Biology subjects

Cao, S.

Publications and source records attributed to Cao, S..

At least 91 records · Page 5Linked to original sources

bioRxiv2024

Blockade of TREM2 ameliorates pulmonary inflammation and fibrosis by modulating sphingolipid metabolism

Pulmonary fibrosis is a chronic interstitial lung disease involving systemic inflammation and abnormal collagen deposition. Dysregulations in lipid metabolism, such as macrophage-dependent lipid catabolism, have been recognized as critical factors for the development of pulmonary fibrosis. However, little is known about the signaling pathways involved and the key regulators. Here we found that triggering receptor expressed on myeloid cells 2 (TREM2) plays a pivotal role in regulating the lipid handling capacities of pulmonary macrophages and triggering fibrosis. By integrating analysis of single-cell and bulk RNA sequencing data from patients and mice with pulmonary fibrosis, we revealed that pulmonary macrophages consist of heterogeneous populations with distinct pro-fibrotic properties, and found that both sphingolipid metabolism and the expression of chemotaxis-related genes are elevated in fibrotic lungs. TREM2, a sensor recognizing multiple lipid species, is specifically upregulated in a subset of monocyte- derived macrophages. Blockade of TREM2 by gene knock-out or soluble TREM2 administration can both attenuate bleomycin-induced pulmonary fibrosis. By utilizing scRNA Seq and lipidomics, we found that Trem2 deficiency downregulates the synthesis of various sphingomyelins, and inhibits the expression of chemokines such as Ccl2. Together, our findings not only reveal the alterations in lipidomic profiles and the atlas of pulmonary macrophages during pulmonary fibrosis, but also suggest that targeting TREM2, the crucial regulator affecting both pulmonary sphingolipid metabolism and the chemokines secretion, can benefit pulmonary fibrosis patients in the future.

pharmacology and toxicology↗

bioRxiv2023

Integrative genomics reveals the polygenic basis of seedlessness in grapevine

Seedlessness is a crucial quality trait in table grape (Vitis vinifera L.) breeding. However, the development of seeds involved intricate regulations, while the polygenic basis of seed abortion remains unclear. Here, we combine comparative genomics, population genetics, quantitative genetics, and integrative genomics to unravel the evolution and polygenic basis of seedlessness in grapes. We generated four haplotype-resolved telomere-to-telomere (T2T) genomes for two seedless grape cultivars, Thompson Seedless (TS, syn. Sultania) and Black Monukka (BM). Comparative genomics identified a [~]4.25 Mb hemizygous inversion on Chr10 specific in seedless cultivars, with seedless-associated genes VvTT16 and VvSUS2 located at breakpoints. Population genomic analyses of 548 grapevine accessions revealed two distinct clusters of seedless cultivars, tracing the origin of the seedlessness trait back to Sultania. Introgression, rather than convergent selection, shaped the evolutionary history of seedlessness in grape improvement. Genome-wide association study (GWAS) analysis identified 110 quantitative trait loci (QTLs) associated with 634 candidate genes, including novel candidate genes, such as three 11S GLOBULIN SEED STORAGE PROTEIN and two CYTOCHROME P450 genes, and well-known genes like VviAGL11. Integrative genomic analyses resulted in 339 core candidate genes categorized into 13 groups related to seed development. Machine learning based genomic selection achieved a remarkable 99% precision in predicting grapevine seedlessness. Our findings highlight the polygenic nature of seedless and provide novel candidate genes for molecular genetics and an effective prediction for seedlessness in grape genomic breeding.

genetics↗

bioRxiv2023

Post-synaptic competition between calcineurin and PKA regulates mammalian sleep-wake cycles

Phosphorylation of synaptic proteins is a pivotal biochemical reaction that controls the sleep-wake cycle in mammals. Protein phosphorylation in vivo is reversibly regulated by kinases and phosphatases. In this study, we investigated a pair of kinases and phosphatases that reciprocally regulate sleep duration. Through comprehensive screening of Protein kinase A (PKA) and phosphoprotein phosphatase (PPP) family genes via the generation of 40 gene knockout mouse lines including post-natal CRISPR targeting, we identified a regulatory subunit of PKA (Prkar2b), a regulatory subunit of protein phosphatase (PP) 1 (Pppr1r9b), and catalytic and regulatory subunits of PP2B (calcineurin) (Ppp3ca and Ppp3r1) as sleep control genes. AAV-mediated stimulation of PKA and PP1/calcineurin activities confirmed PKA as a wake-promoting kinase, while PP1 and calcineurin function as sleep-promoting phosphatases. The importance of these phosphatases in sleep regulation is supported by the dramatic changes in sleep duration associated with their increased and decreased activity, ranging from approximately 17.3 hours/day (PP1 expression) to 6.7 hours/day (post-natal CRISPR targeting of calcineurin). For these phosphatases to exert their sleep-promoting effects, localization signals to the excitatory post-synapse were necessary. Furthermore, the wake-promoting effect of PKA localized to the excitatory post-synapse negated the sleep-promoting effect of calcineurin, suggesting that PKA and calcineurin construct a hierarchical phosphorylation control network for sleep regulation at excitatory post-synapses.

neuroscience↗

bioRxiv2023

Predicting the Trend of SARS-CoV-2 Mutation Frequencies Using Historical Data

As the SARS-CoV-2 virus rapidly evolves, predicting the trajectory of viral variations has become a critical yet complex task. A deep understanding of future mutation patterns, in particular the mutations that will prevail in the near future, is vital in steering diagnostics, therapeutics, and vaccine strategies in the coming months. In this study, we developed a model to forecast future SARS-CoV-2 mutation surges in real-time, using historical mutation frequency data from the USA. To improve upon the accuracy of traditional time-series models, we transformed the prediction problem into a supervised learning framework using a sliding window approach. This involved breaking the time series of mutation frequencies into very short segments. Considering the time-dependent nature of the data, we focused on modeling the first-order derivative of the mutation frequency. We predicted the final derivative in each segment based on the preceding derivatives, employing various machine learning methods, including random forest, XGBoost, support vector machine, and neural network models, in this supervised learning setting. Empowered by the novel transformation strategy and the high capacity of machine learning models, we witnessed low prediction error that is confined within 0.1% and 1% when making predictions for future 30 and 80 days respectively. In addition, the method also led to a notable increase in prediction accuracy compared to traditional time-series models, as evidenced by lower MAE, and MSE for predictions made within different time horizons. To further assess the methods effectiveness and robustness in predicting mutation patterns for unforeseen mutations, we categorized all mutations into three major patterns. The model demonstrated its robustness by accurately predicting unseen mutation patterns when training on data from two pattern categories while testing on the third pattern category, showcasing its potential in forecasting a variety of mutation trajectories. To enhance accessibility and utility, we built our methodology into an R-shiny app (https://swdatpredicts.shinyapps.io/rshiny_predict/), a tool with potential applicability in studying other infectious diseases, thus extending its relevance beyond the current pandemic.

bioinformatics↗

bioRxiv2023

Exploratory study of pulsed electric field ablation on atherosclerotic plaque in a rabbit model

New understanding of the pathogenesis of atherosclerotic diseases has led to the emergence of new therapeutic approaches. We explored the potential therapeutic effects of pulsed field potential ablation (PFA), a non-thermal ablation technique with high tissue selectivity, on atherosclerotic plaques. Carotid arteries of 30 high-fat rabbits were dilated with a balloon to obtain atherosclerotic plaques. PFA was administered on the carotid atherosclerotic plaques with 1000V/cm, 2000V/cm, and 1000V/cm ablation followed by rapamycin infusion. There were no visible changes in blood vessels after acute ablation, but apoptosis and polarity of cells were observed in atherosclerotic plaques. At 7 and 30 days after ablation, the density of lipid deposition in the plaque was significantly reduced, and multiple layers of new arranged anterograde smooth muscle cells appeared, replacing the original atherosclerotic plaque. The residual atherosclerotic structure is sandwiched between the new smooth muscle layer and the original smooth muscle layer, which makes vascular wall thicker and makes vascular wall elasticity increased. Rapamycin delays the vascular remodeling process. Conclusion: PFA ablation can reduce lipid deposition in atherosclerotic plaques, cause vascular remodeling, and enhance vascular elasticity. We believe that it may be a potential method for the treatment of atherosclerotic plaques.

biophysics↗

bioRxiv2023

Integration of multi-source gene interaction networks and omics data with graph attention networks to identify novel disease genes

The pathogenesis of diseases is closely associated with genes, and the discovery of disease genes holds significant importance for understanding disease mechanisms and designing targeted therapeutics. However, biological validation of all genes for diseases is expensive and challenging. In this study, we propose DGP-AMIO, a computational method based on graph attention networks, to rank all unknown genes and identify potential novel disease genes by integrating multi-omics and gene interaction networks from multiple data sources. DGP-AMIO outperforms other methods significantly on 20 disease datasets, with an average AUROC and AUPR exceeding 0.9. The superior performance of DGP-AMIO is attributed to the integration of multiomics and gene interaction networks from multiple databases, as well as triGAT, a proposed GAT-based method that enables precise identification of disease genes in directed gene networks. Enrichment analysis conducted on the top 100 genes predicted by DGP-AMIO and literature research revealed that a majority of enriched GO terms, KEGG pathways and top genes were associated with diseases supported by relevant studies. We believe that our method can serve as an effective tool for identifying disease genes and guiding subsequent experimental validation efforts.

bioinformatics↗

bioRxiv2023

Cross-modal Generation of Hit-like Molecules via Foundation Model Encoding of Gene Expression Signatures

Designing de novo molecules with specific biological activity is an essential task since it holds the potential to bypass the exploration of target genes, which is an initial step in the modern drug discovery paradigm. However, traditional methods mainly screen molecules by comparing the desired molecular effects within the documented experimental results. The data set limits this process, and it is hard to conduct direct cross-modal comparisons. Therefore, we propose a solution based on cross-modal generation called GexMolGen (Gene Expression-based Molecule Generator), which generates hit-like molecules using gene expression signatures alone. These signatures are calculated by inputting control and desired gene expression states. Our model GexMolGen adopts a "first-align-then-generate" strategy, aligning the gene expression signatures and molecules within a mapping space, ensuring a smooth cross-modal transition. The transformed molecular embeddings are then decoded into molecular graphs. In addition, we employ an advanced single-cell large language model for input flexibility and pre-train a scaffold-based molecular model to ensure that all generated molecules are 100% valid. Empirical results show that our model can produce molecules highly similar to known references, whether feeding in- or out-of-domain transcriptome data. Furthermore, it can also serve as a reliable tool for cross-modal screening.

bioinformatics↗

bioRxiv2023

A telomere-to-telomere genome assembly of Zhonghuang 13, a widely-grown soybean variety from the original center of Glycine max

Soybean (Glycine max) stands as a globally significant agricultural crop, and the comprehensive assembly of its genome is of paramount importance for unraveling its biological characteristics and evolutionary history. Nevertheless, previous soybean genome assemblies have harbored gaps and incompleteness, which have constrained in-depth investigations into soybean. Here, we present the first Telomere-to-Telomere (T2T) assembly of the Chinese soybean cultivar "Zhonghuang 13" (ZH13) genome, termed ZH13-T2T, utilizing PacBio Hifi and ONT ultralong reads. We employed a multi-assembler approach, integrating Hifiasm, NextDenovo, and Canu, to minimize biases and enhance assembly accuracy. The assembly spans 1,015,024,879 bp, effectively resolving all 393 gaps that previously plagued the reference genome. Our annotation efforts identified 50,564 high-confidence protein-coding genes, 707 of which are novel. ZH13-T2T revealed longer chromosomes, 421 not-aligned regions (NARs), 112 structure variations (SVs), and a substantial expansion of repetitive element compared to earlier assemblies. Specifically, we identified 25.67 Mb of tandem repeats, an enrichment of 5S and 48S rDNAs, and characterized their genotypic diversity. In summary, we deliver the first complete Chinese soybean cultivar T2T genome. The comprehensive annotation, along with precise centromere and telomere characterization, as well as insights into structural variations, further enhance our understanding of soybean genetics and evolution.

plant biology↗

bioRxiv2023

Genomic insights into post-domestication expansion and selection of body size in ponies

Horses domestication revolutionized human civilization by changing transportation, farming, and warfare patterns. Despite extensive studies on modern domestic horse origins, the intricate demographic history and genetic signatures of pony size demand further exploration. Here, we present a high-quality genome of the Chinese Debao pony and extensively analyzed 385 individuals from 49 horse breeds. We reveal the conservation of ancient components in East Asian horses and close relationships between Asian horses and specific European pony lineages. Genetic analysis uncovers Asian paternal origin for European pony breeds, and these pony-sized horses share a close genetic affinity due to the presence of a potential ancestral ghost pony population. Additionally, we identify promising cis-regulatory elements influencing horse withers height by regulating genes like RFLNA and FOXO1. Overall, our study provides insightful perspectives into the development history and genetic determinants underlying body size in ponies and offers broader implications for horse population management and improvement. TeaserDecoding pony genetics: exploring origins and size determinants sheds light on their historical and biological impacts.

genomics↗

bioRxiv2023

Genome analyses reveal the secondary metabolites potentially influence the geographical distribution of Fusarium pseudograminearum populations

Fusarium crown rot (FCR), caused by Fusarium pseudograminearum, significantly impacts wheat yield and quality in Chinas Huanghuai region. The rapid F. pseudograminearum epidemic and FCR outbreak within a decade remain unexplained. In this study, two high-quality, chromosome-level genomes of F. pseudograminearum strains producing 3-acetyl-deoxynivalenol (3AcDON) and 15-acetyl-deoxynivalenol (15AcDON) toxins were assembled. Additionally, 38 related strains were resequenced. Genomic differences such as single nucleotide polymorphisms (SNPs), insertions/deletions (indels), and structural variations (SVs) among F. pseudograminearum strains were analyzed. The whole-genome SNP locus based population classification mirrored the toxin chenotype (3AcDON and 15AcDON)-based classification, indicating the presence of genes associated with the trichothecene toxin gene cluster. Further analysis of differential SNP, indel, and SV loci between the 3AcDON and 15AcDON populations revealed a predominant connection to secondary metabolite synthesis genes. Notably, the majority of the secondary metabolite biosynthesis gene cluster (SMGC) loci were located in SNP-dense genomic regions, suggesting high mutability and a possible contribution to F. pseudograminearum population structure and environmental adaptability. This study provides insightful perspectives on the distribution and evolution of F. pseudograminearum, and for forecasting the spread of wheat FCR, thereby aiding in the development of preventive measures and control strategies.

microbiology↗

bioRxiv2023

Injectable butyrate-prodrug micelles induce long-acting immune modulation and suppress autoimmune arthritis in mice

Dysbiosis is linked to autoimmune diseases such as rheumatoid arthritis (RA), where microbial metabolites, such as short chain fatty acids (SCFAs), mediate the so-called gut-joint axis. The therapeutic potential of SCFAs is limited due to the frequent and high oral dosage requirements. RA is characterized by aberrant activation of peripheral T cells and myeloid cells. We aim to deliver butyrate, an SCFA, directly to the lymphatics using a polymeric micelle as a butyrate prodrug, creating a depot for inducing long-lasting immunomodulatory effects. Notably, negatively charged micelles (Neg-ButM) demonstrate superior efficacy in targeting the lymphatics post-subcutaneous administration, and were retained in the draining lymph nodes, spleen, and liver for over a month. In a mouse RA model, we found that Neg-ButM substantially mitigated arthritis symptoms and promoted tolerogenic phenotypes in T cells and myeloid cells, both locally and systemically. These findings suggest potential applications of this approach in treating inflammatory autoimmune diseases.

bioengineering↗

bioRxiv2023

Seryl-butyrate: a prodrug that enhances butyrate's oral bioavailability and suppresses autoimmune arthritis and experimental autoimmune encephalomyelitis

Butyrate, a metabolite produced by commensal bacteria, has been intensively studied for its immunomodulatory effects on various immune cells, including T regulatory cells, macrophages, and dendritic cells. Butyrates development as a drug has been limited by its poor oral bioavailability due to its rapid metabolism in the gut, its low potency and thus high dosing, and its foul smell and taste. By simply esterifying butyrate to serine (O-butyryl-L-serine, SerBut), a design based on the concept of utilizing amino acid transporters to escape the gut and enhance systemic uptake thus increasing bioavailability, we developed an odorless and tasteless compound for oral administration. In the collagen antibody-induced arthritis (CAIA) and experimental autoimmune encephalomyelitis (EAE) murine models of rheumatoid arthritis and multiple sclerosis, we demonstrated that SerBut significantly ameliorated disease severity, modulated key immune cell populations both systemically and in disease-associated tissues, and reduced inflammatory responses without compromising global immune response to vaccination. Our findings highlight SerBut as a promising next-generation therapeutic agent for autoimmune and inflammatory diseases.

bioengineering↗

bioRxiv2023

Glycopolymer-conjugated antigens as an inverse vaccine platform prevent anaphylaxis in a pre-clinical model of food allergy

The only FDA-approved oral immunotherapy for a food allergy provides protection against accidental exposure to peanuts. However, this therapy often causes discomfort or side effects and requires long-term commitment. Better preventive and therapeutic solutions are urgently needed. We have developed a tolerance-inducing vaccine technology that utilizes glycosylation-modified antigens to induce antigen-specific non-responsiveness. The glycosylation-modified antigens were administered intravenously (i.v.) or subcutaneously (s.c.) and were found to traffic to the liver or lymph nodes, respectively, leading to preferential internalization by antigen-presenting cells, educating the immune system to respond in an innocuous way. In a mouse model of cows milk allergy, treatment with glycosylation-modified {beta}- lactoglobulin (BLG) was effective in preventing the onset of allergy. In addition, s.c. administration of glycosylation-modified BLG showed superior safety and potential in treating existing allergies in combination with an anti-CD20 co-therapy. This platform may provide an antigen-specific immunomodulatory strategy to prevent and treat food allergies.

bioengineering↗

bioRxiv2023

LDHA maintains the growth and migration of vascular smooth muscle cells and promotes neointima formation via crosstalk between K5 crotonylation and K76 mono-ubiquitination

Phenotypic plasticity of vascular smooth muscle cells (VSMCs) under stress is believed to be a key factor in neointima formation. Lactate dehydrogenase A (LDHA), a key enzyme for glycolysis, has been demonstrated to promote the proliferation and migration of VSMCs. However, the mechanism by which LDHA regulates this process is still unclear. Here we show that the crotonylation and mono-ubiquitination of LDHA are increased in platelet-derived growth factor (PDGF)-BB-induced proliferative VSMCs. Crotonylation at lysine 5 (K5) activates LDHA through tetramer formation to enhance lactate production and VSMCs growth. Mono-ubiquitination at K76 induces the translocation of LDHA into mitochondria, which promotes mitochondria fission and subsequent the formation of lamellipodia and podosomes, thereby enhancing VSMC migration and growth. Furthermore, the increase of crotonylation and ubiquitination were also observed in the carotid arteries of ligation injury mice. Deletion of LDHA K5 crotonylation or K76 mono-ubiquitination decreases ligation-induced neointima formation. Our study reveals a novel mechanism that combines VSMC metabolic reprogramming and behavioral abnormity through crosstalk between LDHA K5 crotonylation and K76 mono-ubiquitination.

biochemistry↗

bioRxiv2023

Metabolomics reveals nucleoside analogs for regulating mucosal-associated invariant T cell responses

Although mucosal-associated invariant T (MAIT) cells recognize riboflavin-like metabolites from Gram-negative bacteria, MAIT cell stimulation by broad bacterial families and mammalian cells suggests the existence of novel ligands from different biological sources. Here we established a comparative platform of functional metabolomics and used Mycobacterium tuberculosis as a model to characterize novel metabolites for MAIT cell activation. We extracted and fractionated small metabolites of M. tuberculosis using high-performance liquid chromatography, showing a different MAIT cell stimulation pattern of M. tuberculosis metabolite fractions in comparison with Escherichia coli fractions. Mass profiling predicted multiple nucleoside analogs enriched in a biologically active fraction of M. tuberculosis. Whereas the synthetic forms of these predicted M. tuberculosis nucleosides were unavailable, structural-based autodocking of analogous nucleosides conserved in mammals supported potential binding with MR1 protein. Indeed, functional assays of these conserved nucleosides demonstrated guanosine as a stimulator and deoxyformyluridine as an inhibitor of MAIT cell activation. Identification of bioactive nucleoside metabolites broadly conserved in bacterial and mammalian systems will facilitate an understanding of the regulatory roles of MAIT cells in infectious and inflammatory conditions.

immunology↗

bioRxiv2022

Extreme diversity of mycoviruses present in four strains of Rhizoctonia cerealis, the pathogen of wheat sharp eyespot

Rhizoctonia cerealis is the pathogen of wheat sharp eyespot, which occurs throughout temperate wheat growing regions of the world. In this project, the genomes of viruses from four strains of R. cerealis were analyzed based on Illumina high-throughput RNA-Seq data. Ribosomal RNA-depleted total RNA and purified dsRNA from cultivated mycelia of each isolate were used for cDNA library construction and sequencing. After filtering out reads that mapped to the fungal genome, viral genomes were assembled using the remaining reads from the rRNA-depleted and dsRNA-Seq data. In total, 131 viral genome sequences containing complete ORFs, belonging to 117 viruses, were obtained. Based on phylogenetic analysis, some of them were identified as novel members of the families Curvulaviridae, Endornaviridae, Hypoviridae, Mitoviridae, Mymonaviridae and Phenuiviridae, while others were unclassified viruses. We compared the integrity and reliability of the viral sequences obtained by the two sequencing methods and, for the first time, estimated the density of some viruses in host cells. Most of these viruses from R. cerealis were sufficiently different from those deposited in databases. We propose the establishment of a new family, Rhizoctobunyaviridae, and two new genera, Rhizoctobunyavirus and Iotahypovirus. We further clarified the distribution and co-infection of these viruses in the four R. cerealis strains. In conclusion, the diversity of mycoviruses in R. cerealis is extremely rich. We report a series of novel viruses and provide important insight into virus evolution.

microbiology↗

bioRxiv2022

Flux estimation analysis systematically characterizes the metabolic shifts of the central metabolism pathway in human cancer.

Glucose and glutamine are major carbon and energy sources that promote the fast proliferation of cancer cells. Metabolic shifs observed on cell line or mouse models may not reflect the general metabolic shifts in real human cancer tissue. In this study, we conducted a computational characterization of the flux distribution and variations of the central energy metabolism and key branches in a pan-cancer analysis, including glycolytic pathway, production of lactate, TCA cycle, nucleic acids synthesis, glutaminolysis, glutaminate, glutamine and glutathione metabolism, amino acids synthesis, in 11 cancer subtypes and 9 matched adjacent normal tissue types, by using TCGA tissue transcriptomics data. Our analysis confirms the increased influx in glucose uptake and glycolysis and decreased upper part of TCA cycle, i.e., Warbug effect in the analyzed cancer types. However, consistently increased lactate production and second half of TCA cycle were only seen in certain cancer types. More interestingly, we did not see cancer tissues have highly shifted glutaminolysis compared to their adjacent normal controls. A systems biology model of metabolic shifts in through cancer and tissue types is further developed and analyzed. We observed that (1) normal tissues have distinct metabolic phenotypes, (2) cancer types have drastically different metabolic shifts compared to their adjacent normal controls, and (3) the different shifts happened to tissue specific metabolic phenotypes result in a converged metabolic phenotype through cancer types and cancer progression. This study strongly suggests the possibility to have a unified framework for studies of cancer-inducing stressors, adaptive metabolic reprogramming, and cancerous behaviors.

bioinformatics↗

bioRxiv2022

Comprehensive integration of single-cell transcriptomic data illuminates the regulatory network architecture of plant cell fate specification

Plant morphogenesis relies on precise gene expression programs at the proper time and position which is orchestrated by transcription factors (TFs) in intricate regulatory networks at a cell-type specific manner. Here we presented a reference single-cell transcriptomic atlas of Arabidopsis seedlings by integration of 40 published scRNA-seq datasets from representative tissues as well as the entire under- and above-ground parts. We identified 34 distinct cell types or states, largely expanding our current view of plant cell compositions. We then mapped the developmental trajectory of root-shoot lineage separation and identified differential gene expression programs that may regulate the cell fate determination of under- and above-ground organs. Lastly, we systematically constructed cell-type specific gene regulatory networks and uncovered key regulators that act in a coordination manner to control cell-type specific gene expression. Taken together, our study not only offers a valuable resource plant cell atlas exploration but also provides molecular insights into gene-regulatory programs that determines organ specify, particularly the differentiation between root and shoot.

bioinformatics↗