Biology subjects

Guo, Z.

Publications and source records attributed to Guo, Z..

At least 91 records · Page 5Linked to original sources

bioRxiv2025

Induction of TFEB promotes Kupffer cell survival and reduces lipid accumulation and inflammation in MASLD

Kupffer cells (KCs) are the tissue-resident macrophage of the liver where they serve a critical role in maintaining liver tissue homeostasis and as a filter for circulation. The composition of liver macrophages changes during metabolic dysfunction-associated liver disease (MASLD), with the loss of resident KCs being a hallmark of disease progression. The mechanism(s) and consequences of KC death in metabolic liver disease have yet to be defined. Transcription factor EB (TFEB) is a master regulator of lysosome function and lipid metabolism which has been shown to protect macrophages from lipid stress in atherosclerosis. We hypothesized that TFEB would improve KC fitness in MASLD. To investigate this possibility, we created a transgenic mice in which TFEB was induced specifically in KCs. We found that TFEB induction protected KCs from cell death in two mouse models of MASLD. KC preservation through TFEB induction reduced liver steatosis via a mechanism that was dependent on macrophage lysosomal lipolysis and mitochondrial fatty acid oxidation. The protection from cell death in TFEB KCs was the result of reduced oxidative stress and ferroptosis through a mechanism that involved enhanced NADPH levels. Together, we provide evidence that TFEB promotes KC fitness during MASLD and orchestrates beneficial effects on liver pathology, thus providing potential targets to develop cell-specific therapeutics.

immunology↗

bioRxiv2025

Activation of complement protein C3 depicts the dynamic tissue damage of the cochlea after noise trauma.

Hearing loss is characterized by dysfunction and pathological changes of the cochlea, including the loss of sensory hair cells and connected synapses. Growing evidence has revealed that the immune system plays critical roles in shaping cochlear responses to tissue injury and the clearance of damaged cells under pathological conditions such as noise-induced hearing loss (NIHL). However, the underlying mechanisms that regulate this process remain unclear. As a crucial part of the innate immune system, the complement system is widely known to respond to tissue damage and help remove cellular debris. Such functions are yet to be fully explored in the auditory system, especially in the cochlea. Among various complement factors, the activation of complement protein C3 is an essential functional hub of the complement cascade, resulting in the phagocytosis of dead or dying cells. In this study, we sought to investigate whether C3 exists in the cochlea and what roles it might play upon noise injury. To test this, we studied C3 activation using immunohistochemistry in the cochleae of various mouse models that were noise exposed to an octave band noise (8-16 kHz) for two hours at 112 dB SPL. Mice were sacrificed at various post exposure times to examine cochlear pathology. We found damage dependent C3 activity in the organ of Corti in mice after noise exposure (NE), especially in damaged outer hair cell (OHC) area. Specifically, C3 opsonized damaged cellular structures include degenerating OHCs, OHC debris, ribbon synapses, and efferent synaptic boutons, and the temporal dynamics of the opsonization closely resemble the timing of cochlear tissue damages post exposure. Unexpectedly, C3-deficient mice exhibited similar ABR thresholds and OHC counts at baseline as wild type mice, as well as comparable ABR threshold shifts and OHC loss after NE. However, we observed significantly reduced MOC terminal bouton degeneration in C3-deficient mice upon 112 dB SPL noise injury, indicating that C3 does modulate tissue damage and clearance, at least at the MOC terminals. Our results suggest that complement C3 is dynamically activated in the cochlea upon noise injury, which may play significant roles in damage recognition and further immune recruitment during the development of NIHL.

neuroscience↗

bioRxiv2025

Dynamic Pathway of Guanidine-III Riboswitch Folding Revealed by Single-Molecule FRET: Mg2+-Assisted Preorganization and Ligand-Induced Kinetic Trapping

Riboswitches are structured RNA elements that regulate gene expression by sensing and binding small molecules. The guanidine-III riboswitch, a critical bacterial regulator responding to guanidine toxicity, undergoes precise conformational changes that remain poorly characterized at a dynamic, mechanistic level. In this study, we employed single-molecule Forster Resonance Energy Transfer (smFRET) coupled with molecular dynamics (MD) simulations to delineate how the guanidine-III riboswitch transitions among distinct conformational states. We identify three principal states [-] an extended (E-state), a compacted prefolded intermediate (P-state), and a folded pseudoknot structure (F-state) [-] with rapid interconversion in the absence of ligand. Magnesium ions significantly stabilize intermediate states via a cooperative, preorganization mechanism, enhancing ligand binding efficiency. Binding of guanidine drastically suppresses the reverse transitions, kinetically trapping the riboswitch into its active folded state primarily through a conformational selection mechanism, with additional contributions from induced-fit dynamics. This work illuminates the unique dynamic pathway by which the guanidine-III riboswitch integrates ionic and ligand cues, ensuring precise gene regulatory responses in bacteria.

biophysics↗

bioRxiv2025

Identification of Rapaglutin E as An Isoform-specific Inhibitor of Glucose Transporter 1

Natural products rapamycin and FK506 are macrocyclic compounds with therapeutic benefits whose unique scaffold inspired the generation and exploration of the hybrid macrocycle rapafucins. From this library, a potent inhibitor of the facilitative glucose transporter (GLUT), rapaglutin A (RgA) was previously identified. RgA is a pan-GLUT inhibitor of Class I isoforms GLUT1, GLUT3, and GLUT4. Herein, we report the discovery of rapaglutin E (RgE). Unlike RgA, RgE is highly specific for GLUT1. Further characterization revealed that RgE and RgA likely bound to distinct sites on GLUT1 despite their shared FKBP-binding domain, suggesting that the distinct effector domains of RgE and RgA play key roles in recognition of GLUTs. TOC GRAPHIC O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=168 SRC="FIGDIR/small/641094v1_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@d69b12org.highwire.dtl.DTLVardef@15ee120org.highwire.dtl.DTLVardef@e2495org.highwire.dtl.DTLVardef@83e270_HPS_FORMAT_FIGEXP M_FIG C_FIG

pharmacology and toxicology↗

bioRxiv2025

Highly accurate prophage island detection with PIDE

As important mobile elements in prokaryotes, prophages shape the genomic context of their hosts and regulate the structure of bacterial populations. However, it is challenging to precisely identify prophages through computational methods. Here, we introduce PIDE for identifying prophages from bacterial genomes or metagenome-assembled genomes. PIDE integrates a pre-trained protein language model and gene density clustering algorithm to distinguish prophages. Benchmarking on bacterial genomes with experimental prophage annotation demonstrates that PIDE pinpoints prophages with precise boundaries. Applying PIDE to 4,744 human gut representative genomes reveals 24,467 prophages with widespread functional capacity. PIDE is open source and is available at https://github.com/chyghy/PIDE.

bioinformatics↗

bioRxiv2025

Rapaprotin is Activated by an Endopeptidase to Disassemble 26S Proteasome

The 19S regulatory particle (RP) associates with the 20S core particle (CP) to form the 26S proteasome, an evolutionarily conserved holoenzyme that plays key roles in both physiological and pathological processes. Proteasome inhibitors that target the catalytic subunits within the 20S have proven to be valuable research tools and therapeutics for various cancers. Herein we report the discovery of rapaprotin, a 26S proteasome assembly inhibitor from our natural product-inspired hybrid macrocycle rapafucin library. Rapaprotin induces apoptosis in both myeloma and leukemia cell lines. Genome-wide CRISPR-Cas9 screen identified a cytosolic enzyme, prolyl endopeptidase (PREP) that is required for the pro-apoptotic activity of rapaprotin. Further mechanistic studies revealed that rapaprotin acts as a molecular transformer, changing from an inactive cyclic form into an active linear form, rapaprotin-L, upon PREP cleavage, to block 26S proteasome activity. Time-resolved cryogenic electron microscopy (cryo-EM) revealed that rapaprotin-L induces dissociation of the 19S RP from the 26S holoenzyme, which was verified in cells. Furthermore, rapaprotin exhibits a marked synergistic effect with FDA-approved proteasome inhibitors and resensitizes drug-resistant multiple myeloma cells from patients to bortezomib. Taken together, these results suggest that rapaprotin is a new chemical tool to probe the dynamics of the 26S proteasome assembly and a promising anticancer drug lead.

pharmacology and toxicology↗

bioRxiv2025

SynSeg: Generating Synthetic Datasets for Accurate Subcellular Segmentation with U-net

Accurate segmentation of subcellular components is crucial for understanding cellular processes, but traditional methods struggle with noise and complex structures. Convolutional neural networks improve accuracy but require large, time-consuming, and biased manually annotated datasets. Here, we developed SynSeg, a pipeline that generates synthetic training data to train a U-net model for subcellular structure segmentation, eliminating the need for manual annotation. SynSeg leverages synthetic datasets with variations in intensity, morphology, and signal distribution to deliver context-aware segmentations, even in challenging imaging conditions. We demonstrate SynSegs superior performance in segmenting vesicles and cytoskeletal filaments from culture cells and live C. elegans, outperforming traditional methods such as Otsus thresholding, ILEE, and FilamentSensor 2.0. Additionally, SynSeg effectively quantified disease-associated microtubule morphology in live cells, uncovering structural defects caused by mutant Tau proteins linked to neurodegenerative diseases. These results highlight the potential of synthetic data-driven approaches to advance biological segmentation and enhance microscopy techniques. Significance StatementThis study introduces a novel approach for accurately segmenting cellular structures, such as microtubules and vesicles, using synthetic datasets and advanced deep learning techniques. By leveraging a U-Net model trained on thousands of artificially generated images, our method eliminates the need for labor-intensive experimental data and simplifies the data creation process. Importantly, it incorporates noise and variability into the training datasets to make the model more robust and biologically relevant. Our findings demonstrate that the model can successfully identify cellular components, paving the way for its application in real-world microscopy images. This innovation has the potential to accelerate discoveries in cell biology by providing an efficient, scalable tool for analyzing complex cellular structures, even in challenging imaging conditions.

bioinformatics↗

bioRxiv2025

Carbon monoxide exposure stimulates growth and activity of primary producers in diverse soil ecosystems

Carbon monoxide (CO) is both a potent poison for many aerobic organisms and a desirable energy source for diverse microorganisms. Atmospheric emissions of this gas have increased since industrialization and their levels are highly elevated in many urban and natural environments; however, it is unresolved whether elevated levels of CO at environmentally relevant concentrations are primarily stimulatory or inhibitory to soil microbial communities. Here, we showed that CO exposure minimally affects microbial abundance, richness, and composition in diverse ecosystem soils, suggesting most microbes are tolerant of this gas. Genome-resolved metagenomic profiling showed that these soils harbored diverse bacteria capable of using CO an electron donor for aerobic respiration and carbon fixation. CO stimulated the growth of several of these putative CO-oxidizing bacteria in a dose-dependent manner, especially widespread proteobacterial and actinobacterial lineages. Additionally, we found a strong relationship between CO oxidation and carbon fixation and observed an enrichment of several carboxydotrophic MAGs capable of carbon fixation in most soil types. These findings highlight that environmentally relevant CO levels do not inhibit soil microbes, but instead foster the growth of distinct carboxydotrophic bacteria, suggesting a robust soil CO sink that could help mitigate anthropogenic CO emissions and contribute to carbon cycling in terrestrial ecosystems.

biochemistry↗

bioRxiv2024

Antigen flexibility supports the avidity of hemagglutinin-specific antibodies at low antigen densities

The receptor-binding protein of influenza A virus, hemagglutinin (HA), is the most abundant protein on the viral surface. While high densities of HA are thought to improve cellular attachment by increasing avidity for the viral receptor, they may also increase the avidity of neutralizing antibodies. The tradeoff between these two competing effects of avidity is not well understood. To better understand how features of the viral surface influence antibody avidity, we developed fluorescence-based assays to measure dissociation kinetics and steady-state binding of antibodies to intact virions. Focusing on two antibodies that bind to the HA head domain (S139/1 and C05), we confirm that binding orientations that favor bivalent attachment of antibodies to the viral surface can offset weak monovalent affinity by facilitating crosslinking. By modulating HA density in both engineered viruses and synthetic nanoparticles, we find that bivalent antibody binding remains resilient down to one-tenth the HA density on the viral surface and, in the case of C05, that antibody occupancy increases at these lowest densities. Finally, using a combination of structure-guided modeling and antibodies that lock HA in a tilted conformation, we identify flexibility of the HA ectodomain as an additional determinant of antibody avidity. Together, these results establish features of the viral surface that help support or suppress the binding of neutralizing antibodies.

biophysics↗

bioRxiv2024

Modulation of B cell receptor activation by antibody competition

During repeated virus exposure, pre-existing antibodies can mask viral epitopes by competing with B cell receptors for antigen. Although this phenomenon has the potential to steer B cell responses away from conserved epitopes, the factors that influence epitope masking by competing antibodies remain unclear. Using engineered, influenza-reactive B cells, we investigate how antibodies influence the accessibility of epitopes on the viral surface. We find that membrane-proximal epitopes on influenza hemagglutinin are fundamentally at a disadvantage for B cell recognition because they can be blocked by both directly and indirectly competing antibodies. While many influenza-specific antibodies can inhibit B cell activation, the potency of masking depends on proximity of the targeted epitopes as well as antibody affinity, kinetics, and valency. Although most antibodies are inhibitory, we identify one that can enhance accessibility of hidden viral epitopes. Together, these findings establish rules for epitope masking that could help advance immunogen design.

immunology↗

bioRxiv2024

Nanoscale Optical Imaging, Reconstruction, and Spatial Analysis of Whole Mouse Glomeruli

Renal glomeruli have traditionally been studied by micrometer-scale optical microscopy to interrogate overall physiology or molecular distributions and by nanoscale electron microscopy to interrogate the ultrastructure of thin sections. While these approaches are powerful, they have been limited in their ability to obtain detailed views of the glomeruli as holistic 3D functional units. To fill this knowledge gap, we have developed a novel pipeline for imaging, reconstructing, and analyzing whole mouse glomeruli at 100 nm resolution using super-resolution fluorescence microscopy. This pipeline integrates both manual and machine learning approaches to annotate and analyze glomerular structures. Using this method, we created 18 detailed glomerulus models, from a range of healthy, aged, and model diseased mice, that outline all major structures and cell types. These models have been made publicly accessible in an online repository, providing a valuable resource for further studies. Our results also uncovered a diverse set of novel phenotypes including nuclear enlargement in all glomerular cell types in aging and disease, as well as an aging-related pattern of regional thickening of the Bowmans capsule basement membrane near the tubular-glomerular junction.

physiology↗

bioRxiv2024

Hydroxy polyethylene glycol: a solution to evade human pre-existing anti-PEG antibodies for efficient delivery

Polyethylene glycol (PEG) has been extensively utilized in food, cosmetics, and pharmaceutical fields, especially in the realm of nanomedicines, where it serves as a pivotal excipient for extending the nanoparticles circulation half-life. Contrary to its historical perception as non-immunogenic, pre-existing anti-PEG antibodies have been widely detected in human who even have never been exposed to PEGylated therapeutics, which considered to be associated with serious side effects of PEGylated nanomedicines including infusion reactions and other hypersensitive reactions. Herein, we elucidated the prevalence and distribution characteristics of pre-existing anti-PEG antibodies in 2074 human blood samples, and investigated its binding with PEG. Pre-existing anti-PEG antibodies were found to primarily recognize the PEG terminus, especially methoxy, which is the only PEG terminus contained in currently marketed PEGylated nanomedicines. While hydroxy PEG (OH-PEG) significantly evaded binding with pre-existing anti-PEG antibodies among most clinical samples. Noteworthily, substituting OH-PEG for MeO-PEG significantly mitigated complement activation of lipid nanoparticle (LNP) caused by pre-existing anti-PEG antibodies, thereby markedly enhancing stability and reducing mRNA leakage in human serum. Additionally, LNP modified with OH-PEG exhibited reduced immunogenicity, which was crucial for repeated drug administrations. The present work elucidated the crucial role of OH-PEG in evading human pre-existing anti-PEG antibodies, and discovered that the current pre-clinical studies inadequately simulated the biological effects of clinical pre-existing anti-PEG antibodies on such formulations through interspecies study, which had a profound impact on clinical translation of PEGylated nanomedicines.

pharmacology and toxicology↗

bioRxiv2024

m6A-mediated epi-transcriptomic dysregulation underlies synaptic dysfunction in fragile X syndrome

Fragile X syndrome (FXS), the leading genetic cause of intellectual disability, arises from FMR1 gene silencing and loss of the FMRP protein. N6-methyladenosine (m6A) is a prevalent mRNA modification essential for post-transcriptional regulation. FMRP is known to bind to and regulate the stability of m6A-containing transcripts. However, how loss of FMRP impacts on transcriptome-wide m6A modifications in FXS patients remains unknown. To answer this question, we generated cortical neurons differentiated from induced pluripotent stem cells (iPSC) derived from healthy subjects and FXS patients. In electrophysiology recordings, we validated that synaptic and neuronal network defects in iPSC-derived FXS neurons corresponded to the clinical EEG data of the patients from which the corresponding iPSC line was derived. In analysis of transcriptome-wide methylation, we show that FMRP deficiency led to increased translation of m6A writers, resulting in hypermethylation that primarily affecting synapse-associated transcripts and increased mRNA decay. Conversely, in the presence of an m6A writer inhibitor, synaptic defects in FXS neurons were rescued. Taken together, our findings uncover that an FMRP-dependent epi-transcriptomic mechanism contributes to FXS pathogenesis by disrupting m6A modifications in FXS, suggesting a promising avenue for m6A- targeted therapies.

neuroscience↗

bioRxiv2024

Kinesin Autoinhibition Requires Elbow Phosphorylation

Kinesin motor proteins facilitate microtubule-based transport by converting chemical energy into mechanic forces, but this activity is autoinhibited until cargo is loaded. Regulatory mechanisms underlying this autoinhibitory conformation are not well understood. Here, we show that a NEver in mitosis Kinase NEKL-3 directly phosphorylates a flexible elbow region between two coiled coil domains connecting the motor head and tail of an intraflagellar transport kinesin, OSM-3. The phosphor dead (PD) mutation, but not phosphor mimic (PM) mutation, induce constitutive motility of OSM-3 in vitro. Using knock-in animals, we discovered that both PD and PM mutations shorten the C. elegans sensory cilia. The constitutively active OSM-3PD fails to enter cilia and abnormally accumulates in neurites, mimicking another hyperactive mutation, OSM-3G444E. Conversely, OSM-3PM enters cilia but moves at a reduced speed, indicating an inhibitory role of elbow phosphorylation in kinesin motility. These findings highlight the crucial role of elbow phosphorylation in regulating kinesin autoinhibition.

cell biology↗

bioRxiv2024

GABAergic neuron dysregulation in a human neurodevelopmental model for major psychiatric disorders

"GABA dysfunction" is a major hypothesis for the biological basis of schizophrenia with indirect supporting evidence from human post-mortem brain and genetic studies. Patient-derived induced pluripotent stem cells (iPSCs) have emerged as a valuable platform for modeling psychiatric disorders, and previous modeling has revealed glutamatergic synapse deficits. Whether GABAergic synapse properties are affected in patient-derived human neurons and how this impacts neuronal network activity remain poorly understood. Here we optimized a protocol to differentiate iPSCs into highly enriched ganglionic eminence-like neural progenitors and GABAergic neurons. Using a collection of iPSCs derived from patients of psychiatric disorders carrying a Disrupted-in-Schizophrenia 1 (DISC1) mutation and their unaffected family member, together with respective isogenic lines, we identified mutation-dependent deficits in GABAergic synapse formation and function, a phenotype similar to that of mutant glutamatergic neurons. However, mutant glutamatergic and GABAergic neurons contribute differentially to neuronal network excitability and synchrony deficits. Finally, we showed that GABAergic synaptic transmission is also defective in neurons derived from several idiopathic schizophrenia patient iPSCs. Transcriptome analysis further showed some shared gene expression dysregulation, which is more prominent in DISC1 mutant neurons. Together, our study supports a functional GABAergic synaptic deficit in major psychiatric disorders.

neuroscience↗

bioRxiv2024

Leveraging large language models for metabolic engineering design

Establishing efficient cell factories involves a continuous process of trial and error due to the intricate nature of metabolism. This complexity makes predicting effective engineering targets a challenging task. Therefore, it is vital to learn from the accumulated successes of previous designs for advancing future cell factory development. In this study, we developed a method based on large language models (LLMs) to extract metabolic engineering strategies from research articles on a large scale. We created a database containing over 29006 metabolic engineering entries, 1210 products and 751 organisms. Using this extracted data, we trained a hybrid model combining deep learning and mechanistic approaches to predict engineering targets. Our model outperformed traditional metabolic engineering target prediction algorithms, excelled in predicting the effects of gene modifications, and generalized well to out-of-distribution products and multiple gene combinations. Our study provides a valuable dataset, a chatbot, and an engineering target prediction model for the metabolic engineering field and exemplifies an efficient method for leveraging existing knowledge for future predictions.

systems biology↗

bioRxiv2024

Indiv-Brain: Individualized Brain Network Partition Learned from Individual fMRI Data using Deep Clustering with Vertex-level Attention

Individualized functional network partitioning is increasingly critical in elucidating individual differences in cognition, development, and behavior. The previous studies grouped brain regions that were pre-defined by common brain parcellations into individualized brain networks. The employment of common brain region parcellations ignores the individual variations in brain structure and reduces the spatial resolution of the results. Moreover, some studies trained models on a group of subjects to guide individual network partitioning. These methods largely depend on the sample size and encounter challenges in the case of limited subject data. In this paper, we propose Indiv-Brain which automatically partition brain vertices into different brain networks based on individual fMRI data without any prior brain parcellation. The Indiv-Brain consists of three sequential modules: stacked denoising autoencoder (SDAE) for mapping the raw fMRI data to a latent embedding space, masked vertex modeling (MVM) for learning attention-enhanced representations of brain vertices, and deep embedding clustering with spatial attention (DEC-A) for unsupervised clustering on the learned vertex representations. The experiments on Human Connectome Project (HCP) demonstrate that the accuracy of Indiv-Brain outperforms existing methods. We compared the model with methods like SDAE, DEC, IDEC, and k-means. For the results of 8 subjects, the accuracy of Indiv-Brain was consistently the highest, averaging 6.65 percentage points higher than the IDEC method. To the best of our knowledge, this is the first study to obtain individualized brain network partition based on individual fMRI data with deep learning models. Our study provides a novel insight into understanding individualized brain networks, especially suitable for special patients.

neuroscience↗

bioRxiv2024

Overcrowding Drives Tumor Invasion by Inducing Nanotopographical Transition of Plasma Membrane

During the progression from epithelial neoplasms to invasive carcinoma, cells are subjected to prolonged confinement. However, the response of cancer cells to such mild yet sustained compressive pressure during the initial stages of tumor invasion remain poorly understood. Here, using a spontaneous crowding model to recapitulate the progressive compressive stress caused by cell proliferation, we demonstrated that prolonged crowding alone is sufficient to induce the acquisition of an invasive phenotype and associated gene expression patterns in cancer cells. This invasiveness persisted even after cells were removed from the crowded environment, a phenomenon mediated by mechanomemory. By combining genetic manipulations, mechanical modeling, and biophysical measurements, we revealed that the disaggregation of membrane domains--driven by a nanoscale smooth-corrugated topography transition of plasma membranes induced by Laplace pressure under crowded conditions--is essential for initiating cancer cell invasion. Inhibiting membrane domains disaggregation through membrane-to-cortex-attachment effectively suppresses cancer cell invasion in both cellular crowding models and mouse xenograft models. This study underscores the critical role of tissue-scale mechanics in regulating the biophysics of mechanosensitive membrane domains during the early stages of tumor invasion.

cancer biology↗