Biology subjects

Hu, Y.

Publications and source records attributed to Hu, Y..

At least 271 records · Page 15Linked to original sources

bioRxiv2024

Molecular stratification of human fetal vaginal epithelium by spatial transcriptome analysis

The human vaginal epithelium is a crucial component in numerous reproductive processes and serves as a vital protective barrier against pathogenic invasion. Despite its significance, a comprehensive exploration of its molecular profiles, including molecule expression and distribution across its multiple layers, remains elusive. In our study, we undertook a spatial transcriptomic analysis within the vaginal wall of human fetuses to fill this knowledge gap. We successfully categorized vaginal epithelium into four distinct zones based on their transcriptomic profiles and anatomical features. This approach unveiled unique transcriptomic signatures within these regions, allowing us to identify differentially expressed genes and uncover novel markers for distinct regions of the vaginal epithelium. Additionally, our findings have highlighted the varied expression of KRT genes across different zone of the vaginal epithelium, with a gradual shift in expression patterns observed from the basal layer to the surface/superficial layer. This suggests a potential differentiation trajectory of human vaginal epithelium, shedding light on the dynamic nature of this tissue. Furthermore, abundant biological processes were found to be enriched in the basal zone by the KEGG pathway analysis, indicating an active state of the basal zone cells. Subsequently, the expression of latent stem cell markers in the basal zone were identified. In summary, our research provides crucial understanding of human vaginal epithelial cells and the complex mechanisms of the vaginal mucosa, with potential applications in vaginal reconstruction and drug delivery, making this atlas a valuable tool for future research in womens health and reproductive medicine.

cell biology↗

bioRxiv2024

Development of an engineered extracellular vesicles-based vaccine platform for combined delivery of mRNA and protein to induce functional immunity

mRNA incorporated in lipid nanoparticles (LNPs) became a new class of vaccine modality for induction of immunity against COVID-19 and ushered in a new era in vaccine development. Here, we report a novel, easy-to-execute, and cost effective engineered extracellular vesicles (EVs)-based combined mRNA and protein vaccine platform (EVX-M+P vaccine) and explore its utility in proof-of-concept immunity studies in the settings of cancer and infectious disease. As a first example, we engineered EVs to contain ovalbumin mRNA and protein (EVOvaM+P) to serve as cancer vaccine against ovalbumin-expressing melanoma tumors. EVOvaM+P administration to mice with established melanoma tumors resulted in tumor regression associated with effective humoral and adaptive immune responses. As a second example, we generated engineered EVs, natural nanoparticle carriers shed by all cells, that contain mRNA and protein Spike (S) protein to serve as a combined mRNA and protein vaccine (EVSpikeM+P vaccine) against SARS-CoV-2 infection. EVSpikeM+P vaccine administration in mice and baboons elicited robust production of neutralizing IgG antibodies against RBD (receptor binding domain) of S protein and S protein specific T cell responses. Our proof-of-concept study describes a new platform with an ability for rapid development of combination mRNA and protein vaccines employing EVs for deployment against cancer and other diseases.

immunology↗

bioRxiv2024

Multivalent 28S rRNA Is the Organizer of the Nucleolus's Multi-layered Architecture

The nucleolus widely exists in all eukaryotic species. Throughout evolution, two types of nucleoli have emerged: bipartite, which has two-layered subcompartments, and tripartite, which features three nested sub-compartments: granular component (GC), dense fibrillar component (DFC), and fibrillar center (FC). FC and DFC form a core-shell architecture and are immersed by a large GC. However, factors that mediated the formation of the three-layered architecture remain largely unknown. Here, we discovered that rRNAs have specific localizations within the nucleolus, with 28S rRNA forming assemblies surrounding the DFC. Multivalent interactions of 28S rRNA drove the formation of the hollow shell structure of DFC, which mediated the development of a three-layered structure resembling nucleolar GC-DFC-FC. Moreover, in organisms with a tripartite nucleolus, 28S rRNA has evolved to acquire a higher degree of multivalency. Our data implies that the emergence of multivalency of 28S rRNA facilitates the transition of bipartite to tripartite nucleolus.

cell biology↗

bioRxiv2024

Benchmarking clustering, alignment, and integration methods for spatial transcriptomics

Spatial transcriptomics (ST) is advancing our understanding of complex tissues and organisms. However, building a robust clustering algorithm to define spatially coherent regions in a single tissue slice, and aligning or integrating multiple tissue slices originating from diverse sources for essential downstream analyses remain challenging. Numerous clustering, alignment, and integration methods have been specifically designed for ST data by leveraging its spatial information. The absence of benchmark studies complicates the selection of methods and future method development. Here we systematically benchmark a variety of state-of-the-art algorithms with a wide range of real and simulated datasets of varying sizes, technologies, species, and complexity. Different experimental metrics and analyses, like adjusted rand index (ARI), uniform manifold approximation and projection (UMAP) visualization, layer-wise and spot-to-spot alignment accuracy, spatial coherence score (SCS), and 3D reconstruction, are meticulously designed to assess method performance as well as data quality. We analyze the strengths and weaknesses of each method using diverse quantitative and qualitative metrics. This analysis leads to a comprehensive recommendation that covers multiple aspects for users. The code used for evaluation is available on GitHub. Additionally, we provide jupyter notebook tutorials and documentation to facilitate the reproduction of all benchmarking results and to support the study of new methods and new datasets (https://benchmarkst-reproducibility.readthedocs.io/en/latest/).

bioinformatics↗

bioRxiv2024

DNA-based ForceChrono Probes for Deciphering Single-Molecule Force Dynamics in Living Cells

Accurate measurement of mechanical forces in cells is key to understanding how cells sense and respond to mechanical stimuli, a central aspect of mechanobiology. However, accurately quantifying dynamic forces at the single-molecule level in living cells is a significant challenge. Here, weve developed the DNA-based ForceChrono probe to enable in-depth studies of integrin force dynamics at the single-molecule level in living cells. By illuminating two distinct mechanical points and circumventing the inherent fluctuations of single-molecule fluorescence, the ForceChrono probe enables analysis of the complex dynamics of mechanical forces at the single-molecule level, such as loading rates and durations. Our results refine previous broad estimates of cellular loading rates to a more precise range of 0.5 to 2 pN/s, shedding light on the specifics of cellular mechanics. In addition, this study reveals a critical link between the magnitude and duration of integrin forces, consistent with the catch-bond behavior demonstrated in vitro. The ForceChrono probe has distinct advantages, such as precise analysis of single-molecule force dynamics and robust resistance to fluorescence fluctuations, which will significantly advance our understanding of cell adhesion and mechanotransduction at the single-molecule level.

biophysics↗

bioRxiv2024

RGS10 deficiency facilitates distant metastasis by inducing epithelial-mesenchymal transition in breast cancer

AbstractDistant metastasis is the major cause of death in patients with breast cancer. Epithelial-mesenchymal transition (EMT) contributes to breast cancer metastasis. Regulator of G protein-signaling (RGS) proteins modulate metastasis in various cancers. This study identified a novel role for RGS10 in EMT and metastasis in breast cancer. RGS10 protein levels were significantly lower in breast cancer tissues compared to normal breast tissues, and deficiency in RGS10 protein predicted a worse prognosis in patients with breast cancer. RGS10 protein levels were lower in the highly aggressive cell line MDA-MB-231 than in the poorly aggressive, less invasive cell lines MCF7 and SKBR3. Silencing RGS10 in SKBR3 cells enhanced EMT and caused SKBR3 cell migration and invasion. The ability of RGS10 to suppress EMT and metastasis in breast cancer was dependent on lipocalin-2 and miR-539-5p. These findings identify RGS10 as a tumor suppressor, prognostic biomarker, and potential therapeutic target for breast cancer.

cancer biology↗

bioRxiv2024

Thermal Characterization and Preclinical Validation of an Accessible, Carbon Dioxide-Based Cryotherapy System

To investigate the potential of an affordable cryotherapy device for accessible treatment of breast cancer, the performance of a novel carbon dioxide-based device was evaluated through both benchtop and in vivo canine models. This novel device was quantitatively compared to a commercial device that utilizes argon gas as the cryogen. The thermal behavior of each device was characterized through calorimetry and by measuring the temperature profiles of iceballs generated in tissue phantoms. A 45-minute treatment from the carbon dioxide device in a tissue phantom produced a 1.67 {+/-} 0.06 cm diameter lethal isotherm that was equivalent to a 7-minute treatment from the commercial argon-based device which produced a 1.53 {+/-} 0.15 cm diameter lethal isotherm. In vivo validation was performed with the carbon dioxide-based device in one spontaneously occurring canine mammary mass with two standard 10-minutes freezes. Following cryotherapy, this mass was surgically resected and analyzed for necrosis margins via histopathology. The histopathology margin of necrosis from the in vivo treatment with the carbon dioxide device at 14 days post cryoablation was 1.57 cm. While carbon dioxide gas has historically been considered an impractical cryogen due to its low working pressure and high boiling point, this study shows that carbon dioxide-based cryotherapy may be equivalent to conventional argon-based cryotherapy in the size of the ablation zone in a standard treatment time. The validation of the carbon dioxide device performed in this study is an important step towards bringing accessible breast cancer treatment to women in low-resource settings.

bioengineering↗

bioRxiv2024

TASOR expression in naive embryonic stem cells safeguards their developmental potential

The seamless transition through stages of pluripotency relies on a delicate balance between transcription factor networks and epigenetic silencing mechanisms that ensure proper regulation of the developmental program, critical for normal development. Here, we uncover the pivotal role of the transgene activation suppressor (TASOR), a component of the human silencing hub (HUSH) complex, in sustaining cell viability during the transition from naive to primed pluripotency, despite its rapid downregulation during this transition. Loss of TASOR in naive cells triggers replication stress, disrupts H3K9me3 heterochromatin formation, and compromise the transcriptional and post-transcriptional silencing of LINE-1 (L1) transposable elements (TEs), with these effects become more pronounced in primed cells. Remarkably, the survival of Tasor-knockout cells during naive to primed transition can be restored through the inhibition of cysteine-aspartic acid protease (Caspase) or deletion of mitochondrial antiviral signaling protein (MAVS). This suggests that unscheduled L1 expression activates an innate immune response, leading to programmed cell death, specifically in cells exiting naive pluripotency. Additionally, we propose that HUSH-promoted H3K9me3 in naive PSCs sets the stage for ensuing DNA methylation in primed cells, establishing long-term silencing during differentiation. Our findings shed insights on the crucial impact of epigenetic programs established in early developmental stages on subsequent phases, underscoring their significance in the developmental process.

developmental biology↗

bioRxiv2024

MaskGraphene: Advancing joint embedding, clustering, and batch correction for spatial transcriptomics using graph-based self-supervised learning

Recent advancements in spatial transcriptomics (ST) have underscored the importance of integrating data from multiple ST slices for joint analysis. A major challenge remains generating interpretable joint embeddings that preserve geometric information for downstream analyses. Here we introduce MaskGraphene, a graph neural network that combines self-supervised and self-contrastive training to integrate gene expression and spatial location into joint embeddings. By employing clusterwise alignment and a graph attention autoencoder with masked self-supervised and triplet loss optimizations, MaskGraphene effectively preserves geometric structures while achieving batch correction. In benchmarks against seven state-of-the-art methods, MaskGraphene consistently demonstrated superior alignment accuracy and geometric fidelity across diverse ST datasets. Its interpretable embeddings significantly enhanced downstream applications, including domain identification, spatial trajectory reconstruction, biomarker discovery, and the creation of topographical maps of brain slices. Notably, MaskGraphene successfully recovered layer-wise brain structures with near-perfect accuracy. MaskGraphene provides a powerful and versatile framework for advancing ST data integration and analysis, unlocking valuable biological insights.

bioinformatics↗

bioRxiv2024

Degradation of IKAROS prevents epigenetic progression of T cell exhaustion in a novel antigen-specific assay

In cancer, chronic antigen stimulation drives effector T cells to exhaustion, limiting the efficacy of T cell therapies. Recent studies have demonstrated that epigenetic rewiring governs the transition of T cells from effector to exhausted states and makes a subset of exhausted T cells non-responsive to PD1 checkpoint blockade. Here, we describe an antigen-specific assay for T cell exhaustion that generates T cells that are phenotypically and transcriptionally similar to those found in human tumors. We performed a screen of human epigenetic regulators, identifying and validating IKAROS as a driver of T cell exhaustion. We found that the IKAROS degrader iberdomide prevents exhaustion by blocking chromatin remodeling at T cell effector enhancers and preserving binding of AP-1, NF-{kappa}B, and NFAT. Thus, our study uncovered a role for IKAROS as a driver of T cell exhaustion through epigenetic modulation, providing a rationale for the potential use of iberdomide in solid tumors to prevent T cell exhaustion. HighlightsO_LINovel in vitro assay generates antigen-specific exhausted T cells from human T cells C_LIO_LIIKAROS (IKZF1) is a key driver of T cell exhaustion C_LIO_LIIberdomide (IKZF1/3 degrader) prevents the progression of exhaustion C_LIO_LITF footprinting reveals IKAROS silences effector genes by inhibiting AP-1, NF-{kappa}B and NFAT binding C_LI

genomics↗

bioRxiv2024

CNVeil enables accurate and robust tumor subclone identification and copy number estimation from single-cell DNA sequencing data

Single-cell DNA sequencing (scDNA-seq) has significantly advanced cancer research by enabling precise detection of chromosomal aberrations, such as copy number variations (CNVs), at a single-cell level. These variations are crucial for understanding tumor progression and heterogeneity among tumor subclones. However, accurate CNV inference in scDNA-seq has been constrained by several factors, including low coverage, sequencing errors, and data variability. To address these challenges, we introduce CNVeil, a robust quantitative algorithm designed to accurately reveal CNV profiles while overcoming the inherent noise and bias in scDNA-seq data. CNVeil incorporates a unique bias correction method using normal cell profiles identified by a PCA-based Gini coefficient, effectively mitigating sequencing bias. Subsequently, a multi-level hierarchical clustering, based on selected highly variable bins, is employed to initially identify coarse subclones for robust ploidy estimation and further identify fine subclones for segmentation. To infer the CNV segmentation landscape, a novel change rate-based across-cell breakpoint identification approach is specifically designed to diminish the effects of low coverage and data variability on a per-cell basis. Finally, a consensus segmentation is utilized to further standardize read depth for the inference of the final CNV profile. In comprehensive benchmarking experiments, where we compared CNVeil with seven state-of-the-art CNV detection tools, CNVeil exhibited exceptional performance across a diverse set of simulated and real scDNA-seq data in cancer genomics. CNVeil excelled in subclone identification, segmentation, and CNV profiling. In light of these results, we anticipate that CNVeil will significantly contribute to single-cell CNV analysis, offering enhanced insights into chromosomal aberrations and genomic complexity.

bioinformatics↗

bioRxiv2024

Molecular and Cellular Mechanisms of Teneurin Signaling in Synaptic Partner Matching

In developing brains, axons exhibit remarkable precision in selecting synaptic partners among many non-partner cells. Evolutionally conserved teneurins were the first identified transmembrane proteins that instruct synaptic partner matching. However, how intracellular signaling pathways execute teneurins functions is unclear. Here, we use in situ proximity labeling to obtain the intracellular interactome of teneurin (Ten-m) in the Drosophila brain. Genetic interaction studies using quantitative partner matching assays in both olfactory receptor neurons (ORNs) and projection neurons (PNs) reveal a common pathway: Ten-m binds to and negatively regulates a RhoGAP, thus activating the Rac1 small GTPases to promote synaptic partner matching. Developmental analyses with single-axon resolution identify the cellular mechanism of synaptic partner matching: Ten-m signaling promotes local F-actin levels and stabilizes ORN axon branches that contact partner PN dendrites. Combining spatial proteomics and high-resolution phenotypic analyses, this study advanced our understanding of both cellular and molecular mechanisms of synaptic partner matching. HIGHLIGHTSO_LIIn situ spatial proteomics reveal the first intracellular interactome of teneurins C_LIO_LITen-m signals via a RhoGAP and Rac1 GTPase to regulate synaptic partner matching C_LIO_LISingle-axon analyses reveal a stabilization-upon-contact model for partner matching C_LIO_LITen-m signaling promotes F-actin in axon branches contacting partner dendrites C_LI

neuroscience↗

bioRxiv2024

Interplay between Mg2+ and Ca2+ at multiple sites of the ryanodine receptor

RyR1 is an intracellular Ca2+ channel important in excitable cells. Ca2+ activates it at low concentrations and inhibits it at high concentrations. Mg2+ is the main physiological RyR1 inhibitor, an effect that is overridden upon activation. Despite the significance of Mg2+-mediated inhibition, the molecular-level mechanisms remain unclear. We determined two cryo-EM structures of RyR1 with Mg2+ up to 2.8 [A] resolution, identifying multiple Mg2+ binding sites. Mg2+ inhibits at the known Ca2+ activating site and we propose that the EF hand domain is an inhibitory divalent cation sensor. Both divalent cations bind to ATP within a crevice, contributing to the precise transmission of allosteric changes within the enormous channel protein. Notably, Mg2+ inhibits RyR1 by interacting with the gating helices as validated by molecular dynamics. This structural insight enhances our understanding of how Mg2+ inhibition is overcome during excitation.

biophysics↗

bioRxiv2024

Enhanced Protein-Protein Interaction Discovery via AlphaFold-Multimer

Accurately mapping protein-protein interactions (PPIs) is critical for elucidating cellular functions and has significant implications for health and disease. Conventional experimental approaches, while foundational, often fall short in capturing direct, dynamic interactions, especially those with transient or small interfaces. Our study leverages AlphaFold-Multimer (AFM) to re-evaluate high-confidence PPI datasets from Drosophila and human. Our analysis uncovers a significant limitation of the AFM-derived interface pTM (ipTM) metric, which, while reflective of structural integrity, can miss physiologically relevant interactions at small interfaces or within flexible regions. To bridge this gap, we introduce the Local Interaction Score (LIS), derived from AFMs Predicted Aligned Error (PAE), focusing on areas with low PAE values, indicative of the high confidence in interaction predictions. The LIS method demonstrates enhanced sensitivity in detecting PPIs, particularly among those that involve flexible and small interfaces. By applying LIS to large-scale Drosophila datasets, we enhance the detection of direct interactions. Moreover, we present FlyPredictome, an online platform that integrates our AFM-based predictions with additional information such as gene expression correlations and subcellular localization predictions. This study not only improves upon AFMs utility in PPI prediction but also highlights the potential of computational methods to complement and enhance experimental approaches in the identification of PPI networks.

bioinformatics↗

bioRxiv2024

Visualizing the M2 muscarinic acetylcholine receptor activation regulated by aromatic ring dynamics

A detailed molecular understanding of the G-protein coupled receptor (GPCR) activation mechanism is crucial for rational drug design. Despite the growing number of GPCR structures being resolved in the inactive and activated states, the detailed molecular mechanism of how receptors transits from the inactive towards the active one upon agonist binding remains to be further understood. Herein, we performed comprehensive atomic-level simulations of the M2 muscarinic receptor (M2R) to determine how ligand binding modulates the receptor conformational dynamics. The results reveal that aromatic residue dynamics are closely associated with receptor activation. Binding of antagonists or agonists differentially alters the interacting patterns of critical aromatic residues, stabilizing them into distinct conformations. In addition, we found that the change of interaction and dynamics of the W4006.48-F3966.44 pair at the transmembrane core plays an essential role in the structural transition of M2R from the inactive state into an active-like state induced by binding of the supra-physiological agonist iperoxo. Moreover, we found that the sidechain dynamics of Y2065.58 is important in modulating the conformation of the intracellular cavity. Our work highlights the role of protein conformational dynamics in M2R activation, and provides new insights for future drug designs.

biochemistry↗

bioRxiv2024

R-Loop Functions in Brca1-Associated Mammary Tumorigenesis

Excessive R-loops, a DNA-RNA hybrid structure, are associated with genome instability and BRCA1 mutation-related breast cancer. Yet the causality of R-loops in tumorigenesis remains unclear. Here we show that R-loop removal by Rnaseh1 overexpression (Rh1-OE) in Brca1-knockout (BKO) mouse mammary epithelium exacerbates DNA replication stress without affecting homology-directed DNA repair. R-loop removal also diminishes luminal progenitors, the cell of origin for estrogen receptor (ER)-negative BKO tumors. However, R-loop reduction does not dampen spontaneous BKO tumor incidence. Rather, it gives rise to a significant percentage of ER-expressing BKO tumors. Thus, R-loops reshape mammary tumor subtype rather than promoting tumorigenesis.

cancer biology↗

bioRxiv2024

BayVarC: an ultra-sensitive ctDNA variant caller using Bayesian approach

In liquid biopsy, it is critical to detect variants of allele frequencies as low as 0.1% or even lower, especially when used to monitor secondary resistant mutations and minimal residual disease. Despite the efforts on improving experimental design, it remains challenging to distinguish low-frequency variants from technical noises in the downstream bioinformatic analysis. Here, we introduce BayVarC, a novel variant caller specifically designed for variant calling in liquid biopsy. It applies Bayesian inference to accurately quantify noise level in a locus-specific manner, enabling the discrimination between technical noise and low-frequency cancer variants. Detailed in-silico simulation and in-vitro experiments demonstrated BayVarC superior performance over existing state-of-the-art tools. BayVarC can effectively detect low frequency variants while maintaining low false positive rate (0.05 FP/KB). Meanwhile, it achieves Limit of Detection (LoD) as low as 0.1%. Furthermore, empowered by its architecture, BayVarC shows promising applicability in Minimal Residual Disease (MRD) detection. BayVarC is freely available at https://github.com/GenetronBioinfomatics/BayVarC.

bioinformatics↗

bioRxiv2024

Neural ensembles that encode affective mechanical and heat pain in mouse spinal cord

Acute pain is an unpleasant experience caused by noxious stimuli. How the spinal neural circuits attribute differences in quality of noxious information remains unknown. By means of genetic capturing, activity manipulation and single cell RNA sequencing, we identified distinct neural ensembles in mouse spinal cord encoding mechanical and heat pain. Re-activation or silencing of these ensembles potentiated or stopped, respectively, affective but not reflex behaviour without altering pain behaviour to cross stimuli modality. Within ensembles, polymodal Gal+ inhibitory neurons with monosynaptic contacts to A-fiber sensory neurons gated affective pain independent of modality. Peripheral nerve injury led to microglia driven inflammation and an ensemble transition with decreased recruitment of Gal+ inhibitory neurons and increased excitatory drive. However, activating Gal+ neurons reversed hypersensitivity associated with neuropathy. Our results reveal the existence of a spinal representation which forms the neural basis of the discriminative and affective qualities of acute pain and that these neurons are under the control of a shared feed-forward inhibition.

neuroscience↗