Biology subjects

Wang, B.

Publications and source records attributed to Wang, B..

At least 505 records · Page 28Linked to original sources

bioRxiv2021

Broad and Long-lasting Immune Response against SARS-CoV-2 Omicron and Other Variants by PIKA-Adjuvanted Recombinant SARS-CoV-2 Spike (S) Protein Subunit Vaccine (YS-SC2-010)

Recently SARS-CoV-2 Omicron (B.1.1.529) variant was identified in South Africa with numerous mutations in spike protein, and numerous community infections have been reported and raised grave concern around the world. Some studies found that the neutralization effects of several licensed vaccines against Omicron were dramatically reduced, which significantly affected antibody mediated protection, especially for individuals whose immunization were completed after extended period. In this regard, we studied the persistence and neutralization activity toward mutant strains in animal serum immunized with PIKA-adjuvanted recombinant SARS-CoV-2 spike protein subunit vaccine (YS-SC2-010). Here we are reporting that animal serum collected at 596 days after immunization with YS-SC2-010 still retains high and persistent neutralizing activity against all the Variant of Concern (VOC) variants, including Omicron variant. Although it is a blessed event to achieve 20 months long neutralization against Omicron variant after immunization with YS-SC2-010, it was also founded that the neutralization effect of immune serum on Omicron decreased by 6.29 folds as compared to D614G, more significantly when compared with other mutant strains.

immunology↗

bioRxiv2021

An ensemble of toxic channel types underlies the severity of the de novo variant G375R of the human BK channel

The molecular basis of a severe developmental and neurological disorder associated with a de novo G375R variant of the tetrameric BK channel is unknown. Here we address this question by recording from single BK channels expressed for a heterozygous G375R mutation. Five different types of functional BK channels were observed: 3% were WT, 12% were homomeric mutant, and 85% were three different types of hybrid channels. All channel types except WT showed a marked gain-of-function in voltage activation and a smaller loss-of-function in single channel conductance, with both becoming more pronounced as the number of mutant subunits per tetrameric channel increased. The molecular phenotype suggested codominance for the two homomeric channels and partial dominance for the hybrid channels. A model in which BK channels are randomly assembled from mutant and WT subunits, with each subunit contributing increments of activation and conductance, approximated the molecular phenotype of the heterozygous G375R mutation.

neuroscience↗

bioRxiv2021

Towards mechanistic models of mutational effects: Deep Learning on Alzheimer's Aβ peptide

Alzheimers Disease (AD) is a debilitating form of dementia with a high prevalence in the global population and a large burden on the community and health care systems. ADs complex pathobiology consists of extracellular {beta}-amyloid deposition and intracellular hyperphosphorylated tau. Comprehensive mutational analyses can generate a wealth of knowledge about protein properties and enable crucial insights into molecular mechanisms of disease. Deep Mutational Scanning (DMS) has enabled multiplexed measurement of mutational effects on protein properties, including kinematics and self-organization, with unprecedented resolution. However, potential bottlenecks of DMS characterization include experimental design, data quality, and the depth of mutational coverage. Here, we apply Deep Learning to comprehensively model the mutational effect of the AD-associated peptide A{beta}42 on aggregation-related biochemical traits from DMS measurements. Among tested neural network architectures, Convolutional Neural Networks (ConvNets) and Recurrent Neural Networks (RNN) are found to be the most cost-effective models with robust high performance even under insufficiently-sampled DMS studies. While sequence features are essential for satisfactory prediction from neural networks, geometric-structural features further enhance the prediction performance. Notably, we demonstrate how mechanistic insights into phenotype may be extracted from the neural networks themselves suitably designed. This methodological benefit is particularly relevant for biochemical systems displaying a strong coupling between structure and phenotype such as the conformation of A{beta}42 aggregate and nucleation, as shown here using a Graph Convolutional Neural Network (GCN) developed from the protein atomic structure input. In addition to accurate imputation of missing values (which here ranged up to 55% of all phenotype values at key residues), the mutationally-defined nucleation phenotype generated from a GCN shows improved resolution for identifying known disease-causing mutations relative to the original DMS phenotype. Our study suggests that neural network derived sequence-phenotype mapping can be exploited not only to provide direct support for protein engineering or genome editing but also to facilitate therapeutic design with the gained perspectives from biological modeling.

bioinformatics↗

bioRxiv2021

Changes of small non-coding RNAs by severe acute respiratory syndrome coronavirus 2 infection

The ongoing pandemic of coronavirus disease 2019 (COVID-19), which results from the rapid spread of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is a significant global public health threat, with molecular mechanisms underlying its pathogenesis largely unknown. Small non-coding RNAs (sncRNAs) are known to play important roles in almost all biological processes. In the context of viral infections, sncRNAs have been shown to regulate the host responses, viral replication, and host-virus interaction. Compared with other subfamilies of sncRNAs, including microRNAs (miRNAs) and Piwi-interacting RNAs (piRNAs), tRNA-derived RNA fragments (tRFs) are relatively new and emerge as a significant regulator of host-virus interactions. Using T4 PNK-RNA-seq, a modified next-generation sequencing (NGS), we recently found that nasopharyngeal swabs (NPS) samples from SARS-CoV-2 positive and negative subjects show a significant difference in sncRNA profiles. There are about 166 SARS-CoV-2-impacted sncRNAs. Among them, tRFs are the most significantly affected and almost all impacted tRFs are derived from the 5-end of tRNAs (tRF5). Using a modified qRT-PCR, which was recently developed to specifically quantify tRF5s by isolating the tRF signals from its corresponding parent tRNA signals, we validated that tRF5s derived from tRNA GluCTC (tRF5-GluCTC), LysCTT (tRF5-LysCTT), ValCAC (tRF5-ValCAC), CysGCA (tRF5-CysGCA) and GlnCTG (tRF5-GlnCTG) are enhanced in NPS samples of SARS-CoV2 patients and SARS-CoV2-infected airway epithelial cells. In addition to host-derived ncRNAs, we also identified several sncRNAs derived from the virus (svRNAs), among which a svRNA derived from CoV2 genomic site 346 to 382 (sv-CoV2-346) has the highest expression. The induction of both tRFs and sv-CoV2-346 has not been reported previously, as the lack of the 3-OH ends of these sncRNAs prevents them to be detected by routine NGS. In summary, our studies demonstrated the involvement of tRFs in COVID-19 and revealed new CoV2 svRNAs.

microbiology↗

bioRxiv2021

Cell transcriptomic atlas of the non-human primate Macaca fascicularis

Studying tissue composition and function in non-human primates (NHP) is crucial to understand the nature of our own species. Here, we present a large-scale single-cell and single-nucleus transcriptomic atlas encompassing over one million cells from 43 tissues from the adult NHP Macaca fascicularis. This dataset provides a vast, carefully annotated, resource to study a species phylogenetically close to humans. As proof of principle, we have reconstructed the cell-cell interaction networks driving Wnt signalling across the body, mapped the distribution of receptors and co-receptors for viruses causing human infectious diseases and intersected our data with human genetic disease orthologous coordinates to identify both expected and unexpected associations. Our Macaca fascicularis cell atlas constitutes an essential reference for future single-cell studies in human and NHP.

cell biology↗

bioRxiv2021

Tabula Microcebus: A transcriptomic cell atlas of mouse lemur, an emerging primate model organism

Mouse lemurs are the smallest, fastest reproducing, and among the most abundant primates, and an emerging model organism for primate biology, behavior, health and conservation. Although much has been learned about their physiology and their Madagascar ecology and phylogeny, little is known about their cellular and molecular biology. Here we used droplet- and plate-based single cell RNA-sequencing to profile 226,000 cells from 27 mouse lemur organs and tissues opportunistically procured from four donors clinically and histologically characterized. Using computational cell clustering, integration, and expert cell annotation, we defined and biologically organized over 750 mouse lemur molecular cell types and their full gene expression profiles. These include cognates of most classical human cell types, including stem and progenitor cells, and the developmental programs for spermatogenesis, hematopoiesis, and other adult tissues. We also described dozens of previously unidentified or sparsely characterized cell types and subtypes. We globally compared cell type expression profiles to define the molecular relationships of cell types across the body, and explored primate cell and gene expression evolution by comparing mouse lemur cell transcriptomes to those of human, mouse, and macaque. This revealed cell type specific patterns of primate specialization, as well as many cell types and genes for which lemur provides a better human model than mouse. The atlas provides a cellular and molecular foundation for studying this primate model organism, and establishes a general approach for other emerging model organisms.

genetics↗

bioRxiv2021

Single-cell profiling of healthy human kidney reveals features of sex-based transcriptional programs and tissue-specific immunity

Maintaining organ homeostasis requires complex functional synergy between distinct cell types, a snapshot of which is glimpsed through the simultaneously broad and granular analysis provided by single-cell atlases. Knowledge of the transcriptional programs underpinning the complex and specialized functions of human kidney cell populations at homeostasis is limited by difficulty accessing healthy, fresh tissue. Here, we present a single-cell perspective of healthy human kidney from 19 living donors, with equal contribution from males and females, profiling the transcriptome of 27677 high-quality cells to map healthy kidney at high resolution. Our sex-balanced dataset revealed sex-based differences in gene expression within proximal tubular cells, specifically, increased anti-oxidant metallothionein genes in females and the predominance of aerobic metabolism-related genes in males. Functional differences in metabolism were confirmed between male and female proximal tubular cells, with male cells exhibiting higher oxidative phosphorylation and higher levels of energy precursor metabolites. Within the immune niche, we identified kidney-specific lymphocyte populations with unique transcriptional profiles indicative of kidney-adapted functions and validated findings by flow cytometry. We observed significant heterogeneity in resident myeloid populations and identified an MRC1+ LYVE1+ FOLR2+ C1QC+ population as the predominant myeloid population in healthy kidney. This study provides a detailed cellular map of healthy human kidney, revealing novel insights into the complexity of renal parenchymal cells and kidney-resident immune populations.

immunology↗

bioRxiv2021

Long read sequencing reveals sequential complex rearrangements driven by Hepatitis B virus integration

Integration of Hepatitis B virus (HBV) into human genome disrupts genetic structures and cellular functions. Here, we conducted multiplatform long read sequencing on two cell lines and five clinical samples of HBV-infected hepatocellular carcinomas (HCC). We resolved three types of viral integration-induced complex genome rearrangements (CGR) and proposed a model of multi-hits and sequential-breaks to depict their formation process by differentiating inserted HBV copies with HiFi long reads. We deduced that all three complex types were initialized from focal replacement and fragile virus-human junctions triggered subsequent rearrangements. We further revealed that such rearrangements caused a prevalent loss-of-heterozygosity at chr4q, accounting for 19.5% of HCC samples in ICGC cohort and contributing to immune and metabolic dysfunction. Overall, our long read based analysis reveals novel sequential rearrangement processes initiated by HBV integration, hinting its structural and functional impact on HCC.

genomics↗

bioRxiv2021

Receptor binding and escape from Beta antibody responses drive Omicron-B.1.1.529 evolution

On the 24th November 2021 the sequence of a new SARS CoV-2 viral isolate spreading rapidly in Southern Africa was announced, containing far more mutations in Spike (S) than previously reported variants. Neutralization titres of Omicron by sera from vaccinees and convalescent subjects infected with early pandemic as well as Alpha, Beta, Gamma, Delta are substantially reduced or fail to neutralize. Titres against Omicron are boosted by third vaccine doses and are high in cases both vaccinated and infected by Delta. Mutations in Omicron knock out or substantially reduce neutralization by most of a large panel of potent monoclonal antibodies and antibodies under commercial development. Omicron S has structural changes from earlier viruses, combining mutations conferring tight binding to ACE2 to unleash evolution driven by immune escape, leading to a large number of mutations in the ACE2 binding site which rebalance receptor affinity to that of early pandemic viruses.

microbiology↗

bioRxiv2021

Intestinal SEC16B modulates obesity by controlling dietary lipid absorption

Genome-wide association studies (GWAS) have identified genetic variants in SEC16 homolog B (SEC16B) locus to be associated with obesity and body mass index (BMI) in various populations. SEC16B encodes a scaffold protein located at endoplasmic reticulum (ER) exit sites that is implicated to participate in the trafficking of COPII vesicles in mammalian cells. However, the function of SEC16B in vivo, especially in lipid metabolism, has not been investigated. Here we demonstrated that intestinal SEC16B is required for dietary lipid absorption in mice. We showed that Sec16b intestinal knockout (IKO) mice, especially female mice, were protected from HFD-induced obesity. Loss of SEC16B in intestine dramatically reduced postprandial serum triglyceride output upon intragastric lipid load or during overnight fasting and high-fat diet (HFD) refeeding. Further studies showed that intestinal SEC16B deficiency impaired apoB lipidation and chylomicron secretion. These results revealed that SEC16B plays important roles in dietary lipid absorption, which may shed light on the association between variants in SEC16B and obesity in human.

physiology↗

bioRxiv2021

A modified porous silicon microparticle promotes mucosal delivery of SARS-CoV-2 antigen and induction of potent and durable systemic and mucosal T helper 1 skewed protective immunity

Development of optimal SARS-CoV-2 vaccines to induce potent, long-lasting immunity and provide cross-reactive protection against emerging variants remains a high priority. Here, we report that a modified porous silicon microparticle (mPSM)-adjuvanted SARS-CoV-2 receptor-binding domain (RBD) vaccine activated dendritic cells and generated more potent and durable SARS-CoV-2-specific systemic humoral and type 1 helper T (Th) cell-mediated immune responses than alum-formulated RBD following parenteral vaccination, and protected mice from SARS-CoV-2 and Beta variant infection. mPSM facilitated the uptake of SARS-CoV-2 RBD antigens by nasal and airway epithelial cells. Parenteral and intranasal prime and boost vaccinations with mPSM-RBD elicited potent systemic and lung resident memory T and B cells and SARS-CoV-2 specific IgA responses, and markedly diminished viral loads and inflammation in the lung following SARS-CoV-2 Delta variant infection. Our results suggest that mPSM can serve as potent adjuvant for SARS-CoV-2 subunit vaccine which is effective for systemic and mucosal vaccination.

immunology↗

bioRxiv2021

Identification of a promiscuous conserved CTL epitope within the SARS-CoV-2 spike protein

The COVID-19 disease caused by infection with SARS-CoV-2 and its variants is devastating to the global public health and economy. To date, over a hundred COVID-19 vaccines are known to be under development and the few that have been approved to fight the disease are using the spike protein as the primary target antigen. Although virus neutralizing epitopes are mainly located within the RBD of the spike protein, the presence of T cell epitopes, particularly the CTL epitopes that are likely to be needed for killing infected cells, has received comparatively little attention. In this study, we predicted several potential T cell epitopes with web-based analytic tools, and narrowed them down from several potential MHC-I and MHC-II epitopes by ELIspot and cytolytic assays to a conserved MHC-I epitope. The epitope is highly conserved in current viral variants including the most recent Omicron and compatible with presentation by most HLA alleles worldwide. In conclusion, we identified a CTL epitope suitable for evaluating the CD8+ T cell-mediated cellular response and potentially for addition into future COVID-19 vaccine candidates to maximize CTL responses against SARS-CoV-2.

immunology↗

bioRxiv2021

Global Mutational Sweep of SARS-CoV-2: from Chaos to Order

Analysis of large-scale genome sequences demonstrates the mutation of SARS-CoV-2 has been undergoing significant sweeps. Driven by emerging variants, global sweeps are accelerated and purified over time. This may prolong the pandemic with repeating epidemics, presenting challenges to the control and prevention of SARS-CoV-2.

evolutionary biology↗

bioRxiv2021

NucleoMap: a computational tool for identifying nucleosomes in ultra-high resolution contact maps

1Although poorly positioned nucleosomes are ubiquitous in the prokaryote genome, they are difficult to identify with existing nucleosome identification methods. Recently available enhanced high-throughput chromatin conformation capture techniques such as Micro-C, DNase Hi-C, and Hi-CO characterize nucleosome-level chromatin proximity, probing the positions of mono-nucleosomes and the spacing between nucleosome pairs at the same time, enabling profiling of nucleosomes in poorly positioned regions. Here we develop a novel computational approach, NucleoMap, to identify nucleosome positioning from ultra-high resolution chromatin contact maps. By integrating nucleosome binding preferences, read density, and pairing information, NucleoMap precisely locates nucleosomes in both eukaryotic and prokaryotic genomes and outperforms existing nucleosome identification methods in precision and recall. We rigorously characterize genome-wide association in eukaryotes between the spatial organization of mono-nucleosomes and their corresponding histone modifications, protein binding activities, and higher-order chromatin functions. We also predict two tetra-nucleosome folding structures in human embryonic stem cells using machine learning methods and analysis their distribution at different structural and functional regions. Based on the identified nucleosomes, nucleosome contact maps are constructed, reflecting the inter-nucleosome distances and preserving the original datas contact distance profile.

bioinformatics↗

bioRxiv2021

Identification and Characterization of Long Non-Coding RNA in Tomato Roots under Salt Stress

As one of the most important vegetable crops in the world, the production of tomatoes was restricted by salt stress. Therefore, it is of great interest to analyze the salt stress tolerance genes. As the non-coding RNAs (ncRNAs) with a length of more than 200 nucleotides, long non-coding RNAs (lncRNAs) lack the ability of protein-coding, but they can play crucial roles in plant development and response to abiotic stresses by regulating gene expression. Nevertheless, there are few studies on the roles of salt-induced lncRNAs in tomatoes. Therefore, we selected wild tomato Solanum pennellii (S. pennellii) and cultivated tomato M82 to be materials. By high-throughput sequencing, 1044 putative lncRNAs were identified here. Among them, 154 and 137 lncRNAs were differentially expressed in M82 and S. pennellii, respectively. Through functional analysis of target genes of differentially expressed lncRNAs (DE-lncRNAs), some genes were found to respond positively to salt stress by participating in Abscisic Acid (ABA) signaling pathway, brassinosteroid (BR) signaling pathway, ethylene (ETH) signaling pathway and anti-oxidation process. We also construct a salt-induced lncRNA-mRNA co-expression network to dissect the putative mechanisms of high salt tolerance in S. pennellii. We analyze the function of salt-induced lncRNAs in tomato roots at the genome-wide levels for the first time. These results will contribute to understanding the molecular mechanisms of salt tolerance in tomatoes from the perspective of lncRNAs.

bioinformatics↗

bioRxiv2021

A novel cryo-electron microscopy support film based on 2D crystal of HFBI protein

Cryo-electron microscopy (cryo-EM) has become the most powerful tool to resolve the high-resolution structures of biomacromolecules in solution. However, the air-water interface induced preferred orientation, dissociation or denaturation of biomacromolecules during cryo-vitrification is still a major limitation factor for many specimens. To solve this bottleneck, we developed a new type of cryo-EM support film using the 2D crystal of hydrophobin I (HFBI) protein. The HFBI-film utilizes its hydrophilic side to adsorb protein particles via electrostatic interactions and keep air-water interface away, allowing thin-enough ice and high-quality data collection. The particle orientation distribution can be optimized by changing the buffer pH. We, for the first time, solved the cryo-EM structure of catalase (2.28-[A]) that exhibited strong preferred orientation using conventional cryo-vitrification protocol. We further proved the HFBI-film is suitable to solve the high-resolution structures of small proteins including aldolase (150 kDa, 3.34-[A]) and hemoglobin (64 kDa, 3.6-[A]). Our work implied that the HFBI-film will have a wide application in the future to increase the successful rate and efficiency of cryo-EM.

biophysics↗

bioRxiv2021

A graph neural network approach to molecule carcinogenicity prediction

Molecular carcinogenicity is a preventable cause of cancer, however, most experimental testing of molecular compounds is an expensive and time consuming process, making high throughput experimental approaches infeasible. In recent years, there has been substantial progress in machine learning techniques for molecular property prediction. In this work, we propose a model for carcinogenicity prediction, CONCERTO, which uses a graph transformer in conjunction with a molecular fingerprint representation, trained on multi-round muta-genicity and carcinogenicity objectives. To train and validate CONCERTO, we augment the training dataset with more informative labels and utilize a larger external validation dataset. Extensive experiments demonstrate that our model yields results superior to alternate approaches for molecular carcinogenicity prediction.

bioinformatics↗

bioRxiv2021

scDeepHash: An automatic cell type annotation and cell retrieval method for large-scale scRNA-seq datasets using neural network-based hashing

Single-cell RNA-sequencing technologies measure transcriptomic expressions, which quantifies cell-to-cell heterogeneity at an unprecedented resolution. As these technologies become more readily available, the number of scRNA-seq datasets increases drastically. Prior works have demonstrated that bias-free, holistic single-cell profiling infrastructures are essential to the emerging automatic cell-type annotation methods. We propose scDeepHash, a scalable scRNA-seq analytic tool that employs content-based deep hashing to index single-cell gene expressions. scDeepHash allows for fast and accurate automated cell-type annotation and similar-cell retrieval. We also demonstrate the performance of scDeepHash by benchmarking it against current state-of-the-art methods across multiple public scRNA-seq datasets.

bioinformatics↗