen on a large scale is not practical. Additionally, variability in flowering time within and among individual plants may impact the techniques effectiveness. Mass pollination may also lead to a female-biased sex ratio in the progeny, a phenomenon known as certation. Therefore, in this study, we aimed to: (1) identify a suitable dry (inert) diluent and the most effective pollen-to-diluent ratio for large-scale application, and (2) determine the most effective combination of initiation time, frequency, and number of sterile pollen applications, and 3) test for evidence of certation in A. palmeri. Plants were grown in the greenhouse in summer 2021. Sterilized pollen irradiated at 300 Gy was mixed with talc or wheat powder flour, respectively, at six v/v ratios (pollen%/powder%) of 0/100 (powder alone), 5/95, 10/90, 25/75, 50/50, or 100/0 (pure irradiated pollen). An equal amount of the pollen-diluent powder mixture was then brushed onto the standardized lengths of inflorescence of receptive female plants. Flower and seed number on each inflorescence was counted and used to calculate seed set in each treatment. The findings showed that a minimum of 25% irradiated pollen in the mixture, either with talc powder or wheat flour, can effectively reduce seed set in A. palmeri. Building on this, a second round of greenhouse experiments was conducted in fall 2021, where female plants were pollinated with a 25% irradiated pollen and talc powder mixture using a powder duster. Pollination treatments were initiated at different times after anthesis (7, 14, and 21 days), and the number of applications varied (once, twice, or three times) with intervals of one, two, or three weeks between applications. The greatest reduction in seed output was achieved when sterile pollen application began seven days after anthesis and was repeated three times at 7-day intervals. Evidence of certation was also observed in A. palmeri, with the progeny of mass-pollinated females showing a higher female ratio (58%) compared to the open-pollinated population (47%). Mass pollination also led to a slight, though not statistically significant, reduction in plant size traits such as height and number of branches, providing an additional potential benefit of the sterile pollen technique.

plant biology↗

bioRxiv2025

Abnormal Elevated Connectivity During Language Processing is Associated with Poor Cognitive Performance in Children with Self-limited Epilepsy with Centrotemporal Spikes

Self-Limited Epilepsy with Centrotemporal Spikes (SeLECTS) is associated with language impairments despite seizures originating in the motor cortex, suggesting aberrant cross-network interactions. Here we tested whether functional connectivity in SeLECTS during language tasks predicts language performance. We recorded high-density EEG from right-handed children with SeLECTS (n=31) and age-matched controls (n=32) during verb generation, repetition, and resting tasks. Phonological awareness was assessed using the Comprehensive Test of Phonological Processing-2. Connectivity between bilateral motor cortices and language regions (the left inferior frontal and superior temporal cortices and their right hemisphere homologues) was measured using weighted Phase Lag Index (wPLI). Children with SeLECTS demonstrated significantly elevated connectivity between motor and language regions during language processing. Motor-to-frontal connectivity was higher in SeLECTS during both verb generation and repetition tasks. Frontal-to-temporal connectivity was elevated specifically during verb generation. Higher interhemispheric connectivity (between the left and right hemispheres) during language tasks strongly predicted worse phonological awareness in children with SeLECTS ({beta}= -40 to -61, all p<0.005), but not controls. Together, we found that children with SeLECTS exhibited pathologically elevated connectivity between motor and language networks that was strongly associated with impaired phonological awareness. These findings identify aberrant interhemispheric connectivity as a pathophysiological mechanism underlying language dysfunction and establish EEG-based connectivity measures as a potential biomarker for guiding targeted neuromodulation therapies to treat cognitive impairments in pediatric epilepsy.

neuroscience↗

bioRxiv2025

Unlocking the Neuropeptidome using a Novel Endogenous Peptidomics Framework

Endogenous peptides have garnered increasing attention over the past decade driven by the development of advanced analytical methods. However, large-scale investigations of peptides as potential disease biomarkers or drug candidates are still hindered by their challenging biochemical properties and the scarcity of specialized analytical tools. Among these, neuropeptides are particularly challenging to study due to their low in vivo concentration, rapid turnover rate, and high structural variability. Data-independent acquisition (DIA) mass spectrometry (MS) has shown great ability in profiling low-abundance ions. Nevertheless, most available DIA analytical tools are designed for proteomics studies and are not suitable for endogenous peptides, as there is no set enzymatic cleavage for these peptides. Here, we introduce the novel EndoGenius platform, paired with DIA-NN, to achieve high-confidence neuropeptide identification using an updated spectral library for DIA MS analysis. By employing orthogonal offline fractionation, ion mobility instrumentation, and an optimized database searching algorithm specifically for neuropeptides, we have constructed the largest crustacean neuropeptide spectral library to date. With this library, in combination with neural networking technology, we report a 100-fold increase in the number of neuropeptides identified in all Cancer borealis tissues analyzed. We also cross-validated these findings with transcriptomics data to enhance identification confidence. This workflow presents a novel analytical framework for DIA peptidomics analysis, offering a robust approach to studying neuropeptides and other endogenous peptides. TOC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=140 SRC="FIGDIR/small/659356v1_ufig1.gif" ALT="Figure 1"> View larger version (28K): org.highwire.dtl.DTLVardef@1bae342org.highwire.dtl.DTLVardef@9e26d8org.highwire.dtl.DTLVardef@1084f06org.highwire.dtl.DTLVardef@7c1371_HPS_FORMAT_FIGEXP M_FIG C_FIG SynopsisWe present a framework that capitalizes on robust analytical innovations and an optimized bioinformatics pipeline to provide the most comprehensive snapshot of the crustacean neuropeptidome to-date.

neuroscience↗

bioRxiv2025

Mitochondrial calcium influx-driven bioenergetics in the dopaminergic system selectively enable drug reward

Drugs of abuse hijack the brains reward system, driving pathological dopamine surges that underlie compulsive behavior and addiction. However, directly targeting dopamine signaling for treatment risks disrupting natural reward processes. Here, we identify a bioenergetic mechanism that selectively promotes addiction-related dopamine release and behaviors. Opioids and methamphetamine, but not natural rewards, induce mitochondrial calcium (Ca2+) influx via the mitochondrial calcium uniporter (MCU) in dopaminergic terminals of the nucleus accumbens. Optogenetic stimulation reveals that this mitochondrial Ca2+ influx occurs exclusively during high-intensity dopaminergic neuronal activation. This Ca2+ influx drives rapid ATP production, compensating for energy deficits caused by neuronal hyperactivity and enabling sustained dopamine release. Genetic deletion or pharmacological inhibition of MCU in dopaminergic neurons selectively reduces drug-induced dopamine release and prevents addictive behaviors while sparing natural reward processing in mice. These findings uncover a distinct mitochondrial bioenergetic mechanism underlying drug reward and propose MCU as a promising therapeutic target for addiction treatment.

neuroscience↗

bioRxiv2025

Structural Basis for Cas9-Directed Spacer Acquisition in Type II-A CRISPR-Cas Systems

CRISPR-Cas systems confer prokaryotic adaptive immunity by integrating foreign DNA (prespacers) into host arrays. Type II-A systems employ Cas9 for protospacer adjacent motif (PAM) recognition and coordinate with Csn2 and the Cas1-Cas2 integrase during spacer acquisition, yet their structural basis remains unresolved. Here, we report cryo-EM structures of the Enterococcus faecalis Cas9-Csn2-Cas1-Cas2 supercomplex in apo and DNA-bound states. The apo-state structure (Cas92-Csn28-Cas18-Cas24) adopts a resting conformation, with Cas9 locked in a nuclease-inactive state and Cas1-Cas2 sterically blocked from prespacer loading. Upon DNA engagement, Cas9 undergoes a conformational transition, forming a prespacer catching complex that threads the DNA through Csn2s central channel. This architecture enables Cas9 to interrogate the PAM sequence while sliding along the DNA, with Cas9 and Csn2 jointly define a 30-bp DNA segment which matches the prespacer length. Subsequent dissociation of Cas9 triggers a structural reconfiguration of the Csn2-Cas1-Cas2 assembly. The PAM-proximal DNA becomes accessible, and Cas1-Cas2 relocates to bind to the exposed DNA, enabling further prespacer processing and directional integration. These findings reveal how Cas9 collaborates with Csn2 and Cas1-Cas2 to couple PAM recognition with prespacer selection, resolving the dynamic structural transitions that ensure fidelity during type II-A CRISPR adaptation.

molecular biology↗

bioRxiv2025

Oblique Thick Light-Sheet Microscopy with Spatiotemporal 3D Localization for RNA Imaging in Intact 50 μm-Thick Sections

Neuron typing in intact brain sections demands 3D imaging reconciling thickness compatibility with large-area coverage--a persistent challenge for RNA imaging methods limited by either restricted fields-of-view (<1 mm2) or thin-section constraints (<20 m). Here we introduce oblique thick light-sheet microscopy integrated with spatiotemporal 3D localization, enabling multiplexed RNA imaging across 50 m-thick tissue sections and centimeter-scale regions. The 45{degrees} illumination geometry achieves optical-interference-free imaging in >100 m-thick tissues during single-plane scans, while a spatiotemporal localization algorithm recovers submicron resolution by pinpointing fluorescence in situ hybridization (FISH) spots within volumetric excitation. This strategy reveals layer-spanning neuronal distributions and region-specific expression gradients unattainable with conventional RNA imaging approaches. By resolving the historical trade-off between imaging depth and spatial coverage, our platform advances whole-brain transcriptomics, enabling 3D neuron typing capability critical for deciphering brain-wide cellular architectures.

biophysics↗

bioRxiv2025

GENERanno: A Genomic Foundation Model for Metagenomic Annotation

The rapid growth of genomic and metagenomic data has underscored the pressing need for advanced computational tools capable of deciphering complex biological sequences. In this study, we introduce Generanno, a compact yet powerful genomic foundation model (GFM) specifically optimized for metagenomic annotation. Trained on an extensive dataset comprising 715 billion base pairs (bp) of prokaryotic DNA, Generanno employs a transformer encoder architecture with 500 million parameters, enabling bidirectional attention over sequences up to 8192 bp at single-nucleotide resolution. This design addresses key limitations of existing methods, including the inability of traditional Hidden Markov Models (HMMs) to handle fragmented DNA sequences from multi-species microbial communities, as well as the suboptimal tokenization schemes of existing GFMs that compromise fine-grained analysis. At its core, Generanno excels in identifying coding regions from fragmented and mixed DNA sequences--a hallmark of metagenomic analysis. It achieves superior accuracy compared to traditional HMM-based methods (e.g., GLIMMER3, GeneMarkS2, Prodigal) and recent LLM-based approaches (e.g., GeneLM), while demonstrating robust generalization ability on archaeal genomes. Leveraging its advanced contextual understanding capability, Generanno further enables two essential functions: pseudogene prediction and taxonomic classification--both performed based solely on raw sequence data, without reliance on reference databases or comparative genomics. These functionalities collectively streamline the metagenomic analysis pipeline, significantly reducing preprocessing requirements and enabling end-to-end interpretation of sequencing data. Beyond its primary role in metagenomic annotation, Generanno also serves as a powerful GFM. To evaluate its broader utility, we curated the Prokaryotic Gener Tasks--a comprehensive benchmark suite specifically tailored for prokaryotic genomic analysis. It includes gene fitness prediction, antibiotic resistance identification, gene classification, and taxonomic classification, reflecting diverse aspects of functional genomics. On this benchmark, Generanno consistently outperforms existing GFMs such as DNABERT-2, NT-v2, and GenomeOcean, demonstrating strong generalization capabilities across a wide range of genomic tasks. Overall, Generanno provides a unified framework that integrates multiple critical functions for metagenomic annotation and beyond. By eliminating dependencies on external resources and offering rich contextual understanding of genomic sequences, this work delivers a foundational tool for advancing functional genomics in complex microbial communities. Implementation details and supplementary resources are available at https://github.com/GenerTeam/GENERanno.

genomics↗

bioRxiv2025

IL-17A-driven Macrophage Disorder Promotes Plaque Instability in Psoriatic Atherosclerosis

Psoriasis is a common chronic inflammatory skin disease that predisposes individuals to cardiovascular diseases such as atherosclerosis. However, the underlying mechanisms linking these conditions have not yet been fully elucidated. Recent studies have indicated that the inflammatory cytokine IL-17A plays a significant role in both diseases. The aim of this study was to investigate how psoriasis affects the stability of atherosclerotic plaques via the IL-17A/IL-17RA pathway. We performed single-cell sequencing on patients with both psoriasis and atherosclerosis to analyze changes in the immune microenvironment within their carotid plaques and psoriatic lesions. We found that IL-17A significantly upregulated the expression of pro-inflammatory factors (e.g., CXCL8) in macrophages of psoriatic atherosclerosis patients, leading to weakening of the fibrous cap structure of plaques. Additionally, IL-17A further exacerbated plaque instability by interfering with macrophage lipid metabolism, particularly sphingolipid metabolism. Finally, using in vitro experiments and animal models, we demonstrated that IL-17A enhances pro-inflammatory and metabolic abnormalities in macrophages by downregulating PPAR{gamma}. Therapeutic strategies targeting IL-17A may contribute to the simultaneous mitigation of psoriasis and atherosclerosis-associated cardiovascular risk, providing new directions for clinical intervention.

cell biology↗