COVID-19 immune features revealed by a large-scale single-cell transcriptome atlas.

A dysfunctional immune response in coronavirus disease 2019 (COVID-19) patients is a recurrent theme impacting symptoms and mortality, yet a detailed understanding of pertinent immune cells is not complete. We applied single-cell RNA sequencing to 284 samples from 196 COVID-19 patients and controls and created a comprehensive immune landscape with 1.46 million cells. The large dataset enabled us to identify that different peripheral immune subtype changes are associated with distinct clinical features, including age, sex, severity, and disease stages of COVID-19. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) RNA was found in diverse epithelial and immune cell types, accompanied by dramatic transcriptomic changes within virus-positive cells. Systemic upregulation of S100A8/A9, mainly by megakaryocytes and monocytes in the peripheral blood, may contribute to the cytokine storms frequently observed in severe patients. Our data provide a rich resource for understanding the pathogenesis of and developing effective therapeutic strategies for COVID-19.

Host-Viral Infection Maps Reveal Signatures of Severe COVID-19 Patients.

Viruses are a constant threat to global health as highlighted by the current COVID-19 pandemic. Currently, lack of data underlying how the human host interacts with viruses, including the SARS-CoV-2 virus, limits effective therapeutic intervention. We introduce Viral-Track, a computational method that globally scans unmapped single-cell RNA sequencing (scRNA-seq) data for the presence of viral RNA, enabling transcriptional cell sorting of infected versus bystander cells. We demonstrate the sensitivity and specificity of Viral-Track to systematically detect viruses from multiple models of infection, including hepatitis B virus, in an unsupervised manner. Applying Viral-Track to bronchoalveloar-lavage samples from severe and mild COVID-19 patients reveals a dramatic impact of the virus on the immune system of severe patients compared to mild cases. Viral-Track detects an unexpected co-infection of the human metapneumovirus, present mainly in monocytes perturbed in type-I interferon (IFN)-signaling. Viral-Track provides a robust technology for dissecting the mechanisms of viral-infection and pathology.

Chiral kagome superconductivity modulations with residual Fermi arcs.

Superconductivity involving finite-momentum pairing1 can lead to spatial-gap and pair-density modulations, as well as Bogoliubov Fermi states within the superconducting gap. However, the experimental realization of their intertwined relations has been challenging. Here we detect chiral kagome superconductivity modulations with residual Fermi arcs in KV3Sb5 and CsV3Sb5 using normal and Josephson scanning tunnelling microscopy down to 30 millikelvin with a resolved electronic energy difference at the microelectronvolt level. We observe a U-shaped superconducting gap with flat residual in-gap states. This gap shows chiral 2a × 2a spatial modulations with magnetic-field-tunable chirality, which align with the chiral 2a × 2a pair-density modulations observed through Josephson tunnelling. These findings demonstrate a chiral pair density wave (PDW) that breaks time-reversal symmetry. Quasiparticle interference imaging of the in-gap zero-energy states reveals segmented arcs, with high-temperature data linking them to parts of the reconstructed vanadium d-orbital states within the charge order. The detected residual Fermi arcs can be explained by the partial suppression of these d-orbital states through an interorbital 2a × 2a PDW and thus serve as candidate Bogoliubov Fermi states. In addition, we differentiate the observed PDW order from impurity-induced gap modulations. Our observations not only uncover a chiral PDW order with orbital selectivity but also show the fundamental space-momentum correspondence inherent in finite-momentum-paired superconductivity.

Stigma receptors control intraspecies and interspecies barriers in Brassicaceae.

Flowering plants have evolved numerous intraspecific and interspecific prezygotic reproductive barriers to prevent production of unfavourable offspring1. Within a species, self-incompatibility (SI) is a widely utilized mechanism that rejects self-pollen2,3 to avoid inbreeding depression. Interspecific barriers restrain breeding between species and often follow the SI × self-compatible (SC) rule, that is, interspecific pollen is unilaterally incompatible (UI) on SI pistils but unilaterally compatible (UC) on SC pistils1,4-6. The molecular mechanisms underlying SI, UI, SC and UC and their interconnections in the Brassicaceae remain unclear. Here we demonstrate that the SI pollen determinant S-locus cysteine-rich protein/S-locus protein 11 (SCR/SP11)2,3 or a signal from UI pollen binds to the SI female determinant S-locus receptor kinase (SRK)2,3, recruits FERONIA (FER)7-9 and activates FER-mediated reactive oxygen species production in SI stigmas10,11 to reject incompatible pollen. For compatible responses, diverged pollen coat protein B-class12-14 from SC and UC pollen differentially trigger nitric oxide, nitrosate FER to suppress reactive oxygen species in SC stigmas to facilitate pollen growth in an intraspecies-preferential manner, maintaining species integrity. Our results show that SRK and FER integrate mechanisms underlying intraspecific and interspecific barriers and offer paths to achieve distant breeding in Brassicaceae crops.

Surge of neurophysiological coupling and connectivity of gamma oscillations in the dying human brain.

The brain is assumed to be hypoactive during cardiac arrest. However, animal models of cardiac and respiratory arrest demonstrate a surge of gamma oscillations and functional connectivity. To investigate whether these preclinical findings translate to humans, we analyzed electroencephalogram and electrocardiogram signals in four comatose dying patients before and after the withdrawal of ventilatory support. Two of the four patients exhibited a rapid and marked surge of gamma power, surge of cross-frequency coupling of gamma waves with slower oscillations, and increased interhemispheric functional and directed connectivity in gamma bands. High-frequency oscillations paralleled the activation of beta/gamma cross-frequency coupling within the somatosensory cortices. Importantly, both patients displayed surges of functional and directed connectivity at multiple frequency bands within the posterior cortical "hot zone," a region postulated to be critical for conscious processing. This gamma activity was stimulated by global hypoxia and surged further as cardiac conditions deteriorated in the dying patients. These data demonstrate that the surge of gamma power and connectivity observed in animal models of cardiac arrest can be observed in select patients during the process of dying.

LncRNA DCRT Protects Against Dilated Cardiomyopathy by Preventing NDUFS2 Alternative Splicing by Binding to PTBP1.

BACKGROUND: Dilated cardiomyopathy is characterized by left ventricular dilation and continuous systolic dysfunction. Mitochondrial impairment is critical in dilated cardiomyopathy; however, the underlying mechanisms remain unclear. Here, we explored the cardioprotective role of a heart-enriched long noncoding RNA, the dilated cardiomyopathy repressive transcript (DCRT), in maintaining mitochondrial function. METHODS: The DCRT knockout (DCRT-/-) mice and DCRT knockout cells were developed using CRISPR-Cas9 technology. Cardiac-specific DCRT transgenic mice were generated using α-myosin heavy chain promoter. Chromatin coimmunoprecipitation, RNA immunoprecipitation, Western blot, and isoform sequencing were performed to investigate the underlying mechanisms. RESULTS: We found that the long noncoding RNA DCRT was highly enriched in the normal heart tissues and that its expression was significantly downregulated in the myocardium of patients with dilated cardiomyopathy. DCRT-/- mice spontaneously developed cardiac dysfunction and enlargement with mitochondrial impairment. DCRT transgene or overexpression with the recombinant adeno-associated virus system in mice attenuated cardiac dysfunction induced by transverse aortic constriction treatment. Mechanistically, DCRT inhibited the third exon skipping of NDUFS2 (NADH dehydrogenase ubiquinone iron-sulfur protein 2) by directly binding to PTBP1 (polypyrimidine tract binding protein 1) in the nucleus of cardiomyocytes. Skipping of the third exon of NDUFS2 induced mitochondrial dysfunction by competitively inhibiting mitochondrial complex I activity and binding to PRDX5 (peroxiredoxin 5) and suppressing its antioxidant activity. Furthermore, coenzyme Q10 partially alleviated mitochondrial dysfunction in cardiomyocytes caused by DCRT reduction. CONCLUSIONS: Our study revealed that the loss of DCRT contributed to PTBP1-mediated exon skipping of NDUFS2, thereby inducing cardiac mitochondrial dysfunction during dilated cardiomyopathy development, which could be partially treated with coenzyme Q10 supplementation.

OPUS-Fold3: a gradient-based protein all-atom folding and docking framework on TensorFlow.

For refining and designing protein structures, it is essential to have an efficient protein folding and docking framework that generates a protein 3D structure based on given constraints. In this study, we introduce OPUS-Fold3 as a gradient-based, all-atom protein folding and docking framework, which accurately generates 3D protein structures in compliance with specified constraints, such as a potential function as long as it can be expressed as a function of positions of heavy atoms. Our tests show that, for example, OPUS-Fold3 achieves performance comparable to pyRosetta in backbone folding and significantly better in side-chain modeling. Developed using Python and TensorFlow 2.4, OPUS-Fold3 is user-friendly for any source-code level modifications and can be seamlessly combined with other deep learning models, thus facilitating collaboration between the biology and AI communities. The source code of OPUS-Fold3 can be downloaded from http://github.com/OPUS-MaLab/opus_fold3. It is freely available for academic usage.

Overexpression of DUSP26 gene suppressed the proliferation, migration, and invasion of human prostate cancer cells.

Prostate cancer (PCa) is threatening the health of millions of people, the pathological mechanism of prostate cancer has not been fully elaborated, and needs to be further explored. Here, we found that the expression of DUSP26 is dramatically suppressed, and a positive connection of its expression with PCa prognosis was also observed. In vitro, overexpression of DUSP26 significantly inhibited the proliferative, migrative, and invasive capacities of PC3 cells, DUSP26 silencing presented opposite results. Tumor formation experiments in subcutaneous nude mice demonstrated that DUSP26 overexpression could significantly suppress PC3 growth in vivo. Moreover, the mechanism of DUSP26 gene and PCa was discovered by RNA-Seq analysis. We found that DUSP26 significantly inhibited MAPK signaling pathway activation, and further experiments displayed that DUSP26 could impair TAK1, p38, and JNK phosphorylation. Interestingly, treatment with the TAK1 inhibitor (iTAK1) attenuated the effect of DUSP26 on PC3 cells. Together, these results suggested that DUSP26 may serve as a novel therapeutic target for PC3 cell type PCa, the underlying mechanism may be through TAK1-JNK/p38 signaling.

Construction of a cross-species cell landscape at single-cell level.

Individual cells are basic units of life. Despite extensive efforts to characterize the cellular heterogeneity of different organisms, cross-species comparisons of landscape dynamics have not been achieved. Here, we applied single-cell RNA sequencing (scRNA-seq) to map organism-level cell landscapes at multiple life stages for mice, zebrafish and Drosophila. By integrating the comprehensive dataset of > 2.6 million single cells, we constructed a cross-species cell landscape and identified signatures and common pathways that changed throughout the life span. We identified structural inflammation and mitochondrial dysfunction as the most common hallmarks of organism aging, and found that pharmacological activation of mitochondrial metabolism alleviated aging phenotypes in mice. The cross-species cell landscape with other published datasets were stored in an integrated online portal-Cell Landscape. Our work provides a valuable resource for studying lineage development, maturation and aging.

How many cell types are there in nature? How do they change during the life cycle? These are two fundamental questions that researchers have been trying to understand in the area of biology. In this study, single-cell mRNA sequencing data were used to profile over 2.6 million individual cells from mice, zebrafish and Drosophila at different life stages, 1.3 million of which were newly collected. The comprehensive datasets allow investigators to construct a cross-species cell landscape that helps to reveal the conservation and diversity of cell taxonomies at genetic and regulatory levels. The resources in this study are assembled into a publicly available website at http://bis.zju.edu.cn/cellatlas/.

Quantum Interference and Coherent Population Trapping in a Double Quantum Dot.

Quantum interference is a natural consequence of wave-particle duality in quantum mechanics, and is widely observed at the atomic scale. One interesting manifestation of quantum interference is coherent population trapping (CPT), first proposed in three-level driven atomic systems and observed in quantum optical experiments. Here, we demonstrate CPT in a gate-defined semiconductor double quantum dot (DQD), with some unique twists as compared to the atomic systems. Specifically, we observe CPT in both driven and nondriven situations. We further show that CPT in a driven DQD could be used to generate adiabatic state transfer. Moreover, our experiment reveals a nontrivial modulation to the CPT caused by the longitudinal driving field, yielding an odd-even effect and a tunable CPT. Our results broaden the field of CPT, and open up the possibility of quantum simulation and quantum computation based on adiabatic passage in quantum dot systems.

A midposition NOTCH3 truncation in inherited cerebral small vessel disease may affect the protein interactome.

Mutations in NOTCH3 underlie cerebral autosomal dominant arteriopathy with subcortical infarcts and leukoencephalopathy (CADASIL), the most common inherited cerebral small vessel disease. Two cleavages of NOTCH3 protein, at Asp80 and Asp121, were previously described in CADASIL pathological samples. Using monoclonal antibodies developed against a NOTCH3 neoepitope, we identified a third cleavage at Asp964 between an Asp-Pro sequence. We characterized the structural requirements for proteolysis at Asp964 and the vascular distribution of the cleavage event. A proteome-wide analysis was performed to find proteins that interact with the cleavage product. Finally, we investigated the biochemical determinants of this third cleavage event. Cleavage at Asp964 was critically dependent on the proline adjacent to the aspartate residue. In addition, the cleavage product was highly enriched in CADASIL brain tissue and localized to the media of degenerating arteries, where it deposited with the two additional NOTCH3 cleavage products. Recombinant NOTCH3 terminating at Asp964 was used to probe protein microarrays. We identified multiple molecules that bound to the cleaved NOTCH3 more than to uncleaved protein, suggesting that cleavage may alter the local protein interactome within disease-affected blood vessels. The cleavage of purified NOTCH3 protein at Asp964 in vitro was activated by reducing agents and NOTCH3 protein; cleavage was inhibited by specific dicarboxylic acids, as seen with cleavage at Asp80 and Asp121. Overall, we propose homologous redox-driven Asp-Pro cleavages and alterations in protein interactions as potential mechanisms in inherited small vessel disease; similarities in protein cleavage characteristics may indicate common biochemical modulators of pathological NOTCH3 processing.

Integrated analysis of single-cell and bulk RNA sequencing data reveals prognostic characteristics of lysosome-dependent cell death-related genes in osteosarcoma.

BACKGROUND: Tumor cells exhibit a heightened susceptibility to lysosomal-dependent cell death (LCD) compared to normal cells. However, the role of LCD-related genes (LCD-RGs) in Osteosarcoma (OS) remains unelucidated. This study aimed to elucidate the role of LCD-RGs and their mechanisms in OS using several existing OS related datasets, including TCGA-OS, GSE16088, GSE14359, GSE21257 and GSE162454. RESULTS: Analysis identified a total of 8,629 DEGs1, 2,777 DEGs2 and 21 intersection genes. Importantly, two biomarkers (ATP6V0D1 and HDAC6) linked to OS prognosis were identified to establish the prognostic model. Significant differences in risk scores for OS survival were observed between high and low-risk cohorts. Additionally, scores of dendritic cells (DC), immature DCs and γδT cells differed significantly between the two risk cohorts. Cell annotations from GSE162454 encompassed eight types (myeloid cells, osteoblastic OS cells and plasma cells). ATP6V0D1 was found to be significantly over-expressed in myeloid cells and osteoclasts, while HDAC6 was under-expressed across all cell types. Moreover, single-cell trajectory mapping revealed that myeloid cells and osteoclasts differentiated first, underscoring their pivotal role in patients with OS. Furthermore, ATP6V0D1 expression progressively decreased with time. CONCLUSIONS: A new prognostic model for OS, associated with LCD-RGs, was developed and validated, offering a fresh perspective for exploring the association between LCD and OS.

Karyotype and LTR-RTs analysis provide insights into oak genomic evolution.

BACKGROUND: Whole-genome duplication and long terminal repeat retrotransposons (LTR-RTs) amplification in organisms are essential factors that affect speciation, local adaptation, and diversification of organisms. Understanding the karyotype projection and LTR-RTs amplification could contribute to untangling evolutionary history. This study compared the karyotype and LTR-RTs evolution in the genomes of eight oaks, a dominant lineage in Northern Hemisphere forests. RESULTS: Karyotype projections showed that chromosomal evolution was relatively conservative in oaks, especially on chromosomes 1 and 7. Modern oak chromosomes formed through multiple fusions, fissions, and rearrangements after an ancestral triplication event. Species-specific chromosomal rearrangements revealed fragments preserved through natural selection and adaptive evolution. A total of 441,449 full-length LTR-RTs were identified from eight oak genomes, and the number of LTR-RTs for oaks from section Cyclobalanopsis was larger than in other sections. Recent amplification of the species-specific LTR-RTs lineages resulted in significant variation in the abundance and composition of LTR-RTs among oaks. The LTR-RTs insertion suppresses gene expression, and the suppressed intensity in gene regions was larger than in promoter regions. Some centromere and rearrangement regions indicated high-density peaks of LTR/Copia and LTR/Gypsy. Different centromeric regional repeat units (32, 78, 79 bp) were detected on different Q. glauca chromosomes. CONCLUSION: Chromosome fusions and arm exchanges contribute to the formation of oak karyotypes. The composition and abundance of LTR-RTs are affected by its recent amplification. LTR-RTs random retrotransposition suppresses gene expression and is enriched in centromere and chromosomal rearrangement regions. This study provides novel insights into the evolutionary history of oak karyotypes and the organization, amplification, and function of LTR-RTs.

Ensemble species distribution modeling and multilocus phylogeography provide insight into the spatial genetic patterns and distribution dynamics of a keystone forest species, Quercus glauca.

BACKGROUND: Forests are essential for maintaining species diversity, stabilizing local and global climate, and providing ecosystem services. Exploring the impact of paleogeographic events and climate change on the genetic structure and distribution dynamics of forest keystone species could help predict responses to future climate change. In this study, we combined an ensemble species distribution model (eSDM) and multilocus phylogeography to investigate the spatial genetic patterns and distribution change of Quercus glauca Thunb, a keystone of East Asian subtropical evergreen broad-leaved forest. RESULTS: A total of 781 samples were collected from 77 populations, largely covering the natural distribution of Q. glauca. The eSDM showed that the suitable habitat experienced a significant expansion after the last glacial maximum (LGM) but will recede in the future under a general climate warming scenario. The distribution centroid will migrate toward the northeast as the climate warms. Using nuclear SSR data, two distinct lineages split between east and west were detected. Within-group genetic differentiation was higher in the West than in the East. Based on the identified 58 haplotypes, no clear phylogeographic structure was found. Populations in the Nanling Mountains, Wuyi Mountains, and the southwest region were found to have high genetic diversity. CONCLUSIONS: A significant negative correlation between habitat stability and heterozygosity might be explained by the mixing of different lineages in the expansion region after LGM and/or hybridization between Q. glauca and closely related species. The Nanling Mountains may be important for organisms as a dispersal corridor in the west-east direction and as a refugium during the glacial period. This study provided new insights into spatial genetic patterns and distribution dynamics of Q. glauca.

Enabling Gradient-Structured Solid Electrolyte Interphase by a Hydrated Eutectic Electrolyte for High-Performance Zn Metal Batteries.

Aqueous Zn metal batteries are attracting tremendous interest as promising energy storage systems due to their intrinsic safety and cost-effectiveness. Nevertheless, the reversibility of Zn metal anodes (ZMAs) is hindered by water-induced parasitic reactions and dendrite growth. Herein, a novel hydrated eutectic electrolyte (HEE) consisting of Zn(BF4)2·xH2O and sulfolane (SL) is developed to prevent the side reactions and achieve the outstanding cyclability of ZMAs. The strong coordination between Zn2+ and SL triggers the eutectic feature, enabling the low-temperature availability of HEEs. The restriction of BF4 - hydrolysis in the eutectic system can realize favorable compatibility between Zn(BF4)2-based electrolyte and ZMAs. Besides, the newly-established solvation structure with the participation of SL, H2O, and BF4 -, can induce in situ formation of desirable SEI with gradient structure consisting of B,O-rich species, ZnS, and ZnF2, to offer satisfactory protection toward ZMAs. Consequently, the HEE allows the Zn||Zn symmetric cell to cycle over 1650 h at 2 mA cm-2 and 1 mA h cm-2. Moreover, the Zn||NH4V4O10 full batteries can deliver a prolonged lifespan for 1000 cycles with a high capacity retention of 83.4%. This work represents a feasible approach toward the elaborate design of advanced electrolyte systems for next-generation batteries.

A new modular framework for high-level application development at HEPS.

As a representative of the fourth-generation light sources, the High Energy Photon Source (HEPS) in Beijing, China, utilizes a multi-bend achromat lattice to obtain an approximately 100 times emittance reduction compared with third-generation light sources. New technologies bring new challenges to operate the storage ring. In order to meet the beam commissioning requirements of HEPS, a new framework for the development of high-level applications (HLAs) has been created. The key part of the new framework is a dual-layer physical module to facilitate the seamless fusion of physical simulation models with the real machine, allowing for fast switching between different simulation models to accommodate the various simulation scenarios. As a framework designed for development of physical applications, all variables are based on physical quantities. This allows physicists to analytically assess measurement parameters and optimize machine parameters in a more intuitive manner. To enhance both extensibility and adaptability, a modular design strategy is utilized, partitioning the entire framework into discrete modules in alignment with the requirements of HLA development. This strategy not only facilitates the independent development of each module but also minimizes inter-module coupling, thereby simplifying the maintenance and expansion of the entire framework. To simplify the development complexity, the design of the new framework is implemented using Python and is called Python-based Accelerator Physics Application Set (Pyapas). Taking advantage of Python's flexibility and robust library support, we are able to develop and iterate quickly, while also allowing for seamless integration with other scientific computing applications. HLAs for both the HEPS linac and booster have been successfully developed. During the beam commissioning process at the linac, Pyapas's ease of use and reliability have significantly reduced the time required for the beam commissioning operators. As a development framework for HLA designed for the new-generation light sources, Pyapas has the versatility to be employed with HEPS, as well as with other comparable light sources, due to its adaptability.

OPUS-Rota4: a gradient-based protein side-chain modeling framework assisted by deep learning-based predictors.

Accurate protein side-chain modeling is crucial for protein folding and protein design. In the past decades, many successful methods have been proposed to address this issue. However, most of them depend on the discrete samples from the rotamer library, which may have limitations on their accuracies and usages. In this study, we report an open-source toolkit for protein side-chain modeling, named OPUS-Rota4. It consists of three modules: OPUS-RotaNN2, which predicts protein side-chain dihedral angles; OPUS-RotaCM, which measures the distance and orientation information between the side chain of different residue pairs and OPUS-Fold2, which applies the constraints derived from the first two modules to guide side-chain modeling. OPUS-Rota4 adopts the dihedral angles predicted by OPUS-RotaNN2 as its initial states, and uses OPUS-Fold2 to refine the side-chain conformation with the side-chain contact map constraints derived from OPUS-RotaCM. Therefore, we convert the side-chain modeling problem into a side-chain contact map prediction problem. OPUS-Fold2 is written in Python and TensorFlow2.4, which is user-friendly to include other differentiable energy terms. OPUS-Rota4 also provides a platform in which the side-chain conformation can be dynamically adjusted under the influence of other processes. We apply OPUS-Rota4 on 15 FM predictions submitted by AlphaFold2 on CASP14, the results show that the side chains modeled by OPUS-Rota4 are closer to their native counterparts than those predicted by AlphaFold2 (e.g. the residue-wise RMSD for all residues and core residues are 0.588 and 0.472 for AlphaFold2, and 0.535 and 0.407 for OPUS-Rota4).

Studying protein-protein interaction through side-chain modeling method OPUS-Mut.

Protein side chains are vitally important to many biological processes such as protein-protein interaction. In this study, we evaluate the performance of our previous released side-chain modeling method OPUS-Mut, together with some other methods, on three oligomer datasets, CASP14 (11), CAMEO-Homo (65) and CAMEO-Hetero (21). The results show that OPUS-Mut outperforms other methods measured by all residues or by the interfacial residues. We also demonstrate our method on evaluating protein-protein docking pose on a dataset Oligomer-Dock (75) created using the top 10 predictions from ZDOCK 3.0.2. Our scoring function correctly identifies the native pose as the top-1 in 45 out of 75 targets. Different from traditional scoring functions, our method is based on the overall side-chain packing favorableness in accordance with the local packing environment. It emphasizes the significance of side chains and provides a new and effective scoring term for studying protein-protein interaction.

TRIM6 facilitates SARS-CoV-2 proliferation by catalyzing the K29-typed ubiquitination of NP to enhance the ability to bind viral genomes.

The Nucleocapsid Protein (NP) of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is not only the core structural protein required for viral packaging, but also participates in the regulation of viral replication, and its post-translational modifications such as phosphorylation have been shown to be an important strategy for regulating virus proliferation. Our previous work identified NP could be ubiquitinated, as confirmed by two independent studies. But the function of NP ubiquitination is currently unknown. In this study, we first pinpointed TRIM6 as the E3 ubiquitin ligase responsible for NP ubiquitination, binding to NP's CTD via its RING and B-box-CCD domains. TRIM6 promotes the K29-typed polyubiquitination of NP at K102, K347, and K361 residues, increasing its binding to viral genomic RNA. Consistently, functional experiments such as the use of the reverse genetic tool trVLP model and gene knockout of TRIM6 further confirmed that blocking the ubiquitination of NP by TRIM6 significantly inhibited the proliferation of SARS-CoV-2. Notably, the NP of coronavirus is relatively conserved, and the NP of SARS-CoV can also be ubiquitinated by TRIM6, indicating that NP could be a broad-spectrum anti-coronavirus target. These findings shed light on the intricate interaction between SARS-CoV-2 and the host, potentially opening new opportunities for COVID-19 therapeutic development.