Search bioRxiv⌕ Search

Biology subjects

Guo, L.

Publications and source records attributed to Guo, L..

At least 109 records · Page 6Linked to original sources

A Computational Framework to Optimize the Mechanical Behavior of Synthetic Vascular Grafts

The failure of synthetic small-diameter vascular grafts has been attributed to a mismatch in the compliance between the graft and native artery, driving mechanisms that promote thrombosis and neointimal hyperplasia. Additionally, the buckling of grafts results in large deformations that can lead to device failure. Although design features can be added to lessen the buckling potential, the addition is detrimental to decreasing compliance (e.g., reinforcing coil). Herein, we developed a novel finite element framework to inform vascular graft design by evaluating compliance and resistance to buckling. A batch-processing scheme iterated across the multi-dimensional design parameter space, which included three parameters: coil thickness, modulus, and spacing. Three types of finite element models were created in FEBio for each unique coil-reinforced graft parameter combination to simulate pressurization, axial buckling, and bent buckling, and results were analyzed to quantify compliance, buckling load, and kink radius, respectively, from each model. Importantly, model validation demonstrated that model predictions agree qualitatively and quantitatively with experimental observations. Subsequently, data for each design parameter combination were integrated into an optimization function for which a minimum value was sought. The optimization values identified various candidate graft designs with promising mechanical properties. Our investigation successfully demonstrated the model-directed framework identified vascular graft designs with optimal mechanical properties, which can potentially improve clinical outcomes by addressing device failure. In addition, the presented computational framework promotes model-directed device design for a broad range of biomaterial and regenerative medicine strategies.

bioengineering↗

GDF11 secreting cell transplant efficiently ameliorates age-related pulmonary fibrosis

Here, we present a combination of cell and gene therapy that harnesses the regenerative properties of GDF11 in age-related pulmonary fibrosis. Our genome-edited FailSafeTM-GDF11 mouse ESC line provides controlled proliferation and efficient derivation to lung progenitors while inducibly expressing GDF11. When these cells were transplanted into bleomycin-injured aged mice, they acted as a source of reparative cells, restoring the damaged alveolar epithelium. Furthermore, the transplanted cells acted as an "in situ factory", enabling the production of GDF11 in response to the inducer drug. This approach attenuated age-associated senescence and led to the successful resolution of fibrosis. Our study presents a promising method for treating pulmonary fibrosis. Additionally, this approach offers a versatile tool that can be expanded to incorporate other regenerative and anti-aging factors. This helps overcome limitations such as high production costs and a short half-life of therapeutic factors. One of the strengths of our system is its ability to allow precise regulation of factor-expression when needed to address specific aging phenotypes.

developmental biology↗

Spatiotemporal Single-Cell Roadmap of Human Skin Wound Healing

Wound healing is vital for human health, yet the details of cellular dynamics and coordination in human wound repair remain largely unexplored. To address this, we conducted single-cell and spatial transcriptomics analyses on human skin and acute wound tissues through inflammation, proliferation, and remodeling phases of wound repair from the same individuals, monitoring the cellular and molecular dynamics of human skin wound healing at an unprecedented spatiotemporal resolution. This singular roadmap reveals the cellular architecture of the wound margin and identifies FOSL1 as a critical driver of re-epithelialization. It shows that pro-inflammatory macrophages and fibroblasts sequentially support keratinocyte migration like a relay race across different healing stages. Comparison with single-cell data from venous and diabetic foot ulcers uncovers a link between failed keratinocyte migration and impaired inflammatory response in chronic wounds. Additionally, comparing human and mouse acute wound transcriptomes underscores the indispensable value of this roadmap in bridging basic research with clinical innovations. HighlightsO_LIA spatiotemporal atlas to explore human in vivo gene expression across wound healing C_LIO_LIWound margin architecture unveils a model for human re-epithelialization C_LIO_LIDistinct healing challenges in venous ulcers and diabetic foot ulcers C_LIO_LIUnique human healing traits emerge in cellular heterogeneity and gene expression C_LI

cell biology↗

Exploiting functional regions in the viral RNA genome as druggable entities

RNA-targeting compounds or small interfering RNAs (siRNAs) offer a potent means for controlling viral infections. An essential prerequisite to their design depends on identifying conserved and functional viral RNA structures in cells. Techniques that probe RNA structures in situ have been developed recently including SHAPE-MaP, which has been helpful in analyzing the secondary structures of RNA. In this study, we report on the application of SHAPE-MaP to the Porcine Epidemic Diarrhoea Virus (PEDV) RNA genome to categorize different functional regions including potential quadruplex forming sequence and target sites of siRNA. Our results show that these structures can be exploited to inhibit viral proliferation and that SHAPE-MaP is an effective method to the identification of secondary structures in RNA genomes.

genomics↗

Structural insights into the in situ assembly of clustered protocadherin γB4

Clustered protocadherins (cPcdhs) belong to the cadherin superfamily and play important roles in neural development. cPcdhs can mediate homophilic adhesion and lead to self-avoidance and tiling by giving neurons specific identities in vertebrates. Structures and functions of cPcdhs have been studied extensively in the past decades, but the mechanisms behind the functions have not been fully understood. Here we investigate the in situ assembly of cPcdh-{gamma}B4, a member in the {gamma} subfamily of cPcdhs, by electron tomography and find that the full length cPcdh-{gamma}B4 does not show regular organization at the adhesion interfaces. By contrast, cPcdh-{gamma}B4 lacking the intracellular domain can generate an ordered zigzag pattern between cells and the cis interacting mode is different from the crystal packing of the ectodomain. We also identify the residues on the ectodomain that might be important for the zigzag pattern formation by mutagenesis. Furthermore, truncation mutants of the intracellular domain of cPcdh-{gamma}B4 reveal different assembly patterns between cell membranes, suggesting that the intracellular domain plays a crucial role in the intermembrane organization of cPcdh-{gamma}B4. Taken together, these results suggest both ectodomain and intracellular domain regulate the in situ assembly of cPcdh-{gamma}B4 at the adhesion interfaces, thereby providing mechanistic insights into the functional roles of cPcdhs during neuronal wiring.

biophysics↗

A Regularized Bayesian Dirichlet-multinomial Regression Model for Integrating Single-cell-level Omics and Patient-level Clinical Study Data

SummaryThe abundance of various cell types can vary significantly among patients with varying phenotypes and even those with the same phenotype. Recent scientific advancements provide mounting evidence that other clinical variables, such as age, gender, and lifestyle habits, can also influence the abundance of certain cell types. However, current methods for integrating single-cell-level omics data with clinical variables are inadequate. In this study, we propose a regularized Bayesian Dirichlet-multinomial regression framework to investigate the relationship between single-cell RNA sequencing data and patient-level clinical data. Additionally, the model employs a novel hierarchical tree structure to identify such relationships at different cell-type levels. Our model successfully uncovers significant associations between specific cell types and clinical variables across three distinct diseases: pulmonary fibrosis, COVID-19, and non-small cell lung cancer. This integrative analysis provides biological insights and could potentially inform clinical interventions for various diseases.

bioinformatics↗

Frontotemporal dementia-like disease progression elicited by seeded aggregation and spread of FUS

RNA binding proteins have emerged as central players in the mechanisms of many neurodegenerative diseases. In particular, a proteinopathy of fused in sarcoma (FUS) is present in some instances of familial Amyotrophic lateral sclerosis (ALS) and about 10% of sporadic FTLD. Here we establish that focal injection of sonicated human FUS fibrils into brains of mice in which ALS-linked mutant or wild-type human FUS replaces endogenous mouse FUS is sufficient to induce focal cytoplasmic mislocalization and aggregation of mutant and wild-type FUS which with time spreads to distal regions of the brain. Human FUS fibril-induced FUS aggregation in the mouse brain of humanized FUS mice is accelerated by an ALS-causing FUS mutant relative to wild-type human FUS. Injection of sonicated human FUS fibrils does not induce FUS aggregation and subsequent spreading after injection into naive mouse brains containing only mouse FUS, indicating a species barrier to human FUS aggregation and its prion-like spread. Fibril-induced human FUS aggregates recapitulate pathological features of FTLD including increased detergent insolubility of FUS and TAF15 and amyloid-like, cytoplasmic deposits of FUS that accumulate ubiquitin and p62, but not TDP-43. Finally, injection of sonicated FUS fibrils is shown to exacerbate age-dependent cognitive and behavioral deficits from mutant human FUS expression. Thus, focal seeded aggregation of FUS and further propagation through prion-like spread elicits FUS-proteinopathy and FTLD-like disease progression.

neuroscience↗

The complete genome of lettuce reveals centromere landscape and empowers breeding

Lettuce (Lactuca sativa L.) is a globally grown vegetable crop as the most popular salad ingredient. Lettuce breeding is crucial to enhancing yield, nutrition and disease resistance, but impeded by lacking a high-quality genome resource. In addition, the released genomes remain fragmented (with hundreds of gaps) and incomplete with omitting pivotal centromeres and telomeres. Here, we report a 2.59 Gb complete telomere-to-telomere (T2T) genome assembly for lettuce. T2T genome analysis revealed the unique genetic and epigenetic architectures of centromere repeats dominated by retrotransposons and satellites. The complete genome and annotation facilitate the identification of candidate disease resistance (NLR) genes induced during grey mold infection. The genomic resources, and biological insights into genetic and epigenetic landscape of centromeres not only advance lettuce research and breeding, but also propel the biology and evolution of centromeres across plant kingdom.

genomics↗

Engineering PEG10 assembled endogenous virus-like particles with genetically encoded neoantigen peptides for cancer vaccination

Tumor neoantigen peptide vaccines hold potential for boosting cancer immunotherapy, yet efficiently co-delivering peptides and adjuvants to antigen-presenting cells in vivo remains challenging. Virus-like particle (VLP), which is a kind of multiprotein structure organized as virus, can deliver therapeutic substances into cells and stimulate immune response. However, the weak targeted delivery of VLP in vivo and its susceptibility to neutralization by antibodies hinder their clinical applications. Here, we firstly designed a novel protein carrier using the mammalian-derived capsid protein PEG10, which can self-assemble into endogenous VLP (eVLP) with high protein loading and transfection efficiency. Then, an engineered tumor vaccine, named ePAC, was developed by packaging genetically encoded neoantigen into eVLP with further modification of CpG-ODN on its surface to serve as an adjuvant and targeting unit to dendritic cells (DCs). Significantly, ePAC can efficiently target and transport neoantigens to DCs, and promote DCs maturation to induce neoantigen-specific T cells. Moreover, in mouse orthotopic liver cancer and humanized mouse tumor models, ePAC combined with anti-TIM-3 exhibited remarkable antitumor efficacy. Overall, these results support that ePAC could be safely utilized as cancer vaccines for antitumor therapy, showing significant potential for clinical translation.

cancer biology↗

Wampee chromosome-level reference genome elucidates fruit sugar-acid metabolism

Wampee (Clausena lansium) is an economically significant subtropical fruit tree widely cultivated in Southern China. High-quality genomic resources are unavailable, but they are essential for functional genomics and germplasm enhancement of wampee. Here, we provide a chromosome-level genome sequence for the wampee cultivar JinFeng and a population genomic analysis of 266 accessions. The 297.1 Mb wampee genome, containing nine chromosomes with a scaffold N50 of 29.2 Mb and encoding 23,468 protein-coding genes, showed a significant improvement over the previous version. We dissected the wampee population structure and genetic differentiation in China using population genomic analysis, which detected 110 and 671 genes under a selective sweep associated with sour and sweet wampee evolution in domesticated clones, respectively. Homozygous non-synonymous single nucleotide polymorphisms are likely associated with fruit flavor differentiation. A genome-wide association study identified 220 remarkable marker-trait associations for total acid content, harboring 289 genes encoding transcription factors, transporters, and enzymes involved in sugar and acid metabolism, which are potentially useful for sour and sweet taste development in wampee fruit. Furthermore, the ethylene response factor family gene ClERF061 and the SWEET family gene ClSWEET7 were identified. Linkage assessment between the relative expression levels of ClERF061 or ClSWEET7 and the total acid/total sugar contents implied their potential involvement in sugar-acid metabolism in wampee fruits. High-quality genome resources are valuable for expediting wampee research and genome-assisted breeding.

genomics↗

Super Pangenome of Grapevines Empowers Improvement of the Oldest Domesticated Fruit

Grapevine (Vitis) is the oldest domesticated fruit crop with great cultural and economic importance. Here, we assemble and annotate haplotype-resolved genomes of 72 Vitis accessions including 25 wild and 47 cultivated grapevines, and a haplotype-resolved complete genome of V. vinifera. Coalescent phylogenomics of 142 haplotype genomes disentangles the mysterious hybridization history of grapevines, revealing enormous genetic diversity among species. Pangenome analysis together with phenotyping data reveals that European cultivars, more susceptible to the most destructive disease downy mildew (DM), had a smaller repertoire of disease resistance genes of NLR family. Through extensive structural variation (SV) characterization, phenotyping, transcriptome profiling of 113 Vitis accessions, and SV-eQTL analysis, we have identified over 79 SVs and their relevant genes significantly associated with DM resistance, exemplified by a lysine histidine transporter, VvLHT8. This haplotype-resolved complete genome and pangenome of Vitis genus will accelerate grapevine breeding and enrich our understanding of the evolution and biology of grapevines.

plant biology↗

A comprehensive personal omics clinical interpreter based on genomic and transcriptomic profiles

Advances in precision medicine rely on the accurate identification and analysis of molecular alterations for personalized diagnostic, prognostic, and therapeutic decision-making. A critical obstacle is the integration of heterogeneous interpretations of clinically actionable alterations from various knowledgebases. Here, we present the Personal Omics Interpreter (POI), a web-based application engineered to aggregate and interpret therapeutic options, including targeted, immunological, and chemotherapeutic agents, by leveraging personal genomic and transcriptomic profiles. POI employs the Precision Medicine Knowledgebase (PreMedKB), an updated harmonized resource we previously reported, to annotate the clinically actionable somatic variants. It further incorporates a predictive algorithm to broaden therapeutic options according to established gene-gene interactions and offers insights into phenotypic responses of chemotherapeutic agents through phasing germline diplotypes. Validated against three cohort datasets encompassing over 22,000 cancer patients, POI demonstrates consistently high matching rates (94.7 [~] 95.6%) between patients and suggested therapies, highlighting its potential in supporting precision-driven informed treatment strategies.

genomics↗

PerturBase: a comprehensive database for single-cell perturbation data analysis and visualization

Single-cell perturbation sequencing techniques (scPerturbation), represented by single cell genetic perturbation sequencing (e.g., Perturb-seq) and single cell chemical perturbation sequencing (e.g., sci-Plex), result from the integration of single-cell toolkits with conventional bulk screening methods. These innovative sequencing techniques empower researchers to dissect perturbation functions and mechanisms in complex biological systems at an unprecedented resolution. Despite these advancements, a notable gap exists in the availability of a dedicated database for exploring and querying scPerturbation data. To address this gap and facilitate seamless data sharing for researchers, we present PerturBase--the first and most comprehensive database designed for the analysis and visualization of scPerturbation data (http://www.perturbase.cn/). PerturBase consolidates 122 datasets from 46 publicly accessible research studies, covering 115 single-modal and 7 multi-modal datasets that include 24254 genetic and 230 chemical perturbations from about 6 million cells. The database provides insights through various software-analyzed results, encompassing quality control, denoising, differential expression gene analysis, perturbation function analysis, and correlation characterization between perturbations. All datasets and in-depth analyses are presented in user-friendly, easy-to-browse pages and can be visualized through intuitive tables and various image formats. In summary, PerturBase stands as a pioneering high-content database, intended for searching, visualizing, and analyzing scPerturbation datasets, contributing to an enhanced understanding of perturbation functions and mechanisms. Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=159 SRC="FIGDIR/small/578767v1_ufig1.gif" ALT="Figure 1"> View larger version (56K): org.highwire.dtl.DTLVardef@15bdfcborg.highwire.dtl.DTLVardef@c1be77org.highwire.dtl.DTLVardef@1bf7e32org.highwire.dtl.DTLVardef@f62e8b_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

CAT Bridge: an efficient toolkit for compound-transcript association mining from multi-omics data

BackgroundWith advancements in sequencing and mass spectrometry technologies, multi-omics data can now be easily acquired for understanding complex biological systems. Nevertheless, substantial challenges remain in determining the association between gene-metabolite pairs due to the non-linear and multifactorial interactions within cellular networks. The complexity arises from the interplay of multiple genes and metabolites, often involving feedback loops and time-dependent regulatory mechanisms that are not easily captured by traditional analysis methods. FindingsHere, we introduce Compounds And Transcripts Bridge (abbreviated as CAT Bridge, available at https://catbridge.work), a free user-friendly platform for longitudinal multi-omics analysis to efficiently identify transcripts associated with metabolites using time-series omics data. To evaluate the association of gene-metabolite pairs, CAT Bridge is a pioneering work benchmarking a set of statistical methods spanning causality estimation and correlation coefficient calculation for multi-omics analysis. Additionally, CAT Bridge features an artificial intelligence (AI) agent to assist users interpreting the association results. ConclusionsWe applied CAT Bridge to experimentally obtained Capsicum chinense (chili pepper) and public human and Escherichia coli (E. coli) time-series transcriptome and metabolome datasets. CAT Bridge successfully identified genes involved in the biosynthesis of capsaicin in C. chinense. Furthermore, case study results showed that the convergent cross mapping (CCM) method outperforms traditional approaches in longitudinal multi-omics analyses. CAT Bridge simplifies access to various established methods for longitudinal multi-omics analysis, and enables researchers to swiftly identify associated gene-metabolite pairs for further validation.

bioinformatics↗

Switching circuits: Modulating NK cell response to TGF-β using novel receptors

Engineered natural killer (NK) cells offer a promising treatment strategy for multiple therapeutic areas, yet tuning cell function to diverse environmental and inhibitory contexts remains a significant challenge. An attractive strategy for functional rescue in the presence of inhibitory ligands is the use of switch receptors, surface-expressed chimeric receptors that convert an external inhibitory cue into an intracellular activation signal. Here, we discover novel engineered switch receptors in NK cells that are responsive to TGF-{beta}, a soluble inhibitory factor present in many therapeutic contexts. Through a pooled screen of an 11,131 member library, we identified multiple novel signaling endodomains and endodomain combinations that improve both the acute cytotoxicity and persistence of NK cells in the presence of TGF-{beta}, demonstrating a novel and flexible approach to switch receptor discovery.

immunology↗

Unravelling neuronal and glial differences in ceramide composition, synthesis, and sensitivity to toxicity

Ceramides are lipids that play vital roles in complex lipid synthesis, membrane function, and cell signaling. Disrupted ceramide homeostasis is implicated in cell-death and several neurologic diseases. Ceramides are often analyzed in tissue, but this approach fails to resolve cell-type differences in ceramide homeostasis that are likely essential to understanding cell and non-cell autonomous contributions to neurodegeneration. We show that human iPSC-derived neurons and glia differ in their rate of ceramide synthesis, ceramide isoform composition, and responses to altered ceramide levels. RNA-sequencing of cells treated to increase or decrease ceramides revealed connections to inflammation, ER stress, and apoptosis. Moreover, introducing labeled sphinganine showed that glia readily synthesize ceramide de novo and that neurons are relatively more sensitive to ceramide toxicity. Our findings provide a framework for understanding neurologic diseases with sphingolipid alternations and insights in to designing therapeutics that target ceramide for treating them.

neuroscience↗

Stereopy: modeling comparative and spatiotemporal cellular heterogeneity via multi-sample spatial transcriptomics

Tracing cellular dynamic changes across conditions, time, and space is crucial for understanding the molecular mechanisms underlying complex biological systems. However, integrating multi-sample data in a unified and flexible way to explore cellular heterogeneity remains a major challenge. Here, we present Stereopy, a flexible and versatile framework for modeling and dissecting comparative and spatiotemporal patterns in multi-sample spatial transcriptomics with interactive data visualization. To optimize this flexible framework, we have developed three key components: a multi-sample tailored data container, a scope controller, and an analysis transformer. Furthermore, Stereopy showcases three transformative applications supported by pivotal algorithms. Firstly, the multi-sample cell community detection (CCD) algorithm introduces an innovative capability to detect specific cell communities and identify genes responsible for pathological changes in comparable datasets. Secondly, the spatially resolved temporal gene pattern inference (TGPI) algorithm represents a notable advancement in detecting important spatiotemporal gene patterns while concurrently considering spatial and temporal features, which enhances the identification of important genes, domains and regulatory factors closely associated with temporal datasets. Finally, the 3D niche-based regulation inference tool, named NicheReg3D, reconstructs the 3D cell niches to enable the inference of cell-gene interaction network within the spatial texture, thus bridging intercellular communications and intracellular regulations to unravel the intricate regulatory mechanisms that govern cellular behavior. Overall, Stereopy serves as both a bioinformatics toolbox and an extensible framework that provides researchers with enhanced data interpretation abilities and new perspectives for mining multi-sample spatial transcriptomics data.

bioinformatics↗

SpaGRN: investigating spatially informed regulatory paths for spatially resolved transcriptomics data

Cells expressing similar transcriptional regulatory circuits spatially aggregate into distinct cell types or states. However, most existing methods for inferring gene regulatory networks from spatially resolved transcriptomics are devoted to spatial co-expression modules or interactions between transcription factors and target genes, neglecting mediated effects from extracellular signals. Here we introduce SpaGRN, a statistical framework for predicting the comprehensive intracellular regulatory network underlying spatial patterns by integrating spatial expression profiles with prior knowledge on regulatory relationships and signaling paths. We validate and assess SpaGRN using simulated and real datasets, demonstrating its efficiency, performance, and robustness. When applied to 3D datasets of developing Drosophila embryos and larvae, SpaGRN identifies spatiotemporal variations in specific regulatory patterns, delineating the cascade of events from receptor stimulation to downstream transcription factors and targets, revealing synergetic regulation mechanism during organogenesis. Moreover, SpaGRN provides flexible visualization functions. We construct an online 3D regulatory network atlas database for interactive exploration and sharing.

bioinformatics↗