Biology subjects

Shen, H.

Publications and source records attributed to Shen, H..

At least 55 records · Page 3Linked to original sources

bioRxiv2025

JIP4 deficiency causes a novel lysosome storage disease arising from impaired cystine efflux

Lysosomes break down macromolecules, clear cellular waste and recycle nutrients such as cystine. We describe a novel mechanism whereby JIP4 regulates lysosomal cystine storage by controlling the abundance of cystinosin (CTNS), the transporter responsible for lysosomal cystine efflux. To this end, JIP4, previously characterized as a motor adaptor and kinase signaling scaffold, suppresses TMEM55B-dependent ubiquitylation of CTNS. Loss of JIP4 reduces CTNS protein levels, leading to lysosomal cystine accumulation and lysosomal storage defects that phenocopy loss of CTNS in both human cells and the renal proximal tubules of JIP4 knockout mice. These phenotypes mirror cystinosis, the lysosomal storage disease caused by CTNS loss-of-function. Our findings thus reveal a fundamental process that controls the efflux of lysosomal cystine and has relevance to understanding human disease arising from JIP4 mutations.

cell biology↗

bioRxiv2025

Synthbar: A Lightweight Tool for Adding Synthetic Barcodes to Sequencing Reads

Preparation of single-cell sequencing libraries includes adding nucleotide barcodes to assist with pooling samples or cells together for sequencing. The popularity of droplet-based single-cell protocols has spurred the development of computational tools that expect the read structure of the assay to include a cell barcode (CB). Microwell plate-based protocols, such as the Switching Mechanism At the 5 end of the RNA Transcript (SMART) single-cell RNA sequencing (scRNA-seq) family of methods, typically do not add a CB as part of the library preparation method as there is typically one cell per well and standard unique dual indices are sufficient for multiplexing. While several tools exist to manipulate and parse varying single-cell read structures, no tool is currently available to easily add synthetic CBs to enable use of computational tooling that expects the presence of a CB, such as STARsolo, zUMIs, and Alevin. Synthbar fills this gap as a lightweight tool that is assay agnostic, can add user-defined CBs, and modify read structures. Availability and ImplementationSource code and binaries are freely available at https://github.com/jamorrison/synthbar under the MIT license. Synthbar is implemented in C and is supported on macOS and Linux. Supplementary informationSupplementary data are available at the end of the document.

bioinformatics↗

bioRxiv2025

Fine-Resolution Asymmetric Migration Estimation

The genetic structure of populations is often shaped by processes and events that introduce asymmetries to gene flow between geographic locations. Here, we first develop an algorithm that allows efficient computation of pairwise coalescent times in time-homogeneous models of population structure at migration-drift equilibrium. We then use the algorithm as the foundation for a new method to infer asymmetric migration rates in spatial models of population structure. The inferred equilibrium migration rates provide a novel representation of the geographic structure of genetic variation. We assess the method using a variety of simulated histories of gene flow, and apply the method to datasets from poplar trees, North American gray wolves, and human archaeogenetic samples, revealing complex asymmetric migration signals and providing a more refined view of the geographic structure of genetic variation.

genetics↗

bioRxiv2025

Plastic-elastomer heterostructure for robust flexible brain-computer interfaces

Electronics for neural signal recording must be robust across multiple and deep brain regions while preserving tissue-level flexibility to ensure stable tracking over months or years. However, existing electronics cannot simultaneously achieve robustness and tissue-level flexibility, limiting their potential for customizable and scalable neuroscience research and clinical applications. Here, we introduce FlexiSoft, an electronic platform based on a plastic-elastomer heterostructure that uniquely integrates mechanical robustness and tissue-level flexibility. Compared to conventional flexible electronics of similar thickness, the FlexiSoft platform demonstrates an order-of- magnitude improvement in both mechanical robustness (critical energy release rate) and flexibility (flexural rigidity). Leveraging these mechanical advantages, we developed FlexiSoft probe for robust implantation, demonstrated by its ability to withstand repeated insertion and removal, as well as to reach centimeter-scale depths comparable to those in the human brain. The platform enables long-term recording from the same neurons across the hippocampus (HPC) and primary motor cortex (M1) during a months-long motor learning task, thereby revealing long-term dynamic changes in neuronal firing patterns. Additionally, FlexiSofts unique robustness and flexibility enable curved implantation routes, opening new directions of customizable implantation pathways. In summary, we present FlexiSoft as a novel, robust, and tissue-level flexible heterostructure electronics platform that advances flexible brain-computer interfaces (BCIs) with strong translational potential for neuroscience and clinical applications.

bioengineering↗

bioRxiv2025

Single-Cell eQTL Mapping Reveals Cell Type-Specific Genetic Regulation in Lung Cancer

Genome-wide association studies (GWAS) have identified over 50 lung cancer risk loci; however, the precise cellular context of these genetic mechanisms remains unclear due to limitations in bulk tissue eQTL analyses. Here, we present the largest single-cell eQTL atlas of human lung tissue to date, profiling 222 donors using multiplexed scRNA-seq. We identified 16,785 eQTLs across 17 cell types, with over 90% of sc-eQTLs and 59% eGene being cell-type-specific, and fewer than 23% were detectable in paired bulk datasets. Integration with GWAS for non-small cell lung cancer highlighted epithelial and immune cells as key contributors to genetic susceptibility, identifying 28 candidate genes within known risk loci and 24 in novel regions. Notably, 47% of established NSCLC susceptibility loci exhibited cell-type-specific pleiotropic genetic regulation. This study provides a valuable resource of lung sc-eQTLs and illuminates how genetic variation modulates gene expression in a cell-type-specific fashion, contributing to lung cancer susceptibility.

genetics↗

bioRxiv2025

Mapping cellular targets of covalent cancer drugs in the entire mammalian body

As our understanding of biological systems reaches single-cell and high spatial resolutions, it becomes imperative that pharmacological approaches match this precision to understand drug actions. This need is particularly urgent for the targeted covalent inhibitors that are currently re-entering the stage for cancer treatments. By leveraging the unique kinetics of click reactions, we developed volumetric clearing-assisted tissue click chemistry (vCATCH) to enable deep and homogeneous click labeling across the 3D mammalian body. With simple and passive incubation steps, vCATCH offers cellular resolution drug imaging in the entire adult mouse. We combined vCATCH with HYBRiD imaging and virtual reality to visualize and quantify in vivo targets of two clinical cancer drugs, afatinib and ibrutinib, which recapitulated their known pharmacological distribution and revealed previously unreported tissue and cell type engagement potentially linked to off-target effects. vCATCH provides a body-wide, unbiased platform to map covalent drug engagements at unprecedented scale and precision.

pharmacology and toxicology↗

bioRxiv2025

De novo design of inducibly assembling multi-component filaments

The design of multi-component nanomaterials is an outstanding challenge. Here, we describe the computational design of protein filaments with two or three distinct structural components that assemble into micron-scale, well-ordered fibers when mixed. CryoEM structure determination of four fiber designs was close to the computational design models. Filament assembly can be initiated by mixing the components, and modulated by addition and/or phosphorylation of designed regulatory subunits. This work demonstrates that regulatable multi-component protein filament systems can now be designed, opening the door to a wide range of engineered materials.

bioengineering↗

bioRxiv2025

Ultradeep N-glycoproteome Atlas of Mouse Reveals Spatiotemporal Signatures of Brain Aging and Neurodegenerative Diseases

The current depth of site-specific N-glycoproteomics is insufficient to fully characterize glycosylation events in biological samples. Herein, we achieved an ultradeep and precision analysis of the N-glycoproteome of mouse tissues by integrating multiple workflows. The largest N-glycoproteomic dataset to date was established on mice, which contained 91,972 precursor glycopeptides, 62,216 glycoforms, 8,939 glycosites and 4,563 glycoproteins. The database consisted of 6.8 million glyco-spectra (containing oxonium ions), among which 160,928 were high-quality spectra with confident N-glycopeptide identifications. The large-scale and high-quality dataset enhanced the performance of current artificial intelligence models for glycopeptide tandem spectrum prediction. Using this ultradeep dataset, we observed tissue specific microheterogeneity and functional implications of protein glycosylation in mice. Furthermore, the region-resolved brain N-glycoproteomes for Alzheimers Diseases, Parkinson Disease and aging mice revealed the spatiotemporal signatures and distinct pathological functions of the N-glycoproteins. A comprehensive database resource of experimental N-glycoproteomic data from this study and previous literatures were further established. This N-glycoproteome atlas serves as a promising tool for revealing the role of protein glycosylation in biological systems.

neuroscience↗

bioRxiv2024

Structural basis of phosphate export by human XPR1

Phosphate is essential for all life forms because of its indispensable roles in energy metabolism, nucleic acid and phospholipid synthesis, cellular signaling, and the formation of bones and teeth. Its homeostasis is maintained through balanced import and export processes. In humans, XPR1 has been proposed as the sole phosphate exporter, although some controversy remains. Here, we report the closed and open structures of human XPR1, purified in the absence and presence of exogenous InsP6, respectively. The exporter forms a symmetric homodimer, with transmembrane helix (TM) 1 serving as the dimeric interface. The transmembrane domain of each protomer contains a transport module (TM5-10) and a supporting module (TM1-4). Compared to the closed XPR1, the open structure demonstrates a significant displacement of the extracellular portion of TM9 towards the periphery of the phosphate transport pathway, creating an open portal to the extracellular milieu. Additionally, a potential phosphate ion coordination site is strategically located in the middle of the transport pathway. On the intracellular side, the pathway entrance is obstructed by a cluster of residues, the C-plug, positioned on the carboxyl side of TM10. Consistently, the removal of the C-terminus significantly increases the transport activity of XPR1 in reconstituted liposomes. Our findings provide a comprehensive understanding of the export mechanism of human XPR1 and hold promise for the development of potential therapeutics for primary familial brain calcification and ovarian cancer.

biochemistry↗

bioRxiv2024

AtKC1 inhibits AtAKT1 activation via its amino-terminal inhibitory domain

AKT1 is a plant Shaker-like, hyperpolarization-activated K+ channel which plays a crucial role in K+ absorption. Besides phosphorylation, AKT1 is subject to negative regulation by AtKC1, a silent channel of the same family. Previous structural studies unveiled that AKT1 and AtKC1 form 2:2 heterotetramer in purified samples. However, the structural analysis failed to offer more insight into the inhibition mechanism of AKT1 activation by AtKC1. Here, inspecting the complex structure of AKT1-AtKC1 reveals that a stable domain of AtKC1 (residues 53 to 80), named inhibitory domain or I-domain, may inhibit AKT1 activation by stabilizing its depolarized, closed conformation. We confirmed this hypothesis with electrophysiological experiments. Interestingly, a single-point mutation (G315D) in AtKC1 has been reported to abolish its ability to inhibit AKT1. We solved the structure of AKT1-AtKC1(G315D) at a resolution of 2.8 [A] which revealed an unexpected stoichiometry alteration between AKT1 and AtKC1 from 2:2 to 3:1. This stoichiometry change further supports the hypothesis as we reason that single I-domain of AtKC1 in the channel complex is insufficient to effectively inhibit channel activation. Our findings reveal the inhibition mechanism of AtKC1 on AKT1 and offer insight into the regulatory mechanisms of hyperpolarization-activated channels.

biochemistry↗

bioRxiv2024

Macrophage migration-dependent retraction fibers and migrasomes - a structural basis for spatiotemporal cytokine secretion.

Migrating cells leave behind trails of matrix-bound retraction fibers and migrasomes, but their cell-specific physiological functions are largely unknown. We comprehensively characterize retraction fibers and migrasomes of migrating macrophages in mouse and zebrafish in vitro and in vivo models. These structures share common and macrophage-centric components of tetraspanin enriched microdomains (TEMs) including tetraspanin 4 (TSPAN4), the integrin CD11b and the pTRAP, SCIMP; like TSPAN4, we show that SCIMP expression modulates retraction fiber and migrasome formation. In immune-activated migrating macrophages, rear-positioned recycling endosomes regulate the secretory trafficking of newly synthesized inflammatory cytokines into retraction fibers and migrasomes. Transmembrane TNF is delivered via SNARE-mediated carriers to the cell surface and to the surfaces of both retraction fibers and migrasomes, from where it can be released. Retraction fibers are thus newly identified here as cytokine secretion sites, and along with migrasomes they allow migrating macrophages to secrete more cytokine compared to stationary cells. Whereas cytokine secretion has been viewed as a process of ad hoc diffusion, instead, we reveal a new mechanism of migration-dependent, localized deposition and spatiotemporal release of bioactive cytokines from RFs and migrasomes. Cytokine deployment is thus organized in a constrained manner facilitating direct influence on local inflammatory responses.

cell biology↗

bioRxiv2024

Dietary Restriction Enhances CD8+ T Cell Ketolysis to Limit Exhaustion and Boost Anti-Tumor Immunity

Reducing calorie intake without malnutrition limits tumor progression but the underlying mechanisms are poorly understood. Here we show that dietary restriction (DR) suppresses tumor growth by enhancing CD8+ T cell-mediated anti-tumor immunity. DR reshapes CD8+ T cell differentiation within the tumor microenvironment (TME), promoting the development of effector T cell subsets while limiting the accumulation of exhausted T (Tex) cells, and synergizes with anti-PD1 immunotherapy to restrict tumor growth. Mechanistically, DR enhances CD8+ T cell metabolic fitness through increased ketone body oxidation (ketolysis), which boosts mitochondrial membrane potential and fuels tricarboxylic acid (TCA) cycle-dependent pathways essential for T cell function. T cells deficient for ketolysis exhibit reduced mitochondrial function, increased exhaustion, and fail to control tumor growth under DR conditions. Our findings reveal a critical role for the immune system in mediating the anti-tumor effects of DR, highlighting nutritional modulation of CD8+ T cell fate in the TME as a critical determinant of anti-tumor immunity.

immunology↗

bioRxiv2024

A comprehensive foundation model for cryo-EM image processing

Cryogenic electron microscopy (cryo-EM) has become a premier technique for high-resolution structural determination of biological macromolecules1-4. However, its widespread adoption is hampered by the need for specialized expertise. We introduce the Cryo-EM Image Evaluation Foundation (Cryo-IEF) model, pre-trained on an extensive dataset of approximately 65 million cryo-EM particle images using unsupervised learning. Cryo-IEF excels in various cryo-EM data processing tasks, such as classifying particles from different structures, clustering particles by pose, and assessing the quality of particle images. Upon fine-tuning, the model effectively ranks particle images by quality at high efficiency, enabling the creation of CryoWizard--a fully automated single-particle cryo-EM data processing pipeline. This pipeline has successfully resolved high-resolution structures of diverse properties and proven adept at mitigating the prevalent preferred orientation challenge in many cryo-EM samples. The Cryo-IEF model and CryoWizard pipeline collectively represent a significant advancement in rendering cryo-EM technology more accessible, efficient, and robust, with substantial implications for life sciences research.

bioinformatics↗

bioRxiv2024

High-throughput, multiplexed quantification, and sorting of single EVs at single-molecule level

We have developed a platform for the high-throughput, multiplexed, and ultra-sensitive profiling of individual extracellular vesicles (EVs) directly in plasma, which we call BDEVS - Agarose Bead-based Digital Single Molecule-Single EV Sorting. Unlike conventional approaches, BDEVS achieves single molecule sensitivity and moderate multiplexing (demonstrated 3-plex) without sacrificing the throughput (processing ten thousand of EVs per minute) necessary to resolve EVs directly in human plasma. Our platform integrates rolling circle amplification (RCA) of EV surface proteins, which are cleaved from single EVs, and amplified within agarose droplets, followed by flow cytometry-based readout and sorting, overcoming steric hindrance, non-specific binding, and the lack of quantitation of multiple proteins on EVs that have plagued earlier approaches. We evaluated the analytical capabilities of BDEVS through head-to-head comparison with gold-standard technologies, and demonstrated a [~]100x improvement in the limit of detection of EV subpopulations. We demonstrate the high throughput ([~]100k beads / minute) profiling of individual EVs for key immune markers PD-L1, CD155, and the melanoma tumor marker TYRP-1, and showed that BDEVS can precisely quantify and sort EVs, offering unprecedented resolution for analyzing tumor-immune interactions and detecting rare EV subpopulations in complex clinical specimens. We demonstrate BDEVSs potential as a transformative tool for EV-based diagnostics and therapeutic monitoring in the context of cancer immunology by analyzing plasma samples from patients with melanoma, where EV heterogeneity plays a critical role in disease progression and response to therapy. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=93 SRC="FIGDIR/small/621423v1_ufig1.gif" ALT="Figure 1"> View larger version (37K): org.highwire.dtl.DTLVardef@1a8a542org.highwire.dtl.DTLVardef@f9b9f0org.highwire.dtl.DTLVardef@11e4758org.highwire.dtl.DTLVardef@de1645_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioengineering↗

bioRxiv2024

High-coverage allele-resolved single-cell DNA methylation profiling by scDEEP-mC reveals cell lineage, X-inactivation state, and replication dynamics

DNA methylation is a relatively stable epigenetic mark with important roles in development and disease.1 Since cell-to-cell variation in epigenetic programming can reflect important differences in cell state and fate, it is clear that single-cell methods are essential to understanding this key epigenetic mark in heterogeneous tissues. Existing single-cell whole-genome bisulfite sequencing (scWGBS) methods2 have significant shortcomings, including very low CpG coverage3-7 or inefficient library generation requiring extremely deep sequencing.8 These methods offer limited insight into focal regulatory regions and generally preclude direct cell-to-cell comparisons. To address these shortcomings, we have developed an improved method, scDEEP-mC (single-cell Deep and Efficient Epigenomic Profiling of methyl-C). We show that high-coverage promoter methylation profiling by scDEEP-mC can identify multiple cell types, while allele-resolved methylation calls allow assessment of X-inactivation state in single cells and identification of transcription factor binding sites (TFBS) enriched for hemi-methylation. We also use scDEEP-mC to profile single-cell copy number alterations, identify actively replicating cells, and track DNA methylation dynamics during and after DNA replication. The high coverage of scDEEP-mC creates an exceptional opportunity to explore DNA methylation biology in individual cells.

genomics↗

bioRxiv2024

Multi-View Integrative Approach For Imputing Short-Chain Fatty Acids and Identifying Key factors predicting Blood SCFA

Short-chain fatty acids (SCFAs) are the main metabolites produced by bacterial fermentation of dietary fiber within gastrointestinal tract. SCFAs produced by gut microbiotas (GMs) are absorbed by host, reach bloodstream, and are distributed to different organs, thus influencing host physiology. However, due to the limited budget or the poor sensitivity of instruments, most studies on GMs have incomplete blood SCFA data, limiting our understanding of the metabolic processes within the host. To address this gap, we developed an innovative multi-task multi-view integrative approach (M2AE, Multi-task Multi-View Attentive Encoders), to impute blood SCFA levels using gut metagenomic sequencing (MGS) data, while taking into account the intricate interplay among the gut microbiome, dietary features, and host characteristics, as well as the nuanced nature of SCFA dynamics within the body. Here, each view represents a distinct type of data input (i.e., gut microbiome compositions, dietary features, or host characteristics). Our method jointly explores both view-specific representations and cross-view correlations for effective predictions of SCFAs. We applied M2AE to two in-house datasets, which both include MGS and blood SCFAs profiles, host characteristics, and dietary features from 964 subjects and 171 subjects, respectively. Results from both of two datasets demonstrated that M2AE outperforms traditional regression-based and neural-network based approaches in imputing blood SCFAs. Furthermore, a series of gut bacterial species (e.g., Bacteroides thetaiotaomicron and Clostridium asparagiforme), host characteristics (e.g., race, gender), as well as dietary features (e.g., intake of fruits, pickles) were shown to contribute greatly to imputation of blood SCFAs. These findings demonstrated that GMs, dietary features and host characteristics might contribute to the complex biological processes involved in blood SCFA productions. These might pave the way for a deeper and more nuanced comprehension of how these factors impact human health.

bioinformatics↗

bioRxiv2024

Nucleation limited assembly and polarized growth of a de novo-designed allosterically modulatable protein filament

The design of inducibly assembling protein nanomaterials is an outstanding challenge. Here, we describe the computational design of a protein filament formed from a monomeric subunit that binds a peptide ligand. The cryoEM structure of the micron-scale fibers is very close to the computational design model. The ligand acts as a tunable allosteric modulator: while not part of the fiber subunit-subunit interfaces, the assembly of the filament is dependent on ligand addition, with longer peptides having more extensive interaction surfaces with the monomer, promoting more rapid growth. Seeded growth and capping experiments reveal that the filaments grow primarily from one end. We show that designed nucleators that present 12 copies of the peptide ligand promote fiber assembly at concentrations where otherwise assembly occurs very slowly, likely by generating critical local concentrations of monomer in the assembly competent conformation. Following filament assembly, the peptide ligand can be exchanged with free peptide in solution fused to any functional protein of interest, opening the door to a wide variety of tunable engineered materials.

bioengineering↗

bioRxiv2024

Random Sanitization in DNA information storage using CRISPR-Cas12a

DNA information storage provides an excellent solution for metadata storage due to its high density, programmability, and long-term stability. However, current research in DNA storage primarily focuses on the processes of storing and reading data, lacking comprehensive solutions for the secure metadata wiping. Herein, we present a method of random sanitization in DNA information storage using CRISPR-Cas12a (RSDISC) based on precise control of the thermodynamic energy of primer-template hybridization. We utilize the collateral cleavage (trans-activity) of single-stranded DNA (ssDNA) by CRISPR-Cas12a to achieve selective sanitization of files in metadata. This method enables ssDNA degradation with different GC content, lengths, and secondary structures to achieve a sanitization efficiency up to 99.9% for 28,258 oligonucleotides in DNA storage within one round. We demonstrate that the number of erasable files could reach 1011.7 based on a model of primer-template hybridization efficiency. Overall, RSDISC provides a random sanitization approach to set the foundation of information encryption, file classification, memory deallocation and accurate reading in DNA data storage.

synthetic biology↗