Biology subjects

An, L.

Publications and source records attributed to An, L..

At least 19 recordsLinked to original sources

bioRxiv2026

A coordinated and reproducible multicellular response to AD pathology

While single-cell measurements of the Alzheimer's disease (AD) brain allow investigation of vulnerable cells in unprecedented depth, reported findings are heterogeneous, mostly descriptive and often ignore interdependence of cellular responses. Operationalization of these findings requires a multi-cellular model of AD that is robust and reproducible. Here, we utilize a coordinated multicellular community approach across 2.3 million nuclei from 427 ROSMAP donors to identify robust multicellular axes associated with AD pathology and sex. The AD signature comprised profound alteration to RORB-GABRG excitatory neurons and disrupted oligodendrocyte precursor cell signaling. A separate set of AD-related cell-type specific molecular processes with strong sexual dimorphism also emerged. Importantly, these signatures developed and ROSMAP predicted neuropathology and sex, respectively, in a completely independent dataset (SEA-AD). These findings altogether summarize a highly consistent multi-cellular response to AD pathology in the human brain, creating a baseline cellular model to which perturbation and treatment experiments can be compared.

neuroscience↗

bioRxiv2026

SEMFA: A General Framework for Inferring Statistical Significance of Mahalanobis Similarity between Multi-Omics Profiled Samples Built on Multiple Factor Analysis

MotivationWith rapid advances in sequencing technologies, many heterogeneous omics datasets have been generated, as seen in the Encyclopedia of DNA Elements (ENCODE) and many single-cell multi-omics sequencing projects, bringing substantial challenges to existing integrative methods. In this article, we report a novel multi-omics fusion and analysis software SEMFA which performs general parametric tests for the Mahalanobis Similarity of samples based on the factor scores generated by an Extended version of conventional Multiple Factor Analysis. ResultsOur developed method is effective and robust under both Gaussian and non-Gaussian assumptions. The mean F1 scores are over 0.8 when the column similarity level is 0.9 and the noise level ranges between 0.1 and 0.2, using simulation studies based on ENCODE count data. It was also efficient and effective at handling large-scale single-cell multi-omics data, as demonstrated in colon cancer cases as it unveiled signature network organization patterns of cells for stages III and IV.

bioinformatics↗

bioRxiv2026

Widespread use of invalid statistical tests in biomedical machine learning

Cross-validation is routinely used to compare performance in biomedical artificial intelligence. Standard tests ignore correlation across cross-validation folds, inflating false-positive rates. In a PRISMA-guided meta-analysis of 184 studies (impact factor [≥] 15) across 30 biomedical fields, 97% use invalid tests. Among studies with abstract-level claims supported by invalid tests, 59% rely on a spurious comparison: one that loses significance after correcting for this correlation. On average, regaining significance requires a 43% larger effect. Extending these findings to the broader literature, we estimate that spurious comparisons occur in nearly two in three studies and support abstract-level claims in nearly one in three studies. Simulations confirm false-positive rates paradoxically approach 100% when cross-validation is repeated to improve stability. We introduce SHARP, a redesign of cross-validation, which best balances false-positive control and power among 13 benchmarked tests. These results reveal widespread fragility in biomedical artificial intelligence and offer a practical route to valid comparisons.

bioinformatics↗

bioRxiv2026

Generalized Normative Modeling: A One-Step Hierarchical Kernel Framework for Multi-Site Brain Charts with Self-Correcting Z-Scores

Normative modeling expresses individual brain phenotypes as z-scores relative to a population norm, but in multi-site studies batch effects contaminate these z-scores and undermine their biomarker value. Existing approaches either harmonize data before fitting a normative model (ComBat+Normative), letting residual site effects leak into z-scores, or use parametric one-step methods (GAMLSS, HBR) that cannot flexibly model multivariate covariate interactions. We propose Generalized Normative Modeling (GNM), a onestep hierarchical framework that jointly estimates the global trajectory and site-specific effects via NUFFT-accelerated kernel regression with GCV bandwidth selection. Because the z-score is the ratio of batch-corrected residual to batch-corrected scale, residual site variance cancels algebraically -- a property we term self-correction. On ABIDE I cortical thickness (387 HC, 11 sites, 68 ROIs) and HarMNqEEG log-power spectra (1,564 subjects, 14 sites, 18 channels x 235 frequency bins), GNM produced the most site-invariant z-scores and best age-signal preservation among four methods. This work provides an open-source MATLAB toolbox with a declarative formula interface (https://github.com/LMNonlinear/Generalized-Normative-Modeling), enabling reliable individual-level inference in pooled multi-site cohorts and advancing the use of normative deviations as clinical biomarkers in precision psychiatry and neurology.

bioengineering↗

bioRxiv2026

Contamination of Engram Coactivity Networks During Forgetting

Forgetting is a fundamental component of adaptive memory and essential for cognitive flexibility, yet its cellular basis remains unclear. Here we establish a mouse model of retroactive interference (RI) and show that post-learning novelty exploration induces active forgetting of hippocampus-dependent object location memory only within a discrete consolidation window defined by protein synthesis sensitivity. RI imposed within this window reduces engram reactivation and destabilizes a structured coactivity network formed during learning. Mice that forget retrieve reorganized engram with increased edge turnover and reduced training edge survival during recall. During this vulnerable period, RI infiltrates the engram core, whereas after consolidation it remains confined to the network periphery. Over the consolidation window, the engram network progressively matures, acquiring greater density, similarity, and k-core robustness, features that confer resistance to interference. Importantly, blocking RI infiltration rescues memory formation. Together, these findings show that forgetting arises from reorganization of engram topology during consolidation and identify engram core contamination as a network-level substrate for forgetting.

neuroscience↗

bioRxiv2026

Retinoic acid resolves the conflict between X-chromosome inactivation and pluripotency program in female cleavage-stage embryos

The tight coupling of X-chromosome inactivation (XCI) and pluripotency is a paradigm of holistic developmental regulation, and their inverse correlation enables XCI establishment during implantation. In contrast, the co-establishment of imprinted XCI (iXCI) and pluripotency program in female preimplantation embryos challenges the holistic pattern, but how embryos coordinate the two remains unknown. Here, we find that Nanog during the cleavage stage strongly represses the co-upregulated Rnf12-Xist axis, the triggering signaling of iXCI, creating a conflict that threatens iXCI. We identify retinoic acid (RA) as the coordinator that resolves the conflict and safeguards iXCI. RA activates its receptor RARG to evict NANOG from Rnf12 5region, avoiding NANOGs threat. In vivo, either maternal vitamin A deficiency or embryonic RA synthesis defects results in impaired iXCI and female-biased embryonic lethality. Thus, we highlight RA as a master regulator to holistically balance iXCI and pluripotency during cleavage stages, thereby ensuring proper female embryogenesis.

developmental biology↗

bioRxiv2026

MiCBuS: Marker Gene Mining for Unknown Cell Types Using Bulk and Single Cell RNA-Seq Data

Identifying cell type-specific expressed genes (marker genes) is essential for understanding the roles and interactions of cell populations within tissues. To achieve this, the traditional differential analysis approaches are often applied to individual cell-type bulk RNA-seq and single-cell RNA-seq data. However, real-world datasets often pose challenges, such as heterogeneous bulk RNA-seq and incomplete scRNA-seq. Heterogeneous bulk RNA-seq amalgamates gene expression profiles from multiple cell types and results in low resolution, while incomplete scRNA-seq does not capture some cell types from the tissue, leading to unknown cell types. Traditional methods fail to identify marker genes for such unknown cell types. MiCBuS addresses this limitation by generating Dirichlet-pseudo-bulk RNA-seq based on bulk and incomplete single-cell RNA-seq data. By performing differential analysis of gene expressions on bulk and Dirichlet-pseudo-bulk RNA-seq samples, MiCBuS can identify the marker genes of unknown cell types, enabling the identification and characterization of these elusive cellular components. Simulation studies and real data analyses demonstrate that MiCBuS reliably and robustly identifies marker genes specific to unknown cell types, a capability that traditional differential analysis methods cannot achieve. Availability and implementationMiCBuS is implemented in the R language and freely available at https://github.com/Shanshan-Zhang/MiCBuS.

bioinformatics↗

bioRxiv2026

AAV-Mediated Dual-Gene Therapy Restores Metabolic Function in Mice with Propionic Acidemi

Background and AimsPropionic acidemia (PA) is a rare autosomal recessive disorder caused by mutations in PCCA or PCCB, which encode the two subunits of propionyl-CoA carboxylase (PCC). PCC deficiency causes toxic metabolite accumulation and multi-organ damage. Current management, including dietary restriction, pharmacological support, and liver transplantation, does not restore enzymatic activity. We developed a dual-gene adeno-associated virus (AAV) therapy that delivers both PCC subunits to treat both PA subtypes. MethodsWe generated a clinically relevant PCCA-R73W knock-in mouse model and administered AAV8 vectors encoding native human PCCA and PCCB under the control of a liver-specific thyroxine-binding globulin promoter (AAV8-TBG-hPCCA-P2A-hPCCB). Metabolite levels and organ safety were longitudinally assessed. ResultsDual-gene therapy produced dose-dependent reductions in plasma C3/C2 ratio, 3-hydroxypropionic acid, 2-methylcitric acid, and propionylglycine, and significantly outperformed single-gene (PCCA-only) therapy. Neonatal facial-vein injection achieved metabolic correction comparable to or better than adult treatment. The longitudinal follow-up revealed sustained efficacy over a 16-week period, with no signs of hepatotoxicity or adverse effects. ConclusionsSingle-dose, dual-gene AAV therapy achieves sustained metabolic correction and demonstrates long-term safety in a clinically relevant PA model, supporting its translational potential for both type I and type II propionic acidemia.

genetics↗

bioRxiv2025

Mapping the circulating proteome across neurodegeneration: A harmonized, consortium-scale framework for uncovering molecular pathophysiology

Large-scale plasma proteomics offers unprecedented opportunities to investigate the systemic biology of neurodegeneration, yet technical heterogeneity, site-specific artifacts, and clinical confounding remain major barriers to reproducible discovery. Leveraging data from 13,733 individuals with Alzheimers disease (AD), Parkinsons disease (PD), frontotemporal dementia (FTD), Parkinsons disease dementia (PDD), amyotrophic lateral sclerosis (ALS), and non-impaired controls in the Global Neurodegeneration Proteomics Consortium (GNPC), we present a scalable and generalizable analytical framework for harmonizing and interpreting consortium-scale proteomic datasets. Using a high-dimensional perturbation framework, we systematically benchmark five commonly used batch correction methods across a range of realistic confounding structures, including site-disease imbalance, nonlinear effects, and heteroskedasticity. Empirical Bayes modelling via limma consistently emerged as the most robust method, optimally balancing removal of site-related technical variance with retention of disease-relevant biological signal. On this harmonized foundation, we resolve neurodegenerative disease plasma signatures, including a shared immune-metabolic axis in AD and PD, neuromuscular disruption in ALS, and proteostatic imbalance in PD. Tissue and cell-type enrichment highlight widespread immune-endocrine involvement in AD and hematopoietic activation in PD. Demographically matched analyses nominate distinct, candidate biomarkers across diseases, including lipid, redox, and complement factors in AD, lysosomal and cytoskeletal proteins in PD, and muscle-derived markers in ALS. This study establishes a scalable analytical framework for integrating real-world proteomic data and provides a disease-resolved catalogue of circulating signatures to inform biomarker development and targeted intervention across neurodegenerative diseases.

neuroscience↗

bioRxiv2025

Longitudinal analysis of bacterial community dynamics in normal hospital ward following patient occupancy

The hospital microbiome significantly influences patient recovery and clinical outcomes. However, the dynamics of microbial colonization and transmission following initial patient occupancy remain poorly understood. Here, we employed 16S rRNA gene amplicon sequencing to investigate bacterial community dynamics on surfaces within neurosurgery ward and patients as a new hospital became operational. Our results showed that bacterial colonization in hospital wards follows distinct site-specific patterns, after hospital opening, alpha diversity was significantly increased on floors and drawer handles but decreased on bedrails and faucet handles compared to preopening. Beta diversity analysis showed that surfaces frequently contacted by patients exhibited the greatest compositional turnover, such as bedrails, drawer handles, and faucet handles, bacterial communities in after-opening were more homogeneous across sites than preopening, indicating potential bacterial transmission. Moreover, we found following patient admission, patient hand-derived microbiomes exert a significant influence on the bacterial communities in hospital wards, with a particularly pronounced impact on bedrails. Additionally, the potential disease risk of bedrails in post-opening was significantly higher than preopening. Taken together, these findings underscore the critical role of human contact in shaping hospital microbiomes and highlight the importance of targeted infection control strategies to mitigate pathogen transmission.

bioinformatics↗

bioRxiv2025

Advancing Snow Leopard Density Estimates to Assess Population Dynamics Over Time in Afghanistan

Effective wildlife monitoring requires innovative methodologies to ensure accurate population assessments for conservation planning. This study focuses on snow leopards (Panthera uncia), a species classified as Vulnerable by the IUCN due to habitat loss, climate change, and over-exploitation. Employing spatial capture-recapture (SCR) models and AI-assisted individual identification, we analyzed camera trapping data from 2012-2013 and 2017-2019 to assess changes in snow leopard density and abundance in Wakhan National Park, Afghanistan. Our analysis used single-session and multi-session models to provide a comprehensive view of population dynamics. Single-session models revealed a substantial increase in density, with the full model estimate rising from 1.38 {+/-} 0.39 SE to 3.57 {+/-} 0.88 SE, while right-only and left-only models showed increases from 1.43 {+/-} 0.53 SE to 3.38 {+/-} 1.01 SE and from 1.04 {+/-} 0.36 SE to 2.21 {+/-} 0.72 SE, respectively. Our findings also highlight the importance of incorporating bilateral asymmetry into population estimates to avoid overestimation. For single-session models, the full model density estimate was 11.7% higher in 2012-2013 and 27.8% higher in 2017-2019 compared to the average of the left-only and right-only estimates. For multi-session models, the full model density estimate was 13.0% higher in 2012-2013 and 46.9% higher in 2017-2019. This emphasizes the importance of addressing asymmetry to avoid potential overestimation. This study demonstrates the potential of combining advanced analytical frameworks with AI to improve wildlife population assessments. By refining SCR methodologies and addressing key biases, these methods provide critical insights for snow leopard conservation and broader applications to wildlife monitoring. While the results indicate a significant increase in snow leopard populations, continued monitoring and long-term studies are essential to account for changes due to environmental and anthropogenic factors.

ecology↗

bioRxiv2025

Design of Orthogonal Far-Red, Orange and Green Fluorophore-binding Proteins for Multiplex Imaging

Fluorescent proteins and small molecule dyes have complementary strengths for biological imaging: the former are genetically manipulatable enabling tagging of specific proteins and detection of protein interactions, while the latter have greater photostability and brightness but are difficult to target. To combine these strengths, we used de novo protein design to generate binders to three bright, stable, cell-permeable dyes spanning the visible spectrum: JF657 (far red), JF596 (orange-red) and JF494 (green). For each dye, we obtain nanomolar binders with weak or no binding to the other two dyes; the accuracy of the design approach is confirmed by a crystal structure of one binder which is very close to the design model. Fusion of the JF567, JF596 and JF494 binders to three different targets followed by staining with the three dyes simultaneously enables multiplex imaging. We further expand functionality by incorporating an active site carrying out nucleophilic aromatic substitution to form a covalent linkage with the dye, and developing split versions which reconstitute fluorescence at subcellular locations where both halves are present, enabling both protein-protein interaction detection and chemically induced dimerization with fluorescence reporting. Our designs combine the advantages of fluorescent proteins and small molecule dyes and should be broadly useful for cellular imaging.

biochemistry↗

bioRxiv2025

Structural insights into type I and type II Lamassu anti-phage systems

Bacteria have developed a variety of immune systems to combat phage infections. The Lamassu system is a prokaryotic immune system with a core conserved Structural Maintenance of Chromosomes (SMC) superfamily protein LmuB and diverse effectors named LmuA, whose mechanism remains unclear. Here, we present a series of cryo-electron microscopy structures of type I Lamassu complex from Bacillus cellulasensis and type II Lamassu complex from Vibrio cholerae, both in apo- and dsDNA-bound states, which reveal an unexpected stoichiometry and topological architecture, distinct from canonical SMC complexes. Combined structural and biochemical analyses show how the nuclease effector LmuA is sequestered in an inactive monomeric form within the Lamassu complex, and upon sensing foreign DNA ends, dissociates and assembles into an active tetramer capable of DNA cleavage. Our findings elucidate the mechanism by which Lamassu systems detect viral replication and implement anti-phage defense, highlighting the unprecedented roles of SMC proteins in prokaryotic immunity.

microbiology↗

bioRxiv2025

Harmonizing single cell 3D genome data with STARK and scNucleome

Single-cell three-dimensional genome sequencing (sc3DG-seq) is advancing our understanding of genome regulation and cellular heterogeneity in diverse biological processes. Despite significant technological advancements, a universal tool capable of processing sc3DG-seq data and benchmarking the performance of various techniques in resolving 3D chromatin structures is absent. To fill this gap, we present STARK, a versatile toolkit designed for the preprocessing, quality control and analysis of all spectrum of sc3DG-seq data. Utilizing STARK, we systematically processed 11 sc3DG-seq technologies data, enabling a quantitative benchmarking of each technologys strengths and limitations. Additionally, we developed the EmptyCells algorithm to distinguish high quality from empty barcodes, and introduced the Spatial Structure Capture Efficiency (SSCE) metric to assess the ability of single cells to capture chromatin structures. Furthermore, we established scNucleome, an extensive repository of uniformly processed sc3DG-seq datasets, offering a foundational resource to catalyze further exploration and discovery in the 3D genome research.

bioinformatics↗

bioRxiv2025

Brain network dynamics determine tau presence while regional vulnerability governs tau load in Alzheimer's disease

In Alzheimers disease (AD), tau pathology accumulates gradually throughout the brain, with clinical decline reflecting tau progression. A comprehensive understanding of, first, whether tau propagation is predominantly governed by connectome-based diffusion, regional vulnerability, or an interplay of both, and second, which types of brain connectivity or regional factors best explain tau propagation, remains crucial for advancing our understanding of AD progression. Here, we apply multi-scale, biologically informed disease progression simulations to human data, to disentangle the influence of local mechanisms on global tau progression patterns in AD. We find that whether tau reaches a brain region (presence) and how much tau accumulates there (load) are governed by different mechanisms. Tau presence patterns are highly consistent across the population, and can be largely explained through synaptic spread through white-matter networks and excitatory-inhibitory dynamics. Meanwhile tau load differs across people, and is driven by a combination of synaptic spread and intrinsic or extrinsic regional properties, including regional {beta}-amyloid load, MAPT gene expression and regional blood flow. Finally, while distinct tau patterns in the population could each be explained by established AD mechanisms, our models highlight a role of distinct brain networks (parietal networks in MTL-sparing AD tau subtype) and neurotransmitter systems (cholinergic system in posterior subtype). Together, this work suggests that network dynamics likely determine the sequence of regional tau progression, while individual-specific tissue-vulnerability factors influence regional tau load.

neuroscience↗

bioRxiv2025

Metagenomics reveals potential interactions between CPR bacteria and their phages in groundwater ecosystems

Candidate phyla radiation (CPR) is a vast lineage composed of bacteria with ultra-small size, streamlined genomes, notable defects in core metabolic potential and symbiotic lifestyle, which are widely detected in groundwater ecosystems. Increasing attention has focused on the physiological and ecological significance of CPR bacteria, while the potential interactions between CPR bacteria and their phages still need more exploration. Here, we collected 82 groundwater metagenomic datasets and further derived 1,162 phages with the potential to infect 2,439 groundwater CPR metagenome-assembled genomes (MAGs). Notably, the groundwater CPR MAGs were predominantly infected by temperate phages, and the abundance profiles of phage-CPR interactions in groundwater ecosystems supported the Piggybacking the Winner (PtW) hypothesis, suggesting that lysogenic infection was a strategy co-evolved by CPR bacteria and their phages in groundwater ecosystems. Intriguingly, the groundwater CPR phages encoded various auxiliary metabolic genes (AMGs) that might promote symbiotic lifestyle and metabolic potential of host CPR MAGs. These included AMGs associated with concanavalin A-like lectin/glucanases superfamily and O-Antigen nucleotide sugar biosynthesis, which could enhance surface adhesion of host CPR MAGs. Moreover, AMGs related to ABC transport system and P-type transporter could strengthen metabolic exchange and uptake of essential nutrients from surroundings. Additionally, AMGs involved in various metabolic pathways might alleviate metabolic deficiencies in host CPR MAGs. This study elucidated the mechanisms of phage-CPR interactions and the potential roles of phages in modulating the physiology and ecology of CPR bacteria within groundwater ecosystems.

microbiology↗

bioRxiv2025

Chronic degenerative failure of salivary glands can be reversed through restoring mitochondrial function

Chronic degenerative wounds are often deemed irreparable, directing research efforts to focus predominantly on acute tissue injury regeneration while leaving endogenous repair mechanisms for chronically damaged tissues largely unexplored. In this study, we demonstrate that non-healing, severely degenerated salivary gland tissues can be fundamentally restored through first-line treatment with muscarinic agonists. This approach rescues tissue structure and function, returning it to a homeostatic-like state, and reactivates endogenous regeneration processes to drive new cell expansion that persists for months post-treatment. Furthermore, neuromimetic activation profoundly depletes radiation-induced DNA damage and re-establishes the nerve-acinar relationship, ultimately restoring the tissues physiological capacity to maintain homeostasis, even in the absence of treatment. We show that full recovery of organ function, comparable to uninjured controls, is primarily mediated by the re-differentiation of aberrantly de-differentiated epithelial acinar cells and the restoration of mitochondrial function via a muscarinic-calcium signaling pathway. These findings challenge the prevailing notion that chronic organ degeneration is irreversible and propose a readily testable therapeutic strategy for epithelial restoration with potential applications across a spectrum of chronic injuries.

cell biology↗

bioRxiv2024

Rebuilding the autoimmune-damaged corneal stroma through topical lubrication

Corneal lubrication is the most common treatment for relieving the signs and symptoms of dry eye and is considered to be largely palliative with no regenerative functions. Here we challenge this notion by demonstrating that wetting the desiccated cornea of an aqueous-deficient mouse model with the simplest form of lubrication, a saline-based solution, is sufficient to rescue the severely disrupted collagen-rich architecture of the stroma, the largest corneal compartment that is essential to transparency and vision. At the single cell level we show that stromal keratocytes responsible for maintaining stromal integrity are converted from an inflammatory state into unique reparative cell states by lubrication alone, thus revealing the extensive plasticity of these cells and the regenerative function of lubricating the surface. We further show that the generation of a reparative phenotype is due, in part, to disruption of an IL1{beta} autocrine amplification loop promoting chronic inflammation. Thus, our study uncovers the regenerative potential of topical lubrication in dry eye and represents a paradigm shift in our understanding of its therapeutic impact.

immunology↗