Biology subjects

Yu, Y.

Publications and source records attributed to Yu, Y..

At least 343 records · Page 19Linked to original sources

bioRxiv2022

Induced Degradation of Lineage-specific Oncoproteins Drives the Selective PARP1 Inhibitor Toxicity in Small Cell Lung Cancer

A subset of small cell lung cancer (SCLC) shows clinically relevant response to PARP1 inhibitors (PARPi). However, BRCA1/2 mutations are not commonly found in SCLC, and the underlying mechanism(s) of PARPi sensitivity in SCLC is poorly understood. We performed quantitative proteomic analyses and identified proteomic changes that signify PARPi responses in a large panel of molecularly annotated patient-derived SCLC lines. We found that the toxicity of PARPi in SCLC could be explained, at least in part, by the PARPi-induced degradation of key lineage-specific oncoproteins including ASCL1, NEUROD1, POU2F3, KDM4A, and KDM5B. Importantly, the degradation of these SCLC lineage-specific oncoproteins could also be induced by commonly used chemotherapeutic agents. Biochemical experiments showed that PARPi-induced activation of E3 ligases (e.g., HUWE1 and RNF8) mediated the ubiquitin-proteasome system (UPS)-dependent degradation of these oncoproteins. Interestingly, although PARPi resulted in a general DNA damage response in SCLC cells, this signal is sensed by different SCLC cell lines to generate a cell-specific response. The dissection of the cell-specific oncoprotein degradation response led to the identification of potentially predictive biomarkers for PARPi in SCLC. The combination of PARPi and agents targeting these pathways led to dramatically improved cytotoxicity in SCLC. PARPi-induced degradation of lineage-specific oncoproteins therefore represents a novel mechanism to explain the efficacy of PARPi in tumors without BRCA1/2 mutations. HighlightsO_LIQuantitative mass spectrometric analysis identifies proteomic changes associated with PARPi treatment in a large panel of SCLC cell lines. C_LIO_LIPARPi leads to the degradation of lineage-specific oncoproteins (e.g., ASCL1 and KDM4A) via the DNA damage responsive E3 ubiquitin ligases (e.g., HUWE1 and RNF8). C_LIO_LIA combination of PARPi and agents targeting the lineage-specific oncoproteins offers a more complete and durable therapeutic response in SCLC, compared to PARPi alone. C_LIO_LIExpression of lineage-specific oncoproteins and the associated ubiquitination machinery are predictive biomarkers for PARPi-induced cytotoxicity in SCLC. C_LI

cancer biology↗

bioRxiv2022

Age-specific activation of microglial genes in a mouse model of AD

Alzheimers disease (AD) is a neurodegenerative disease that increases its prevalence with age. AD is characterized by a progressive loss of cognitive function, leading to dementia. The conventional pathological hallmarks of AD include deposition of amyloid plaque, aggregation of neurofibrillary tangles, and sustained inflammation. Recent studies have confirmed that immune responses play an important role in AD progression. Single-cell RNA-sequencing (RNA-seq) studies of the AD mouse model identified the disease-associated microglia (DAM) population during AD progression, where the pro-inflammatory activity was mediated by Trem2. However, the time points and nature of DAM activation remain largely unknown. Here, we compared the time-result bulk sequencing andsingle nuclei RNA sequencing data in a mouse model of AD. We identified an age-dependent activation of Trem2 targeted immune-related genes. We showed that Trem2 affected DAM activation at an early stage (4-8 months) rather than the late stage (12-16 months). Our results highlight an age-dependent change in the Trem2-linked immune response in AD.

neuroscience↗

bioRxiv2022

Ratio-based quantitative multiomics profiling using universal reference materials empowers data integration

Multiomics profiling is a powerful tool to characterize the same samples with complementary features orchestrating the genome, epigenome, transcriptome, proteome, and metabolome. However, the lack of ground truth hampers the objective assessment of and subsequent choice from a plethora of measurement and computational methods aiming to integrate diverse and often enigmatically incomparable omics datasets. Here we establish and characterize the first suites of publicly available multiomics reference materials of matched DNA, RNA, proteins, and metabolites derived from immortalized cell lines from a family quartet of parents and monozygotic twin daughters, providing built-in truth defined by family relationship and the central dogma. We demonstrate that the "ratio"-based omics profiling data, i.e., by scaling the absolute feature values of a study sample relative to those of a concurrently measured universal reference sample, were inherently much more reproducible and comparable across batches, labs, platforms, and omics types, thus empower the horizontal (within-omics) and vertical (cross-omics) data integration in multiomics studies. Our study identifies "absolute" feature quantitation as the root cause of irreproducibility in multiomics measurement and data integration, and urges a paradigm shift from "absolute" to "ratio"-based multiomics profiling with universal reference materials.

systems biology↗

bioRxiv2022

Quartet protein reference materials and datasets for multi-platform assessment of label-free proteomics

Quantitative proteomics is an indispensable tool in life science research. However, there is a lack of reference materials for evaluating the reproducibility of label-free liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based measurements among different instruments and laboratories. We developed the Quartet as a proteome reference material with built-in truths, and distributed the same aliquots to 15 laboratories with nine conventional LC-MS/MS platforms across six cities in China. Relative abundance of over 12,000 proteins on 816 MS files were obtained and compared for reproducibility among the instruments and laboratories to ultimately generate proteomics benchmark datasets. There was a wide dynamic range of proteomes spanning ~7 orders of magnitude (101-108 copies/cell), and the injection order had marked effects on quantitative instead of qualitative. Overall, the Quartet offers valuable standard materials and data resources for improving the quality control of proteomic analyses as well as the reproducibility and reliability of research findings.

molecular biology↗

bioRxiv2022

Targeting oncogenic Wnt/β-catenin signaling in adrenocortical carcinoma disrupts ECM expression and impairs tumor growth.

Adrenocortical carcinoma (ACC) is a rare, but highly aggressive cancer with limited treatment options and poor survival for patients with advanced disease. Improved understanding of transcriptional programs engaged in ACC will help direct rational, targeted therapies. While activating mutations in Wnt/{beta}-catenin signaling are frequently observed, the {beta}-catenin-dependent transcriptional targets that promote tumor progression are poorly understood. To address this question, we used independent component analysis and identified a novel Wnt/{beta}-catenin-associated signature in ACC predictive of poor survival. This signature was enriched for the extracellular matrix (ECM), suggesting a potential role for Wnt/{beta}-catenin in regulating the ACC microenvironment. We further investigated the minor fibrillar collagen, collagen XI alpha 1 (COL11A1), and found that COL11A1 expression strongly correlated with both Wnt/{beta}-catenin activation and poor patient survival. Inhibition of constitutively active Wnt/{beta}-catenin signaling in the human ACC cell line, NCI-H295R, significantly reduced expression of COL11A1 and other ECM components, and decreased viability of cancer cells in vitro. To investigate the preclinical potential of Wnt/{beta}-catenin inhibition in vivo, we developed and characterized a novel orthotopic xenograft model utilizing minimally invasive techniques. Treatment with the newly developed Wnt/{beta}-catenin:TBL1 inhibitor Tegavivint significantly reduced tumor growth in this preclinical model. Together, our data supports that inhibition of aberrantly active Wnt/{beta}-catenin disrupts transcriptional reprogramming of the microenvironment and reduces ACC growth and survival. Furthermore, this {beta}-catenin-dependent oncogenic program can be therapeutically targeted with a newly developed Wnt/{beta}-catenin inhibitor. These results show promise for further clinical development of Wnt/{beta}-catenin inhibitors in ACC and unveil a novel Wnt/{beta}-catenin-regulated transcriptome. Simple SummaryAdrenocortical carcinoma (ACC) is a rare, often deadly cancer arising from the adrenal gland. Mortality associated with ACC remains unchanged over the last several decades. The rarity of ACC, an incomplete understanding of its molecular basis, and limited availability of pre-clinical models have hampered the development of new effective therapies. The present work aims to address these gaps with a focus on the Wnt/{beta}-catenin cell signaling pathway, which is aberrantly activated in ~40% of ACC tumors. We discover a novel ECM program activated in ACC that is associated with Wnt/{beta}-catenin and poor survival. Wnt/{beta}-catenin inhibition disrupts expression of ECM genes and induces loss of cancer cell viability. To extend these findings, we develop a rapid orthotopic mouse model of ACC and demonstrate that disruption of the Wnt/{beta}-catenin axis with novel small molecule inhibitor Tegavivint is a potential effective therapeutic strategy to reduce ACC tumor burden in vivo.

cancer biology↗

bioRxiv2022

Correcting batch effects in large-scale multiomic studies using a reference-material-based ratio method

Batch effects are notorious technical variations that are common in multiomic data and may result in misleading outcomes. With the era of big data, tackling batch effects in multiomic integration is urgently needed. As part of the Quartet Project for quality control and data integration of multiomic profiling, we comprehensively assess the performances of seven batch-effect correction algorithms (BECAs) for mitigating the negative impact of batch effects in multiomic datasets, including transcriptomics, proteomics, and metabolomics. Performances are evaluated based on accuracy of identifying differentially expressed features, robustness of predictive models, and the ability of accurately clustering cross-batch samples into their biological sample groups. Ratio-based method is more effective and widely applicable than others, especially in cases when batch effects are highly confounded with biological factors of interests. We further provide practical guidelines for the implementation of ratio-based method using universal reference materials profiled with study samples. Our findings show the promise for eliminating batch effects and enhancing data integration in increasingly large-scale, cross-batch multiomic studies.

systems biology↗

bioRxiv2022

Proteomic profiling reveals lysosomal heterogeneity in association with longevity

Lysosomes are active sites to integrate cellular metabolism and signal transduction. A collection of proteins associated with the lysosome mediate these metabolic and signaling functions. Both lysosomal metabolism and lysosomal signaling have been linked to longevity regulation; however, how lysosomes adjust their protein composition to accommodate this regulation remains unclear. Using deep proteomic profiling, we systemically profiled lysosome-associated proteins linked with different longevity mechanisms. We further discovered the lysosomal recruitment of AMPK and nucleoporin proteins and their requirements for longevity in response to increased lysosomal lipolysis. Through comparative proteomic analyses of lysosomes from different tissues and labeled with different markers, we discovered lysosomal heterogeneity across tissues as well as the specific enrichment of the Ragulator complex on Cystinosin positive lysosomes. Together, this work uncovers lysosomal proteome heterogeneity at different levels and provides resources for understanding the contribution of lysosomal protein dynamics to signal transduction, organelle crosstalk and organism longevity.

cell biology↗

bioRxiv2022

Nimbolide Targets RNF114 to Induce the Trapping of PARP1 and Poly-ADP-Ribosylation-Dependent DNA Repair Factors

PARP1 is an abundant nuclear enzyme that is critically involved in DNA damage response. Its main enzymatic function is to catalyze a protein post-translational modification known as poly-ADP-ribosylation (PARylation). Despite the tremendous progresses of PARP1 inhibitors (PARPi) in the clinic, the basic mechanism of action of PARPi is poorly understood. Recent studies point to PARP1 trapping as a key factor driving the cytotoxic and immunomodulatory functions of PARPi. However, the molecular underpinnings of PARP1 trapping remain elusive. Here, using an unbiased, quantitative proteomic screen, we identified RING finger protein 114 (RNF114), as a PARylation-dependent, ubiquitin E3 ligase involved in DNA damage response. Upon sensing DNA damage, RNF114 was recruited, in a PAR-dependent manner, to the DNA lesions, where it specifically targeted PARylated-PARP1 for ubiquitin-proteasomal degradation. The blockade of this pathway interfered with the removal of PARP1 from the DNA damage site, leading to profound PARP1 trapping. We show that a natural product, Nimbolide, targeted RNF114 to block the degradation and removal of PARylated-PARP1 from DNA lesions. Unlike conventional PARPi, nimbolide treatment induced the trapping of both PARP1 and PARylation-dependent DNA repair factors. This unique mechanism of action of nimbolide translated into its superior cytotoxic effects against BRCA-deficient cancers. Furthermore, we demonstrated that, as a super trapper of both PARylated-PARP1 and PARylation-dependent DNA repair factors, nimbolide was able to overcome the intrinsic and acquired resistance to PARPi. Finally, we showed that nimbolide treatment activated innate immune signaling and was able to synergize with various cytotoxic agents. These results point to the exciting possibility of targeting homologous recombination-deficient cancers using nimbolide and its analogs.

cancer biology↗

bioRxiv2022

The Quartet Data Portal: integration of community-wide resources for multiomics quality control

The implementation of quality control for multiomic data requires the widespread use of well-characterized reference materials, reference datasets, and related resources. The Quartet Data Portal was built to facilitate community access to such rich resources established in the Quartet Project. A convenient platform is provided for users to request the DNA, RNA, protein, and metabolite reference materials, as well as multi-level datasets generated across omics, platforms, labs, protocols, and batches. Interactive visualization tools are offered to assist users to gain a quick understanding of the reference datasets. Crucially, the Quartet Data Portal continuously collects, evaluates, and integrates the community-generated data of the distributed Quartet multiomic reference materials. In addition, the portal provides analysis pipelines to assess the quality of user-submitted multiomic data. Furthermore, the reference datasets, performance metrics, and analysis pipelines will be improved through periodic review and integration of multiomic data submitted by the community. Effective integration of the evolving technologies via active interactions with the community will help ensure the reliability of multiomics-based biological discoveries. The Quartet Data Portal is accessible at https://chinese-quartet.org. Graphical Abstract O_FIG_DISPLAY_L [Figure 1] M_FIG_DISPLAY C_FIG_DISPLAY

systems biology↗

bioRxiv2022

Quartet DNA reference materials and datasets for comprehensively evaluating germline variants calling performance

Current methods for evaluating the accuracy of germline variant calls are restricted to easy-to-detect high-confidence regions, thus ignoring a substantial portion of difficult variants beyond the benchmark regions. We established four DNA reference materials from immortalized cell lines derived from a Chinese Quartet including parents and monozygotic twins. We integrated benchmark calls of 4.2 million small variants and 15,000 structural variants from multiple platforms and bioinformatic pipelines for evaluating the reliability of germline variant calls inside the benchmark regions. The genetic built-in-truth of the Quartet family design not only improved sensitivity of benchmark calls by removing additional false positive variants with apparently high quality, but also enabled estimation of the precision of variants calls outside the benchmark regions. Batch effects of variant calling in large-scale DNA sequencing efforts can be effectively identified with the concurrent use of the Quartet DNA reference materials along with study samples, and can be alleviated by training a machine learning model with the Quartet reference datasets to remove potential artifact calls. Matched RNA and protein reference materials were also established in the Quartet project, thereby enabling benchmark calls constructed from DNA reference materials for evaluation of variants calling performance on RNA and protein data. The Quartet DNA reference materials from this study are a resource for objective and comprehensive assessment of the accuracy of germline variant calls throughout the whole-genome regions.

bioinformatics↗

bioRxiv2022

From Correlation to Communication: disentangling hidden factors from functional connectivity changes

While correlations in the BOLD fMRI signal are widely used to capture functional connectivity (FC) and its changes across contexts, its interpretation is often ambiguous. The entanglement of multiple factors including local coupling of two neighbors and non-local inputs from the rest of the network (affecting one or both regions) limits the scope of the conclusions that can be drawn from correlation measures alone. Here we present a method of estimating the contribution of non-local network input to FC changes across different contexts. To disentangle the effect of task-induced coupling change from the network input change, we propose a new metric, "communication change", utilizing BOLD signal correlation and variance. With a combination of simulation and empirical analysis, we demonstrate that 1) input from the rest of the network accounts for a moderate but significant amount of task-induced FC change; 2) the proposed "communication change" is a promising candidate for tracking the local coupling in task context-induced change. Additionally, when compared to FC change across three different tasks, communication change can better discriminate specific task types. Taken together, this novel index of local coupling may have many applications in improving our understanding of local and widespread interactions across large-scale functional networks.

neuroscience↗

bioRxiv2022

Quartet RNA reference materials and ratio-based reference datasets for reliable transcriptomic profiling

As an indispensable tool for transcriptome-wide analysis of differential gene expression, RNA sequencing (RNAseq) has demonstrated great potential in clinical applications. However, the lack of multi-group RNA reference materials of biological relevance and the corresponding reference datasets for assessing the reliability of RNAseq hampers its wide clinical applications wherein the underlying biological differences among study groups are often small. As part of the Quartet Project for quality control and data integration of multiomic profiling, we established four RNA reference materials derived from immortalized B-lymphoblastoid cell lines from four members of a monozygotic twin family. Additionally, we constructed ratio-based transcriptome-wide reference datasets using multi-batch RNAseq datasets, providing "ground truth" for benchmarking. Moreover, Quartet-sample-based quality metrics were developed for assessing reliability of RNAseq technology in terms of intra-batch proficiency and cross-batch reproducibility. The small intrinsic biological differences among the Quartet samples enable sensitive assessment of performance of transcriptomic measurements. The Quartet RNA reference materials combined with the reference datasets can be served as unique resources for assessing data quality and improving reliability of transcriptomic profiling.

genetics↗

bioRxiv2022

Imprinted SARS-CoV-2 humoral immunity induces converging Omicron RBD evolution

Continuous evolution of Omicron has led to a rapid and simultaneous emergence of numerous variants that display growth advantages over BA. 5. Despite their divergent evolutionary courses, mutations on their receptor-binding domain (RBD) converge on several hotspots. The driving force and destination of such convergent evolution and its impact on humoral immunity remain unclear. Here, we demonstrate that these convergent mutations can cause striking evasion of neutralizing antibody (NAb) drugs and convalescent plasma, including those from BA.5 breakthrough infection, while maintaining sufficient ACE2 binding capability. BQ.1.1.10, BA.4.6.3, XBB, and CH. 1.1 are the most antibody-evasive strain tested, even exceeding SARS-CoV-1 level. To delineate the origin of the convergent evolution, we determined the escape mutation profiles and neutralization activity of monoclonal antibodies (mAbs) isolated from BA.2 and BA.5 breakthrough-infection convalescents. Importantly, due to humoral immune imprinting, BA.2 and especially BA.5 breakthrough infection caused significant reductions in the epitope diversity of NAbs and increased proportion of non-neutralizing mAbs, which in turn concentrated humoral immune pressure and promoted convergent evolution. Moreover, we showed that the convergent RBD mutations could be accurately inferred by integrated deep mutational scanning (DMS) profiles, and the evolution trends of BA.2.75/BA.5 subvariants could be well-simulated through constructed convergent pseudovirus mutants. Together, our results suggest current herd immunity and BA.5 vaccine boosters may not provide good protection against infection. Broad-spectrum SARS-CoV-2 vaccines and NAb drugs development should be highly prioritized, and the constructed mutants could help to examine their effectiveness in advance.

immunology↗

bioRxiv2022

Spatial transcriptomics reveals ovarian cancer subclones with distinct tumour microenvironments

High-grade serous ovarian carcinoma (HGSOC) is characterised by recurrence, chemotherapy resistance and overall poor prognosis. Genetic heterogeneity of tumour cells and the microenvironment of the tumour have been hypothesised as key determinants of treatment resistance and relapse. Here, using a combination of spatial and single cell transcriptomics (10x Visium and Chromium platforms), we examine tumour genetic heterogeneity and infiltrating populations of HGSOC samples from eight patients with variable response to neoadjuvant chemotherapy. By inferring gross copy number alterations (CNAs), we identified distinct tumour subclones co-existing within individual tumour sections. These tumour subclones have unique CNA profiles and spatial locations within each tumour section, which were further validated by ultra-low-pass whole genome sequencing. Differential expression analysis between subclones within the same section identified both tumour cell intrinsic expression differences and markers indicative of different infiltrating cell populations. The gene sets differentially expressed between subclones were significantly enriched for genes encoding plasma membrane and secreted proteins, indicative of subclone-specific microenvironments. Furthermore, we identified tumour derived ligands with variable expression levels between subclones that correlated or anticorrelated with various non-malignant cell infiltration patterns. We highlight several of these that are potentially direct tumour-stroma/immune cell relationships as the non-malignant cell type expresses a cognate receptor for the tumour derived ligand. These include predictions of CXCL10-CXCR3 mediated recruitment of T and B cells to associate with the subclones of one patient and CD47-SIRPA mediated exclusion of macrophages from association with subclones of another. Finally, we show that published HGSOC molecular subtype signatures associated with prognosis are heterogeneously expressed across tumour sections and that areas containing different tumour subclones with different infiltration patterns can match different subtypes. Our study highlights the high degree of intratumoural subclonal and infiltrative heterogeneity in HGSOC which will be critical to better understand resistance and relapse.

cancer biology↗

bioRxiv2022

Stac1 Regulates Sensory Stimulus Induced Escape Locomotion

The stac family of genes are expressed by several cell types including neurons and muscles in a wide variety of animals. In vertebrates, stac3 encodes an adaptor protein specifically expressed by skeletal muscle that regulates L-type calcium channels (CaChs) and excitation-contraction coupling. The function of Stac proteins expressed by neurons in the vertebrate CNS, however, is unclear. To better understand neuronal Stac proteins, we identified the stac1 gene in zebrafish. stac1 is expressed selectively in the embryonic CNS including in Kolmer-Agduhr (KA) neurons, the cerebral fluid-contacting neurons (CSF-cNs) in the spinal cord. Previously CSF-cNs in the spinal cord were implicated in locomotion by zebrafish larvae. Thus, expression of stac1 by CSF-cNs and the regulation of CaChs by Stac3 suggest the hypothesis that Stac1 may be important for normal locomotion by zebrafish embryos. We tested to see if optogenetic activation of CSF-cNs was sufficient to induced swimming in embryos as it is in larvae. Indeed, optogenetic activation of CSF-cNs in embryos induced swimming in embryos. Next, we generated stac1-/- null embryos and found that both mechanosensory and noxious stimulus-induced swimming were decreased. We further found that zebrafish embryos respond more vigorously to tactile stimulation in the light compared to the dark. Interestingly, light enhancement of touch-induced swimming was eliminated in stac1 mutants. Thus, Stac1 regulates escape locomotion in zebrafish embryos perhaps by regulating the activity of CSF-cNs. SIGNIFICANCE STATEMENTThe stac genes are a small family of genes found in neurons and muscle in both vertebrates and invertebrates. Stac3 is a muscle protein that controls excitation-contraction coupling via regulation of L-type calcium channels and in humans a STAC3 mutation is responsible for a congenital myopathy. The function of neural Stac proteins, however, is unknown in vertebrates. The findings of this report show that neural stac1 is expressed by cerebral fluid-contacting neurons (CSF-cNs) in the spinal cord of zebrafish embryos and that it is necessary for normal sensory stimulus induced escape swimming. To our knowledge this is the first demonstration of a function for stac genes in neurons in the vertebrate nervous system.

neuroscience↗

bioRxiv2022

Widely Used and Fast De Novo Drug Design by a Protein Sequence-Based Reinforcement Learning Model

De novo molecular design has facilitated the exploration of large chemical space to accelerate drug discovery. Structure-based de novo method can overcome the data scarcity of active ligands by incorporating drug-target interaction into deep generative architectures. However, these strategies are bottlenecked by the small fraction of experimentally determined protein or complex structures. In addition, the cost of the molecular generation is computationally expensive due to 3D representations of both molecule and protein. Here, we demonstrate a widely used and fast protein sequence-based reinforcement learning (RL) model for drug discovery. In the generative model, one of the reward components, a binding affinity predictor, is based on 1D protein sequence and molecular SMILES. As a proof of concept, the RL model was utilized to design molecules for four targets. The generated compounds showed bioactivities by the validation of both QSAR and molecular docking with experimental 3D binding pockets. We also found that the performance of generated molecules depends on the selection of data source training for the binding predictor. Furthermore, drug design for a kinase without any experimental structure, CDK20, was studied. By only 1D protein sequence as input, the generated novel compounds showed favorable binding affinity based on the AlphaFold predicted structure.

bioinformatics↗

bioRxiv2022

Development of highly potent non-covalent inhibitors of SARS-CoV-2 3CLpro

The SARS-CoV-2 virus is the causal agent of the ongoing pandemic of coronavirus disease 2019 (COVID-19). There is an urgent need for potent, specific antiviral compounds against SARS-CoV-2. The 3C-like protease (3CLpro) is an essential enzyme for the replication of SARS-CoV-2 and other coronaviruses, and thus is a target for coronavirus drug discovery. Nearly all inhibitors of coronavirus 3CLpro reported so far are covalent inhibitors. Here, we report the development of specific, non-covalent inhibitors of 3CLpro. The most potent one, WU-04, effectively blocks SARS-CoV-2 replications in human cells with EC50 values in the 10-nM range. WU-04 also inhibits the 3CLpro of SARS-CoV and MERS-CoV with high potency, indicating that it is a pan-inhibitor of coronavirus 3CLpro. WU-04 showed anti-SARS-CoV-2 activity similar to that of PF-07321332 (Nirmatrelvir) in K18-hACE2 mice when the same dose was administered orally. Thus, WU-04 is a promising drug candidate for coronavirus treatment. One-Sentence SummaryA oral non-covalent inhibitor of 3C-like protease effectively inhibits SARS-CoV-2 replication.

microbiology↗

bioRxiv2022

Further humoral immunity evasion of emerging SARS-CoV-2 BA.4 and BA.5 subvariants

Multiple BA.4 and BA.5 subvariants with R346 mutations on the spike glycoprotein have been identified in various countries, such as BA.4.6/BF.7 harboring R346T, BA.4.7 harboring R346S, and BA.5.9 harboring R346I. These subvariants, especially BA.4.6, exhibit substantial growth advantages compared to BA.4/BA.5. In this study, we showed that BA.4.6, BA.4.7, and BA.5.9 displayed higher humoral immunity evasion capability than BA.4/BA.5, causing 1.5 to 1.9-fold decrease in NT50 of the plasma from BA.1 and BA.2 breakthrough-infection convalescents compared to BA.4/BA.5. Importantly, plasma from BA.5 breakthrough-infection convalescents also exhibits significant neutralization activity decrease against BA.4.6, BA.4.7, and BA.5.9 than BA.4/BA.5, showing on average 2.4 to 2.6-fold decrease in NT50. For neutralizing antibody drugs, Bebtelovimab remains potent, while Evusheld is completely escaped by these subvariants. Together, our results rationalize the prevailing advantages of the R346 mutated BA.4/BA.5 subvariants and urge the close monitoring of these mutants, which could lead to the next wave of the pandemic.

immunology↗