Biology subjects

Shi, X.

Publications and source records attributed to Shi, X..

At least 163 records · Page 9Linked to original sources

bioRxiv2022

Pericytes control vascular stability and auditory spiral ganglion neuron survival

The inner ear has a rich population of pericytes, a multi-functional mural cell essential for sensory hair cell heath and normal hearing. However, the mechanics of how pericytes contribute to the homeostasis of the auditory vascular-neuronal complex in the spiral ganglion is not yet known. In this study, using an inducible and conditional pericyte depletion mouse (PdgfrbCreERT2+/-; ROSA26iDTR+/-) model, we demonstrate, for the first time, that pericyte depletion causes loss of vascular volume and spiral ganglion neurons (SGNs) and adversely affects hearing sensitivity. Using an in vitro trans-well co-culture system, we show pericytes markedly promote neurite and vascular branch growth in neonatal SGN explants and adult SGNs. The pericyte-controlled neural growth is strongly mediated by pericyte-released exosomes containing vascular endothelial growth factor-A (VEGF-A). Treatment of neonatal SGN explants or adult SGNs with pericyte-derived exosomes significantly enhances angiogenesis, SGN survival, and neurite growth, all of which were inhibited by a selective blocker of the VEGF receptor 2 (Flk1). Our study demonstrates that pericytes in the adult ear are critical for vascular stability and SGN health. Cross-talk between pericytes and SGNs via exosomes is essential for neuronal and vascular health and normal hearing.

neuroscience↗

bioRxiv2022

Droplet microfluidics forward for tracing target cells at single-cell transcriptome resolution

The rapid promotion of single-cell omics in various fields has begun to help solve many problems encountered in research including precision medicine, prenatal diagnosis, and embryo development. Meanwhile, single-cell techniques are also constantly updated with increasing demand. For some specific target cells, the workflow from droplet screening to single-cell sequencing is a preferred option, which also should reduce the impact of operation steps such as demulsification and cell recovery. We developed an all-in-droplet method integrating cell encapsulation, target sorting, droplet picoinjection, and single-cell transcriptome profiling on chips to achieve a labor-saving monitor of TCR-T cells. As a proof of concept, in this research, TCR-T cells were encapsulated, sorted, and performed single-cell transcriptome sequencing (scRNA-seq) by injecting reagents into droplet. It avoided the tedious operation of droplet breakage and re-encapsulation between droplet sorting and scRNA-seq. Moreover, convenient device operation will accelerate the progress of chip marketization. The strategy achieved an excellent recovery performance of single cell transcriptome with a median gene number over 4000 and a cross-contamination rate of 8.2 {+/-} 2%. Furthermore, this strategy allows us to develop a device with high integrability to monitor infused TCR-T cells, which will promote the development of adoptive T cell immunotherapy and their clinical application.

cell biology↗

bioRxiv2022

SPRAY-INDUCED GENE SILENCING IDENTIFIES PATHOGEN PROCESSES CONTRIBUTING TO POWDERY MILDEW PROLIFERATION

Spray-induced gene silencing (SIGS) is an emerging tool for crop pest protection. It utilizes exogenously applied double stranded RNA to specifically reduce pest target gene expression using endogenous RNA interference machinery. Powdery mildews, widespread obligate biotrophic fungi infect agricultural crops including wheat, barley, cucurbits, grapevine, and ornamentals such as roses. In this study, SIGS methods were developed and optimized for powdery mildews using the known azole-fungicide target CYP51 and the Golovinomyces orontii-Arabidopsis thaliana pathosystem. Additional screening resulted in the identification of conserved gene targets and processes important to powdery mildew proliferation: apoptosis-antagonizing transcription factor in essential cellular metabolism and stress response; lipase a, lipase 1, and acetyl-CoA oxidase in lipid catabolism; 9-cis-epoxycarotenoid dioxygenase, xanthoxin dehydrogenase, and a putative abscisic acid G-protein coupled receptor predicted to function in manipulation of the plant hormone abscisic acid; and the secreted effector EC2. Powdery mildew is the dominant disease impacting grapes and extensive powdery mildew resistance to applied fungicides has been reported. Therefore, we developed SIGS for the Erysiphe necator-Vitis vinifera system and tested six successful targets identified using the G. orontii-A. thaliana system. For all targets tested, a similar reduction in powdery mildew disease was observed between systems. This indicates screening of broadly conserved targets in the G. orontii-A. thaliana pathosystem identifies targets and processes for the successful control of other powdery mildews. The flexibility, specificity, reduced environmental and health risks, and rapid transition from the bench to the field make SIGS an exciting prospect for commercial powdery mildew control.

microbiology↗

bioRxiv2022

Orientation-locked DNA origami for stable trapping of small proteins in the NEOtrap

Nanopores are versatile single-molecule sensors that offer a simple label-free readout with great sensitivity. We recently introduced the Nanopore Electro-Osmotic trap (NEOtrap) which can trap and sense single unmodified proteins for long times. The trapping is achieved by the electro-osmotic flow (EOF) generated from a DNA-origami sphere docked onto the pore, but thermal fluctuations of the origami limited the trapping of small proteins. Here, we use site-specific cholesterol functionalization of the origami sphere to firmly link it to the lipid-coated nanopore. We can lock the origami in either a vertical or horizontal orientation which strongly modulates the EOF. The optimized EOF greatly enhances the trapping capacity, yielding reduced noise, reduced measurement heterogeneity, an increased capture rate, and 100-fold extended observation times. We demonstrate the trapping of a variety of single proteins, including small ones down to a molecular mass of 14 kDa. The cholesterol functionalization significantly expands the application range of the NEOtrap technology.

biophysics↗

bioRxiv2022

Combinatorial perturbation sequencing on single cells using microwell-based droplet random pairing

Combinatorial drug therapy reduces drug resistance and disease relapse, but informed drug combinations are lacking due to the high scale of possible combinations and the relatively simple phenotyping strategies. Here we report combinatorial perturbation sequencing (CP-seq) on single cells using microwell-base droplet random pairing. CP-seq uses oligonucleotides to barcode drugs, encapsulates drugs and cells in separate droplets, and pairs cell droplets with two drug droplets randomly on a microwell array chip to complete combinatorial drug treatment and barcode-tagging on cells. The subsequent single-cell RNA sequencing simultaneously detects the single-cell transcriptomes and drug barcodes to demultiplex the corresponding drug treatment. The microfluidic droplet operations had robust performance, with overall success rate among the microwells being up to 83%. We then progressively validated the CP-seq by performing single drug treatment and then combinatorial drug treatment. Leveraging the advantage of droplet microfluidics in massive multiplexing, the CP-seq can test thousands of drug combinations in a single experiment and represents a great technology for combinatorial perturbation screening with high throughput and comprehensive profiling.

bioengineering↗

bioRxiv2022

Systematic comparison and rational design of theophylline riboswitches for efficient gene repression

Riboswitches are promising regulatory tools in synthetic biology. To date, 25 theophylline riboswitches have been developed for gene expression regulation in bacteria. However, no one has systematically evaluated their regulatory effects. To facilitate rational selection of theophylline riboswitches, we examined 25 theophylline riboswitches in Escherichia coli and surprised to find that none of the five repressive riboswitches were more than 2-fold effective. To solve this problem, we rationally designed a transcriptional repressive riboswitch and demonstrated its effect not only in various bacterial strains but also in different growth media or different temperatures. By introducing two copies of theophylline riboswitches and a RepA protein degradation tag coding sequence at the 5-end of a reporter gene, we successfully constructed a dual gene expression regulatory system with up to 150-fold potency, namely the R2-RepA system. R2-RepA system is only 218 bp in length, expression of any protein could be repressed efficiently by simply inserting this system upstream of the target protein-coding sequence. This study represented a crucial step toward harnessing theophylline riboswitches and expanding the synthetic biology toolbox.

synthetic biology↗

bioRxiv2022

Probabilistic embedding and clustering with alignment for spatial transcriptomics data integration with PRECAST

Spatially resolved transcriptomics involves a set of emerging technologies that enable the transcriptomic profiling of tissues with the physical location of expressions. Although a variety of methods have been developed for data integration, most of them are for single-cell RNA-seq datasets without consideration of spatial information. Thus, methods that can integrate spatial transcriptomics data from multiple tissue slides, possibly from multiple individuals, are needed. Here, we present PRECAST, a data integration method for multiple spatial transcriptomics datasets with complex batch effects and/or biological effects between slides. PRECAST unifies spatial factor analysis simultaneously with spatial clustering and embedding alignment, while requiring only partially shared cell/domain clusters across datasets. Using both simulated and four real datasets, we show improved cell/domain detection with outstanding visualization, and the estimated aligned embeddings and cell/domain labels facilitate many downstream analyses. We demonstrate that PRECAST is computationally scalable and applicable to spatial transcriptomics datasets from different platforms.

genomics↗

bioRxiv2022

Thinking like a structural biologist: A pocket-based 3D molecule generative model fueled by electron density

We report for the first time the use of experimental electron density (ED) as training data for the generation of drug-like three-dimensional molecules based on the structure of a target protein pocket. Similar to a structural biologist building molecules based on their ED, our model functions with two main components: a generative adversarial network (GAN) to generate the ligand ED in the input pocket and an ED interpretation module for molecule generation. The model was tested on three targets including kinase (HPK1), protease (Covid19-3CL), and nuclear receptor (VDR), and evaluated with a reference dataset composed of over 8,000 compounds that have their activities reported in the literature. The evaluation examined the chemical validity, chemical space distribution-based diversity, and similarity with reference active compounds concerning the molecular structure and pocket-binding mode. Our model can reproduce classical active compounds and can also generate novel molecules with similar binding modes as active compounds, making it a promising tool for library generation supporting high-throughput virtual screening. Our model is available as an online service to academic users via https://edmg.stonewise.cn/#/create.

bioinformatics↗

bioRxiv2022

Development and application of an uncapped mRNA platform

A novel uncapped mRNA platform was developed. Five lipid nanoparticle (LNP)-encapsulated mRNA constructs were made to evaluate several aspects of our platform, including transfection efficiency and durability in vitro and in vivo and the activation of humoral and cellular immunity in several animal models. The constructs were eGFP-mRNA-LNP (for enhanced green fluorescence mRNA), Fluc-mRNA-LNP (for firefly luciferase mRNA), S{delta}T-mRNA-LNP (for Delta strain SARS-CoV-2 spike protein trimer mRNA), gDED-mRNA-LNP (for truncated glycoprotein D mRNA coding ectodomain from herpes simplex virus type 2 (HSV2)) and gDFR-mRNA-LNP (for truncated HSV2 glycoprotein D mRNA coding amino acids 1[~]400). Quantifiable target protein expression was achieved in vitro and in vivo with eGFP-and Fluc-mRNA-LNP. S{delta}T-mRNA-LNP, gDED-mRNA-LNP and gDFR-mRNA-LNP induced both humoral and cellular immune responses comparable to those obtained by previously reported capped mRNA-LNP constructs. Notably, S{delta}T-mRNA-LNP elicited neutralizing antibodies in hamsters against the Omicron and Delta strains. Additionally, gDED-mRNA-LNP and gDFR-mRNA-LNP induced potent neutralizing antibodies in rabbits and mice. The mRNA constructs with uridine triphosphate (UTP) outperformed those with N1-methylpseudouridine triphosphate (N1m{psi}TP) in the induction of antibodies via S{delta}T-mRNA-LNP. Our uncapped, process-simplified, and economical mRNA platform may have broad utility in vaccines and protein replacement drugs.

bioengineering↗

bioRxiv2022

A Parabrachial to Hypothalamic Neurocircuit Mediates Defensive Behavior

Defensive behaviors are critical for animals survival. Both the paraventricular nucleus of the hypothalamus (PVN) and the parabrachial nucleus (PBN) have been shown to be involved in defensive behaviors. However, whether there are direct connections between them to mediate defensive behaviors remains unclear. Here, by retrograde and anterograde tracing, we uncover that cholecystokinin (CCK)-expressing neurons in the lateral PBN (LPBCCK) directly project to the PVN. By in vivo fiber photometry recording, we found that LPBCCK neurons actively respond to various threat stimuli. Selective photoactivation of LPBCCK neurons promotes aversion and defensive behaviors. Conversely, photoinhibition of LPBCCK neurons attenuates rat or looming stimuli-induced flight responses. Optogenetic activation of LPBCCK axon terminals within the PVN or PVN glutamatergic neurons promote defensive behaviors. Whereas chemogenetic and pharmacological inhibition of local PVN neurons prevent LPBCCK-PVN pathway activation-driven flight responses. These data suggest that LPBCCK neurons recruit downstream PVN neurons to actively engage in flight responses. Our study identifies a previously unrecognized role for the LPBCCK-PVN pathway in controlling defensive behaviors.

neuroscience↗

bioRxiv2022

Structural basis of a two-antibody cocktail exhibiting highly potent and broadly neutralizing activities against SARS-CoV-2 variants including diverse Omicron sublineages

SARS-CoV-2 variants of concern (VOCs), especially the latest Omicron, have exhibited severe antibody evasion. Broadly neutralizing antibodies with high potency against Omicron are urgently needed for understanding working mechanisms and developing therapeutic agents. In this study, we characterized previously reported F61, which was isolated from convalescent patients infected with prototype SARS-CoV-2, as a broadly neutralizing antibody against all VOCs including Omicron BA.1, BA.1.1, BA.2, BA.3 and BA.4 sublineages by utilizing antigen binding and cell infection assays. We also identified and characterized another broadly neutralizing antibody D2 with epitope distinct from that of F61. More importantly, we showed that a combination of F61 with D2 exhibited synergy in neutralization and protecting mice from SARS-CoV-2 Delta and Omicron BA.1 variants. Cryo-EM structures of the spike-F61 and spike-D2 binary complexes revealed the distinct epitopes of F61 and D2 at atomic level and the structural basis for neutralization. Cryo-EM structure of the Omicron-spike-F61-D2 ternary complex provides further structural insights into the synergy between F61 and D2. These results collectively indicated F61 and F61-D2 cocktail as promising therapeutic antibodies for combating SARS-CoV-2 variants including diverse Omicron sublineages.

biochemistry↗

bioRxiv2022

A Unified Catalog of 19,251 Non-human Reference Species Genomes Provides New Insights into the Mammalian Gut Microbiomes

The gut microbiota is essential for host health and survival. Here, using samples from animals living in the Qinghai-Tibetan Plateau, we recovered 119,568 metagenome-assembled genomes (MAGs) that were clustered into 19,251 species-level genome bins (SGBs) of which most represent novel species. We present a novel mechanism shaping mammalian gut microbiomes using ancestral founder bacteria (AFB) as a core skeleton and recurring lineage-specific gains of microbial species that are transferred frequently among multiple hosts, not strictly limited by host phylogeny. Such lineage specific gains are responsible for increasing gut microbial diversity, maintaining functional stability, and endowing specific functions for host adaptions. Our analyses did not support the existence of co-phylogeny or co-speciation events between mammal hosts and their individual gut symbionts. The results presented in this study not only reveal novel unique gut microbial species and offer insight of value for understanding the diversity, stability, functionality of the mammalian gut microbiomes, and the co-evolution with their hosts, but also emphasize that animals living in extreme environments are a promising resource for the discovery of novel biological functions.

microbiology↗

bioRxiv2022

Broadly neutralizing and protective nanobodies against diverse sarbecoviruses

As SARS-CoV-2 Omicron and other variants of concern continue spreading around the world, development of antibodies and vaccines to confer broad and protective activity is a global priority. Here, we report on the identification of a special group of nanobodies from immunized alpaca with exceptional breadth and potency against diverse sarbecoviruses including SARS-CoV-1, Omicron BA.1, and BA.2. Crystal structure analysis of one representative nanobody, 3-2A2-4, revealed a highly conserved epitope between the cryptic and the outer face of the receptor binding domain (RBD). The epitope is readily accessible regardless of RBD in "up" or "down" conformation and distinctive from the receptor ACE2 binding site. Passive delivery of 3-2A2-4 protected K18-hACE2 mice from infection of authentic SARS-CoV-2 Delta and Omicron. This group of nanobodies and the epitope identified should provide invaluable reference for the development of next generation antibody therapies and vaccines against wide varieties of SARS-CoV-2 infection and beyond.

immunology↗

bioRxiv2022

TCGADEPMAP -- Mapping Translational Dependencies and Synthetic Lethalities within The Cancer Genome Atlas

The Cancer Genome Atlas (TCGA) has yielded unprecedented genetic and molecular characterization of the cancer genome, yet the functional consequences and patient-relevance of many putative cancer drivers remain undefined. TCGADEPMAP is the first hybrid map of translational tumor dependencies that was built from machine learning of gene essentiality in the Cancer Dependency Map (DEPMAP) and then translated to TCGA patients. TCGADEPMAP captured well-known and novel cancer lineage dependencies, oncogenes, and synthetic lethalities, demonstrating the robustness of TCGADEPMAP as a translational dependency map. Exploratory analyses of TCGADEPMAP also unveiled novel synthetic lethalities, including the dependency of PAPSS1 driven by loss of PAPSS2 which is collaterally deleted with the tumor suppressor gene PTEN. Synthetic lethality of PAPSS1/2 was validated in vitro and in vivo, including the underlying mechanism of synthetic lethality caused by the loss of protein sulfonation that requires PAPSS1 or PAPSS2. Moreover, TCGADEPMAP demonstrated that patients with predicted PAPSS1/2 synthetic lethality have worse overall survival, suggesting that these patients are in greater need of drug discovery efforts to target PAPSS1. Other map "extensions" were built to capture unique aspects of patient-relevant tumor dependencies using the flexible analytical framework of TCGADEPMAP, including translating gene essentiality to drug response in patient-derived xenograft (PDX) models (i.e., PDXEDEPMAP) and predicting gene tolerability within normal tissues (GTEXDEPMAP). Collectively, this study demonstrates how translational dependency maps can be used to leverage the rapidly expanding catalog of patient genomic datasets to identify and prioritize novel therapeutic targets with the best therapeutic indices.

cancer biology↗

bioRxiv2022

Discovery of therapeutic agents targeting PKLR for NAFLD using drug repositioning

Background & AimsNon-alcoholic fatty liver disease (NAFLD) encompasses a wide spectrum of liver pathologies. However, not medical treatment has been approved for the treatment of the disease. In our previous study, we found PKLR could be a potential target for treatment of NALFD. Here, the aim is to investigate the effect of PKLR in in vivo model and perform drug repositioning to identify a drug candidate for treatment of NAFLD. MethodsBiopsies from liver, muscle, white adipose tissue and heart were obtained from control and PKLR knockout mice fed with chow and high sucrose diets. Lipidomics as well as transcriptmics analyses were conducted using these tissue samples. In addition, a computational drug repositioning analysis was performed and drug candidates were identified. The drug candidates were finally tested in both in vitro and in vivo models to evaluated their toxicity and efficacy. ResultsThe Pklr KO reversed the increased hepatic triglyceride level in mice fed with high sucrose diet and partly recovered the transcriptomic changes in liver as well as other three tissues. Both liver and white adipose tissues exhibited dysregulated circadian transcriptomic profiles, and these dysregulations were reversed by hepatic knockout of Pklr. In addition, 10 small molecule drugs were identified as potential inhibitor of PKLR by the drug repositioning pipeline, and two of them significantly inhibited both the PKLR expression and triglyceride level in in vitro model. Finally, the two selected small molecule drugs were evaluated in in vivo rat models and it was demonstrated that these drugs attenuated hepatic steatosis without side effect on other tissues. ConclusionIn conclusion, our study provided biological insights about the critical role of PKLR in NAFLD progression and proposed a treatment strategy for NAFLD patients, which has been validated in preclinical experiment.

systems biology↗

bioRxiv2022

Modeling of Alpha-1 Antitrypsin Deficiency with Syngeneic Human iPSC-Hepatocytes Reveals Metabolic Dysregulation and Cellular Heterogeneity in PiMZ and PiZZ Hepatocytes

Individuals homozygous for the pathogenic "Z" mutation in alpha-1 antitrypsin deficiency (AATD) are known to be at increased risk for chronic liver disease. That some degree of risk is similarly conferred by the heterozygous state, estimated to affect 2% of the US population, has also become clear. A lack of model systems that recapitulate heterozygosity in human hepatocytes has limited the ability to study the impact of expressing a single ZAAT allele on hepatocyte biology. Here, through the application of CRISPR-Cas9 editing, we describe the derivation of syngeneic induced pluripotent stem cells (iPSCs) engineered to determine the effects of ZAAT heterozygosity in iPSC-derived hepatocytes (iHeps) relative to homozygous mutant (ZZ) or corrected (MM) cells. We find that heterozygous MZ iHeps exhibit an intermediate disease phenotype and share with ZZ iHeps alterations in AAT protein processing and downstream perturbations in hepatic metabolic function including ER and mitochondrial morphology, reduced mitochondrial respiration, and branch-specific activation of the unfolded protein response in subpopulations of cells. Our cellular model of MZ heterozygosity thus provides evidence that expression of a single Z allele is sufficient to disrupt hepatocyte homeostatic function and suggest a mechanism underlying the increased risk of liver disease observed among MZ individuals.

cell biology↗

bioRxiv2022

SELINA: Single-cell Assignment using Multiple-Adversarial Domain Adaptation Network with Large-scale References

The rapid accumulation of single-cell RNA-seq data has provided rich resources to characterize various human cell types. Cell type annotation is the critical step in analyzing single-cell RNA-seq data. However, accurate cell type annotation based on public references is challenging due to the inconsistent annotations, batch effects, and poor characterization of rare cell types. Here, we introduce SELINA (single cELl identity NAvigator), an integrative annotation transferring framework for automatic cell type annotation. SELINA optimizes the annotation for minority cell types by synthetic minority over-sampling, removes batch effects among reference datasets using a multiple-adversarial domain adaptation network (MADA), and fits the query data with reference data using an autoencoder. Finally, SELINA affords a comprehensive and uniform reference atlas with 1.7 million cells covering 230 major human cell types. We demonstrated the robustness and superiority of SELINA in most human tissues compared to existing methods. SELINA provided a one-stop solution for human single-cell RNA-seq data annotation with the potential to extend for other species.

bioinformatics↗

bioRxiv2021

Joint dimension reduction and clustering analysis for single-cell RNA-seq and spatial transcriptomics data

Dimension reduction and (spatial) clustering is usually performed sequentially; however, the low-dimensional embeddings estimated in the dimension-reduction step may not be relevant to the class labels inferred in the clustering step. We therefore developed a computation method, Dimension-Reduction Spatial-Clustering (DR-SC), that can simultaneously perform dimension reduction and (spatial) clustering within a unified framework. Joint analysis by DR-SC produces accurate (spatial) clustering results and ensures the effective extraction of biologically informative low-dimensional features. DR-SC is applicable to spatial clustering in spatial transcriptomics that characterizes the spatial organization of the tissue by segregating it into multiple tissue structures. Here, DR-SC relies on a latent hidden Markov random field model to encourage the spatial smoothness of the detected spatial cluster boundaries. Underlying DR-SC is an efficient expectation-maximization algorithm based on an iterative conditional mode. As such, DR-SC is scalable to large sample sizes and can optimize the spatial smoothness parameter in a data-driven manner. With comprehensive simulations and real data applications, we show that DR-SC outperforms existing clustering and spatial clustering methods: it extracts more biologically relevant features than conventional dimension reduction methods, improves clustering performance, and offers improved trajectory inference and visualization for downstream trajectory inference analyses.

genomics↗