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Biology subjects

Zhu, S.

Publications and source records attributed to Zhu, S..

At least 55 records · Page 3Linked to original sources

A Common PD-Risk GBA1 Variant Disrupts LIMP2 Interaction, Impairs Glucocerebrosidase Function, and Drives Lysosomal and Mitochondrial Dysfunction

Variants in GBA1 cause Gaucher disease (GD), a lysosomal storage disorder, and represent the most common genetic risk factor for Parkinsons disease (PD). While some GBA1 variants are associated with both GD and PD, several coding mutations, including E326K, specifically confer risk for developing PD. It is established that GD-linked variants in {beta}-glucocerebrosidase (GCase), the enzyme encoded by GBA1, are loss-of-function, but it remains unclear whether variants solely associated with PD similarly reduce GCase activity. The mechanisms by which some of these variants impact GCase activity and PD-associated pathways, including lysosomal and mitochondrial function, are also poorly defined. Here, we show that the PD-linked E326K variant significantly reduces lysosomal GCase activity by impairing its delivery to lysosomes via altered interactions with its receptor, LIMP2. Biophysical and structural characterization of this variant, both alone and in complex with LIMP2, reveals a dimeric organization that appears to result from the loss of a key salt bridge between E326 and R329. Restoration of this salt bridge through the introduction of a negatively charged side chain at position 329 promotes monomeric organization and interaction with LIMP2 in cells. GBA1-p.E326K cell models show greater deficits in PD-linked pathways compared to more severe loss of GCase function, including secondary lysosomal lipid storage and mitochondrial dysfunction. We confirm the E326K variant impacts GCase pathway activity in relevant CNS cell types, including iPSC-derived microglia, and in biofluids from heterozygous GBA1-p.E326K variant carriers. Together, our data provide key insights into the nature of GCase dysfunction in GBA1-PD and can inform the development of GCase-targeted therapeutic strategies to treat PD.

cell biology↗

Spen and Nito prevent dedifferentiation of progenitors by translationally repressing E(Spl)mγ

Rapid termination of Notch signaling by asymmetrically segregated Numb is essential for specification of differentiating progeny during asymmetric stem cell division. Using Drosophila type II neuroblasts as a model, here we report that specification of the differentiating progeny also requires the expression of the Notch target E(Spl)m{gamma} in the stem cell to be kept at low levels by the SPEN family proteins, Spen and Nito. We show that loss of Spen or Nito leads to a drastic increase in E(Spl)m{gamma} expression in the stem cell and subsequent dedifferentiation of its progeny. Genetic and biochemical studies demonstrate that Spen and Nito maintain the expression of E(Spl)m{gamma} in the stem cell at low levels by directly binding to two identical novel motifs in the 5UTR to repress its translation. The low expression in the stem cell prevents excessive inheritance of E(Spl)m{gamma} proteins by the differentiating progeny and ensures its rapid removal from the progeny. Together, our work uncovers a novel post-transcriptional mechanism regulating Notch signaling that is critical for cell fate specification during asymmetric stem cell division.

developmental biology↗

Type 1 Regulatory T cells induced by intestinal epithelial cells respond to food antigen

As the first-line barrier against food antigens, the intestinal epitheliums role in establishing peripheral immune tolerance to food remains completely unknown. Additionally, the specific types of regulatory T cells induced to maintain food tolerance--along with their antigen specificity--are still unclear. Here we found small intestinal FOXP3-IL-10+ Tr1 cells, but not Treg cells, can respond to food antigens presented by intestinal epithelial cells (IECs) in an antigen-specific manner. Through immunopeptidome analysis of MHCII-presented peptides, we demonstrate that IECs can present food-derived antigens. Importantly, these IEC-presented food antigens are exclusively recognized by the TCR repertoire of small intestinal Tr1 cells, not Treg cells. Furthermore, we show that T cells recognizing IEC-presented food antigens specifically differentiate into Tr1 cells in the siLP. These findings establish two key insights: first, that maintaining food tolerance represents a physiological function of Tr1 cells, and second, that IECs play a central role in maintaining food tolerance. Our work thus provides mechanistic understanding of how the intestinal epithelium contributes to immune tolerance through its antigen presentation capacity and subsequent Tr1 cell induction.

immunology↗

An atlas of cell type specific regulatory effects in cattle

Understanding the genetic and molecular architecture of complex traits and artificial selection is crucial for advancing sustainable precision breeding in cattle and other livestock. Yet, how genetic variation affects cellular gene expression remains elusive in cattle. Here, by integrating 8,866 bulk RNA-seq samples and 999,192 single cells of 81 cell types in 22 bovine tissues, we presented a comprehensive atlas of regulatory variants at the cell type resolution in cattle. By colocalizing with bulk-tissue expression quantitative trait loci (beQTL), we detected 57,043 novel cell-type stratified eQTL and cell-type/state interaction eQTL in 18,153 genes, which also exhibited a stronger tissue/cell-type specificity than beQTL. By examining genome-wide associations (GWAS) of 44 complex traits, these cell-resolved eQTL were colocalized with 505 (24%) additional GWAS loci compared to beQTL. Through integrating this resource with selection signatures between dairy and beef cattle, we provided tissue/cell-specific regulatory insights into cattle breeding. Overall, the current atlas of cell-type-specific regulatory variants will serve as an invaluable resource for cattle genomics and selective breeding.

genetics↗

Improving Cellular Senescence Detection with Weak Gene Markers in Single-Cell RNA-seq vi Iterative Imputation

BackgroundCellular senescence represents a stable cell cycle arrest state that plays critical roles in tissue aging and age-related pathologies. Although single-cell RNA sequencing (scRNA-seq) enables comprehensive profiling of millions of cells in aged tissues, reliably identifying senescent cells remains challenging due to the weak and non-specific expression of their marker genes. Existing computational methods can detect active cell states through gene set scoring, but their performance for senescence genes has not been rigorously evaluated. ResultsIn this study, we show that senescence genes display weak, non-specific expression patterns across different tissues and are susceptible to dropout events in scRNA-seq. Current scoring approaches suffer intrinsic limitations in single-cell detection using weakly expressed markers. Simply expanding the gene set of weak markers failed to improve detection accuracy. To overcome these limitations, we developed ICE (Imputation-based Cell Enrichment), a computational framework that combines expression imputation with iterative marker refinement. ICE substantially improved detection precision in pancreatic cells with weakly expressed markers, increasing it from 56% to 98%. Using consensus markers, ICE identified senescent fibro-adipogenic progenitors (FAPs) in muscle tissue, characterized by elevated expression of senescence-associated secretory phenotype (SASP) genes. When applied to individual senescence markers (CDKN1A/p21, CDKN2A/p16, ATF3, and MX1), ICE successfully identified marker-specific cell populations. These included stressed {beta} cells in aging and type-I interferon-responsive microglia in Alzheimers disease (AD). ConclusionsOur study introduces ICE, a rigorous framework for detecting cell states defined by weakly expressed markers at the single-cell level. This tool enables the reliable identification of senescence-associated populations, facilitating a deeper characterization of their heterogeneity and temporal dynamics across diverse human tissues and disease contexts.

genomics↗

METTL3 regulates exocytosis independently of m6A

RNA modification pathways are often mis-regulated in various cancers, with N6-methyladenosine (m6A) having a pivotal role in cancer progression and metastasis. Methyltransferase-like 3 (METTL3), a core component of the m6A methyltransferase complex, functions not only as an m6A writer but also promotes tumorigenesis through m6A-independent mechanisms. Here, we show that METTL3 is mislocalized to the cytoplasm in breast cancer tumors from patients, contributing to the oncogenic phenotype. Cytoplasmic METTL3 interacts with EXOC7, a key regulator of exocytosis, promoting its stabilization. Additionally, METTL3 regulates m6A-dependent alternative splicing of EXOC7. Silencing METTL3 impairs vesicle trafficking and the breast cancer secretome - effects that do not rely on its enzymatic activity but instead involve METTL3-mediated stabilization of EXOC7 and potentially other exocyst components. Furthermore, METTL3 knockdown impairs invadopodia formation, collagen matrix invasion, and focal adhesion morphology in vitro, while inhibition of METTL3 catalytic activity does not. Our findings uncover non-catalytic roles of METTL3 in regulating exocytosis and the cancer secretome.

molecular biology↗

High-resolution laminar recordings reveal structure-function relationships in monkey V1

The relationship between structural properties of diverse neuronal populations in monkey primary visual cortex (V1) and their in vivo functional responses is not fully understood. We combined high-density Neuropixels recordings across cortical layers of macaque V1 with non-linear dimensionality reduction on waveform shape to delineate nine putative cell classes: 4 narrow-spiking (NS), 4 broad-spiking (BS) and 1 tri-phasic (TP). Using targeted analyses of laminar organization, spike amplitude, multichannel waveforms, functional properties, and network connectivity of these cell classes, we demonstrate four aspects of the V1 microcircuit predicted by anatomical studies but never fully demonstrated in vivo. First, NS neurons were concentrated in layer 4. Second, a large-amplitude NS cell class in layer 4B showed strong direction selectivity. Third, another layer 4B NS class exhibited robust bursting and orientation selectivity. Finally, cross-correlation analysis revealed functional interactions between cells in different layers. Our results highlight how high-resolution electrophysiology can reveal novel relationships between in vivo function of neurons and the underlying circuit. TeaserHigh-resolution electrophysiology used with machine learning reveals links between function and the underlying neural circuitry.

neuroscience↗

High-Throughput Machine Learning-Aided Antibody Discovery for Cell Surface Antigens

Machine learning (ML) has the potential to revolutionize antibody design and selection, but its success depends on access to extensive, well-curated datasets of antibody-antigen interactions. To address this need, we developed a synthetic Fab yeast display library optimized for seamless ML integration, focusing on sequence diversity within the CDRH3 loop. The library incorporates key sequence features derived from human B cell repertoires essential for efficient antibody generation captured in a compact antigen recognition module (ARM) format. Built using the VH1-69 heavy chain and four light chains, the library was evaluated against ten human and murine cell surface antigens, including PD-L1, TIGIT, and ROBO1. This approach yielded hundreds of antibodies with robust biophysical properties, validated for functional performance in flow cytometry and immunohistochemistry. Furthermore, ML analysis identified additional antibodies for ROBO2 and PD-L2 from the aggregate sequencing data, demonstrating utility for hybrid in silico and experimental workflows. We provide a publicly accessible dataset comprising more than 68,000 Fab sequences and 486 characterized antibodies. This study establishes an ML-compatible framework designed to accelerate and streamline antibody discovery and development.

biophysics↗

MKFGO: Integrating Multi-Source Knowledge Fusion with Pre-Trained Language Model for High-Accuracy Protein Function Prediction

Accurately identifying protein functions is essential to understand life mechanisms and thus advance drug discovery. Although biochemical experiments are the gold standard for determining protein functions, they are often time-consuming and labor-intensive. Here, we proposed a novel composite deep-learning method, MKFGO, to infer Gene Ontology (GO) attributes through integrating five complementary pipelines built on multi-source biological data. MKFGO was rigorously benchmarked on 1522 non-redundant proteins, demonstrating superior performance over 11 state-of-the-art function prediction methods. Comprehensive data analyses revealed that the major advantage of MKFGO lies in its two deep-learning components, HFRGO and PLMGO, which derive handcraft features and protein large language model (PLM)-based features, respectively, from protein sequences in different biological views, with effective knowledge fusion at the decision-level. HFRGO leverages an LSTM-attention network embedded with handcraft features, in which the triplet loss-based guilt-by-association strategy is designed to enhance the correlation between feature similarity and function similarity. PLMGO employs the PLM to capture feature embeddings with discriminative functional patterns from sequences. Meanwhile, another three components provide complementary insights for further improving prediction accuracy, driven by protein-protein interaction, GO term probability, and protein-coding gene sequence, respectively. The source codes and models of MKFGO are freely available at https://github.com/yiheng-zhu/MKFGO.

bioinformatics↗

Root hair lifespan is antagonistically controlled by autophagy and programmed cell death

Root hairs are tubular tip-growing extensions of root epidermal cells that enhance root surface area for water and nutrient uptake. While mechanisms governing root hair fate, polarity, and tip growth are well understood, the regulation of root hair longevity remains largely unknown. Here, we show that root hair cells employ high levels of autophagy to promote their lifespan. Loss-of-function mutations in the autophagy regulators ATG2, ATG5, or ATG7 induce a premature, cell-autonomous cell death program. This cell death is activated via a gene regulatory network downstream of the NAC transcription factors ANAC046 and ANAC087. Our findings uncover an antagonistic relationship between autophagy and developmentally controlled cell death in root hair lifespan regulation, with potential implications for optimizing plant nutrient and water uptake in crop breeding. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=193 SRC="FIGDIR/small/643910v1_ufig1.gif" ALT="Figure 1"> View larger version (80K): org.highwire.dtl.DTLVardef@1bd570borg.highwire.dtl.DTLVardef@19db5eborg.highwire.dtl.DTLVardef@11279fborg.highwire.dtl.DTLVardef@661c7_HPS_FORMAT_FIGEXP M_FIG C_FIG

plant biology↗

The architecture, assembly, and evolution of a complex flagellar motor

Bacterial flagella drive motility in many species, likely including the last bacterial common ancestor 1,2. Knowledge of flagellar assembly and function has mainly come from studies of Escherichia coli and Salmonella enterica, which have simple flagellar motors 3-7. However, most flagellated bacteria possess complex motors with unique, species-specific adaptations whose mechanisms and evolution remain largely unexplored 8-10. Here, we deploy a multidisciplinary approach to build a near-complete model of the flagellar motor in Campylobacter jejuni, revealing its remarkable complexity in architecture and composition. We identify an E-ring around the MS-ring, a periplasmic cage with two distinctive conformations, and an intricate interaction network between the E-ring and cage. These scaffolds play critical roles in stabilizing and regulating 17 torque-generating stator complexes for optimal motility. In-depth evolutionary analyses uncover the ancient origin and prevalence of the E-ring in flagellated species of the domain Bacteria as well as a unique exaptation of type IV pili components PilMNOPQF in the ancestral motor of the phylum Campylobacterota. Collectively, our studies reveal novel mechanisms of assembly and function in complex flagellar motors and shed light on the evolution of flagella and modern bacterial species.

microbiology↗

Genomic tree scans identify loci underlying adaptive peaks in Antirrhinum

A key question in evolutionary biology is how barriers to gene flow operate and arise between populations, leading to speciation. Barriers are typically identified by comparing populations distinguished by phenotype, geographical location and/or environment. However, such prior classifications may bias recovery towards features obvious to the human eye, influencing mechanistic interpretations. Here we develop a method blind to prior classifications. We apply it to 18 Antirrhinum populations occupying habitats from coastal to alpine. By scanning the genome for regions with deeply rooted similar trees, we identify a single multi-locus partition, comprising less than 0.5% of the genome. It derives from eight genes, three newly identified here, which interact to generate complementary pollinator guides, likely corresponding to two adaptive peaks in a fitness landscape. Hybrid genotypes fall in a fitness valley, allowing the partition to be maintained through hybrid incompatibility and creating steep clines in allele frequency at a hybrid zone. Another partition derives from a single locus linked to a gene controlling plant height. The locus exhibits a shallow cline in allele frequency across an eco-geographic barrier and may be eco-adaptive. Our results suggest that two ancestral subspecies underwent extensive gene flow except at a few barrier loci, showing how both hybrid incompatibility and eco-adaptation can operate to maintain diversity.

evolutionary biology↗

SLICK: A Sandwich-LIke Culturing Kit for in situ Cryo-ET Sample Preparation

In situ cryo-electron tomography (cryo-ET) has recently been widely used in observing subcellular structures and macromolecules in their native states at high resolution. One of the reasons that it has not been more widely adopted by cell biologists and structural biologists is the difficulties in sample preparation. Here we present the Sandwich-LIke Culturing Kit (SLICK), simplifying the procedure and increasing the throughput for sample preparation for in situ cryo-ET (69 words).

biophysics↗

Systems Pharmacology Screening Reveals Mertk and other Targetable Kinases in Supratentorial Ependymomas

Ependymomas (EPN) are rare central nervous system tumors that account for approximately 10% of intracranial tumors in children and 4% in adults. Despite their clinical and molecular heterogeneity, spanning supratentorial, posterior fossa, and spinal subtypes, treatment remains limited to surgery and radiotherapy, with chemotherapy offering minimal benefit. Here, we performed transcriptomic analysis of 370 human ependymoma samples and identified two distinct molecular subgroups: EPN-E1 and EPN-E2. The EPN-E1 cluster is enriched for supratentorial tumors harboring ZFTA-RELA fusions (ZFTA-RELAfus), which occur in over 70% of cases and are associated with poor prognosis. To identify targeted therapies for this aggressive subtype, we validated a ZFTA-RELAfus mouse model that recapitulates the human EPN-E1 transcriptome and used it for target discovery. Through Kinome Regularization, a machine learning-driven polypharmacology approach, we identified MERTK as a critical regulator of tumor cell viability. Genetic depletion or pharmacologic inhibition of Mertk reduced cell growth ex vivo, and treatment with a clinical-grade MERTK inhibitor significantly suppressed tumor proliferation in vivo. Both human EPN-E1 tumors and ZFTA-RELAfus mouse tumors exhibited elevated expression of MERTK and its ligand GAS6, and MERTK inhibition led to suppression of pro-survival signaling pathways including MEK/ERK and PI3K/AKT. Notably, over 80% of genes upregulated in ZFTA-RELAfus tumors were downregulated following MERTK inhibition, indicating a strong dependency on this pathway for tumor maintenance. These findings define a signaling vulnerability in ZFTA-RELA-driven ependymomas and support the clinical development of MERTK-targeted therapies for patients with the high-risk EPN-E1 subtype.

cancer biology↗

Symmetry as a Fundamental Principle in Defining Gene Expression and Phenotypic Traits

Symmetry refers to properties that remain invariant upon mathematical transformations. The principles of symmetry have guided numerous important discoveries in physics and chemistry but not in biology and medicine. Here, we aim to explore the presence of symmetry relationships at the gene expression level as a mean to distinguish between healthy and disease states. We deployed Learning-Based Invariant Feature Engineering - LIFE, a hybrid machine learning approach implemented with two symmetric invariant feature functions (IFFs) to identify Invariant Feature Genes (IFGs), which are gene pairs whose IFF single-value outputs remain invariant across individual samples in a given biological phenotype. Our multiclass classification results across the transcriptomes of 25 normal organs, 25 cancer types, and blood samples obtained from 4 different types of neurodegenerative diseases revealed the presence of unique phenotype-specific IFGs. We constructed networks using these IFGs (IF-Nets) and intriguingly, we demonstrated that the hubs could serve as information encoders, capable of reconstructing sample-wise expression values in relation to their counterpart genes. More importantly, we found that hubs of cancer IF-Nets were enriched with both approved and clinical trial drugs, highlighting "symmetry breaking" as a novel approach for treating diseases.

systems biology↗

Effector-triggered processing body formation attenuates host translation via ER stress responses and autophagy upon bacterial infection

Pathogens employ sophisticated strategies to modulate host protein homeostasis by targeting proteolytic pathways, but their impact on protein synthesis remains elusive. We report that pathogenic bacteria Pseudomonas syringae (Pst) targets ribonucleoprotein condensates, known as processing bodies (P-bodies), to attenuate host translation through two effectors with liquid-like properties. We uncovered a previously unknown link that Pst-mediated repression of the ER stress response is required for P-body assembly. Furthermore, we identify a novel intersection between P-bodies and autophagy, demonstrating that autophagic clearance of P-bodies is crucial for maintaining the balance between translationally active and inactive mRNAs. Altogether, our discoveries provide novel insights on how host translation is attenuated by bacteria to dampen plant immunity and uncover unknown connections between ER stress responses and autophagy with P-body dynamics.

plant biology↗

A Palette of Bridged Bicycle-Strengthened Fluorophores

Organic fluorophores are the keystone of advanced biological imaging. The vast chemical space of fluorophores has been extensively explored in seek of molecules with ideal properties. However, within the current molecular constraints, there appears to be a trade-off between high brightness, robust photostability, and tunable biochemical properties. Herein we report a general strategy to systematically boost the performance of donor-acceptor-type fluorophores by leveraging SO2 and O-substituted azabicyclo[3.2.1] octane auxochromes. These bicyclic heterocycles give rise to a collection of Bridged dyes (BD) spanning the UV and visible range with top-notch quantum efficiencies, enhanced water solubility, and tunable cell-permeability. Notably, these azabicyclic fluorophores showed remarkable photostability than its tetramethyl or azatidine analogue, at the same time completely resistant to oxidative photobluing rendered by the Bredts rule. Functionalized BD dyes are tailored for applications in single-molecule imaging, super-resolution imaging (STED and SIM) in fixed or live mammalian cells and plant cells, and live zebrafish imaging or chemigenetic voltage imaging. Synergizing with advanced imaging methods, the bridge bicycle dyes represent a versatile palette for biological researches.

biophysics↗

Outer membrane tube formation by Francisella novicida involves extensive envelope modifications and is linked with type VI secretion and alterations to the host phagosomal membrane

Francisella tularensis is a Gram-negative, intracellular pathogen that causes the zoonotic disease tularemia. Due to its ease of dissemination and high lethality, F. tularensis is classified as a Tier 1 Select Agent with potential for misuse as a bioweapon. The mechanisms by which Francisella replicates intracellularly and interacts with the host during infection are not well understood. Francisella produces spherical outer membrane vesicles (OMV) and novel tubular extensions of its cell surface that are also released extracellularly. These OMV and outer membrane tubes (OMT) contain Francisella virulence factors and are produced in response to amino acid starvation and during infection of macrophages. To investigate how the OMT are formed, we used cryogenic electron tomography to examine the model Francisella species, F. novicida, during in vitro culture and within the macrophage phagosome. OMT formation involved progressive alterations of the bacterial envelope, resulting in extensions of both the inner and outer membranes. A dynamic cytoplasmic structure was present at the base of the OMT that extended into the tubes during elongation, together with cytoplasmic material. OMT produced within the macrophage phagosome were associated with changes to the phagosomal membrane, suggesting a role in phagosomal escape. Consistent with this, using confocal microscopy, we observed colocalization of the Francisella type VI secretion system with the OMT, both within bacteria and in released tubular vesicles. These findings reveal the cellular transformations that occur during membrane tubulation by Francisella and provide insights into the function of membrane-derived structures during host-pathogen interactions.

microbiology↗