Biology subjects

Cai, H.

Publications and source records attributed to Cai, H..

At least 73 records · Page 4Linked to original sources

bioRxiv2024

Aging represses lung tumorigenesis and alters tumor suppression

Most cancers are diagnosed in persons over the age of sixty, but little is known about how age impacts tumorigenesis. While aging is accompanied by mutation accumulation -- widely understood to contribute to cancer risk -- it is also associated with numerous other cellular and molecular changes likely to impact tumorigenesis. Moreover, cancer incidence decreases in the oldest part of the population, suggesting that very old age may reduce carcinogenesis. Here we show that aging represses tumor initiation and growth in genetically engineered mouse models of human lung cancer. Moreover, aging dampens the impact of inactivating many, but not all, tumor suppressor genes with the impact of inactivating PTEN, a negative regulator of the PI3K/AKT pathway, weakened to a disproportionate extent. Single-cell transcriptomic analysis revealed that neoplastic cells from tumors in old mice retain many age-related transcriptomic changes, showing that age has an enduring impact that persists through oncogenic transformation. Furthermore, the consequences of PTEN inactivation were strikingly age-dependent, with PTEN deficiency reducing signatures of aging in cancer cells and the tumor microenvironment. Our findings suggest that the relationship between age and lung cancer incidence may reflect an integration of the competing effects of driver mutation accumulation and tumor suppressive effects of aging.

cancer biology↗

bioRxiv2024

Unveiling Tissue Structure and Tumor Microenvironment from Spatially Resolved Transcriptomics by Hypergraph Learning

Spatial omics technologies have revolutionized life sciences by enabling the simultaneous acquisition of biomolecular and spatial information. Identifying spatial patterns is crucial for understanding organ development and tumor microenvironments. However, the emergence of diverse spatial omics resolutions in these technologies has made it challenging to accurately characterize spatial domains at finer resolutions. To address this, we propose HyperSTAR, a hypergraph-based method designed to precisely identify spatial domains across varying resolutions by leveraging higher-order relationships among spatially adjacent tissue programs. Specifically, a gene expression-guided hyperedge decomposition module is introduced to refine the hypergraph structure to accurately delineate spatial domains boundaries. Additionally, a hypergraph attention convolutional neural network is designed to adaptively learn the importance of each hyperedge, enhancing the models ability to capture complex higher-order relationships within spatially neighboring multi-spots and/or single cells. HyperSTAR outperforms existing graph neural network models in tasks such as uncovering tissue substructures, inferring spatiotemporal patterns, and denoising spatially resolved gene expressions. It effectively handles diverse spatial omics data types and scales seamlessly to large datasets. The method successfully reveals spatial heterogeneity in breast cancer sections, with findings validated through functional and survival analyses of independent clinical data. HyperSTAR represents a significant advancement in spatial omics analysis, representing a robust tool for exploring complex spatial patterns across varying resolutions and data types. Its ability to capture intricate higher-order relationships among spatially neighboring spots/cells makes it an invaluable tool for advancing research in life sciences, particularly in cancer and developmental biology.

bioinformatics↗

bioRxiv2024

Multivalent Targeting of Blood-Brain Barrier LRP1 for Neurovascular Recovery Therapy for Alzheimer s Disease

The blood-brain barrier (BBB) is a highly selective permeability barrier that safeguards the central nervous system (CNS) from potentially harmful substances while regulating the transport of essential molecules. Its dysfunction is increasingly recognized as a pivotal factor in the pathogenesis of Alzheimers disease (AD), contributing to the accumulation of amyloid-{beta} (A{beta}) plaques. We propose an AD therapeutic strategy targeting the BBB low-density lipoprotein receptor-related protein 1 (LRP1). We show that a multivalent scaffold with LRP1-specific peptide modulates the A{beta} transport at the BBB. We show via detailed experimentation on AD model mice that this intervention markedly reduces A{beta} deposits and prevents cognitive decline. This study marks a new approach to drug design, combining multivalent targeting with the regulation of membrane trafficking through advanced molecular engineering. Crucially, the therapeutic effects emerge from the multivalent nature of our proposed system. Furthermore, our findings underscore the paramount significance of the BBB in AD pathogenesis, particularly emphasizing the critical role of LRP1-mediated A{beta} clearance in mitigating disease progression.

neuroscience↗

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

Extracellular vesicles-based point-of-care testing for the diagnosis and monitoring of Alzheimer's disease

Alzheimers disease (AD) is a debilitating condition that affects millions of people worldwide. One promising strategy for detecting and monitoring AD early on is using extracellular vesicles (EVs)-based point-of-care testing; however, diagnosing AD using EVs poses a challenge due to the low abundance of EV-biomarkers. Here, we present a fully integrated organic electrochemical transistor (OECT) that enables high accuracy, speed, and convenience in the detection of EVs from AD patients. We incorporated self-aligned acoustoelectric enhancement of EVs on a chip that rapidly propels, enriches, and specifically binds EVs to the OECT detection area. With our enhancement of pre-concentration, we increased the sensitivity to a limit of detection of 500 EV particles/L and reduced the required detection time to just two minutes. We also tested the sensor on an AD mouse model to monitor AD progression, examined mouse A{beta} EVs at different time courses, and compared them with intraneuronal A{beta} cumulation using MRI. This innovative technology has the potential to diagnose Alzheimers and other neurodegenerative diseases accurately and quickly, enabling monitoring of disease progression and treatment response.

bioengineering↗

bioRxiv2024

U-FISH: a universal deep learning approach for accurate FISH spot detection across diverse datasets

In the rapidly advancing landscape of fluorescence in situ hybridization (FISH) technologies, there is a critical need for sophisticated yet adaptable methods for spot detection. This study introduces U-FISH, a deep learning approach that significantly improves accuracy and generalization capabilities. Our method utilizes a U-Net model to transform noisy and ambiguous FISH images into a standardized representation with consistent signal characteristics, facilitating efficient spot detection. For the training and evaluation of the U-FISH model, we have constructed a comprehensive dataset comprising over 4,000 images and more than 1.6 million manually annotated spots, sourced from both experimental and simulated environments. Our benchmarks demonstrate that U-FISH outperforms existing methods for FISH spot detection, offering improved versatility by eliminating the need for laborious manual parameter adjustments. This allows for its application across a broad spectrum of datasets and formats. Furthermore, U-FISH is designed for high scalability and is capable of processing 3D data, supporting the latest generation of file formats for large and complex datasets. To promote community adoption and ensure accessibility, we provide a user-friendly interfaces: Napari plugin, web application and command-line interface. The complete training dataset is made publicly available, laying a solid foundation for future research in this field.

bioinformatics↗

bioRxiv2023

Preclinical Characterization of the Omicron XBB.1.5-Adapted BNT162b2 COVID-19 Vaccine

As SARS-CoV-2 continues to evolve, increasing in its potential for greater transmissibility and immune escape, updated vaccines are needed to boost adaptive immunity to protect against COVID-19 caused by circulating strains. Here, we report features of the monovalent Omicron XBB.1.5-adapted BNT162b2 vaccine, which contains the same mRNA backbone as the original BNT162b2 vaccine, modified by the incorporation of XBB.1.5-specific sequence changes in the encoded prefusion-stabilized SARS-CoV-2 spike protein (S(P2)). Biophysical characterization of Omicron XBB.1.5 S(P2) demonstrated that it maintains a prefusion conformation that adopts a flexible and predominantly open one-RBD-up state, with high affinity binding to the human ACE-2 receptor. When administered as a 4th dose in BNT162b2-experienced mice, the monovalent Omicron XBB.1.5 vaccine elicited substantially higher serum neutralizing titers against pseudotyped viruses of Omicron XBB.1.5, XBB.1.16, XBB.1.16.1, XBB.2.3, EG.5.1 and HV.1 sublineages and the phylogenetically distant BA.2.86 lineage than the bivalent Wild Type + Omicron BA.4/5 vaccine. Similar trends were observed against Omicron XBB sublineage pseudoviruses when the vaccine was administered as a 2-dose primary series in naive mice. Strong S-specific Th1 CD4+ and IFN{gamma}+ CD8+ T cell responses were also observed. These findings, together with prior experience with variant-adapted vaccine responses in preclinical and clinical studies, suggest that the monovalent Omicron XBB.1.5-adapted BNT162b2 vaccine is anticipated to confer protective immunity against dominant SARS-CoV-2 strains. ONE-SENTENCE SUMMARYThe monovalent Omicron XBB.1.5-adapted BNT162b2 mRNA vaccine encodes a prefusion-stabilized spike immunogen that elicits more potent neutralizing antibody responses against homologous XBB.1.5 and other circulating sublineage pseudoviruses compared to the bivalent Wild Type + Omicron BA.4/5 BNT162b2 vaccine, thus demonstrating the importance of annual strain changes to the COVID-19 vaccine.

immunology↗

bioRxiv2023

Efficient computation by molecular competition networks

Most biomolecular systems exhibit computation abilities, which are often achieved through complex networks such as signal transduction networks. Particularly, molecular competition in these networks can introduce crosstalk and serve as a hidden layer for cellular information processing. Despite the increasing evidence of competition contributing to efficient cellular computation, how this occurs and the extent of computational capacity it confers remain elusive. In this study, we introduced a mathematical model for Molecular Competition Networks (MCNs) and employed a machine learning-based optimization method to explore their computational capacity. Our findings revealed that MCNs, when compared to their non-competitive counterparts, demonstrate superior performance in both discrete decision-making and analog computation tasks. Furthermore, we examined how real biological constraints influence the computational capacity of MCNs, and highlighted the nonnegligible role of weak interactions. The study suggested the potential of MCNs as efficient computational structures in both in vivo and in silico scenarios, providing new insights into the understanding and application of cellular information processing.

systems biology↗

bioRxiv2023

Pretrainable Geometric Graph Neural Network for Antibody Affinity Maturation

Increasing the binding affinity of an antibody to its target antigen is a crucial task in antibody therapeutics development. This paper presents a pretrainable geometric graph neural network, GearBind, and explores its potential in in silico affinity maturation. Leveraging multi-relational graph construction, multi-level geometric message passing and contrastive pretraining on mass-scale, unlabeled protein structural data, GearBind outperforms previous state-of-the-art approaches on SKEMPI and an independent test set. A powerful ensemble model based on GearBind is then derived and used to successfully enhance the binding of two antibodies with distinct formats and target antigens. ELISA EC50 values of the designed antibody mutants are decreased by up to 17 fold, and KD values by up to 6.1 fold. These promising results underscore the utility of geometric deep learning and effective pretraining in macromolecule interaction modeling tasks.

bioinformatics↗

bioRxiv2023

Pathogenic entero- and salivatypes harbour changes in microbiome virulence and antimicrobial resistance genes with increasing chronic liver disease severity

Background & AimsLife-threatening complications of cirrhosis are triggered by bacterial infections, with the ever-increasing threat of antimicrobial resistance (AMR). Alterations in the gut microbiome in decompensated cirrhosis (DC) and acute-on-chronic liver failure (ACLF) are recognised to influence clinical outcomes, whilst the role of the oral microbiome is still being explored. Our aims were to simultaneously interrogate the gut and oral micro- and mycobiome in cirrhotic patients, and assess microbial community structure overlap in relation to clinical outcomes, as well as alterations in virulence factors and AMR genes. Methods18 healthy controls (HC), 20 stable cirrhotics (SC), 50 DC, 18 ACLF and 15 with non-liver sepsis (NLS) i.e. severe infection but without cirrhosis, were recruited at a tertiary liver centre. Shotgun metagenomic sequencing was undertaken from saliva (S) and faecal (F) samples (paired where possible). Salivatypes and enterotypes based on clustering of genera were calculated and compared in relation to cirrhosis severity and in relation to specific clinical parameters. Virulence and antimicrobial resistance genes (ARGs) were evaluated in both oral and gut niches, and distinct resistotypes identified. ResultsSpecific saliva- and enterotypes revealed a greater proportion of pathobionts with concomitant reduction in autochthonous genera with increasing cirrhosis severity, and in those with hyperammonemia. Overlap between oral and gut microbiome communities was observed and was significantly higher in DC and ACLF vs SC and HCs, independent of antimicrobial, beta-blocker and acid suppressant use. Two distinct gut microbiome clusters [ENT2/ENT3] harboured genes encoding for the phosphoenolpyruvate:sugar phosphotransferase system (PTS) system and other virulence factors in patients with DC and ACLF. Substantial numbers of ARGs (oral: 1,218 and gut: 672) were detected with 575 ARGs common to both sites. The cirrhosis resistome was significantly different to HCs, with three and four resistotypes identified for the oral and gut microbiome, respectively. DiscussionOral and gut microbiome profiles differ significantly with increasing severity of cirrhosis, with progressive dominance of pathobionts and loss of commensals. DC and ACLF have significantly worse microbial diversity than NLS, despite similar antimicrobial exposure, supporting the additive patho-biological effect of cirrhosis. The degree of microbial community overlap between sites, frequency of virulence factors and presence of ARGs, all increment significantly with hepatic decompensation. These alterations may predispose to higher infection risk, poorer response to antimicrobial therapy and worsening outcomes, and provide the rationale for developing non-antibiotic-dependent microbiome-modulating therapies.

physiology↗

bioRxiv2023

Structural Visualization of HECT-E3 Ufd4 accepting and transferring Ubiquitin to Form K29/K48-branched Polyubiquitination on N-degron

The K29/K48-linked ubiquitination generated by the cooperative catalysis of E3 ligase Ufd4 and Ubr1 is an enhanced protein degradation signal, in which Ufd4 is responsible for introducing K29-linked ubiquitination to K48-linked ubiquitin chains to augment polyubiquitination. How HECT-E3 ligase Ufd4 mediates the ubiquitination event remains unclear. Here, we biochemically determine that Ufd4 preferentially catalyses K29-linked ubiquitination on K48-linked ubiquitin chains to generate K29/K48-branched ubiquitin chains and capture structural snapshots of Ub transfer cascades for Ufd4-mediated ubiquitination. The N-terminal ARM region and HECT domain C-lobe of Ufd4 are identified and characterized as key structural elements that together recruit K48-linked diUb and orient Lys29 of its proximal Ub to the active cysteine of Ufd4 for K29-linked branched ubiquitination. These structures not only provide mechanistic insights into the architecture of the Ufd4 complex but also provide structural visualization of branched ubiquitin chain formation by a HECT-type E3 ligase.

biochemistry↗

bioRxiv2023

Dissecting genetic correlation through recombinantperturbations: the role of developmental bias

Genetic correlation represents an important class of evolutionary constraint, which is itself evolvable. Empirical studies have found mixed results on whether genetic correlations change rapidly or slowly. This uncertainty challenges our ability to predict the outcome of selection. Despite the tremendous diversity and complexity of life forms, there are certain forms of life that are never observed. This might be because of developmental biases that restrict how organisms can evolve, or because they have low fitness in any environment yet available on Earth. Given that both developmental bias and selection can generate similar phenotypes, it is difficult to distinguish between the two causes of evolutionary stasis among related taxa. For example, remarkably invariant traits are observed spanning million years, such as wing shape in Drosophila wherein qualitative differences are rare within genera. Here, we ask whether the absence of certain combinations of traits, as indicated by genetic correlation, reflects developmental bias. However, much confusion and controversy remain over definitions of developmental bias, and probing it is challenging. We thus present a novel approach aiming to dissect genetic correlations and estimate the relative contribution of developmental bias in maintaining genetic correlations. We do so by leveraging a common but under-utilized type of data: genetic crosses. Through empirical analyses, we find that our approach can distinguish whether genetically correlated traits are developmentally constrained to covary. We also find that our developmental bias metric is an indicator of genetic correlation stability across conditions. Our framework presents a feasible way to dissect the mechanisms underlying genetic correlation and pleiotropy.

evolutionary biology↗

bioRxiv2023

A novel virus-induced cyclic dinucleotide, 2'3'-c-di-GMP, mediates STING-dependent antiviral immunity in Drosophila

In mammals, the enzyme cGAS senses the presence of cytosolic DNA and synthesizes the cyclic dinucleotide (CDN) 2'3'-cGAMP. This CDN binds to and activates the protein STING to trigger immunity. We recently discovered in the model organism Drosophila melanogaster two cGAS-like receptors (cGLRs) that activate STING-dependent antiviral immunity and can produce 3'2'-cGAMP, in addition to 2'3'-cGAMP. Here we explore CDN-mediated immunity in 14 different Drosophila species covering 50 million years of evolution and report that 2'3'-cGAMP and 3'2'-cGAMP fail to control infection by Drosophila C virus in D. serrata, D. sechellia and D. mojavensis. Using an accurate and sensitive mass spectrometry method, we discover an unexpected diversity of CDNs produced in a cGLR-dependent manner in response to viral infection in D. melanogaster, including a novel CDN, 2'3'-c-di-GMP. We show that 2'3'-c-di-GMP is the most potent STING agonist identified so far in D. melanogaster and that this molecule also activates a strong antiviral transcriptional response in D. serrata. Our results shed light on the evolution of cGLRs in flies and provide a basis for the understanding of the function and regulation of this emerging family of PRRs in animal innate immunity.

immunology↗

bioRxiv2023

Exploring the Landscape of Spatial Transcriptome Analysis: Introducing STASH, a Database of Spatial Transcriptome Tools

Spatial transcriptomics (ST) has emerged as a powerful tool for unravelling tissue structure and function. However, the continuous development of ST has made it challenging to select and effectively use appropriate analysis tools. To address this issue, we have developed the Spatial Transcriptome Analysis Hub (STASH, http://cailab.labshare.cn:7004), a comprehensive, systematic, and user-friendly database of ST analysis tools. STASH collects and categorizes most of the tools currently available and provides insight into their current status and trends. This can help researchers quickly locate the appropriate tool for their needs, or even guide researchers in the development of better tools.

bioinformatics↗

bioRxiv2023

Amoeboid cells undergo durotaxis with soft end polarized NMIIA

Cell migration towards stiff substrates has been coined as durotaxis and implicated in development, wound healing and cancer, where complex interplays between immune and non-immune cells are present. Compared to the emerging mechanisms underlying the strongly adhesive mesenchymal durotaxis, little is known about whether immune cells - migrating in amoeboid mode - could follow mechanical cues. Here we develop an imaging-based confined migration device with stiffness gradient. By tracking live cell trajectory and analyzing the directionality of T cells and neutrophils, we observe that amoeboid cells can durotax. We further delineate the underlying mechanism to involve non-muscle myosin IIA (NMIIA) polarization towards the soft-matrix-side but may not require differential actin flow up- or down-stiffness gradient. Using the protista Dictyostelium, we demonstrate the evolutionary conservation of amoeboid durotaxis. Finally, these experimental phenomena are theoretically captured by an active gel model capable of mechanosensing. Collectively, these results may shed new lights on immune surveillance and recently identified confined migration of cancer cells, within the mechanically inhomogeneous tumor microenvironment or the inflamed fibrotic tissues.

cell biology↗

bioRxiv2023

A new tractable method for generating Human Alveolar Macrophage Like cells in vitro to study lung inflammatory processes and diseases

Alveolar macrophages (AMs) are unique lung resident cells that contact airborne pathogens and environmental particulates. The contribution of human AMs (HAM) to pulmonary diseases remains poorly understood due to difficulty in accessing them from human donors and their rapid phenotypic change during in vitro culture. Thus, there remains an unmet need for cost-effective methods for generating and/or differentiating primary cells into a HAM phenotype, particularly important for translational and clinical studies. We developed cell culture conditions that mimic the lung alveolar environment in humans using lung lipids, i.e., Infasurf (calfactant, natural bovine surfactant) and lung-associated cytokines (GM-CSF, TGF-{beta}, and IL-10) that facilitate the conversion of blood-obtained monocytes to an AM-Like (AML) phenotype and function in tissue culture. Similar to HAM, AML cells are particularly susceptible to both Mycobacterium tuberculosis and severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections. This study reveals the importance of alveolar space components in the development and maintenance of HAM phenotype and function, and provides a readily accessible model to study HAM in infectious and inflammatory disease processes, as well as therapies and vaccines. IMPORTANCEMillions die annually from respiratory disorders. Lower respiratory track gas-exchanging alveoli maintain a precarious balance between fighting invaders and minimizing tissue damage. Key players herein are resident AMs. However, there are no easily accessible in vitro models of HAMs, presenting a huge scientific challenge. Here we present a novel model for generating AML cells based on differentiating blood monocytes in a defined lung component cocktail. This model is non-invasive, significantly less costly than performing a bronchoalveolar lavage, yields more AML cells than HAMs per donor and retains their phenotype in culture. We have applied this model to early studies of M. tuberculosis and SARS-CoV-2. This model will significantly advance respiratory biology research.

immunology↗

bioRxiv2023

miRNA binding pressure channels evolution of SARS-CoV-2 genomes

In somatic cells, microRNAs (miRNAs) bind to the genomes of RNA viruses and influence their translation and replication. Here we demonstrate that a significant number of miRNA binding sites locate in the NSP4 region of the SARS-CoV-2 genome, and the intestinal human miRNAs exert evolutionary pressure on this region. Notably, in infected cells, NSP4 promotes the formation of double-membrane vesicles, which serve as the scaffolds for replication-transcriptional complexes and protect viral RNA from intracellular destruction. In three years of selection, the loss of many miRNA binding sites, in particular, those within the NSP4, has shaped the SARS-CoV-2 genomes to promote the descendants of the BA.2 variants as the dominant strains and define current momentum of the pandemics.

evolutionary biology↗

bioRxiv2023

Integration of Avidity and Differentiation is enabled by CD8+ T-cell sensing of IFN-γ

The most effective responses to intracellular pathogens have a breadth of T-cell clones with different affinities for their cognate peptide, and a diversity of functional phenotypes, from effector to long-lived memory cells. While high- and low-affinity T-cells are inherently skewed towards becoming effector and memory, respectively, overall, both functional subsets exploit a wide range of affinities. How the breadth of affinities and functionalities are coordinated is therefore unclear. In this study, we provide evidence that direct sensing of the cytokine IFN-{gamma} by CD8+ T-cells is a factor controlling the integration of T-cell affinity and differentiation during infection. IFN-{gamma} increases the expansion of low-affinity T-cells, allowing them to overcome the selective advantage of high-affinity T-cells. Concomitantly, IFN-{gamma} reinforces high-affinity T-cell entry into the memory pool. As a result, direct IFN-{gamma} sensing by CD8+ T-cells increases the avidity of the memory response. This comes at the expense of the primary T-cell response, for which IFN-{gamma} decreases the avidity, leading to sub-optimum immunity to infection. IFN-{gamma} sensing by CD8+ T-cells is paracrine, provided by a distinct subset of CD8+ T-cells called Virtual Memory T-cells, an antigen inexperienced subset that harbors memory features. Overall, we propose that IFN-{gamma} and Virtual Memory T-cells fulfil a critical immunoregulatory role by enabling the coordination of T-cell avidity and fate.

immunology↗