Current trends in RNA virus detection through metatranscriptome sequencing data.

With advances in sequencing technology, metatranscriptome sequencing from a variety of environmental and biological sources has revealed the existence of various previously unknown RNA viruses. This review presents recent major RNA virome studies sampled from invertebrate and vertebrate species as well as aquatic environments. In particular, we focus on severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) and related RNA virus identification through metatranscriptome sequencing analyses. Recently developed bioinformatics software and databases for RNA virus identification are introduced. A relationship between newly identified RNA viruses and endogenous viral elements in host genomes is also discussed.

Synergy of Small Antiviral Molecules on a Black-Phosphorus Nanocarrier: Machine Learning and Quantum Chemical Simulation Insights.

Favipiravir (FP) and Ebselen (EB) belong to a broad range of antiviral drugs that have shown active potential as medications against many viruses. Employing molecular dynamics simulations and machine learning (ML) combined with van der Waals density functional theory, we have uncovered the binding characteristics of these two antiviral drugs on a phosphorene nanocarrier. Herein, by using four different machine learning models (i.e., Bagged Trees, Gaussian Process Regression (GPR), Support Vector Regression (SVR), and Regression Trees (RT)), the Hamiltonian and the interaction energy of antiviral molecules in a phosphorene monolayer are trained in an appropriate way. However, training efficient and accurate models for approximating the density functional theory (DFT) is the final step in using ML to aid in the design of new drugs. To improve the prediction accuracy, the Bayesian optimization approach has been employed to optimize the GPR, SVR, RT, and BT models. Results revealed that the GPR model obtained superior prediction performance with an R2 of 0.9649, indicating that it can explain 96.49% of the data's variability. Then, by means of DFT calculations, we examine the interaction characteristics and thermodynamic properties in a vacuum and a continuum solvent interface. These results illustrate that the hybrid drug is an enabled, functionalized 2D complex with vigorous thermostability. The change in Gibbs free energy at different surface charges and temperatures implies that the FP and EB molecules are allowed to adsorb from the gas phase onto the 2D monolayer at different pH conditions and high temperatures. The results reveal a valuable antiviral drug therapy loaded by 2D biomaterials that may possibly open a new way of auto-treating different diseases, such as SARS-CoV, in primary terms.

Computational network analysis of host genetic risk variants of severe COVID-19.

BACKGROUND: Genome-wide association studies have identified numerous human host genetic risk variants that play a substantial role in the host immune response to SARS-CoV-2. Although these genetic risk variants significantly increase the severity of COVID-19, their influence on body systems is poorly understood. Therefore, we aim to interpret the biological mechanisms and pathways associated with the genetic risk factors and immune responses in severe COVID-19. We perform a deep analysis of previously identified risk variants and infer the hidden interactions between their molecular networks through disease mapping and the similarity of the molecular functions between constructed networks. RESULTS: We designed a four-stage computational workflow for systematic genetic analysis of the risk variants. We integrated the molecular profiles of the risk factors with associated diseases, then constructed protein-protein interaction networks. We identified 24 protein-protein interaction networks with 939 interactions derived from 109 filtered risk variants in 60 risk genes and 56 proteins. The majority of molecular functions, interactions and pathways are involved in immune responses; several interactions and pathways are related to the metabolic and cardiovascular systems, which could lead to multi-organ complications and dysfunction. CONCLUSIONS: This study highlights the importance of analyzing molecular interactions and pathways to understand the heterogeneous susceptibility of the host immune response to SARS-CoV-2. We propose new insights into pathogenicity analysis of infections by including genetic risk information as essential factors to predict future complications during and after infection. This approach may assist more precise clinical decisions and accurate treatment plans to reduce COVID-19 complications.

Computational Studies of Auto-Active van der Waals Interaction Molecules on Ultra-Thin Black-Phosphorus Film.

Using the van der Waals density functional theory, we studied the binding peculiarities of favipiravir (FP) and ebselen (EB) molecules on a monolayer of black phosphorene (BP). We systematically examined the interaction characteristics and thermodynamic properties in a vacuum and a continuum, solvent interface for active drug therapy. These results illustrate that the hybrid molecules are enabled functionalized two-dimensional (2D) complex systems with a vigorous thermostability. We demonstrate in this study that these molecules remain flat on the monolayer BP system and phosphorus atoms are intact. It is inferred that the hybrid FP+EB molecules show larger adsorption energy due to the van der Waals forces and planar electrostatic interactions. The changes in Gibbs free energy at different surface charge fluctuations and temperatures imply that the FP and EB are allowed to adsorb from the gas phase onto the 2D film at high temperatures. Thereby, the results unveiled beneficial inhibitor molecules on two dimensional BP nanocarriers, potentially introducing a modern strategy to enhance the development of advanced materials, biotechnology, and nanomedicine.

Development and Validation of Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) as a Simple and Rapid Diagnostic Tool for SARS-CoV-2 Detection.

Since the COVID-19 pandemic outbreak in the world, many countries have searched for quick diagnostic tools to detect the virus. There are many ways to design diagnostic assays; however, each may have its limitations. A quick, sensitive, specific, and simple approach is essential for highly rapidly transmitted infections, such as SARS-CoV-2. This study aimed to develop a rapid and cost-effective diagnostic tool using a one-step Reverse Transcriptase Loop-Mediated Isothermal Amplification (RT-LAMP) approach. The results were observed using the naked eye within 30-60 min using turbidity or colorimetric analysis. The sensitivity, specificity, and lowest limit of detection (LoD) for SARS-CoV-2 RNA against the RT-LAMP assay were assessed. This assay was also verified and validated against commercial quantitative RT-PCR used by health authorities in Saudi Arabia. Furthermore, a quick and direct sampling from the saliva, or buccal cavity, was applied after simple modification, using proteinase K and heating at 98 °C for 5 min to avoid routine RNA extraction. This rapid single-tube diagnostic tool detected COVID-19 with an accuracy rate of 95% for both genes (ORF1a and N) and an LoD for the ORF1a and N genes as 39 and 25 copies/reaction, respectively. It can be potentially used as a high-throughput national screening for different respiratory-based infections within the Middle East region, such as the MERS virus or major zoonotic pathogens such as Mycobacterium paratuberculosis and Brucella spp., particularly in remote and rural areas where lab equipment is limited.

Rapid evolution of SARS-CoV-2 challenges human defenses.

The race between pathogens and their hosts is a major evolutionary driver, where both reshuffle their genomes to overcome and reorganize the defenses for infection, respectively. Evolutionary theory helps formulate predictions on the future evolutionary dynamics of SARS-CoV-2, which can be monitored through unprecedented real-time tracking of SARS-CoV-2 population genomics at the global scale. Here we quantify the accelerating evolution of SARS-CoV-2 by tracking the SARS-CoV-2 mutation globally, with a focus on the Receptor Binding Domain (RBD) of the spike protein determining infection success. We estimate that the > 820 million people that had been infected by October 5, 2021, produced up to 1021 copies of the virus, with 12 new effective RBD variants appearing, on average, daily. Doubling of the number of RBD variants every 89 days, followed by selection of the most infective variants challenges our defenses and calls for a shift to anticipatory, rather than reactive tactics involving collaborative global sequencing and vaccination.

Angiotensin-Converting Enzyme (ACE) 1 Gene Polymorphism and Phenotypic Expression of COVID-19 Symptoms.

The renin-angiotensin-aldosterone system (RAAS) appears to play an important role in SARS-CoV-2 infection. Polymorphisms within the genes that control this enzymatic system are candidates for elucidating the pathogenesis of COVID-19, since COVID-19 is not only a pulmonary disease but also affects many organs and systems throughout the body in multiple ways. Most striking is the fact that ACE2, one of the major components of the RAAS, is a prerequisite for SARS-COV-2 infection. Recently, we and other groups reported an association between a polymorphism of the ACE1 gene (a homolog of ACE2) and the phenotypic expression of COVID-19, particularly in its severity. The ethnic difference in ACE1 insertion (I)/deletion (D) polymorphism seems to explain the apparent difference in mortality between the West and East Asia. The purpose of this review was to further evaluate the evidence linking ACE1 polymorphisms to COVID-19. We searched the Medline database (2019-2021) for reference citations of relevant articles and selected studies on the clinical outcome of COVID-19 related to ACE1 I/D polymorphism. Although the numbers of patients are not large enough yet, most available evidence supports the notion that the DD genotype adversely influences COVID-19 symptoms. Surprisingly, small studies conducted in several countries yielded opposite results, suggesting that the ACE1 II genotype is a risk factor. This contradictory result may be the case in certain geographic areas, especially in subgroups of patients. It may also be due to interactions with other genes or to yet unexplained biochemical mechanisms. According to our hypothesis, such candidates are genes that are functionally involved in the pathophysiology of COVID-19, can act in concert with the ACE1 DD genotype, and that show differences in their frequency between the West and East Asia. For this, we conducted research focusing on Alu-related genes. The current study on the ACE1 genotype will provide potentially new clues to the pathogenesis, treatment, and diagnosis of SARS-CoV-2 infections.

Re-infection with a different SARS-CoV-2 clade and prolonged viral shedding in a hematopoietic stem cell transplantation patient.

Immunocompromised patients who have a severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection pose many clinical and public health challenges. We describe the case of a hematopoietic stem cell transplantation patient with lymphoma who had a protracted illness requiring three consecutive hospital admissions. Whole genome sequencing confirmed two different SARS-CoV-2 clades. Clinical management issues and the unanswered questions arising from this case are discussed.

Detection of SARS-CoV-2 variants requires urgent global coordination.

OBJECTIVES: To assess the efforts deployed by different nations and territories in sequencing SARS-CoV-2 isolates, thus enabling detection of variants, known and novel, of concern. METHODS: The sources of over one million full genome sequences of SARS-CoV-2 virus available in the COVID-19 virus Mutation Tracker (CovMT) were analyzed to determine the number of variants in the RBD region of the genome determining infectivity detected in the various nations and territories. RESULTS: The number of detected variants increased as the square root of sequencing effort by nations. Eight nations have contributed 79% of all SARS-CoV-2 isolates that have been sequenced, with two-thirds of all unique variants, adding to 1118 RBD variants, reported by five nations. The median number of sequenced isolates required to detect, on average, one novel RBD variant is 24.05, which is a threshold achieved by 70 nations. CONCLUSIONS: Many developing nations have not contributed any sequences due to lack of capacity. This poses a risk of dangerous virus variants in these under-sampled regions spreading globally before being detected. A collaborative program to sequence SARS-CoV-2 isolates, and other pathogens of concern, is needed to monitor, track, and control the pandemic.

Rise and fall of the global conversation and shifting sentiments during the COVID-19 pandemic

Social media (e.g., Twitter) has been an extremely popular tool for public health surveillance. The novel coronavirus disease 2019 (COVID-19) is the first pandemic experienced by a world connected through the internet. We analyzed 105+ million tweets collected between March 1 and May 15, 2020, and Weibo messages compiled between January 20 and May 15, 2020, covering six languages (English, Spanish, Arabic, French, Italian, and Chinese) and represented an estimated 2.4 billion citizens worldwide. To examine fine-grained emotions during a pandemic, we built machine learning classification models based on deep learning language models to identify emotions in social media conversations about COVID-19, including positive expressions (optimistic, thankful, and empathetic), negative expressions (pessimistic, anxious, sad, annoyed, and denial), and a complicated expression, joking, which has not been explored before. Our analysis indicates a rapid increase and a slow decline in the volume of social media conversations regarding the pandemic in all six languages. The upsurge was triggered by a combination of economic collapse and confinement measures across the regions to which all the six languages belonged except for Chinese, where only the latter drove conversations. Tweets in all analyzed languages conveyed remarkably similar emotional states as the epidemic was elevated to pandemic status, including feelings dominated by a mixture of joking with anxious/pessimistic/annoyed as the volume of conversation surged and shifted to a general increase in positive states (optimistic, thankful, and empathetic), the strongest being expressed in Arabic tweets, as the pandemic came under control.

Transmission dynamics of SARS-CoV-2 on the Diamond Princess uncovered using viral genome sequence analysis.

An outbreak of coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) occurred aboard the Diamond Princess cruise ship between her January 20 departure and late February 2020. Here, we used phylodynamic analyses to investigate the transmission dynamics of SARS-CoV-2 during the outbreak. Using a Bayesian coalescent-based method, the estimated mean nucleotide substitution rate of 240 SARS-CoV-2 whole-genome sequences was approximately 7.13 × 10-4 substitutions per site per year. Population dynamics and the effective reproductive number (Re) of SARS-CoV-2 infections were estimated using a Bayesian framework. The estimated origin of the outbreak was January 21, 2020. The infection spread substantially before quarantine on February 5. The Re peaked at 6.06 on February 4 and gradually declined to 1.51, suggesting that transmission continued slowly even after quarantine. These findings highlight the high transmissibility of SARS-CoV-2 and the need for effective measures to control outbreaks in confined settings.

No Evidence for Temperature-Dependence of the COVID-19 Epidemic.

The pandemic of the COVID-19 extended from China across the north-temperate zone, and more recently to the tropics and southern hemisphere. The hypothesis that COVID-19 spread is temperature-dependent was tested based on data derived from nations across the world and provinces in China. No evidence of a pattern between spread rates and ambient temperature was found, suggesting that the SARS-CoV-2 is unlikely to behave as a seasonal respiratory virus.

Functional Pangenome Analysis Shows Key Features of E Protein Are Preserved in SARS and SARS-CoV-2.

The spread of the novel coronavirus (SARS-CoV-2) has triggered a global emergency, that demands urgent solutions for detection and therapy to prevent escalating health, social, and economic impacts. The spike protein (S) of this virus enables binding to the human receptor ACE2, and hence presents a prime target for vaccines preventing viral entry into host cells. The S proteins from SARS and SARS-CoV-2 are similar, but structural differences in the receptor binding domain (RBD) preclude the use of SARS-specific neutralizing antibodies to inhibit SARS-CoV-2. Here we used comparative pangenomic analysis of all sequenced reference Betacoronaviruses, complemented with functional and structural analyses. This analysis reveals that, among all core gene clusters present in these viruses, the envelope protein E shows a variant cluster shared by SARS and SARS-CoV-2 with two completely-conserved key functional features, namely an ion-channel, and a PDZ-binding motif (PBM). These features play a key role in the activation of the inflammasome causing the acute respiratory distress syndrome, the leading cause of death in SARS and SARS-CoV-2 infections. Together with functional pangenomic analysis, mutation tracking, and previous evidence, on E protein as a determinant of pathogenicity in SARS, we suggest E protein as an alternative therapeutic target to be considered for further studies to reduce complications of SARS-CoV-2 infections in COVID-19.

SARS-CoV-2 infections and COVID-19 mortalities strongly correlate with ACE1 I/D genotype.

Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) causes coronavirus disease 2019 (COVID-19). The relentless spread and pathogenicity of the virus have become a global public health emergency. One of the striking features of this pandemic is the pronounced impact on specific regions and ethnic groups. In particular, compared with East Asia, where the virus first emerged, SARS-CoV-2 has caused high rates of morbidity and mortality in Europe. This has not been experienced in past global viral infections, such as influenza, severe acute respiratory syndrome (SARS) and Middle East respiratory syndrome (MERS) and is unique to SARS-CoV-2. For this reason, we investigated the involvement of genetic factors associated with SARS-CoV-2 infection with a focus on angiotensin-converting enzyme (ACE)-related genes, because ACE2 is a receptor for SARS-CoV-2. We found that the ACE1 II genotype frequency in a population was significantly negatively correlated with the number of SARS-CoV-2 cases. Similarly, the ACE1 II genotype was negatively correlated with the number of deaths due to SARS-CoV-2 infection. These data suggest that the ACE1 II genotype may influence the prevalence and clinical outcome of COVID-19 and serve as a predictive marker for COVID-19 risk and severity.