Biology subjects

Yu, Y.

Publications and source records attributed to Yu, Y..

At least 397 records · Page 22Linked to original sources

bioRxiv2021

B.1.1.529 escapes the majority of SARS-CoV-2 neutralizing antibodies of diverse epitopes

The SARS-CoV-2 B.1.1.529 variant (Omicron) contains 15 mutations on the receptor-binding domain (RBD). How Omicron would evade RBD neutralizing antibodies (NAbs) requires immediate investigation. Here, we used high-throughput yeast display screening1,2 to determine the RBD escaping mutation profiles for 247 human anti-RBD NAbs and showed that the NAbs could be unsupervised clustered into six epitope groups (A-F), which is highly concordant with knowledge-based structural classifications3-5. Strikingly, various single mutations of Omicron could impair NAbs of different epitope groups. Specifically, NAbs in Group A-D, whose epitope overlap with ACE2-binding motif, are largely escaped by K417N, G446S, E484A, and Q493R. Group E (S309 site)6 and F (CR3022 site)7 NAbs, which often exhibit broad sarbecovirus neutralizing activity, are less affected by Omicron, but still, a subset of NAbs are escaped by G339D, N440K, and S371L. Furthermore, Omicron pseudovirus neutralization showed that single mutation tolerating NAbs could also be escaped due to multiple synergetic mutations on their epitopes. In total, over 85% of the tested NAbs are escaped by Omicron. Regarding NAb drugs, the neutralization potency of LY-CoV016/LY-CoV555, REGN10933/REGN10987, AZD1061/AZD8895, and BRII-196 were greatly reduced by Omicron, while VIR-7831 and DXP-604 still function at reduced efficacy. Together, data suggest Omicron would cause significant humoral immune evasion, while NAbs targeting the sarbecovirus conserved region remain most effective. Our results offer instructions for developing NAb drugs and vaccines against Omicron and future variants.

immunology↗

bioRxiv2021

Consequence of adjustments for demographic or clinical covariates and a recommended solution in genome-wide association studies

Genome-wide association study (GWAS) is fundamentally designed to detect disease-causing genes. To reduce spurious associations or improve statistical power, about 80% of GWASs arbitrarily adjusted for demographic or clinical covariates. However, adjustment strategies in GWASs have not achieved consistent conclusions. Given the initial aim of GWAS that is to identify the causal association between a specific causal single-nucleotide polymorphism (SNP) and disease trait, we summarized all complex relationships of the target SNP, covariate and disease trait into 15 causal diagrams according to various roles of the covariate. Following each causal diagram, we conducted a series of theoretical justifications and statistical simulations. Our results demonstrate that it is unadvisable to adjust for any demographic or clinical covariates. We illustrate our point by applying GWASs for body mass index (BMI) and breast cancer, including adjusting and non-adjusting for age and smoking status. Genetic effects and P values might vary across different strategies. Instead, adjustments for SNPs (G') should be strongly recommended when G' are in linkage disequilibrium with the target SNP, and correlated with disease trait conditional on the target SNP. Specifically, adjustment for such G' can block all the confounding paths between the target SNP and disease trait, and avoid over-adjusting for colliders or intermediaries.

bioinformatics↗

bioRxiv2021

Selective representations of texture and motion in mouse higher visual areas

Mice have a constellation of higher visual areas, but their functional specializations are unclear. Here, we used a data-driven approach to examine neuronal representations of complex visual stimuli across mouse higher visual areas, measured using large field-of-view two-photon calcium imaging. Using specialized stimuli, we found higher fidelity representations of texture in area LM, compared to area AL. Complementarily, we found higher fidelity representations of motion in area AL, compared to area LM. We also observed this segregation of information in response to naturalistic videos. Finally, we explored how popular models of visual cortical neurons could produce the segregated representations of texture and motion we observed. These selective representations could aid in behaviors such as visually guided navigation.

neuroscience↗

bioRxiv2021

Secreted ORF8 is a pathogenic cause of severe Covid-19 and potentially targetable with select NLRP3 inhibitors

COVID-19 is a significant cause of morbidity and mortality in blood cancer patients, especially those on immunosuppressive therapy. Despite extensive research, the specific factor associated with SARS-CoV-2 infection that mediates the life-threatening inflammatory cytokine response in patients with severe COVID-19 remains unidentified. Herein we demonstrate that the virus-encoded Open Reading Frame 8 (ORF8) protein is abundantly secreted as a glycoprotein in vitro and in symptomatic patients with COVID-19. ORF8 specifically binds to the NOD-like receptor family pyrin domain-containing 3 (NLRP3) in CD14+ monocytes to induce a non-canonical inflammasomal response, and a canonical response when the second activation signal is present. Levels of ORF8 protein in the blood correlate with severity and disease-specific mortality in patients with acute SARS-CoV-2 infection. Furthermore, the ORF8-induced inflammasome response was readily inhibited by the NLRP3 inhibitor MCC950 in vitro. Our study identifies a dominant cause of pathogenesis, its underlying mechanism, and a potential new treatment for severe COVID-19. Key pointsO_LISecreted glycoprotein ORF8 induces monocytic pro-inflammatory cytokines involving the activation of the NLPR3 inflammasome pathway. C_LIO_LIORF8 is prognostically present in the blood of symptomatic patients with covid-19 and is targetable with NLRP3 inhibitor MCC-950. C_LI

immunology↗

bioRxiv2021

The high-resolution structure of cell membranes revealed by in situ cryo-electron tomography

As the structural unit of life, cell is defined by the membrane system. The cell membrane separates the internal and external environment of the cell, and the endomembrane system defines the organelles to perform different functions1-3. However, lack of tools to in situ observe membrane proteins at a molecular resolution has limited our understanding of membrane organization and membrane protein interactions. Here we characterize the high-resolution 3D structure of human red blood cell (hRBC) membranes and the membrane proteins for the first time in situ by cryo-electron tomography (CryoET)4-7. By analyzing tomograms, we have obtained the first fine three-dimensional (3D) structure of hRBC membranes and found the asymmetrical distribution of membrane proteins on both sides of the membranes. We found that the membrane proteins are mainly located on the cytoplasmic side of hRBC membranes, with protein sizes ranging from 6nm to 8nm, in contrast to the ectoplasmic side with basically no proteins. Quantitative analysis of the density of hRBC membrane proteins shows that the membranes with higher protein occupancy have less phospholipid, making the membranes more rigid. Meanwhile, we obtained the channel protein-like structures by preliminary analysis of the membrane protein. Our results represent the first in situ structure characterization of the cell membranes and membrane proteins through cryoET and opens the door for understanding the biological functions of cell membranes in their physiological environments.

biophysics↗

bioRxiv2021

A target expression threshold dictates invader defense and autoimmunity by CRISPR-Cas13

Immune systems must recognize and clear foreign invaders without eliciting autoimmunity. CRISPR-Cas immune systems in prokaryotes manage this task by following two criteria: extensive guide:target complementarity and a defined target-flanking motif. Here we report an additional requirement for RNA-targeting CRISPR-Cas13 systems: expression of the target transcript exceeding a threshold. This finding is based on targeting endogenous non-essential transcripts, which rarely elicited dormancy through collateral RNA degradation. Instead, eliciting dormancy required over-expressing targeted transcripts above a threshold. A genome-wide screen confirmed target expression levels as the principal determinant of cytotoxic autoimmunity and revealed that the threshold shifts with the guide:target pair. This expression threshold ensured defense against a lytic bacteriophage yet allowed tolerance of a targeted beneficial gene expressed from an invading plasmid. These findings establish target expression levels as a third criterion for immune activation by RNA-targeting CRISPR-Cas systems, buffering against autoimmunity and distinguishing pathogenic and benign invaders. HIGHLIGHTSO_LICas13-induced dormancy requires RNA target levels to exceed an expression threshold C_LIO_LIThe expression threshold can prevent cytotoxic self-targeting for endogenous transcripts C_LIO_LIThe threshold shifts depending on the CRISPR RNA guide:target pair C_LIO_LIThe threshold allows cells to distinguish pathogenic and benign infections C_LI

molecular biology↗

bioRxiv2021

CyanoHABs: inevitable evolutionary ecological consequence for low nutrient-requiring cyanobacteria in water eutrophication

Cyanobacterial harmful algal blooms (CyanoHABs) arise as cyanobacteria dominate phytoplankton communities when nutrient levels increase from oligotrophic state. From a wholistic perspective, this longstanding altered phytoplankton structure results from two conditions: one sufficient condition that cyanobacteria can grow maximally with elevated nutrients; one necessary condition that co-living algae cannot grow fast or dominate at the same levels. The sufficient condition, the special mechanism of CyanoHABs at the population level, has been established as the synergistic interaction between superior cyanobacterial ecophysiology and elevated nutrients. But it is unknown how these functions arise or whether they are under directed evolution to water eutrophication. The necessary condition, the general mechanism of CyanoHABs at the community level, is little understood: why co-living algae cannot form blooms as cyanobacteria? Literature and bioinformatics analyses show that the superior ecophysiology undergoes no directed positive evolution to worldwide eutrophication in general or any local eutrophic waters in particular; instead, these functions are under strong purifying selection and likely acquired through early adaptive radiation in nutrient-deficient conditions, as functions enabling extant cyanobacteria to occupy other niches. The general mechanism turns out to be quite straightforward: cyanobacteria are simple life forms and thus have lower per capita nutrient demand for growth, compared to co-existing eukaryotic algae in cell size and structure, genome size, size of genome-scale metabolic networks, cell content, nutrient requirement. Lower nutrient demand is proved by existing field nutrient supplementation. Both the special and general mechanisms of CyanoHABs are tentative frameworks awaiting further theoretic improvement and empirical assessment.

evolutionary biology↗

bioRxiv2021

Inhibition of SAR S-CoV-2 infection and replication by lactoferrin, MUC1 and α-lactalbumin identified in human breastmilk

The global pandemic of COVID-19 caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) infection confers great threat to the public health. Human breastmilk is an extremely complex with nutritional composition to nourish infants and protect them from different kinds of infection diseases and also SARS-CoV-2 infection. Previous studies have found that breastmilk exhibited potent antiviral activity against SARS-CoV-2 infection. However, it is still unknown which component(s) in the breastmilk is responsible for its antiviral activity. Here, we identified Lactoferrin (LF), MUC1 and -Lactalbumin (-LA) from human breastmilk by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and in vitro confirmation that inhibited SARS-CoV-2 infection and analyzed their antiviral activity using the SARS-CoV-2 pseudovirus system and transcription and replication-competent SARS-CoV-2 virus-like-particles (trVLP) in the Huh7.5, Vero E6 and Caco-2-N cell lines. Additionally, we found that LF and MUC1 could inhibit viral attachment, entry and post-entry replication, while -LA just inhibit viral attachment and entry. Importantly, LF, MUC1 and -LA possess potent antiviral activities towards not only wild-type but also variants such as B.1.1.7 (alpha), B.1.351 (beta), P.1 (gamma) and B.1.617.1 (kappa). Moreover, LF from other species (e.g., bovine and goat) is still capable of blocking viral attachment to cellular heparan sulfate. Taken together, our study provided the first line of evidence that human breastmilk components (LF, MUC1 and -LA) are promising therapeutic candidates warranting further development or treatingVID-19 given their exceedingly safety levels.

microbiology↗

bioRxiv2021

Extracellular loop 2 of G protein-coupled olfactory receptors is critical for odorant recognition

G protein-coupled olfactory receptors (ORs) enable us to detect innumerous odorants. They are also ectopically expressed, emerging as attractive drug targets. ORs can be promiscuous or highly specific, which is part of Natures strategy for odor discrimination. This work demonstrates that the extracellular loop 2 (ECL2) plays critical roles in OR promiscuity and specificity. Using site-directed mutagenesis and molecular modeling, we constructed 3D OR models in which ECL2 forms a lid of the orthosteric pocket. ECL2 controls the shape and the volume of the odorant-binding pocket, maintains the pocket hydrophobicity and acts as a gatekeeper of odorant binding. The interplay between the specific orthosteric pocket and the variable, less specific ECL2 controls OR specificity and promiscuity. The 3D models enabled virtual screening of new OR agonists and antagonists, exhibiting 78% hit rate in cell assays. This approach can be generalized to structure-based ligand screening for other GPCRs that lack high-resolution 3D structures.

molecular biology↗

bioRxiv2021

Spatially-resolved transcriptomics analyses of invasive fronts in solid tumors

Solid tumors are complex ecosystems, and heterogeneity is the major challenge for overcoming tumor relapse and metastasis. Uncovering the spatial heterogeneity of cell types and functional states in tumors is essential for developing effective treatment, especially in invasive fronts of tumor, the most active region for tumor cells infiltration and invasion. We firstly used SpaTial Enhanced REsolution Omics-sequencing (Stereo-seq) with a nanoscale resolution to characterize the tumor microenvironment of intrahepatic cholangiocarcinoma (ICC). Enrichment of distinctive immune cells, suppressive immune microenvironment and metabolic reprogramming of tumor cells were identified in the 500{micro}m-wide zone centered bilaterally on the tumor boundary, namely invasive fronts of tumor. Furthermore, we found the damaged states of hepatocytes with overexpression of Serum Amyloid A (SAA) in invasive fronts, recruiting macrophages for facilitating further tumor invasion, and thus resulting in a worse prognosis. We also confirmed these findings in hepatocellular carcinoma and other liver metastatic cancers. Our work highlights the remarkable potential of high-resolution-spatially resolved transcriptomic approaches to provide meaningful biological insights for comprehensively dissecting the tumor ecosystem and guiding the development of novel therapeutic strategies for solid tumors.

cancer biology↗

bioRxiv2021

Genetic and environmental influences on the evolution of virulence in the HIV-associated opportunistic human fungal pathogen Cryptococcus neoformans

The fungus Cryptococcus neoformans is considered the leading cause of death in immunocompromised patients. Despite numerous investigations concerning its molecular epidemiology, there are only a few studies addressing the impacts of varying factors on genotype-phenotype correlations. It remains largely unknown whether genetic and environmental variabilities among isolates from different sources may have dramatic consequences on virulence. In this study, we analyzed 105 Chinese C. neoformans isolates, including 54 from HIV-infected patients, 44 from HIV-uninfected individuals and 7 from a natural environment, to investigate factors influencing the outcome of C. neoformans infection. MLST analysis clearly identified sequence type (ST) 5 as the prevalent sequence type in all clinical isolates and interestingly, genotypic diversities were observed in isolates from both HIV-uninfected individual and natural environment but not those from HIV-infected patients. Moreover, we found that compared to those from HIV-infected patients, the isolates from HIV-uninfected individuals exhibited enhanced virulence-associated traits including significantly elevated capsule production and melanin formation, increases in survival in human cerebrospinal fluid (CSF), less effective uptake by host phagocytes, and higher mortality in a mouse model of cryptococcosis. Consistently, pathogenic phenotypes were associated with CD4 counts of patients, implying environmental impact on within-host C. neoformans virulence. Importantly, a large-scale whole-genome sequencing analysis revealed that genomic variations within genes related to specific functions may act as a vital driving force of host intrinsic virulence evolution. Taken together, our results support a strong genotype-phenotype correlation suggesting that the pathogenic evolution of C. neoformans could be heavily affected by both genetic and environmental factors.

genetics↗

bioRxiv2021

The adenosine analogue prodrug ATV006 is orally bioavailable and has potent preclinical efficacy against SARS-CoV-2 and its variants

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which causes the COVID-19 pandemic, is rapidly evolving. Due to the limited efficacy of vaccination in prevention of SARS-CoV-2 transmission and continuous emergence of variants of concern (VOC), including the currently most prevalent Delta variant, orally bioavailable and broadly efficacious antiviral drugs are urgently needed. Previously we showed that adenosine analogue 69-0 (also known as GS-441524), possesses potent anti-SARS-CoV-2 activity. Herein, we report that esterification of the 5-hydroxyl moieties of 69-0 markedly improved the antiviral potency. The 5-hydroxyl-isobutyryl prodrug, ATV006, showed excellent oral bioavailability in rats and cynomolgus monkeys and potent antiviral efficacy against different VOCs of SARS-CoV-2 in cell culture and three mouse models. Oral administration of ATV006 significantly reduced viral loads, alleviated lung damage and rescued mice from death in the K18-hACE2 mouse model challenged with the Delta variant. Moreover, ATV006 showed broad antiviral efficacy against different mammal-infecting coronaviruses. These indicate that ATV006 represents a promising oral drug candidate against SARS-CoV-2 VOCs and other coronaviruses.

microbiology↗

bioRxiv2021

Pleiotropic and Non-redundant Effects of an Auxin Importer in Setaria and Maize

Directional transport of auxin is critical for inflorescence and floral development in flowering plants, but the role of auxin influx carriers (AUX1 proteins) has been largely overlooked. Taking advantage of available AUX1 mutants in Setaria viridis and maize, we uncover previously unreported aspects of plant development that are affected by auxin influx, including higher order branches in the inflorescence, stigma branch number, and glume (floral bract) development, and plant fertility. However, disruption of auxin flux does not affect all parts of the plant, with little obvious effect on inflorescence meristem size, time to flowering, and anther morphology. In double mutant studies in maize, disruptions of ZmAUX1 also affect vegetative development. A GFP-tagged construct of SvAUX1 under its native promoter showed that the AUX1 protein localizes to the plasma membrane of outer tissue layers in both roots and inflorescences, and accumulates specifically in inflorescence branch meristems, consistent with the mutant phenotype and expected auxin maxima. RNA-seq analysis finds that most gene expression modules are conserved between mutant and wildtype plants, with only a few hundred genes differentially expressed in spp1 inflorescences. Using CRISPR-Cas9 technology, we disrupted SPP1 and the other four AUX1 homologs in S. viridis. SvAUX1/SPP1 has a larger effect on inflorescence development than the others, although all contribute to plant height, tiller formation, leaf, and root development. The AUX1 importers are thus not fully redundant in S. viridis. Our detailed phenotypic characterization plus a stable GFP-tagged line offer tools for future dissection of the function of auxin influx proteins. One sentence summaryMutations in a single auxin importer gene Spp1/SvAUX1 uncover broad and unexpected effects in nearly all aspects of the development of shoots, inflorescences, and flowers.

plant biology↗

bioRxiv2021

Early evolution of beetles regulated by the end-Permian deforestation

The end-Permian mass extinction (EPME) led to a severe terrestrial ecosystem collapse. However, the ecological response of insects--the most diverse group of organisms on Earth--to the EPME remains poorly understood. Here, we analyse beetle evolutionary history based on taxonomic diversity, morphological disparity, phylogeny, and ecological shifts from the Early Permian to Middle Triassic, using a comprehensive new data set. Permian beetles were dominated by xylophagous stem groups with a high diversity and disparity, which probably played an underappreciated role in the Permian carbon cycle. Our suite of analyses shows that Permian xylophagous beetles suffered a severe extinction during the EPME largely due to the collapse of forest ecosystems, resulting in an Early Triassic gap of xylophagous beetles. New xylophagous beetles appeared widely in the early Middle Triassic, which is consistent with the restoration of forest ecosystems. Our results highlight the ecological significance of insects in deep-time terrestrial ecosystems.

paleontology↗

bioRxiv2021

PharmacoDB 2.0 : Improving scalability and transparency of in vitro pharmacogenomics analysis

Cancer pharmacogenomics studies provide valuable insights into disease progression and associations between genomic features and drug response. PharmacoDB integrates multiple cancer pharmacogenomics datasets profiling approved and investigational drugs across cell lines from diverse tissue types. The web-application enables users to efficiently navigate across datasets, view and compare drug dose-response data for a specific drug-cell line pair. In the new version of PharmacoDB (version 2.0, https://pharmacodb.ca/), we present: (i) new datasets such as NCI-60, the Profiling Relative Inhibition Simultaneously in Mixtures (PRISM) dataset, as well as updated data from the Genomics of Drug Sensitivity in Cancer (GDSC) and the Genentech Cell Line Screening Initiative (gCSI); (ii) implementation of FAIR data pipelines using ORCESTRA and PharmacoDI; (iii) enhancements to drug response analysis such as tissue distribution of dose-response metrics and biomarker analysis; (iv) improved connectivity to drug and cell line databases in the community. The web interface has been rewritten using a modern technology stack to ensure scalability and standardization to accommodate growing pharmacogenomics datasets. PharmacoDB 2.0 is a valuable tool for mining pharmacogenomics datasets, comparing and assessing drug response phenotypes of cancer models. HIGHLIGHTSO_LIPharmacoDB 2.0 includes new and updated large pharmacogenomic datasets. The data processing for PharmacoDB is made fully reproducible through the use of the ORCESTRA platform and automated data ingestion pipelines C_LIO_LIThe new release contains enriched annotations for drugs and cell lines via connectivity to external databases, as well as new analytical methods for tissue-specific and pan-cancer biomarker discovery C_LIO_LIThe new version of PharmacoDB incorporates a scalable and reproducible framework that can accelerate the implementation of analytical pipelines including machine learning/AI for biomarker discovery in the future C_LI

bioinformatics↗

bioRxiv2021

Regional Cell Atlas of Human Intestine Shapes Distinct Immune Surveillance

Regional intestinal immune surveillance remains obscure. In this study, we integrated single-cell RNA sequencing and spatial transcriptomics to create a regional atlas of fetal and adult intestines, consisting of 59 cell subsets, of which eight new subsets and ILCs transition states were identified. Results revealed that microenvironment determines in-situ cell differentiation and shapes the regional molecular characteristics, allowing different intestinal segments with diverse functions. We characterized the regional expression of mucins, immunoglobulins, and antimicrobial peptides (AMPs) and their shift during development and in inflammatory bowel disease. Notably, -defensins expressed most abundantly in small intestinal LGR5+ stem cells, rather than in Paneth cells, and down-regulated as cell maturing. Common upstream transcription factors controlled the AMPs expression, illuminating the concurrent change of AMPs during epithelial differentiation, and the spatial co-expression patterns. We demonstrated the correspondence of cell focus of risk genes to diseases location susceptibility and identified distinct cell-cell crosstalk and spatial heterogeneity of immune cell homing in different gut segments. Overall, a cross-spatiotemporal approach to transcriptomes at single-cell resolution revealed that the regional milieu of the human intestine determined cellular and molecular cues of immune surveillance, dictating gut homeostasis and disease.

cell biology↗

bioRxiv2021

The gut microbial signature of gestational diabetes mellitus and the association with diet intervention

Gestational diabetes mellitus (GDM) is a high-risk pregnancy complication that is associated with metabolic disorder phenotypes, such as abnormal blood glucose and obesity. The link between microbiota and diet management contributes to metabolic homeostasis in GDM. Therefore, it is crucial to understand the structure of the gut microbiota in GDM and to explore the effect of dietary management on the microbiota structure. In this study, we analyzed the composition of the gut microbiota between 27 GDM and 30 healthy subjects at two time points using Illumina HiSeq 2500 platform. The taxonomy analyses suggested that the overall bacteria clustered by diabetes status, rather than diet intervention. Of particular interest, the phylum Acidobacteria in GDM was significantly increased, and positively correlated with blood glucose levels. Moreover, Partial least-squares discriminant analysis (PLS-DA) revealed that certain genera in the phyla Firmicutes, Bacteroidetes, Proteobacteria, and Lentisphaerae characterized the GDM gut microbiota. Correlation analysis indicated that blood glucose levels and BMI index were correlated with the relative abundance of SCFAS-producing genera. Through the comparison between the GDM and healthy samples with or without diet intervention, we discovered that the role of short-term diet management in GDM processes is associated with the change in the Firmicutes/Bacteroidetes ratio and some specific taxa, rather than an alternative gut microbial pattern. Our study have important implications for understanding the beneficial effects of diet intervention on the specific gut microbiota and thus possibly their metabolism in pregnant women with GDM. ImportanceUnderstanding the composition and dynamics of the gut microbiota in GDM women under diet intervention is important because there may be opportunities for preventive strategies. We examined the relationships between GDM gut microbiota at two times before and after the diet intervention during second trimester of pregnancy and clinical characteristics in cohort of GDM women. We found that short-term diet management in GDM processes is associated with changes in the Firmicutes/Bacteroidetes ratio and some specific taxa rather than an alternative gut microbial pattern. Our study highlights the importance of considering diet intervention as the rescue of microbial dysfunction of GDM disease and can serve as a strategy for early prevention in future study.

microbiology↗

bioRxiv2021

Both Simulation and Sequencing Data Reveal Multiple SARS-CoV-2 Variants Coinfection in COVID-19 Pandemic

SARS-CoV-2 is a single-stranded RNA betacoronavirus with a high mutation rate. The rapidly emerged SARS-CoV-2 variants could increase the transmissibility, aggravate the severity, and even fade the vaccine protection. Although the coinfections of SARS-CoV-2 with other respiratory pathogens have been reported, whether multiple SARS-CoV-2 variants coinfection exists remains controversial. This study collected 12,986 and 4,113 SARS-CoV-2 genomes from the GISAID database on May 11, 2020 (GISAID20May11) and April 1, 2021 (GISAID21Apr1), respectively. With the single-nucleotide variants (SNV) and network clique analysis, we constructed the single-nucleotide polymorphism (SNP) coexistence networks and noted the SNP number of the maximal clique as the coinfection index. The coinfection indices of GISAID20May11 and GISAID21Apr1 datasets were 16 and 34, respectively. Simulating the transmission routes and the mutation accumulations, we discovered the linear relationship between the coinfection index and the coinfected variant number. Based on the linear relationship, we deduced that the COVID-19 cases in the GISAID20May11 and GISAID21Apr1 datasets were coinfected with 2.20 and 3.42 SARS-CoV-2 variants on average. Additionally, we performed Nanopore sequencing on 42 COVID-19 patients to explore the virus mutational characteristics. We found the heterozygous SNPs in 41 COVID-19 cases, which support the coinfection of SARS-CoV-2 variants and challenge the accuracy of phylogenetic analysis. In conclusion, our findings reported the coinfection of SARS-CoV-2 variants in COVID-19 patients, demonstrated the increased coinfected variants number in the epidemic, and provided clues for the prolonged viral shedding and severe symptoms in some cases.

bioinformatics↗