Cross-platform comparison of highly-sensitive immunoassays for inflammatory markers in a COVID-19 cohort (preprint)

A variety of commercial platforms are available for the simultaneous detection of multiple cytokines and associated proteins, often employing antibody pairs to capture and detect target proteins. In this study, we comprehensively evaluated the performance of three distinct platforms: the fluorescent bead-based Luminex assay, the proximity extension-based Olink assay, and a novel proximity ligation assay platform known as Alamar NULISAseq. These assessments were conducted on serum samples from the NIH IMPACC study, with a focus on three essential performance metrics: detectability, correlation, and differential expression. Our results reveal several key findings. Firstly, the Alamar platform demonstrated the highest overall detectability, followed by Olink and then Luminex. Secondly, the correlation of protein measurements between the Alamar and Olink platforms tended to be stronger than the correlation of either of these platforms with Luminex. Thirdly, we observed that detectability differences across the platforms often translated to differences in differential expression findings, although high detectability did not guarantee the ability to identify meaningful biological differences. Our study provides valuable insights into the comparative performance of these assays, enhancing our understanding of their strengths and limitations when assessing complex biological samples, as exemplified by the sera from this COVID-19 cohort.

NULISA: a novel proteomic liquid biopsy platform with attomolar sensitivity and high multiplexing (preprint)

The blood proteome holds great promise for precision medicine but poses daunting challenges due to the low abundance of the majority of plasma proteins and the vast dynamic range across the proteome. We report the development and validation of a novel proteomic analysis technology - NUcleic acid Linked Immuno-Sandwich Assay (NULISA) - that incorporates a dual capture and release mechanism to suppress the assay background to the minimum, thus drastically improving the signal-to-noise ratio. NULISA improves the sensitivity of the proximity ligation assay by over 10,000-fold to the attomolar level, which is enabled by antibody-conjugated DNA sequences that mediate the purification of immunocomplexes and contain target- and sample-specific barcodes for next-generation sequencing-based, highly multiplexed analysis. To demonstrate its performance and utility, we developed a 200-plex NULISA targeting 124 cytokines and chemokines and 80 other immune response-related proteins that demonstrated superior sensitivity for detecting low-abundance proteins and high concordance with other immunoassays. The ultra-high sensitivity enabled the detection of previously difficult-to-detect but biologically important, low-abundance biomarkers in patients with autoimmune diseases and COVID-19. Fully automated NULISA uniquely addresses longstanding challenges in the proteomic analysis of liquid biopsy samples and makes broad and in-depth proteomic analysis accessible to the general research community and future diagnostic applications.

Chest computed tomography findings of the Omicron variants of SARS-CoV-2 with different cycle threshold values.

BACKGROUND: The Omicron variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) mainly infects the upper respiratory tract. This study aimed to determine whether the probability of pulmonary infection and the cycle threshold (Ct) measured using the fluorescent polymerase chain reaction (PCR) method were related to pulmonary infections diagnosed via computed tomography (CT). AIM: To analyze the chest CT signs of SARS-CoV-2 Omicron variant infections with different Ct values, as determined via PCR. METHODS: The chest CT images and PCR Ct values of 331 patients with SARS-CoV-2 Omicron variant infections were retrospectively collected and categorized into low (< 25), medium (25.00-34.99), and high (≥ 35) Ct groups. The characteristics of chest CT images in each group were statistically analyzed. RESULTS: The PCR Ct values ranged from 13.36 to 39.81, with 99 patients in the low, 155 in the medium, and 77 in the high Ct groups. Six abnormal chest CT signs were detected, namely, focal infection, patchy consolidation shadows, patchy ground-glass shadows, mixed consolidation ground-glass shadows, subpleural interstitial changes, and pleural changes. Focal infections were less frequent in the low Ct group than in the medium and high Ct groups; these infections were the most common sign in the medium and high Ct groups. Patchy consolidation shadows and pleural changes were more frequent in the low Ct group than in the other two groups. The number of patients with two or more signs was greater in the low Ct group than in the medium and high Ct groups. CONCLUSION: The chest CT signs of patients with pulmonary infection caused by the Omicron variants of SARS-CoV-2 varied depending on the Ct values. Identification of the characteristics of Omicron variant infection can help subsequent planning of clinical treatment.

Uncovering novel disinfection mechanisms of solar light/periodate system: The dominance of singlet oxygen and metabolomic insights

Disinfection plays an essential role in waterborne pathogen control and disease prevention, especially during the COVID-19 pandemic. Catalyst-free solar light/periodate (PI) system has recently presented great potential in water disinfection, whereas the in-depth chemical and microbiological mechanisms for efficient bacterial inactivation remain unclear. Our work delineated firstly the critical role of singlet oxygen, instead of reported hydroxyl radicals and superoxide radicals, in dominating bacterial inactivation by the PI/simulated sunlight (SSL) system. Multi-evidence demonstrated the prominent disinfection performance of this system for Staphylococcus aureus in terms of culturability (> 6 logs CFU), cellular integrity, and metabolic activity. Particularly, the excellent intracellular DNA removal (> 95%) indicated that PI/SSL system may function as a selective disinfection strategy to diminish bacterial culturability without damaging the cell membrane. The PI/SSL system could also effectively inhibit bacterial regrowth for > 5 days and horizontal gene transfer between E. coli genera. Nontargeted metabolomic analysis suggested that PI/SSL system inactivated bacteria by triggering the accumulation of intracellular reactive oxygen species and the depletion of reduced glutathione. Additionally, the PI/SSL system could accomplish simultaneous micropollutant removal and bacterial inactivation, suggesting its versatility in water decontamination. Overall, this study deciphers more comprehensive antibacterial mechanisms of this environmentally friendly disinfection system, facilitating the technical development and application of the selective disinfection strategy in environmental pathogen control. [Display omitted] • PI/SSL system selectively inactivates cells by targeting intracellular DNA first. • PI/SSL treatment inhibits bacterial regrowth and horizontal gene transfer potential. • The bactericidal effect of 1O 2 in PI/SSL system was proposed for the first time. • Metabolomics showed that ROS accumulation is one of the antibacterial mechanisms. • PI/SSL system holds great promise in decontamination of the actual water system. [ FROM AUTHOR]

Reciprocal Effect between Depressive Symptoms and Adolescent Non-suicidal self-injury before and after COVID-19: A Longitudinal Study (preprint)

Background Non-suicidal   self-injury (NSSI) is a common psychological and behavioral problem among   adolescents and has now become a major public health problem for adolescents.   Since the COVID-19 outbreak in 2019, it has caused various mental health   problems, such as anxiety, depression, and mental burnout, contributing to a   severe mental health crisis globally. Thus far, a few studies recorded the   temporal change in adolescents’ psychological status during the COVID-19   pandemic as well as that with the implementation of large-scale public health   intervention methods, and this study adds to the evidence. Methods Based on   the Chengdu Positive Child Development (CPCD) survey, the baseline dataset   was collected in December 2019, and the first follow-up of the CPCD was conducted   in July 2020. A total of 6,023 adolescents aged 10-19 were recruited from   five primary and middle schools. Two independent autoregressive cross-lagged   models were used to test the bidirectional relationship between NSSI and   depressive symptoms in adolescents; logistic regression analysis was used to   explore the predictors of NSSI implementation in adolescents with depressive   symptoms, which could provide an entry point for behavioral interventions to   NSSI. Results The   prevalence of depressive symptoms among our participants was 32.69% at   baseline, and 34.27% at follow-up. The occurrence rate of NSSI in adolescents   who may have depressive symptoms was 44.34%%, and that during the pandemic   was 53.44%. The difference was statistically significant (P <   0.05). The results of the binary logistic analysis showed that among   adolescents, gender, duration of the online class, depression mood, place of   residence, and self-perception of relationship with caregivers were the risk   factors for NSSI (or > 1, β> 0), and daily sleep hours positive mood   was the protective factor (or < 1, β< 0).  The lag effect of adolescent depression on   their NSSI behavior is significant, which means that based on controlling the   adolescent baseline NSSI, the deeper the adolescent depression degree, the   more frequent their NSSI behavior (β=0.26, P<0.01). At the same time,   adolescents' NSSI behavior also had a lagging effect on depressive symptoms,   and adolescents with self-injury behavior were more likely to be depressed (β=0.02, P<0.01). Depression and   NSSI are mutual(β=0.77,   P<0.05；β=0.27,   P<0.01). Conclusions The   increased depressive symptoms among adolescents exacerbated their NSSI   behaviors and hurt their mental health during COVID-19. Screening for   depression should be carried out early to serve as a warning sign in   preventing and reducing NSSI in adolescents.

A swarm-optimizer-assisted simulation and prediction model for emerging infectious diseases based on SEIR.

Mechanism-driven models based on transmission dynamics and statistic models driven by public health data are two main methods for simulating and predicting emerging infectious diseases. In this paper, we intend to combine these two methods to develop a more comprehensive model for the simulation and prediction of emerging infectious diseases. First, we combine a standard epidemic dynamic, the susceptible-exposed-infected-recovered (SEIR) model with population migration. This model can provide a biological spread process for emerging infectious diseases. Second, to determine suitable parameters for the model, we propose a data-driven approach, in which the public health data and population migration data are assembled. Moreover, an objective function is defined to minimize the error based on these data. Third, based on the proposed model, we further develop a swarm-optimizer-assisted simulation and prediction method, which contains two modules. In the first module, we use a level-based learning swarm optimizer to optimize the parameters required in the epidemic mechanism. In the second module, the optimized parameters are used to predicate the spread of emerging infectious diseases. Finally, various experiments are conducted to validate the effectiveness of the proposed model and method.

Uncovering Novel Disinfection Mechanisms of Solar Light/Periodate System:The Dominance of Singlet Oxygen and Metabolomic Insights

Disinfection plays an essential role in waterborne pathogen control and disease prevention, especially during the COVID-19 pandemic. Catalyst-free solar light/periodate (PI) system has recently presented great potential in water disinfection, whereas the in-depth chemical and microbiological mechanisms for efficient bacterial inactivation remain unclear. Our work delineated firstly the critical role of singlet oxygen, instead of reported hydroxyl radicals and superoxide radicals, in dominating bacterial inactivation by the PI/simulated sunlight (SSL) system. Multi-evidence demonstrated the prominent disinfection performance of this system for Staphylococcus aureus in terms of culturability (> 6 logs CFU), cellular integrity, and metabolic activity. Particularly, the excellent intracellular DNA removal (> 95%) indicated that PI/SSL system may function as a selective disinfection strategy to diminish bacterial culturability without damaging the cell membrane. The PI/SSL system could also effectively inhibit bacterial regrowth for > 5 days and horizontal gene transfer between E. coli genera. Nontargeted metabolomic analysis suggested that PI/SSL system inactivated bacteria by triggering the accumulation of intracellular reactive oxygen species and the depletion of reduced glutathione. Additionally, the PI/SSL system could accomplish simultaneous micropollutant removal and bacterial inactivation, suggesting its versatility in water decontamination. Overall, this study deciphers more comprehensive antibacterial mechanisms of this environmentally friendly disinfection system, facilitating the technical development and application of the selective disinfection strategy in environmental pathogen control.

Proteomic and Metabolomic Characterization of SARS-CoV-2-Infected Cynomolgus Macaque at Early Stage.

Although tremendous effort has been exerted to elucidate the pathogenesis of severe COVID-19 cases, the detailed mechanism of moderate cases, which accounts for 90% of all patients, remains unclear yet, partly limited by lacking the biopsy tissues. Here, we established the COVID-19 infection model in cynomolgus macaques (CMs), monitored the clinical and pathological features, and analyzed underlying pathogenic mechanisms at early infection stage by performing proteomic and metabolomic profiling of lung tissues and sera samples from COVID-19 CMs models. Our data demonstrated that innate immune response, neutrophile and platelet activation were mainly dysregulated in COVID-19 CMs. The symptom of neutrophilia, lymphopenia and massive "cytokines storm", main features of severe COVID-19 patients, were greatly weakened in most of the challenged CMs, which are more semblable as moderate patients. Thus, COVID-19 model in CMs is rational to understand the pathogenesis of moderate COVID-19 and may be a candidate model to assess the safety and efficacy of therapeutics and vaccines against SARS-CoV-2 infection.

Fatality assessment and variant risk monitoring for COVID-19 using three new hospital occupancy related metrics.

BACKGROUND: Though case fatality rate (CFR) is widely used to reflect COVID-19 fatality risk, its use is limited by large temporal and spatial variation. Hospital mortality rate (HMR) is also used to assess the severity of COVID-19, but HMR data is not directly available globally. Alternative metrics are needed for COVID-19 severity and fatality assessment. METHODS: We introduce new metrics for COVID-19 fatality risk measurements/monitoring and a new mathematical model to estimate average hospital length of stay for deaths (Ldead) and discharges (Ldis). Multiple data sources were used for our analyses. FINDINGS: We propose three, new metrics: hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR), and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated Ldead and Ldis for 501,079 COVID-19 hospitalizations in 34 US states between 7 August 2020 and 1 March 2021 were 18·2(95%CI:17·9-18·5) and 14·0(95%CI:13·9-14·0) days, respectively. We found the dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant (58·6% of US new cases as of 25 December 2021) decreased 65·16% in the US as of 16 January 2022. INTERPRETATION: The new and reliable measurements described here could be useful for COVID-19 fatality risk and variant-associated risk monitoring. FUNDING: No specific funding was associated with the present study.

[Overview of Meta-analysis of Lianhua Qingwen preparations in treatment of viral diseases].

This study aims to obtain higher-level evidence by overviewing the Meta-analysis of Lianhua Qingwen preparations in the treatment of viral diseases including influenza, coronavirus disease 2019(COVID-19), and hand, foot and mouth disease(HFMD). CNKI, Wanfang, VIP, China Clinical Trial Registry(ChiCTR), PubMed, EMbase, Web of Science, and Cochrane Library were searched for the Meta-analysis about the treatment of viral diseases with Lianhua Qingwen preparations from the database establishment to April 1, 2022. After literature screening and data extraction, AMSTAR2 and the grading of recommendations assessment, development and evaluations(GRADE) system were used to assess the methodological quality and evidence quality, respectively, and then the efficacy and safety outcomes of Lianhua Qingwen preparations in the treatment of viral diseases were summarized. Thirteen Meta-analysis were finally included, three of which were rated as low grade by AMSTAR2 and ten as very low grade. A total of 75 outcome indicators were obtained, involving influenza, COVID-19, and HFMD. According to the GRADE scoring results, the 75 outcome indicators included 5(6.7%) high-level indicators, 18(24.0%) mediate-level indicators, 25(33.3%) low-level evidence indicators, and 27(36.0%) very low-level indicators.(1)In the treatment of influenza, Lianhua Qingwen preparations exhibited better clinical efficacy than other Chinese patent medicines and Ribavirin and had similar clinical efficacy compared with Oseltamivir. Lianhua Qingwen preparations were superior to other Chinese patent medicines, Oseltamivir, and Ribavirin in alleviating clinical symptoms. They showed no significant differences from Oseltamivir or conventional anti-influenza treatment in terms of the time to and rate of negative result of viral nucleic acid test.(2)In the treatment of COVID-19, Lianhua Qingwen preparation alone or combined with conventional treatment was superior to conventional treatment in terms of total effective rate, main symptom subsidence rate and time, fever clearance rate, duration of fever, time to fever clearance, cough subsidence rate, time to cough subsidence, fatigue subsidence rate, time to fatigue subsidence, myalgia subsidence rate, expectoration subsidence rate, chest tightness subsidence rate, etc. Lianhua Qingwen preparations no difference from conventional treatment in terms of subsiding sore throat, nausea, diarrhea, loss of appetite, headache, and dyspnea. In terms of chest CT improvement rate, rate of progression to severe case, cure time, and hospitalization time, Lianhua Qingwen alone or in combination with conventional treatment was superior to conventional treatment.(3)In the treatment of HFMD, Lianhua Qingwen Granules was superior to conventional treatment in terms of total effective rate, average fever clearance time, time to herpes subsidence, and time to negative result of viral nucleic acid test.(4)In terms of safety, Lianhua Qingwen preparations led to low incidence of adverse reactions, all of which were mild and disappeared after drug withdrawal. The available evidence suggests that in the treatment of influenza, COVID-19, and HFMD, Lianhua Qingwen preparations can relieve the clinical symptoms, shorten the hospitalization time, and improve the chest CT. They have therapeutic effect and good safety in the treatment of viral diseases. However, due to the low quality of available studies, more high-quality clinical trials are needed to support the above conclusions.

Proteomic and Metabolomic Characterization of SARS-CoV-2-Infected Cynomolgus Macaque at Early Stage

Although tremendous effort has been exerted to elucidate the pathogenesis of severe COVID-19 cases, the detailed mechanism of moderate cases, which accounts for 90% of all patients, remains unclear yet, partly limited by lacking the biopsy tissues. Here, we established the COVID-19 infection model in cynomolgus macaques (CMs), monitored the clinical and pathological features, and analyzed underlying pathogenic mechanisms at early infection stage by performing proteomic and metabolomic profiling of lung tissues and sera samples from COVID-19 CMs models. Our data demonstrated that innate immune response, neutrophile and platelet activation were mainly dysregulated in COVID-19 CMs. The symptom of neutrophilia, lymphopenia and massive “cytokines storm”, main features of severe COVID-19 patients, were greatly weakened in most of the challenged CMs, which are more semblable as moderate patients. Thus, COVID-19 model in CMs is rational to understand the pathogenesis of moderate COVID-19 and may be a candidate model to assess the safety and efficacy of therapeutics and vaccines against SARS-CoV-2 infection.

Frontiers of COVID-19-related myocarditis as assessed by cardiovascular magnetic resonance.

Coronavirus disease 2019 (COVID-19) is caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. In some patients, COVID-19 is complicated with myocarditis. Early detection of myocardial injury and timely intervention can significantly improve the clinical outcomes of COVID-19 patients. Although endomyocardial biopsy (EMB) is currently recognized as the 'gold standard' for the diagnosis of myocarditis, there are large sampling errors, many complications and a lack of unified diagnostic criteria. In addition, the clinical methods of treating acute and chronic COVID-19-related myocarditis are different. Cardiac magnetic resonance (CMR) can evaluate the morphology of the heart, left and right ventricular functions, myocardial perfusion, capillary leakage and myocardial interstitial fibrosis to provide a noninvasive and radiation-free diagnostic basis for the clinical detection, efficacy and risk assessment, and follow-up observation of COVID-19-related myocarditis. However, for the diagnosis of COVID-19-related myocarditis, the Lake Louise Consensus Criteria may not be fully applicable. COVID-19-related myocarditis is different from myocarditis related to other viral infections in terms of signal intensity and lesion location as assessed by CMR, which is used to visualize myocardial damage, locate lesions and quantify pathological changes based on various sequences. Therefore, the standardized application of CMR to timely and accurately evaluate heart injury in COVID-19-related myocarditis and develop rational treatment strategies could be quite effective in improving the prognosis of patients and preventing potential late-onset effects in convalescent patients with COVID-19.

Identification of a recombinant equine coronavirus in donkey, China.

Equine coronavirus (ECoV) was first identified in the USA and has been previously described in several countries. In order to test the presence of ECoV in China, we collected 51 small intestinal samples from donkey foals with diarrhoea from a donkey farm in Shandong Province, China between August 2020 and April 2021. Two samples tested positive for ECoV and full-length genome sequences were successfully obtained using next-generation sequencing, one of which was further confirmed by Sanger sequencing. The two strains shared 100% sequence identity at the scale of whole genome. Bioinformatics analyses further showed that the two Chinese strains represent a novel genetic variant of ECoV and shared the highest sequence identity of 97.05% with the first identified ECoV strain - NC99. In addition, it may be a recombinant, with the recombination region around the NS2 gene. To our knowledge, this is the first documented report of ECoV in China, highlighting its risk to horse/donkey breeding. In addition, its potential risk to public health also warrants further investigation.

Fatality assessment and variant risk monitoring for COVID-19 using three new hospital occupancy related metrics (preprint)

Background Though case fatality rate (CFR) and hospital mortality rate (HMR) are used to reflect COVID-19 fatality risk, they are limited by temporal and spatial variation of CFR and availability of HMR. Alternative metrics are needed for COVID-19 fatality measurement and variant risk monitoring. Methods New metrics and their applications in fatality measurements and risk monitoring are proposed here. We also introduce a new mathematical model to estimate average hospital length of stay for death (Ldead) and discharges (Ldis). Multiple data sources were used for our analysis. Findings We propose three new metrics, hospital occupancy mortality rate (HOMR), ratio of total deaths to hospital occupancy (TDHOR) and ratio of hospital occupancy to cases (HOCR), for dynamic assessment of COVID-19 fatality risk. Estimated Ldead and Ldis for 501079 COVID-19 hospitalizations in US 34 states between Aug 7, 2020 and Mar 1, 2021 were 14.0 and 18.2 days, respectively. We found that TDHOR values of 27 countries are less spatially and temporally variable and more capable of detecting changes in COVID-19 fatality risk. The dramatic changes in COVID-19 CFR observed in 27 countries during early stages of the pandemic were mostly caused by undiagnosed cases. Compared to the first week of November, 2021, the week mean HOCRs (mimics hospitalization-to-case ratio) for Omicron variant decreased 34.08% and 65.16% in the United Kingdom and USA respectively as of Jan 16, 2022. Interpretation These new and reliable measurements for COVID-19 that could be expanded as a general index to other fatal infectious diseases for disease fatality risk and variant-associated risk monitoring.

Analysis of trends in patent development for coronavirus detection, prevention, and treatment technologies in key countries.

Coronavirus causes significant damage to human health and the global economy. In this paper, we undertake patent analysis and data mining to systematically analyze the trend in patent applications for coronavirus detection, prevention, and treatment technologies. Our goals are to determine the correlation between typical coronavirus outbreaks and changes in patent technology applications, and to compare the research and development (R&D) progress, patent layout, and characteristics of major institutions in various countries experiencing coronavirus outbreaks. We find that the United States commenced coronavirus detection and vaccine technology R&D earlier than other countries, as it attached importance to the R&D for treatment technologies from the time of the SARS outbreak and initiated the trend of multi-party R&D, with full technology chain coverage by the government, enterprises, universities, and research institutions. China's patent applications have grown rapidly in recent years, mainly based on the R&D of research institutions and universities, although it has formed full technology chain coverage. However, the patent quality and technology global layout still need to be improved. This paper reviews the patent development trends of important coronavirus technologies, and proposes that policymakers should establish a long-term mechanism for R&D, pay attention to intellectual property protection, and deepen international technical cooperation to provide a reference for the development and application of coronavirus detection technology, vaccine technology, and treatment technology.

Mesenchymal stem cell treatment improves outcome of COVID-19 patients via multiple immunomodulatory mechanisms.

The infusion of coronavirus disease 2019 (COVID-19) patients with mesenchymal stem cells (MSCs) potentially improves clinical symptoms, but the underlying mechanism remains unclear. We conducted a randomized, single-blind, placebo-controlled (29 patients/group) phase II clinical trial to validate previous findings and explore the potential mechanisms. Patients treated with umbilical cord-derived MSCs exhibited a shorter hospital stay (P = 0.0198) and less time required for symptoms remission (P = 0.0194) than those who received placebo. Based on chest images, both severe and critical patients treated with MSCs showed improvement by day 7 (P = 0.0099) and day 21 (P = 0.0084). MSC-treated patients had fewer adverse events. MSC infusion reduced the levels of C-reactive protein, proinflammatory cytokines, and neutrophil extracellular traps (NETs) and promoted the maintenance of SARS-CoV-2-specific antibodies. To explore how MSCs modulate the immune system, we employed single-cell RNA sequencing analysis on peripheral blood. Our analysis identified a novel subpopulation of VNN2+ hematopoietic stem/progenitor-like (HSPC-like) cells expressing CSF3R and PTPRE that were mobilized following MSC infusion. Genes encoding chemotaxis factors - CX3CR1 and L-selectin - were upregulated in various immune cells. MSC treatment also regulated B cell subsets and increased the expression of costimulatory CD28 in T cells in vivo and in vitro. In addition, an in vivo mouse study confirmed that MSCs suppressed NET release and reduced venous thrombosis by upregulating kindlin-3 signaling. Together, our results underscore the role of MSCs in improving COVID-19 patient outcomes via maintenance of immune homeostasis.

A novel SARS-CoV-2 related coronavirus with complex recombination isolated from bats in Yunnan province, China.

At the end of 2019, A new type of beta-CoV, SARS-CoV-2 emerged and triggered the COVID-19 pandemic, which spread overwhelmingly around the world in less than a year. However, the origin and direct ancestral viruses of SARS-CoV-2 remain unknown. RaTG13, a novel coronavirus found in bats in China's Yunnan Province, is the closest relative virus of the SARS-CoV-2 identified so far. In this study, a new SARS-CoV-2 related virus, provisionally named PrC31, was discovered in Yunnan province by retrospectively analyse bat next generation sequencing (NGS) data of intestinal samples collected in 2018. PrC31 shared 90.7% and 92.0% nucleotide identities to the genomes of SARS-CoV-2 and the bat SARSr-CoV ZC45, respectively. Sequence alignment of PrC31 showed that several genomic regions, especially orf1a and orf8 had the highest homology with those corresponding genomic regions of SARS-CoV-2 than any other related viruses. Phylogenetic analysis indicated that PrC31 shared a common ancestor with SARS-CoV-2 in evolutionary history. The differences between the PrC31 and SARS-CoV-2 genomes were mainly manifested in the spike genes. The amino acid homology between the receptor binding domains of PrC31 and SARS-CoV-2 was only 64.2%. Importantly, recombination analysis revealed that PrC31 underwent multiple complex recombination events (including three recombination breakpoints) involving the SARS-CoV and SARS-CoV-2 sub-lineages, indicating that PrC31 evolved from yet-to-be-identified intermediate recombination strains. Combined with previous studies, it is revealed that the beta-CoVs may possess a more complex recombination mechanism than we thought.