RNA based mNGS approach identifies a novel human coronavirus from two individual pneumonia cases in 2019 Wuhan outbreak

Ribonucleic acid genome mutations induced by the Casimir effect

In this paper, we investigate the Casimir effect within a virus RNA, particularizing the study to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Then, we discuss the possibility of occurring damage or mutation in its genome due to the presence of quantum vacuum fluctuations inside and around the RNA ribbon. For this, we consider the geometry and the nontrivial topology of the viral RNA as having a simple helical structure. We initially compute the non-thermal Casimir energy associated to that geometry, considering boundary conditions that constrain the zero point oscillations of a massless scalar field to the cylindrical cavity containing a helix pitch of RNA ribbon. Then we extend the obtained result to the electromagnetic field and, following, we calculate the probability of occurring damage or mutation in RNA by using the normalized inverse exponential distribution, which suppresses very low energies, and consider cutoff (threshold) energies corresponding to UV-A and UV-C rays, surely responsible by mutations. Then, by taking into account UV-A, we arrive at a mutation rate per base per infection cycle, which in the case of the SARS-CoV-2 is non-negligible. We find a maximum value of this mutation rate for an RNA ribbon radius, applying it for SARS-CoV-2, in particular. We also calculate a characteristic longitudinal oscillation frequency for the helix pitch value corresponding to the local minimum of the Casimir energy. Finally, we consider thermal fluctuations of classical and quantum nature and show that the corresponding probability of mutation is completely negligible for that virus. Therefore, we conclude that only the nontrivial topology and the geometric attributes of the RNA molecule contribute to the possible mutations caused by quantum vacuum fluctuations in the viral genome.

High-throughput sequencing approaches applied to SARS-CoV-2

High-throughput sequencing is crucial for surveillance and control of viral outbreaks. During the ongoing coronavirus disease 2019 (COVID-19) pandemic, advances in the high-throughput sequencing technology resources have enhanced diagnosis, surveillance, and vaccine discovery. From the onset of the pandemic in December 2019, several genome-sequencing approaches have been developed and supported across the major sequencing platforms such as Illumina, Oxford Nanopore, PacBio, MGI DNBSEQTM and Ion Torrent. Here, we share insights from the sequencing approaches developed for sequencing of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) between December 2019 and October 2022.

Radu E, Matei L, Maria Ruta S, Bleotu C. SARS-CoV-2 Variant Surveillance in Genomic Medicine Era

In the genomic medicine era, the emergence of SARS-CoV-2 was immediately followed by viral genome sequencing and world-wide sequences sharing. Almost in real-time, based on these sequences, resources were developed and applied around the world, such as molecular diagnostic tests, informed public health decisions, and vaccines. Molecular SARS-CoV-2 variant surveillance was a normal approach in this context yet, considering that the viral genome modification occurs commonly in viral replication process, the challenge is to identify the modifications that significantly affect virulence, transmissibility, reduced effectiveness of vaccines and therapeutics or failure of diagnostic tests. However, assessing the importance of the emergence of new mutations and linking them to epidemiological trend, is still a laborious process and faster phenotypic evaluation approaches, in conjunction with genomic data, are required in order to release timely and efficient control measures.

Analytical performance evaluation of Lumipulse® SARS-CoV-2 antigen assay in 392 asymptomatic patients

INTRODUCTION

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is one of the current public health care challenges. The main strategy adopted to prevent the spread of infection is the rapid identification of COVID-19-positive subjects. The aim of this study was to compare the performance of Lumipulse® antigen immunoassay with the real-time RT-PCR, the gold standard for the diagnosis of SARS-CoV-2 infection, in a strictly selected asymptomatic population.

MATERIALS AND METHODS

A total of 392 consecutive oro-nasopharyngeal swabs were collected from patients with no symptoms related to COVID-19 at the Emergency Department of AORN Sant'Anna e San Sebastiano, Caserta, Italy to evaluate the analytical performance of Lumipulse® SARS-CoV-2 antigen compared to qualitative real-time RT-PCR in asymptomatic patients.

RESULTS

Lumipulse® SARS-CoV-2 antigen assay shows an overall agreement rate of 97% with a sensitivity of 96% and a specificity of 98%, with a PPV and NPV of 97%. The sensitivity varies according to the cycle threshold (C_t )-value reaching 100% and 86% with 15 < C_t  < 25 and C_t  ≥ 25, respectively. The ROC analysis yielded an AUC value of 0.98, suggesting that the antigen test may accurately detect SARS-CoV-2.

CONCLUSION

Our data showed that Lumipulse® SARS-CoV-2 antigen assay might be an efficient tool in the identification and limitation of SARS-CoV-2 transmission in large asymptomatic populations.

Identifying promising druggable binding sites and their flexibility to target the receptor-binding domain of SARS-CoV-2 spike protein

The spike protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is crucial for viral infection. The interaction of its receptor-binding domain (RBD) with the human angiotensin-converting enzyme 2 (ACE2) protein is required for the virus to enter the host cell. We identified RBD binding sites to block its function with inhibitors by combining the protein structural flexibility with machine learning analysis. Molecular dynamics simulations were performed on unbound or ACE2-bound RBD conformations. Pockets estimation, tracking and druggability prediction were performed on a large sample of simulated RBD conformations. Recurrent druggable binding sites and their key residues were identified by clustering pockets based on their residue similarity. This protocol successfully identified three druggable sites and their key residues, aiming to target with inhibitors for preventing ACE2 interaction. One site features key residues for direct ACE2 interaction, highlighted using energetic computations, but can be affected by several mutations of the variants of concern. Two highly druggable sites, located between the spike protein monomers interface are promising. One weakly impacted by only one Omicron mutation, could contribute to stabilizing the spike protein in its closed state. The other, currently not affected by mutations, could avoid the activation of the spike protein trimer.

Genetic characterization of human adenoviruses in patients using metagenomic next-generation sequencing in Hubei, China, from 2018 to 2019

Objectives

This study aimed to characterize the genomic epidemiology of human adenoviruses (HAdVs) in Hubei, China, using metagenomic next-generation sequencing (mNGS).

Methods

In total, 25 HAdV-positive samples collected from 21 pediatric patients were sequenced and subjected to mNGS using the NextSeq 550 and GenoLab M sequencing platforms. The metagenomic data were assembled de novo for molecular typing, phylogenetic and recombination analyzes.

Results

We assembled 50 HAdV genomes, 88% (22/25) genomes from GenoLab M, and 84% (21/25) genomes from NextSeq 550 have perfect alignments to reference genomes with greater than 90%. The most fully assembled 25 genomes were categorized into 7 HAdV genotypes, the most abundant of which were HAdV-B3 (9/25) and HAdV-C2 (6/25). Phylogenetic analyzes revealed that the newly isolated HAdV-B3 strains diverged into separate clusters according to their genotypes. Vigilance is needed that HAdV-B3 isolates have begun to form new distinct clusters. High nucleotide identity was observed in the whole genome level within the same HAdV genotypes, while marked differences of three capsid genes across HAdV genotypes were noted. The high nucleotide diversity regions were concordant with the reported hypervariable regions. Further, three recombinant strains were identified: S64 and S71 originated from the parental strains HAdV-B14 and HAdV-B11, and S28 originated from HAdV-C1, HAdV-C5, and HAdV-CBJ113. GenoLab M and NextSeq 550 showed comparable performance with respect to data yield, duplication rate, human ratio, and assembly completeness.

Conclusion

The sequencing quality and assembly accuracy showed that mNGS assembled genomes can be used for subsequently HAdV genotyping and genomic characterization. The high nucleotide diversity of capsid genes and high frequency of recombination events has highlighted the necessity for HAdV epidemiological surveillance in China.

Research Progress on the detection methods of porcine reproductive and respiratory syndrome virus

Porcine reproductive and respiratory syndrome virus (PRRSV) causes clinical syndromes typified as reproductive disorders in sows and respiratory diseases in piglets. PRRSV remains one of the most prevalent pathogens affecting the pig industry, because of its complex infection profile and highly heterogeneous genetic and recombination characteristics. Therefore, a rapid and effective PRRSV detection method is important for the prevention and control of PRRS. With extensive in-depth research on PRRSV detection methods, many detection methods have been improved and promoted. Laboratory methods include techniques based on virus isolation (VI), enzyme-linked immunosorbent assays (ELISA), indirect immunofluorescence assays (IFA), immunoperoxidase monolayer assays (IPMA), polymerase chain reaction (PCR), quantitative real-time PCR (qPCR), digital PCR (dPCR), loop-mediated isothermal amplification (LAMP), recombinase polymerase amplification (RPA), clustered regularly interspaced short palindromic repeats (CRISPR), metagenomic next-generation sequencing (mNGS), and other methods. This study reviews the latest research on improving the main PRRSV detection methods and discusses their advantages and disadvantages.

New Short RNA Motifs Potentially Relevant in the SARS-CoV-2 Genome

Background

The coronavirus disease has led to an exhaustive exploration of the SARS-CoV-2 genome. Despite the amount of information accumulated, the prediction of short RNA motifs encoding peptides mediating protein-protein or protein-drug interactions has received limited attention.

Objective

The study aims to predict short RNA motifs that are interspersed in the SARS-CoV-2 genome.

Methods

A method in which 14 trinucleotide families, each characterized by being composed of triplets with identical nucleotides in all possible configurations, was used to find short peptides with biological relevance. The novelty of the approach lies in using these families to search how they are distributed across genomes of different CoV genera and then to compare the distributions of these families with each other.

Results

We identified distributions of trinucleotide families in different CoV genera and also how they are related, using a selection criterion that identified short RNA motifs. The motifs were reported to be conserved in SARS-CoVs; in the remaining CoV genomes analysed, motifs contained, exclusively, different configurations of the trinucleotides A, T, G and A, C, G. Eighty-eight short RNA motifs, ranging in length from 12 to 49 nucleotides, were found: 50 motifs in the 1a polyprotein-encoding orf, 27 in the 1b polyprotein-encoding orf, 5 in the spike-encoding orf, and 6 in the nucleocapsid-encoding orf. Although some motifs (~27%) were found to be intercalated or attached to functional peptides, most of them have not yet been associated with any known functions.

Conclusion

Some of the trinucleotide family distributions in different CoV genera are not random; they are present in short peptides that, in many cases, are intercalated or attached to functional sites of the proteome.

Investigating the binding affinity of andrographolide against human SARS-CoV-2 spike receptor-binding domain through docking and molecular dynamics simulations

SARS-CoV-2 is a positive-sense single-stranded RNA virus that causes a deadly coronavirus disease (COVID-19) in humans. The infection of SARS-CoV-2 in humans involves a viral surface spike glycoprotein containing the receptor-binding domain (RBD). The interactions of SARS-CoV-2 with the host angiotensin-converting enzyme 2 (ACE2) receptor are mediated by RBD. It binds to the host ACE2 and influences viral replication and disease pathogenesis. Therefore, targeting the RBD to prevent SARS-CoV-2 infections is of utmost importance. In this study, we used docking and molecular dynamics simulations to understand the binding effect of andrographolide on the SARS-CoV-2 spike protein. During docking, a strong binding affinity was observed between the ligand and the target receptor protein. MD results demonstrated higher conformational fluctuations in the ligand-free protein compared to the bound form. Several residues in the active sites make conformational rearrangements for the S protein to interact with the ligand. While RBD experiences conformational transition to gain more stability upon binding with the ligand. This binding is strengthened via several non-covalent interactions that make the complex structure more stable with higher binding affinity. Overall findings of the study may shed some valuable insights concerning the development of potential therapeutics in the strategies for COVID-19 prevention.

Advances in the oral microbiota and rapid detection of oral infectious diseases

Several studies have shown that the dysregulation of the oral microbiota plays a crucial role in human health conditions, such as dental caries, periodontal disease, oral cancer, other oral infectious diseases, cardiovascular diseases, diabetes, bacteremia, and low birth weight. The use of traditional detection methods in conjunction with rapidly advancing molecular techniques in the diagnosis of harmful oral microorganisms has expanded our understanding of the diversity, location, and function of the microbiota associated with health and disease. This review aimed to highlight the latest knowledge in this field, including microbial colonization; the most modern detection methods; and interactions in disease progression. The next decade may achieve the rapid diagnosis and precise treatment of harmful oral microorganisms.

Vitamin D and estrogen steroid hormones and their immunogenetic roles in Infectious respiratory (TB and COVID-19) diseases

The role of steroid hormones against infectious diseases has been extensively studied. From immunomodulatory action to direct inhibition of microorganism growth, hormones D3 (VD3) and 17β-estradiol (E2), and the genetic pathways modulated by them, are key targets for a better understanding pathogenesis of infectious respiratory diseases (IRD) such as tuberculosis (TB) and the coronavirus disease-19 (COVID-19). Currently, the world faces two major public health problems, the outbreak of COVID-19, accounting for more than 6 million so far, and TB, more than 1 million deaths per year. Both, although resulting from different pathogens, the Mtb and the SARS-CoV-2, respectively, are considered serious and epidemic. TB and COVID-19 present similar infection rates between men and women, however the number of complications and deaths resulting from the two infections is higher in men when compared to women in childbearing age, which may indicate a role of the sex hormone E2 in the context of these diseases. E2 and VD3 act upon key gene pathways as important immunomodulatory players and supporting molecules in IRDs. This review summarizes the main roles of these hormones (VD3 and E2) in modulating immune and inflammatory responses and their relationship with TB and COVID-19.

Insight into SARS-CoV-2 Omicron variant immune escape possibility and variant independent potential therapeutic opportunities

The Omicron, the latest variant of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), was first detected in November 2021 in Botswana, South Africa. Compared to other variants of SARS-CoV-2, the Omicron is the most highly mutated, with 50 mutations throughout the genome, most of which are in the spike (S) protein. These mutations may help the Omicron to evade host immunity against the vaccine. Epidemiological studies suggest that Omicron is highly infectious and spreads rapidly, but causes significantly less severe disease than the wild-type strain and the other variants of SARS-CoV-2. With the increased transmissibility and a higher rate of re-infection, Omicron has now become a dominant variant worldwide and is predicted to be able to evade vaccine-induced immunity. Several clinical studies using plasma samples from individuals receiving two doses of US Food and Drugs Administration (FDA)-approved COVID-19 vaccines have shown reduced humoral immune response against Omicron infection, but T cell-mediated immunity was well preserved. In fact, T cell-mediated immunity protects against severe disease, and thus the disease caused by Omicron remains mild. In this review, I surveyed the current status of Omicron variant mutations and mechanisms of immune response in the context of immune escape from COVID-19 vaccines. I also discuss the potential implications of therapeutic opportunities that are independent of SARS-CoV-2 variants, including Omicron. A better understanding of vaccine-induced immune responses and variant-independent therapeutic interventions that include potent antiviral, antioxidant, and anti-cytokine activities may pave the way to reducing Omicron-related COVID-19 complications, severity, and mortality. Collectively, these insights point to potential research gaps and will aid in the development of new-generation COVID-19 vaccines and antiviral drugs to combat Omicron, its sublineages, or upcoming new variants of SARS-CoV-2.

Vaccination with Span, an antigen guided by SARS-CoV-2 S protein evolution, protects against challenge with viral variants in mice

SARS-CoV-2 continues to accumulate mutations to evade immunity, leading to breakthrough infections after vaccination. How researchers can anticipate the evolutionary trajectory of the virus in advance in the design of next-generation vaccines requires investigation. Here, we performed a comprehensive study of 11,650,487 SARS-CoV-2 sequences, which revealed that the SARS-CoV-2 spike (S) protein evolved not randomly but into directional paths of either high infectivity plus low immune resistance or low infectivity plus high immune resistance. The viral infectivity and immune resistance of variants are generally incompatible, except for limited variants such as Beta and Kappa. The Omicron variant has the highest immune resistance but showed high infectivity in only one of the tested cell lines. To provide cross-clade immunity against variants that undergo diverse evolutionary pathways, we designed a new pan-vaccine antigen (S_pan). S_pan was designed by analyzing the homology of 2675 SARS-CoV-2 S protein sequences from the NCBI database before the Delta variant emerged. The refined S_pan protein harbors high-frequency residues at given positions that reflect cross-clade generality in sequence evolution. Compared with a prototype wild-type (S_wt) vaccine, which, when administered to mice, induced serum with decreased neutralization activity against emerging variants, S_pan vaccination of mice elicited broad immunity to a wide range of variants, including those that emerged after our design. Moreover, vaccinating mice with a heterologous S_pan booster conferred complete protection against lethal infection with the Omicron variant. Our results highlight the importance and feasibility of a universal vaccine to fight against SARS-CoV-2 antigenic drift.

The performance of metagenomic next-generation sequencing in diagnosing pulmonary infectious diseases using authentic clinical specimens: The Illumina platform versus the Beijing Genomics Institute platform

Introduction: Metagenomic next-generation sequencing (mNGS) has been increasingly used to detect infectious organisms and is rapidly moving from research to clinical laboratories. Presently, mNGS platforms mainly include those from Illumina and the Beijing Genomics Institute (BGI). Previous studies have reported that various sequencing platforms have similar sensitivity in detecting the reference panel that mimics clinical specimens. However, whether the Illumina and BGI platforms provide the same diagnostic performance using authentic clinical samples remains unclear. Methods: In this prospective study, we compared the performance of the Illumina and BGI platforms in detecting pulmonary pathogens. Forty-six patients with suspected pulmonary infection were enrolled in the final analysis. All patients received bronchoscopy, and the specimens collected were sent for mNGS on the two different sequencing platforms. Results: The diagnostic sensitivity of the Illumina and BGI platforms was notably higher than that of conventional examination (76.9% vs. 38.5%, p < 0.001; 82.1% vs. 38.5%, p < 0.001; respectively). The sensitivity and specificity for pulmonary infection diagnosis were not significantly different between the Illumina and BGI platforms. Furthermore, the pathogenic detection rate of the two platforms were not significantly different. Conclusion: The Illumina and BGI platforms exhibited similar diagnostic performance for pulmonary infectious diseases using clinical specimens, and both are superior to conventional examinations.

Associated factors of burnout among Chinese vaccination staff during COVID-19 epidemic: A cross-sectional study

Objective

During the COVID-19 epidemic, vaccination staff had three main aspects of work: routine vaccination for children and adults, COVID-19 vaccination and COVID-19 prevention and control. All these works significantly increased the workload of vaccination staff. This study aimed to investigate the prevalence and influencing factors of burnout among vaccination staff in Hangzhou, China.

Methods

A total of 501 vaccination staff from 201 community/township healthcare centers in Hangzhou were recruited using a cross-sectional survey through WeChat social platform. The Maslach Burnout Inventory-General Scale (MBI-GS) was used to assess the level of burnout. Descriptive statistics were made on the characteristics of participants. Univariate analysis using the chi-square test and multivariable analysis using binary logistic regression were conducted to determine the relative predictors of burnout. Univariate analysis and multiple linear regression were used to determine the relative predictors of exhaustive emotion, cynicism, and personal accomplishment.

Results

During the COVID-19 pandemic, 20.8% of the vaccination staff experienced burnout. Educational level above undergraduate education level, medium professional title, and more working time in COVID-19 vaccination work reported a higher degree of job burnout. The vaccination staff was experiencing a high degree of exhaustive emotion, cynicism, and low personal accomplishment. Professional title, working place, and working time for COVID-19 vaccination were associated with exhaustive emotion and cynicism. Professional title and participation time for COVID-19 prevention and control were associated with personal accomplishment.

Conclusions

Our findings suggest that the prevalence rate of burnout is high among vaccination staff during the COVID-19 pandemic, especially with a low level of personal accomplishment. Psychological intervention for vaccination staff is urgently needed.

Analysis of bronchoalveolar lavage fluid metatranscriptomes among patients with COVID-19 disease

To better understand the potential relationship between COVID-19 disease and hologenome microbial community dynamics and functional profiles, we conducted a multivariate taxonomic and functional microbiome comparison of publicly available human bronchoalveolar lavage fluid (BALF) metatranscriptome samples amongst COVID-19 (n = 32), community acquired pneumonia (CAP) (n = 25), and uninfected samples (n = 29). We then performed a stratified analysis based on mortality amongst the COVID-19 cohort with known outcomes of deceased (n = 10) versus survived (n = 15). Our overarching hypothesis was that there are detectable and functionally significant relationships between BALF microbial metatranscriptomes and the severity of COVID-19 disease onset and progression. We observed 34 functionally discriminant gene ontology (GO) terms in COVID-19 disease compared to the CAP and uninfected cohorts, and 21 GO terms functionally discriminant to COVID-19 mortality (q < 0.05). GO terms enriched in the COVID-19 disease cohort included hydrolase activity, and significant GO terms under the parental terms of biological regulation, viral process, and interspecies interaction between organisms. Notable GO terms associated with COVID-19 mortality included nucleobase-containing compound biosynthetic process, organonitrogen compound catabolic process, pyrimidine-containing compound biosynthetic process, and DNA recombination, RNA binding, magnesium and zinc ion binding, oxidoreductase activity, and endopeptidase activity. A Dirichlet multinomial mixtures clustering analysis resulted in a best model fit using three distinct clusters that were significantly associated with COVID-19 disease and mortality. We additionally observed discriminant taxonomic differences associated with COVID-19 disease and mortality in the genus Sphingomonas, belonging to the Sphingomonadacae family, Variovorax, belonging to the Comamonadaceae family, and in the class Bacteroidia, belonging to the order Bacteroidales. To our knowledge, this is the first study to evaluate significant differences in taxonomic and functional signatures between BALF metatranscriptomes from COVID-19, CAP, and uninfected cohorts, as well as associating these taxa and microbial gene functions with COVID-19 mortality. Collectively, while this data does not speak to causality nor directionality of the association, it does demonstrate a significant relationship between the human microbiome and COVID-19. The results from this study have rendered testable hypotheses that warrant further investigation to better understand the causality and directionality of host-microbiome-pathogen interactions.

Novel coronavirus mutations: Vaccine development and challenges

The ongoing global pandemic of novel coronavirus pneumonia (COVID-19) caused by the SARS-CoV-2 has a significant impact on global health and economy system. In this context, there have been some landmark advances in vaccine development. Over 100 new coronavirus vaccine candidates have been approved for clinical trials, with ten WHO-approved vaccines including four inactivated virus vaccines, two mRNA vaccines, three recombinant viral vectored vaccines and one protein subunit vaccine on the "Emergency Use Listing". Although the SARS-CoV-2 has an internal proofreading mechanism, there have been a number of mutations emerged in the pandemic affecting its transmissibility, pathogenicity and immunogenicity. Of these, mutations in the spike (S) protein and the resultant mutant variants have posed new challenges for vaccine development and application. In this review article, we present an overview of vaccine development, the prevalence of new coronavirus variants and their impact on protective efficacy of existing vaccines and possible immunization strategies coping with the viral mutation and diversity.

A brief review on the validation of biology methods for COVID-19 detection

The COVID-19 global pandemic has been going on for more than two years, and the evolution of SARS-CoV-2 with many variants of concern still poses a risk to public health. Sufficient access to qualified and validated testing plays an important role in detecting and alerting trends of the pandemic and provides evidence for making decisions in preventive strategies and policies. Depending on the method of testing and laboratory conditions, validation parameters (i.e., analytical sensitivity, limit of detection, diagnostic sensitivity, analytical specificity, diagnostic specificity, repeatability, reproducibility, robustness, positive predictive value, negative predictive value, applicability, practicability, and time to results) can be very different. With three main types of COVID-19 detection kits available, comprising nucleic acid, serological, and antigen detection, the kind of validation parameters that should be used becomes a complicated consideration and takes time to assess. Our review provides valuable and comprehensive information for laboratories in the assessment and selection of the optimal parameters to validate new COVID-19 test kits.

The COVID-19 Pandemic and Explaining Outcomes in Africa: Could Genomic Variation Add to the Debate?

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the etiological agent of COVID-19, emanated from the Wuhan Province in China and rapidly spread across the globe causing extensive morbidity and mortality rate, and affecting the global economy and livelihoods. Contrary to early predictions of "body bags" across Africa, the African COVID-19 pandemic was marked by apparent low case numbers and an overall mortality rate when compared with the other geographical regions. Factors used to describe this unexpected pattern included a younger population, a swifter and more effective national health policy, limited testing capacities, and the possibility of inadequate reporting of the cases, among others. However, despite genomics contributing to interindividual variations in many diseases across the world, there are inadequate genomic and multiomics data on COVID-19 in Africa that prevent richer transdisciplinary discussions on the contribution of genomics to the spread of COVID-19 pandemic. To invite future debates on comparative studies of COVID-19 genomics and the pandemic spread around the world regions, this expert review evaluates the reported frequency distribution of genetic variants in candidate genes that are likely to affect COVID-19 infection dynamics/disease outcomes. We propose here that genomic variation should be considered among the many factors determining the COVID-19 infection and its outcomes in African populations and across the world.

Novel application of metagenomics for the strain-level detection of bacterial contaminants within non-sterile industrial products - a retrospective, real-time analysis

The home and personal care (HPC) industry generally relies on initial cultivation and subsequent biochemical testing for the identification of microorganisms in contaminated products. This process is slow (several days for growth), labour intensive, and misses organisms which fail to revive from the harsh environment of preserved consumer products. Since manufacturing within the HPC industry is high-throughput, the process of identification of microbial contamination could benefit from the multiple cultivation-independent methodologies that have developed for the detection and analysis of microbes. We describe a novel workflow starting with automated DNA extraction directly from a HPC product, and subsequently applying metagenomic methodologies for species and strain-level identification of bacteria. The workflow was validated by application to a historic microbial contamination of a general-purpose cleaner (GPC). A single strain of Pseudomonas oleovorans was detected metagenomically within the product. The metagenome mirrored that of a contaminant isolated in parallel by a traditional cultivation-based approach. Using a dilution series of the incident sample, we also provide evidence to show that the workflow enables detection of contaminant organisms down to 100 CFU/ml of product. To our knowledge, this is the first validated example of metagenomics analysis providing confirmatory evidence of a traditionally isolated contaminant organism, in a HPC product.

RT-LAMP in SARS-CoV-2 detection: point to improve primer designing and decrease molecular diagnosis pitfalls

BACKGROUND

Due to the high transmission rate of SARS-CoV-2, diagnostic tests have become tools for identifying patients. The key points were the virus genomes survey to design RT-LAMP primers; comparing the sensitivity and specificity of RT-LAMP and RT-qPCR; and determining the relationship among clinical symptoms, CT scan, RT-qPCR, and RT-LAMP results.

METHODS

This cohort study included 444 symptomatic patients. The specificity and sensitivity of RT-LAMP were assayed. The five statistical models, simultaneously, by RapidMiner to find the best method for detecting the virus were done through the correlation between the clinical symptoms, RT-LAMP, RT-qPCR, and CT scan results. The chi-square test by SPSS 26.0 was used to calculate kappa agreement.

RESULTS

The virus genome was detected in all the positive samples (198) by RT-qPCR and RT-LAMP. In addition, 246 samples were negative by RT-qPCR, while 88 were positive by RT-LAMP. Data mining analysis indicated that there were most associations between the RT-LAMP and CT scan data compared to RT-qPCR and CT scan data.

CONCLUSIONS

RT-LAMP could detect SARS-CoV-2 with great simplicity, speed, and cheapness. Therefore, it is logical to screen, a large number of patients by RT-LAMP, and then RT-qPCR can be used on the limited samples.

Diagnostic value of bronchoalveolar lavage fluid metagenomic next-generation sequencing in pediatric pneumonia

OBJECTIVES

The aim of this study was to evaluate the diagnostic value of bronchoalveolar lavage fluid (BALF) metagenomic next-generation sequencing (mNGS) versus conventional microbiological tests (CMTs) for pediatric pneumonia.

METHODS

This retrospective observational study enrolled 103 children who were diagnosed with pneumonia and hospitalized at Hubei Maternity and Child Health Care Hospital between 15 October 2020 and 15 February 2022. The pneumonia diagnosis was based on clinical manifestations, lung imaging, and microbiological tests. Pathogens in the lower respiratory tract were detected using CMTs and BALF mNGS (of DNA and RNA). The diagnostic performance of BALF mNGS was compared with that of CMTs.

RESULTS

In 96 patients, pathogens were identified by microbiological tests. The overall pathogen detection rate of mNGS was significantly higher than that of CMTs (91.3% vs. 59.2%, p = 0.000). The diagnostic performance of mNGS varied for different pathogens; however, its sensitivity and accuracy for diagnosing bacterial and viral infections were both higher than those of CMTs (p = 0.000). For the diagnosis of fungi, the sensitivity of mNGS (87.5%) was higher than that of CMTs (25%); however, its specificity and accuracy were lower than those of CMTs (p < 0.01). For the diagnosis of Mycoplasma pneumoniae, the specificity (98.8%) and accuracy (88.3%) of mNGS were high; however, its sensitivity (42.1%) was significantly lower than that of CMTs (100%) (p = 0.001). In 96 patients with definite pathogens, 52 cases (50.5%) were infected with a single pathogen, while 44 cases (42.7%) had polymicrobial infections. Virus-bacteria and virus-virus co-infections were the most common. Staphylococcus aureus, Haemophilus influenzae, rhinovirus, cytomegalovirus, parainfluenza virus, and fungi were more likely to be associated with polymicrobial infections.

CONCLUSIONS

BALF mNGS improved the detection rate of pediatric pneumonia, especially in mixed infections. The diagnostic performance of BALF mNGS varies according to pathogen type. mNGS can be used to supplement CMTs. A combination of mNGS and CMTs may be the best diagnostic strategy.

Insight into genomic organization of pathogenic coronaviruses, SARS-CoV-2: Implication for emergence of new variants, laboratory diagnosis and treatment options

SARS-CoV-2 is a novel zoonotic positive-sense RNA virus (ssRNA+) belonging to the genus beta coronaviruses (CoVs) in the Coronaviridae family. It is the causative agent for the outbreak of the disease, COVID-19. It is the third CoV causing pneumonia around the world in the past 2 decades. To date, it has caused significant deaths worldwide. Notably, the emergence of new genetic variants conferring efficient transmission and immune evasion remained a challenge, despite the reduction in the number of death cases, owing to effective vaccination regimen (boosting) and safety protocols. Thus, information harnessed from SARS-CoV-2 genomic organization is indispensable for seeking laboratory diagnosis and treatment options. Here in, we review previously circulating variants of SARS-CoV-2 designated variant of concern (VOC) including the Alpha (United Kingdom), Beta (South Africa), Gamma (Brazil), Delta (India), and recently circulating VOC, Omicron (South Africa) and its divergent subvariants (BA.1, BA.2, BA.3, BA.2.12.1, BA.4 and BA.5) with BA.5 currently becoming dominant and prolonging the COVID pandemic. In addition, we address the role of computational models for mutagenesis analysis which can predict important residues that contribute to transmissibility, virulence, immune evasion, and molecular detections of SARS-CoV-2. Concomitantly, the importance of harnessing the immunobiology of SARS-CoV-2 and host interaction for therapeutic purpose; and use of an in slilico based biocomputational approaches to achieve this purpose via predicting novel therapeutic agents targeting PRR such as toll like receptor, design of universal vaccine and chimeric antibodies tailored to the emergent variant have been highlighted.

Biofilms possibly harbor occult SARS-CoV-2 may explain lung cavity, re-positive and long-term positive results

During the COVID-19 pandemic, there have been an increasing number of COVID-19 patients with cavitary or cystic lung lesions, re-positive or long-term positive nucleic acid tests, but the mechanism is still unclear. Lung cavities may appear at long time interval from initial onset of coronavirus infection, generally during the absorption phase of the disease. The main histopathological characteristic is diffuse alveolar damage and may have more severe symptoms after initial recovery from COVID-19 and an increased mortality rate. There are many possible etiologies of pulmonary cavities in COVID-19 patients and we hypothesize that occult SARS-CoV-2, in the form of biofilm, is harbored in the airway lacuna with other pathogenic microorganisms, which may be the cause of pulmonary cavities and repeated and long-term positive nucleic acid tests.

Insight into the Relationship between Oral Microbiota and the Inflammatory Bowel Disease

Inflammatory bowel disease has been a growing concern of lots of people globally, including both adults and children. As a chronic inflammatory disease of the intestine, even though the etiology of inflammatory bowel disease is still unclear, the available evidence from clinic observations has suggested a close association with microorganisms. The oral microbiota possesses the characteristics of a large number and abundant species, second only to the intestinal microbiota in the human body; as a result, it successfully attracts the attention of researchers. The highly diverse commensal oral microbiota is not only a normal part of the oral cavity but also has a pronounced impact on the pathophysiology of general health. Numerous studies have shown the potential associations between the oral microbiota and inflammatory bowel disease. Inflammatory bowel disease can affect the composition of the oral microbiota and lead to a range of oral pathologies. In turn, there are a variety of oral microorganisms involved in the development and progression of inflammatory bowel disease, including Streptococcus spp., Fusobacterium nucleatum, Porphyromonas gingivalis, Campylobacter concisus, Klebsiella pneumoniae, Saccharibacteria (TM7), and Candida albicans. Based on the above analysis, the purpose of this review is to summarize this relationship of mutual influence and give further insight into the detection of flora as a target for the diagnosis and treatment of inflammatory bowel disease to open up a novel approach in future clinical practice.

ACE2-containing defensosomes serve as decoys to inhibit SARS-CoV-2 infection

Extracellular vesicles of endosomal origin, exosomes, mediate intercellular communication by transporting substrates with a variety of functions related to tissue homeostasis and disease. Their diagnostic and therapeutic potential has been recognized for diseases such as cancer in which signaling defects are prominent. However, it is unclear to what extent exosomes and their cargo inform the progression of infectious diseases. We recently defined a subset of exosomes termed defensosomes that are mobilized during bacterial infection in a manner dependent on autophagy proteins. Through incorporating protein receptors on their surface, defensosomes mediated host defense by binding and inhibiting pore-forming toxins secreted by bacterial pathogens. Given this capacity to serve as decoys that interfere with surface protein interactions, we investigated the role of defensosomes during infection by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), the etiological agent of Coronavirus Disease 2019 (COVID-19). Consistent with a protective function, exosomes containing high levels of the viral receptor ACE2 in bronchoalveolar lavage fluid (BALF) from critically ill COVID-19 patients was associated with reduced intensive care unit (ICU) and hospitalization times. We found ACE2+ exosomes were induced by SARS-CoV-2 infection and activation of viral sensors in cell culture, which required the autophagy protein ATG16L1, defining these as defensosomes. We further demonstrate that ACE2+ defensosomes directly bind and block viral entry. These findings suggest that defensosomes may contribute to the antiviral response against SARS-CoV-2 and expand our knowledge on the regulation and effects of extracellular vesicles during infection.

Autophagy proteins mediate the production of extracellular vesicles termed defensosomes in response to innate immune ligands. This study reveals that ACE2-containing defensosomes bind and inhibit SARS-CoV-2 infection, and are associated with reduced length of hospital stay for patients with COVID-19.

Advantages and challenges of metagenomic sequencing for the diagnosis of pulmonary infectious diseases

Objective

We aim to familiarize the application status of metagenomic sequencing in diagnosing pulmonary infections, to compare metagenomic sequencing with traditional diagnostic methods, to conclude the advantages and limitations of metagenomic sequencing, and to provide some advice for clinical practice and some inspiration for associated researches.

Data Sources

The data were obtained from peer‐reviewed literature, white papers, and meeting reports.

Results

This review focused on the applications of untargeted metagenomic sequencing in lungs infected by bacteria, viruses, fungi, chlamydia pneumoniae, Mycoplasma pneumoniae, parasites, and other pathogens. Compared with conventional diagnostic methods, metagenomic sequencing is better in detecting novel, rare, and unexpected pathogens and being applied in co‐infections. Meanwhile, it can also provide more comprehensive information about pathogens. However, metagenomic sequencing still has limitations. Also, the situations that should be applied in and how the results should be interpreted are discussed in this review.

Conclusion

Metagenomic sequencing improves efficiency to identify pathogens compared with traditional diagnostic methods and can be applied in clinical diagnosis. However, the technology of metagenomic sequencing still needs to be improved. Also, clinicians should learn more about when to use metagenomic sequencing and how to interpret its results.

Non-PCR Ultrasensitive Detection of Viral RNA by a Nanoprobe-Coupling Strategy: SARS-CoV-2 as an Example

Developing efficient and highly sensitive diagnostic techniques for early detections of pathogenic viruses such as Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) is vitally important for preventing its widespread. However, the conventional polymerase chain reaction (PCR)-based detection features high complexity, excessive time-consumption, and labor-intensiveness, while viral protein-based detections suffer from moderate sensitivity and specificity. Here, a non-PCR but ultrasensitive viral RNA detection strategy is reported based on a facile nanoprobe-coupling strategy without enzymatic amplification, wherein PCR-induced bias and other shortcomings are successfully circumvented. This approach endows the viral RNA detection with ultra-low background to maximum signal ratio in the linear signal amplification by using Au nanoparticles as reporters. The present strategy exhibits 100% specificity toward SARS-CoV-2 N gene, and ultrasensitive detection of as low as 52 cp mL-1 of SARS-CoV-2 N gene without pre-PCR amplification. This approach presents a novel ultrasensitive tool for viral RNA detections for fighting against COVID-19 and other types of pathogenic virus-caused diseases.

SARS-CoV-2 infection: Pathogenesis, Immune Responses, Diagnosis

COVID-19 has emerged as the most alarming infection of the present time instigated by the virus SARS-CoV-2. In spite of advanced research technologies, the exact pathophysiology and treatment of the condition still need to be explored. However, SARS-CoV-2 has several structural and functional similarities that resemble SARS-CoV and MERS-CoV which may be beneficial in exploring the possible treatment and diagnostic strategies for SARS-CoV-2. This review discusses the pathogen phenotype, genotype, replication, pathophysiology, elicited immune response and emerging variants of SARS-CoV-2 and their similarities with other similar viruses. SARS-CoV-2 infection is detected by a number of diagnostics techniques, their advantages and limitations are also discussed in detail. The review also focuses on nanotechnology-based easy and fast detection of SARS-CoV-2 infection. Various pathways which might play a vital role during SARS-CoV-2 infection have been elaborately discussed since immune response plays a major role during viral infections.

A Preliminary Study about the Role of Reactive Oxygen Species and Inflammatory Process after COVID-19 Vaccination and COVID-19 Disease

During the last couple of critical years, worldwide, there have been more than 550 million confirmed cases of COVID-19, including more than 6 million deaths (reported by the WHO); with respect to these cases, several vaccines, mainly mRNA vaccines, seem to prevent and protect from SARS-CoV-2 infection. We hypothesize that oxidative stress is one of the key factors playing an important role in both the generation and development of various kinds of disease, as well as antibody generation, as many biological paths can generate reactive oxygen species (ROS), and cellular activities can be modulated when ROS/antioxidant balance is interrupted. A pilot study was conducted in two stages during the COVID-19 pandemic in 2021 involving 222 participants between the ages of 26 and 66 years. ROS levels were measured before an after vaccination in the blood samples of 20 individuals who were vaccinated with two doses of mRNA vaccine, and an increase in ROS levels was observed after the first dose, with no modifications observed until the day before the second vaccination dose. A statistically significant difference (p < 0.001) was observed between time points 3 and 4 (before and after second dose), when participants were vaccinated for the second time, and ROS levels decreased from 21,758 to 17,580 a.u. In the second stage, blood was collected from 28 participants 45 days after COVID-19 infection (Group A), from 131 participants 45 days after receiving two doses of mRNA vaccine against COVID-19 (Group B), and from 13 healthy individuals as a control group (Group C). Additionally, antibodies levels were measured in all groups to investigate a possible correlation with ROS levels. A strong negative correlation was found between free radicals and disease antibodies in Group A (r = −0.45, p = 0.001), especially in the male subgroup (r = −0.88, p = 0.001), as well as in the female subgroup (r = −0.24, p < 0.001). Furthermore, no significant correlation (only a negative trend) was found with antibodies derived from vaccination in Group B (r = −0.01), and a negative trend was observed in the female subgroup, whereas a positive trend was observed in the male subgroup.

A gold nanoparticle-protein G electrochemical affinity biosensor for the detection of SARS-CoV-2 antibodies: a surface modification approach

As COVID-19 waves continue to spread worldwide, demand for a portable, inexpensive and convenient biosensor to determine community immune/infection status is increasing. Here we describe an impedance-based affinity biosensor using Interdigitated Electrode (IDE) arrays to detect antibodies to SARS-CoV-2 in serum. We created the biosensor by functionalizing the IDEs' surface with abaculaovirus-expressed and purified Spike (S) protein to bind anti-SARS CoV-2antibodies. Gold nanoparticles (GNP) fused to protein G were used to probe for bound antibodies. An ELISA assay using horseradish peroxidase-protein G to probe for bound IgG confirmed that the purified S protein bound a commercial source of anti-SARS-CoV-2 antibodies specifically and bound anti-SARS-CoV-2 antibodies in COVID-19 positive serum. Then we demonstrated that our biosensor could detect anti-SARS-CoV-2 antibodies with 72% sensitivity in 2 h. Using GNP-protein G, the affinity biosensor had increased impedance changes with COVID-19positive serum and minimal or decreased impedance changes with negative serum. This demonstrated that our biosensor could discriminate between COVID-19 positive and negative sera, which were further improved using poly(vinyl alcohol)as a blocking agent.

Clinical evaluation of metagenomic next-generation sequencing for detecting pathogens in bronchoalveolar lavage fluid collected from children with community-acquired pneumonia

This study is to evaluate the usefulness of pathogen detection using metagenomic next-generation sequencing (mNGS) on bronchoalveolar lavage fluid (BALF) specimens from children with community-acquired pneumonia (CAP). We retrospectively collected BALF specimens from 121 children with CAP at Tianjin Children's Hospital from February 2021 to December 2021. The diagnostic performances of mNGS and conventional tests (CT) (culture and targeted polymerase chain reaction tests) were compared, using composite diagnosis as the reference standard. The results of mNGS and CT were compared based on pathogenic and non-pathogenic organisms. Pathogen profiles and co-infections between the mild CAP and severe CAP groups were also analyzed. The overall positive coincidence rate was 86.78% (105/121) for mNGS and 66.94% (81/121) for CT. The proportion of patients diagnosed using mNGS plus CT increased to 99.18%. Among the patients, 17.36% were confirmed only by mNGS; Streptococcus pneumoniae accounted for 52.38% and 23.8% of the patients were co-infected. Moreover, Bordetella pertussis and Human bocavirus (HBoV) were detected only using mNGS. Mycoplasma pneumoniae, which was identified in 89 (73.55%) of 121 children with CAP, was the most frequent pathogen detected using mNGS. The infection rate of M. pneumoniae in the severe CAP group was significantly higher than that in the mild CAP group (P = 0.007). The symptoms of single bacterial infections (except for mycoplasma) were milder than those of mycoplasma infections. mNGS identified more bacterial infections when compared to the CT methods and was able to identify co-infections which were initially missed on CT. Additionally, it was able to identify pathogens that were beyond the scope of the CT methods. The mNGS method is a powerful supplement to clinical diagnostic tools in respiratory infections, as it can increase the precision of diagnosis and guide the use of antibiotics.

China's Fight Against COVID-19: What We Have Done and What We Should Do Next?

Background

Chinese government conducted unprecedented massive public health prevention interventions at the national level, which have effectively contained the spread of Coronavirus Disease 2019 (COVID-19) infections. Specifically, the outbreak in Wuhan has been effectively controlled. Meanwhile, the Chinese efforts to contain the virus have been widely recognized. Even the World Health Organization has praised the efforts of the Chinese government and advised other countries to learn from China's experience in the fight against COVID-19. However, the measures that have been conducted by China to effectively prevent the spread of COVID 19 in the country have not been rigorously analyzed. Therefore, this study aimed to explore the characteristics of China's control and prevention strategies, and identify the elements that changed the epidemiological curve of rapidly rising new confirmed cases of COVID-19.

Methods

Public health intervention measures and their effects on the spread of COVID-19 in terms of daily newly confirmed and cumulative cases were collected between January 20, 2020, and March 5. Notices of the Joint Prevention and Control Mechanism for COVID-19 of the State Council on Implementing Measures in Hubei were collected. Information obtained by relevant important documents and announcements was collected from the official website of the Chinese government. Additionally, from other media platforms, news, articles, and reviews were used to explain the intervention measure. Thus, using these data, we performed a retrospective description of the intervention strategies at three stages.

Results

The Chinese government adopted non-pharmacological interventions measures (NPIs) timely and efficiently. On February 20, the declining epidemic trend in China indicated that the three strictest disease prevention and control strategies issued by the Hubei Government had contributed to a smooth decline in the spread of the epidemic.

Conclusions

The NPIs taken by China play a decisive role to control the spread of novel coronavirus outbreaks. Further research and action are needed to ensure a sufficiently sensitive surveillance system and strong response mechanism, including the establishment of a highly accessible laboratory network, maintenance of awareness of both primary healthcare providers and the public, and regular training and exercise of local Centers for Disease Control and Prevention and general practitioners in the community-level.

Culturing Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) for Diagnosis and Genome Sequencing

OBJECTIVE

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) nucleic acid detection "re-positive" phenomenon is encountered clinically. The accuracy of a viral nucleic acid test is crucial to prevent reintroduction of the virus into the community. This study evaluated the effect of virus culturing on increasing the sensitivity and specificity of real-time polymerase chain reaction (RT-PCR) detection and viral genomic sequencing.

METHODS

A series of tenfold dilutions of a SARS-CoV-2 viral stock were conducted and cultured for either 24 or 48 hours. The viral load of cultured samples was determined by RT-PCR. The cultured and non-cultured samples of 1x 50% tissue culture infectious dose (TCID50) were sequenced using metagenomic next-generation sequencing. The depth and coverage of SARS-CoV-2 genome were measured.

RESULTS

The lowest viral load detectable in a sample with RT-PCR was 0.01 TCID50. After a 24-h culture, the viral ORF 1ab and N-gene cycle threshold (CT) values were reduced by 4.4 points and 1 point, respectively. One TCID50 viral load of post 24-h culture revealed the sequence depth reached an average of 752 reads, compared with 0.15 in the nonculture; furthermore, the coverage was 99.99% while 6.42% in the nonculture.

CONCLUSION

These results indicate that virus culturing can significantly increase the viral load, which can increase the certainty of true-positive detection of the viral nucleic acids, and improve the quality of virus genomic sequencing.

A Bioinformatics Approach to Investigate Structural and Non-Structural Proteins in Human Coronaviruses

Recent studies confirmed that people unexposed to SARS-CoV-2 have preexisting reactivity, probably due to previous exposure to widely circulating common cold coronaviruses. Such preexistent reactivity against SARS-CoV-2 comes from memory T cells that can specifically recognize a SARS-CoV-2 epitope of structural and non-structural proteins and the homologous epitopes from common cold coronaviruses. Therefore, it is important to understand the SARS-CoV-2 cross-reactivity by investigating these protein sequence similarities with those of different circulating coronaviruses. In addition, the emerging SARS-CoV-2 variants lead to an intense interest in whether mutations in proteins (especially in the spike) could potentially compromise vaccine effectiveness. Since it is not clear that the differences in clinical outcomes are caused by common cold coronaviruses, a deeper investigation on cross-reactive T-cell immunity to SARS-CoV-2 is crucial to examine the differential COVID-19 symptoms and vaccine performance. Therefore, the present study can be a starting point for further research on cross-reactive T cell recognition between circulating common cold coronaviruses and SARS-CoV-2, including the most recent variants Delta and Omicron. In the end, a deep learning approach, based on Siamese networks, is proposed to accurately and efficiently calculate a BLAST-like similarity score between protein sequences.

Understanding the mutational frequency in SARS-CoV-2 proteome using structural features

The prolonged transmission of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus in the human population has led to demographic divergence and the emergence of several location-specific clusters of viral strains. Although the effect of mutation(s) on severity and survival of the virus is still unclear, it is evident that certain sites in the viral proteome are more/less prone to mutations. In fact, millions of SARS-CoV-2 sequences collected all over the world have provided us a unique opportunity to understand viral protein mutations and develop novel computational approaches to predict mutational patterns. In this study, we have classified the mutation sites into low and high mutability classes based on viral isolates count containing mutations. The physicochemical features and structural analysis of the SARS-CoV-2 proteins showed that features including residue type, surface accessibility, residue bulkiness, stability and sequence conservation at the mutation site were able to classify the low and high mutability sites. We further developed machine learning models using above-mentioned features, to predict low and high mutability sites at different selection thresholds (ranging 5-30% of topmost and bottommost mutated sites) and observed the improvement in performance as the selection threshold is reduced (prediction accuracy ranging from 65 to 77%). The analysis will be useful for early detection of variants of concern for the SARS-CoV-2, which can also be applied to other existing and emerging viruses for another pandemic prevention.

The utility of SARS-CoV-2 nucleocapsid protein in laboratory diagnosis

Background

The Coronavirus Disease 2019 (COVID‐19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2), which has now become a global pandemic owing to its high transmissibility. The SARS‐CoV‐2 nucleocapsid protein tests are playing an important role in screening and diagnosing patients with COVID‐19, and studies about the utility of SARS‐CoV‐2 nucleocapsid protein tests are increasing now.

Methods

In this review, all the relevant original studies were assessed by searching in electronic databases including Scopus, Pubmed, Embase, and Web of Science. “SARS‐CoV‐2”, “COVID‐19”, “nucleocapsid protein”, and “antigen detection” were used as keywords.

Results

In this review, we summarized the utility of SARS‐CoV‐2 nucleocapsid protein in laboratory diagnosis. Among the representative researches, this review analyzed, the sensitivity of SARS‐CoV‐2 nucleocapsid protein detection varies from 13% to 87.9%, while the specificity could almost reach 100% in most studies. As a matter of fact, the sensitivity is around 50% and could be higher or lower due to the influential factors.

Conclusion

It is well suggested that SARS‐CoV‐2 nucleocapsid protein is a convenient method with a short turnaround time of about half an hour, and the presence of N antigen is positively related to viral transmissibility, indicating that SARS‐CoV‐2 N protein immunoassays contribute to finding out those infected people rapidly and segregating them from the uninfected people.

Emerging SARS-CoV-2 variants: Why, how, and what's next?

The emergence of the SARS-CoV-2 Omicron variant poses a striking threat to human society. More than 30 mutations in the Spike protein of the Omicron variant severely compromised the protective immunity elicited by either vaccination or prior infection. The persistent viral evolutionary trajectory generates Omicron-associated lineages, such as BA.1 and BA.2. Moreover, the virus recombination upon Delta and Omicron co-infections has been reported lately, although the impact remains to be assessed. This minireview summarizes the characteristics, evolution and mutation control, and immune evasion mechanisms of SARS-CoV-2 variants, which will be helpful for the in-depth understanding of the SARS-CoV-2 variants and policy-making related to COVID-19 pandemic control.

SARS-CoV-2 Molecular Diagnostics in China

The COVID-19 pandemic remains a significant problem involving health systems worldwide. Several diagnostic methods are reported for detecting the coronavirus in clinical, research, and public health laboratories. rRT-PCR is considered the gold standard; however, as it required skilled personnel and special equipment, rapid antigen tests have been developed and used as first-line screening. The serologic testing of antibodies can also be used to enhance the detection sensitivity and accuracy, which are used to assess the overall infection rate. This review summarizes the molecular techniques and serologic assays widely used in China and discusses the advantages and disadvantages of these techniques.

Rapid metagenomic identification of two major swine pathogens with real-time nanopore sequencing

Metagenomic next-generation sequencing (mNGS) is a rapid deep-sequencing diagnostic tool for the unbiased identification of pathogens. In this study, we established a nanopore-sequencing-based mNGS protocol to detect two major viral pathogens of swine, Porcine reproductive and respiratory syndrome virus (PRRSV) and Porcine epidemic diarrhea virus (PEDV). Samples were spiked with the serially diluted viruses as standard references to define the specific protocols. The utility of the method was evaluated with key parameters. The limits of detection for PRRSV and PEDV were 2.3 × 10² and 9.0 × 10⁴ copies per reaction, respectively, and good correlations between PCR quantification cycle value and the mapped read count (log value) were observed. Only the nanopore reads could be assembled de novo into nearly full-length of the PRRSV genome, with 99.9% pairwise identity, and 90.0% genome coverage for PEDV. The established protocol was validated in PRRSV-positive clinical samples. The results for PRRSV-positive tissue and serum samples tested with mNGS protocol were 100% concordant with quantitative PCR results. The protocol also recognized infections of single or multiple viruses in a single sample. In conclusion, we have established a nanopore-sequencing-based mNGS protocol that efficiently identifies and characterizes viral pathogen(s) in a variety of clinical sample types.

Analysis of Negative Results of Metagenomics Next-Generation Sequencing in Clinical Practice

Background

Metagenomics next-generation sequencing (mNGS) has been increasingly used in the clinic, which provides a powerful tool for the etiological diagnosis of infectious diseases. Precise treatment can be carried out according to the positive mNGS results. However, the role of negative results of mNGS remains poorly defined in clinical practice.

Methods

The results of 1,021 samples from patients who received the mNGS test at Zhongshan Hospital, Fudan University, between January 2019 and December 2019 were analyzed.

Results

There were 308 samples (30.17%) of negative results included in the current study. The top 2 types of negative samples were blood (130/308) and tissue (63/308), which also accounted for the highest negative proportion in diseases. Sputum and bronchoalveolar lavage fluid (BALF) were more likely to have positive results. In false-negative results (defined as negative in mNGS test but reported positive in other sample types or assays), 118 samples were found when compared to regular microbiological assays. The negative predictive value (NPV) of mNGS was 95.79% [95%CI, 93.8%–97.8%] as compared to culture and smear. Mycobacterium, Aspergillus, and Mycoplasma ranked as the top 3 microorganisms on the undetected pathogen list.

Conclusions

The present data indicate that when the mNGS test is negative, the negative prediction accuracy rate of the original specimen is significant. However, other laboratory assays results and clinical presentations should always be carefully considered prior to drawing a diagnosis.

Cumulative SARS-CoV-2 mutations and corresponding changes in immunity in an immunocompromised patient indicate viral evolution within the host

Different scenarios explaining the emergence of novel variants of concern (VOC) of the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) have been reported, including their evolution in scarcely monitored populations, in animals as alternative hosts, or in immunocompromised individuals. Here we report SARS-CoV-2 immune escape mutations over a period of seven months in an immunocompromised patient with prolonged viral shedding. Signs of infection, viral shedding and mutation events are periodically analyzed using RT-PCR and next-generation sequencing based on naso-pharyngeal swabs, with the results complemented by immunological diagnostics to determine humoral and T cell immune responses. Throughout the infection course, 17 non-synonymous intra-host mutations are noted, with 15 (88.2%) having been previously described as prominent immune escape mutations (S:E484K, S:D950N, S:P681H, S:N501Y, S:del(9), N:S235F and S:H655Y) in VOCs. The high frequency of these non-synonymous mutations is consistent with multiple events of convergent evolution. Thus, our results suggest that specific mutations in the SARS-CoV-2 genome may represent positions with a fitness advantage, and may serve as targets in future vaccine and therapeutics development for COVID-19.

Enhanced DNA and RNA pathogen detection via metagenomic sequencing in patients with pneumonia

BACKGROUND

Metagenomic next-generation sequencing (mNGS) is an important supplement to conventional tests for pathogen detections of pneumonia. However, mNGS pipelines were limited by irregularities, high proportion of host nucleic acids, and lack of RNA virus detection. Thus, a regulated pipeline based on mNGS for DNA and RNA pathogen detection of pneumonia is essential.

METHODS

We performed a retrospective study of 151 patients with pneumonia. Three conventional tests, culture, loop-mediated isothermal amplification (LAMP) and viral quantitative real-time polymerase chain reaction (qPCR) were conducted according to clinical needs, and all samples were detected using our optimized pipeline based on the mNGS (DNA and RNA) method. The performances of mNGS and three other tests were compared. Human DNA depletion was achieved respectively by MolYsis kit and pre-treatment using saponin and Turbo DNase. Three RNA library preparation methods were used to compare the detection performance of RNA viruses.

RESULTS

An optimized mNGS workflow was built, which had only 1-working-day turnaround time. The proportion of host DNA in the pre-treated samples decreased from 99 to 90% and microbiome reads achieved an approximately 20-fold enrichment compared with those without host removal. Meanwhile, saponin and Turbo DNase pre-treatment exhibited an advantage for DNA virus detection compared with MolYsis. Besides, our in-house RNA library preparation procedure showed a more robust RNA virus detection ability. Combining three conventional methods, 76 (76/151, 50.3%) cases had no clear causative pathogen, but 24 probable pathogens were successfully detected in 31 (31/76 = 40.8%) unclear cases using mNGS. The agreement of the mNGS with the culture, LAMP, and viral qPCR was 60%, 82%, and 80%, respectively. Compared with all conventional tests, mNGS had a sensitivity of 70.4%, a specificity of 72.7%, and an overall agreement of 71.5%.

CONCLUSIONS

A complete and effective mNGS workflow was built to provide timely DNA and RNA pathogen detection for pneumonia, which could effectively remove the host sequence, had a higher microbial detection rate and a broader spectrum of pathogens (especially for viruses and some pathogens that are difficult to culture). Despite the advantages, there are many challenges in the clinical application of mNGS, and the mNGS report should be interpreted with caution.

Intracellular flow cytometry complements RT-qPCR detection of circulating SARS-CoV-2 variants of concern

Basic and antiviral research on SARS-CoV-2 rely on cellular assays of virus replication in vitro. In addition, accurate detection of virus-infected cells and released virus particles is needed to study virus replication and to profile new candidate antiviral drugs. Here, by flow cytometry, we detect SARS-CoV-2 infection at single cell level and distinguish infected Vero E6 cells from uninfected bystander cells. Furthermore, based on the viral nucleocapsid expression, subpopulations of infected cells that are in an early or late phase of viral replication can be differentiated. Importantly, this flow cytometric technique complements our duplex RT-qPCR detection of viral E and N, and it can be applied to all current SARS-CoV-2 variants of concern, including the highly mutated Omicron variant.

This study describes the characterization of SARS-CoV-2 infected cells using intracellular flow cytometric viral nucleocapsid staining that complements RT-qPCR quantification of viral RNA. The technique makes it possible to distinguish between infected cells in the early (low N) or late phase (high N) of viral replication. It can also be applied to the different variants of concern of SARS-CoV-2, including the Omicron variant.

Conventional and Microfluidic Methods for the Detection of Nucleic Acid of SARS-CoV-2

Nucleic acid testing (NAT) played a crucial role in containing the spread of SARS-CoV-2 during the epidemic. The gold standard technique, the quantitative real-time polymerase chain reaction (qRT-PCR) technique, is currently used by the government and medical boards to detect SARS-CoV-2. Due to the limitations of this technology, it is not capable of meeting the needs of large-scale rapid detection. To solve this problem, many new techniques for detecting nucleic acids of SARS-CoV-2 have been reported. Therefore, a review that systematically and comprehensively introduces and compares various detection technologies is needed. In this paper, we not only review the traditional NAT but also provide an overview of microfluidic-based NAT technologies and summarize and discuss the characteristics and development prospects of these techniques.

The active lung microbiota landscape of COVID-19 patients through the metatranscriptome data analysis

Introduction: With the outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), the interaction between the host and SARS-CoV-2 was widely studied. However, it is unclear whether and how SARS-CoV-2 infection affects lung microflora, which contribute to COVID-19 complications.

Methods: Here, we analyzed the metatranscriptomic data of bronchoalveolar lavage fluid (BALF) of 19 COVID-19 patients and 23 healthy controls from 6 independent projects and detailed the active microbiota landscape in both healthy individuals and COVID-19 patients.

Results: The infection of SARS-CoV-2 could deeply change the lung microbiota, evidenced by the α-diversity, β-diversity, and species composition analysis based on bacterial microbiota and virome. Pathogens (e.g., Klebsiella oxytoca causing pneumonia as well), immunomodulatory probiotics (e.g., lactic acid bacteria and Faecalibacterium prausnitzii, a butyrate producer), and Tobacco mosaic virus (TMV) were enriched in the COVID-19 group, suggesting a severe microbiota dysbiosis. The significant correlation between Rothia mucilaginosa, TMV, and SARS-CoV-2 revealed drastic inflammatory battles between the host, SARS-CoV-2, and other microbes in the lungs. Notably, TMV only existed in the COVID-19 group, while human respirovirus 3 (HRV 3) only existed in the healthy group. Our study provides insights into the active microbiota in the lungs of COVID-19 patients and would contribute to the understanding of the infection mechanism of SARS-CoV-2 and the treatment of the disease and complications.

Conclusion: SARS-COV-2 infection deeply altered the lung microbiota of COVID-19 patients. The enrichment of several other pathogens, immunomodulatory probiotics (lactic acid or butyrate producers), and TMV in the COVID-19 group suggests a complex and active lung microbiota disorder.

Identification of host transcriptome-guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches

Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) is one of the most severe global pandemic due to its high pathogenicity and death rate starting from the end of 2019. Though there are some vaccines available against SAER-CoV-2 infections, we are worried about their effectiveness, due to its unstable sequence patterns. Therefore, beside vaccines, globally effective supporting drugs are also required for the treatment against SARS-CoV-2 infection. To explore commonly effective repurposable drugs for the treatment against different variants of coronavirus infections, in this article, an attempt was made to explore host genomic biomarkers guided repurposable drugs for SARS-CoV-1 infections and their validation with SARS-CoV-2 infections by using the integrated bioinformatics approaches. At first, we identified 138 differentially expressed genes (DEGs) between SARS-CoV-1 infected and control samples by analyzing high throughput gene-expression profiles to select drug target key receptors. Then we identified top-ranked 11 key DEGs (SMAD4, GSK3B, SIRT1, ATM, RIPK1, PRKACB, MED17, CCT2, BIRC3, ETS1 and TXN) as hub genes (HubGs) by protein-protein interaction (PPI) network analysis of DEGs highlighting their functions, pathways, regulators and linkage with other disease risks that may influence SARS-CoV-1 infections. The DEGs-set enrichment analysis significantly detected some crucial biological processes (immune response, regulation of angiogenesis, apoptotic process, cytokine production and programmed cell death, response to hypoxia and oxidative stress), molecular functions (transcription factor binding and oxidoreductase activity) and pathways (transcriptional mis-regulation in cancer, pathways in cancer, chemokine signaling pathway) that are associated with SARS-CoV-1 infections as well as SARS-CoV-2 infections by involving HubGs. The gene regulatory network (GRN) analysis detected some transcription factors (FOXC1, GATA2, YY1, FOXL1, TP53 and SRF) and micro-RNAs (hsa-mir-92a-3p, hsa-mir-155-5p, hsa-mir-106b-5p, hsa-mir-34a-5p and hsa-mir-19b-3p) as the key transcriptional and post- transcriptional regulators of HubGs, respectively. We also detected some chemicals (Valproic Acid, Cyclosporine, Copper Sulfate and arsenic trioxide) that may regulates HubGs. The disease-HubGs interaction analysis showed that our predicted HubGs are also associated with several other diseases including different types of lung diseases. Then we considered 11 HubGs mediated proteins and their regulatory 6 key TFs proteins as the drug target proteins (receptors) and performed their docking analysis with the SARS-CoV-2 3CL protease-guided top listed 90 anti-viral drugs out of 3410. We found Rapamycin, Tacrolimus, Torin-2, Radotinib, Danoprevir, Ivermectin and Daclatasvir as the top-ranked 7 candidate-drugs with respect to our proposed target proteins for the treatment against SARS-CoV-1 infections. Then, we validated these 7 candidate-drugs against the already published top-ranked 11 target proteins associated with SARS-CoV-2 infections by molecular docking simulation and found their significant binding affinity scores with our proposed candidate-drugs. Finally, we validated all of our findings by the literature review. Therefore, the proposed candidate-drugs might play a vital role for the treatment against different variants of SARS-CoV-2 infections with comorbidities, since the proposed HubGs are also associated with several comorbidities.

Reviewing findings on the polypeptide sequence of the SARS-CoV-2 S-protein to discuss the origins of the virus

Several investigations suggested origins of SARS-CoV-2 from the recombination of coronaviruses of various animals, including the bat Rhinolophus affinis and the pangolin Manis javanica, despite the processes describing the adaptation from a reservoir of animals to human are still debated. In this perspective, I will remark two main inconsistencies on the origins of SARS-CoV-2: polypeptide sequence alignment of the S-proteins does not return the expected identity of the receptor-binding motif among most of pangolin-CoVs and SARS-CoV-2; accurate referencing for samplings and sequencing deposition of the ancestral bat coronavirus named RaTG13 was missing since the first reports on the SARS-CoV-2 coronavirus. This contribution aims to stimulate discussion about the origins of SARS-CoV-2 and considers other intermediate hosts as a reservoir for coronavirus.