Biology subjects

Wu, Y.

Publications and source records attributed to Wu, Y..

At least 577 records · Page 32Linked to original sources

bioRxiv2023

Sexually dimorphic mechanisms of VGLUT-mediated protection from dopaminergic neurodegeneration

Parkinsons disease (PD) targets some dopamine (DA) neurons more than others. Sex differences offer insights, with females more protected from DA neurodegeneration. The mammalian vesicular glutamate transporter VGLUT2 and Drosophila ortholog dVGLUT have been implicated as modulators of DA neuron resilience. However, the mechanisms by which VGLUT2/dVGLUT protects DA neurons remain unknown. We discovered DA neuron dVGLUT knockdown increased mitochondrial reactive oxygen species in a sexually dimorphic manner in response to depolarization or paraquat-induced stress, males being especially affected. DA neuron dVGLUT also reduced ATP biosynthetic burden during depolarization. RNA sequencing of VGLUT+ DA neurons in mice and flies identified candidate genes that we functionally screened to further dissect VGLUT-mediated DA neuron resilience across PD models. We discovered transcription factors modulating dVGLUT-dependent DA neuroprotection and identified dj-1{beta} as a regulator of sex-specific DA neuron dVGLUT expression. Overall, VGLUT protects DA neurons from PD-associated degeneration by maintaining mitochondrial health.

neuroscience↗

bioRxiv2023

Nucleotide Excision Repair of Aflatoxin-induced DNA Damage within the 3D Human Genome Organization

Aflatoxin B1 (AFB1), a potent mycotoxin, is one of the two primary risk factors that cause liver cancer. In the liver, the bioactivated AFB1 intercalates into the DNA double helix to form a bulky DNA adduct which will lead to mutation if left unrepaired. We have adapted the tXR-seq method to measure the nucleotide excision repair of AFB1-induced DNA adducts. We have found that transcription-coupled repair plays a major role in the damage removal process and the released excision products have a distinctive length distribution pattern. We further analyzed the impact of 3D genome organization on the repair of AFB1-induced DNA adducts. We have revealed that chromosomes close to the nuclear center and A compartments undergo expedited repair processes. Notably, we observed an accelerated repair around both TAD boundaries and loop anchors. These findings provide insights into the complex interplay between repair, transcription, and 3D genome organization, shedding light on the mechanisms underlying AFB1-induced liver cancer. TEASERGenome-wide mapping repair of AFB1-caused DNA damage by tXR-seq reveals 3D genome organizations significant impact on the repair.

genetics↗

bioRxiv2023

Full-Length Single-Molecule Protein Fingerprinting

Proteins are the primary functional actors of the cell. Hence, their identification is pivotal to advance our understanding of cell biology and disease. Current protein analysis methods are of limited use for distinguishing proteoforms. In particular, mass spectrometric methods often provide only ambiguous information on post-translational modification sites, and sequences of co-existing modifications may not be resolved. Here we demonstrate FRET-based single-molecule protein fingerprinting to map the location of individual amino acids and a post-translational modification within single full-length protein molecules. Using an approach that relies on transient binding of fluorescently labeled DNA strands to probe the amino acids on a protein one by one we show that we can fingerprint intrinsically disordered proteins as well as folded globular proteins with sub-nanometer resolution. We anticipate that this technology will be used for proteoform identification in biological and translational research with ultimate sensitivity.

biophysics↗

bioRxiv2023

A Scalable Staining Strategy for Whole-Brain Connectomics

Mapping the complete synaptic connectivity of a mammalian brain would be transformative, revealing the pathways underlying perception, behavior, and memory. Serial section electron microscopy, via membrane staining using osmium tetroxide, is ideal for visualizing cells and synaptic connections but, in whole brain samples, faces significant challenges related to chemical treatment and volume changes. These issues can adversely affect both the ultrastructural quality and macroscopic tissue integrity. By leveraging time-lapse X-ray imaging and brain proxies, we have developed a 12-step protocol, ODeCO, that effectively infiltrates osmium throughout an entire mouse brain while preserving ultrastructure without any cracks or fragmentation, a necessary prerequisite for constructing the first comprehensive mouse brain connectome.

neuroscience↗

bioRxiv2023

Spatial transcriptomics and single-nucleus RNA sequencing reveal a transcriptomic atlas of adult human spinal cord

Despite the recognized importance of the spinal cord in sensory processing, motor behaviors, and neural diseases, the underlying organization of neuronal clusters and their spatial location remain elusive. Recently, several studies have attempted to define the neuronal types and functional heterogeneity in the spinal cord using single-cell or single-nucleus RNA sequencing in animal models or developing humans. However, molecular evidence of cellular heterogeneity in the adult human spinal cord is limited. Here, we classified spinal cord neurons into 21 subclusters and determined their distribution from nine human donors using single-nucleus RNA sequencing and spatial transcriptomics. Moreover, we compared the human findings with previously published single-nucleus data of the mouse adult spinal cord, which revealed an overall similarity in the neuronal composition of the spinal cord between the two species while simultaneously highlighting some degree of heterogeneity. Additionally, we examined the sex differences in the spinal neuronal subclusters. Several genes, such as SCN10A and HCN1, showed sex differences in motor neurons. Finally, we classified human dorsal root ganglia (DRG) neurons using spatial transcriptomics and explored the putative interactions between DRG and spinal cord neuronal subclusters. In summary, these results illustrate the complexity and diversity of spinal neurons in humans and provide an important resource for future research to explore the molecular mechanisms underlying spinal cord physiology and diseases.

neuroscience↗

bioRxiv2023

Differential effects of aneuploidy on growth and differentiation in human intestinal stem cells

Aneuploidy, a near ubiquitous genetic feature of tumors, is a context-dependent driver of cancer evolution; however, the mechanistic basis of this role remains unclear. Here, by inducing heterogeneous aneuploidy in non-transformed human colon organoids (colonoids), we investigate how the effects of aneuploidy on cell growth and differentiation may promote malignant transformation. Single-cell RNA sequencing reveals that the gene expression signature across over 100 unique aneuploid karyotypes is enriched with p53 responsive genes. The primary driver of p53 activation is karyotype complexity. Complex aneuploid cells with multiple unbalanced chromosomes activate p53 and undergo G1 cell-cycle arrest, independent of DNA damage and without evidence of senescence. By contrast, simple aneuploid cells with 1-3 chromosomes gained or lost continue to proliferate, demonstrated by single cell tracking in colonoids. Notably, simple aneuploid cells exhibit impaired differentiation when niche factors are withdrawn. These findings suggest that while complex aneuploid cells are eliminated from the normal epithelium due to p53 activation, simple aneuploid cells can escape this checkpoint and may contribute to niche factor-independent growth of cancer-initiating cells.

cell biology↗

bioRxiv2023

TIM-4 identifies effector B cells expressing an IL-23-driven proinflammatory cytokine module that promotes immune responses

B cells can express pro-inflammatory cytokines that promote a wide variety of immune responses. Here we show that B cells expressing the phosphatidylserine receptor TIM-4, preferentially express IL-17A, as well as IL-22, IL-6, IL-1{beta}, and GM-CSF - a pattern of cytokines reminiscent of pathogenic Th17 cells. Expression of this proinflammatory module requires IL-23R signaling and selective expression of ROR{gamma}t by TIM-4+ B cells. TIM-4+ B cell-derived-IL-17A not only enhances the severity of experimental autoimmune encephalomyelitis (EAE) and promotes allograft rejection but also acts in an autocrine manner to prevent their conversion into IL-10-expressing B cells with regulatory function. Thus, IL-17A acts as an inflammatory mediator and enforces the proinflammatory activity of TIM-4+ B cells. Moreover, TIM-4 serves as a broad marker for ROR{gamma}t-expressing effector B cells (Beff). These findings allow further study of the signals regulating Beff differentiation and effector molecule expression.

immunology↗

bioRxiv2023

Probing Molecular Diversity and Ultrastructure of Brain Cells with Fluorescent Aptamers

Detergent-free immunolabeling has been proven feasible for correlated light and electron microscopy, but its application is restricted by the availability of suitable affinity reagents. Here we introduce CAptVE, a method using slow off-rate modified aptamers for cell fluorescence labeling on ultrastructurally reconstructable electron micrographs. CAptVE provides labeling for a wide range of biomarkers, offering a pathway to integrate molecular analysis into recent approaches to delineate neural circuits via connectomics.

neuroscience↗

bioRxiv2023

Prediction of Interactions between Cell Surface Proteins by Machine Learning

Cells detect changes of external environments or communicate with each other through proteins on their surfaces. These cell surface proteins form a complicated network of interactions in order to fulfill their functions. The interactions between cell surface proteins are highly dynamic and thus challenging to detect using traditional experimental techniques. Here we tackle this challenge by a computational framework. The primary focus of the framework is to develop new tools to identify interactions between domains in immunoglobulin (Ig) fold, which is the most abundant domain family in cell surface proteins. These interactions could be formed between ligands and receptors from different cells, or between proteins on the same cell surface. In practice, we collected all structural data of Ig domain interactions and transformed them into an interface fragment pair library. A high dimensional profile can be then constructed from the library for a given pair of query protein sequences. Multiple machine learning models were used to read this profile, so that the probability of interaction between the query proteins can be predicted. We tested our models to an experimentally derived dataset which contains 564 cell surface proteins in human. The cross-validation results show that we can achieve higher than 70% accuracy in identifying the PPIs within this dataset. We then applied this method to a group of 46 cell surface proteins in C elegans. We screened every possible interaction between these proteins. Many interactions recognized by our machine learning classifiers have been experimentally confirmed in the literatures. In conclusion, our computational platform serves a useful tool to help identifying potential new interactions between cell surface proteins in addition to current state-of-the-art experimental techniques. The tool is freely accessible for use by the scientific community. Moreover, the general framework of the machine learning classification can also be extended to study interactions of proteins in other domain superfamilies.

bioinformatics↗

bioRxiv2023

Functional connectome through the human life span

The lifespan growth of the functional connectome remains unknown. Here, we assemble task-free functional and structural magnetic resonance imaging data from 33,250 individuals aged 32 postmenstrual weeks to 80 years from 132 global sites. We report critical inflection points in the nonlinear growth curves of the global mean and variance of the connectome, peaking in the late fourth and late third decades of life, respectively. After constructing a fine-grained, lifespan-wide suite of system-level brain atlases, we show distinct maturation timelines for functional segregation within different systems. Lifespan growth of regional connectivity is organized along a primary-to-association cortical axis. These connectome-based normative models reveal substantial individual heterogeneities in functional brain networks in patients with autism spectrum disorder, major depressive disorder, and Alzheimers disease. These findings elucidate the lifespan evolution of the functional connectome and can serve as a normative reference for quantifying individual variation in development, aging, and neuropsychiatric disorders.

neuroscience↗

bioRxiv2023

Encoding the Space of Protein-protein Binding Interfaces by Artificial Intelligence

The physical interactions between proteins are largely determined by the structural properties at their binding interfaces. It was found that the binding interfaces in distinctive protein complexes are highly similar. The structural properties underlying different binding interfaces could be further captured by artificial intelligence. In order to test this hypothesis, we broke protein-protein binding interfaces into pairs of interacting fragments. We employed a generative model to encode these interface fragment pairs in a low-dimensional latent space. After training, new conformations of interface fragment pairs were generated. We found that, by only using a small number of interface fragment pairs that were generated by artificial intelligence, we were able to guide the assembly of protein complexes into their native conformations. These results demonstrate that the conformational space of fragment pairs at protein-protein binding interfaces is highly degenerate. Our study illustrates how artificial intelligence can be used to understand and characterize protein-protein binding interfaces. The method will be potentially useful to search for the conformation of unknown protein-protein interactions. This result demonstrated that the structural space of protein-protein interactions is highly degenerate under the representation of interface fragment pairs. Features in this degenerate space can be well characterized by artificial intelligence. In summary, our machine learning method will be potentially useful to search for and predict the conformations of unknown protein-protein interactions.

bioinformatics↗

bioRxiv2023

STASCAN deciphers fine-resolution cell-distribution maps in spatial transcriptomics by deep learning

BackgroundThe spatial transcriptomics (ST) technologies have been widely applied to decode the spatial distribution of cells by resolving gene expression profiles in tissues. However, a fine-resolved spatial cell map is still limited by algorithmic tools and sequencing techniques. ResultsHere we develop a novel deep learning approach, STASCAN, which could define the spatial cellular distribution of both captured and uncharted areas by cell feature learning that combines gene expression profiles and histology images. STASCAN additionally adopts optional transfer learning and pseudo-labeling methods to improve the accuracy of the cell-type prediction from images. We have successfully applied STASCAN to enhance cell resolution, and revealed finer organizational structures across diverse datasets from various species and tissues generated from 10x Visium technology. STASCAN improves cell resolution of Schmidtea mediterranea datasets by six times and reconstructs more detailed 3D cell-type models. Furthermore, STASCAN could accurately pinpoint the boundaries of distinct cell layers in human intestinal tissue, specifically identify a micrometer-scale smooth muscle bundle structure in consistent with anatomic insights in human lung tissue, and redraw the spatial structural variation with enhanced cell patterns in human myocardial infarction tissue. Additionally, through STASCAN on embryonic mouse brain datasets generated by DBiT-derived MISAR-seq technology, the increased cellular resolution and distinct anatomical tissue domains with cell-type niches are revealed. Collectively, STASCAN is compatible with different ST technologies and has notable advantages in generating cell maps solely from histology images, thereby enhancing the spatial cellular resolution. ConclusionsIn short, STASCAN displays significant advantages in deciphering higher-resolution cellular distribution, resolving enhanced organizational structures and demonstrating its potential applications in exploring cell-cell interactions within the tissue microenvironment.

bioinformatics↗

bioRxiv2023

Cytoskeletal activation of NHE1 regulates cell volume and DNA methylation

Mammalian cells can rapidly respond to osmotic and hydrostatic pressure imbalances during an environmental change, generating large fluxes of water and ions that alter cell volume within minutes. While the role of ion pump and leak in cell volume regulation has been well-established, the potential contribution of the actomyosin cytoskeleton and its interplay with ion transporters is unclear. We discovered a cell volume regulation system that is controlled by cytoskeletal activation of ion transporters. After a hypotonic shock, normal-like cells (NIH-3T3, MCF-10A, and others) display a slow secondary volume increase (SVI) following the immediate regulatory volume decrease. We show that SVI is initiated by hypotonic stress induced Ca2+ influx through stretch activated channel Piezo1, which subsequently triggers actomyosin remodeling. The actomyosin network further activates NHE1 through their synergistic linker ezrin, inducing SVI after the initial volume recovery. We find that SVI is absent in cancer cell lines such as HT1080 and MDA-MB-231, where volume regulation is dominated by intrinsic response of ion transporters. A similar cytoskeletal activation of NHE1 can also be achieved by mechanical stretching. On compliant substrates where cytoskeletal contractility is attenuated, SVI generation is abolished. Moreover, cytoskeletal activation of NHE1 during SVI triggers nuclear deformation, leading to a significant, immediate transcriptomic change in 3T3 cells, a phenomenon that is again absent in HT1080 cells. While hypotonic shock hinders ERK-dependent cell growth, cells deficient in SVI are unresponsive to such inhibitory effects. Overall, our findings reveal the critical role of Ca2+ and actomyosin-mediated mechanosensation in the regulation of ion transport, cell volume, transcriptomics, and cell proliferation.

biophysics↗

bioRxiv2023

HCN channels sense temperature and determine heart rate responses to heat

Heart rate increases with heat, [1-3] constituting a fundamental physiological relationship in vertebrates. Each normal heartbeat is initiated by an action potential generated in a sinoatrial nodal pacemaker cell. Pacemaker cells are enriched with hyperpolarization activated cyclic nucleotide-gated ion channels (HCN) that deliver cell membrane depolarizing inward current that triggers action potentials. HCN channel current increases due to cAMP binding, a mechanism coupling adrenergic tone to physiological fight or flight heart rate acceleration. However, the mechanism(s) for heart rate response to thermal energy is unknown. We used thermodynamical and homology computational modeling, site-directed mutagenesis and mouse models to identify a concise motif on the S4-S5 linker of the cardiac pacemaker HCN4 channels (M407/Y409) that determines HCN4 current (If) and cardiac pacemaker cell responses to heat. This motif is required for heat sensing in cardiac pacemaker cells and in isolated hearts. In contrast, the cyclic nucleotide binding domain is not required for heat induced HCN4 current increases. However, a loss of function M407/Y409 motif mutation prevented normal heat and cAMP responses, suggesting that heat sensing machinery is essential for operating the cAMP allosteric pathway and is central to HCN4 modulation. The M407/Y409 motif is conserved across all HCN family members suggesting that HCN channels participate broadly in coupling heat to changes in cell membrane excitability.

physiology↗

bioRxiv2023

Altered DNA methylation underlies monocyte dysregulation and innate exhaustion memory in sepsis

Innate immune memory is the process by which pathogen exposure elicits cell-intrinsic states to alter the strength of future immune challenges. Such altered memory states drive monocyte dysregulation during sepsis, promoting pathogenic behavior characterized by pro-inflammatory, immunosuppressive gene expression in concert with emergency hematopoiesis. Epigenetic changes, notably in the form of histone modifications, have been shown to underlie innate immune memory, but the contribution of DNA methylation to this process remains poorly understood. Using an ex vivo sepsis model, we discovered broad changes in DNA methylation throughout the genome of exhausted monocytes, including at several genes previously implicated as major drivers of immune dysregulation during sepsis and Covid-19 infection (e.g. Plac8). Methylome alterations are driven in part by Wnt signaling inhibition in exhausted monocytes, and can be reversed through treatment with DNA methyltransferase inhibitors, Wnt agonists, or immune training molecules. Importantly, these changes are recapitulated in septic mice following cecal slurry injection, resulting in stable changes at critical immune genes that support the involvement of DNA methylation in acute and long-term monocyte dysregulation during sepsis.

immunology↗

bioRxiv2023

Chemogenetic inhibition of IST1-CHMP1B interaction impairs endosomal recycling and promotes unconventional LC3 lipidation at stalled endosomes

The Endosomal Sorting Complex Required for Transport (ESCRT) machinery constitutes a multisubunit protein complex that plays an essential role in membrane remodeling and trafficking. ESCRTs regulate a wide array of cellular processes, encompassing cytokinetic abscission, cargo sorting into multivesicular bodies (MVBs), membrane repair and autophagy. Given the versatile functionality of ESCRTs and the intricate organizational structure of the ESCRT complex, the targeted modulation of distinct ESCRT-mediated membrane deformations for functional dissection poses a considerable challenge. This study presents a pseudo-natural product targeting IST1-CHMP1B within the ESCRT-III complex. This compound specifically disrupts the interaction between IST1 and CHMP1B, thereby inhibiting the formation of IST1-CHMP1B copolymers essential for normal-topology membrane scission events. While the compound has no impact on cytokinesis, MVB sorting and exosome biogenesis, it rapidly hinders transferrin receptor (TfR) recycling in cells, resulting in the accumulation of transferrin in perinuclear endosomal recycling tubules. Stalled recycling endosomes acquire unconventional LC3 lipidation, establishing a link between non-canonical LC3 lipidation and endosomal recycling.

cell biology↗

bioRxiv2023

Glycolytic Metabolon Assembly on Mitochondria via Hexokinase O-GlcNAcylation Promotes Metabolic Efficiency

Glucose, the primary cellular energy source, is metabolized through glycolysis initiated by the rate-limiting enzyme Hexokinase (HK). In energy-demanding tissues like the brain, HK1 is the dominant isoform, primarily localized on mitochondria, crucial for efficient glycolysis-oxidative phosphorylation coupling and optimal energy generation. This study unveils a unique mechanism regulating HK1 activity, glycolysis, and the dynamics of mitochondrial coupling, mediated by the metabolic sensor enzyme O-GlcNAc transferase (OGT). OGT catalyzes reversible O-GlcNAcylation, a post-translational modification, influenced by glucose flux. Elevated OGT activity induces dynamic O-GlcNAcylation of HK1s regulatory domain, subsequently promoting the assembly of the glycolytic metabolon on the outer mitochondrial membrane. This modification enhances HK1s mitochondrial association, orchestrating glycolytic and mitochondrial ATP production. Mutations in HK1s O-GlcNAcylation site reduce ATP generation, affecting synaptic functions in neurons. The study uncovers a novel pathway that bridges neuronal metabolism and mitochondrial function via OGT and the formation of the glycolytic metabolon, offering new prospects for tackling metabolic and neurological disorders.

cell biology↗

bioRxiv2023

scCancer2: data-driven in-depth annotations of the tumor microenvironment at single-level resolution

Single-cell RNA-seq (scRNA-seq) is a powerful technique for decoding the complex cellular compositions in the tumor microenvironment (TME). As previous studies have defined many meaningful cell subtypes in several tumor types, there is a great need to computationally transfer these labels to new datasets. Also, different studies used different approaches or criteria to define the cell subtypes for the same major cell lineages. The relationships between the cell subtypes defined in different studies should be carefully evaluated. In this updated package scCancer2, designed for integrative tumor scRNA-seq data analysis, we developed a supervised machine learning framework to annotate TME cells with annotated cell subtypes from 15 scRNA datasets with 594 samples in total. Based on the trained classifiers, we quantitatively constructed the similarity maps between the cell subtypes defined in different references by testing on all the 15 datasets. Secondly, to improve the identification of malignant cells, we designed a classifier by integrating large-scale pan-cancer TCGA bulk gene expression datasets and scRNA-seq datasets (10 cancer types, 159 samples, 652,160 cells). This classifier shows robust performances when no internal confidential reference cells are available. Thirdly, this package also integrated a module to process the seq-based spatial transcriptomic data and analyze the spatial features of TME. Software availability: http://lifeome.net/software/sccancer2/.

bioinformatics↗