Specific lateral flow detection of isothermal nucleic acid amplicons for accurate point-of-care testing.

For point-of-care testing (POCT), coupling isothermal nucleic acid amplification schemes (e.g., recombinase polymerase amplification, RPA) with lateral flow assay (LFA) readout is an ideal platform, since such integration offers both high sensitivity and deployability. However, isothermal schemes typically suffers from non-specific amplification, which is difficult to be differentiated by LFA and thus results in false-positives. Here, we proposed an accurate POCT platform by specific recognition of target amplicons with peptide nucleic acid (PNA, assisted by T7 Exonuclease), which could be directly plugged into the existing RPA kits and commercial LFA test strips. With SARS-CoV-2 as the model, the proposed method (RPA-TeaPNA-LFA) efficiently eliminated the false-positives, exhibiting a lowest detection concentration of 6.7 copies/µL of RNA and 90 copies/µL of virus. Using dual-gene (orf1ab and N genes of SARS-CoV-2) as the targets, RPA-TeaPNA-LFA offered a high specificity (100%) and sensitivity (RT-PCR Ct < 31, 100%; Ct < 40, 71.4%), and is valuable for on-site screening or self-testing during isolation. In addition, the dual test lines in the test strips were successfully explored for simultaneous detection of SARS-CoV-2 and H1N1, showing great potential in response to future pathogen-based pandemics.

Metatranscriptomic Analysis Reveals Disordered Alterations in Oropharyngeal Microbiome during the Infection and Clearance Processes of SARS-CoV-2: A Warning for Secondary Infections.

This study was conducted to investigate oropharyngeal microbiota alterations during the progression of coronavirus disease 2019 (COVID-19) by analyzing these alterations during the infection and clearance processes of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The diagnosis of COVID-19 was confirmed by using positive SARS-CoV-2 quantitative reverse transcription polymerase chain reaction (RT-qPCR). The alterations in abundance, diversity, and potential function of the oropharyngeal microbiome were identified using metatranscriptomic sequencing analyses of oropharyngeal swab specimens from 47 patients with COVID-19 (within a week after diagnosis and within two months after recovery from COVID-19) and 40 healthy individuals. As a result, in the infection process of SARS-CoV-2, compared to the healthy individuals, the relative abundances of Prevotella, Aspergillus, and Epstein-Barr virus were elevated; the alpha diversity was decreased; the beta diversity was disordered; the relative abundance of Gram-negative bacteria was increased; and the relative abundance of Gram-positive bacteria was decreased. After the clearance of SARS-CoV-2, compared to the healthy individuals and patients with COVID-19, the above disordered alterations persisted in the patients who had recovered from COVID-19 and did not return to the normal level observed in the healthy individuals. Additionally, the expressions of several antibiotic resistance genes (especially multi-drug resistance, glycopeptide, and tetracycline) in the patients with COVID-19 were higher than those in the healthy individuals. After SARS-CoV-2 was cleared, the expressions of these genes in the patients who had recovered from COVID-19 were lower than those in the patients with COVID-19, and they were different from those in the healthy individuals. In conclusion, our findings provide evidence that potential secondary infections with oropharyngeal bacteria, fungi, and viruses in patients who have recovered from COVID-19 should not be ignored; this evidence also highlights the clinical significance of the oropharyngeal microbiome in the early prevention of potential secondary infections of COVID-19 and suggests that it is imperative to choose appropriate antibiotics for subsequent bacterial secondary infection in patients with COVID-19.

CRISPR-Cas13a cascade-based viral RNA assay for detecting SARS-CoV-2 and its mutations in clinical samples.

SARS-CoV-2 is one of the greatest threats to global human health. Point-of-care diagnostic tools for SARS-CoV-2 could facilitate rapid therapeutic intervention and mitigate transmission. In this work, we report CRISPR-Cas13a cascade-based viral RNA (Cas13C) assay for label-free and isothermal determination of SARS-CoV-2 and its mutations in clinical samples. Cas13a/crRNA was utilized to directly recognize the target of SARS-CoV-2 RNA, and the recognition events sequentially initiate the transcription amplification to produce light-up RNA aptamers for output fluorescence signal. The recognition of viral RNA via Cas13a-guide RNA ensures a high specificity to distinguish SARS-CoV-2 from MERS-CoV and SARS-CoV, as well as viral mutations. A post transcription amplification strategy was triggered after CRISPR-Cas13a recognition contributes to an amplification cascade that achieves high sensitivity for detecting SARS-CoV-2 RNA, with a limit of detection of 0.216 fM. In addition, the Cas13C assay could be able to discriminate single-nucleotide mutation, which was proven with N501Y in SARS-Cov-2 variant. This method was validated by a 100% agreement with RT-qPCR results from 12 clinical throat swab specimens. The Cas13C assay has the potential to be used as a routine nucleic acid test of SARS-CoV-2 virus in resource-limited regions.

Applications of laboratory findings in the prevention, diagnosis, treatment, and monitoring of COVID-19.

The worldwide pandemic of coronavirus disease 2019 (COVID-19) presents us with a serious public health crisis. To combat the virus and slow its spread, wider testing is essential. There is a need for more sensitive, specific, and convenient detection methods of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Advanced detection can greatly improve the ability and accuracy of the clinical diagnosis of COVID-19, which is conducive to the early suitable treatment and supports precise prophylaxis. In this article, we combine and present the latest laboratory diagnostic technologies and methods for SARS-CoV-2 to identify the technical characteristics, considerations, biosafety requirements, common problems with testing and interpretation of results, and coping strategies of commonly used testing methods. We highlight the gaps in current diagnostic capacity and propose potential solutions to provide cutting-edge technical support to achieve a more precise diagnosis, treatment, and prevention of COVID-19 and to overcome the difficulties with the normalization of epidemic prevention and control.

Development and Validation of a Predictive Model for Severe COVID-19: A Case-Control Study in China.

Background: Predicting the risk of progression to severe coronavirus disease 2019 (COVID-19) could facilitate personalized diagnosis and treatment options, thus optimizing the use of medical resources. Methods: In this prospective study, 206 patients with COVID-19 were enrolled from regional medical institutions between December 20, 2019, and April 10, 2020. We collated a range of data to derive and validate a predictive model for COVID-19 progression, including demographics, clinical characteristics, laboratory findings, and cytokine levels. Variation analysis, along with the least absolute shrinkage and selection operator (LASSO) and Boruta algorithms, was used for modeling. The performance of the derived models was evaluated by specificity, sensitivity, area under the receiver operating characteristic (ROC) curve (AUC), Akaike information criterion (AIC), calibration plots, decision curve analysis (DCA), and Hosmer-Lemeshow test. Results: We used the LASSO algorithm and logistic regression to develop a model that can accurately predict the risk of progression to severe COVID-19. The model incorporated alanine aminotransferase (ALT), interleukin (IL)-6, expectoration, fatigue, lymphocyte ratio (LYMR), aspartate transaminase (AST), and creatinine (CREA). The model yielded a satisfactory predictive performance with an AUC of 0.9104 and 0.8792 in the derivation and validation cohorts, respectively. The final model was then used to create a nomogram that was packaged into an open-source and predictive calculator for clinical use. The model is freely available online at https://severeconid-19predction.shinyapps.io/SHINY/. Conclusion: In this study, we developed an open-source and free predictive calculator for COVID-19 progression based on ALT, IL-6, expectoration, fatigue, LYMR, AST, and CREA. The validated model can effectively predict progression to severe COVID-19, thus providing an efficient option for early and personalized management and the allocation of appropriate medical resources.

Genomic monitoring of SARS-CoV-2 uncovers an Nsp1 deletion variant that modulates type I interferon response.

The SARS-CoV-2 virus, the causative agent of COVID-19, is undergoing constant mutation. Here, we utilized an integrative approach combining epidemiology, virus genome sequencing, clinical phenotyping, and experimental validation to locate mutations of clinical importance. We identified 35 recurrent variants, some of which are associated with clinical phenotypes related to severity. One variant, containing a deletion in the Nsp1-coding region (Δ500-532), was found in more than 20% of our sequenced samples and associates with higher RT-PCR cycle thresholds and lower serum IFN-ß levels of infected patients. Deletion variants in this locus were found in 37 countries worldwide, and viruses isolated from clinical samples or engineered by reverse genetics with related deletions in Nsp1 also induce lower IFN-ß responses in infected Calu-3 cells. Taken together, our virologic surveillance characterizes recurrent genetic diversity and identified mutations in Nsp1 of biological and clinical importance, which collectively may aid molecular diagnostics and drug design.

Detection of SARS-CoV-2 and Its Mutated Variants via CRISPR-Cas13-Based Transcription Amplification.

The outbreak of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) caused a global health emergency, and its gene mutation and evolution further posed uncertainty of epidemic risk. Herein, we reported a light-up CRISPR-Cas13 transcription amplification method, which enables the detection of SARS-CoV-2 and its mutated variants. Sequence specificity was ensured by both the ligation process and Cas13a/crRNA recognition, allowing us to identify viral RNA mutation. Light-up RNA aptamer allows sensitive output of amplification signals via target-activated ribonuclease activity of CRISPR-Cas13a. The RNA virus assay has been designed to detect coronavirus, SARS-CoV-2, Middle East respiratory syndrome (MERS), and SARS, as well as the influenza viruses such as, H1N1, H7N9, and H9N2. It was accommodated to sense as low as 82 copies of SARS-CoV-2. Particularly, it allowed us to strictly discriminate key mutation of the SARS-CoV-2 variant, D614G, which may induce higher epidemic and pathogenetic risk. The proposed RNA virus assays are promising for point-of-care monitoring of SARS-CoV-2 and its risking variants.

Dynamics of NK, CD8 and Tfh cell mediated the production of cytokines and antiviral antibodies in Chinese patients with moderate COVID-19.

Recent studies have demonstrated a marked decrease in peripheral lymphocyte levels in patients with coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Few studies have focused on the changes of NK, T- and B-cell subsets, inflammatory cytokines and virus-specific antibodies in patients with moderate COVID-19. A total of 11 RT-PCR-confirmed convalescent patients with COVID-19 and 11 patients with non-SARS-CoV-2 pneumonia (control patients) were enrolled in this study. NK, CD8+ T, CD4+ T, Tfh-like and B-cell subsets were analysed using flow cytometry. Cytokines and SARS-CoV-2-specific antibodies were analysed using an electrochemiluminescence immunoassay. NK cell counts were significantly higher in patients with COVID-19 than in control patients (P = 0.017). Effector memory CD8+ T-cell counts significantly increased in patients with COVID-19 during a convalescent period of 1 week (P = 0.041). TIM-3+ Tfh-like cell and CD226+ Tfh-like cell counts significantly increased (P = 0.027) and decreased (P = 0.022), respectively, during the same period. Moreover, ICOS+ Tfh-like cell counts tended to decrease (P = 0.074). No abnormal increase in cytokine levels was observed. The high expression of NK cells is important in innate immune response against SARS-CoV-2. The increase in effector memory CD8+ T-cell counts, the up-regulation of inhibitory molecules and the down-regulation of active molecules on CD4+ T cells and Tfh-like cells in patients with COVID-19 would benefit the maintenance of balanced cellular and humoural immune responses, may prevent the development of severe cases and contribute to the recovery of patients with COVID-19.

Expression of eosinophil in peripheral blood of patients with COVID-19 and its clinical significance.

AIMS: To investigate the eosinophil cell (EC) expression in peripheral blood of patients infected with severe acute respiratory syndrome coronavirus 2(SARS-CoV-2) and its clinical significance of diagnosis and prognosis. METHODS: 95 patients, whose nucleic acid test of SARS-CoV-2 was positive to make a definite diagnosis of COVID-19, were selected as the study group. They were admitted at the Chengdu Public Health Clinical Medical Center from January 21 to March 2, 2020. Another 95 healthy subjects and 95 non-infectious fever patients during the same period were selected as the control group. The BC-6900 blood cell analyzer was used to continuously observe and detect ECs in 95 patients with COVID-19 and the control group. The differences in expression levels of ECs in peripheral blood were analyzed. RESULTS: ECs were significantly decreased in 95 (75.8%) COVID-19 patients (P < .01). The absolute EC count IQR was 0.01 × 109/L (0 × 109/L - 0.04 × 109/L), and the EC percentage IQR was 0.3% (0.1% - 0.8%). As the patients' condition improved, the ECs returned to normal, but for those without improvement, ECs continued to decline. CONCLUSIONS: ECs decreased remarkably in patients with COVID-19, and gradually returned to normal after the improvement of the patients' condition, while EC continued to decrease in patients without improvement. It is suggested that ECs have certain clinical significance in the diagnosis and prognosis of COVID-19, and may be a useful index in the early warning of acute infectious diseases.

Epidemiological surveillance of common respiratory viruses in patients with suspected COVID-19 in Southwest China.

BACKGROUND: The outbreak of coronavirus disease 2019 (COVID-19) caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is currently the peak season of common respiratory viral infections. However, the clinical symptoms of most SARS-CoV-2 infected patients are not significantly different from those of common respiratory viral infections. Therefore, knowing the epidemiological patterns of common respiratory viruses may be valuable to improve the diagnostic and therapeutic efficacy of patients with suspected COVID-19, especially in Southwest China (a mild epidemic area). METHODS: A total of 2188 patients with clinically suspected of COVID-19 in Southwest China were recruited from January 21 to February 29, 2020. Nasopharyngeal swabs, throat swabs and sputum specimens were collected to detect SARS-CoV-2 by using real-time reverse transcription-polymerase chain reaction (RT-PCR) and other 12 viruses via PCR fragment analysis combined with capillary electrophoresis. Clinical characteristics and laboratory test findings were acquired from electronic medical records. All data were analyzed to unravel the epidemiological patterns. RESULTS: Only 1.1% (24/2188) patients with suspected COVID-19 were eventually confirmed to have SARS-CoV-2 infection, and the most frequently observed symptoms were fever (75.0%, 18/24) and cough (20.8%, 5/24). The overall detection rate of other respiratory pathogens was 10.3% (226/2188). Among them, human rhinovirus (3.2%, 71/2188), human parainfluenza viruses (1.6%, 35/2188), influenza B virus (1.2%, 26/2188) and mycoplasma pneumonia (1.2%, 26/2188) were the predominantly detected pathogens in this study. Moreover, the co-infection was observed in 22 specimens. Notably, one COVID-19 case had a coexisting infection with human parainfluenza virus (4.2%, 1/24) and bocavirus was the most common virus tending to occur in co-infection with other respiratory pathogens. CONCLUSIONS: This study reveals the epidemiological features of common respiratory viruses and their clinical impact during the ongoing outbreak of COVID-19 in a mild epidemic area. The findings highlight the importance of understanding the transmission patterns of the common respiratory virus in COVID-19 regions, which can provide information support for the development of appropriate treatment plans and health policies, while eliminating unnecessary fear and tension.

A precision medicine approach to managing 2019 novel coronavirus pneumonia.

In December 2019, several patients with pneumonia of an unknown cause were detected in Wuhan, China. On 7 January 2020, the causal organism was identified as a new coronavirus, later named as the 2019 novel coronavirus (2019-nCoV). Genome sequencing found the genetic sequence of 2019-nCoV homologous to that of severe acute respiratory syndrome-associated coronavirus. As of 29 January 2020, the virus had been diagnosed in more than 7000 patients in China and 77 patients in other countries. It is reported that both symptomatic and asymptomatic patients with 2019-nCoV can play a role in disease transmission via airborne and contact. This finding has caused a great concern about the prevention of illness spread. The clinical features of the infection are not specific and are often indistinguishable from those of other respiratory infections, making it difficult to diagnose. Given that the virus has a strong ability to spread between individuals, it is of top priority to identify potential or suspected patients as soon as possible-or the virus may cause a serious pandemic. Therefore, a precision medicine approach to managing this disease is urgently needed for detecting and controlling the spread of the virus. In this article, we present such an approach to managing 2019-nCoV-related pneumonia based on the unique traits of the virus recently revealed and on our experience with coronaviruses at West China Hospital in Chengdu, China.