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Shi, L.

Publications and source records attributed to Shi, L..

At least 91 records · Page 5Linked to original sources
bioRxiv2025

Personalized Multiscale Modeling of Left Atrial Mechanics and Blood Flow

We present a personalized multiscale mechanics model of the left atrium (LA) to simulate its deformation throughout the cardiac cycle and drive blood flow. Our patient data-driven model tightly integrates 3D structural mechanics of the LA myocardium, incorporating both passive and active components, with a 0D closed-loop lumped parameter network (LPN)-based circulatory system model. A finite element (FE) model of LA tissue is constructed from the patients images, assuming uniform thickness and employing rule-based fiber directions, a structurally based constitutive model for the passive mechanics, and a phenomenological contraction model while applying physiologically relevant boundary conditions. We then adopted a multi-step personalization approach, in which the LPN parameters with a surrogate LA model are first optimized to match cuff-based blood pressures and cardiac lumen volumes derived from time-resolved 3D gated computed tomography angiography (CTA) images. The surrogate LA pressure during passive expansion is used to estimate myocardial passive mechanics parameters and the reference unloaded configuration using an inverse finite element analysis (iFEA) framework. Finally, a robust multiscale coupling is applied between the iFEA-optimized FE model and the tuned 0D LPN model to characterize LA contraction. This effectively captures the 8-shaped pressure-volume curve and reasonably aligns with the image-based cavity volumes and deformation. The resulting simulation-predicted deformation is imposed as a moving-wall boundary condition to model atrial hemodynamics. Overall, this comprehensive digital twinning platform could be applied to study LA biomechanics in health and disease and assist in devising personalized treatment plans.

bioengineering↗
bioRxiv2025

A Telomere-to-Telomere Diploid Reference Genome and Centromere Structure of the Chinese Quartet

Recent advances in sequencing technologies have enabled the complete assembly of human genomes from telomere to telomere (T2T), resolving previously inaccessible regions such as centromeres and segmental duplications. Here, we present an updated, higher-quality, haplotype-phased T2T assembly of the Chinese Quartet (T2T-CQ), a family cohort comprising monozygotic twins and their parents, generated using high-coverage ONT ultralong and PacBio HiFi sequencing. The T2T-CQ assembly serves as a crucial reference genome for integrating publicly available multi-omics data and advances the utility of the Quartet reference materials. The T2T-CQ assembly scores highly on multiple metrics of continuity and completeness, with Genome Continuity Inspector (GCI) scores of 77.76 (maternal) and 76.41 (paternal), quality values (QV) > 70, and Clipping Reveals Assembly Quality (CRAQ) scores > 99.6 for both haplotypes, enabling complete annotation of centromeric regions. Within these regions, we identified novel 13-mer higher-order repeat patterns on chromosome 17 which exhibited a monophyletic origin and emerged approximately 230 thousand years ago. Overall, this work establishes an essential genomic resource for the Han Chinese population and advances the development of a T2T pan-Chinese reference genome, which will significantly enable future investigations both into population-specific structural variants and the evolutionary dynamics of centromeres.

genomics↗
bioRxiv2025

Soluble Immune Factor Profiles in Blood and CSF Associated with LRRK2 Mutations and Parkinson's Disease

Background and ObjectivesMutations in the Leucine-rich repeat kinase 2 (LRRK2) gene are one of the most common genetic causes of Parkinsons disease (PD) and are linked to immune dysregulation in both the central nervous system and periphery. However, peripheral and central profiles of soluble immune factors associated with LRRK2 mutations and PD have not been comprehensively characterized. Using serum and CSF samples from the LRRK2 Cohort Consortium (LCC), this study aimed to probe a broad range of soluble immune biomarkers associated with LRRK2 mutations and PD. MethodsWe investigated the levels of soluble immune regulators in the serum (n=651) and cerebrospinal fluid (CSF, n=129) of LRRK2 mutation carriers and non-carriers, both with and without PD. A total of 65 cytokines, chemokines, growth factors, and soluble receptors were assessed by Luminex immunoassay. A multivariable robust linear model was used to determine levels associated with LRRK2 mutations and PD status, adjusting for age, sex, and sample cohort. Correlations were assessed using the Spearman correlation coefficient. LRRK2 G2019S knock-in mice were used to validate the associations identified in the LCC. ResultsIn this extensive discovery cohort, we identified several elevated serum immune regulatory factors associated with LRRK2 mutations. In particular, serum stromal cell-derived factor-1 alpha (SDF-1 alpha) levels, as supported by findings in LRRK2 G2019S knock-in mice, and tumor necrosis factor receptor II (TNF-RII) were significantly increased after multiple comparison adjustment. In contrast, LRRK2 mutations were associated with reduced soluble immune markers, including BAFF, CD40-Ligand, I-TAC, MIP-3 alpha, NGF beta, and IL-27 in CSF. Those with clinically diagnosed PD, with or without LRRK2 mutations, did not show strong signals in serum but reduced inflammatory analytes in CSF, including MIF, MMP-1, CD30, Tweak, and SDF-1 alpha. In addition, we found that the serum levels of these soluble immune factors display varied correlations with their corresponding CSF levels. DiscussionThis study highlights distinct immune profiles associated with LRRK2 mutations and PD in the periphery and CNS. Serum levels of SDF-1alpha and TNF-RII were elevated in LRRK2 mutation carriers, while CSF immune markers were reduced. In PD, irrespective of LRRK2 status, reduced CSF inflammatory analytes and weak serum signals were observed. These results provide insight into immune dysregulation linked to LRRK2 mutations. If replicable in independent datasets, they offer potential avenues for biomarker and therapeutic exploration.

neuroscience↗
bioRxiv2025

High-Quality Cell Capture Reveals Transcriptomic Changes After Single-Axon Injury of Mauthner Cells

In vivo single-cell capture methods based on micropipettes are essential for correlating morphological characteristics with transcriptomic profiling under physiological conditions. However, they often suffer from significant contamination of off-target cells. Consequently, we developed Hip-seq, which significantly reduces heavily contaminated cells, decreases contamination levels, improves cell reproducibility, and enhances data analysis accuracy compared to patch-seq. Using Hip-seq, we found that axon regeneration failure could be due to abnormal activation of translation and the circadian clock. Axon-regenerable central neurons reactivated axon development-related genes during regeneration. And one-to-one associated analysis helped identify pro-regenerative genes.

neuroscience↗
bioRxiv2025

Micromechanics of lung capillaries across mouse lifespan and in positive- vs negative-pressure ventilation

The lung undergoes continuous remodeling throughout normal development and aging, including changes to alveolar and capillary structure and function. While histological methods allow static analysis of these age-related changes, characterizing the changes that occur in response to mechanical stimuli remains difficult, particularly over a dynamic, physiologically relevant range in a functioning lung. Alveolar and capillary distension - the change in diameter of alveoli and capillaries, respectively, in response to pressure changes - is one such process, where dynamically controlling and monitoring the diameter of the same capillary or alveolus is essential to infer its mechanical properties. We overcome these limitations by utilizing the recently developed crystal ribcage to image the alveoli and vasculature of a functional mouse lung across the lifespan in postnatal (6-7 days), young adult (12-18 weeks), and aged (20+ months) mice. Using a range of biologically relevant vascular (0-15 cmH2O) and transpulmonary (3-12 cmH2O) pressures, we directly quantify vascular and alveolar distention in the functional lung as we precisely adjust pulmonary pressures. Our results show differences in age-related alveolar and vascular distensibility: when we increase transpulmonary alveolar or vascular pressure, vessels in postnatal lungs expand less and undergo less radial and axial strain, under each respective pressure type, suggesting stiffer capillaries than in older lungs. However, while vessels in young adult and aged lungs respond similarly to variations in vascular pressure, differences in elasticity start to emerge at the alveolar scale in response to transpulmonary alveolar pressure changes. Our results further indicate that differing effects of ventilation mode (i.e., positive vs negative) present themselves at the capillary level, with vessels under positive pressure undergoing more compression than when under negative-pressure conditions. These findings contribute both to the understanding of the functional changes that occur within the lung across the lifespan, as well as to the debate of ventilation effects on lung microphysiology.

physiology↗
bioRxiv2025

GenomeOcean: An Efficient Genome Foundation Model Trained on Large-Scale Metagenomic Assemblies

Functional genomic sequences occupy an infinitesimal fraction of the astronomically large DNA sequence space, implying that evolution explores a low-dimensional manifold shaped by universal biochemical and evolutionary constraints. To investigate this underexplored Genomic Manifold Hypothesis using scalable, data-driven evidence, we developed GenomeOcean, a 4-billion-parameter generative model trained on 219 TB of diverse, co-assembled global environmental metagenomic data using an optimized transformer. The model captures both universal phylogenetic syntax and protein-coding fidelity. Furthermore, we validate the embeddings intrinsic low dimensionality. Crucially, comparisons with the independently trained Evo 2 model demonstrate a strong linear correspondence between their embedding spaces and convergent generative behaviors. These results suggest that the genomic manifold represents a fundamental biological principle, offering a unified framework for understanding evolutionary constraints and guiding synthetic biology.

bioinformatics↗
bioRxiv2025

Thermal cycling transcription boosts RNA production.

Efficient RNA production is essential for therapeutic applications. Currently, mRNA is generated by in vitro transcription with RNA polymerases at a constant temperature. The success of these transcriptions depends on various factors including sequence composition and size. Sometimes, especially for long RNAs, achieving efficient transcript yields are challenging. We developed a novel approach by incorporating a high-temperature denaturation step. Our protocol includes the following two steps of thermal cycling RNA transcription: the initial enzyme-driven RNA transcription step is done at RNA polymerase active temperature (37 {degrees}C); then the nucleic acids melting step is carried out at elevated temperatures (55-70{degrees}C); after the reaction is cooled to the temperature of optimal polymerase activity, the first step is repeated. Denaturation enables the generation of optimized, more stable mRNAs, which alleviates the mRNA instability that often occurs during RNA-based therapeutic development. For example, this new thermal cycling RNA transcription approach can employ high GC content, thus increasing RNA stability. For long and difficult templates, the combination of sequence optimization by LinearDesign algorithm in conjunction with transcription via thermal cycling significantly improved mRNA production. Thermal cycling transcription dramatically increased the efficiency of most RNA products while reducing costs, facilitating RNA-based therapeutic development.

biochemistry↗
bioRxiv2024

Small Molecule Modulators of Beta-arrestins

{beta}-arrestins are multifunctional regulators of G protein-coupled receptor (GPCR) signaling, orchestrating diverse downstream signaling events and physiological responses across the vast GPCR superfamily. While GPCR pharmacology has advanced to target orthosteric and allosteric sites, as well as G proteins and GRKs, comparable chemical tools to study {beta}-arrestins remain lacking. Here, we report the discovery of small-molecule inhibitors that selectively target {beta}-arrestins and delineate their mechanism of action through integrated pharmacological, biochemical, biophysical, and structural analyses. These inhibitors disrupt {beta}-arrestin-engagement with agonist-activated GPCRs, impairing desensitization, internalization, and {beta}-arrestin-dependent functions while sparing G protein-receptor coupling. Cryo-EM, MD simulations, and structure-guided mutagenesis reveal that one modulator, Cmpd-5, engages a cryptic pocket formed by the middle, C-, and lariat loops of {beta}-arrestin1--a critical receptor-binding interface--stabilizing a distinct conformation incompatible with GPCR engagement. Together, these findings provide a mechanistic framework for {beta}-arrestin modulation, introducing transducer-targeted strategies to fine-tune GPCR signaling and guide the development of pathway-specific therapeutics.

biochemistry↗
bioRxiv2024

A practical DNA data storage using expanded alphabet introducing 5-methylcytosine

DNA molecular is a promising next-generation data storage medium. Recently, it has been theoretically proposed that non-natural or modified bases can serve as extra molecular letters to increase the information density. However, the feasibility of the strategy is challenging due to the difficulty in synthesizing and the complex structure of non-natural DNA sequences. Here, we described a practical DNA data storage transcoding scheme named R+ based on expanded molecular alphabet by introducing 5-methlcytosine(5mC). We also demonstrated the experimental validation by encoding one representative file into several 1.3~1.6 kbps in vitro DNA fragments for nanopore sequencing. The results show an average data recovery rate of 98.97% and 86.91% with and without reference respectively. This work validates the practicability of 5mC in DNA storage systems, with a potentially wide range of applications. Availability & ImplementationR+ is implemented in Python and the code is available under the MIT license at https://github.com/Incpink-Liu/DNA-storage-R_plus

synthetic biology↗
bioRxiv2024

Quantifying Molecular Changes in the Preeclamptic Rat Placenta with Targeted Contrast-Enhanced Ultrasound Imaging

PurposeAbnormal placental remodeling is linked to various pregnancy-related diseases, including preeclampsia (PE). This study applies a bicompartmental (BCM) model to quantify molecular expression changes in the placenta, indicative of abnormal placental remodeling, and evaluates the effectiveness of targeted contrast-enhanced ultrasound (T-CEUS) in detecting the abnormal placental vasculature. The BCM model provides high temporal resolution and differentiation of anatomical artery structures within the placenta by analyzing the distribution of contrast agents. MethodsA targeted contrast agent (TCA) composed of gas-filled microbubbles (MB), with a surface-conjugated peptide to target {nu}{beta}3 integrin, a biomarker for angiogenesis, was used for quantifying placental vascular development. CEUS images were acquired from timed pregnant Sprague Dawley rats with experimentally-induced reduced uterine perfusion pressure (RUPP) placental insufficiency. On gestational day (GD) 18 of a 21-day gestation, CEUS images were acquired from both Normal pregnant (NP; n=6) and RUPP (n=6) dams after injection of the TCA. The BCM model was used to estimate the binding dynamics of the TCA, providing a parametric map of the binding constant (Kb) of the placenta. ResultsThe RUPP group showed a significant reduction in the value of Kb compared to the NP group (p < 0.05). A histogram of the placental Kb was compared to alternative analyses (differential target enhancement, dTE and late enhancement, LE) to demonstrate that it can differentiate between anatomical artery structures with a higher contrast-to-background ratio. ConclusionsThe BCM method differentiates molecular changes associated with the abnormal placental development associated with PE. It also reveals more intricate internal anatomical structures of the placenta in comparison to dTE and LE, suggesting that the BCM could enhance early detection and monitoring of PE.

bioengineering↗
bioRxiv2024

Automated Cell Type Annotation with Reference Cluster Mapping

Single-cell RNA sequencing has transformed the field of cellular biology by providing unprecedented insights into cellular heterogeneity. However, characterizing scRNA-seq datasets remains a significant challenge. We introduce RefCM, a novel computational method that combines optimal transport and integer programming to enhance the annotation of scRNA clusters using established reference datasets. Our method produces highly accurate cross-technology, cross-tissue, and cross-species mappings while remaining tractable at atlas scale, outperforming existing methods across all these tasks. By providing precise annotations, RefCM can enable the discovery of new cell types, states, and relationships in single-cell transcriptomic data.

bioinformatics↗
bioRxiv2024

Stage-Specific Transcriptome Landscape of Hepatocellular Carcinoma: Insights from Super and Poor Survivors with Prognostic Signature Identification

BackgroundThe prognosis for hepatocellular carcinoma (HCC) patients can vary significantly even within the same clinical stage. This study aims to characterize the stage-specific transcriptomic landscape of super survivors with HCC and identify a prognostic gene signature. MethodsWe analyzed data from The Cancer Genome Atlas (TCGA) for 76 matched super survivors (alive at 5 years) and poor survivors (deceased within 1 year) with HCC. Gene set enrichment analysis stratified by stage was conducted and a key prognostic gene signature was developed. The signature was then applied to the full TCGA cohort and independently validated in International Cancer Genome Consortium (ICGC) data. FindingsStage-specific transcriptomic profiling revealed distinct patterns in super survivors. Stage I and II showed positive enrichment in immune response pathways, while stage III exhibited enhanced catabolic activities and reduced glycolysis. Across all stages, cell cycle processes were less active in super survivors. A 19-gene signature, incorporating immune, metabolic, and cell cycle genes, accurately distinguished super from poor survivors with 91% accuracy (69/76). The signature reliably predicted overall survival in both the verification cohort (1-year, 3-year, and 5-year AUROCs of 0.82, 0.80, and 0.78) and the independent validation cohort (1-year and 3-year AUROCs of 0.80 and 0.83). Consistent AUROCs were observed across all tumor stages. InterpretationOur findings reveal a dynamic shift in HCC progression, with immune dominance in early stages and metabolic dominance in later stages, alongside reduced cell cycle activity across all stages. Integrating stage-specific transcriptomic profiles offers a promising approach to enhancing individualized management for HCC patients.

bioinformatics↗
bioRxiv2024

All-Optical Multimodal Mapping of Single Cell Type-Specific Metabolic Activities via REDCAT

Metabolism underlies cell growth, survival, and function, yet its activities vary widely across cell types and tissue environments. Spatially resolving these processes in situ at single-cell resolution is essential to advance our understanding of cellular function and tissue physiology in health and disease. However, existing approaches are limited by either destructive workflows, insufficient spatial resolution and biochemical specificity, or lack of direct linkage to cell identity. Here, we present Raman Enhanced Delineation of Cell Atlases in Tissues (REDCAT), a multimodal all-optical platform that integrates stimulated Raman scattering, autofluorescence redox imaging, second harmonic generation, and high-plex immunofluorescence to co-map metabolic activities and cell types within the same tissue section. REDCAT achieves subcellular resolution profiling of protein, lipid, redox, and nuclear acid metabolism, together with extracellular matrix composition, in both FFPE and fresh-frozen human tissues. Applied to normal lymph nodes, REDCAT delineated distinct redox and lipid remodeling programs across germinal center B-cell zones and immune subsets, highlighting cell-type-specific metabolic specialization. In lymphoma, it revealed profound metabolic reprogramming, including extensive lipid accumulation, nuclear metabolic heterogeneity, and a transitional metabolic state associated with transformation from chronic lymphocytic leukemia to diffuse large B-cell lymphoma, thereby illuminating tumor evolution in situ. In human liver, REDCAT resolved cell-type-specific lipid droplet diversity and zonation-dependent nuclear metabolic gradients, uncovering new principles of spatial metabolic organization. By directly linking cell identity with spatial metabolic states at single-cell or subcellular resolution, REDCAT establishes a broadly applicable framework for studying immune function, tumor progression, and tissue physiology, and offers a new path to deciphering the metabolic basis of health and disease.

cell biology↗
bioRxiv2024

DNA replication fork speed Acts as an Engine in Cortical Neurogenesis

DNA replication fork speed, which controls the rate of genome duplication, has emerged as a key regulator of cellular plasticity. However, its role in neurogenesis remains unexplored. Mini-chromosome maintenance complex (MCMs)-binding protein (MCMBP) functions as a chaperone for newly synthesized MCMs, increasing chromatin coverage to restrain fork speed. We demonstrate that selective deletion of MCMBP in neural progenitor radial glial cells (RGCs) accelerates fork speed, triggering widespread apoptosis, DNA damage, and micronuclei formation, ultimately activating p53 and causing microcephaly. Unexpectedly, concurrent deletion of Trp53 and Mcmbp further increased fork speed, leading to extensive RGC detachment from the ventricular zone and acquisition of outer-RGC characteristics. Mechanistically, we found that the MCM3 subunit coordinates DNA and centrosome duplication, thereby mediating RGC attachment. Behavioral analysis revealed that disruption of fork speed results in anxiety-like behavior in mice. These findings unveil a previously unrecognized role for replication fork speed in neurogenesis.

neuroscience↗
bioRxiv2024

Label-Free Optical Biopsy Reveals Biomolecular and Morphological Features of Diabetic Kidney Tissue in 2D and 3D

Kidney disease, the ninth leading cause of death in the United States, has one of the poorest diagnostic efficiencies of only 10%1. Conventional diagnostic methods often rely on light microscopy analysis of 2D fixed tissue sections with limited molecular insight compared to omics studies. Targeting multiple features in a biopsy using molecular or chemical reagents can enhance molecular phenotyping but are limited by overlap of their spatial and chromatic properties, variations in quality of the products, limited multimodal nature and need additional tissue processing. To overcome these limitations and increase the breadth of molecular information available from tissue without an impact on routine diagnostic workup, we implemented label-free imaging modalities including stimulated Raman scattering (SRS) microscopy, second harmonic generation (SHG), and two photon fluorescence (TPF) into a single microscopy setup. We visualized and identified morphological, structural, lipidomic, and metabolic biomarkers of control and diabetic human kidney biopsy samples in 2D and 3D at a subcellular resolution. The label-free biomarkers, including collagen fiber morphology, mesangial-glomerular fractional volume, lipid saturation, redox status, and relative lipid and protein concentrations in the form of Stimulated Raman Histology (SRH), illustrate distinct features in kidney disease tissues not previously appreciated. The same tissue section can be used for routine diagnostic work up thus enhancing the power of cliniopathological insights obtainable without compromising already limited tissue. The additional multimodal biomarkers and metrics are broadly applicable and deepen our understanding of the progression of kidney diseases by integrating lipidomic, fibrotic, and metabolic data. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=125 SRC="FIGDIR/small/620507v1_ufig1.gif" ALT="Figure 1"> View larger version (76K): org.highwire.dtl.DTLVardef@116edb1org.highwire.dtl.DTLVardef@4f010corg.highwire.dtl.DTLVardef@cde718org.highwire.dtl.DTLVardef@1ff0841_HPS_FORMAT_FIGEXP M_FIG O_FLOATNOGraphical AbstractC_FLOATNO Label-free indicators of diabetic nephropathies. C_FIG

bioengineering↗
bioRxiv2024

Dissecting the Contribution of Transposable Elements to Interphase Chromosome Structure

Transposable elements (TEs) occupy nearly half of the human genome and play diverse biological roles. Despite their abundance, the extent to which TEs contribute to three-dimensional (3D) genome structure remains unclear. To investigate this, we developed te_hic, a computational pipeline that integrates genomic data with chromatin interactions. Our analysis reveals that TE sequences are responsible for 3D genome structure in interphase nuclei. This phenomenon is mediated by the recruitment of specific transcription factors to TEs, which enables both the formation and disruption of chromatin contacts. We computationally identified known contact-forming proteins (CTCF, RAD21, SMC3) and breaking proteins (RNF2), as well as novel candidate contact-formers (SMARCA4, MAFK). Knockdown of the predicted contact-formers SMARCA4 and MAFK decreased contacts and loops at and between TEs. Notably, SMARCA4 knockdown selectively reduced short-range contacts, highlighting its role in maintaining 3D genome structure mediated by TE binding. Overall, our findings demonstrate that TEs are crucial determinants of 3D genome organization in mammalian cells. Key findingsO_LITEs determine 48% of the 3D genome structure alone, and 70% of heterotypic contacts. C_LIO_LIA/B compartments, TADs, and loop signatures can be retrieved using TE-mapped reads only. C_LIO_LITFs can be divided into contact formers and breakers at TEs. C_LIO_LISMARCA4 and MAFK build chromatin contacts between TE sequences. C_LI

cell biology↗
bioRxiv2024

Superimposed inhibitory surrounds underlying Saliency-based Stimulus Selection in avian Midbrain isthmi pars magnocellularis

In the avian midbrain network, bottom-up spatial attention is directed by saliency-based stimulus selection. However, it remains unclear whether the isthmi pars magnocellularis (Imc), the first site in the midbrain network to represent stimulus selection, can represent stimulus salience and what is the mechanism by which the midbrain network computes salience. Here, we used two separate translational motion stimuli as the main stimulation protocols and conducted in vivo electrophysiological experiments in the pigeons Imc. By combining bio-plausible model validation, we found two types of inhibitory surrounds of the Imc neuron receptive field, homogenous inhibitory surrounds (HIS) and non-homogenous inhibitory surrounds (non-HIS), and elucidated the mechanism by which both arise. While HIS is local and depends on stimulus feature similarity, which can be used to compute stimulus saliency, non-HIS is global and doesnt depend on stimulus feature similarity, which can be used to compute stimulus selection. Moreover, the superimposition of HIS and non-HIS modulates the neural response of Imc. The two inhibitory surrounds of Imc identified in this study more clearly elucidate the full process of achieving bottom-up stimulus selection based on saliency in the midbrain network and show that Imc is a nucleus that can represent both stimulus saliency and stimulus selection.

neuroscience↗