Biology subjects

Yang, P.

Publications and source records attributed to Yang, P..

At least 145 records · Page 8Linked to original sources

bioRxiv2021

Spatial analysis for highly multiplexed imaging data to identify tissue microenvironments

Highly multiplexed in situ imaging cytometry assays have made it possible to study the spatial organisation of numerous cell types simultaneously. We have addressed the challenge of quantifying complex multi-cellular relationships by proposing a statistical method which clusters local indicators of spatial association. Our approach successfully identifies distinct tissue architectures in datasets generated from three state-of-the-art high-parameter assays demonstrating its value in summarising the information-rich data generated from these technologies.

bioinformatics↗

bioRxiv2021

Learning directed acyclic graphs for ligands and receptors based on spatially resolved transcriptomic analysis of ovarian cancer

To unravel the mechanism of immune activation and suppression within tumors, a critical step is to identify transcriptional signals governing cell-cell communication between tumor and immune/stromal cells in the tumor microenvironment. Central to this communication are interactions between secreted ligands and cell-surface receptors, creating a highly connected signaling network among cells. Recent advancement in in situ-omics profiling, particularly spatial transcriptomic (ST) technology, provide unique opportunities to directly characterize ligand-receptor signaling networks that powers cell-cell communication. In this paper, we propose a novel statistical method, LRnetST, to characterize the ligand-receptor interaction networks between adjacent tumor and stroma cells based on ST data. LRnetST utilizes a directed acyclic graph (DAG) model with a novel treatment to handle the zero-inflated distribution observed in the ST data. It also leverages existing ligand-receptor regulation databases as prior information, and employs a bootstrap aggregation strategy to achieve robust network estimation. Application of LRnetST to ST data of high-grade serous ovarian tumor samples revealed both common and distinct ligand-receptor regulations across different tumors. Some of these interactions were validated through a MERFISH data set of independent ovarian tumor samples. These results cast light on biological processes relating to the communication between tumor and immune/stromal cells in ovarian tumors. An open-source R package of LRnetST is available on GitHub at https://github.com/jie108/LRnetST.

systems biology↗

bioRxiv2021

Single-cell RNA Sequencing Reveals the Temporal Diversity and Dynamics of Cardiac Immunity after Myocardial Infarction

Myocardial infarction (MI) is strongly associated with the temporal regulation of cardiac immunity. However, a variety of current clinical trials have failed because of the lack of post-MI immunomodulating/anti-inflammatory targets. We performed single-cell RNA sequencing analysis of cardiac Cd45+ immune cell at 0, 3, 7, and 14 days after injury in a mouse left anterior descending coronary artery ligation model. Major immune cell populations, distinct subsets, and dynamic changes were identified. Macrophages (Mo)/monocytes were most abundant, peaking at 3 days after infarction. Mo-5 and Mo-6 were the predominant infiltrated subsets at this time point, with strong expression of inflammatory factors. Further analysis demonstrated that suppressing these sets attenuated pathological MI progression by preventing subsequent leukocyte extravasation and adverse remodeling. We also detected abundant apoptotic neutrophils and a profibrotic macrophage subset on days 7 and 14 respectively. These results provide a basis for developing cell type- and time-specific interventions in MI. Graphic abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=179 SRC="FIGDIR/small/452902v1_ufig1.gif" ALT="Figure 1"> View larger version (53K): org.highwire.dtl.DTLVardef@1d7c810org.highwire.dtl.DTLVardef@18f9c9dorg.highwire.dtl.DTLVardef@17325f7org.highwire.dtl.DTLVardef@c1a4e7_HPS_FORMAT_FIGEXP M_FIG C_FIG Temporal regulation of cardiac immunity is strongly associated with the onset, progression, and outcomes of MI. Our study of time-series scRNA-seq on the whole cardiac immune cells isolated from the LAD ligation mice and the tanshinone IIA treated mice shed light on the underlying pathology of MI.

cell biology↗

bioRxiv2021

A benchmark study of simulation methods for single-cell RNA sequencing data

Single-cell RNA-seq (scRNA-seq) data simulation is critical for evaluating computational methods for analysing scRNA-seq data especially when ground truth is experimentally unattainable. The reliability of evaluation depends on the ability of simulation methods to capture properties of experimental data. However, while many scRNA-seq data simulation methods have been proposed, a systematic evaluation of these methods is lacking. We developed a comprehensive evaluation framework, SimBench, including a novel kernel density estimation measure to benchmark 12 simulation methods through 35 scRNA-seq experimental datasets. We evaluated the simulation methods on a panel of data properties, ability to maintain biological signals, scalability and applicability. Our benchmark uncovered performance differences among the methods and highlighted the varying difficulties in simulating data characteristics. Furthermore, we identified several limitations including maintaining heterogeneity of distribution. These results, together with the framework and datasets made publicly available as R packages, will guide simulation methods selection and their future development.

bioinformatics↗

bioRxiv2021

Single-cell transcriptome profiling reveals multicellular ecosystem of nucleus pulposus during degeneration progression

Degeneration of the nucleus pulposus (NP) is a major contributor to intervertebral disc degeneration (IVDD) and low back pain. However, the underlying molecular complexity and cellular heterogeneity remain poorly understood. Here, we first reported a comprehensive single-cell resolution transcriptional landscape of human NP. Six novel human nucleus pulposus cell (NPCs) populations were identified by distinct molecular signatures. The potential functional differences among NPC subpopulations were analyzed at the single-cell level. Predictive genes, transcriptional factors, and signal pathways with respect to degeneration grades were analyzed. We reported that fibroNPCs, one of our identified subpopulations, might be a population for NP regeneration. CD90+NPCs were observed to be progenitor cells in degenerative NP tissues. NP-infiltrating immune cells comprise a previously unrecognized diversity of cell types, including granulocytic myeloid-derived suppressor cells (G-MDSCs). We uncovered CD11b, OLR1, and CD24 as surface markers of NP-derived G-MDSCs. The G-MDSCs were also found to be enriched in mildly degenerated (grade I and II) NP tissues compared to severely degenerated (grade III and IV) NP tissues. Their immunosuppressive function and protective effects for NPCs were revealed. Collectively, this study revealed the NPC type complexity and phenotypic characteristics in NP, providing new insights and clues for IVDD treatment.

cell biology↗

bioRxiv2021

Differentiation of cortical brain organoids and optic nerve-like structures from retinal confluent cultures of pluripotent stem cells

Advances in the study of neurological conditions have been possible due to induced pluripotent stem cell technologies and the generation of neural cell types and organoids. Numerous studies have described the generation of neural ectoderm-derived retinal and brain structures from pluripotent stem cells. However, the field is still troubled by technical challenges, including high culture costs and organoid-to-organoid variability. Here, we describe a simple and economical protocol that reproducibly gives rise to the neural retina and cortical brain regions from confluent cultures of stem cells. The spontaneously generated cortical organoids were isolated and cultured in suspension conditions for maturation and are transcriptionally comparable to organoids generated by other methods and to human foetal cortex. Furthermore, these organoids show spontaneous functional network activity with proteomic analysis and electron microscopy demonstrating the presence of synaptic components and maturity. The generation of retinal and brain organoids in close proximity also enabled their mutual isolation. Further culture of this complex organoid system demonstrated the formation of optic nerve-like structures connecting retinal and brain organoids, which might facilitate the investigation of the mechanisms of neurological diseases of the eye and brain.

neuroscience↗

bioRxiv2021

Decoding microbiome and protein family linkage to improve protein structure prediction

Information extracted from microbiome sequences through deep-learning techniques can significantly improve protein structure and function modeling. However, the model training and metagenome search were largely blind with low efficiency. Built on 4.25 billion microbiome sequences from four major biomes (Gut, Lake, Soil and Fermentor), we proposed a MetaSource model to decode the inherent link of microbial niches with protein homologous families. Large-scale protein family folding experiments showed that a targeted approach using predicted biomes significantly outperform combined metagenome datasets in both speed of MSA collection and accuracy of deep-learning structure assembly. These results revealed the important link of biomes with protein families and provided a useful bluebook to guide future microbiome sequence database and modeling development for protein structure and function prediction.

bioinformatics↗

bioRxiv2021

Characterization of a glycolipid glycosyltransferase with broad substrate specificity from the marine bacterium Candidatus Pelagibacter sp. HTCC7211

In the marine environment, phosphorus availability significantly affects the lipid composition in many cosmopolitan marine heterotrophic bacteria, including members of the SAR11 clade and the Roseobacter clade. Under phosphorus stress conditions, non-phosphorus sugar-containing glycoglycerolipids are substitutes for phospholipids in these bacteria. Although these glycoglycerolipids play an important role as surrogates for phospholipids under phosphate deprivation, glycoglycerolipid synthases in marine microbes are poorly studied. In the present study, we biochemically characterized a glycolipid glycosyltransferase (GTcp) from the marine bacterium Candidatus Pelagibacter sp. HTCC7211, a member of the SAR11 clade. Our results showed that GTcp is able to act as a multifunctional enzyme by synthesizing different glycoglycerolipids with UDP-glucose, UDP-galactose, or UDP-glucuronic acid as sugar donors and diacylglycerol as the acceptor. Analyses of enzyme kinetic parameters demonstrated that Mg2+ notably changes the enzymes affinity for UDP-glucose, which improves its catalytic efficiency. Homology modelling and mutational analyses revealed binding sites for the sugar donor and the diacylglycerol lipid acceptor, which provided insights into the retaining mechanism of GTcp with its GT-B fold. A phylogenetic analysis showed that GTcp and its homologs form a group in the GT4 glycosyltransferase family. These results not only provide new insights into the glycoglycerolipid synthesis mechanism in lipid remodelling, but also describe an efficient enzymatic tool for future synthesis of bioactive molecules. ImportanceThe bilayer formed by membrane lipids serves as the containment unit for living microbial cells. In the marine environment, it has been firmly established that phytoplankton and heterotrophic bacteria can substitute phospholipids with non-phosphorus sugar-containing glycoglycerolipids in response to phosphorus limitation. However, little is known about how these glycoglycerolipids are synthesized. Here, we determined the biochemical characteristics of a glycolipid glycosyltransferase (GTcp) from the marine bacterium Candidatus Pelagibacter sp. HTCC7211. GTcp and its homologs form a group in the GT4 glycosyltransferase family, and can synthesize neutral glycolipids (MGlc-DAG and MGal-DAG) and an acidic glycolipid (MGlcA-DAG). We also uncover the key residues for DAG-binding through molecular docking, site-direct mutagenesis and subsequent enzyme activity assays. Our data provide new insights into the glycoglycerolipid synthesis mechanism in lipid remodelling.

microbiology↗

bioRxiv2021

GproDIA enables data-independent acquisition glycoproteomics with comprehensive statistical control

Large-scale profiling of intact glycopeptides is critical but challenging in glycoproteomics. Data independent acquisition (DIA) is an emerging technology with deep proteome coverage and accurate quantitative capability in proteomics studies, but is still in the early stage of development in the field of glycoproteomics. We propose GproDIA, a framework for the proteome-wide characterization of intact glycopeptides from DIA data with comprehensive statistical control by a 2-dimentional false discovery rate approach and a glycoform inference algorithm, enabling accurate identification of intact glycopeptides using wide isolation windows. We further adapt a semi-empirical spectrum prediction strategy to expand the coverage of spectral libraries of glycopeptides. We benchmark our method for N-glycopeptide profiling on DIA data of yeast and human serum samples, demonstrating that DIA with GproDIA outperforms the data dependent acquisition (DDA) based methods for glycoproteomics in terms of capacity and data completeness of identification, as well as accuracy and precision of quantification. We expect that this work can provide a powerful tool for glycoproteomic studies.

bioinformatics↗

bioRxiv2021

Gold nanocluster mediated delivery of siRNA to intact plant cells for efficient gene knockdown

RNA interference (RNAi), which involves the delivery of small interfering RNA molecules (siRNA), has been used to validate target genes in plants, to understand and control cellular metabolic pathways, and as a green alternative for crop pest tolerance. Conventional siRNA delivery methods such as viruses and Agrobacterium-mediated delivery exhibit limitations in host plant species range and their use can result in uncontrolled DNA integration into the plant host genome. Here, we synthesize polyethyleneimine functionalized gold nanoclusters (PEI-AuNCs) to mediate siRNA delivery into intact plant cells and show these constructs enable efficient gene knockdown. We demonstrate that functionalized AuNCs protect siRNA from RNase degradation and are small enough (~2 nm) to bypass the plant cell wall which exhibits a size exclusion limit of 5-20 nm. These AuNCs in turn enable up to 76.5 {+/-} 5.9% GFP mRNA knockdown efficiency with no cellular toxicity. Our data suggest this simple and biocompatible platform for passive delivery of siRNA into intact plant cells could have broad applications in plant biotechnology.

bioengineering↗

bioRxiv2021

Community Evaluation of Glycoproteomics Informatics Solutions Reveals High-Performance Search Strategies of Glycopeptide Data

Glycoproteome profiling (glycoproteomics) is a powerful yet analytically challenging research tool. The complex tandem mass spectra generated from glycopeptide mixtures require sophisticated analysis pipelines for structural determination. Diverse software aiding the process have appeared, but their relative performance remains untested. Conducted through the HUPO Human Proteome Project - Human Glycoproteomics Initiative, this community study, comprising both developers and users of glycoproteomics software, evaluates the performance of informatics solutions for system-wide glycopeptide analysis. Mass spectrometry-based glycoproteomics datasets from human serum were shared with all teams. The relative team performance for N- and O-glycopeptide data analysis was comprehensively established and validated through orthogonal performance tests. Excitingly, several high-performance glycoproteomics informatics solutions were identified. While the study illustrated that significant informatics challenges remain, as indicated by a high discordance between annotated glycopeptides, lists of high-confidence (consensus) glycopeptides were compiled from the standardised team reports. Deep analysis of the performance data revealed key performance-associated search variables and led to recommendations for improved "high coverage" and "high accuracy" glycoproteomics search strategies. This study concludes that diverse software for comprehensive glycopeptide data analysis exist, points to several high-performance search strategies, and specifies key variables that may guide future software developments and assist informatics decision-making in glycoproteomics.

biochemistry↗

bioRxiv2021

SnapKin: a snapshot deep learning ensemble for kinase-substrate prediction from phosphoproteomics data

Mass spectrometry (MS)-based phosphoproteomics enables the quantification of proteome-wide phosphorylation in cells and tissues. A major challenge in MS-based phosphoproteomics lies in identifying the substrates of kinases, as currently only a small fraction of substrates identified can be confidently linked with a known kinase. By leveraging large-scale phosphoproteomics data, machine learning has become an increasingly popular approach for computationally predicting substrates of kinases. However, the small number of high-quality experimentally validated kinase substrates (true positive) and the high data noise in many phosphoproteomics datasets together impact the performance of existing approaches. Here, we aim to develop advanced kinase-substrate prediction methods to address these challenges. Using a collection of seven large phosphoproteomics datasets, including six published datasets and a new muscle differentiation dataset, and both traditional and deep learning models, we first demonstrate that a pseudo-positive learning strategy for alleviating small sample size is effective at improving model predictive performance. We next show that a data re-sampling based ensemble learning strategy is useful for improving model stability while further enhancing prediction. Lastly, we introduce an ensemble deep learning model ( SnapKin) incorporating the above two learning strategies into a snapshot ensemble learning algorithm. We demonstrate that the SnapKin model achieves overall the best performance in kinase-substrate prediction. Together, we propose SnapKin as a promising approach for predicting substrates of kinases from large-scale phosphoproteomics data. SnapKin is freely available at https://github.com/PYangLab/SnapKin.

bioinformatics↗

bioRxiv2021

Cholecystokinin 1 Receptor (Cck1R) Activates mTORC1 signaling and is Protective to Purkinje cells in SCA Mice

Spinocerebellar Ataxias (SCAs) are a group of genetic diseases characterized by progressive ataxia and neurodegeneration, often in cerebellar Purkinje neurons. A SCA1 mouse model, Pcp2-ATXN1[30Q]D776, has severe ataxia in absence of progressive Purkinje neuron degeneration and death. Previous RNA-seq analyses identified cerebellar up-regulation of the peptide hormone Cholecystokinin (Cck) in Pcp2-ATXN1[30Q]D776 mice. Importantly, absence of Cck1 receptor (Cck1R) in Pcp2-ATXN1[30Q]D776 mice confers a progressive disease with Purkinje neuron death. A Cck1R agonist, A71623 administered to Pcp2-ATXN1[30Q]D776;Cck-/- and Pcp2-AXTN1[82Q] mice dampened Purkinje neuron pathology and associated deficits in motor performance. In addition, A71623 administration improved motor performance of Pcp2-ATXN2[127Q] SCA2 mice. Moreover, the Cck1R agonist A71623 corrected mTORC1 signaling and improved expression of calbindin in cerebella of AXTN1[82Q] and ATXN2[127Q] mice. These results indicate that manipulation of the Cck-Cck1R pathway is a potential therapeutic target for treatment of diseases involving Purkinje neuron degeneration.

neuroscience↗

bioRxiv2021

Discovery of a molecular glue that enhances UPRmt to restore proteostasis via TRKA-GRB2-EVI1-CRLS1 axis

Lowering proteotoxicity is a potentially powerful approach for the treatment of neurological disorders, such as Parkinsons disease. The unfolded protein response (UPR) is a major mechanism that preserves the network maintaining cellular proteostasis. In the present study, we developed the screening strategy to discover compounds that significantly enhanced the activation of mitochondrial UPR (UPRmt) through increasing cardiolipin content. We identified that ginsenoside Rg3 (Rg3) increased cardiolipin depending on cardiolipin synthase 1 (CRLS1) in both worms and in human neural cells. Using LiP-SMap (limited proteolysis-mass spectrometry) strategy, we identified GRB2 (growth factor receptor bound protein 2) as a direct target of Rg3 in human neural cells. Rg3 enhances the binding between GRB2 and TRKA, that transduces signals via phosphrorylation of ERK. We provide bioinformatic and experimental evidence that EVI1, the critical oncogenic transcriptional regulator in leukemia, binds to CRLS1 promoter region and stimulated CRLS1 expression and subsequently increased cardiolipin content in the presence of Rg3. In a Parkinsons disease mouse model, Rg3 restores motor function by protecting nigral dopaminergic neurons dependent on Grb2. Our data recapitulate the TRKA-GRB2-EVI1-CRLS1 axis in maintaining proteostasis in Parkinsons disease via UPRmt.

pharmacology and toxicology↗

bioRxiv2021

A potent bispecific nanobody protects hACE2 mice against SARS-CoV-2 infection via intranasal administration

The dramatically expanding COVID-19 needs multiple effective countermeasures. Neutralizing antibodies are a potential therapeutic strategy for treating COVID-19. A number of neutralizing nanobodies (Nbs) were reported for their in vitro activities. However, in vivo protection of these nanobodies was not reported in animal models. In the current report, we characterized several RBD-specific Nbs isolated from a screen of an Nb library derived from an alpaca immunized with SARS-CoV-2 spike glycoprotein (S); among them, three Nbs exhibited picomolar potency against SARS-CoV-2 live virus, pseudotyped viruses, and 15 circulating SARS-CoV-2 variants. To improve the efficacy, various configurations of Nbs were engineered. Nb15-NbH-Nb15, a novel trimer constituted of three Nbs, was constructed to be bispecific for human serum albumin (HSA) and RBD of SARS-CoV-2. Nb15-NbH-Nb15 exhibited sub-ng/ml neutralization potency against the wild-type and currently circulating variants of SARS-CoV-2 with a long half-life in vivo. In addition, we showed that intranasal administration of Nb15-NbH-Nb15 provided 100% protection for both prophylactic and therapeutic purposes against SARS-CoV-2 infection in transgenic hACE2 mice. Nb15-NbH-Nb15 is a potential candidate for both prevention and treatment of SARS-CoV-2 through respiratory administration. One sentence summaryNb15-NbH-Nb15, with a novel heterotrimeric bispecific configuration, exhibited potent and broad neutralization potency against SARS-CoV-2 in vitro and provided in vivo protection against SARS-CoV-2 infection in hACE2 transgenic mice via intranasal delivery. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=156 SRC="FIGDIR/small/429275v1_ufig1.gif" ALT="Figure 1"> View larger version (47K): org.highwire.dtl.DTLVardef@a30bc8org.highwire.dtl.DTLVardef@5a872eorg.highwire.dtl.DTLVardef@1610f74org.highwire.dtl.DTLVardef@13d9bd8_HPS_FORMAT_FIGEXP M_FIG Graphical abstract: C_FIG HighlightsO_LIWe described a novel heterotrimeric configuration of Nb-NbH-Nb (Nb15-NbH-Nb15) that exhibited improved viral inhibition and stability. C_LIO_LINb15-NbH-Nb15 provides ultrahigh neutralization potency against SARS-CoV-2 wild type and 18 mutant variants, including the current circulating variants of D614G and N501Y predominantly in the UK and South Africa. C_LIO_LIIt is the first to demonstrate the Nbs efficacy in preventing and treating SARS-CoV-2 infection in hACE2 transgenic mice via intranasal delivery. C_LI

microbiology↗

bioRxiv2021

Cepo uncovers cell identity through differential stability

We present Cepo, a method to generate cell-type-specific gene statistics of differentially stable genes from single-cell RNA-sequencing (scRNA-seq) data to define cell identity. Cepo outperforms current methods in assigning cell identity and enhances several cell identification applications such as cell-type characterisation, spatial mapping of single cells, and lineage inference of single cells.

systems biology↗

bioRxiv2021

Single-cell and single-variant resolution analysis of clonal evolution in human liver cancer

Genetic heterogeneity of tumor is closely related to clonal evolution, phenotypic diversity and treatment resistance. Such heterogeneity has been characterized in liver cancer at single-cell sub-chromosomal scale, and a more precise single-variant resolution analysis is lacking. Here we employed a strategy to analyze both the single-cell genomic mutations and transcriptomic changes in 5 patients with liver cancer. Target sequencing was done for a total of 480 single cells in a patient-specific manner. DNA copy number status of point mutations was obtained from single-cell mutational profiling. The clonal structures of liver cancers were then uncovered at single-variant resolution, and mutation combinations in single cells enabled reconstruction of their evolutionary history. A common origin but independent evolutionary fate was revealed for primary liver tumor and intrahepatic metastatic portal vein tumor thrombus. The mutational signature suggested early evolutionary process may be related to specific etiology like aristolochic acids. By parallel single-cell RNA-Seq, the transcriptomic phenotype was found to be related with genetic heterogeneity in liver cancer. We reconstructed the single-cell and single-variant resolution clonal evolutionary history of liver cancer, and dissection of both genetic and phenotypic heterogeneity provides knowledge for mechanistic understanding of liver cancer initiation and progression.

genomics↗

bioRxiv2020

Landscapes and dynamic diversifications of B-cell receptor repertoires in COVID-19 patients

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has caused the pandemic of coronavirus disease 2019 (COVID-19). Great international efforts have been put into the development of prophylactic vaccines and neutralizing antibodies. However, the knowledge about the B cell immune response induced by the SARS-CoV-2 virus is still limited. Here, we report a comprehensive characterization of the dynamics of immunoglobin heavy chain (IGH) repertoire in COVID-19 patients. By using next-generation sequencing technology, we examined the temporal changes in the landscape of the patients immunological status, and found dramatic changes in the IGH within the patients immune system after the onset of COVID-19 symptoms. Although different patients have distinct immune responses to SARS-CoV-2 infection, by employing clonotype overlap, lineage expansion and clonotype network analyses, we observed a higher clonotype overlap and substantial lineage expansion of B cell clones during 2-3 weeks of illness, which is of great importance to B-cell immune responses. Meanwhile, for preferences of V gene usage during SARS-CoV-2 infection, IGHV3-74 and IGHV4-34 and IGHV4-39 in COVID-19 patients were more abundant than that of healthy controls. Overall, we present an immunological resource for SARS-CoV-2 that could promote both therapeutic development as well as mechanistic research.

immunology↗