Biology subjects

Ma, D.

Publications and source records attributed to Ma, D..

At least 19 recordsLinked to original sources

bioRxiv2026

NeCS-Flow: Necrosis-Guided Contrast-Enhanced MRI Synthesis with Rectified-Flow Refinement

Background: Gadolinium-based contrast agents raise concerns about tissue deposition, adverse reactions, and increased costs. Purpose: To develop and validate a deep learning pipeline for gadolinium-free post-contrast T1w brain MRI synthesis incorporating necrotic scaling and Posterior-Mean Rectified Flow (PMRF) refinement, and to evaluate diagnostic utility through a blinded multi-reader study. Study Type: Retrospective. Population: 454 patients with adult-type gliomas (grade 2-4) from four publicly available datasets. Training used 374 patients; internal testing used 60 held-out patients; external validation used 20 patients. Field Strength/Sequence: 1.5-3.0 T; pre-contrast T1w, T2w, and FLAIR as inputs; post-contrast T1w as synthesis target. Assessment: A three-stage pipeline comprising nnU-Net Necrotic core segmentation, necrotic-scaling-guided U-Net Contrast Synthesis, and PMRF perceptual refinement (NeCS-Flow) was evaluated using whole-brain and tumor-region similarity metrics, enhancing tumor Dice scores, perceptual quality metrics, and a blinded three-reader study assessing diagnostic accuracy, enhancement detection, image quality, and real-versus-synthetic discriminability. Statistical Tests: Paired t-tests and two one-sided tests for model comparison; Fisher's exact test and two-sample t-tests for reader study comparisons, with p < 0.05 considered significant. Results: Necrotic scaling consistently improved real versus synthetic enhancing tumor Dice internally (HGG: 0.793 to 0.816) and externally (HGG: 0.465 to 0.612). NeCS-Flow outperformed two benchmark architectures on all quantitative metrics in internal and external testing, although absolute enhancing tumor accuracy declined for all models on the external cohort. PMRF refinement improved perceptual realism across both tumor types, reducing both FID and KID. Readers distinguished synthetic from real images only modestly above chance (overall accuracy 61.7%), and no significant differences between real and synthetic images were found for any clinical metric. Data Conclusion: NeCS-Flow synthesizes perceptually realistic and diagnostically equivalent post-contrast T1w brain MRI, with necrotic scaling improving enhancing tumor delineation and PMRF refinement improving perceptual realism across gliomas. Performance on an external cohort was preserved relative to benchmark methods, though reduced in absolute terms.

bioinformatics↗

bioRxiv2026

Streamline CNV - A Handy Nextflow Pipeline for Chromosomal Copy Number Variation Analysis

Background Aneuploidy, characterized by imbalanced chromosomal copy number variation (CNV), occurs in both normal somatic tissues and a wide range of diseases. Low pass whole genome sequencing (LP-WGS) to detect CNVs in cells and tissues has been widely used in all biological research. Existing informatics tools for detecting CNV often require computational expertise, often posing challenges for wet-lab biologists. To address this need, we developed Streamline CNV (SLCNV) - a user-friendly and flexible copy number analysis pipeline that allows researchers to perform many copy number-related analyses steps with a single, straightforward command. Results Streamline CNV is based on Nextflow and is packaged in a Docker image that can be executed using Singularity, making it portable and reproducible across different user environments. The pipeline automatically processes input data, performs sequencing quality control to filter problematic samples, outputs mapping statistics, CNV calling, and generates outputs including intuitive CNV plots, segmentation files (with statistics), annotation of genes on altered chromosomes, evaluation of proportion of chromosomal regions that are non-euploid. Based on user preferences, it can cluster samples solely based on CNV patterns, map the genomic location and density of genes of interest along chromosomes, and visually highlight regions with evident CNVs. In addition, it allows users to select and order chromosomes for display in plots, define sample label color palettes, and choose whether to include sample labels in the clustering visualizations. It also allows users to specify the amount of computing resources to allocate to the pipeline, such as CPU, memory, and runtime. Streamline CNV can be customizable and upgradable. It works with any species and genome assembly and efficiently supports both single-cell and bulk sequencing data with improved performance coding. Jobs can be distributed across cores of a basic Unix workstation, multiple nodes in a high-performance computing cluster using the Slurm scheduler, or cloud environments, as needed. Conclusions We demonstrated the tool using an in-house sequencing dataset of human and mouse cell lines. Our results showed that the Streamline CNV pipeline effectively detected copy number patterns and generated informative summaries. It annotated the findings by identifying affected genes within the copy-number segments and at the break-end regions. It also reported the proportions of altered chromosomal regions impacted by copy number changes for each sample. The clustering plot demonstrated the relationships between samples based on their copy number profiles. Gene density plots aid in interpreting how genes from distinct pathways are associated with CNV pattern alterations. This tool enables researchers, regardless of bioinformatics expertise, to perform comprehensive CNV analyses across a wide range of scenarios. It also facilitates the interpretation of the copy number results and makes it possible for transforming raw CNV data into further exploration of meaningful biological insights.

bioinformatics↗

bioRxiv2026

Restoration of deficient IL-15 signaling enhances innate lymphoid cell immunity in brain metastasis

Natural killer (NK) cells and type 1 innate lymphoid cells (ILC1s), collectively known as group 1 innate lymphoid cells (ILCs), are critical mediators of anti-tumor immunity, yet their role in brain metastasis remains poorly defined. Using single-cell RNA sequencing and functional depletion models, we show that group 1 ILCs fail to provide adequate tumor control in breast cancer brain metastasis (BCBM). In contrast to the liver, where diverse, functionally competent group 1 ILC populations facilitate excellent metastatic control, group 1 ILCs in BCBM show limited diversity and profound tissue-specific dysfunction such that their depletion had no effect on tumor burden despite modest parenchymal infiltration. We attribute this group 1 ILC dysfunction to severely restricted IL-15 availability, with IL-15R protein detected at 500-fold lower concentration in the brain than in the liver. Local IL-15 complex administration restored group 1 ILC accumulation, cytotoxicity, and tissue residency, significantly reducing brain metastatic burden independent of T cells. Intracranial delivery of IL-15-secreting induced pluripotent stem-cell-derived (iPSC)-NK cells, already in clinical testing for non-small cell lung cancer, significantly reduced tumor burden. Collectively, these findings reveal how tissue-specific differences in cytokine availability shape group 1 ILC population diversity and disease response, establishing localized IL-15 signaling as a compelling strategy to unlock innate immunity against intracranial malignancies.

immunology↗

bioRxiv2026

Cell-of-origin shapes tumor subtype in BRCA1-associated triple-negative breast cancer

Pathogenic germline BRCA1 variants greatly increase lifetime breast cancer risk, with no targeted prevention. Accrual of mutations following DNA repair errors in luminal progenitors is considered the chief mechanism of triple-negative breast cancer (TNBC) initiation, which cannot explain the organ specificity nor the phenotypic spectrum of the disease. Here we show that TNBC also originates in basal-myoepithelial cells, and that the cell of origin shapes TNBC subtype through aberrant epithelial differentiation, likely due to pleiotropic role of BRCA1 in regulating hormone signaling. Single-cell RNA sequencing of 67,001 cells from Wap-Cre Brca1/p53 mice and reanalysis of published Blg-Cre data show that aberrant basal-myoepithelial differentiation (Wap-Cre) generates the mesenchymal subtype (TNBC-M) and aberrant luminal differentiation (Blg-Cre) the basal-like subtype (TNBC-BL1). We also show that both subtypes occur at comparable frequency in BRCA1 carriers. Aberrant basal-myoepithelial differentiation precedes tumor formation, and only tumors derived from transplanted basal cells reproduce the basal-containing phenotype of spontaneous tumors. Comparison with a developmental atlas identifies de-differentiation of myoepithelial cells into basal cells lacking myoepithelial markers, a fetal state, whereas experimental metastases shift toward luminal states while retaining a TNBC-M-like transcriptional program. These findings support the inclusion of basal-myoepithelial and luminal cells in targeted prevention strategies for BRCA1 carriers, and adoption of TNBC subtyping for patient stratification and improving outcomes.

cancer biology↗

bioRxiv2026

ctDNA Release Heterogeneity in Luminal Breast Cancer Revealed by Single-Cell Multi-Omics Spatial Analysis

Backgroud Breast cancer is a leading cause of cancer-related mortality, and HR+/HER2-; is the predominant subtype. Molecular pathology, including PIK3CA and ESR1 mutation, informs prognosis and treatment selection. Circulating tumor DNA (ctDNA) offers a non-invasive approach for cancer monitoring, but its clinical utility is limited by tissue plasma discordance, reflecting heterogeneous ctDNA release. The cellular and spatial determinants of this release remain poorly understood, particularly in HR+/HER2-; subtype, where heterogeneity across subclones complicates liquid biopsy interpretation. Results To identify the cellular and spatial determinants of ctDNA release, we developed scMASTER, integrating single-cell transcriptomes and mutations, spatial transcriptomics and matched tumor and plasma DNA sequencing. In ten patients with non-metastatic HR+/HER2- breast cancer, eight recurrent malignant epithelial states showed distinct ctDNA release potential. Antigen-presentation, stress, mitosis and mesenchymal-like states showed high release. PIK3CA and ESR1 mutations were linked to distinct functional states and altered ctDNA detectability. Three spatial architectures, EMT-enriched regions, intraductal luminal progenitors and avascular hypoxic zones, showed high release. Tumor-microenvironment interactions were bidirectional: anti-tumoral immunity correlated with reduced release, whereas immunomodulatory components correlated with increased release. A stratification model based on these features identified high-risk, immunosuppressed patients with poor prognosis, validated across external cohorts. Conclusions Our study establishes a single-cell spatial framework for decoding ctDNA release heterogeneity, linking tumor states, somatic mutations, spatial architecture, and immune interactions to ctDNA release. These findings provide mechanistic insights into tissue-plasma discordance, offer a biological rationale for interpreting ctDNA dynamics, refine patient risk stratification and liquid biopsy-based monitoring in HR+/HER2-; breast cancer.

cancer biology↗

bioRxiv2026

Xenon improves autism-like behaviors in mice through potentiation of PVT-CeA glutamatergic neurotransmission

Autism spectrum disorder (ASD) is a common neurodevelopmental disease with no currently effective treatments. In this study, Xenon (Xe), a noble gas used clinically as an anesthetic and a neuroprotectant, has been investigated for its potential therapeutic effects in ASD. Two genetic ASD mouse models (Mef2c mutant and Shank3-/- mice) were exposed to a low concentration of xenon (25%) mixed with oxygen (30%) and balanced with nitrogen for a single exposure of 30 min or for 10 min per day for 10 days. These Xe exposure paradigms rescued ASD-like behaviors in both male and female mice. The behavioral improvements persisted for up to 10 days following termination of the 10-day exposure paradigm. Mechanistically, Xe reduced glutamic acid decarboxylase expression in the inhibitory neurons (verified with RNAseq) of the paraventricular thalamic nucleus (PVT) and decreased GABA release during social interaction. Targeted infusion of the GABAA receptor agonist muscimol into the PVT abolished the Xe-mediated behavioral improvements. Reduced GABAergic transmission following Xe exposure increased PVT glutamatergic neuronal activity. Chemogenetic inhibition of these neurons eliminated the therapeutic effects of Xe, whereas chemogenetic activation mimicked the Xe-induced behavioral improvements. Furthermore, opto-inhibition of PVT glutamatergic projections to the central amygdala (CeA) blocked Xe-mediated behavioral improvement. Opto-activation of the PVT-CeA glutamatergic circuit reversed ASD-like behaviors. These findings demonstrate that Xe ameliorates ASD-like phenotypes in mouse models by modulating the PVT Glu-CeA circuit, supporting Xe as a novel potential therapy for ASD.

animal behavior and cognition↗

bioRxiv2026

Molecular dynamics descriptors for 1,079 post-translationally modified protein systems

Databases of post-translational modifications (PTMs) catalogue modified sites and increasingly add static structural context, but trajectory-derived descriptors remain scattered across specialised tools and general molecular dynamics archives. Dyna-MO PTM brings together 1,079 AlphaFold 3-seeded systems covering lysine acetylation, lysine and arginine monomethylation, and serine, threonine and tyrosine phosphorylation. Each system is linked to three completed 10 ns replicas generated with CHARMM36m and TIP3P, for 32.37 s of aggregate sampling. A 118-column table joins simulation and quality-control provenance with global relaxation measures, site solvent exposure, rotamers, secondary structure and ionic-contact proxies. Versioned identifiers connect the records to starting structures, trajectories, manifests and analysis scripts. Researchers can use the resource to filter PTM contexts, reproduce descriptors, prioritise longer simulations and evaluate trajectory-analysis or generative methods. The trajectories describe finite-window relaxation rather than equilibrium free energies, kinetics or matched PTM effects.

biophysics↗

bioRxiv2026

Invariant scaling of the Species Abundance Distribution in observed and simulated marine plankton communities

Marine plankton are functionally diverse and span over five orders of magnitude in diameter, with important consequences for marine biogeochemical cycles. Marine ecosystem simulations are beginning to resolve this diversity; however, major uncertainties persist regarding the structure and function of planktonic ecosystems. Here we diagnosed plankton Species Abundance Distributions (SADs) in large-scale surveys and in a global, mechanistic plankton community simulation. The fitted slopes of the SADs vary by less than 10% across latitude, season, and biome in both observations and the simulation. Fitting parametric SADs further reveals spatial structure in the shape and functional form of the SAD aligned with established biogeographic provinces. Together, these results demonstrate a largely invariant structure of marine plankton communities that persists despite strong environmental gradients and taxonomic turnover. These findings suggest that the emergent shape and scaling of plankton SADs reflect fundamental constraints on community assembly and provide a compact quantitative diagnostic for planktonic ecosystem structure.

ecology↗

bioRxiv2026

Minimally invasive monitoring of clonal evolution through integrated single cell and ctDNA analysis

Circulating cell-free DNA (cfDNA) offers a minimally invasive lens into tumor evolution. However, the accurate quantification of clonal composition from cfDNA remains challenging. Existing methods for clone tracking using liquid biopsies are constrained by issues such as their reliance on bulk tissue references, incomplete representations of clonal architecture or limited breadth of mutation panels. To address these limitations, we developed cfClone, a Bayesian framework that integrates single-cell whole-genome sequencing (scWGS) derived clonal structures with cfDNA whole-genome sequencing (cfDNA-WGS) data to enable high-resolution tissue-informed clonal tracking. By jointly modeling local copy-number alterations and haplotype-specific signals via Bayesian model selection and Markov chain Monte Carlo (MCMC) sampling, the algorithm yields uncertainty-aware estimates of clonal prevalence and tumour fraction (TF). Applied to longitudinal clinical cohorts, cfClone can be used to reconstruct evolutionary trajectories and uncovers clonal selection driving therapeutic resistance, including the de novo detection of emergent clonal populations. We demonstrate that cfClone achieves accurate TF estimates and circulating tumor DNA (ctDNA) detection in malignancies with varying degrees of copy-number variant (CNV) burden using semi-synthetic data. We then compare to the state of the art scWGS informed panel based approach, and demonstrate cfClone provides comparable accuracy while allowing for the tracking of more clones and detection of novel clones. Finally, we show how cfClone can be used to quantitatively track clonal dynamics in response to treatment in high grade serous ovarian cancer. Github link: https://github.com/Roth-Lab/cfclone

cancer biology↗

bioRxiv2026

Utanos: A general-purpose shallow whole-genome sequencing analysis workflow identifies interpretable copy number signatures

SummaryA modular FASTQ-to-figures solution for analyzing low-depth or shallow whole-genome sequencing (sWGS) data. Shallow WGS can be used to detect copy number (CN) aberrations, Homologous Recombination Deficiency (HRD), and to detect and create CN signatures. Growing in popularity, this sequencing type is used for neonatal diagnostics and studying cancer. One of the major benefits is the reduced cost compared with deeper sequencing modalities such as Whole Genome Sequencing (WGS). With just 15 million reads often targeted, and sample substrate options like Formalin-Fixed, Paraffin-Embedded (FFPE) blocks widely available, this approach enables an affordable study to be performed at scale. Our pipeline and R package are an end-to-end solution implemented with reusability and modularity in mind. It makes entry and exit from the ecosystem easy, providing regular standardized output formats throughout execution. The pipeline is written in the well-supported and cross-platform Nextflow framework and has been submitted for inclusion in nf-core. Additionally, a Docker image for the utanos R package has been created to improve modularity. Availability and ImplementationThe latest version of all software is freely available on GitHub. For the full processing pipeline, visit: https://github.com/Huntsmanlab/swgs-processing-pipeline. For just the utanos R package, visit: https://github.com/Huntsmanlab/utanos.

bioinformatics↗

bioRxiv2026

ProteinSketch translates spatial intuition into protein design with bimanual interaction in VR

Generative AI-based protein design can create diverse structures for desired functions but offers human designers limited control over three-dimensional architectures. We developed ProteinSketch, a bimanual virtual reality platform in which immersive backbone sketches and volumetric envelopes are directly created and translated into constraints for diffusion-based protein generation. RFdiffusion-based real-time refinement enabled interactive exploration and construction of user-specified protein topologies. Volumetric conditioning of sketched envelopes enabled high-fidelity control of anisometric geometries, confirmed by cryo-electron microscopy. These user-defined volumetric constraints enabled functional-binder design and extension of pre-existing minibinders to surfaces otherwise difficult to access within complex molecular environments using conventional design approaches. This collaborative human-AI framework integrates human spatial reasoning with generative AI for spatially directed, shape-controlled design of protein structure and function. One-sentence summaryImmersive ProteinSketch embeds human spatial reasoning in AI-guided design of protein topology, shape, and function.

bioengineering↗

bioRxiv2026

A Moonlighting Function of Kinetochore Complex Proteins in Golgi Assembly of Neural Stem Cells

Kinetochores play an essential role in mitosis, and human kinetochore variants are associated with microcephaly. However, their functions in quiescent/interphase cells are unknown. Here, we demonstrate that Drosophila kinetochore proteins promote the reactivation of quiescent NSCs and their regeneration upon injury by organizing Golgi-dependent acentrosomal microtubules. Drosophila kinetochore proteins localize to the Golgi vicinity in quiescent NSCs and are required for proper localization of Golgi proteins, including the Golgi-resident small GTPase Arf1 known to regulate quiescent NSC reactivation and regeneration. Moreover, Drosophila kinetochore proteins physically associate with Arf1 and function upstream of it during reactivation. Remarkably, human kinetochore protein SPC25 localizes to Golgi in interphase NSCs and HEK293T cells. Furthermore, human kinetochores have a conserved function in promoting Golgi organization and, in turn, microtubule dynamics, in interphase cells. Together, our findings reveal a conserved moonlighting role for kinetochores in Golgi assembly in quiescent Drosophila NSCs and human interphase cells.

neuroscience↗

bioRxiv2026

ProteinFlux: accurate, rapid and scalable generative prediction of protein dynamics driven by post-translational modifications

The function of proteins, the building blocks of life, in health and disease depends not only on their 3D-conformational states but most importantly on the dynamic transition between states controlled by a wide array of post-translational modifications (PTMs). Recent major advances have been made in our ability to predict static 3D structures; however, understanding and predicting the impact of PTMs on protein conformational dynamics remains a major question and challenge in the field. Molecular dynamics (MD) simulation remains the major computational approach for studying protein dynamics. However, the high computational cost, lack of integration of PTMs as conditioning inputs and inefficient generation of continuous protein dynamics largely precludes PTM-regulated conformational dynamics and the study of slow conformational processes. To address this critical bottleneck, we developed ProteinFlux, a flow-matching generative framework that links PTM-conditioned conformational dynamics to evolutionary constraints encoded by PTM sites. Evolutionary information plays a critical role in capturing conformational dynamics beyond sequence identity, and PTM sites inherently encode evolutionary constraints critical to protein functional regulation. We therefore built FluxSite, a dual-modal PTM site predictor that integrates sequence evolutionary information and 3D structural features to generate a continuous conditional signal encoding conservation and functional importance for each predicted site. FluxSite achieves robust generalization across 18 PTM types and 30 disease-associated proteomes. ProteinFlux generates phosphorylation-conditioned, all-atom conformational trajectories across diverse protein fold classes, faithfully reproducing both thermodynamic properties such as free energy landscapes and kinetic features such as conformational transition pathways. It outperforms state-of-the-art predictors while achieving inference speeds several orders of magnitude faster than traditional MD. In addition, we introduce DynaMo-phos, a benchmark dataset of phosphorylated protein MD simulations. Together, ProteinFlux, FluxSite and DynaMo-phos provide a scalable, high-throughput platform for elucidating PTM-driven conformational mechanisms, with potential applications across allosteric drug design, functional annotation of disease-associated modifications and mechanism-guided therapeutic development.

bioinformatics↗

bioRxiv2026

Structure-based design of soluble prefusion-stabilized herpes simplex virus type 2 glycoprotein B antigens

Herpes simplex virus type 2 (HSV-2) causes genital herpes through latent infection and periodic reactivation. Although antivirals alleviate symptoms, no prophylactic or therapeutic vaccines have been licensed. Glycoprotein B (gB) is a class III fusion protein that mediates entry by irreversibly transitioning from a metastable prefusion conformation to a stable postfusion conformation. Leveraging prior structure-based designs for human cytomegalovirus (HCMV) gB, we engineered amino acid substitutions in HSV-2 gB to stabilize its prefusion conformation. Cryo-EM of the engineered construct revealed a prefusion conformation and non-native dimers of gB trimers. Introduction of N-linked glycosylation sites resulted in the gB-G3 variant, which exhibited improved expression and reduced dimerization. Cryo-EM of gB-G3 bound to neutralizing antibodies yielded a 2.8 [A] resolution structure of the stabilized prefusion conformation in a closed state, which differs from the open states observed in recently published HSV gB structures. Both prefusion and postfusion gB variants were evaluated for immunogenicity in mice, delivered either as a protein subunit or mRNA vaccine. Each gB conformation elicited robust humoral and cellular responses. However, prefusion stabilization of gB did not improve neutralizing antibody titers relative to the postfusion construct, consistent with prior observations for HCMV gB. Collectively, these findings reveal insights into prefusion gB conformational dynamics, provide stabilized reagents for studying gB-directed immune responses and inform HSV-2 vaccine design.

microbiology↗

bioRxiv2026

Synchrony is a robust iEEG biomarker for antiseizure medication load in epileptic patients

With new, minimally invasive continuous EEG and wearable monitoring systems for epilepsy nearing regulatory approval, there is a rush to determine how to make these devices most useful to patients. One application is to track biomarkers of antiseizure medication (ASM) levels to help manage seizure risk and side effects. In this paper, we validate one such biomarker, phase synchronization, during medication taper and presurgical evaluation in a cohort of 80 consecutive patients recorded with intracranial EEG (iEEG) at the University of Pennsylvania. While previous investigators have demonstrated that synchrony is negatively correlated with ASM load at the resolution of 1 day, we hypothesize that synchrony continuously tracks and can predict ASM load on a clinically useful time scale. We test this hypothesis using a pharmacokinetic model generating continuous ASM load values previously published by our group and correlate it with continuous synchrony values derived from the iEEG. We use a linear mixed effect model to examine the relationship between ASM load, synchrony, vigilance, and other time dependent factors. We use dominance analysis to rank the relative importance of predictors based on their influence on ASM load. We find that synchrony not only can predict ASM load but is also the most significant predictor. Our study highlights the potential of synchrony as a biomarker for ASM load, and its utility in an ambulatory implantable device that can alert patients to conditions lowering their medications (e.g., adherence, drug interactions, generic change, pregnancy, etc.) or potential medication toxicity. We propose that measures like synchrony, packaged in an appropriate interface, could bring substantial value to ambulatory epilepsy management devices.

bioengineering↗

bioRxiv2026

Therapeutic interleukin-2 rewires skeletal-immune circuits to reverse postmenopausal bone loss

Postmenopausal osteoporosis results from excessive osteoclast activity, but the immune circuits that limit osteoclastogenesis in the bone marrow remain poorly understood. Here, we tested a clinically accessible immunotherapy low-dose interleukin-2 (IL-2) as a therapeutic intervention in mice with established ovariectomy-induced bone loss, integrating microcomputed tomography imaging, single-cell transcriptomics, genetic perturbation, and human monocyte-osteoclast assays. Therapeutic administration of IL-2 reversed trabecular bone loss, expanded CXCR3 regulatory T cells in bone marrow, and promoted IL-10- and CGRP-producing ILC2s that were required for protection. IL-2 also acted directly on the osteoclast lineage, suppressing mouse and human osteoclastogenesis through activation of a STAT1-IRF1-dependent IFN program in RANKL-stimulated monocytes. Together, these data define an IL-2-responsive skeletal-immune network that can be therapeutically engaged to suppress osteoclastogenesis, which opens new avenues for cytokine-based immunotherapies in postmenopausal osteoporosis and related bone disorders.

immunology↗

bioRxiv2025

Organization of mouse prefrontal cortex subnetwork revealed by spatial single-cell multi-omic analysis of SPIDER-Seq

Deciphering the connectome, anatomy, transcriptome and spatial-omics integrated multi-modal brain atlas and the underlying organization principles remains a great challenge. We developed a Single-cell Projectome-transcriptome In situ Deciphering Sequencing (SPIDER-Seq) technique by combining viral barcoding tracing with single-cell sequencing and spatial-omics. This empowers us to delineate a integrated single-cell spatial molecular, cellular, anatomic and projectomic atlas of mouse prefrontal cortex (PFC). The projectomic and transcriptomic cell clusters display distinct modular organization principles, but are coordinately configured in the PFC. The projection neurons gradiently occupied different territories in the PFC aligning with their wiring patterns. Importantly, they show higher co-projection probability to the downstream nuclei with reciprocal circuit connections. Moreover, we integrated projectomic atlas with their distinct spectrum of neurotransmitter/neuropeptide and the receptors-related gene profiles and depicted PFC neural signal transmission network. By which, we uncovered potential mechanisms underlying the complexity and specificity of neural transmission. Finally, leveraging machine learning, we predicted neuron projections with high accuracy by combining gene profiles and spatial information. As a proof of concept, we used this model to predict projections of fear recall engram neurons. This study facilitates our understanding of brain multi-modal network and neural computation.

neuroscience↗

bioRxiv2025

Transcriptomic and functional characterization indicate sexual dimorphism of discrete circadian neuron subtypes

While many sexually dimorphic behaviors exhibit distinct time-of-day preferences, our understanding of how sex shapes the molecular and circuit properties of central brain neurons remain limited. Here, we uncover the transcriptomic and circuit basis of sexual dimorphism within the Drosophila circadian network. By leveraging single-cell RNA sequencing of male and female clock neurons, we identify specific subsets of dorsal lateral neurons (LNds), dorsal neurons 1p (DN1ps), and dorsal neurons 3 (DN3s) with dramatic dimorphic gene expression profiles. These sex differences are primarily characterized by cell-type-specific expression of genes involved in neural connectivity, particularly cell adhesion molecules (CAMs). Focusing on the dimorphic Cry-negative E3 LNds, we show that they form functionally active, synaptic connections with downstream doublesex-expressing pC1 and pCd-1 neurons, which serve as central regulators of dimorphic behaviors. Moreover, we demonstrate that formation and maintenance of these connections are mediated at least in part by sex-enriched CAMs, dpr9 in males and dpr3 in females. Thus, our work reveals sexual differentiation mechanisms at both the molecular and circuit levels, identifying specific molecules that sculpt sex-specific pathways to link the circadian clock to dimorphic outputs.

molecular biology↗