Biology subjects

Liu, L.

Publications and source records attributed to Liu, L..

At least 577 records · Page 32Linked to original sources

bioRxiv2022

Selective degradation of an ER stress-induced protein by ER-associated degradation mechanism during stress recovery

Unfolded protein response (UPR) is a conserved signaling pathway that is activated by accumulation of misfolded proteins in the endoplasmic reticulum (ER) and stimulates production of ER chaperones to restore ER proteostasis. However, little is known how UPR-induced proteins return to their pre-stress levels upon removal of ER stress. TUNICAMYCIN-INDUCED1 (TIN1) is an Arabidopsis protein that is normally expressed in pollen but is rapidly induced by ER stresses in vegetative tissues. Here we show that the ER stress-induced TIN1 is rapidly degraded in the UPR recovery phase. We found that TIN1 degradation depends on its asparagine-linked glycans and requires both EMS-mutagenized bri1 suppressor 5 (EBS5) and EBS6 for its recruitment to the ER-associated degradation (ERAD) complex. Loss-of-function mutations in Arabidopsis ERAD components greatly stabilize TIN1. Interestingly, two other UPR-induced proteins that are coexpressed with TIN1 remained stable upon removal of ER stress, suggesting that rapid degradation during the stress-recovery phase likely applies to a subset of UPR-induced proteins. Further investigation should uncover the mechanisms by which the ERAD machinery differentially recognizes UPR-induced ER proteins.

biochemistry↗

bioRxiv2022

Arabidopsis MLO4 Functions as a Ca2+ Channel Essential for Mechanosensing in Root Tips

Mechanical stimuli guide root growth to avoid obstacles in the soil. Although mechanisms underlying root mechanosensing remain largely unknown, calcium signaling is proposed to be an early event that proceeds directional root growth. In response to mechanical perturbations, root cells produce transient spikes in the cytosolic free Ca2+ levels. Loss-of-function mutations of MLOs cause root curling upon contact with hard surface of obstacles, the mechanism for MLOs action in root thigmomorphogenesis has been enigmatic. WT and mlo4 seedlings were grown on MS media containing gradient agar concentrations mimicking different levels of soil hardness and compared their root growth into the agar gradient mlo4 had much less roots penetrated the harder agar barrier as compared to WT roots. The channel activity of MLO4 was examined in Xenopus oocytes using the two-electrode voltage clamp (TEVC) method. The TEVC recording showed that the oocytes injected with MLO cRNA displayed large inward currents in the presence of Ca2+. MLO4 rescued the cch1/mid1 from growth arrest by the pheromone, these results indicate that MLO4 constitutes a novel Ca2+-permeable channel. Ca2+ spike was hardly detectable in mlo4/GCaMP6s seedings in response to a hard surface during root elongation. In summary, MLO4 functions as a typical Ca2+ channel that links touch stimulation to Ca2+ elevation in root tip cells.

plant biology↗

bioRxiv2022

Parallel analysis of RNA ends reveals global microRNA-mediated target RNA cleavage in maize

MicroRNAs (miRNAs) are endogenous 20-to 24-nucleotide (nt) noncoding RNAs that play important regulatory roles in many biological processes in eukaryotes. miRNAs modulate the expression of target genes at the post-transcriptional level by transcript cleavage or translational inhibition. Identification of miRNA target genes have been extensively investigated in Arabidopsis and rice, but an in-depth global analysis of miRNA-mediated target regulation is still lacking in maize. Here, we report a transcriptome-wide identification of miRNA targets by analyzing Parallel Analysis of RNA Ends (PARE) datasets derived from nine different tissues at five developmental stages of the maize (Zea mays L.) B73 cultivar. 246 targets corresponding to 60 miRNAs from 25 families were identified, including transcription factors and other genes. In addition, PARE analysis revealed that miRNAs guide specific target transcript cleavage in a tissue-preferential manner. Interestingly, primary transcripts of MIR159c and MIR169e were found to be cleaved by mature miR159 and miR169, respectively, indicating a positive-feedback regulatory mechanism in miRNA biogenesis. Moreover, several new miRNA-target gene pairs involved in seed germination were identified and experimentally validated. Our PARE analyses generated a wide and detailed miRNA-target interaction atlas, which provides a valuable resource for investigating the roles of miRNAs and their targets in maize.

plant biology↗

bioRxiv2022

Structure-based prediction and characterization of photo-crosslinking in native protein-RNA complexes

UV-crosslinking of protein and RNA in direct contacts has been widely used to study protein-RNA complexes despite our poor understanding on the mechanisms of photo-crosslinking. This knowledge gap is due to the challenge to precisely map the crosslink sites in protein and RNA simultaneously in their native sequence and structural contexts. Here we developed PxR3D-map, a computational method to analyze protein-RNA interactions and photo-crosslinking by bridging crosslinked nucleotides and amino acids mapped using different assays with protein-RNA complex structures. PxR3D-map reliably predicts crosslink sites using structural information characterizing protein-RNA interaction interfaces. We found that photo-crosslinking is facilitated by base stacking with not only aromatic residues, but also dipeptide bonds that involve glycine, and distinct mechanisms are utilized by different types of RNA-binding domains. Our work suggests protein-RNA photocrosslinking is highly selective in the cellular environment, which can guide interpretation of data generated by UV-crosslinking-based assays and further technology development.

biophysics↗

bioRxiv2022

Spatial-ID: a cell typing method for spatially resolved transcriptomics via transfer learning and spatial embedding

Spatially resolved transcriptomics (SRT) provides the opportunity to investigate the gene expression profiles and the spatial context of cells in naive state. Cell type annotation is a crucial task in the spatial transcriptome analysis of cell and tissue biology. In this study, we propose Spatial-ID, a supervision-based cell typing method, for high-throughput cell-level SRT datasets that integrates transfer learning and spatial embedding. Spatial-ID effectively incorporates the existing knowledge of reference scRNA-seq datasets and the spatial information of SRT datasets. A series of quantitative comparison experiments on public available SRT datasets demonstrate the superiority of Spatial-ID compared with other state-of-the-art methods. Besides, the application of Spatial-ID on a SRT dataset with 3D spatial dimension measured by Stereo-seq shows its advancement on the large field tissues with subcellular spatial resolution.

genomics↗

bioRxiv2022

SARS-CoV-2 Omicron BA.2.12.1, BA.4, and BA.5 subvariants evolved to extend antibody evasion

SARS-CoV-2 Omicron subvariants BA.2.12.1 and BA.4/5 have surged dramatically to become dominant in the United States and South Africa, respectively1,2. These novel subvariants carrying additional mutations in their spike proteins raise concerns that they may further evade neutralizing antibodies, thereby further compromising the efficacy of COVID-19 vaccines and therapeutic monoclonals. We now report findings from a systematic antigenic analysis of these surging Omicron subvariants. BA.2.12.1 is only modestly (1.8-fold) more resistant to sera from vaccinated and boosted individuals than BA.2. However, BA.4/5 is substantially (4.2-fold) more resistant and thus more likely to lead to vaccine breakthrough infections. Mutation at spike residue L452 found in both BA.2.12.1 and BA.4/5 facilitates escape from some antibodies directed to the so-called class 2 and 3 regions of the receptor-binding domain3. The F486V mutation found in BA.4/5 facilitates escape from certain class 1 and 2 antibodies but compromises the spike affinity for the viral receptor. The R493Q reversion mutation, however, restores receptor affinity and consequently the fitness of BA.4/5. Among therapeutic antibodies authorized for clinical use, only bebtelovimab retains full potency against both BA.2.12.1 and BA.4/5. The Omicron lineage of SARS-CoV-2 continues to evolve, successively yielding subvariants that are not only more transmissible but also more evasive to antibodies.

microbiology↗

bioRxiv2022

Spatial Transcriptomics-correlated Electron Microscopy

Current spatial transcriptomics methods identify cell states in a spatial context but lack morphological information. Scanning electron microscopy, in contrast, provides structural details at nanometer resolution but lacks molecular decoding of the diverse cellular states. To address this, we correlated MERFISH spatial transcriptomics with large area volume electron microscopy using adjacent tissue sections. We applied our technology to characterize the damage-associated microglial identities in mouse brain, allowing us, for the first time, to link the morphology of foamy microglia and interferon-response microglia with their transcriptional signatures.

neuroscience↗

bioRxiv2022

Mechanosensor Piezo1 Mediates Bimodal Patterns of Intracellular Signaling

Piezo1 belongs to mechano-activatable cation channels serving as biological force sensors. However, the molecular events downstream of Piezo1 activation remain unclear. In this study, we used biosensors based on fluorescence resonance energy transfer (FRET) to investigate the dynamic modes of Piezo1-mediated signaling and revealed a bimodal pattern of Piezo1-induced intracellular calcium signaling. Laser-induced shockwaves (LIS) and its associated shear stress can mechanically activate Piezo1 to induce transient intracellular calcium (Ca[i]) elevation, accompanied by an increase in FAK activity. Interestingly, multiple pulses of shockwave stimulation caused a more sustained calcium increase and a decrease of FAK activity. Similarly, tuning the degree of Piezo1 activation by titrating either the dosage of Piezo1 ligand Yoda1 or the expression level of Piezo1, produced a similar bimodal pattern of FAK responses. Specifically, a low degree of Piezo1 activation (transient mode) leads to a transient Ca[i] response with FAK activation, whereas a high degree of Piezo1 activation (sustained mode) causes a sustained Ca[i] response with FAK suppression. Further investigation revealed that SHP2 serves as an intermediate regulator mediating this bimodal pattern in Piezo1 sensing and signaling. These results suggest that the degrees of Piezo1 activation induced by both mechanical LIS and chemical ligand stimulation may determine downstream signaling characteristics.

biophysics↗

bioRxiv2022

Complexity of enhancer networks predicts cell identity and disease genes revealed by single-cell multi-omics analysis

Many enhancers exist as clusters in the genome and control cell identity and disease genes; however, the underlying mechanism remains largely unknown. Here, we introduce an algorithm, eNet, to build enhancer networks by integrating single-cell chromatin accessibility and gene expression profiles. Enhancer network is a gene regulation model we proposed that not only delineates the mapping between enhancers and target genes, but also quantifies the underlying regulatory relationships among enhancers. The complexity of enhancer networks is assessed by two metrics: the number of enhancers and the frequency of predicted enhancer interactions (PEIs) based on chromatin co-accessibility. We apply eNet algorithm to a human blood dataset and find cell identity and disease genes tend to be regulated by complex enhancer networks. The network hub enhancers (enhancers with frequent PEIs) are the most functionally important in enhancer networks. Compared with super-enhancers, enhancer networks show better performance in predicting cell identity and disease genes. The establishment of enhancer networks drives gene expression during lineage commitment. Applying eNet in various datasets in human or mouse tissues across different single-cell platforms, we demonstrate eNet is robust and widely applicable. Thus, we propose a model of enhancer networks containing three modes: Simple, Multiple and Complex, which are distinguished by their complexity in regulating gene expression. Taken together, our work provides an unsupervised approach to simultaneously identify key cell identity and disease genes and explore the underlying regulatory relationships among enhancers in single cells, without requiring the cell type identity in advance. HighlightsO_LIeNet, a computational method to build enhancer network based on scATAC-seq and scRNA-seq data C_LIO_LICell identity and disease genes tend to be regulated by complex enhancer networks, where network hub enhancers are functionally important C_LIO_LIEnhancer network outperforms the existing models in predicting cell identity and disease genes, such as super-enhancer and enhancer cluster C_LIO_LIWe propose a model of enhancer networks in gene regulation containing three modes: Simple, Multiple and Complex C_LI

bioinformatics↗

bioRxiv2022

Actuating tension-loaded DNA clamps drives membrane tubulation

Membrane dynamics in living organisms can arise from proteins adhering to, assembling on, and exerting force on cell membranes. Programmable synthetic materials, such as self-assembled DNA nanostructures, offer the capability to drive membrane remodeling events in a way that resembles protein-mediated dynamics, but with user-defined outcomes. An example showcasing this capability is the tubular deformation of liposomes by DNA nanostructures with purposely designed shapes, surface modifications, and self-assembling properties. However, stimulus-responsive membrane tubulation mediated by DNA structure reconfiguration remains challenging. Here we present the triggered formation of membrane tubes in response to specific DNA signals that actuate membrane-bound DNA clamps from an open state to various predefined closed states, releasing pre-stored energy to activate membrane deformation. Using giant unilamellar vesicles (GUVs) as a model system, we show that the timing and efficiency of tubulation, as well as the width of membrane tubes, are modulated by the conformational change of DNA clamps, marking a solid step toward spatiotemporal control of membrane dynamics in an artificial system.

synthetic biology↗

bioRxiv2022

Spatiotemporal landscape of SARS-CoV-2 pulmonary infection reveals Slamf9+Spp1+ macrophages promoting viral clearance and inflammation resolution

While SARS-CoV-2 pathogenesis has been intensively investigated, the host mechanisms of viral clearance and inflammation resolution are still elusive because of the ethical limitation of human studies based on COVID-19 convalescents. Here we infected Syrian hamsters by authentic SARS-CoV-2 and built an ideal model to simulate the natural recovery process of SARS-CoV-2 infection from severe pneumonia1,2. We developed and applied a spatial transcriptomic sequencing technique with subcellular resolution and tissue-scale extensibility, i.e., Stereo-seq3, together with single-cell RNA sequencing (scRNA-seq), to the entire lung lobes of 45 hamsters and obtained an elaborate map of the pulmonary spatiotemporal changes from acute infection, severe pneumonia to the late viral clearance and inflammation resolution. While SARS-CoV-2 infection caused massive damages to the hamster lungs, including naive T cell infection and deaths related to lymphopenia, we identified a group of monocyte-derived proliferating Slamf9+Spp1+ macrophages, which were SARS-CoV-2 infection-inducible and cell death-resistant, recruiting neutrophils to clear viruses together. After viral clearance, the Slamf9+Spp1+ macrophages differentiated into Trem2+ and Fbp1+ macrophages, both responsible for inflammation resolution and replenishment of alveolar macrophages. The existence of this specific macrophage subpopulation and its descendants were validated by RNAscope in hamsters, immunofluorescence in hACE2 mice, and public human autopsy scRNA-seq data of COVID-19 patients. The spatiotemporal landscape of SARS-CoV-2 infection in hamster lungs and the identification of Slamf9+Spp1+ macrophages that is pivotal to viral clearance and inflammation resolution are important to better understand the critical molecular and cellular players of COVID-19 host defense and also develop potential interventions of COVID-19 immunopathology.

immunology↗

bioRxiv2022

Genomic, transcriptomic and proteomic depiction of iPSC-derived smooth muscle cells as emerging cellular models for arterial diseases

BackgroundVascular smooth muscle cells (VSMCs) plasticity is a central mechanism in cardiovascular health and disease. We aimed at providing deep cellular phenotyping, epigenomic and proteomic depiction of SMCs derived from induced pluripotent stem cells (iPSCs) and evaluating their potential as cellular models in the context of complex genetic arterial diseases. MethodsWe differentiated 3 human iPSC lines using either RepSox (R-SMCs) or PDGF-BB and TGF-{beta} (TP-SMCs), during the second half of a 24-days-long protocol. In addition to cellular assays, we performed RNA-Seq and assay for transposase accessible chromatin (ATAC)-Seq at 6 time-points of differentiation. The extracellular matrix content (matrisome) generated by iPSCs derived SMCs was analyzed using mass spectrometry. ResultsBoth iPSCs differentiation protocols generated SMCs with positive expression of SMC markers. TP-SMCs exhibited greater capacity of proliferation, migration and lower calcium release in response to contractile stimuli compared to R-SMCs. RNA-Seq data showed that genes involved in the contractile function of arteries were highly expressed in R-SMCs compared to TP-SMCs or primary SMCs. Matrisome analyses supported an overexpression of proteins involved in wound repair in TP-SMCs and a higher secretion of basal membrane constituents by R-SMCs. Open chromatin regions of R-SMCs and TP-SMCs were significantly enriched for variants associated with coronary artery disease and blood pressure, while only TP-SMCs were enriched for variants associated with peripheral artery disease. ConclusionsOur study portrayed two iPSCs derived SMCs models presenting complementary cellular phenotypes of high relevance to SMC plasticity. In combination with genome-editing tools, our data supports high relevance of the use of these cellular models to the study of complex regulatory mechanisms at genetic risk loci involved in several arterial diseases. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=179 HEIGHT=200 SRC="FIGDIR/small/490058v1_ufig1.gif" ALT="Figure 1"> View larger version (29K): org.highwire.dtl.DTLVardef@1f1002corg.highwire.dtl.DTLVardef@1426fa7org.highwire.dtl.DTLVardef@b05b56org.highwire.dtl.DTLVardef@3c6e88_HPS_FORMAT_FIGEXP M_FIG C_FIG

cell biology↗

bioRxiv2022

Senescence-Induced Immune Remodeling Facilitates Metastatic Adrenal Cancer in a Sex-Dimorphic Manner

Aging is a carcinogen that markedly increases cancer risk, yet we have limited mechanistic understanding of cancer initiation in aged cells. Here, we demonstrate induction of the hallmark aging process cellular senescence, triggered by loss of Wnt inhibitor ZNRF3, remodels the tissue microenvironment and ultimately permits metastatic adrenal cancer. Detailed characterization reveals a striking sexual dimorphism. Males exhibit earlier senescence activation and a greater innate immune response. This results in high myeloid cell accumulation and lower incidence of malignancy. Conversely, females present a dampened immune response and are more prone to metastatic cancer. Senescence-recruited myeloid cells become increasingly depleted with advanced tumor progression, which is recapitulated in patients where a low myeloid signature is associated with worse outcome. Collectively, our study reveals a novel role for myeloid cells in restraining adrenal cancer progression with significant prognostic value, and provides a model for interrogating pleiotropic effects of cellular senescence in cancer. O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=67 SRC="FIGDIR/small/488426v1_ufig1.gif" ALT="Figure 1"> View larger version (21K): org.highwire.dtl.DTLVardef@bddf22org.highwire.dtl.DTLVardef@18434a3org.highwire.dtl.DTLVardef@9bc772org.highwire.dtl.DTLVardef@1430fbb_HPS_FORMAT_FIGEXP M_FIG Graphical abstract created with BioRender.com C_FIG

cancer biology↗

bioRxiv2022

Machine-Learning-Based Olfactometry: Odor Descriptor Clustering Analysis for Olfactory Perception Prediction of Odorant Molecules

Although gas chromatography/olfactometry (GC/O) has been employed as a powerful analytical tool in odor measurement, its application is limited by the variability, subjectivity, and high cost of the trained panelists who are used as detectors in the system. The advancements in data-driven science have made it possible to predict structure-odor-relationship (SOR) and thus to develop machine-learning-based olfactometry (ML-GCO) in which the human panelists may be replaced by machine learning models to obtain the sensory information of GC-separated chemical compounds. However, one challenge remained in ML-GCO is that there are too many odor descriptors (ODs) being used to describe the sensory characteristics of odorants. It is impractical to build a corresponding model for each OD. To solve this issue, we propose a SOR prediction approach based on odor descriptor clustering. 256 representative ODs are firstly classified into 20 categories using a co-occurrence Bayesian embedding model. The categorization effect is explained according to the semantic relationships using a pre-trained Word2Vec model. Various molecular structure features including molecularly parameters, molecular fingerprints, and molecular 2D graphic features extracted by convolutional neural networks, are employed to predict the aforementioned odor categories. High prediction accuracies (Area under ROC curve was 0.800{+/-}0.004) demonstrate the rationality of the proposed clustering scenario and molecular feature extraction. This study makes the ML-GCO models much closer to the practical application since they can be expected as either an auxiliary system or complete replacement of human panelists to perform the olfactory evaluation.

molecular biology↗

bioRxiv2022

Odorant molecular feature mining by diverse deep neural networks for prediction of odor perception categories

The use of an artificial intelligence (AI)-based prediction model of the structure-odor relationship (SOR) has shown great potential in the replacement of human panelists in gas chromatography-olfactometry (GCO). However, the Al-based GCO encounters issues such as poor accuracy, generalization, and practicality, owning to the insufficient feature extraction of odorant molecular structure. The purpose of this study is to the prediction of odor perception categories based on the odorant structure feature extraction by diverse deep neural networks, including molecular graphic convolution neural network (MG-CNN), molecular graph transformer neural network, and atom interaction neural networks. The results of the performance comparison of different feature extractors demonstrate that the MG-CNN model produces the highest accuracy and thus may be most suitable for the SOR prediction. It is hoped that the proposed method can be applied in practice as an auxiliary tool of GCO for the sensory evaluation of key compounds in food ingredients. HighlightsO_LIDifferent deep neural networks were used to predict categorized odor descriptors. C_LIO_LIEnd-to-end-based representation learning was performed for molecular feature extraction. C_LIO_LIMolecular graphs with pre-training of convolution neural networks was most accurate. C_LI Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/488977v2_ufig1.gif" ALT="Figure 1"> View larger version (33K): org.highwire.dtl.DTLVardef@10495a2org.highwire.dtl.DTLVardef@1fbf27eorg.highwire.dtl.DTLVardef@1ed3664org.highwire.dtl.DTLVardef@8e1383_HPS_FORMAT_FIGEXP M_FIG C_FIG

bioinformatics↗

bioRxiv2022

BIN2 phosphorylates the Thr280 of CO to restrict its function in promoting Arabidopsis flowering

CONSTANS (CO) is a central regulator of floral initiation in response to photoperiod. In this study, we show that the GSK3 kinase BIN2 physically interacts with CO and the gain-of-function mutant bin2-1 displays late flowering phenotype through down-regulation of FT transcription. Genetic analyses show that BIN2 genetically acts upstream of CO in regulating flowering time. Further, we illustrate that BIN2 phosphorylates the Thr280 residue of CO. Importantly, the BIN2 phosphorylation of Thr280 residue restricts the function of CO in promoting flowering. Moreover, we reveal that the N-terminal part of CO harboring the B-Box domain mediates the interaction of both CO-CO and BIN2-CO. We find that BIN2 inhibits the formation of CO dimer/oligomer. Taken together, this study reveals that BIN2 regulates flowering time through phosphorylating the Thr280 of CO and inhibiting the CO-CO interaction in Arabidopsis. HighlightBIN2 regulates flowering time through phosphorylating the Thr280 of CO in Arabidopsis.

molecular biology↗

bioRxiv2022

Cadmium is detrimental to Caenorhabditis elegans via anetwork involving circRNA, lncRNA and phosphorylatedprotein

Cadmium (Cd) as a heavy metal causes serious environmental pollution and multiple organ and system damage in human. However, little is known about the specific molecular mechanisms of the associated regulatory networks. In this study, we selected Caenorhabditis elegans (C. elegans) to investigate the effects of Cd exposure as it acts as an acknowledged and established genetic model organism. A total of 26 differentially-expressed circular RNA (DEcircRNAs), 143 lncRNAs (DElncRNAs), 69 microRNAs (DEmiRNAs) and 6209 mRNAs (DEmRNAs) were found and identified, which might influence reproductive function, aging processes and nervous system functions through regulating the levels of circRNAs and lncRNAs and the controlling of regulatory networks of circRNA/lncRNA-miRNA-mRNA. Based on quantitative PCR, four DEcircRNAs and three DElncRNAs were confirmed to have different expression levels between the Cd-treated and control group. Further, 5 protein-coding genes might be regulated by DElnRNAs through cis-acting and 114 by trans-acting elements. Additionally, 42 differentially regulative phosphopeptides were detected and 4 novel pairs of transcription factors (TFs)-kinase-substrate that might be influenced by Cd exposure were constructed by phosphoproteomics. Our findings suggest that Cd might influence multi-functions and the aging process of C. elegans and may inhibit the expression of TFs to reduce phosphorylated levels of the corresponding protein. SynopsisCadmium exists widely in soil, water and air. This study manifested the regulatory network involving circRNA, lncRNA and phosphorylated protein in C.elegans after Cd exposure, which revealing the potential molecular mechanism underlying the toxic effect caused by Cd. Graphic Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=82 SRC="FIGDIR/small/486470v1_ufig1.gif" ALT="Figure 1"> View larger version (26K): org.highwire.dtl.DTLVardef@1a012bborg.highwire.dtl.DTLVardef@2dc128org.highwire.dtl.DTLVardef@1e43ebaorg.highwire.dtl.DTLVardef@1d236b8_HPS_FORMAT_FIGEXP M_FIG C_FIG

molecular biology↗

bioRxiv2022

A high potent synthetic nanobody with broad-spectrum activity neutralizes SARS-Cov-2 virus and Omicron variant through a unique binding mode

The major challenge to control COVID pandemic is the rapid mutation rate of the SARS-Cov-2 virus, leading to the escape of the protection of vaccines and most of the neutralizing antibodies to date. Thus, it is essential to develop neutralizing antibodies with broad-spectrum activity targeting multiple SARS-Cov-2 variants. Here, we reported a synthetic nanobody (named C5G2) obtianed by phage display and subsequent antibody engineering. C5G2 has a single digit nanomolar binding affinity to RBD domain and inhibits its binding to ACE2 with an IC50 of 3.7 nM. Pseudovirus assay indicated that the monovalent C5G2 could protect the cells from the infection of SARS-Cov-2 wild type virus and most of the virus of concern, i.e. Alpha, Beta, Gamma and Omicron variants. Strikingly, C5G2 has the highest potency against Omicron among all the variants with the IC50 of 4.9ng/mL. The Cryo-EM structure of C5G2 in complex with the Spike trimer showed that C5G2 bind to RBD mainly through its CDR3 at a conserved region that not overlapping with the ACE2 binding surface. Additionally, C5G2 bind simultaneously to the neighboring NTD domain of spike trimer through the same CDR3 loop, which may further increase its potency against the virus infection. Third, the steric hindrance caused by FR2 of C5G2 could inhibit the binding of ACE2 to RBD as well. Thus, this triple-function nanobody may be served as an effective drug for the prophylaxis and therapy against Omicron as well as future variants.

biochemistry↗