Biology subjects

Liao, S.

Publications and source records attributed to Liao, S..

At least 37 records · Page 2Linked to original sources

bioRxiv2024

Proteolysis-targeting vaccines (PROTAVs) for robust tumor combination immunotherapy

Protein/peptide subunit vaccines are promising to promote the tumor therapeutic efficacy of immune checkpoint blockade (ICB). However, current protein/peptide vaccines elicit limited antitumor T cell responses, leading to suboptimal therapeutic efficacy. Here, we present proteolysis-targeting vaccines (PROTAVs) that facilitate antigen proteolytic processing and cross-presentation to potentiate T cell responses for robust ICB combination immunotherapy of melanoma. PROTAVs are modular conjugates of protein/peptide antigens, E3 ligase-binding ligands, and linkers. In antigen-presenting cells (APCs), PROTAVs bind to E3 ligases to rapidly ubiquitinate PROTAV antigens, facilitating antigen proteolytic processing by proteasome, and thereby promoting antigen cross-presentation to T cells and potentiating CD8+ T cell responses. We developed a melanoma PROTAV using a tandem peptide of trivalent melanoma-associated antigens. Co-delivered by lipid nanoparticles (LNPs) with bivalent immunostimulant adjuvants, this PROTAV promotes the quantity and quality of melanoma-specific CD8+ T cells in mice. Further, combining PROTAV and ICB ameliorates the immunosuppressive melanoma microenvironment. As a result, PROTAV and ICB combination enhances melanoma complete regression rates and eradicated 100% large BrafV600E melanoma without recurrence in syngeneic mice. PROTAVs hold the potential for robust tumor combination immunotherapy.

bioengineering↗

bioRxiv2024

Pdgfab/Pdgfra-mediated chemoattraction guides the migration of sclerotome-derived fibroblast precursors in zebrafish

In vertebrates, the sclerotome is a transient embryonic structure that gives rise to various tissue support cells, including fibroblasts. However, how fibroblast precursors are guided to diverse tissues remain poorly understood. Using zebrafish, our lab has previously shown that sclerotome-derived cells undergo extensive migration to generate distinct fibroblasts subtypes, including tenocytes along the myotendinous junction and fin mesenchymal cells in the fin fold. Interestingly, the pan-fibroblast gene platelet-derived growth factor receptor a (pdgfra), which has been implicated in cell migration across various contexts, is specifically expressed in the sclerotome and its descendants. Loss of functional Pdgfra in a pdgfra gene-trap mutant results in severe defects in the migration of sclerotome- derived cells, leading to a dose-dependent loss of tenocytes and fin mesenchymal cells. By combining live imaging and mosaic labeling with a membrane-bound dominant-negative tool, we demonstrate that Pdgfra acts cell-autonomously to regulate the migration of sclerotome- derived cells. In the absence of ligand pdgfab, which is expressed in the medial somite, sclerotome-derived cells fail to migrate medially, resulting in a loss of tenocytes, although they can migrate normally toward the fin fold and generate fin mesenchymal cells. Strikingly, localized expression of Pdgfab in pdgfab mutants can direct the migration of sclerotome- derived cells to both normal and ectopic locations, suggesting a chemoattractive role for the Pdgfab ligand. Together, our results demonstrate that Pdgfab/Pdgfra-mediated chemoattraction guides the migration of sclerotome-derived fibroblast precursors to specific locations, where they diversify into distinct fibroblast subtypes.

developmental biology↗

bioRxiv2024

Structures of Epstein-Barr virus and Kaposi's sarcoma-associated herpesvirus virions reveal species-specific tegument and envelope features

Epstein-Barr virus (EBV) and Kaposis sarcoma-associated herpesvirus (KSHV) are classified into the gammaherpesvirus subfamily of Herpesviridae, which stands out from its alpha- and betaherpesvirus relatives due to the tumorigenicity of its members. Although structures of human alpha- and betaherpesviruses by cryogenic electron tomography (cryoET) have been reported, reconstructions of intact human gammaherpesvirus virions remain elusive. Here, we structurally characterize extracellular virions of EBV and KSHV by deep learning-enhanced cryoET, resolving both previously known monomorphic capsid structures and previously unknown pleomorphic features beyond the capsid. Through subtomogram averaging and subsequent tomogram-guided sub-particle reconstruction, we determined the orientation of KSHV nucleocapsids from mature virions with respect to the portal to provide spatial context for the tegument within the virion. Both EBV and KSHV have an eccentric capsid position and polarized distribution of tegument. Tegument species span from the capsid to the envelope and may serve as scaffolds for tegumentation and envelopment. The envelopes of EBV and KSHV are less densely populated with glycoproteins than those of herpes simplex virus 1 and human cytomegalovirus, representative members of alpha- and betaherpesviruses, respectively. This population density of glycoproteins correlates with their relative infectivity against HEK293T cells. Also, we observed fusion protein gB trimers exist within triplet arrangements in addition to standalone complexes, which is relevant to understanding dynamic processes such as fusion pore formation. Taken together, this study reveals nuanced yet important differences in the tegument and envelope architectures among human herpesviruses and provides insights into their varied cell tropism and infection. ImportanceDiscovered in 1964, Epstein-Barr virus (EBV) is the first identified human oncogenic virus and the founding member of the gammaherpesvirus subfamily. In 1994, another cancer-causing virus was discovered in lesions of AIDS patients and later named Kaposis sarcoma-associated herpesvirus (KSHV), the second human gammaherpesvirus. Despite the historical importance of EBV and KSHV, technical difficulties with isolating large quantities of these viruses and the pleiomorphic nature of their envelope and tegument layers have limited structural characterization of their virions. In this study, we employed the latest technologies in cryogenic electron microscopy (cryoEM) and tomography (cryoET) supplemented with an artificial intelligence-powered data processing software package to reconstruct 3D structures of the EBV and KSHV virions. We uncovered unique properties of the envelope glycoproteins and tegument layers of both EBV and KSHV. Comparison of these features with their non-tumorigenic counterparts provides insights into their relevance during infection.

microbiology↗

bioRxiv2024

SCIITensor: A tensor decomposition based algorithm to construct actionable TME modules with spatially resolved intercellular communications

Advanced spatial transcriptomics (ST) technology has paved the way for elucidating the spatial architecture of the tumor microenvironment (TME) from multiple perspectives. However, available tools only focus on the static molecular and cellular composition of the TME when analyzing the high-throughput ST data, neglecting to uncover the in-depth spatial co-variation of intercellular communications arising from heterogeneous spatial TMEs. Here, we introduce SCIITensor, which decomposes TME modules from the perspective of spatially resolved intercellular communication by spatially quantifying the cellular and molecular interaction intensities between proximal cells within each domain. It then constructs a three-dimensional matrix, formulating the task as a matrix decomposition problem, and identifies biologically relevant spatial interactions and TME patterns using Non-Negative Tucker Decomposition (NTD). We evaluated the performance of SCIITensor on liver cancer datasets obtained from multiple ST platforms. At the research setting of a single-sample investigation, SCIITensor precisely identified a functional TME module indicating a tumor boundary structure specific domain with co-variant interaction contexts, which were involved in construction of immunosuppressive TME. Moreover, we also proved that SCIITensor was able to construct TME meta-modules across multiple samples and to further identify an immune-infiltration associated and sample-common meta-module. We demonstrate that SCIITensor is applicable for dissecting TME modules from a new perspective by constructing spatial interaction contexts using ST datasets of individual and multiple samples, providing new insights into tumor research and potential therapeutic targets.

bioinformatics↗

bioRxiv2024

StereoMM: A Graph Fusion Model for Integrating Spatial Transcriptomic Data and Pathological Images

Spatially resolved omics technologies generating multimodal and high-throughput data lead to the urgent need for advanced analysis to allow the biological discoveries by comprehensively utilizing information from multi-omics data. The H&E image and spatial transcriptomic data indicate abundant features which are different and complementary to each other. AI algorithms can perform nonlinear analysis on these aligned or unaligned complex datasets to decode tumoral heterogeneity for detecting functional domain. However,the interpretability of AI-generated outcomes for human experts is a problem hindering application of multi-modal analysis in clinic. We presented a machine learning based toolchain called StereoMM, which is a graph fusion model that can integrate gene expression, histological images, and spatial location. StereoMM firstly performs information interaction on transcriptomic and imaging features through the attention module, guaranteeing explanations for its decision-making processes. The interactive features are input into the graph autoencoder together with the graph of spatial position, so that multimodal features are fused in a self-supervised manner. Here, StereoMM was subjected to mouse brain tissue, demonstrating its capability to discern fine tissue architecture, while highlighting its advantage in computational speed. Utilizing data from Stereo-seq of human lung adenosquamous carcinoma and 10X Visium of human breast cancer, we showed its superior performance in spatial domain recognition over competing software and its ability to reveal tumor heterogeneity. The fusion approach for imaging and gene expression data within StereoMM aids in the more accurate identification of domains, unveils critical molecular features, and elucidates the connections between different domains, thereby laying the groundwork for downstream analysis.

bioinformatics↗

bioRxiv2024

Spatiotemporal transcriptomic profiling reveals the dynamic immunological landscape of alveolar echinococcosis

Alveolar echinococcosis (AE) is caused by the invasive growth of the metacestodes of Echinococcus multilocularis (E. multilocularis). The early diagnosis, management, and treatment of AE remains challenging. Herein, we integrated bulk RNA-seq, scRNA-seq, and ST technologies to reveal the immune characteristics both spatially and chronologically in E. multilocularis infected mouse liver. An unprecedented high-resolution spatial atlas of the E. multilocularis infection foci was obtained, revealing the pivotal role of neutrophils, Spp1+ monocyte-derived macrophages (MoMFs), and fibroblasts in AE progression. We observed continuous recruitment of neutrophils and macrophages into the infected tissues, indicating prolonged immune stimulation by the growing metacestodes. However, their spatial distribution patterns and functions changed during the infection cause. At the early infection stage, Il1bhi neutrophils aggregated in the lesion displayed the highest pattern-recognition receptor activity and may kill the metacestodes through NETosis, but their death in the infection foci might also trigger immune suppression. Meanwhile, Spp1+ MoMFs attached to the protoscoleces to clear the infection. At the late infection stage, the neutrophils failed to infiltrate into the lesion although their continuous recruitment into the infected liver. Even though the Spp1+ MoMFs enclosing the microcysts of E. multilocularis may retain their pathogen-killing ability, they may also promote fibrosis and angiogenesis through interaction with fibroblasts. The pro- and anti-inflammatory phenotype balance of these immune cells may be associated with the transition of parasite control strategy from "active killing" to "negative segregation" by the host. Our findings identify key molecular traits involved in AE development, which may benefit the treatment of echinococcosis.

immunology↗

bioRxiv2024

High performance TadA-8e derived cytosine and dual base editors with undetectable off-target effects in plants

Cytosine base editors (CBEs) and adenine base editors (ABEs) are powerful tools to install precise C-to-T and A-to-G base edits in living organisms. In recently years, a highly efficient ABE based on engineered TadA-8e, known as ABE8e, has been developed to confer highly efficient A-to-G editing in mammalian cells and plants. Interestingly, TadA-8e can be further evolved and engineered to confer cytosine base editing. In this study, we compare in rice and tomato cells a serial of engineered CBEs derived from TadA-8e and identify TadCBEa, TadCBEd, and TadCBEd_V106W as efficient CBEs with high editing purity, while maintaining the relatively narrow editing window of ABE8e. Excitingly, we show TadDE is a new class of dual base editor where a single deaminase domain promotes simultaneous C-to-T and A-to-G base editing in plant cells. Multiplexed base editing is demonstrated in transgenic rice plants with TadCBEa and TadDE. Furthermore, no off-target effects of TadCBEa and TadDE can be detected by whole genome and transcriptome sequencing of the transgenic lines, suggesting high editing specificity. Finally, we demonstrate two gain-of-function crop engineering applications in rice by using the efficient dual base editor, TadDE. In the first case, herbicide resistance alleles of OsALS are introduced by TadDE. In the second case, synonymous mutations are generated in OsSPL14, making its transcript resistant to OsMIR156-mediated degradation. Together, this study reports TadA-8e derived CBEs and a dual base editor with high editing activity, purity, and specificity. They are valuable additions to the expanding plant base editing toolbox.

molecular biology↗

bioRxiv2024

TomoNet: A streamlined cryoET software pipeline with automatic particle picking on flexible lattices

Cryogenic electron tomography (cryoET) is capable of determining in situ biological structures of molecular complexes at near atomic resolution by averaging half a million subtomograms. While abundant complexes/particles are often clustered in arrays, precisely locating and seamlessly averaging such particles across many tomograms present major challenges. Here, we developed TomoNet, a software package with a modern graphical user interface to carry out the entire pipeline of cryoET and subtomogram averaging to achieve high resolution. TomoNet features built-in automatic particle picking and 3D classification functions and integrates commonly used packages to streamline high-resolution subtomogram averaging for structures in one-, two- or three-dimensional arrays. Automatic particle picking is accomplished in two complementary ways: one based on template matching and the other employing deep learning. TomoNets hierarchical file organization and visual display facilitate efficient data management as required for large cryoET datasets. Applications of TomoNet to three types of datasets demonstrate its capability of efficient and accurate particle picking on flexible and imperfect lattices to obtain high-resolution 3D biological structures: virus-like particles, bacterial surface layers within cellular lamellae, and membranes decorated with nuclear egress protein complexes. These results demonstrate TomoNets potential for broad applications to various cryoET projects targeting high-resolution in situ structures.

cell biology↗

bioRxiv2023

Combining Bulk and Single-Cell RNA Sequencing Data to Identify RNA methylation and Autophagy-Related Signatures in Patients with Chronic Obstructive Pulmonary Disease

BackgroundChronic Obstructive Pulmonary Disease (COPD) is a heterogeneous lung condition associated with RNA methylation and autophagy. However, the specific autophagy-related genes and RNA methylation regulators involved in COPD development remain unknown. MethodsWe analyzed COPD and non-COPD patients datasets obtained from the Gene Expression Omnibus database, including Tissue Sequencing Transcriptome (bulk-seq) and single-cell sequencing (scRNA-seq) data. Differentially expressed genes (DEGs) were identified through differential genetic analysis using non-COPD bulk-seq data as the control group and COPD samples were used as the experimental group. Animal experiments were conducted to validate the expression of key genes. COPD model mice were exposed to smoke for four months, and lung function and histopathological changes were assessed. The mRNA and protein expression levels of FTO, IGF2BP2, DDIT3, DNAJB1, and YTHDF3 were measured using RT-qPCR and Western blotting, respectively. ResultsWe identified FTO, IGF2BP2, and YTHDF3 as key methylation genes, along with autophagy hub genes DDIT3 and DNAJB1. Animal experiments showed significantly increased mRNA and protein levels of FTO, YTHDF3 and DNAJB1 and significantly decreased levels of IGF2BP2 in lung tissue of COPD mice compared to the control group. ConclusionOur findings suggest that DDIT3 and DNAJB1 as autophagy hub genes, along with FTO, IGF2BP2 and YTHDF3 as RNA methylation genes, may play crucial roles in the development of COPD. These findings, supported by bulk-seq and scRNA-seq data, contribute novel genetic evidence for understanding the epigenetics of COPD.

cell biology↗

bioRxiv2023

SAW: An efficient and accurate data analysis workflow for Stereo-seq spatial transcriptomics

The basic analysis steps of spatial transcriptomics involve obtaining gene expression information from both space and cells. This process requires a set of tools to be completed, and existing tools face performance issues when dealing with large data sets. These issues include computationally intensive spatial localization, RNA genome alignment, and excessive memory usage in large chip scenarios. These problems affect the applicability and efficiency of the process. To address these issues, a high-performance and accurate spatial transcriptomics data analysis workflow called Stereo-Seq Analysis Workflow (SAW) has been developed for the Stereo-Seq technology developed by BGI. This workflow includes mRNA spatial position reconstruction, genome alignment, gene expression matrix generation and clustering, and generate results files in a universal format for subsequent personalized analysis. The excutation time for the entire analysis process is [~]148 minutes on 1G reads 1*1 cm chip test data, 1.8 times faster than unoptimized workflow.

bioinformatics↗

bioRxiv2023

EasyEyes - Accurate fixation for online vision testing of crowding and beyond

Online methods allow testing of larger, more diverse populations, with much less effort than in-lab testing. However, many psychophysical measurements, including visual crowding, require accurate eye fixation, which is classically achieved by testing only experienced observers who have learned to fixate reliably, or by using a gaze tracker to restrict testing to moments when fixation is accurate. Alas, both approaches are impractical online since online observers tend to be inexperienced, and online gaze tracking, using the built-in webcam, has a low precision ({+/-}4 deg, Papoutsaki et al., 2016). The EasyEyes open-source software reliably measures peripheral thresholds online with accurate fixation achieved in a novel way, without gaze tracking. EasyEyes tells observers to use the cursor to track a moving crosshair. At a random time during successful tracking, a brief target is presented in the periphery. The observer responds by identifying the target. To evaluate EasyEyes fixation accuracy and thresholds, we tested 12 naive observers in three ways in a counterbalanced order: first, in the lab, using gaze-contingent stimulus presentation (Kurzawski et al., 2023; Pelli et al., 2016); second, in the lab, using EasyEyes while independently monitoring gaze; third, online at home, using EasyEyes. We find that crowding thresholds are consistent (no significant differences in mean and variance of thresholds across ways) and individual differences are conserved. The small root mean square (RMS) fixation error (0.6 deg) during target presentation eliminates the need for gaze tracking. Thus, EasyEyes enables fixation-dependent measurements online, for easy testing of larger and more diverse populations.

neuroscience↗

bioRxiv2023

The universal suppressor mutation in the HSV-1 nuclear egress complex restores membrane budding defects by stabilizing the oligomeric lattice

Nuclear egress is an essential process in herpesviral replication whereby nascent capsids translocate from the nucleus to the cytoplasm. This initial step of nuclear egress - budding at the inner nuclear membrane - is coordinated by the nuclear egress complex (NEC). Composed of the viral proteins UL31 and UL34, NEC deforms the membrane around the capsid as the latter buds into the perinuclear space. NEC oligomerization into a hexagonal membrane-bound lattice is essential for budding because mutations designed to perturb lattice interfaces reduce its budding ability. Previously, we identified an NEC suppressor mutation capable of restoring budding to a mutant with a weakened hexagonal lattice. Here, we show that the suppressor mutation can restore budding to a broad range of budding-deficient NEC mutants thereby acting as a universal suppressor. We demonstrate that the suppressor mutation indirectly promotes the formation of new contacts between the NEC hexamers that, ostensibly, stabilize the hexagonal lattice. This stabilization strategy is powerful enough to override the otherwise deleterious effects of mutations that destabilize the NEC lattice by different mechanisms, resulting in a functional NEC hexagonal lattice and restoration of membrane budding.

biophysics↗

bioRxiv2023

Integrated analysis of spatial multi-omics with SpatialGlue

Integration of multiple data modalities in a spatially informed manner remains an unmet need for exploiting spatial multi-omics data. We introduce SpatialGlue, a graph neural network with dual-attention mechanism, to learn each modalitys significance at cross-omics and intra-omics integration. We demonstrate that SpatialGlue can accurately aggregate cell types into spatial domains at a higher resolution on different tissue types and technology platforms, as well as gain insights into cross-modality spatial correlations.

bioinformatics↗

bioRxiv2023

Integrated Spatial Transcriptomic and Proteomic Analysis of Fresh Frozen Tissue Based on Stereo-seq

To simultaneously detect whole transcriptomes and protein markers on the same tissue section, we combined Cellular Indexing of Transcriptomes and Epitopes by Sequencing (CITE-seq) and Stereo-seq to develop the Stereo-CITE-seq workflow. Here, we demonstrated that Stereo-CITE-seq can co-detect mRNAs and proteins in immune organs with high spatial resolution, reproducibility and accuracy.

molecular biology↗

bioRxiv2023

Single-cell analysis reveals distinct fibroblast plasticity during tenocyte regeneration in zebrafish

Despite their importance in tissue maintenance and repair, fibroblast diversity and plasticity remain poorly understood. Using single-cell RNA sequencing, we uncover distinct sclerotome-derived fibroblast populations in zebrafish, including progenitor-like perivascular/interstitial fibroblasts, and specialized fibroblasts such as tenocytes. To determine fibroblast plasticity in vivo, we develop a laser-induced tendon ablation and regeneration model. Lineage tracing reveals that laser-ablated tenocytes are quickly regenerated by preexisting fibroblasts. By combining single-cell clonal analysis and live imaging, we demonstrate that perivascular/interstitial fibroblasts actively migrate to the injury site, where they proliferate and give rise to new tenocytes. By contrast, perivascular fibroblast-derived pericytes or specialized fibroblasts, including tenocytes, exhibit no regenerative plasticity. Interestingly, active Hedgehog (Hh) signaling is required for the proliferation of activated fibroblasts to ensure efficient tenocyte regeneration. Together, our work highlights the functional diversity of fibroblasts and establishes perivascular/interstitial fibroblasts as tenocyte progenitors that promote tendon regeneration in a Hh signaling-dependent manner. TEASERPerivascular/interstitial fibroblasts function as plastic progenitors during tenocyte regeneration.

developmental biology↗

bioRxiv2023

StereoCell enables high accuracy single cell segmentation for spatial transcriptomic dataset

BackgroundOwing to recent advances in resolution and field-of-view, spatially resolved transcriptomics sequencing, such as Stereo-seq, has emerged as a cutting-edge technology for the interpretation of large tissues at the single-cell level. To generate accurate single-cell spatial gene expression profiles from high-resolution spatial omics data, a powerful computational tool is required. FindingsWe present CellBin, an image-facilitated one-stop pipeline for high-resolution and large field-of-view spatial transcriptomic data of Stereo-seq. CellBin provides a comprehensive and systematic platform for generating high-confidence single-cell spatial gene expression profiles, which specifically includes image stitching, image registration, tissue segmentation, nuclei segmentation and molecule labeling. CellBin is user-friendly and does not require a specific level of omics and image analysis expertise. ConclusionsDuring image stitching and molecule labeling, CellBin delivers better-performing algorithms to reduce stitching error and time, in addition to improving the signal-to-noise ratio of single-cell gene expression data, in comparison with existing methods. Additionally, CellBin has been shown to obtain highly accurate single-cell spatial data using mouse brain tissue, which facilitated clustering and annotation.

bioinformatics↗

bioRxiv2022

StereoSiTE: A framework to spatially and quantitatively profile the cellular neighborhood organized iTME

With emerging of Spatial Transcriptomics (ST) technology, a powerful algorithmic framework to quantitatively evaluate the active cell-cell interactions in the bio-function associated iTME unit will pave the ways to understand the mechanism underlying tumor biology. This study provides the StereoSiTE incorporating open source bioinformatics tools with the self-developed algorithm, SCII, to dissect a cellular neighborhood (CN) organized iTME based on cellular compositions, and to accurately infer the functional cell-cell communications with quantitatively defined interaction intensity in ST data. We applied StereoSiTE to deeply decode ST data of the xenograft models receiving immunoagonist. Results demonstrated that the neutrophils dominated CN5 might attribute to iTME remodeling after treatment. To be noted, SCII analyzed the spatially resolved interaction intensity inferring a neutrophil leading communication network which was proved to actively function by analysis of Transcriptional Factor Regulon and Protein-Protein Interaction. Altogether, StereoSiTE is a promising framework for ST data to spatially reveal tumoribiology mechanisms.

cancer biology↗

bioRxiv2022

Spateo: multidimensional spatiotemporal modeling of single-cell spatial transcriptomics

Cells do not live in a vacuum, but in a milieu defined by cell-cell communication that can be measured via emerging high-resolution spatial transcriptomics approaches. However, analytical tools that fully leverage such data for kinetic modeling remain lacking. Here we present Spateo (aristoteleo/spateo-release), a general framework for quantitative spatiotemporal modeling of single-cell resolution spatial transcriptomics. Spateo delivers novel methods for digitizing spatial layers/columns to identify spatially-polar genes, and develops a comprehensive framework of cell-cell interaction to reveal spatial effects of niche factors and cell type-specific ligand-receptor interactions. Furthermore, Spateo reconstructs 3D models of whole embryos, and performs 3D morphometric analyses. Lastly, Spateo introduces the concept of "morphometric vector field" of cell migrations, and integrates spatial differential geometry to unveil regulatory programs underlying various organogenesis patterns of Drosophila. Thus, Spateo enables the study of the ecology of organs at a molecular level in 3D space, beyond isolated single cells.

systems biology↗