Biology subjects

Cheng, Y.

Publications and source records attributed to Cheng, Y..

At least 73 records · Page 4Linked to original sources

bioRxiv2025

Longitudinal Identification of Zebrafish Individuals by Deep Learning

The zebrafish (Danio rerio) is a critical vertebrate model organism in biomedical research. Accurate identification and longitudinal tracking of individual fish within cohorts enable linking genotype to complex phenotypes, essential for elucidating the molecular mechanisms underlying disease pathogenesis and trait formation. Nevertheless, the establishment of reliable long-term individual identification remains a significant challenge, primarily due to their diminutive size and minimal interindividual morphological variations. We developed ESC-IDNet, a dual-stage deep learning cascade architecture deployed on the FishIndivID platform (http://bioinfo.ihb.ac.cn/fishindivid), enabling high-precision identification. Trained and tested on [~]300,000 images from 450 zebrafish (31-122 dpf), our lateral body-based identification maintained >95% accuracy with updates only every 20 days, significantly outperforming dorsal head identification (requiring [~]13-day updates). Both views achieved 100% accuracy in 1-2 day tasks. ESC-IDNet surpassed alternatives in segmentation, alignment, feature extraction, and feature matching. This framework provides a robust, transferable paradigm for individual identification in fish species.

bioinformatics↗

bioRxiv2025

B-cell follicles of lymphatic tissues act as a critical microanatomical niche for sustained viral replication, virus-host interaction and damage during chronic SIV infection

Most people living with HIV-1 (HIV) are diagnosed during the chronic stage of infection, at which point viral setpoint has been established and a substantial immunopathologic damage in the secondary lymphatic tissues (LTs) has been induced. To better characterize virus-host interaction and immunopathologic damage in LTs, we investigated viral spatial distribution patterns and the corresponding LT structural alterations in SIV chronically infected rhesus macaques. Using RNAscope in-situ hybridization (RNAscope) and a combination of CODEX with RNAscope (Comb-CODEX-RNAscope), we demonstrated that in chronic infection, SIV viral RNA (vRNA) is predominantly resides within B-cell follicles with minimal presence in T-cell zones, and there is significant B-cell follicular damage, encompassing follicular hyperplasia, fibrosis, and disintegration of the germinal center. Our results reveal that the B-cell follicles act as a critical microanatomical niche for sustained viral replication, virus-host interaction and tissue damage during SIV chronic infection.

immunology↗

bioRxiv2025

Analysis of SIV Spatiotemporal Dissemination Patterns in Rhesus Macaques During Early Rectal Transmission Demonstrates Systemic Infection Does Not Require Viral Local Amplification at the Entry Portal

Receptive anal sex is a dominant mode of HIV-1 (HIV) transmission, especially among men who have sex with men (MSM). However, the early events during HIV rectal transmission are not well understood and many questions remain, such as, does virus local amplification at the entry portal require for viral distal seeding? What is the spatiotemporal dissemination pattern across whole body? How do three viral forms, i.e., cell-free virus (VCF), cell-associated virus (VCA), and follicular dendritic cell-trapped virus (VFDC), evolve during early infections? To close this knowledge gap, we comprehensively examined rectum, draining lymph nodes (dLN) and distal lymph nodes (disLN), as well as non-lymphoid organs of brain, lungs, and liver of Indian rhesus macaques (RMs) at the early time points following intrarectal SIVmac251 inoculation (1, 2, 3, 4, 6, 10 14, 28 day post inoculation, dpi). Our findings demonstrated SIV rapidly disseminates to distant tissues and organs (<=1 dpi) and virus local amplification in rectum and dLN is not required for viral distal seeding for the establishment of systemic infection, viral forms shift from VCF and VCA to VFDC accompanying from T cell zones into B cell follicles. Collectively, these findings indicate that an effective HIV vaccine needs to induce immune protection both locally at sites of viral entry and systemically.

immunology↗

bioRxiv2025

A BCG toxic effector induces mitochondrial DNA compaction to refrain protective immunity

Innate immune memory typically emphasizes nuclear chromatin remodeling that determines transcriptional memory in monocytes and macrophages. Here, we show that compaction of mitochondrial DNA (mtDNA), governed by mitochondrial transcription factor A (TFAM) abundance and mtATP-dependent remodeling, defines the transcriptional and functional state of trained macrophages. While typical pathogen-associated molecular pattern (PAMPs) triggered mtDNA accessibility, Bacillus Calmette-Guerin (BCG) effector PE18 directly interacted with and activated SLC25A5 to reduce mtATP levels, thereby inhibiting TFAM degradation by AFG3L2. Accumulated TFAM restricts mtDNA accessibility, suppressing the transcription of the mtNd1 and thereby reducing mtNd1-mediated mtROS production, which diminishes the trained capacity of macrophages against secondary infections. Notably, BCG{Delta}pe18 maintains macrophages cytokine transcriptional capacity independent of classical nuclear histone modifications. Moreover, BCG{Delta}pe18 provides robust and lifelong protective immunity against Mycobacterium tuberculosis (Mtb) infection. These findings reveal mitochondrial genome as a regulatory entity in trained immunity, and suggest a potential strategy for improving vaccine performance.

immunology↗

bioRxiv2025

Antibody Reveals Conformational Latch Controlling Herpesvirus Proteases

Human herpesviruses (HHVs) are widespread pathogens that cause severe disease. Their replication depends on the HHV protease (HHV Pr), an enzyme essential for capsid maturation. Because HHV Pr must dimerize to become catalytically active, disrupting dimer formation is a promising strategy for antiviral therapeutic development. We isolated a conformationally selective antibody inhibitor, Fab5, from a fully human naive Fab-phage library that recognizes monomeric human cytomegalovirus protease (HCMV Pr). A 2.6 [A] cryoelectron microscopy (cryo-EM) structure of the Fab5-HCMV Pr complex revealed that Fab5 binds a flexible loop distal from the active site and dimer interface which we call the latch loop. In HCMV Pr dimers, this loop secures the C-terminal tail to the protein core. Structure-guided mutagenesis confirmed that the latch loop is essential for HCMV Pr dimerization and activity. This loop is structurally conserved across all HHV Prs, and we show its functional role in Kaposis Sarcoma-associated herpesvirus (KSHV) Pr as well. The latch loop plays a mechanistic role in the conformational transition required for HHV Pr activity, and it forms a cryptic site that presents a new avenue for future allosteric inhibitor development.

biochemistry↗

bioRxiv2025

MCUR1-CCDC90B complex is a conserved regulator of metabolic homeostasis

The mitochondrial calcium uniporter regulator 1 (MCUR1) is an evolutionarily conserved protein of the inner mitochondrial membrane1, yet its physiological role has remained elusive. Although initially proposed to function as a subunit of the mitochondrial calcium uniporter complex (MCUC)2-4, emerging evidence suggests that MCUR1 has a broader functional spectrum5-7. Here, we identify a biallelic loss-of-function MCUR1 variant (c.802C>T; p.R268X) in a patient with a progressive neurological phenotype. This mutation leads to loss of MCUR1 protein and exerts a dominant-negative effect on its paralog, CCDC90B. We show that MCUR1 and CCDC90B form a hetero-oligomeric complex whose stability depends on MCUR1. Deletion of MCUR1 and CCDC90B in the fission yeast Schizosaccharomyces pombe, which lacks the MCUC, impairs lipid and amino acid metabolism and causes nitrogen source-dependent growth defects that are rescued by expression of human MCUR1. Patient serum metabolomics confirms an imbalance in the amino acid pool, while MCUR1 deficiency in patient-derived skin fibroblasts upregulates autophagy, perturbs non-essential amino acid metabolism, and limits biosynthetic capacity, resulting in delayed proliferation and migration. These findings redefine the MCUR1-CCDC90B coiled-coil complex as a transmembrane scaffold critical for the integrity of mitochondrial protein complexes and the maintenance of metabolic homeostasis, suggesting a potential link between MCUR1 deficiency and human neurometabolic disease.

cell biology↗

bioRxiv2025

A Pangenomic Method for Establishing a Somatic Variant Detection Resource in HapMap Mixtures

Somatic mosaicism is essential in human biology and disease, yet robust benchmarks are scarce. The SMaHT Consortium mixed six HapMap cell lines to create artificial somatic variants spanning 0.25% to 16.5% variant allele fractions. We developed a technology-agnostic method that builds pangenome graphs from individual assemblies to create unified benchmarking sets: > 6M single-nucleotide variants, 1.8M small insertions/deletions, 49K structural variations, and 10K mobile element insertions across autosomes, X, and mitochondrial chromosomes. We validated the variants using ultra-deep simulated reads and developed a binomial-based model to estimate coverage requirements for variant detection. Evaluating multiple callers showed CHM13 alignment improves structural variant detection and offers advantages in difficult-to-map regions compared to GRCh38. Systematic characterization showed regions with low detection rate are enriched in centromeres, satellite sequences, tandem repeats, and falsely duplicated genes. This accurate, versatile resource enables systematic evaluation of somatic variant detection technologies.

genomics↗

bioRxiv2025

NQO1 phase condensation promotes stress granule assembly to facilitate pancreatic carcinogenesis

G3BP1 promotes pancreatic ductal adenocarcinoma (PDAC) tumorigenesis driven by oncogenic KRAS mutations through liquid-liquid phase separation (LLPS)-mediated assembly of stress granules (SGs). However, the regulatory mechanisms remain elusive. We identify the antioxidant enzyme NAD(P)H quinone dehydrogenase 1 (NQO1) as a novel SG regulator that enhances SG assembly in pancreatic cancer cells independently of reactive oxygen species (ROS). Mechanistic studies reveal that NQO1 does not regulate the expression of G3BP1 or other SG-associated genes. Instead, NQO1 undergoes LLPS dependent on its RNA-binding K homology (KH) like domain. Further analysis demonstrates that residues 121-131 of NQO1 directly interact with G3BP1s RNA-binding domain (RBD), enhancing the multivalency of G3BP1 complexes to potentiate LLPS-driven SG assembly. This interaction accelerates cell proliferation, KRAS mutation-induced acinar-to-ductal metaplasia (ADM), and pancreatic carcinogenesis. Notably, the interaction between NQO1 residues 121-131 and G3BP1s RBD is essential for NQO1 phase condensation under stress condition. Integrative analysis of human PDAC transcriptomic datasets reveals a weak association between NQO1 and G3BP1 levels. Importantly, both NQO1 and G3BP1 formed biological condensates and co-localized in the lesions of human PDAC tissue sections. Our study uncovers a novel KRAS mutation-driven mechanism of pancreatic carcinogenesis through the lens of phase separation, transcending conventional gene expression regulation and offering new insights into non-canonical KRAS-NQO1-G3BP1-SG regulatory networks in PDAC initiation.

cancer biology↗

bioRxiv2025

Discovering cell types and states from reference atlases with heterogeneous single-cell ATAC-seq features

Despite substantial recent advances in query mapping and cell type or cell state discovery tools, their application to single-cell assay for transposase-accessible chromatin using sequencing (scATAC-seq) data remains challenging. The heterogeneous nature of peak feature spaces across samples hinders the effectiveness of existing methods, while the absence of dedicated tools for detecting perturbed cell types and states in scATAC-seq data further limits the depth of downstream analyses. To address these limitations, we present EpiPack, an integrative computational toolkit that leverages heterogeneous transfer learning and graph-based modeling strategies to advance scATAC-seq analysis. At its core, the Peak Embedding Informed Variational Inference (PEIVI) framework within EpiPack enhances mappable reference construction, query mapping, and label transfer, demonstrating that leveraging heterogeneous features in scATAC-seq data outperforms methods relying solely on conventional homogeneous features. In addition, EpiPacks global-local out-of-reference (OOR) detection framework achieves robust and efficient detection of perturbed cell types and states, extending the utility of scATAC-seq to disease and perturbation contexts. With its modular design and transferable pre-trained references, EpiPack can be readily applied to diverse analytical tasks and is available as a Python package at https://github.com/ZhangLabGT/EpiPack.

bioinformatics↗

bioRxiv2025

A Universal Duplex Sequencing Approach for Accurate Detection of Somatic Mutations

Ultra-accurate detection of rare somatic mutations is critical for understanding mutational processes in human disease, aging, and environmental exposures, yet current methods are limited by error rates, restricted genome coverage, and high DNA input. We present UDSeq, a duplex sequencing protocol combining random fragmentation, efficient UMI ligation, and quantitative input control to achieve near-complete genome/exome representation from as little as 100 pg DNA. Benchmarking in human sperm estimates a UDSeq error rate of [~]2.5x10-9 per base pair. UDSeq captures mutational signatures from heterogeneous populations without clonal expansion, reproduces exposure-specific patterns in cell lines and rodent models, and enables cross-species profiling. Compared with prior duplex methods, UDSeq yields up to fourfold more usable duplex molecules, improves library conversion, and remains cost-effective. We include a step-by-step protocol with quality-control checkpoints for fragment size, ligation yield, library conversion, and duplication rate. UDSeq provides a scalable, low-input platform for accurate profiling of somatic mutagenesis.

genomics↗

bioRxiv2025

Biodegradation of the endocrine-disrupting compound bisphenol F by Sphingobium yanoikuyae DN12

Bisphenol F (BPF) is an emerging environmental pollutant widely present in surface water and wastewater systems. Microbial activity is crucial in driving its degradation, offering a potential avenue for mitigating its environmental impact. Although the degradation pathway for BPF has been identified in various bacteria, the biodegradation mechanisms remain unclear. In this study, we isolated a highly efficient BPF-degrading strain of Sphingobium yanoikuyae DN12, which could utilize BPF as the sole carbon source and energy source for growth, from a river sediment in Anhui Province China. Through Ultra performance liquid chromatography high-resolution mass spectrometry (UPLC-HRMS) analysis, we found that oxidation and hydrolysis are key steps for BPF biodegradation. Utilizing whole-genome sequencing, comparative transcriptomics analysis and biochemical identification, a gene cluster bpf was identified to be involved in BPF degradation. BpfAB is a two-component oxidoreductase responsible for converting BPF to 4,4-dihydroxybenzophenone (DHBP). BpfC is a Baeyer-Villiger monooxygenase (BVMO) responsible for converting DHBP to 4-hydroxyphenyl-4-hydroxybenzoate (HPHB). Isotope tracing demonstrated that the oxygen atom incorporated by BpfAB originates from water, whereas that incorporated by BpfC derives from molecular oxygen (O2). BpfD is an /{beta} hydrolase responsible for converting HPHB to 4-hydroxybenzoate (4HB) and 1,4-hydroquinone (HQ). Analysis of the taxonomic and habitat of 325 prokaryotic genomes revealed that BpfA-like homologs are predominantly found in the phylum Pseudomonadota, primarily inhabiting soil and aquatic environments. This study enhances our understanding of the biodegradation mechanism of BPF, and provides guidance for the effective remediation of BPF-contaminated environments. IMPORTANCEBPF is a widely used alternative to bisphenol A and poses a growing threat to ecosystems and human health due to its environmental persistence and endocrine-disrupting effects. Although microbial degradation pathways for BPF have been reported, the key enzymes involved and their catalytic mechanisms remain unclear. This work reports the isolation of a Sphingobium strain capable of mineralizing BPF and the genetic basis for the catabolic pathway. Three enzymes--a two-component oxidoreductase, a Baeyer-Villiger monooxygenase, and an /{beta} hydrolase--were biochemically characterized and shown to catalyze the three critical steps in BPF degradation. These findings provide insights into the biochemical processes involved in the microbial degradation of BPF.

microbiology↗

bioRxiv2025

Hyperbolic Wavelet Interaction Network (HyWinNet): Multi-Scale Geometric Learning for Interpretable Protein-Protein Interaction Prediction

Understanding the multi-scale organization of protein-protein interactions (PPIs) is fundamental to deciphering cellular signaling, allosteric regulation, and disease mechanisms, yet existing computational approaches fail to simultaneously resolve atomic-scale binding interfaces and pathway-level coordination. We present HyWinNet, a geometric deep learning framework that unifies Lorentzian hyperbolic graph neural networks with spectral graph wavelet transforms to intrinsically model the hierarchical architecture of biological interactions. The core innovation lies in three synergistic components: (1) Hyperbolic embeddings that preserve evolutionary-conserved topological relationships through negatively curved space projections, capturing scale-free properties of protein networks; (2) Multi-scale wavelet decomposition operating at biologically grounded resolutions to jointly analyze local residue contacts and global pathway dynamics; (3) Contrastive learning with stochastic feature dropout that mimics natural binding interface plasticity. Benchmarked against state-of-the-art methods, HyWinNet demonstrates superior performance in recovering known interactions while predicting previously unannotated functional sites validated through independent structural and biochemical studies. By bridging hyperbolic geometry with graph signal processing, this work establishes a new paradigm for analyzing multi-scale biological networks, offering both interpretable computational predictions and testable hypotheses for experimental validation. The frameworks ability to map hierarchical relationships from atomic details to system-level modules provides a transformative tool for drug discovery and mechanistic studies of complex diseases.

bioinformatics↗

bioRxiv2025

Deep-mutational scanning libraries using tiled-region exchange mutagenesis

The analysis of gene function frequently requires the generation of mutants. Deep-mutational scanning (DMS) has emerged as a powerful tool to decipher important functional residues within genes and proteins. However, methods for performing DMS tend to be complex or laborious. Here, we introduce Tiled-Region Exchange (T-REx) Mutagenesis, which is a multiplexed modification of the EMPIRIC mutagenesis approach. Self-encoded removal fragments are cloned in parallel in non-overlapping gene locations and pooled. In a one-pot reaction, oligonucleotides are then swapped with their corresponding self-encoded removal fragments in bulk using a single Golden Gate reaction. To aid in downstream phenotyping, the library is then fused with unique DNA barcodes using the Bxb1 recombinase. We demonstrate this approach and its optimizations, to show that it is both easy to perform and efficient. This method offers simple and expedient means to create comprehensive mutagenesis libraries. ARTICLE SUMMARYResearchers in the field of molecular genetics frequently investigate protein function via mutations. Here, we present a rapid deep-mutational scanning methodology called Tiled-Region Exchange Mutagenesis that can comprehensively create mutant libraries. The approach is a multiplexed version of the established EMPIRIC mutagenesis approach and retains its simplicity. We show optimizations of the in vitro reactions to reduce cost and improve robustness. This method will be useful to researchers seeking to perform deep-mutational scanning on any gene of interest.

molecular biology↗

bioRxiv2025

Asymmetric Social Representations in the Prefrontal Cortex for Cooperative Behavior

Cooperation is a hallmark of social species, enabling individuals to achieve goals that are unattainable alone. Across species, cooperative behaviors are often organized by distinct social roles such as leaders and followers, yet the neural mechanisms supporting such role-based coordination remain elusive. Here we introduce a new paradigm for studying cooperation in mice, where pairs of animals engage in a joint spatial foraging task that naturally gives rise to stable leader-follower roles predictive of learning speed. Disruption of medial prefrontal cortex (mPFC) activity, particularly in followers, impairs cooperation and induces reciprocal shifts in how animals weigh self- and partner-related cues for decision-making. Calcium imaging reveals that mPFC encodes both leadership dynamics and an egocentric social value map of the partners position, each in an asymmetric, role-specific manner. Combining this behavior with a novel multi-agent inverse reinforcement learning framework, we identify latent value functions that guide cooperative decisions and are decodable from mPFC activity. These findings uncover fundamental neural computations that support cooperation, revealing how social roles shape decision-making in real time. Our work opens new avenues for investigating the cellular and circuit basis of social cognition and collective behavior.

neuroscience↗

bioRxiv2025

Uncertainty and reward histories have distinct effects on decisions after wins and losses

Intelligent behavior necessitates an adaptive integration of feedback. It is well-known that animals asymmetrically learn from positive and negative feedback. While asymmetrical learning is a robust behavioral effect, the latent computations behind how animals represent their environments and use this to differentially weight wins and losses is poorly understood. Here we tested whether and how uncertainty and reward histories modulate the weights placed on wins and losses using a behavioral data set collected in rats. We propose a reinforcement learning model that integrates uncertainty history via an unsigned average reward prediction error and a separate subjective reward history component. We showed that in a dynamic probabilistic reversal learning task with blocks of variable reward predictability, ongoing estimation of uncertainty history and reward history both distinctly influenced rats sensitivity to wins and losses. In more predictable environments, and under low uncertainty levels, i.e., when rats were certain in making correct choices, rats weighted wins more than losses, as indicated by a higher win-stay, and lower lose-shift probability. This asymmetrical learning strategy enabled rats to remain with the correct action, while discounting the influence of rare losses. Further, male rats were more impacted by their reward history, i.e., environmental richness, when making lose-shift decisions, but conversely, female rats were more influenced by their uncertainty history. Hence, we found sex-specific contributions of these latent computations in modulating behavior. We overall demonstrate that asymmetrically weighting wins and losses could form an important behavioral strategy when adapting to ongoing changes in reward and uncertainty history.

animal behavior and cognition↗

bioRxiv2025

The antioxidant networks act as a firewall in maintenance of genomic integrity

Reactive oxygen species (ROS) threatens genomic integrity by both destruction of DNA metabolic enzymes and oxidative DNA damage. We find a negative correlation between oxidative DNA damage and activity of antioxidant enzymes. An antioxidant network formed by interactions between the antioxidant enzymes and the proteins involved in maintenance of genomic integrity was indentified in the nucleus by multi-proteomic investigations. The protein-protein interactions in the antioxidant network are up-regulated under oxidative stress, as proved by quantitative proximity ligation assays in situ within single cells. The antioxidant network catalyzes the ROS dismutation cascade before ROS attacks DNA-processing enzymes, thereby preventing DNA and DNA metabolic enzymes from oxidative damage and dysfunction. Therefore, the antioxidant network plays a firewall role in maintenance of genomic integrity.

biochemistry↗

bioRxiv2025

Prenatal liver is resistant to low glucose-induced inhibition of mTORC1

Prenatal development may adopt unique patterns of metabolic responses to different nutrient supplies. AMPK and mTOR are two central metabolic regulators, with AMPK acting to slow down and mTOR to promote anabolism. Typically, low glucose inhibits TRPVs, leading to AMPK activation and mTOR complex I (mTORC1) inhibition. Here, we observed surprisingly that mTORC1 in the foetal liver remains active in low glucose, although AMPK is effectively activated in an AMP-dependent manner. Mechanistically, we found that TRPV4, a key liver TRPV, is acetylated at K608, disabling its inactivation by fructose-1,6-bisphosphate (FBP)-unoccupied aldolase. Mutation of K608 to arginine renders TRPV4 able to respond to low glucose in foetal hepatocytes. Consistently, embryonic liver-specific expression of acetylation-defective TRPV4-K608R mutant led to mTORC1 inhibition, and caused abnormal intrauterine development or even foetal death. Our findings reveal that the TRPV-mediated resistance of mTORC1 inhibition in low glucose acts as a safeguard for normal foetal development.

biochemistry↗

bioRxiv2025

Enhancing Pharmacometric Modeling with Full Bayesian Inference and Students t-Based M3 Censoring: A Simulated Population PK Study on Robust Handling of Outliers and Censored Data

Pharmacometric modeling and simulation, with population pharmacokinetic (PopPK) modeling as a key component, play a crucial role in characterizing drug disposition and variability, supporting dose optimization and regulatory decision-making. Traditional maximum likelihood estimation (MLE) methods, although efficient, are sensitive to outliers, particularly when datasets contain observations below the limit of quantification (BLQ). As clinical datasets become increasingly complex, more robust modeling approaches are needed. In this study, a simulation-based evaluation was conducted to compare four modeling strategies combining different residual error structures (normal vs. Students t) and censoring methods (M1 vs. M3). Two-compartment pharmacokinetic profiles were simulated for fifty subjects, incorporating varying degrees of outlier contamination and BLQ data. Full Bayesian inference using Markov Chain Monte Carlo (MCMC) methods was employed to estimate posterior distributions of PK parameters at both the population and individual levels. Notably, the combination of Students t-distributed residuals with M3 censoring (Students t_M3) consistently produced the most accurate and precise parameter estimates across all simulation scenarios, even under extreme outlier contamination and substantial BLQ presence. The combination of Students t-distributed residuals with M3 censoring within a Bayesian framework offers a robust and resilient strategy for PopPK modeling, effectively addressing both outlier contamination and data censoring challenges. These findings support the broader adoption of robust Bayesian modeling techniques in pharmacometric practice, particularly for complex and irregular clinical datasets such as cell and gene therapies.

pharmacology and toxicology↗