Biology subjects

Bai, X.

Publications and source records attributed to Bai, X..

At least 127 records · Page 7Linked to original sources

bioRxiv2020

The therapeutic effects of intratumoral injection of IL12IL2GMCSF fusion protein on canine tumors

Regulating the immune system through tumor immunotherapy to defeat tumors is currently one of the most popular methods of tumor treatment. We previously found that the combinations of IL12, IL2 and GMCSF has superior antitumor activities. In this study, IL12IL2GMCSF fusion protein was produced from 293 cells transduced by expression lentiviral vector. IL12IL2GMCSF fusion protein was injected into canine tumors, and the efficacy was monitored to evaluate the potential of tumor immunotherapy. In 14 canines injected with IL12IL2GMCSF protein, 6 had a complete response (CR), 7 had a partial response (PR), and 1 had stable disease (SD). IL12IL2GMCSF fusion protein has great anti-tumor potential. Intratumoral injection of IL12IL2GMCSF can effectively treat tumors without severe adverse effects. It provides a promising immune therapeutics in canine cancers.

cancer biology↗

bioRxiv2020

PLK1- and PLK4-mediated asymmetric mitotic centrosome size and positioning in the early zebrafish embryo.

Factors that regulate mitotic spindle positioning have been elucidated in vitro, however it remains unclear how a spindle is placed within the confines of extremely large cells. Our studies identified a uniquely large centrosome structure in the early zebrafish embryo (246.44{+/-}11.93m2 mitotic centrosome in a 126.86{+/-}0.35m diameter cell), whereas C. elegans centrosomes are notably smaller (6.75{+/-}0.28m2 mitotic centrosome in a 55.83{+/-}1.04m diameter cell). During early embryonic cell divisions, cell size changes rapidly in C. elegans and zebrafish embryos. Notably, mitotic centrosome area scales closely with changing cell size compared to changes in spindle length for both organisms. One interesting difference between the two is that mitotic centrosomes are asymmetric in size across embryonic zebrafish spindles, with the larger mitotic centrosome being 2.14{+/-}0.13-fold larger in size than the smaller. The largest mitotic centrosome is placed towards the embryo center in a Polo-Like Kinase (PLK) 1 and PLK4 dependent manner 87.14{+/-}4.16% of the time. We propose a model in which uniquely large centrosomes direct spindle placement within the disproportionately large zebrafish embryo cells to orchestrate cell divisions during early embryogenesis.

cell biology↗

bioRxiv2020

Joint Inference of Clonal Structure using Single-cell DNA-Seq and RNA-Seq data

Latest advancements in high-throughput single-cell genome (scDNA) and transcriptome (scRNA) sequencing technologies enabled cell-resolved investigation of tissue clones. However, it remains challenging to cluster and couple single cells for heterogeneous scRNA and scDNA data generated from the same specimen. In this study, we present a computational framework called CC-NMF, which employs a novel Coupled-Clone Non-negative Matrix Factorization technique to jointly infer clonal structure for matched scDNA and scRNA data. CCNMF couples multi-omics single cells by linking copy number and gene expression profiles through their general concordance. We validated CC-NMF using both simulated benchmarks and real-world applications, demon-strating its robustness and accuracy. We analyzed scRNA and scDNA data from an ovarian cancer cell lines mixture, a gastric cancer cell line, as well as a primary gastric cancer, successfully resolving underlying clonal structures and identifying high correlations of coexisting clones between genome and transcriptome. Overall, CCNMF is a coherent computational framework that simultaneously resolves genomic and transcriptomic clonal architecture, facilitating understanding of how cellular gene expression changes along with clonal genome alternations.

bioinformatics↗

bioRxiv2020

Unsupervised Topological Alignment for Single-Cell Multi-Omics Integration

Single-cell multi-omics data provide a comprehensive molecular view of cells. However, single-cell multi-omics datasets consist of unpaired cells measured with distinct unmatched features across modalities, making data integration challenging. In this study, we present a novel algorithm, termed UnionCom, for the unsupervised topological alignment of single-cell multi-omics integration. UnionCom does not require any correspondence information, either among cells or among features. It first embeds the intrinsic low-dimensional structure of each single-cell dataset into a distance matrix of cells within the same dataset and then aligns the cells across single-cell multi-omics datasets by matching the distance matrices via a matrix optimization method. Finally, it projects the distinct unmatched features across single-cell datasets into a common embedding space for feature comparability of the aligned cells. To match the complex nonlinear geometrical distorted low-dimensional structures across datasets, UnionCom proposes and adjusts a global scaling parameter on distance matrices for aligning similar topological structures. It does not require one-to-one correspondence among cells across datasets, and it can accommodate samples with dataset-specific cell types. UnionCom outperforms state-of-the-art methods on both simulated and real single-cell multi-omics datasets. UnionCom is robust to parameter choices, as well as subsampling of features. UnionCom software is available at https://github.com/caokai1073/UnionCom.

bioinformatics↗

bioRxiv2020

Dietary supplementation with PUFAs rescues the eggshell defects caused by seipin mutations in C. elegans

SEIPIN, an ER membrane protein, plays critical roles in lipid droplet (LD) formation and lipid storage. Dysfunction of SEIPIN causes a variety of human diseases, including lipodystrophy, neuropathies, and male and female infertility. However, the cellular and molecular mechanisms of SEIPIN in causing these diseases are poorly understood. To address such mechanisms, we investigated the functional roles of R01B10.6 (seip-1), the sole SEIPIN1 ortholog in C. elegans, using CRISPR/Cas9 gene editing, and transcriptional assays. SEIP-1::mScarlet is widely expressed throughout development in C. elegans. Three full gene deletion mutants, generated by CRISPR/Cas9, displayed penetrant embryonic lethality. EM imaging and the visualization of reporter genes revealed that the lipid-rich permeability barrier, the innermost layer of the C. elegans embryonic eggshell, was defective or missing. Intriguingly, depletion of SEIP-1 revealed a perturbed gene expression pattern for fatty acid biosynthesis enzymes, in agreement with the disrupted permeability barrier formation phenotype of the embryos. Lastly, dietary supplementation of PUFAs rescued the embryonic lethality and defective permeability barrier in the deletion mutants. In sum, our study suggests that SEIP-1 may maternally regulate LD biogenesis and maintain lipid homeostasis to orchestrate the formation of the lipid-rich permeability barrier, which is crucial for eggshell formation and embryogenesis.

cell biology↗

bioRxiv2019

Molecular basis of differential parasitism between non-encapsulated and encapsulated Trichinella revealed by a high-quality genome assembly

Understanding roles of repetitive sequences in genomes of parasites could offer insights into their evolution, speciation, and parasitism. As a unique intracellular nematode, Trichinella consists of two clades, encapsulated and non-encapsulated. Genomic correlation to the distinct differences between the two clades is still unclear. Here we report an annotated draft reference genome of non-encapsulated Trichinella, T. pseudospiralis, and performed comparative analyses with encapsulated T. spiralis. Genome analysis revealed that, during Trichinella evolution, repetitive sequence insertions played an important role in gene family expansion in synergy with DNA methylation, especially for the DNase II members of the phospholipase D superfamily and Glutathione S-transferases. We further identify the genomic and epigenomic regulation of excretory/secretory products in relation to differences in parasitism, pathology and immunology between the two clades Trichinella. The present study provided a foundation for further elucidation of mechanism of nurse cell formation and immunoevasion as well as identification of phamarcological and diagnostic targets of trichinellosis.

genomics↗

bioRxiv2019

Caenorhabditis elegans PIEZO Channel Coordinates Multiple Reproductive Tissues to Govern Ovulation

The PIEZO proteins are involved in a wide range of developmental and physiological processes. Human PIEZO1 and PIEZO2 are newly identified excitatory mechano-sensitive proteins; they are non-selective ion channels that exhibit a preference for calcium in response to mechanical stimuli. To further understand the function of these proteins, we investigated the roles of pezo-1, the sole PIEZO ortholog in C. elegans. pezo-1 is expressed throughout development in C. elegans, with strong expression in reproductive tissues. A number of deletion alleles as well as a putative gain-of-function mutant caused severe defects in reproduction. A reduced brood size was observed in the strains depleted of PEZO-1. In vivo observations show that oocytes undergo a variety of transit defects as they enter and exit the spermatheca during ovulation. Post ovulation oocytes were frequently damaged during spermathecal contraction. Calcium signaling in the spermatheca is normal during ovulation in pezo-1 mutants, however, pezo-1 interacts genetically with known regulators of calcium signaling. Lastly, loss of PEZO-1 caused defective sperm navigation after being pushed out of the spermatheca during ovulation. Mating with males rescued these reproductive deficiencies in our pezo-1 mutants. These findings suggest that PEZO-1 may act in different reproductive tissues to promote proper ovulation and fertilization in C. elegans.

developmental biology↗

bioRxiv2019

AutoGenome: An AutoML Tool for Genomic Research

Deep learning have made great successes in traditional fields like computer vision (CV), natural language processing (NLP) and speech processing. Those achievements greatly inspire researchers in genomic study and make deep learning in genomics a very hot topic. Convolutional neural network (CNN) and recurrent neural network (RNN) are frequently used for genomic sequence prediction problems; multiple layer perception (MLP) and auto-encoders (AE) are frequently used for genomic profiling data like RNA expression data and gene mutation data. Here, we introduce a new neural network architecture, named residual fully-connected neural network (RFCN) and demonstrate its advantage for modeling genomic profiling data. We further incorporate AutoML algorithms and implement AutoGenome, an end-to-end automated genomic deep learning framework. By utilizing the proposed RFCN architectures, automatic hyper-parameter search and neural architecture search algorithms, AutoGenome can train high-performance deep learning models for various kinds of genomic profiling data automatically. To make researchers better understand the trained models, AutoGenome can assess the feature importance and export the most important features for supervised learning tasks, and the representative latent vectors for unsupervised learning tasks. We envision AutoGenome to become a popular tool in genomic studies.

genomics↗

bioRxiv2019

The Study on Computer Vision-Assisted Cell Bank Construction and Screening & Classification

Computer vision technology plays an important role in screening and culturing cells. This paper proposes a method to construct a helper cell library based on cell image segmentation and screening. Firstly, cell culture and image acquisition were carried out. The main content is to use laboratory conditions to carry out different cell types. Through careful observation of the whole process of cell proliferation and passage, the representative pictures of different stages were taken. Analysis and summary of the relevant morphology, texture, color characteristics. Secondly, computer vision technology is used to segment cells and extract the main features such as cell perimeter and area. Explore the automatic information extraction method of cell bank, and complete the image segmentation of individual cell image from the whole picture. Finally, the cells were screened and identified. Investigate different pattern recognition methods and neural network structures, and prepare pictures of various cell pictures. The corresponding neural network and prediction program are constructed. This paper proposes an automatic image processing method for each image category in cell culture cycle, which improves the automation of production process. At the same time, compared with the design of a single algorithm for a certain type of cell, different algorithm design ideas are proposed for three types of pictures with different characteristics, which is closer to the dynamic change of cell morphology in the process of cell culture. This research has important application prospects in promoting cell factory research, cell bank construction and automatic screening.

bioinformatics↗

bioRxiv2019

Background free tracking of single RNA in living cells using catalytically inactive CasE

RNAs have important and diverse functions. Visualizing an isolated RNA in living cells provide us essential information of its roles. By now, there are two kinds of live RNA imaging systems invented, one is the MS2 system and the other is the Cas13a system. In this study, we show that when fused with split-Fp, CasE can be engineered into a live RNA tracking tool.

molecular biology↗

bioRxiv2019

Trophoblast proliferation, migration, and invasion is regulated by the miR-195/EGFR signaling pathway in recurrent spontaneous abortion patients

OBJECTIVETo investigate the effect of the miR-195/EGFR signaling pathway on trophoblasts in patients with recurrent spontaneous abortion, thus providing a clinical basis for the diagnosis and treatment of recurrent spontaneous abortion.\n\nMETHODSRT-qPCR, western blot, flow cytometry, CCK8, cell scratch assay, transwell, and a dual Luciferase reporter assay were used to detect changes in the miR-195/EGFR signaling pathways in clinical samples and in vitro cultured cells and to explore how these changes affect trophoblasts in affected patients.\n\nRESULTSExpression of miR-195 was elevated in villus tissues of patients with recurrent spontaneous abortion, while the expression levels of EGFR and its downstream genes p38 and AKT phosphorylation were down-regulated. In vitro cultured cell experiments showed that miR-195 inhibited the proliferation, migration, and invasion of trophoblast cells. EGFR is a target gene of miR-195, and miR-195 suppresses the expression of EGFR.\n\nConclusionThe miR-195/EGFR signaling pathway regulates the proliferation, migration, and invasion of trophoblast cells, thus playing an important role in recurrent spontaneous abortion.

cell biology↗

bioRxiv2019

A high-precision hybrid algorithm for predicting eukaryotic protein subcellular localization

MotivationSubcellular location plays an essential role in protein synthesis, transport, and secretion, thus it is an important step in understanding the mechanisms of trait-related proteins. Generally, homology methods provide reliable homology-based results with small E-values. We must resort to pattern recognition algorithms (SVM, Fisher discriminant, KNN, random forest, etc.) for proteins that do not share significant homologous domains with known proteins. However, satisfying results are seldom obtained.\n\nResultsHere, a novel hybrid method \"Basic Local Alignment Search Tool+Smith-Waterman+Needleman-Wunsch\" or BLAST+SWNW, has been obtained by integrating a loosened E-value Basic Local Alignment Search Tool (BLAST) with the Smith-Waterman (SW) and Needleman-Wunsch (NW) algorithms, and this method has been introduced to predict protein subcellular localization in eukaryotes. When tested on Dataset I and Dataset II, BLAST+SWNW showed an average accuracy of 97.18% and 99.60%, respectively, surpassing the performance of other algorithms in predicting eukaryotic protein subcellular localization.\n\nAvailability and ImplementationBLAST+SWNW is an open source collaborative initiative available in the GitHub repository (https://github.com/ZHANGDAHAN/BLAST-SWNW-for-SLP or http://202.206.64.158:80/link/72016CAC26E4298B3B7E0EAF42288935)\n\nContactzhaqi1972@163.com; zhangdahan@genetics.ac.cn\n\nSupplementary InformationSupplementary data are available at PLOS Computational Biology online.

bioinformatics↗

bioRxiv2019

Sparse Project VCF: efficient encoding of population genotype matrices

SummaryVariant Call Format (VCF), the prevailing representation for germline genotypes in population sequencing, suffers rapid size growth as larger cohorts are sequenced and more rare variants are discovered. We present Sparse Project VCF (spVCF), an evolution of VCF with judicious entropy reduction and run-length encoding, delivering >10X size reduction for modern studies with practically minimal information loss. spVCF interoperates with VCF efficiently, including tabix-based random access. Availability and ImplementationFreely available at github.com/mlin/spVCF Contactdna@mlin.net

bioinformatics↗

bioRxiv2018

Immunomodulatory activity of Ganoderma lucidum immunomodulatory protein via PI3K/Akt and MAPK signaling pathways in macrophage RAW264.7 cells

Ganoderma lucidum, a traditional edible and medicinal fungus, holds an important status in health care systems in China and other Asian countries. Fungal immunomodulatory protein (FIP), one of the active ingredients isolated from G. lucidum, is a class of naturally occurring proteins and possesses potential biological functions. This study was conducted to explore the molecular mechanism of its immunomodulatory potency in immune responses of macrophages. In vitro assays of biological activity indicated that rFIP-glu significantly activated macrophage RAW264.7 cells, and possessed the ability of pro-and anti-inflammation the cells. RNA sequencing analysis showed that macrophage activation involved Toll-like receptors and mitogen-activated protein kinases pathways. Furthermore, qRT-PCR indicated that phosphoinositide 3 kinase inhibitor LY294002 blocked the mRNA levels of MCP-1, MEK1/2 inhibitor U0126 reduced the mRNA levels of TNF- and MCP-1, and JNK inhibitor SP600125 prevented the up-regulation of iNOS mRNA in the rFIP-glu-induced cells. FIP-glu mediated these inflammatory effects not through a general pathway, instead through a different pathway for different inflammatory mediator. These data indicate the possibility that rFIP-glu has an important immune-regulation function and thus has potential therapeutic uses.

immunology↗

bioRxiv2018

GLnexus: joint variant calling for large cohort sequencing

As ever-larger cohorts of human genomes are collected in pursuit of genotype/phenotype associations, sequencing informatics must scale up to yield complete and accurate genotypes from vast raw datasets. Joint variant calling, a data processing step entailing simultaneous analysis of all participants sequenced, exhibits this scaling challenge acutely. We present GLnexus (GL, Genotype Likelihood), a system for joint variant calling designed to scale up to the largest foreseeable human cohorts. GLnexus combines scalable joint calling algorithms with a persistent database that grows efficiently as additional participants are sequenced. We validate GLnexus using 50,000 exomes to show it produces comparable or better results than existing methods, at a fraction of the computational cost with better scaling. We provide a standalone open-source version of GLnexus and a DNAnexus cloud-native deployment supporting very large projects, which has been employed for cohorts of >240,000 exomes and >22,000 whole-genomes.

bioinformatics↗

bioRxiv2018

Programmed Variations of Cytokinesis Contribute to Morphogenesis in the C. elegans embryo

While cytokinesis has been intensely studied, how it is executed during development is not well understood, despite a long-standing appreciation that various aspects of cytokinesis vary across cell and tissue types. To address this, we investigated cytokinesis during the invariant C. elegans embryo lineage and found several reproducibly altered parameters at different stages. During early divisions, furrow ingression asymmetry and midbody inheritance is consistent, suggesting specific regulation of these events. During morphogenesis, we find several unexpected alterations including migration of midbodies to the apical surface during epithelial polarization in different tissues. Aurora B kinase, which is essential for several aspects of cytokinesis, remains localized to the apical membrane after internalization of other midbody components. Inactivation of Aurora B causes cytokinesis failure, which disrupts polarization and tissue formation. Therefore, cytokinesis shows surprising diversity during development and is required during epithelial polarization to establish cellular architecture during morphogenesis.

cell biology↗

bioRxiv2018

DensityPath: a level-set algorithm to visualize and reconstruct cell developmental trajectories for large-scale single-cell RNAseq data

Cell fates are determined by transition-states which occur during complex biological pro-cesses such as proliferation and differentiation. The advance in single-cell RNA sequencing (scRNAseq) provides the snapshots of single cell transcriptomes, thus offering an essential opportunity to study such complex biological processes. Here, we introduce a novel algorithm, DensityPath, which visualizes and reconstructs the underlying cell developmental trajectories for large-scale scRNAseq data. DensityPath has three merits. Firstly, by adopting the nonlinear dimension reduction algorithm elastic embedding, DensityPath reveals the intrinsic structures of the data. Secondly, by applying the powerful level set clustering method, DensityPath extracts the separate high density clusters of representative cell states (RCSs) from the single cell multimodal density landscape of gene expression space, enabling it to handle the heterogeneous scRNAseq data elegantly and accurately. Thirdly, DensityPath constructs cell state-transition path by finding the geodesic minimum spanning tree of the RCSs on the surface of the density landscape, making it more computationally efficient and accurate for large-scale dataset. The cell state-transition path constructed by DensityPath has the physical interpretation as the minimum-transition-energy (least-cost) path. We demonstrate that DensityPath is capable of identifying complex cell development trajectories with bifurcating and trifurcating branches on the human preimplantation embryos. We demonstrate that DensityPath is robust and has high accuracy of pseudotime calculation and branch assignment on the real scRNAseq as well as simulated datasets.

systems biology↗

bioRxiv2018

Cryo-EM structure of the adenosine A2A receptor coupled to an engineered heterotrimeric G protein

The adenosine A2A receptor (A2AR) is a prototypical G protein-coupled receptor (GPCR) that couples to the heterotrimeric G protein GS. Here we determine the structure by electron cryo-microscopy (cryo-EM) of A2AR at pH 7.5 bound to the small molecule agonist NECA and coupled to an engineered heterotrimeric G protein, which contains mini-GS, the {beta}{gamma} subunits and nanobody Nb35. Most regions of the complex have a resolution of ~3.8 [A] or better. Comparison with the 3.4 [A] resolution crystal structure shows that the receptor and mini-GS are virtually identical and that the density of the side chains and ligand are of comparable quality. However, the cryo-EM density map also indicates regions that are flexible in comparison to the crystal structures, which unexpectedly includes regions in the ligand binding pocket. In addition, an interaction between intracellular loop 1 of the receptor and the {beta} subunit of the G protein was observed.

biophysics↗