Biology subjects

Li, Z.

Publications and source records attributed to Li, Z..

At least 397 records · Page 22Linked to original sources

bioRxiv2025

Selective abundance of the stemness-promoting cluster miR-290-295 within the adult substantia nigra dopamine neurons is neuroprotective via preservation of protein synthesis

Locomotor, reward and other critical functions of the body are regulated by the ventral midbrain, with the central role played by dopamine (DA) neurons. The function of these cells from the early development to maturity is critically dependent on the orchestrated expression of coding and non-coding genes. For example, in the stem cells the miR-290-295 cluster constitutes the majority of expressed microRNAs and is critical for stemness in rodents. During development towards various terminally differentiated lineages, such as neurons, the cells typically switch off transcription of these stem cell-specific microRNAs. Here we report that within the adult Substantia Nigra pars compacta (SNpc), the miR-290-295 cluster is exclusively expressed in DA neurons (SNDA), preventing the locomotor deficits and maintaining an adequate expression of proteins involved in DA biogenesis, such as tyrosine hydroxylase (TH), dopa decarboxylase (DDC) and DA transporter (DAT). Importantly, a global knock-out of the miR-290-295 cluster leads to decreased numbers of SNDA neurons in adult mice. Using in vitro and in vivo DA cell-specific loss-of-function models, we demonstrated that miR-292a-3p, the most abundant microRNA in this cluster, directly targets PTEN, a phosphatase antagonizing the neuroprotective phosphatidylinositol-4,5-bisphosphate 3-kinase (PI3K)-AKT-mechanistic target of rapamycin kinase (mTOR) pathways regulating translation initiation. Accordingly, when labelled with the click chemistry-compatible methionine analogue L-azidohomoalanine, miR-290-295 cluster-deficient SNDA neurons revealed a drastic impairment of protein synthesis, which is critical for DA biogenesis. Our surprising findings demonstrate for the first time a selective expression of stem cell-specific and stemness-promoting microRNAs in a distinct population of mature neurons to maintain their physiological functions in the adulthood, suggesting that similar epigenetic disinhibition mechanisms may be also critical for other terminally differentiated cells across species.

neuroscience↗

bioRxiv2025

A complete and near-perfect rhesus macaque reference genome: lessons from subtelomeric repeats and sequencing bias

A truly complete, telomere-to-telomere (T2T), and error-free reference genome remains a foundational resource--and long-standing goal--for unbiased comparative and functional genomics. While recent T2T assemblies of humans and other primates have made substantial progress, most still contain thousands of base-level errors, particularly within highly repetitive regions. Here, we present T2T-MMU8v2.0, a near-perfect T2T assembly of the rhesus macaque (Macaca mulatta), representing the highest base-level accuracy reported in a primate genome to date. By employing an optimized ONT-only assembly strategy, we identify subtelomeric satellite-rich regions as the principal bottleneck to improving assembly quality, owing to technological biases in long-read platforms and limitations in current hybrid assembly frameworks. We discover 268 previously unannotated repeat families and resolve [~]8 Mbp of SATR satellite arrays, with over 99-fold enrichment in historically misassembled subtelomeric regions. These satellites form four distinct genomic architectures, each with unique SATR satellite composition, segmental duplication organization, and epigenetic signatures, distinct from the subtelomeric architectures observed in hominid genomes. Notably, in contrast to the largely gene-poor subtelomeric regions in African hominids, the SATR architectures in macaques harbor 58 actively transcribed genes, supported by open chromatin and expression data, suggesting gene innovation within these repetitive regions. Functionally, T2T-MMU8v2.0 improves read mappability and accuracy across sequencing platforms, and results in a 19% improvement of transcription start site enrichment scores and 5,821 additional chromatin accessibility peaks on average, thereby enhancing variant detection, regulatory annotation, and transcriptomic resolution in population genetics or single-nucleus studies. Together, this work establishes a new benchmark for genomics, offers a roadmap for resolving complex repetitive regions, and reveals previously unrecognized features of subtelomeric genome structure and evolution.

genomics↗

bioRxiv2025

Single Capture Quantitative Oblique Back-Illumination Microscopy

Quantitative oblique back-illumination microscopy (qOBM) has emerged as a powerful technique for label-free, 3D quantitative phase imaging of arbitrarily thick biological specimens. However, in its initial embodiment, qOBM requires multiple captures for phase recovery, which reduces imaging speed and increases system complexity. In this work, we present a novel advancement in qOBM: single-capture qOBM (SCqOBM) which utilizes a deep learning model to accurately reconstruct phase information from a single oblique back-illumination capture. We demonstrate that SCqOBM achieves remarkable phase imaging accuracy, closely matching the results of traditional four-capture qOBM in diverse biological samples. We first highlight the unique potential of SCqOBM for non-invasive, in-vivo imaging applications by visualizing blood flow in mouse brain and human arm. Additionally, we demonstrate single-slice (en-face) quantitative phase imaging at 2 kHz and volumetric refractive index tomography at speeds up to 10 volumes per second. SCqOBM offers transformative advantages in speed, simplicity, and system accessibility, making it highly suitable for dynamic and real-time imaging applications. Its ability to produce high-resolution, quantitative phase and refractive index images with minimal hardware complexity opens new frontiers in biomedical research and clinical diagnostics, including non-invasive hematological assessments and in-vivo tissue imaging.

bioengineering↗

bioRxiv2025

Aeon: an open-source platform to study the neural basis of ethological behaviours over naturalistic timescales

Ethological behaviours are a powerful tool for neuroscience since they leverage the robust neural computations shaped by the species evolution to study the neural basis of cognitive functions. However, such behaviours are often transitory and dependent on factors that vary over space, time and number of individuals, making them difficult to capture with standard laboratory tasks. Here we present Aeon, an open-source platform designed for continuous, long-term study of self-guided behaviours in multiple mice and simultaneous recording of brain activity within large, customizable habitats. By integrating specialized modules for navigation, nesting and sleeping, escaping, foraging, and social interaction, Aeon enables the expression of key ethological behaviours while achieving experimental control and multi-dimensional quantifications from sub-millisecond to month-long durations. Its software architecture ensures robust data acquisition via many synchronized data streams and delivers a new standardised, unified data format that yields seamless, integrated analysis pipelines. Using assays such as digging-to-threshold and social foraging, Aeon reveals how mice adapt strategies in a changing environment and in response to conspecifics. Aeon bridges ecological relevance with rigorous experimental control to advance our understanding of how neural circuit activity gives rise to a range of highly conserved and adaptive behaviours.

neuroscience↗

bioRxiv2025

DAXX governs the silencing of LINE1 during spermatogenesis in mice

The suppression of transposable elements in germline is critical for safeguarding fertility. Here we identify that the DAXX, a potent transcription repressor and an H3.3 chaperone, is indispensable for transposable elements silencing during spermatogenesis. Male mice with conditional knockout of Daxx in germ cells mediated by Ddx4-cre display delayed meiotic progression, deformed and reduced production of sperms, and an age-dependent decline in fertility. The ablation of DAXX results in activation of evolutionarily young LINE1 and ERVs subfamilies. Mechanistically, DAXX interacts with DMAP1 to maintain DNA methylation of LINE1 in meiotic cells. In summary, this study identifies DAXX as a previously unknown regulator of spermatogenesis and demonstrates that it functions as an epigenetic regulator to maintain the silencing the young LINE1 by DNA methylation.

developmental biology↗

bioRxiv2025

A scalable computational framework for predicting gene expression from candidate cis-regulatory elements

Deciphering the relationships between cis-regulatory elements (CREs) and target gene expression has been a long-standing unsolved problem in molecular biology, and the dynamics of CREs in different cell types make this problem more challenging. To address this challenge, we propose a scalable computational framework for predicting gene expression (ScPGE) from discrete candidate CREs (cCREs). ScPGE assembles DNA sequences, transcription factor (TF) binding scores, and epigenomic tracks from discrete cCREs into 3-dimensional tensors, and then models the relationships between cCREs and genes by combining convolutional neural network with transformer. Compared with current state-of-the-art models, ScPGE exhibits superior performance in predicting gene expression and yields higher accuracy in identifying active enhancer-gene interactions through attention mechanisms. By comprehensively analyzing ScPGEs predictions, we find a pattern in true positives (TPs) that the regulatory effect of cCREs on genes decreases with distance. Inspired by the pattern, we design two methods to enhance the ability to capture distal cCRE-gene interactions by incorporating chromatin loops into the ScPGE model. Furthermore, ScPGE accurately discovers some crucial TF motifs within prioritized cCREs and reveals the different regulatory types of these cCREs.

bioinformatics↗

bioRxiv2025

Real-time visualization of ligand-specific conformational dynamics of GPCR C-terminal domain in living cells

The cytoplasmic tails (C-tails) of membrane receptors are fundamental hubs for signal transductions. Yet directly investigating their dynamics in living cells is challenging. We developed a single-molecule technique to sense C-tail's conformational transitions. It was applied to investigate the ligand-induced activation of {beta}2AR, a prototypical G protein-coupled receptor (GPCR). Our data elucidate how the receptor transduces ligand binding to cell-level outcomes, with the ligand efficacy being interpreted in terms of the association and disassociation rates of the G protein. Moreover, upon G protein binding, not only the C-tail is displaced from the intracellular surface of the receptor but also the eighth helix H8 is dissociated from the plasma membrane. This work establishes a robust framework to directly decipher the activation of membrane receptors without interferences from overexpressed downstream transducers.

biophysics↗

bioRxiv2025

Genetically encoded assembly recorder temporally resolves cellular histories in cellulo and in vivo

Mapping cellular activity with high spatiotemporal precision in complex tissues is essential for understanding organ physiology, pathology, and regenerative processes. Here, we introduce Granularly Expanding Memory for Intracellular Narrative Integration (GEMINI), an in cellulo recording platform that leverages a computationally designed protein assembly as an intracellular memory device to record individual cells activity histories. GEMINI grows predictably within live cells with minimal interference to cellular functions, capturing cellular activities as tree-ring-like fluorescent patterns in the expanding scaffolds for imaging-based retrospective readout. Absolute chronological information of activity histories was attainable with hour-level accuracy through the integration of fiducial timestamps. GEMINI effectively resolved differential NF{kappa}B-mediated transcriptional changes, distinguishing fast dynamics of 15 minutes, and providing quantifiable signal amplitudes. In a xenograft model, GEMINI recorded inflammation-induced signaling dynamics across tissue with cellular resolution, revealing spatial heterogeneity linked to vascular density. When expressed in the mouse brain, GEMINI exhibited negligible impact on neuronal survival, with animals maintaining normal motor and cognitive behaviors. In physiological contexts, GEMINI successfully resolved both transcriptional changes and activity patterns of neurons in the brain. Together, GEMINI provides a robust and generalizable means for spatiotemporal mapping of cell dynamics underlying physiological and pathological processes in both culture and intact tissues.

bioengineering↗

bioRxiv2025

A Complete Telomere-to-Telomere Diploid Reference Genome for Indian Population

Human reference genomes have been instrumental in advancing genomic and biomedical research, but South and Southeast Asian populations are underrepresented, despite accounting for a large proportion of world population. As a part of effort on generating reference genomes for these populations, we present the first gapless, telomere-to-telomere (T2T) diploid genome assembly created by using a trio sample set of Indian ancestry (I002C), with NG50 of 154.89 Mb and 146.27 Mb for the maternal and paternal haplotypes, including the fully assembled rDNA array for the maternal chromosome 21 and Y chromosome. With the Merqury QVs of 82.05, 83.08 and 82.64 for the maternal, paternal and haploid assemblies respectively, I002C represents the highest-quality human genome assembled in both diploid and haploid forms to date. Compared to CHM13, the I002C genome displays substantial sequence diversity, resulting in 14,943 structural variants, including 3,236 novel variants absent from public databases. Analysis of trio-phased haplotypes further revealed elevated inter-haplotype divergence within centromeric and subtelomeric regions, along with identification of differentially methylated regions (DMRs) as candidates for novel imprinting loci. As a result of substantial SVs between them, I002C is a more suitable reference than CHM13 for the genomic analysis of South Asian samples with less reference bias and better performance in mapping and variant calling, particularly for long read sequencing data. As the first high-quality T2T diploid reference genome for Indian, the largest worlds population, I002C contributes to the growing set of population-specific reference genomes and helps to overcome a significant gap in human genome diversity.

genomics↗

bioRxiv2025

mTORC1-Dependent Regulation of the CCL24-CCR3 Axis Controls Granuloma Formation and Maintenance in Sarcoidosis

Sarcoidosis is a chronic granulomatous disease marked by persistent inflammation and immune cell aggregation, yet its molecular underpinnings remain incompletely understood, hindering the development of effective targeted therapies. Here, we report that deletion of TSC1 or TSC2 in mice using a Fsp1-Cre leads to spontaneous formation of sarcoid-like granulomas, driven by hyperactivation of the mTORC1 pathway in fibroblasts and interstitial macrophages. Through inflammatory cytokine/chemokine array, we identified CCL24, a chemokine ligand for CCR3, as a key immunoregulatory molecule downregulated in both our murine model and sarcoid cohort plasma. Mechanistically, mTORC1 suppresses CCL24 expression via aberrant STAT3 signaling in fibroblasts and promotes CCR3 expression in interstitial macrophages, uncovering a novel regulatory axis in granuloma formation and maintenance. Pharmacological inhibition using rapamycin and azithromycin markedly attenuated granuloma burden and normalized CCL24-CCR3 signaling, underscoring the therapeutic relevance of this axis. Together, our study establishes a mechanistic link between mTORC1 activation, CCL24-CCR3 dysregulation, and granuloma persistence, offering not only a new insight into molecular mechanisms in sarcoidosis but also identifying promising targets for clinical intervention.

immunology↗

bioRxiv2025

Interwoven DNA-MOF crystals for multi-millennial data storage

DNA has emerged as a promising medium for high-density and energy-efficient data storage, providing a promising solution to capacity constraints and energy demands resulting from the exponential growth of data. Long-term stable storage of DNA data in ambient conditions is a critical requirement for its practical application. Whereas strategies have been proposed to protect DNA from environmental degradation, they are often at the expense of data storage density. Here, we propose a strategy via interweaving metal-organic framework (MOF) and DNA to synthesize DNA-MOF crystal (DNA-MOF), a high-density and long-lifespan DNA-based information material. The uniform distribution of DNA molecules within the crystalline frameworks enables a high loading capacity of up to 30 wt%, corresponding to a theoretical information density of 106.6 exabytes/g. The crystal structure of MOF-DNA demonstrates efficient resistance to environmental damage such as heat, ultraviolet radiation, DNase, etc., achieving an estimated archival half-life over 24,000 years at 9.4 {degrees}C. The interwoven DNA-MOF crystals establish a material foundation for the reliable operation of DNA storage systems in open-field deployment and provide a new pathway toward sustainable long-term management of massive data.

biochemistry↗

bioRxiv2025

A reference panel for linkage disequilibrium and genotype imputation using whole-genome sequencing data from 2,680 participants across India

India is the most populous country globally, yet genetic studies involving Indian individuals remain limited. The Indian population is composed of many founder groups and has a mixed genetic ancestry, including an ancestral component not observed anywhere outside of India. This presents a unique opportunity to uncover novel disease variants and develop more tailored medical interventions. To facilitate genetic research in India, a crucial first step is to create a foundational resource that serves as a benchmark for future population studies and methods development. To this end, we have constructed the largest and most nationally representative linkage disequilibrium and genotype imputation reference panels in India to date, using high-coverage whole-genome sequencing data of 2,680 Indian participants from the Longitudinal Aging Study in India-Harmonized Diagnostic Assessment of Dementia (LASI-DAD). As an LD reference panel, LASI-DAD includes 69.5 million variants, representing 170% and 213% increases relative to the 1000 Genomes Project (1000G) and TOP-LD panels, respectively. Besides serving as an LD lookup panel, LASI-DAD facilitates various statistical analyses that rely on precise LD estimates. In a polygenic risk score (PRS) analysis, LASI-DAD improved the predictive performance of PRS by 2.1% to 35.1% across traits and studies. As an imputation reference panel, LASI-DAD improved the imputation accuracy by 3% to 101% (mean = 38%) compared to the TOPMed panel (Version R3) and by 3% to 73% (mean = 27%) compared to the Genome Asia Pilot (GAsP) panel across different minor allele frequencies. The LASI-DAD reference panel is publicly available to benefit future studies.

genetics↗

bioRxiv2025

Response of human iPSC-cardiomyocytes to adrenergic drugs assessed by high-throughput pericellular oxygen measurements

Rate- and contractility-modulating drugs, such as adrenergic agonists and antagonists, are widely used in the treatment of cardiovascular conditions. Preclinical assessment of new modulators of rate, inotropy and metabolism can be aided by high-throughput (HT) methods for chronic measurements, coupled with scalable human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs). Here, we evaluate the utility of long-term optical (label-free) measurements of pericellular oxygen in a HT format (96-well plates) for the assessment of the effectiveness of adrenergic drugs in hiPSC-CMs. Quantitative oxygen consumption metrics were derived and correlated to measurements performed in the same samples using all-optical electrophysiology. Adrenergic agonists significantly increased oxygen consumption rate (OCR), best seen in the kinetics of initial depletion of pericellular oxygen, i.e. time to reach 5%. Adrenergic antagonists decreased OCR, best quantified using steady-state values for pericellular oxygen after at least 5 hours. OCR-based drug type identification correlated well with the acute spontaneous rate measurements in the same samples. Direct rate modulation with chronic optogenetic pacing sped up OCR in hiPSC-CMs. Blebbistatin, an excitation-contraction uncoupler, significantly reduced OCR. Computational modeling helped interpret our results by capturing the effects of pacing rate, adrenergic stimulation, and blebbistatin on oxygen consumption, thereby highlighting the key contribution of inotropy and mechanical contraction to OCR in hiPSC-CMs. We conclude that HT label-free optical oxygen measurements and the comprehensive in silico hiPSC-CM models, constrained by such measurements, represent valuable human-based approaches for non-invasive assessment of rate- and metabolism-modulating drugs in preclinical studies.

bioengineering↗

bioRxiv2025

A Patient-Specific 3D Printed Carotid Artery Model Integrating Vascular Structure, Flow and Endothelium Responses

The progression of atherosclerosis is driven by the interplay between vascular anatomy, hemodynamic forces, and endothelial responses. However, existing in vitro vascular models have yet to integrate all these elements into a cohesive, patient-specific system. Here, we present the first instance of direct 3D printing of a miniaturized, patient-specific carotid artery model that recapitulates anatomical-dependent hemodynamic changes and vascular cell remodeling. Phase-contrast MRI scans from a healthy donor were used to generate miniaturized 3D carotid artery models, which were analyzed via computational fluid dynamics (CFD) and particle imaging velocimetry (PIV) to validate the preservation of physiological hemodynamic properties. Using digital light processing (DLP) 3D printing, we fabricated the miniaturized carotid artery vessel using GelMA, containing embedded human aortic smooth muscle cells and an endothelialized lumen. Perfusion culture replicated physiological arterial shear stress of up to 10 dynes cm-{superscript 2}, resulting in differential endothelial cell alignment and inflammatory monocyte adhesion corresponding to laminar and turbulent flow regions within the carotid artery. This model serves as a powerful platform to investigate how anatomical variation influences susceptibility to atherosclerosis through its impact on local flow dynamics.

bioengineering↗

bioRxiv2025

Autism-associated oxysterol regulates GABAergic neurogenesis and subtype fates

Distorted GABAergic neurodevelopment is believed to underscore cortical network dysfunction that lies at the heart of neurodevelopmental disorders (NDD) such as autism and schizophrenia. GABAergic neuron diversity is sculptured by cortical environmental cues during protracted postmitotic differentiation. However, the mechanism by which the NDD environment influences GABAergic neuronal development remains largely unknown. Oxysterols are oxidized metabolites of cholesterol that can interact with developmental signaling pathways. Using an iPSC model recapitulating human forebrain GABAergic neuron development and single-cell transcriptomic profiling, we show that 24S, 25-epoxysterol, an NDD-affected oxysterol highly enriched in the fetal brain, promotes neurogenesis, and disturbs the composition of GABAergic neuronal subtypes. Moreover, pharmacological and genetic interrogation identified the liver X receptor as a regulatory pathway mediating the action of 24S, 25-epoxysterol. These findings provide insights into the roles of cholesterol metabolism in neuronal development and a potential mechanism by which dysregulated brain oxysterols contribute to the pathogenesis of NDD.

developmental biology↗

bioRxiv2025

StruCloze: A Unified Framework for Backmapping and Inpainting of Biomolecules

Atomistic resolution is essential for understanding biomolecular structure and function, yet coarse-grained (CG) models remain indispensable for simulating large and dynamic systems. Reconstructing accurate all-atom structures from CG representations, particularly across varied CG schemes and biomolecular types, remains a fundamental challenge. Moreover, flexible or disordered regions may well suffer from failure in structure modeling, making inpainting missing regions another challenging task. Here, we present StruCloze, a deep learning framework for reconstructing atomistic structures from CG models and inpainting missing regions for both proteins and nucleic acids. StruCloze generalizes across various CG levels and biomolecule types on single pretraining, with minimal fine-tuning required for optimal performance on specific representations. It achieves state-of-the-art accuracy in reconstructing both protein and nucleic acid structures, demonstrates superior transferability and speed compared to existing methods. Leveraging masked learning strategy, StruCloze also excels at inpainting structurally missing regions in structures, offering a practical tool for structural refinement and integrative modeling. Our framework provides a general solution for bridging reduced or incomplete representations with full atomistic detail of biomolecular structures, enabling rapid local structure prediction and further analysis on system dynamics.

bioinformatics↗

bioRxiv2025

Differences in external loads of different pitch types in Chinese male college baseball players

BackgroundIn baseball, monitoring player load solely through pitch count and innings overlooks the variability introduced by different pitch types. This study analyzed differences in external load, measured as Player Load, across various pitch types using a GPS-based wearable device. Additionally, the relationship between Player Load and ball velocity was examined. MethodsFour male collegiate Division I baseball players from China (age: 18.5 {+/-} 0.58 years, height: 181.00 {+/-} 6.83 cm, weight: 78.00 {+/-} 5.48 kg) participated in this study. External loads were collected for four pitch types, fastball, changeup, curveball, and slider, using a wearable sensor device that recorded six variables: Maximum Player Load (Max PL), Maximum Rotation (Max Rot), Pitching Hourly Velocity, and Percentage of Acceleration Change in the Three Axes (Up Load %, Side Load %, and Fwd Load %). A Kruskal-Wallis non-parametric test was used to assess differences across pitch types, while stepwise multiple regression analyzed the impact of Player Load on pitching speed. ResultsSignificant differences were observed among pitch types for Max PL, Max Rot, Hourly Speed, Up Load %, and Fwd Load % (p<0.05), while Side Load % did not show a significant difference (p>0.05). Stepwise multiple regression indicated that pitching speed was influenced by Max PL, with the equation: mph = 78.816 + 7.001 Max PL, R2 = 0.192, suggesting that Max PL accounted for 19.2% of the variability in pitching speed. DiscussionExternal training loads in pitching vary by pitch type, with variable-speed pitches generating higher peak external loads, whereas fastballs are associated with greater ball speeds.

scientific communication and education↗

bioRxiv2025

Using Artificial Intelligence to Assess Cross-Species Transmission Potential of Influenza A Virus

Influenza A viruses (IAVs) pose pandemic threats through cross-species transmission, yet predicting their adaptive evolution remains challenging. We introduced Influenza A virus Adaptability to host X (FluAdaX), a deep learning framework that integrates a moving average-equipped gated attention mechanism using full-genome sequences. FluAdaX demonstrated robust host classification performance across endemic IAV strains, and outperformed traditional models in detecting avian-to-human transmission. Spillover score and adaptability score were introduced to evaluate host shift risk, which prioritized variants with elevated human adaptation potential, such as H7N9, H9N2 avian IAVs, and H1N1 swine IAVs. Besides HA and NA genes, PB2 and NS genes were found critical for zoonosis. Potential molecular markers associated with avian/human tropism were identified across PB2 and NS genes using XGBoost. FluAdaX provided a dynamic framework to decode IAV host adaptation, enabling real-time risk assessment of cross-species transmission of emerging IAV variants.

bioinformatics↗