Tracking the first SARS-CoV-2 Omicron BA.5.1.3 outbreak in China.

The SARS-CoV-2 is still undergoing rapid evolution, resulting in the emergence of several variants of concern, especially the Omicron variants (B.1.1.529), which are surging worldwide. In this study, we tracked Omicron subvariant BA.5.1.3 as the causative agent in the Hainan Province wave in China, which started on 1 August 2022. This was China's first case of Omicron subvariant BA.5.1.3 and led to an indefinite total lockdown in Hainan with more than 8,500 confirmed cases. We obtained 391 whole genomes from positive nasopharyngeal swab samples in the city of Sanya in Hainan Province, which was the center of this outbreak. More than half of the infected cases were female (58%, 227/391) with a median age of 37.0 years (IQR 23.0-53.0). Median Ct values were 24.9 (IQR 22.6-27.3) and 25.2 (IQR 22.9-27.6) for ORF1ab and N genes, respectively. The total single-nucleotide polymorphism (SNP) numbers of Omicron BA.5.1.3 sampled in Sanya (median 69.0, IQR = 69.0-70.0) compared to those worldwide (median 63.0, IQR = 61.0-64.0) showed a significant difference (p < 0.05). Unique core mutations, including three non-synonymous mutations in ORF1ab (Y1064N, S2844G, and R3574K) and one synonymous mutation in ORF3a (S74S), were found. Phylogenetic analysis showed that virus from Sanya formed an independent sub-clade within the BA.5.1.3 subvariant, and could be divided into 15 haplotypes based on the S gene. The most recent common ancestor for the virus from Sanya was estimated as appearing on 5 July 2022, with 95% HPD ranging from 15 May to 20 September 2022. Thanks to our results, we were also able to delineate the mutational profile of this outbreak and highlight the importance of global genomic surveillance and data sharing.

Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine.

CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.

Single-cell transcriptomic atlas reveals distinct immunological responses between COVID-19 vaccine and natural SARS-CoV-2 infection.

To control the ongoing coronavirus disease-2019 (COVID-19) pandemic, CoronaVac (Sinovac), an inactivated vaccine, has been granted emergency use authorization by many countries. However, the underlying mechanisms of the inactivated COVID-19 vaccine-induced immune response remain unclear, and little is known about its features compared to (Severe acute respiratory syndrome coronavirus 2) SARS-CoV-2 infection. Here, we implemented single-cell RNA sequencing (scRNA-seq) to profile longitudinally collected PBMCs (peripheral blood mononuclear cells) in six individuals immunized with CoronaVac and compared these to the profiles of COVID-19 infected patients from a Single Cell Consortium. Both inactivated vaccines and SARS-CoV-2 infection altered the proportion of different immune cell types, caused B cell activation and differentiation, and induced the expression of genes associated with antibody production in the plasma. The inactivated vaccine and SARS-COV-2 infection also caused alterations in peripheral immune activity such as interferon response, inflammatory cytokine expression, innate immune cell apoptosis and migration, effector T cell exhaustion and cytotoxicity, however, the magnitude of change was greater in COVID-19 patients, especially those with severe disease, than in immunized individuals. Further analyses revealed a distinct peripheral immune cell phenotype associated with CoronaVac immunization (HLA class II upregulation and IL21R upregulation in naïve B cells) versus SARS-CoV-2 infection (HLA class II downregulation and IL21R downregulation in naïve B cells from severe disease individuals). There were also differences in the expression of important genes associated with proinflammatory cytokines and thrombosis. In conclusion, this study provides a single-cell atlas of the systemic immune response to CoronaVac immunization and revealed distinct immune responses between inactivated vaccines and SARS-CoV-2 infection.

Proteomic and Metabolomic Signatures Associated With the Immune Response in Healthy Individuals Immunized With an Inactivated SARS-CoV-2 Vaccine

CoronaVac (Sinovac), an inactivated vaccine for SARS-CoV-2, has been widely used for immunization. However, analysis of the underlying molecular mechanisms driving CoronaVac-induced immunity is still limited. Here, we applied a systems biology approach to understand the mechanisms behind the adaptive immune response to CoronaVac in a cohort of 50 volunteers immunized with 2 doses of CoronaVac. Vaccination with CoronaVac led to an integrated immune response that included several effector arms of the adaptive immune system including specific IgM/IgG, humoral response and other immune response, as well as the innate immune system as shown by complement activation. Metabolites associated with immunity were also identified implicating the role of metabolites in the humoral response, complement activation and other immune response. Networks associated with the TCA cycle and amino acids metabolic pathways, such as phenylalanine metabolism, phenylalanine, tyrosine and tryptophan biosynthesis, and glycine, serine and threonine metabolism were tightly coupled with immunity. Critically, we constructed a multifactorial response network (MRN) to analyze the underlying interactions and compared the signatures affected by CoronaVac immunization and SARS-CoV-2 infection to further identify immune signatures and related metabolic pathways altered by CoronaVac immunization. These results help us to understand the host response to vaccination of CoronaVac and highlight the utility of a systems biology approach in defining molecular correlates of protection to vaccination.

Super Dominant Pathobiontic Bacteria in the Nasopharyngeal Microbiota Cause Secondary Bacterial Infection in COVID-19 Patients.

Coronavirus disease 2019 (COVID-19) is a respiratory infectious disease responsible for many infections worldwide. Differences in respiratory microbiota may correlate with disease severity. Samples were collected from 20 severe and 51 mild COVID-19 patients. High-throughput sequencing of the 16S rRNA gene was used to analyze the bacterial community composition of the upper and lower respiratory tracts. The indices of diversity were analyzed. When one genus accounted for >50% of reads from a sample, it was defined as a super dominant pathobiontic bacterial genus (SDPG). In the upper respiratory tract, uniformity indices were significantly higher in the mild group than in the severe group (P < 0.001). In the lower respiratory tract, uniformity indices, richness indices, and the abundance-based coverage estimator were significantly higher in the mild group than in the severe group (P < 0.001). In patients with severe COVID-19, SDPGs were detected in 40.7% of upper and 63.2% of lower respiratory tract samples. In patients with mild COVID-19, only 10.8% of upper and 8.5% of lower respiratory tract samples yielded SDPGs. SDPGs were present in both upper and lower tracts in seven patients (35.0%), among which six (30.0%) patients possessed the same SDPG in the upper and lower tracts. However, no patients with mild infections had an SDPG in both tracts. Staphylococcus, Corynebacterium, and Acinetobacter were the main SDPGs. The number of SDPGs identified differed significantly between patients with mild and severe COVID-19 (P < 0.001). SDPGs in nasopharyngeal microbiota cause secondary bacterial infection in COVID-19 patients and aggravate pneumonia. IMPORTANCE The nasopharyngeal microbiota is composed of a variety of not only the true commensal bacterial species but also the two-face pathobionts, which are one a harmless commensal bacterial species and the other a highly invasive and deadly pathogen. In a previous study, we found that the diversity of nasopharyngeal microbiota was lost in severe influenza patients. We named the genus that accounted for over 50% of microbiota abundance as super dominant pathobiontic genus, which could invade to cause severe pneumonia, leading to high fatality. Similar phenomena were found here for SARS-CoV-2 infection. The diversity of nasopharyngeal microbiota was lost in severe COVID-19 infection patients. SDPGs in nasopharyngeal microbiota were frequently detected in severe COVID-19 patients. Therefore, the SDPGs in nasopharynx microbiota might invade into low respiratory and be responsible for secondary bacterial pneumonia in patients with SARS-CoV-2 infection.

A Novel Real-Time Reverse Transcription Loop-Mediated Isothermal Amplification Detection Platform: Application to Diagnosis of COVID-19.

The ongoing Corona virus disease (COVID-19) outbreak has become a huge global health concern. Here, we reported a novel detection platform based on the loop-mediated isothermal amplification (LAMP), termed real-time reverse transcription LAMP (rRT-LAMP) and applied it for the diagnosis of COVID-19 (COVID-19 rRT-LAMP). rRT-LAMP integrates reverse transcription, LAMP amplification, restriction endonuclease cleavage and real-time fluorescence detection into one-pot reaction, and facilitates the diagnosis of COVID-19 at 64°C for only 35 min. The ORF1ab (opening reading frame 1a/b) and NP (nucleoprotein) genes of SARS-CoV-2 were detected for diagnosing COVID-19. The limit of detection (LoD) of COVID-19 rRT-LAMP assay was 14 copies (for each marker) per vessel, and no positive results were obtained from non-SARS-CoV-2 templates. To demonstrate its feasibility, a total of 33 oropharynx swab samples collected from COVID-19 patients also were diagnosed as SARS-CoV-2 infection using COVID-19 rRT-LAMP protocol. No cross-reactivity was yielded from 41 oropharynx swab samples collected from non-COVID-19 patients. These data suggesting that the COVID-19 rRT-LAMP assay is a potential detection tool for the diagnosis of SARS-CoV-2 infection in clinical, field and disease control laboratories, and will be valuable for controlling the COVID-19 epidemic.

Rapid, Ultrasensitive, and Highly Specific Diagnosis of COVID-19 by CRISPR-Based Detection.

Coronavirus Disease 2019 (COVID-19), which is caused by SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2), has rapidly spread leading to a global pandemic. Here, we combined multiple cross displacement amplification (MCDA) with CRISPR-Cas12a-based detection to develop a novel diagnostic test (MCCD) and applied for the diagnosis of COVID-19, called COVID-19 MCCD. The MCCD protocol conducts reverse transcription MCDA (RT-MCDA) reaction for RNA templates followed by CRISPR-Cas12a/CrRNA complex detection of predefined target sequences after which degradation of a single-strand DNA (ssDNA) molecule confirms detection of the target sequence. Two MCDA primer sets and two CrRNAs were designed targeting the opening reading frame 1a/b (ORF1ab) and nucleoprotein (N) of SARS-CoV-2. The optimal conditions include two RT-MCDA reactions at 63 °C for 35 min and a CRISPR-Cas12a/CrRNA detection reaction at 37 °C for 5 min. The COVID-19 MCCD assay can be visualized on a lateral flow biosensor (LFB) and completed within 1 h including RNA extraction (15 min), RT-MCDA reaction (35 min), CRISPR-Cas12a/CrRNA detection reaction (5 min), and reporting of result (within 2 min). The COVID-19 MCCD assay is very sensitive and detects the target gene with as low as seven copies per test and does not cross-react with non-SARS-CoV-2 templates. SARS-CoV-2 was detected in 37 of 37 COVID-19 patient samples, and nonpositive results were detected from 77 non-COVID-19 patients. Therefore, the COVID-19 MCCD assay is a useful tool for the reliable and quick diagnosis of SARS-CoV-2 infection.

Clinical analysis of 214 suspected cases of COVID-19

A retrospective analysis of the epidemiological history, clinical manifestations, the results of CT, blood routine and nucleic acid test of 214 suspected cases with coronavirus disease 2019(COVID-19) in Sanya was conducted to provide a reference for the diagnosis of the disease. Methods The epidemiological data, clinical manifestations, and SARSCoV-2 nucleic acid test of 214 suspected cases of COVID-19 from Sanya People's Hospital from January 24th to March 5th, 2020 were collected. The confirmed infection rates of 214 suspected patients of different genders and ages were analyzed. The white blood cell count, lymphocyte count, C-reactive protein, clinical manifestations and CT of 214 suspected patients were analyzed. Results Among the 214 suspected cases of COVID-19, 24(11.2%) were positive for viral nucleic acid. There were no significant differences in the rates of confirmed infections of different genders in 214 suspected cases of COVID-19 (P > 0.05);there was no significant difference in the confirmed infection rates of different age groups (P > 0.05). The changes in white blood cell counts, lymphocyte counts, and C-reactive protein had no significant difference in the infection rate of COVID-19 (P > 0.05). Of the 24 confirmed cases, 23 had a related epidemiological history (95.8%), and the respiratory symptoms were mainly fever and cough. CT images of 24 confirmed cases showed different degrees of ground glass-like density or bilateral infiltration in lungs. Conclusion The diagnosis of suspected cases of COVID-19, based on a comprehensive analysis of epidemiological history and corresponding clinical manifestations of patients, and it still needs to rely on pathogenic nucleic acid detection.

Multiplex reverse transcription loop-mediated isothermal amplification combined with nanoparticle-based lateral flow biosensor for the diagnosis of COVID-19.

The ongoing global pandemic (COVID-19), caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), has become a huge public health issue. Hence, we devised a multiplex reverse transcription loop-mediated isothermal amplification (mRT-LAMP) coupled with a nanoparticle-based lateral flow biosensor (LFB) assay (mRT-LAMP-LFB) for diagnosing COVID-19. Using two LAMP primer sets, the ORF1ab (opening reading frame 1a/b) and N (nucleoprotein) genes of SARS-CoV-2 were simultaneously amplified in a single-tube reaction, and detected with the diagnosis results easily interpreted by LFB. In presence of FITC (fluorescein)-/digoxin- and biotin-labeled primers, mRT-LAMP produced numerous FITC-/digoxin- and biotin-attached duplex amplicons, which were determined by LFB through immunoreactions (FITC/digoxin on the duplex and anti-FITC/digoxin on the test line of LFB) and biotin/treptavidin interaction (biotin on the duplex and strptavidin on the polymerase nanoparticle). The accumulation of nanoparticles leaded a characteristic crimson band, enabling multiplex analysis of ORF1ab and N gene without instrumentation. The limit of detection (LoD) of COVID-19 mRT-LAMP-LFB was 12 copies (for each detection target) per reaction, and no cross-reactivity was generated from non-SARS-CoV-2 templates. The analytical sensitivity of SARS-CoV-2 was 100% (33/33 oropharynx swab samples collected from COVID-19 patients), and the assay's specificity was also 100% (96/96 oropharynx swab samples collected from non-COVID-19 patients). The total diagnostic test can be completed within 1 h from sample collection to result interpretation. In sum, the COVID-19 mRT-LAMP-LFB assay is a promising tool for diagnosing SARS-CoV-2 infections in frontline public health field and clinical laboratories, especially from resource-poor regions.