Biology subjects

Zhu, R.

Publications and source records attributed to Zhu, R..

At least 73 records · Page 4Linked to original sources

bioRxiv2023

AAV-HBV mouse model replicates immune exhaustion patterns of chronic HBV patients at single-cell level

Background and AimsUnresolved hepatitis B virus (HBV) infection leads to a progressive state of immune exhaustion that impairs resolution of infection, leading to chronic infection (CHB). The immune-competent AAV-HBV mouse is a common HBV preclinical immune competent model, though a comprehensive characterization of the liver immune microenvironment and its translatability to human infection is still lacking. We investigated the intrahepatic immune profile of the AAV-HBV mouse model at a single-cell level and compared with data from CHB patients in immune tolerant (IT) and immune active (IA) clinical stages. MethodsImmune exhaustion was profiled through an iterative subclustering approach for cell-typing analyses of single-cell RNA-sequencing data in CHB donors and compared to the AAV-HBV mouse model 24-weeks post-transduction to assess its translatability. This was validated using an exhaustion flow cytometry panel at 40 weeks post-transduction. ResultsUsing single-cell RNA-sequencing, CD8 pre-exhausted T-cells with self-renewing capacity (TCF7+), and terminally exhausted CD8 T-cells (TCF7-) were detected in the AAV-HBV model. These terminally exhausted CD8 T-cells (expressing Pdcd1, Tox, Lag3, Tigit) were significantly enriched versus control mice and independently identified through flow cytometry. Importantly, comparison to CHB human data showed a similar exhausted CD8 T-cell population in IT and IA donors, but not in healthy individuals. ConclusionsLong term high titer AAV-HBV mouse liver transduction led to T-cell exhaustion, as evidenced by expression of classical immune checkpoint markers at mRNA and protein levels. In both IT and IA donors, a similar CD8 exhausted T-cell population was identified, with increased frequency observed in IA donors. These data support the use of the AAV-HBV mouse model to study T-cell exhaustion in HBV infection and the effect of immune-based therapeutic interventions. Lay SummaryThe AAV-HBV mouse model is used as a research tool to study hepatitis B infection. In this study we evaluated the translation value from mouse to human with regards to T-cell exhaustion. HighlightsO_LIAAV-HBV mice transduced with a high titer vector showed presence of CD8 exhausted T-cells after 24 weeks. C_LIO_LIHigh titer transduced mice, but not lower titer show increased expression of LAG-3, TOX, TIM-3 and TIGIT in CD8 T-cells. PD-1 was increased in CD8 T-cells, independent of HBV transduction titer. C_LIO_LIA similar exhausted CD8 T-cell population could be found in chronic HBV donors, but not in healthy individuals. C_LI Graphical abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=75 SRC="FIGDIR/small/552328v1_ufig1.gif" ALT="Figure 1"> View larger version (14K): org.highwire.dtl.DTLVardef@17db34dorg.highwire.dtl.DTLVardef@186a0b1org.highwire.dtl.DTLVardef@19fd39borg.highwire.dtl.DTLVardef@1fd9f64_HPS_FORMAT_FIGEXP M_FIG C_FIG

immunology↗

bioRxiv2023

Host-microbiota interactions contributing to the heterogeneous tumor microenvironment in colorectal cancer

BackgroundColorectal cancer (CRC) is a highly heterogeneous cancer with four consensus molecular subtypes (CMSs) characterized by distinct tumor microenvironment (TME). We aimed to depict the characteristics of host-microbiota interactions and their contributions to TME in each CMS. MethodsHost transcriptome and intratumoral microbiome profiles of 594 CRC samples were derived from RNA-Seq data from TCGA. Differential host genes and microbes among CMSs were identified. Immune microenvironments were assessed by CIBERSORTx and ESTIMATE and microbial co-abundance analyses were performed by FastSpar. Host-microbiota associations were evaluated by LASSO penalized regression in each CMS. ResultsAlong with distinct host gene signatures, including ferroptosis-related genes and immune microenvironments, 293, 153, 66 and 109 intratumoral differential microbial genera were identified within each of the four CMSs, respectively. Furthermore, the host-microbiota interactions contributed to distinct TME in each CMS, represented by 829, 1,270, 634 and 1,882 robust gene-microbe associations, respectively. The TME in CMS1 was featured with inflammation-related HSF1 activation and interactions between genes of endothelin pathway and Flammeovirga. Integrins-related genes positively correlated with Sutterella in CMS2 while CMS3 displayed microbial associations with biosynthetic and metabolic pathways. Genes in collagens biosynthesis positively correlated with Sutterella, contributing to homeostasis disturbance in CMS4. Besides, ferroptosis dysregulation was more remarkable in immune-high subtypes, which might partly result from the colonization of tissue microbes. ConclusionsWe systematically profiled the landscapes of TME, of each CMS in CRC, encompassing host genes, intratumoral microbiome and their interactions, which could illuminate novel mechanisms for the heterogeneity in CRC and potential therapeutic targets.

microbiology↗

bioRxiv2023

Chirality-Enhanced Transport and Drug Delivery of Graphene Nanocarriers to Tumor-like Cellular Spheroid

Chirality, defined as "a mirror image," is a universal geometry of biological and nonbiological forms of matter. This geometry of molecules determines how they interact during their assembly and transport. With the development of nanotechnology, many nanoparticles with chiral geometry or chiroptical activity have emerged for biomedical research. The mechanisms by which chirality originates and the corresponding synthesis methods have been discussed and developed in the past decade. Inspired by the chiral selectivity in life, a comprehensive and in-depth study of interactions between chiral nanomaterials and biological systems has far-reaching significance in biomedicine. Here, we investigated the effect of the chirality of nanoscale drug carriers, graphene quantum dots (GQDs), on their transport in tumor-like cellular spheroids. Chirality of GQDs (L/D-GQDs) was achieved by the surface modification of GQDs with L/D-cysteines. As an in-vitro tissue model for drug testing, cellular spheroids were derived from a human hepatoma cell line (i.e., HepG2 cells) using the Hanging-drop method. Our results reveal that the L-GQDs had a 1.7-fold higher apparent diffusion coefficient than the D-GQDs, indicating that the left-handed chirality of GQDs can enhance their transport into tumor-like cellular spheroids. Moreover, when loaded with a common chemotherapy drug, Doxorubicin (DOX), via {pi}-{pi} stacking, L-GQDs are more effective as nanocarriers for drug delivery, resulting in 25% higher efficacy for cancerous cellular spheroids than free DOX. Overall, our studies indicated that the chirality of nanocarriers is essential for the design of drug delivery vehicles to enhance the transport of drugs in a cancerous tumor.

bioengineering↗

bioRxiv2023

African swine fever virus I196L is a virulence determinant and its deletant induces robust protection in Domestic pig

The worldwide pandemic of African swine fever virus (ASFV) has a profound impact on the global pig industry. ASFV is a complex multilayered structure and the functions of unknown genes are being revealed. Here we deleted I196L from virulent ASFV SY18 with different length and obtained two recombinant viruses. The replication efficiency of the two recombinant viruses were similar but significantly lower than parental SY18. The pigs all survived the two recombinant viruses with 106.0TCID50 except one pig occurred sudden death and the suvived pigs all resisted the challenge without fever after intramuscularly injecting a lethal dose (102.0TCID50) of ASFV SY18. The recombinant viruses induced a strong anti-p54 humoral immune response. Meanwhile, the pigs also inevitably appeared moderate to high viremia throughout the observation period and presented a gradually downward trend. The results show that deleting I196L gene is a potential and effective vaccine that protects pigs from ASFV. IMPORTANCEThe worldwide outbreak of African swine fever (ASF) cannot be effectively prevented due to no availably commercial vaccine. Many different types of vaccine candidates are researched and reported, which is a hopeful trend to develop safety and efficacy vaccine. Here we report on an unknown functional gene, I196L, which affects the virulence and replication of ASFV. When I196L was deleted from ASFV SY18, the recombinant virus decreased virulence and resisted the challenge of parental strain. This is a novel, effective, potential live attenuated vaccine (LAVs) for ASF.

immunology↗

bioRxiv2023

Acute stress reshapes third-party punishment and help decisions: Behavioral evidence and neurocomputational mechanisms

People tend to intervene in others injustices by either punishing the transgressor or helping the victim. Injustice events often occur under stressful circumstances. However, how acute stress affects a third partys intervention in injustice events remains open. Here, we show a stress-induced shift in third parties willingness to engage in help instead of punishment by acting on emotional salience and central-executive and theory-of-mind networks. Acute stress decreased the third partys willingness to punish the violator and the severity of the punishment and increased their willingness to help the victim. Computational modeling revealed a shift in intervention severity bias from punishment toward help under stress. This finding is consistent with the increased dorsolateral prefrontal engagement observed with higher amygdala activity and greater connectivity with the ventromedial prefrontal cortex. A brain connectivity theory-of-mind network predicted stress-induced severity bias in punishment. Our findings suggest a neurocomputational mechanism of how acute stress reshapes third parties decisions by reallocating neural resources in emotional, executive and mentalizing networks to inhibit punishment bias and decrease punishment severity.

neuroscience↗

bioRxiv2023

Deciphering molecular heterogeneity and dynamics of neural stem cells in human hippocampal development, aging, and injury

While accumulated publications support the existence of neurogenesis in the adult human hippocampus, the homeostasis and developmental potentials of neural stem cells (NSCs) under different contexts remain unclear. Based on our generated single-nucleus atlas of the human hippocampus across neonatal, adult, aging and injury, we dissected the molecular heterogeneity and transcriptional dynamics of human hippocampal NSCs under different contexts. We further identified new specific neurogenic lineage markers that overcome the lack of specificity found in some well-known markers. Based on developmental trajectory and molecular signatures, we found that a subset of NSCs exhibit quiescent properties after birth, and most NSCs become deep quiescence during aging. Furthermore, certain deep quiescent NSCs are re-activated following stroke injury. Together, our findings provide valuable insights into the development, aging, and re-activation of the human hippocampal NSCs, and help to explain why adult hippocampal neurogenesis is infrequently observed in humans.

neuroscience↗

bioRxiv2023

Fecal metagenomics to identify biomarkers of food intake in healthy adults: Findings from randomized, controlled, nutrition trials

BackgroundUndigested components of the human diet affect the composition and function of the microorganisms present in the gastrointestinal tract. Techniques like metagenomic analyses allow researchers to study functional capacity, thus, revealing the potential of using metagenomic data for developing objective biomarkers of food intake. ObjectiveAs a continuation of our previous work using 16S and metabolomic datasets, we aimed to utilize a computationally intensive, multivariate, machine learning approach to identify fecal Kyoto Encyclopedia of Genes and Genomes (KEGG) Orthology (KO) categories as biomarkers that accurately classify food intake. DesignData were aggregated from five controlled feeding studies that studied the individual impact of almonds, avocados, broccoli, walnuts, barley, and oats on the adult gastrointestinal microbiota. DNA from pre-and post-intervention fecal samples underwent shotgun genomic sequencing. After pre-processing, sequences were aligned and functionally annotated with DIAMOND v2.0.11.149 and MEGAN v6.12.2, respectively. After count normalization, the log of the fold change ratio for resulting KOs between pre-and post-intervention of the treatment group against its corresponding control was utilized to conduct differential abundance analysis. Differentially abundant KOs were used to train machine learning models examining potential biomarkers in both single-food and multi-food models. ResultsWe identified differentially abundant KOs in the almond (n = 54), broccoli (n = 2,474), and walnut (n = 732) groups (q < 0.20), which demonstrated classification accuracies of 80%, 87%, and 86% for the almond, broccoli, and walnut groups, respectively, using a random forest model to classify food intake into each food groups respective treatment and control arms. The mixed-food random forest achieved 81% accuracy. ConclusionsOur findings reveal promise in utilizing fecal metagenomics to objectively complement self-reported measures of food intake. Future research on various foods and dietary patterns will expand these exploratory analyses for eventual use in feeding study compliance and clinical settings.

bioinformatics↗

bioRxiv2023

Transcription regulation of SARS-CoV-2 receptor ACE2 by Sp1: a potential therapeutic target

Angiotensin-converting enzyme 2 (ACE2) is a major cell entry receptor for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Induction of ACE2 expression may represent an effective tactic employed by SARS-CoV-2 to facilitate its own propagation. However, the regulatory mechanisms of ACE2 expression after viral infection remain largely unknown. By employing an array of 45 different luciferase reporters, we identify that the transcription factor Sp1 positively and HNF4 negatively regulate the expression of ACE2 at the transcriptional levels in HPAEpiC cells, a human lung epithelial cell line. SARS-CoV-2 infection promotes and inhibits the transcription activity of Sp1 and HNF4, respectively. The PI3K/AKT signaling pathway, which is activated by SARS-CoV-2 infection, is a crucial node for induction of ACE2 expression by increasing Sp1 phosphorylation, an indicator of its activity, and reducing HNF4 nuclear location. Furthermore, we show that colchicine could inhibit the PI3K/AKT signaling pathway, thereby suppressing ACE2 expression. Inhibition of Sp1 by either its inhibitor mithramycin A or colchicine reduces viral replication and tissue injury in Syrian hamsters infected with SARS-CoV-2. In summary, our study uncovers a novel function of Sp1 in regulating ACE2 expression and suggests that Sp1 is a potential target to reduce SARS-CoV-2 infection.

microbiology↗

bioRxiv2023

Multimodal meta-analysis of fecal metagenomes reveals microbial single nucleotide variants as superior biomarkers for early detection of colorectal cancer

Microbial signatures show remarkable potentials in predicting colorectal cancer (CRC). This study aimed to evaluate the diagnostic powers of multimodal microbial signatures, multi-kingdom species, genes, and single-nucleotide variants (SNVs) for detecting pre-cancerous adenomas. We performed cross-cohort analyses on whole metagenome sequencing data of 750 samples via xMarkerFinder to identify adenoma-associated microbial multimodal signatures. Our data revealed that fungal species outperformed species from other kingdoms with an area under the ROC curve (AUC) of 0.71 in distinguishing adenomas from controls, while classifier based on SNVs of bacterial species displayed the strongest diagnostic capability (AUC=0.89). SNV biomarkers also exhibited outstanding performances in three independent validation cohorts (AUCs = 0.83, 0.82, and 0.76, respectively) and were highly specific to adenoma. In further support of the above results, functional analyses revealed more frequent inter-kingdom associations between bacteria and fungi, and abnormalities in quorum sensing, purine and butanoate metabolism in adenoma, which were further validated in a newly-recruited cohort via qRT-PCR. Therefore, these data extend our understanding of adenoma-associated multimodal alterations in the gut microbiome and provide a rationale of microbial SNVs for the early detection of CRC.

cancer biology↗

bioRxiv2023

TERT accelerates BRAF mutant-induced thyroid cancer dedifferentiation and progression by regulating ribosome biogenesis

TERT reactivation occurs frequently in human malignancies. While BRAF activating mutation widely existed in cancers at various stages, TERT reactivation mainly occurs in advanced tumors. However, in vivo evidence for TERT role in cancer progression and the underlying mechanism is currently lacking. In this study, we induced TERT and/or BRAF V600E expression in mouse thyroid epithelium. TERT overexpression alone had no evident effect on tumor initiation. BRAFVE expression itself induced mediocre papillary thyroid cancer (PTC). Notably, the co-expression of BRAFVE and TERT resulted in aggressive poorly differentiated thyroid carcinoma (PDTC). Spatial transcriptome revealed that tumors from co-mutant mice were highly heterogeneous and dedifferentiation process significantly correlated with ribosomal pathways. Mechanistically, TERT boosted ribosomal RNA expression and protein synthesis. CX-5461, a rRNA transcription inhibitor, effectively blocked proliferation and induced redifferentiation. Thus, TERT promotes thyroid cancer progression by inducing dedifferentiation, and ribosome biogenesis inhibition represents a potential treatment strategy for TERT-reactivated cancers. Highlights[tpltrtarr] TERT accelerated thyroid cancer dedifferentiation and metastasis in vivo [tpltrtarr]TERT regulated rRNA metabolism and MTORC1/ S6K/RPS6 activities [tpltrtarr]CX-5461 inhibited the progression of TERT-reactivated melanoma and thyroid cancer [tpltrtarr]Inhibition of rRNA induced redifferentiation of advanced thyroid cancer with TERT activation

cancer biology↗

bioRxiv2023

Chiral Graphene Quantum Dots Enhanced Drug Loading into Exosomes

As nanoscale extracellular vesicles secreted by cells, exosomes have enormous potential as safe and effective vehicles to deliver drugs into lesion locations. Despite promising advances with exosome-based drug delivery systems, there are still challenges to drug loading into exosome, which hinder the clinical applications of exosomes. Herein, we report an exogenous drug-agnostic chiral graphene quantum dots (GQDs) exosome-loading platform, based on chirality matching with the exosome lipid bilayer. Both hydrophobic and hydrophilic chemical and biological drugs can be functionalized or adsorbed onto GQDs by {pi}-{pi} stacking and van der Waals interactions. By tuning the ligands and GQD size to optimize its chirality, we demonstrate drug loading efficiency of 66.3% and 64.1% for Doxorubicin and siRNA, which is significantly higher than other reported exosome loading techniques.

bioengineering↗

bioRxiv2022

Inhibition and Disassembly of Tau Aggregates by Engineered Graphene Quantum Dots

Tauopathies are a class of neurodegenerative diseases resulting in cognitive dysfunction, executive dysfunction, and motor disturbance. The primary pathological feature of tauopathies is the presence of neurofibrillary tangles in the brain composed of tau protein aggregates. Although numerous small molecules are known to inhibit tau aggregation, it is still challenging to use them for therapeutic applications due to their limitations in specific targeting and the blood-brain barrier (BBB) penetration. Graphene quantum dots (GQDs), one of graphene nanoparticles, can penetrate the BBB and are amenable to functionalization for targeted delivery. Moreover, these nanoscale biomimetic particles can self-assemble or assemble with various biomolecules including proteins. In this paper, for the first time, we showed that GQDs interacted with tau proteins via electrostatic and {pi}-{pi} stacking interactions to inhibit the fibrillization of monomeric tau and to trigger the disaggregation of tau filaments. In vitro thioflavin T assays demonstrated that negatively charged GQDs with larger sizes inhibited tau aggregation more efficiently, while positively charged ones were more effective in the disassembly of tau fibrils. Moreover, GQDs blocked the seeding activity of tau fibrils in a cellular propagation assay. Overall, our studies indicate GQDs with engineered properties can efficiently inhibit and disassemble pathological aggregation of tau proteins, which supports their future developments as a potential treatment for tauopathies.

bioengineering↗

bioRxiv2022

A synthetic protein-level neural network in mammalian cells

Artificial neural networks provide a powerful paradigm for information processing that has transformed diverse fields. Within living cells, genetically encoded synthetic molecular networks could, in principle, harness principles of neural computation to classify molecular signals. Here, we combine de novo designed protein heterodimers and engineered viral proteases to implement a synthetic protein circuit that performs winner-take-all neural network computation. This "perceptein" circuit includes modules that compute weighted sums of input protein concentrations through reversible binding interactions, and allow for self-activation and mutual inhibition of protein components using irreversible proteolytic cleavage reactions. Altogether, these interactions comprise a network of 310 chemical reactions stemming from 8 expressed protein species. The complete system achieves signal classification with tunable decision boundaries in mammalian cells. These results demonstrate how engineered protein-based networks can enable programmable signal classification in living cells. One-Sentence SummaryA synthetic protein circuit that performs winner-take-all neural network computation in mammalian cells

synthetic biology↗

bioRxiv2022

Comprehensive machine-learning survival framework develop a consensus model in large scale multi-center cohorts for pancreatic cancer

BackgroundAs the most aggressive tumor, the outcome of pancreatic cancer (PACA) has not improved observably over the last decade. Anatomy-based TNM staging does not exactly identify treatment-sensitive patients, and an ideal biomarker is urgently needed for precision medicine. MethodsA total of 1280 patients from 10 multi-center cohorts were enrolled. 10 machine-learning algorithms were transformed into 76 combinations, which were performed to construct an artificial intelligence-derived prognostic signature (AIDPS). The predictive performance, multi-omic alterations, immune landscape, and clinical significance of AIDPS were further explored. ResultsBased on 10 independent cohorts, we screened 32 consensus prognostic genes via univariate Cox regression. According to the criterion with the largest average C-index in the nine validation sets, we selected the optimal algorithm to construct the AIDPS. After incorporating several vital clinicopathological features and 86 published signatures, AIDPS exhibited robust and dramatically superior predictive capability. Moreover, in other prevalent digestive system tumors, the 9-gene AIDPS could still accurately stratify the prognosis. Of note, our AIDPS had important clinical implications for PACA, and patients with low AIDPS owned a dismal prognosis, relatively high frequency of mutations and copy number alterations, and denser immune cell infiltrates as well as were more sensitive to immunotherapy. Correspondingly, the high AIDPS group possessed dramatically prolonged survival, and panobinostat might be a potential agent for patients with high AIDPS. ConclusionsThe AIDPS could accurately predict the prognosis and immunotherapy efficacy of PACA, which might become an attractive tool to further guide the stratified management and individualized treatment. FundingThis study was supported by the National Natural Science Foundation of China (No. 81870457, 82172944).

bioinformatics↗

bioRxiv2022

Unsupervised approach to decomposing neural tuning variability

Neural representation is often described by the tuning curves of individual neurons with respect to certain stimulus variables. Despite this tradition, it has become increasingly clear that neural tuning can vary substantially in accordance with a collection of internal and external factors. A challenge we are facing is the lack of appropriate methods to accurately capture trial-to-trial tuning variability directly from the noisy neural responses. Here we introduce an unsupervised statistical approach, Poisson functional principal component analysis (Pf-PCA), which identifies different sources of systematic tuning fluctuations, moreover encompassing several current models (e.g.,multiplicative gain models) as special cases. Applying this method to neural data recorded from macaque primary visual cortex- a paradigmatic case for which the tuning curve approach has been scientific essential- we discovered a novel simple relationship governing the variability of orientation tuning, which unifies different types of gain changes proposed previously. By decomposing the neural tuning variability into interpretable components, our method enables discovery of new structure of the neural code, capturing the influence of the stimulus drive and internal states simultaneously.

neuroscience↗

bioRxiv2021

Proteomic Characterization of Serum Small Extracellular Vesicles in Human Breast Cancer

There is a lack of comprehensive understanding of breast cancer (BC) specific sEVs characteristics and composition on BC unique proteomic information from human samples. Here, we interrogated the proteomic landscape of sEVs in 167 serum samples from patients with BC, benign mammary disease (BD) and from healthy donors (HD). The analysis provides a comprehensive landscape of serum sEVs with totally 9,589 proteins identified, considerably expanding the panel of sEVs markers. Of note, serum BC-sEVs protein signatures were distinct from those of BD and HD, representing stage- and molecular subtype-specific patterns. We constructed specific sEVs protein identifiers that could serve as a liquid biopsy tool for diagnosis and classification of BC from benign mammary disease, molecular subtypes, as well as assessment of lymph node metastasis. We also identified 11 potential survival biomarkers for distant metastasis. This work may provide reference value for the accurate diagnosis and monitoring of BC progression using serum sEVs.

bioinformatics↗

bioRxiv2021

Protease-controlled secretion and display of intercellular signals

To program intercellular communication for biomedicine, it is crucial to regulate the secretion and surface display of signaling proteins. If such regulations are at the protein level, there are additional advantages, including compact delivery and direct interactions with endogenous signalling pathways. We created a modular, generalizable design called Retained Endoplasmic Cleavable Secretion (RELEASE), with engineered proteins retained in the endoplasmic reticulum and displayed/secreted in response to specific proteases. The design allows functional regulation of multiple synthetic and natural proteins by synthetic protease circuits to realize diverse signal processing capabilities, including logic operation and threshold tuning. By linking RELEASE to additional novel sensing and processing circuits, we were able to achieve elevated protein secretion in response to "undruggable" oncogene KRAS mutants. RELEASE should enable the local, programmable delivery of intercellular cues for a broad variety of fields such as neurobiology, cancer immunotherapy and cell transplantation.

synthetic biology↗

bioRxiv2021

Role of the amino acid mutations in the HA gene of H9N2 avian influenza virus under selective pressure in escape vaccine antibodies

It has been well-documented that some amino acid mutations in hemagglutinin (HA) of H9N2 avian influenza virus (H9N2 virus) alter the viral antigenicity, but little is reported about the role of antibody escape mutations in escape vaccine antibodies. In this study, we found that the evolution of F/98 strain in chicken embryos or chickens resulted in significant differences in immune escape, and identify the contribution of HA mutations to the antigenic variation and immune escape of H9N2 virus. Among amino acid mutations in the HA of the antigen variant viruses occurring in embryonated chicken eggs and/or chickens with or without the selection pressure of vaccine antibodies, the mutations, S145N, Q164L, A168T, A198V, M224K and Q234L, affect the antigen drift of H9N2 virus. Specially, the A198V mutation, located at the receptor-binding site on the head domain of HA, significantly contributed the antigenic variation of H9N2 virus. The mutation A198V or Q234L significantly improved the receptor binding activity, while S145N mutation decreased the receptor binding activity. Single S145N mutation could promote viral escape from polyclonal antibodies (pAbs) by preventing Ab binding physically, and single A198V mutation could promote viral escape from pAbs by enhancing the receptor binding activity. Additionally, either the mutation S145N or A198V did interfere with the immunogenicity of the inactivated vaccine, resulting in reduction of the protective efficiency of H9N2 inactivated vaccine, which contributed escape from the antibody-based immunity. Our findings provided an important reference for the accurate evaluation of the role of the amino acids mutation in HA affecting the antigenicity of H9N2 virus on immune escape, and delivered a new perspective for monitoring the adaptive evolution of H9N2 virus. ImportanceIn this study, the role of the HA mutations of H9N2 virus occurring with and without antibody selective pressure on escaping from the antibody-based immune response in host was analyzed. The results demonstrated that (i) the HA mutations S145N, Q164L, A168T, A198V, M224K, and Q234L occurring in the process of the adaptive evolution of H9N2 virus in embryonated chicken eggs and/or chickens could affect the antigenic variation of H9N2 virus. Among these mutations, the HA mutation A198V had the most significant effect on the antigenic variation; (ii) S145N mutation promoted viral escape from pAbs by preventing Abs binding physically; (iii) A198V mutation did promote viral escape from pAbs by enhancing the receptor binding activity; (iv) neither the HA mutation S145N or A198V interfered with the immunogenicity of the inactivated vaccine, resulting in reduction of the protective efficiency of H9N2 inactivated vaccine.

evolutionary biology↗