Biology subjects

Yuan, Y.

Publications and source records attributed to Yuan, Y..

At least 109 records · Page 6Linked to original sources

bioRxiv2024

HumanTestisDB: A Comprehensive Atlas of Testicular Transcriptomics and Cellular Interactions

Advances in single-cell technology have enabled the detailed mapping of testicular cell transcriptomes, which is essential for understanding spermatogenesis. However, the fragmented nature of age-specific data from various literature sources has hindered comprehensive analysis. To overcome this, the Human Testis Database (HumanTestisDB) was developed, consolidating multiple human testicular sequencing datasets to address this limitation. Through extensive investigation, 38 unique cell types were identified, providing a detailed perspective on cellular variety. Furthermore, the database systematically categorizes samples into eight developmental stages, offering a structured framework to comprehend the temporal dynamics of testicular development. Each stage features comprehensive maps of cell-cell interactions, elucidating the complex communication network inside the testicular microenvironment at particular developmental stages. Moreover, by facilitating comparisons of interactions among various cell types at different stages, the database permits examining alterations that transpire during critical transitions in spermatogenesis. HumanTestisDB, available at https://shalab.njmu.edu.cn/humantestisdb, offers vital insights into testicular transcriptomics and interactions, serving as an essential resource for advancing research in reproductive biology.

cell biology↗

bioRxiv2024

DGRNA: a long-context RNA foundation model with bidirectional attention Mamba2

Ribonucleic acid (RNA) is an important biomolecule with diverse functions i.e. genetic information transfer, regulation of gene expression and cellular functions. In recent years, the rapid development of sequencing technology has significantly enhanced our understanding of RNA biology and advanced RNA-based therapies, resulting in a huge volume of RNA data. Data-driven methods, particularly unsupervised large language models, have been used to automatically hidden semantic information from these RNA data. Current RNA large language models are primarily based on Transformer architecture, which cannot efficiently process long RNA sequences, while the Mamba architecture can effectively alleviate the quadratic complexity associated with Transformers. In this study, we propose a large foundational model DGRNA based on the bidirectional Mamba trained on 100 million RNA sequences, which has demonstrated exceptional performance across six RNA downstream tasks compared to existing RNA language models.

bioinformatics↗

bioRxiv2024

A tumor-secreted protein utilizes glucagon release to cause host wasting

Tumor-host interaction plays a critical role in malignant tumor-induced organ wasting across multiple species. Despite known regulation of regional wasting of individual peripheral organs by tumors, whether and how tumors utilize critical host catabolic hormone(s) to simultaneously induce systemic host wasting, however, is largely unknown. Using the conserved yki3SA-tumor model in Drosophila, we discovered that tumors increase the production of adipokinetic hormone (Akh), a glucagon-like catabolic hormone, to cause systemic host wasting, including muscle dysfunction, lipid loss, hyperglycemia, and ovary atrophy. We next integrated RNAi screening and Gal4-LexA dual expression system to identify that yki3SA-gut tumors secrete Pvf1 to remotely activate its receptor Pvr in Akh-producing cells (APCs), ultimately promoting Akh production. The underlying molecular mechanisms involved the Pvf1-Pvr axis that triggers Mmp2-dependent ECM remodeling of APCs and enhances innervation from the excitatory cholinergic neurons. Interestingly, we also confirmed the similar mechanisms governing tumor-induced glucagon release and organ wasting in mammals. Blockade of either glucagon or PDGFR (homolog of Pvr) action efficiently ameliorated organ wasting in the presence of malignant tumors. Therefore, our results demonstrate that tumors remotely promote neural-associated Akh/glucagon production via Pvf1-Pvr axis to cause systemic host wasting.

physiology↗

bioRxiv2024

Targeted, high-resolution sensing of volatile organic compounds by covalent nanopore detection

Volatile organic compounds are choice analytes in a variety of contexts. For example, humans release over 4000 volatile organic compounds, many of which are diagnostic of life-threatening medical conditions. A combination of a large number of potential analytes requires the application of costly, cumbersome technology. Here, we show that covalent nanopore sensing can be used for the targeted detection of a reduced set of analytes in a mixture: in this case aldehydes, which constitute [~]5% of human volatiles. Further, nanopore engineering permits high-resolution detection, which allows closely related aldehydes including isomers to be distinguished. Differential sensing of other chemical classes, such as alcohols, is demonstrated by leveraging their enzymatic conversion to aldehydes. Our approach is compatible with the use of cheap, portable, user-friendly diagnostic devices applicable to a wide variety of objectives, including pollutant monitoring, food and beverage testing and the quality control of pharmaceuticals, as well as disease diagnostics.

biochemistry↗

bioRxiv2024

Targeting long non-coding RNA RP11-502I4.3 delays the trend of angiogenesis in diabetic retinopathy

Based on our previous findings, we hypothesized that the long non-coding RNA RP11-502I4.3 may be involved in angiogenesis associated with Diabetic retinopathy (DR). We investigated the role of RP11-502I4.3 in DR by examining its regulation of vascular endothelial growth factor (VEGF). We assessed differences in RP11-502I4.3 expression between the normal control group and streptozotocin-induced diabetic rats or high glucose (HG)-stimulated human retinal microvascular endothelial cells (HRMECs). VEGF expression was measured with and without lentiviral vectors overexpressing RP11-502I4.3. We analyzed the structural and functional alterations related to DR. Our analysis revealed that RP11-502I4.3 expression was lower in the retinas of diabetic rats and in HG-stimulated HRMECs compared with normal glucose conditions. Overexpressing of RP11-502I4.3 resulted in decreased VEGF levels. Diabetic rats exhibited retinopathy characterized by thinning of the retinal layer thickness, structural changes in the inner and outer nuclear layers, a reduced count of retinal ganglion cells, and the presence of acellular capillaries. The proliferative activity, migration count, and tube formation ability of HG-treated HRMECs were significantly higher than those of the normal control group; however, these changes were delayed by RP11-502I4.3 overexpression. RP11-502I4.3 downregulation in DR appears to promote angiogenesis.

zoology↗

bioRxiv2024

DDX3 regulates the cap-independent translation of the Japanese encephalitis virus via its interactions with PABP1 and the untranslated regions of the viral genome

The translation of global cellular proteins is almost completely repressed in cells with flavivirus infection, while viral translation remains efficient. The mechanisms of flaviviruses evade host translational shutoff are largely unknown. Here, we identified viral elements and host factors associated with JEV evasion of host shutoff. JEV 5'UTR lacked IRES or IRES-like activity, while noncapped 5'UTR initiated translation in the presence of 3'UTR. Furthermore, the elements DB2 and sHP-SL within 3'UTR were involved in the regulation of cap-independent translation, which is conserved in the genus Orthoflavivirus. By RNA affinity purification and mass spectrometry analysis, cellular DDX3 and PABP1 were identified as key factors in regulating cap-independent translation of JEV via their interactions with DB2 and sHP-SL RNA structures. Mechanistically, we revealed that DDX3 could bind to both 5'UTR and 3'UTR of the JEV genome to establish a closed-loop architecture, recruit eIF4G/eIF4A to form the DDX3/PABP1/eIF4G/eIF4A tetrameric complex via its interaction with PABP1, thereby recruiting 43S PIC to the 5'-end of the JEV genome to start translation. Our findings demonstrated a noncanonical translation strategy employed by JEV and further revealed the regulatory roles of DDX3 and PABP1 in this mechanism. These results expand our knowledge of the translation initiation regulation in flaviviruses under the state of host translational shutoff, which provides a conserved antiviral target against orthoflavivirus.

microbiology↗

bioRxiv2024

Microscopic deconstruction of cortical circuit stimulation by transcranial ultrasound

Transcranial Ultrasound Stimulation (TUS) can noninvasively and reversibly perturb neuronal activity, but the mechanisms by which ultrasound engages brain circuits to induce functional effects remain unclear. To elucidate these interactions, we applied TUS to the cortex of awake mice and concurrently monitored local neural activity at the acoustic focus with two-photon calcium imaging. We show that TUS evokes highly focal responses in three canonical neuronal populations, with cell-type-specific dose dependencies. Through independent parametric variations, we demonstrate that evoked responses collectively scale with the time-average intensity of the stimulus. Finally, using computational unmixing we propose a physiologically realistic cortical circuit model that predicts TUS-evoked responses as a result of both direct effects and local network interactions. Our results provide a first direct evidence of TUSs focal effects on cortical activity and shed light on the complex circuit mechanisms underlying these effects, paving the way for TUSs deployment in clinical settings.

neuroscience↗

bioRxiv2024

Deciphering gene regulatory programs in mouse embryonic skin through single-cell multiomics analysis

BackgroundCell type-specific transcriptional heterogeneity in embryonic mouse skin is well-documented, but few studies have investigated the regulatory mechanisms. ResultsHere, we present high throughput single-cell chromatin accessibility and transcriptome sequencing (HT-scCAT-seq), a method that simultaneously profiles transcriptome and chromatin accessibility. We utilized HT-scCAT-seq to dissect the gene regulatory mechanism governing epidermal stratification, periderm terminal differentiation, and fibroblast specification. ConclusionsBy linking chromatin accessibility to gene expression, we identified candidate cis-regulatory elements (cCREs) and target genes crucial for dermal and epidermal development. We described cells with similar gene expression profiles that exhibit distinct chromatin accessibility statuses during periderm terminal differentiation. Finally, we characterized the underlying lineage-determining transcription factors (TFs), and demonstrated that ALX4 and RUNX2 were candidate TF regulators of the dermal papilla lineage development through in silico perturbation analysis.

developmental biology↗

bioRxiv2024

Engineered Whole Lungs for Tissue Biology

End-stage lung disease and lung cancer significantly contribute to global mortality, necessitating new research strategies for studying pulmonary biology. Here, we present an engineered whole-lung tissue model used to evaluate the effects of cellular communities on tissue organization and alveolar barrier function. Engineered lungs were grown ex vivo on decellularized whole-lung matrices as structurally biomimetic, bioactive scaffolds. Histologic architecture of engineered lungs improved with the addition of alveolar macrophages, coming to resemble neonatal lung. Incorporating alveolar macrophages maximized the differentiation of native-like cellular communities, including alveolar type I-like epithelium, bronchioalveolar stem cells, microvascular endothelium, and pericytes. Cell-cell signaling in engineered lungs showed activation of developmental and inflammatory pathways, including WNT, Notch, and FGF signaling pathways. Engineered lungs containing alveolar macrophages showed a 668% improvement in measured alveolar barrier function. This work demonstrates the potential utility of engineered lung models for studying principles of tissue biology and pulmonary regeneration.

bioengineering↗

bioRxiv2024

Ultrasensitive in vivo infrared spectroscopic imaging via oblique photothermal microscopy

In vivo IR spectroscopy faces challenges due to poor sensitivity in reflection mode and low resolution at micrometer scale. To break this barrier, we report an oblique photothermal microscope (OPTM) to enable ultrasensitive IR spectroscopic imaging of live subjects at sub-micron resolution. Classic photothermal measurement captures only a small fraction of probe photons through a pinhole to extract the photothermal signal. Instead, OPTM uses a differential split detector placed on the sample surface to collect 500-fold more photons and suppress the laser noise by 12 fold via balanced detection. Leveraging its improved sensitivity, OPTM enables low-dose IR imaging of skin without photodamage. Depth-resolved in vivo OPTM imaging of metabolic markers beneath mouse and human skin is shown. Furthermore, we demonstrate in vivo OPTM tracking of topical drug contents within mouse and human skin. Collectively, OPTM presents a highly sensitive imaging platform for in vivo and in situ molecular analysis.

bioengineering↗

bioRxiv2024

An improved TEAD dominant-negative protein inhibitor to study Hippo YAP1/TAZ-dependent transcription.

Hippo signaling is one of the top pathways altered in human cancer, and intensive focus has been devoted to developing therapies targeting Hippo-dependent transcription mediated by YAP1 and TAZ interaction with TEAD proteins. However, a significant challenge in evaluating the efficacy of these approaches is the lack of models that can precisely characterize the consequences of TEAD inhibition. To address this gap, our laboratory developed a strategy that utilizes a fluorescently traceable, dominant-negative protein named TEADi. TEADi specifically blocks the nuclear interactions of TEAD with YAP1 and TAZ, enabling precise dissection of Hippo TEAD-dependent and independent effects on cell fate. In this study, we aimed to enhance TEADi effectiveness by altering post-transcriptional modification sites within its TEAD-binding domains (TBDs). We demonstrate that a D93E mutation in the YAP1 TBD significantly increases TEADi inhibitory capacity. Additionally, we find that TBDs derived from VGLL4 and YAP1 are insufficient to block TAZ-induced TEAD activity, revealing crucial differences in YAP1 and TAZ displacement mechanisms by dominant-negative TBDs. Structural differences in YAP1 and TAZ TBDs were also identified, which may contribute to the distinct binding of these proteins to TEAD. Our findings expand our understanding of TEAD regulation and highlight the potential of an optimized TEADi as a more potent, specific, and versatile tool for studying TEAD-transcriptional activity.

cell biology↗

bioRxiv2024

Single-cell proteomics of pre-implantation mouse embryos uncovers distinct asymmetry of certain proteins among early blastomeres

During pre-implantation mouse embryonic development, blastomeres undergo division and differentiation, reaching a distinctive level of heterogeneity, hence the completion of the first cell fate determination. However, when the initial asymmetry emerges and how this heterogeneity amplifies, particularly at the protein level, remain elusive. Here, by mass spectrometry-based single-blastomere proteomics, we identified proteins exhibiting significant heterogeneity in abundance among mouse blastomeres as early as the 2-cell stage. Differential gene expression among blastomeres, as indicated by intra-embryo variation in RNA abundance detected through single-cell RNA sequencing, was insufficient to fully explain the corresponding disparities in protein abundance. Instead, the asymmetric distribution of protein molecules during cell division was observed, serving as another mechanism contributing to protein heterogeneity, independent of RNA expression.

developmental biology↗

bioRxiv2024

stFormer: a foundation model for spatial transcriptomics

Recent foundation models for single-cell transcriptomics data generate informative, context-aware representations for genes and cells. The Spatial Transcriptomics (ST) data offer extra positional insights, which were not considered by these single-cell models. Here, we introduce stFormer, a transformer model tailored for ST data. stFormer employs the cross-attention module to incorporate spatial ligand genes into the transformer encoder of single-cell transcriptomics. To unify different ST technologies with trade-off between resolution and gene coverage, we propose a biased cross-attention method that enables the model to do learning with single-cell resolution on whole-transcriptome but low-resolution Visium data. We collected human Visium datasets from a public ST database and performed cell type deconvolution, generating ~4.1 million pretraining samples. As a foundation model for ST data, stFormer improved performance upon the state-of-the-art single-cell foundation model, scFoundation, across a variety of tasks, including cell clustering, batch effect correction, cell type prediction, and gene function prediction. stFormer also revealed intercellular ligand-receptor signaling responses via in silico perturbation.

bioinformatics↗

bioRxiv2024

Direct Nuclear Delivery of Proteins on Living Plant via Partial Enzymatic Cell Wall Digestion

While many variations of protein delivery methods have been described, it can still be difficult or inefficient to introduce exogenous proteins into plants. A major barrier to progress is the cell wall which is primarily composed of polysaccharides and thus only permeable to small molecules. Here, we report a partial enzymatic cell wall digestion-mediated uptake method that efficiently delivers protein into the nucleus of plant cells. Such a method allowed efficient nuclear delivery of GFP proteins into Arabidopsis root cells throughout all cell layers. This study establishes that a partial enzymatic cell wall degradation could enable a myriad of plant biotechnology applications that rely on functional protein delivery into walled plant cells.

bioengineering↗

bioRxiv2024

A flexible high-precision photoacoustic retinal prosthesis

Retinal degenerative diseases of photoreceptors are a leading cause of blindness with no effective treatment. Retinal prostheses aim to restore sight by stimulating residual retinal cells. Here, we present a photoacoustic retinal stimulation technology. We designed a polydimethylsiloxane and carbon-based flexible film that converts near-infrared laser pulses into a localized acoustic field with 56-{micro}m lateral resolution, allowing precise stimulation of mechanosensitive retinal cells. This photoacoustic stimulation robustly and locally modulated retinal ganglion cell activity in both wild-type and degenerated ex vivo rat retinae. In animals subretinally implanted with a millimeter-sized photoacoustic film, pulsed laser stimulation generated neural modulation along the visual pathway to the superior colliculus, as measured by functional ultrasound imaging. The biosafety of the film was confirmed by the absence of short-term adverse effects , while local thermal increases were measured below 1 {degrees}C. These findings demonstrate the potential of photoacoustic stimulation for high-acuity visual restoration in blind patients.

neuroscience↗

bioRxiv2024

Deep contrastive learning enables genome-wide virtual screening

Numerous protein-coding genes are associated with human diseases, yet approximately 90% of them lack targeted therapeutic intervention. While conventional computational methods, such as molecular docking, have facilitated the discovery of potential hit compounds, the development of genome-wide virtual screening against the expansive chemical space remains a formidable challenge. Here we introduce DrugCLIP, a novel framework that combines contrastive learning and dense retrieval to achieve rapid and accurate virtual screening. Compared to traditional docking methods, DrugCLIP improves the speed of virtual screening by up to seven orders of magnitude. In terms of performance, DrugCLIP not only surpasses docking and other deep learning-based methods across two standard benchmark datasets, but also demonstrates high efficacy in wet-lab experiments. Specifically, DrugCLIP successfully identified agonists with < 100 nM affinities for 5HT2AR, a key target in psychiatric diseases. For another target NET, whose structure is newly solved and not included in the training set, our method achieved a hit rate of 15%, with 12 diverse molecules exhibiting affinities better than bupropion. Additionally, two chemically novel inhibitors were validated by structure determination with Cryo-EM. Finally, a novel potential drug target TRIP12, with no experimental structures and inhibitors for reference, was used to challenge DrugCLIP. DrugCLIP achieved a hit rate of 17.5% by screening a pocket identified on an AlphaFold2-predicted structure, verified with multi-cycle SPR assays. Molecules with the highest affinities also showed a dose-dependent inhibition to the enzymatic function of TRIP12. Building on this foundation, we present the results of a pioneering trillion-scale genome-wide virtual screening, encompassing approximately 10,000 AlphaFold2 predicted proteins within the human genome and 500 million molecules from the ZINC and Enamine REAL database. This work provides an innovative perspective on drug discovery in the post-AlphaFold era, where comprehensive targeting of all disease-related proteins is within reach.

bioinformatics↗

bioRxiv2024

PoweREST: Statistical Power Estimation for Spatial Transcriptomics Experiments to Detect Differentially Expressed Genes Between Two Conditions

Recent advancements in Spatial Transcriptomics (ST) have significantly enhanced biological research in various domains. However, the high cost of current ST data generation techniques restricts its application in large-scale population studies. Consequently, there is a pressing need to maximize the use of available resources to achieve robust statistical power. One fundamental question in ST analysis is to detect differentially expressed genes (DEGs) among different conditions using ST data. Such DEG analysis is often performed but the associated power calculation is rarely discussed in the literature. To address this gap, we introduce, PoweREST (https://github.com/lanshui98/PoweREST), a power estimation tool designed to support power calculation of DEG detection with 10X Genomics Visium data. PoweREST enables power estimation both before any ST experiments or after preliminary data are collected, making it suitable for a wide variety of power analyses in ST studies. We also provide a user-friendly, program-free web application (https://lanshui.shinyapps.io/PoweREST/), allowing users to interactively calculate and visualize the study power along with relevant the parameters.

bioinformatics↗

bioRxiv2024

Multimodal Protein-Ligand Contrastive Pretraining for Effective and Efficient Drug Discovery

Recent advancements in genomics and proteomics have identified numerous clinically significant protein targets, with notably 85% categorized as undruggable. These targets present widespread challenges due to their complex structures and dynamics, rendering conventional drug design strategies not always effective. In this study, we introduce Uni-Clip, a contrastive learning framework that incorporates multi-modal features of proteins (structure and residue) and ligands (conformation and graph). Optimized with a specifically designed CF-InfoNCE loss, Uni-Clip enhances the modeling of protein-ligand interactions for both undruggable and druggable proteins. Uni-Clip demonstrates superior performance in benchmark evaluations on widely acknowledged datasets, LIT-PCBA and DUD-E, achieving a 147% and 218% improvements in enrichment factors at 1% compared to baselines. Furthermore, Uni-Clip proves to be a practical tool for various drug discovery applications. In virtual screening for the challenging protein target GPX4 with flat surface, it identified non-covalent inhibitors with an IC50 of 4.17 M, in contrast to the predominantly covalent inhibitors currently known. Through target fishing for benzbromarone, Uni-Clip identified the intrinsically disordered protein c-Myc as a potential target, highlighting benzbromarones potential for repurposing in cancer therapy. Explainable analyses effectively identified binding sites consistent with molecular dynamics and experimental results, even for challenging undruggable targets.

bioinformatics↗