Web tools to fight pandemics: the COVID-19 experience

Intra-host mutation rate of acute SARS-CoV-2 infection during the initial pandemic wave

SARS-CoV-2 mutation is minimized through a proofreading function encoded by NSP-14. Most estimates of the SARS-CoV-2 mutation rate are derived from population based sequence data. Our understanding of SARS-CoV-2 evolution might be enhanced through analysis of intra-host viral mutation rates in specific populations. Viral genome analysis was performed between paired samples and mutations quantified at allele frequencies (AF) ≥ 0.25, ≥ 0.5 and ≥ 0.75. Mutation rate was determined employing F81 and JC69 evolution models and compared between isolates with (ΔNSP-14) and without (wtNSP-14) non-synonymous mutations in NSP-14 and by patient comorbidity. Forty paired samples with median interval of 13 days [IQR 8.5-20] were analyzed. The estimated mutation rate by F81 modeling was 93.6 (95%CI 90.8-96.4], 40.7 (95%CI 38.9-42.6) and 34.7 (95%CI 33.0-36.4) substitutions/genome/year at AF ≥ 0.25, ≥ 0.5, ≥ 0.75 respectively. Mutation rate in ΔNSP-14 were significantly elevated at AF ≥ 0.25 vs wtNSP-14. Patients with immune comorbidities had higher mutation rate at all allele frequencies. Intra-host SARS-CoV-2 mutation rates are substantially higher than those reported through population analysis. Virus strains with altered NSP-14 have accelerated mutation rate at low AF. Immunosuppressed patients have elevated mutation rate at all AF. Understanding intra-host virus evolution will aid in current and future pandemic modeling.

Cross-Species Transcriptomics Analysis Highlights Conserved Molecular Responses to Per- and Polyfluoroalkyl Substances

In recent decades, per- and polyfluoroalkyl substances (PFASs) have garnered widespread public attention due to their persistence in the environment and detrimental effects on the health of living organisms, spurring the generation of several transcriptome-centered investigations to understand the biological basis of their mechanism. In this study, we collected 2144 publicly available samples from seven distinct animal species to examine the molecular responses to PFAS exposure and to determine if there are conserved responses. Our comparative transcriptional analysis revealed that exposure to PFAS is conserved across different tissues, molecules and species. We identified and reported several genes exhibiting consistent and evolutionarily conserved transcriptional response to PFASs, such as ESR1, HADHA and ID1, as well as several pathways including lipid metabolism, immune response and hormone pathways. This study provides the first evidence that distinct PFAS molecules induce comparable transcriptional changes and affect the same metabolic processes across inter-species borders. Our findings have significant implications for understanding the impact of PFAS exposure on living organisms and the environment. We believe that this study offers a novel perspective on the molecular responses to PFAS exposure and provides a foundation for future research into developing strategies for mitigating the detrimental effects of these substances in the ecosystem.

Web Resources for SARS-CoV-2 Genomic Database, Annotation, Analysis and Variant Tracking

The SARS-CoV-2 genomic data continue to grow, providing valuable information for researchers and public health officials. Genomic analysis of these data sheds light on the transmission and evolution of the virus. To aid in SARS-CoV-2 genomic analysis, many web resources have been developed to store, collate, analyze, and visualize the genomic data. This review summarizes web resources used for the SARS-CoV-2 genomic epidemiology, covering data management and sharing, genomic annotation, analysis, and variant tracking. The challenges and further expectations for these web resources are also discussed. Finally, we highlight the importance and need for continued development and improvement of related web resources to effectively track the spread and understand the evolution of the virus.

Evaluation of an Immersive COVID-19 Data Visualization

COVID-19 restrictions have detrimental effects on the population, both socially and economically. However, these restrictions are necessary as they help reduce the spread of the virus. For the public to comply, easily comprehensible communication between decision makers and the public is thus crucial. To address this, we propose a novel 3-D visualization of COVID-19 data, which could increase the awareness of COVID-19 trends in the general population. We conducted a user study and compared a conventional 2-D visualization with the proposed method in an immersive environment. Results showed that the our 3-D visualization approach facilitated understanding of the complexity of COVID-19. A majority of participants preferred to see the COVID-19 data with the 3-D method. Moreover, individual results revealed that our method increases the engagement of users with the data. We hope that our method will help governments to improve their communication with the public in the future.

A hospital demand and capacity intervention approach for COVID-19

The mathematical interpretation of interventions for the mitigation of epidemics in the literature often involves finding the optimal time to initiate an intervention and/or the use of the number of infections to manage impact. Whilst these methods may work in theory, in order to implement effectively they may require information which is not likely to be available in the midst of an epidemic, or they may require impeccable data about infection levels in the community. In reality, testing and cases data can only be as good as the policy of implementation and the compliance of the individuals, which implies that accurately estimating the levels of infections becomes difficult or complicated from the data that is provided. In this paper, we demonstrate a different approach to the mathematical modelling of interventions, not based on optimality or cases, but based on demand and capacity of hospitals who have to deal with the epidemic on a day to day basis. In particular, we use data-driven modelling to calibrate a susceptible-exposed-infectious-recovered-died type model to infer parameters that depict the dynamics of the epidemic in several regions of the UK. We use the calibrated parameters for forecasting scenarios and understand, given a maximum capacity of hospital healthcare services, how the timing of interventions, severity of interventions, and conditions for the releasing of interventions affect the overall epidemic-picture. We provide an optimisation method to capture when, in terms of healthcare demand, an intervention should be put into place given a maximum capacity on the service. By using an equivalent agent-based approach, we demonstrate uncertainty quantification on the likelihood that capacity is not breached, by how much if it does, and the limit on demand that almost guarantees capacity is not breached.

ViralVar: A Web Tool for Multilevel Visualization of SARS-CoV-2 Genomes

The unprecedented growth of publicly available SARS-CoV-2 genome sequence data has increased the demand for effective and accessible SARS-CoV-2 data analysis and visualization tools. The majority of the currently available tools either require computational expertise to deploy them or limit user input to preselected subsets of SARS-CoV-2 genomes. To address these limitations, we developed ViralVar, a publicly available, point-and-click webtool that gives users the freedom to investigate and visualize user-selected subsets of SARS-CoV-2 genomes obtained from the GISAID public database. ViralVar has two primary features that enable: (1) the visualization of the spatiotemporal dynamics of SARS-CoV-2 lineages and (2) a structural/functional analysis of genomic mutations. As proof-of-principle, ViralVar was used to explore the evolution of the SARS-CoV-2 pandemic in the USA in pediatric, adult, and elderly populations (n > 1.7 million genomes). Whereas the spatiotemporal dynamics of the variants did not differ between these age groups, several USA-specific sublineages arose relative to the rest of the world. Our development and utilization of ViralVar to provide insights on the evolution of SARS-CoV-2 in the USA demonstrates the importance of developing accessible tools to facilitate and accelerate the large-scale surveillance of circulating pathogens.

Ethnobotanical Study of Medicinal Plants Used against COVID-19

During the COVID-19 pandemic, the Moroccan population, like the entire population of the world, used medicinal plants to treat or cure symptoms of SARS-CoV-2. The present work was designed to identify the medicinal plants used by the Moroccan population in the prevention or treatment of COVID-19. To achieve this goal, a survey was conducted to collect data on plants along with the sociodemographic parameters of users. The outcome of this work showed that 1,263 people were interviewed with 63.5% male, aged between 18 and 82 years. Most plant users were between 20 and 40 years, which constituted 80.1% of the study population. The level of education of participants was 70.9% university and 27.6% secondary. The most useful plants were eucalyptus, cloves, lemon, and garlic. Notably, 61.9% of interviewed people used plants for preventing or treating COVID-19: 30.6% of them declared one-time use from the beginning of the pandemic, and 47.8% declared frequent daily use until recovery, while 17.4% declared single daily use. Five out of twenty-one plants used in the treatment are known for their potential toxicity, including Artemisia herba-alba and oleander (Nerium oleander). The findings of the present work could serve society by providing potential medicinal plants to control COVID-19.

"pySewage": a hybrid approach to predict the number of SARS-CoV-2-infected people from wastewater in Brazil

It is well known that the new coronavirus pandemic has global environmental, public health, and economic implications. In this sense, this study aims to monitor SARS-CoV-2 in the largest wastewater treatment plant of Goiânia, which processes wastewater from more than 700,000 inhabitants, and to correlate the molecular and clinical data collected. Influent and effluent samples were collected at Dr. Helio de Seixo Britto's wastewater treatment plant from January to August 2021. Viral concentration was performed with polyethylene glycol before viral RNA extraction. Real-time qPCR (N1 and N2 gene assays) was performed to detect and quantify the viral RNA present in the samples. The results showed that 43.63% of the samples were positive. There is no significant difference between the detection of primers N1 (mean 3.23 log10 genome copies/L, std 0.23) and N2 (mean 2.95 log10 genome copies/L, std 0.29); also, there is no significant difference between the detection of influent and effluent samples. Our molecular data revealed a positive correlation with clinical data, and infection prevalence was higher than clinical data. In addition, we developed a user-friendly web application to predict the number of infected people based on the detection of viral load present in wastewater samples and may be applied as a public policy strategy for monitoring ongoing outbreaks.

The R Language: An Engine for Bioinformatics and Data Science

The R programming language is approaching its 30th birthday, and in the last three decades it has achieved a prominent role in statistics, bioinformatics, and data science in general. It currently ranks among the top 10 most popular languages worldwide, and its community has produced tens of thousands of extensions and packages, with scopes ranging from machine learning to transcriptome data analysis. In this review, we provide an historical chronicle of how R became what it is today, describing all its current features and capabilities. We also illustrate the major tools of R, such as the current R editors and integrated development environments (IDEs), the R Shiny web server, the R methods for machine learning, and its relationship with other programming languages. We also discuss the role of R in science in general as a driver for reproducibility. Overall, we hope to provide both a complete snapshot of R today and a practical compendium of the major features and applications of this programming language.

A mixture model for determining SARS-Cov-2 variant composition in pooled samples

MOTIVATION

Despite of the fast development of highly effective vaccines to control the current COVID-19 pandemics, the unequal distribution and availability of these vaccines worldwide and the number of people infected in the world lead to the continuous emergence of Severe Acute Respiratory Syndrome coronavirus 2 (SARS-CoV-2) variants of concern. Therefore, it is likely that real-time genomic surveillance will be continuously needed as an unceasing monitoring tool, necessary to follow the spread of the disease and the evolution of the virus. In this context, new genomic variants of SARS-CoV-2, including variants refractory to current vaccines, makes genomic surveillance programs tools of utmost importance. Nevertheless, the lack of appropriate analytical tools to quickly and effectively access the viral composition in meta-transcriptomic sequencing data, including environmental surveillance, represent possible challenges that may impact the fast adoption of this approach to mitigate the spread and transmission of viruses.

RESULTS

We propose a statistical model for the estimation of the relative frequencies of SARS-CoV-2 variants in pooled samples. This model is built by considering a previously defined selection of genomic polymorphisms that characterize SARS-CoV-2 variants. The methods described here support both raw sequencing reads for polymorphisms-based markers calling and predefined markers in the variant call format. Results obtained using simulated data show that our method is quite effective in recovering the correct variant proportions. Further, results obtained by considering longitudinal data from wastewater samples of two locations in Switzerland agree well with those describing the epidemiological evolution of COVID-19 variants in clinical samples of these locations. Our results show that the described method can be a valuable tool for tracking the proportions of SARS-CoV-2 variants in complex mixtures such as waste water and environmental samples.

AVAILABILITY AND IMPLEMENTATION

http://github.com/rvalieris/LCS.

SUPPLEMENTARY INFORMATION

Supplementary data are available at Bioinformatics online.

Effectiveness of Remdesivir, Lopinavir/Ritonavir, and Favipiravir for COVID-19 Treatment: A Systematic Review

BACKGROUND

The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel strain that causes acute respiratory illnesses known as coronavirus disease 2019 (COVID-19). Currently, there is limited information regarding the therapeutic management for this disease. Several studies have stated that antivirals drugs such as remdesivir, favipiravir, and lopinavir/ritonavir may potentially inhibit the virus from spreading to the host.

OBJECTIVE

The aim of this systematic review was to summarize the clinical effectiveness and safety of remdesivir, favipiravir, and lopinavir/ritonavir on COVID-19.

METHODS

The PubMed and Cochrane Library databases were searched up to July 2021 to identify eligible experimental randomized controlled trials on remdesivir, favipiravir, and lopinavir/ritonavir for COVID-19 patients. This systematic review followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guideline.

RESULTS

From 158 references, 15 studies were included in the review. The results showed that remdesivir has some potential benefits for hospitalized COVID-19 patients, as seen from clinical improvements such as faster recovery time, less duration of hospitalization, and fewer respiratory side effects among COVID-19 patients. However, the impact of remdesivir in reducing mortality remains uncertain. Treatment with favipiravir has shown promising improvement in the clinical status of COVID-19 patients, although the results suggested no significant differences in some clinical parameters such as length of hospitalizations and clinical recovery. A combination of favipiravir with other supportive therapy showed more favorable outcomes for COVID-19 patients. Furthermore, the use of lopinavir/ritonavir in COVID-19 patients reported no significant clinical improvement compared to standard care with notable adverse effect reactions.

CONCLUSION

This study provides an overview of the evidence-based role of remdesivir, favipiravir, and lopinavir/ritonavir in the management of COVID-19. A thorough assessment of the benefit-risk profile in COVID-19 patients is urgently needed. The current review was based on very limited available data; therefore, further well-designed clinical trials are required.

VirusLab: A Tool for Customized SARS-CoV-2 Data Analysis

Since the beginning of 2020, the COVID-19 pandemic has posed unprecedented challenges to viral data analysis and connected host disease diagnostic methods. We propose VirusLab, a flexible system for analysing SARS-CoV-2 viral sequences and relating them to metadata or clinical information about the host. VirusLab capitalizes on two existing resources: ViruSurf, a database of public SARS-CoV-2 sequences supporting metadata-driven search, and VirusViz, a tool for visual analysis of search results. VirusLab is designed for taking advantage of these resources within a server-side architecture that: (i) covers pipelines based on approaches already in use (ARTIC, Galaxy) but entirely cutomizable upon user request; (ii) predigests analysis of raw sequencing data from different platforms (Oxford Nanopore and Illumina); (iii) gives access to public archives datasets; (iv) supplies user-friendly reporting – making it a tool that can also be integrated into a business environment. VirusLab can be installed and hosted within the premises of any organization where information about SARS-CoV-2 sequences can be safely integrated with information about hosts (e.g., clinical metadata). A system such as VirusLab is not currently available in the landscape of similar providers: our results show that VirusLab is a powerful tool to generate tabular/graphical and machine readable reports that can be integrated in more complex pipelines. We foresee that the proposed system can support many research-oriented and therapeutic scenarios within hospitals or the tracing of viral sequences and their mutational processes within organizations for viral surveillance.

Development of interactive biological web applications with R/Shiny

Development of interactive web applications to deposit, visualize and analyze biological datasets is a major subject of bioinformatics. R is a programming language for data science, which is also one of the most popular languages used in biological data analysis and bioinformatics. However, building interactive web applications was a great challenge for R users before the Shiny package was developed by the RStudio company in 2012. By compiling R code into HTML, CSS and JavaScript code, Shiny has made it incredibly easy to build web applications for the large R community in bioinformatics and for even non-programmers. Over 470 biological web applications have been developed with R/Shiny up to now. To further promote the utilization of R/Shiny, we reviewed the development of biological web applications with R/Shiny, including eminent biological web applications built with R/Shiny, basic steps to build an R/Shiny application, commonly used R packages to build the interface and server of R/Shiny applications, deployment of R/Shiny applications in the cloud and online resources for R/Shiny.

Web resources facilitate drug discovery in treatment of COVID-19

The infectious disease Coronavirus 2019 (COVID-19) continues to cause a global pandemic and, thus, the need for effective therapeutics remains urgent. Global research targeting COVID-19 treatments has produced numerous therapy-related data and established data repositories. However, these data are disseminated throughout the literature and web resources, which could lead to a reduction in the levels of their use. In this review, we introduce resource repositories for the development of COVID-19 therapeutics, from the genome and proteome to antiviral drugs, vaccines, and monoclonal antibodies. We briefly describe the data and usage, and how they advance research for therapies. Finally, we discuss the opportunities and challenges to preventing the pandemic from developing further.

Anti-Coronavirus Vaccines: Past Investigations on SARS-CoV-1 and MERS-CoV, the Approved Vaccines from BioNTech/Pfizer, Moderna, Oxford/AstraZeneca and others under Development Against SARS-CoV-2 Infection

The aim of this review article is to summarize the knowledge available to date on prophylaxis achievements to fight against Coronavirus. This work will give an overview of what is reported in the most recent literature on vaccines (under investigation or already developed like BNT162b2, mRNA-1273, and ChAdOx1-S) effective against the most pathogenic Coronaviruses (SARS-CoV-1, MERS-CoV-1, and SARS-CoV-2), with of course particular attention paid to those under development or already in use to combat the current COVID-19 (COronaVIrus Disease 19) pandemic. Our main objective is to make a contribution to the comprehension, additionally at a molecular level, of what is currently ready for anti-SARS-CoV-2 prophylactic intervention, as well as to provide the reader with an overall picture of the most innovative approaches for the development of vaccines that could be of general utility in the fight against the most pathogenic Coronaviruses.

Preliminary report on severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Spike mutation T478K

Several severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) variants have emerged, posing a renewed threat to coronavirus disease 2019 containment and to vaccine and drug efficacy. In this study, we analyzed more than 1,000,000 SARS‐CoV‐2 genomic sequences deposited up to April 27, 2021, on the GISAID public repository, and identified a novel T478K mutation located on the SARS‐CoV‐2 Spike protein. The mutation is structurally located in the region of interaction with human receptor ACE2 and was detected in 11,435 distinct cases. We show that T478K has appeared and risen in frequency since January 2021, predominantly in Mexico and the United States, but we could also detect it in several European countries.

We analyzed 1,180,571 SARS‐CoV‐2 samples from the public repository GISAID (updated to April 27, 2021).

We detected a mutation in SARS‐CoV‐2 Spike (S) protein amino acid 478, S:T478K, which has been growing in sequence in North America (especially Mexico) since January, 2021.

S:T478K is one of the characterizing mutations of lineage B.1.1.519, which is currently independent from B.1.1.7 and B.1.351.

S:T478K is affecting the Spike binding domain with human receptor ACE2, increasing the electrostatic potential on the interface.

Previous experiments show that S:T478K is a possible genetic route for SARS‐CoV‐2 to escape immune recognition.

Pharmacological Modulators of Autophagy as a Potential Strategy for the Treatment of COVID-19

The family of coronaviruses (CoVs) uses the autophagy machinery of host cells to promote their growth and replication; thus, this process stands out as a potential target to combat COVID-19. Considering the different roles of autophagy during viral infection, including SARS-CoV-2 infection, in this review, we discuss several clinically used drugs that have effects at different stages of autophagy. Among them, we mention (1) lysosomotropic agents, which can prevent CoVs infection by alkalinizing the acid pH in the endolysosomal system, such as chloroquine and hydroxychloroquine, azithromycin, artemisinins, two-pore channel modulators and imatinib; (2) protease inhibitors that can inhibit the proteolytic cleavage of the spike CoVs protein, which is necessary for viral entry into host cells, such as camostat mesylate, lopinavir, umifenovir and teicoplanin and (3) modulators of PI3K/AKT/mTOR signaling pathways, such as rapamycin, heparin, glucocorticoids, angiotensin-converting enzyme inhibitors (IECAs) and cannabidiol. Thus, this review aims to highlight and discuss autophagy-related drugs for COVID-19, from in vitro to in vivo studies. We identified specific compounds that may modulate autophagy and exhibit antiviral properties. We hope that research initiatives and efforts will identify novel or "off-label" drugs that can be used to effectively treat patients infected with SARS-CoV-2, reducing the risk of mortality.

Molecular Basis of the Therapeutical Potential of Clove (Syzygium aromaticum L.) and Clues to Its Anti-COVID-19 Utility

The current COronaVIrus Disease 19 (COVID-19) pandemic caused by SARS-CoV-2 infection is enormously affecting the worldwide health and economy. In the wait for an effective global immunization, the development of a specific therapeutic protocol to treat COVID-19 patients is clearly necessary as a short-term solution of the problem. Drug repurposing and herbal medicine represent two of the most explored strategies for an anti-COVID-19 drug discovery. Clove (Syzygium aromaticum L.) is a well-known culinary spice that has been used for centuries in folk medicine in many disorders. Interestingly, traditional medicines have used clove since ancient times to treat respiratory ailments, whilst clove ingredients show antiviral and anti-inflammatory properties. Other interesting features are the clove antithrombotic, immunostimulatory, and antibacterial effects. Thus, in this review, we discuss the potential role of clove in the frame of anti-COVID-19 therapy, focusing on the antiviral, anti-inflammatory, and antithrombotic effects of clove and its molecular constituents described in the scientific literature.

Nucleoside Analogs and Nucleoside Precursors as Drugs in the Fight against SARS-CoV-2 and Other Coronaviruses

Coronaviruses (CoVs) are positive-sense RNA enveloped viruses, members of the family Coronaviridae, that cause infections in a broad range of mammals including humans. Several CoV species lead to mild upper respiratory infections typically associated with common colds. However, three human CoV (HCoV) species: Severe Acute Respiratory Syndrome (SARS)-CoV-1, Middle East Respiratory Syndrome (MERS)-CoV, and SARS-CoV-2, are responsible for severe respiratory diseases at the origin of two recent epidemics (SARS and MERS), and of the current COronaVIrus Disease 19 (COVID-19), respectively. The easily transmissible SARS-CoV-2, emerging at the end of 2019 in China, spread rapidly worldwide, leading the World Health Organization (WHO) to declare COVID-19 a pandemic. While the world waits for mass vaccination, there is an urgent need for effective drugs as short-term weapons to combat the SARS-CoV-2 infection. In this context, the drug repurposing approach is a strategy able to guarantee positive results rapidly. In this regard, it is well known that several nucleoside-mimicking analogs and nucleoside precursors may inhibit the growth of viruses providing effective therapies for several viral diseases, including HCoV infections. Therefore, this review will focus on synthetic nucleosides and nucleoside precursors active against different HCoV species, paying great attention to SARS-CoV-2. This work covers progress made in anti-CoV therapy with nucleoside derivatives and provides insight into their main mechanisms of action.

Mechanistic modeling of the SARS-CoV-2 disease map

Here we present a web interface that implements a comprehensive mechanistic model of the SARS-CoV-2 disease map. In this framework, the detailed activity of the human signaling circuits related to the viral infection, covering from the entry and replication mechanisms to the downstream consequences as inflammation and antigenic response, can be inferred from gene expression experiments. Moreover, the effect of potential interventions, such as knock-downs, or drug effects (currently the system models the effect of more than 8000 DrugBank drugs) can be studied. This freely available tool not only provides an unprecedentedly detailed view of the mechanisms of viral invasion and the consequences in the cell but has also the potential of becoming an invaluable asset in the search for efficient antiviral treatments.