Next-Generation Sequencing: An Eye-Opener for the Surveillance of Antiviral Resistance in Influenza

Advancements in Antiviral Drug Development: Comprehensive Insights into Design Strategies and Mechanisms Targeting Key Viral Proteins

Viral infectious diseases have always been a threat to human survival and quality of life, impeding the stability and progress of human society. As such, researchers have persistently focused on developing highly efficient, low-toxicity antiviral drugs, whether for acute or chronic infectious diseases. This article presents a comprehensive review of the design concepts behind virus-targeted drugs, examined through the lens of antiviral drug mechanisms. The intention is to provide a reference for the development of new, virus-targeted antiviral drugs and guide their clinical usage.

Low antiviral resistance in Influenza A and B viruses isolated in Mexico from 2010 to 2023

The most widely used class of antivirals available for Influenza treatment are the neuraminidase inhibitors (NAI) Oseltamivir and Zanamivir. However, amino acid (AA) substitutions in the neuraminidase may cause reduced inhibition or high antiviral resistance. In Mexico, the current state of knowledge about NAI susceptibility is scarce, in this study we report the results of 14 years of Influenza surveillance by phenotypic and genotypic methods. A total of 255 isolates were assessed with the NAI assay, including Influenza A(H1N1)pdm09, A(H3N2) and Influenza B (IBV). Furthermore, 827 sequences contained in the GISAID platform were analyzed in search of relevant mutations.Overall, five isolates showed highly reduced inhibition or reduced inhibition to Oseltamivir, and two showed reduced inhibition to Zanamivir in the NAI assays. Additionally, five A(H1N1)pdm09 sequences from the GISAID possessed AA substitutions associated to reduced inhibition to Oseltamivir and none to Zanamivir. Oseltamivir resistant A(H1N1)pdm09 harbored the H275Y mutation. No genetic mutations were identified in Influenza A(H3N2) and IBV. Overall, these results show that in Mexico the rate of NAI resistance is low (0.6%), but it is essential to continue the Influenza surveillance in order to understand the drug susceptibility of circulating strains.

A synergistic therapy against influenza virus A/H1N1/PR8 by a HA1 specific neutralizing single-domain VL and an RNA hydrolyzing scFv

The emergence of anti-influenza drug-resistant strains poses a challenge for influenza therapy due to mutations in the virus's surface protein. Recently, there has been increasing interest in combination therapy consisting of two or more drugs as a potential alternative approach, aiming to enhance therapeutic efficacy. In this study, we investigated a novel synergistic therapy with a vertical effect using a single-domain VL-HA1-specific antibody against H1N1/PR8 and a horizontal effect using an RNA catalytic antibody with broad-spectrum influenza antiviral drug. We isolated a single-domain VL-HA1-specific (NVLH8) antibody binding to the virus particles showing a neutralizing activity against influenza virus A, specifically H1N1/PR8, as determined by the reduction in plaque number and lower viral HA protein expression in vitro. The neutralizing antibody likely prevented the viral entry, specifically at the viral genome-releasing step. Additionally, the 3D8 scFv hydrolyzed viral RNAs in the cytoplasm, including mRNA, vRNA, and cRNA in MDCK cells. The combined treatment of neutralizing antibodies for a vertical effect and 3D8 scFv for a horizontal effect produced a synergistic effect providing a novel approach against viral diseases when compared with a single treatment. Our results indicated that combining treatment, in particular two proteins exhibiting different mechanisms of action increased the antiviral activity against the influenza virus.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and the emergence of drug resistance. Host-based antivirals are an alternative, but can cause nonspecific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR knockout (KO) screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting antiviral SL drug targets. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Our comparison of SARS-CoV-2 and influenza infection data revealed potential broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Genomic Analysis of Influenza A and B Viruses Carrying Baloxavir Resistance-Associated Substitutions Serially Passaged in Human Epithelial Cells

Baloxavir marboxil (baloxavir) is an FDA-approved inhibitor of the influenza virus polymerase acidic (PA) protein. Here, we used next-generation sequencing to compare the genomic mutational profiles of IAV H1N1 and H3N2, and IBV wild type (WT) and mutants (MUT) viruses carrying baloxavir resistance-associated substitutions (H1N1-PA I38L, I38T, and E199D; H3N2-PA I38T; and IBV-PA I38T) during passaging in normal human bronchial epithelial (NHBE) cells. We determined the ratio of nonsynonymous to synonymous nucleotide mutations (dN/dS) and identified the location and type of amino acid (AA) substitutions that occurred at a frequency of ≥30%. We observed that IAV H1N1 WT and MUT viruses remained relatively stable during passaging. While the mutational profiles for IAV H1N1 I38L, I38T, and E199D, and IBV I38T MUTs were relatively similar after each passage compared to the respective WTs, the mutational profile of the IAV H3N2 I38T MUT was significantly different for most genes compared to H3N2 WT. Our work provides insight into how baloxavir resistance-associated substitutions may impact influenza virus evolution in natural settings. Further characterization of the potentially adaptive mutations identified in this study is needed.

Current Uses and Future Perspectives of Genomic Technologies in Clinical Microbiology

Recent advancements in sequencing technology and data analytics have led to a transformative era in pathogen detection and typing. These developments not only expedite the process, but also render it more cost-effective. Genomic analyses of infectious diseases are swiftly becoming the standard for pathogen analysis and control. Additionally, national surveillance systems can derive substantial benefits from genomic data, as they offer profound insights into pathogen epidemiology and the emergence of antimicrobial-resistant strains. Antimicrobial resistance (AMR) is a pressing global public health issue. While clinical laboratories have traditionally relied on culture-based antimicrobial susceptibility testing, the integration of genomic data into AMR analysis holds immense promise. Genomic-based AMR data can furnish swift, consistent, and highly accurate predictions of resistance phenotypes for specific strains or populations, all while contributing invaluable insights for surveillance. Moreover, genome sequencing assumes a pivotal role in the investigation of hospital outbreaks. It aids in the identification of infection sources, unveils genetic connections among isolates, and informs strategies for infection control. The One Health initiative, with its focus on the intricate interconnectedness of humans, animals, and the environment, seeks to develop comprehensive approaches for disease surveillance, control, and prevention. When integrated with epidemiological data from surveillance systems, genomic data can forecast the expansion of bacterial populations and species transmissions. Consequently, this provides profound insights into the evolution and genetic relationships of AMR in pathogens, hosts, and the environment.

Predicting host-based, synthetic lethal antiviral targets from omics data

Traditional antiviral therapies often have limited effectiveness due to toxicity and development of drug resistance. Host-based antivirals, while an alternative, may lead to non-specific effects. Recent evidence shows that virus-infected cells can be selectively eliminated by targeting synthetic lethal (SL) partners of proteins disrupted by viral infection. Thus, we hypothesized that genes depleted in CRISPR KO screens of virus-infected cells may be enriched in SL partners of proteins altered by infection. To investigate this, we established a computational pipeline predicting SL drug targets of viral infections. First, we identified SARS-CoV-2-induced changes in gene products via a large compendium of omics data. Second, we identified SL partners for each altered gene product. Last, we screened CRISPR KO data for SL partners required for cell viability in infected cells. Despite differences in virus-induced alterations detected by various omics data, they share many predicted SL targets, with significant enrichment in CRISPR KO-depleted datasets. Comparing data from SARS-CoV-2 and influenza infections, we found possible broad-spectrum, host-based antiviral SL targets. This suggests that CRISPR KO data are replete with common antiviral targets due to their SL relationship with virus-altered states and that such targets can be revealed from analysis of omics datasets and SL predictions.

Agnostic Sequencing for Detection of Viral Pathogens

The advent of next-generation sequencing (NGS) technologies has expanded our ability to detect and analyze microbial genomes and has yielded novel molecular approaches for infectious disease diagnostics. While several targeted multiplex PCR and NGS-based assays have been widely used in public health settings in recent years, these targeted approaches are limited in that they still rely on a priori knowledge of a pathogen's genome, and an untargeted or unknown pathogen will not be detected. Recent public health crises have emphasized the need to prepare for a wide and rapid deployment of an agnostic diagnostic assay at the start of an outbreak to ensure an effective response to emerging viral pathogens. Metagenomic techniques can nonspecifically sequence all detectable nucleic acids in a sample and therefore do not rely on prior knowledge of a pathogen's genome. While this technology has been reviewed for bacterial diagnostics and adopted in research settings for the detection and characterization of viruses, viral metagenomics has yet to be widely deployed as a diagnostic tool in clinical laboratories. In this review, we highlight recent improvements to the performance of metagenomic viral sequencing, the current applications of metagenomic sequencing in clinical laboratories, as well as the challenges that impede the widespread adoption of this technology.

Lessons from resistance analysis in clinical trials of IV zanamivir

Influenza infection causes substantial morbidity and mortality during seasonal epidemics and pandemics. Antivirals, including neuraminidase inhibitors, play an important role in the treatment of severely ill patients infected with influenza. Resistance is a key factor that can affect the efficacy of neuraminidase inhibitors (NAIs). It is a recommendation by regulatory authorities to monitor for resistance during the development of anti-influenza medications. An additional requirement by regulators is to examine amino acid sequences for minority species harbouring resistance substitutions. In a Phase III study of intravenous (IV) zanamivir respiratory samples were analysed for the presence of resistant quasi species using Next Generation Sequencing (NGS). In this study ten resistance substitutions, two of which were treatment emergent, were detected by NGS that otherwise would not have been detectable by Sanger sequencing. None of the substitutions were present at any other timepoints analysed. The effect these mutations have on clinical response is difficult to characterize; in fact, all patients from which these variants were isolated had a successful clinical outcome and the effect on clinical response was therefore likely minimal. Although NGS is becoming a routine method for nucleic acid sequencing and will detect substitutions previously undetected by Sanger sequencing, the value of this technique in identifying minority species with resistance substitutions that are clinically meaningful remains to be demonstrated, particularly with acute infections such as influenza.

Research progress on the antiviral activities of natural products and their derivatives: Structure–activity relationships

Viruses spread rapidly and are well-adapted to changing environmental events. They can infect the human body readily and trigger fatal diseases. A limited number of drugs are available for specific viral diseases, which can lead to non-efficacy against viral variants and drug resistance, so drugs with broad-spectrum antiviral activity are lacking. In recent years, a steady stream of new viral diseases has emerged, which has prompted development of new antiviral drugs. Natural products could be employed to develop new antiviral drugs because of their innovative structures and broad antiviral activities. This review summarizes the progress of natural products in antiviral research and their bright performance in drug resistance issues over the past 2 decades. Moreover, it fully discusses the effect of different structural types of natural products on antiviral activity in terms of structure–activity relationships. This review could provide a foundation for the development of antiviral drugs.

Research needs for optimising wastewater-based epidemiology monitoring for public health protection

Wastewater-based epidemiology (WBE) is an unobtrusive method used to observe patterns in illicit drug use, poliovirus, and severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2). The pandemic and need for surveillance measures have led to the rapid acceleration of WBE research and development globally. With the infrastructure available to monitor SARS-CoV-2 from wastewater in 58 countries globally, there is potential to expand targets and applications for public health protection, such as other viral pathogens, antimicrobial resistance (AMR), pharmaceutical consumption, or exposure to chemical pollutants. Some applications have been explored in academic research but are not used to inform public health decision-making. We reflect on the current knowledge of WBE for these applications and identify barriers and opportunities for expanding beyond SARS-CoV-2. This paper critically reviews the applications of WBE for public health and identifies the important research gaps for WBE to be a useful tool in public health. It considers possible uses for pathogenic viruses, AMR, and chemicals. It summarises the current evidence on the following: (1) the presence of markers in stool and urine; (2) environmental factors influencing persistence of markers in wastewater; (3) methods for sample collection and storage; (4) prospective methods for detection and quantification; (5) reducing uncertainties; and (6) further considerations for public health use.

A general approach to identify low-frequency variants within influenza samples collected during routine surveillance

Influenza viruses exhibit considerable diversity between hosts. Additionally, different quasispecies can be found within the same host. High-throughput sequencing technologies can be used to sequence a patient-derived virus population at sufficient depths to identify low-frequency variants (LFV) present in a quasispecies, but many challenges remain for reliable LFV detection because of experimental errors introduced during sample preparation and sequencing. High genomic copy numbers and extensive sequencing depths are required to differentiate false positive from real LFV, especially at low allelic frequencies (AFs). This study proposes a general approach for identifying LFV in patient-derived samples obtained during routine surveillance. Firstly, validated thresholds were determined for LFV detection, whilst balancing both the cost and feasibility of reliable LFV detection in clinical samples. Using a genetically well-defined population of influenza A viruses, thresholds of at least 10⁴ genomes per microlitre and AF of ≥5 % were established as detection limits. Secondly, a subset of 59 retained influenza A (H3N2) samples from the 2016-2017 Belgian influenza season was composed. Thirdly, as a proof of concept for the added value of LFV for routine influenza monitoring, potential associations between patient data and whole genome sequencing data were investigated. A significant association was found between a high prevalence of LFV and disease severity. This study provides a general methodology for influenza LFV detection, which can also be adopted by other national influenza reference centres and for other viruses such as SARS-CoV-2. Additionally, this study suggests that the current relevance of LFV for routine influenza surveillance programmes might be undervalued.

Enhancing neutralizing activity against influenza H1N1/PR8 by engineering a single-domain VL-M2 specific into a bivalent form

Flu disease, with high mortality and morbidity, is caused by the influenza virus. Influenza infections are most effectively prevented through vaccination, but it requires annual reformulation due to the antigenic shift or drift of hemagglutinin and neuraminidase proteins. Increasing resistance to available anti-influenza drugs was also recently reported. The M2 surface protein of the influenza virus is an attractive target for universal vaccine development as it is highly conserved and multifunctional throughout the viral life cycle. This study aimed to discover a single-chain variable fragment (scFv) targeting the M2 protein of influenza A H1N1/PR8, showing neutralizing activity through plaque inhibition in virus replication. Several candidates were isolated using bio-panning, including scFv and single-domain V_L target M2 protein, which was displayed on the yeast surface. The scFv/V_L proteins were obtained with high yield and high purity through soluble expression in E. coli BL21 (DE3) pLysE strains. A single-domain V_L-M2-specific antibody, NVLM10, exhibited the highest binding affinity to influenza virions and was engineered into a bivalent format (NVL2M10) to improve antigen binding. Both antibodies inhibited virus replication in a dose-dependent manner, determined using plaque reduction- and immunocytochemistry assays. Furthermore, bivalent anti-M2 single-domain V_L antibodies significantly reduced the plaque number and viral HA protein intensity as well as viral genome (HA and NP) compared to the monovalent single-domain V_L antibodies. This suggests that mono- or bivalent single-domain V_L antibodies can exhibit neutralizing activity against influenza virus A, as determined through binding to virus particle activity.

Evolutionary features of a prolific subtype of avian influenza A virus in European waterfowl

Avian influenza A virus (AIV) is ubiquitous in waterfowl and is detected annually at high prevalence in waterfowl during the Northern Hemisphere autumn. Some AIV subtypes are globally common in waterfowl, such as H3N8, H4N6, and H6N2, and are detected in the same populations at a high frequency, annually. In order to investigate genetic features associated to the long-term maintenance of common subtypes in migratory ducks, we sequenced 248 H4 viruses isolated across 8 years (2002-9) from mallards (Anas platyrhynchos) sampled in southeast Sweden. Phylogenetic analyses showed that both H4 and N6 sequences fell into three distinct lineages, structured by year of isolation. Specifically, across the 8 years of the study, we observed lineage replacement, whereby a different HA lineage circulated in the population each year. Analysis of deduced amino acid sequences of the HA lineages illustrated key differences in regions of the globular head of hemagglutinin that overlap with established antigenic sites in homologous hemagglutinin H3, suggesting the possibility of antigenic differences among these HA lineages. Beyond HA, lineage replacement was common to all segments, such that novel genome constellations were detected across years. A dominant genome constellation would rapidly amplify in the duck population, followed by unlinking of gene segments as a result of reassortment within 2-3 weeks following introduction. These data help reveal the evolutionary dynamics exhibited by AIV on both annual and decadal scales in an important reservoir host.

The application of next generation sequencing technology in medical diagnostics: a perspective

Rapid isolation, characterization, and identification are prerequisites of any successful medical intervention to infectious disease treatment. This is a real challenge to the scientific as well as a medical community to find out a proper and robust method of pathogen detection. Classical cultural, as well as biochemical test-based identification, has its own limitations to their time-consuming and ineffectiveness for closely related pathovars. Molecular diagnostics became a popular alternative to classical techniques for the past couple of decades but it required some prior information to detect the pathogen successfully. Recently, with the advent of next-generation sequencing (NGS) technology identification, and characterization of almost all the pathogenic bacteria become possible without any information a priori. Metagenomic next generation sequencing is another specialized type of NGS that is profoundly utilized in medical biotechnology and diagnostics now a days. Therefore, the present review is focused on a brief introduction to NGS technology, its application in medical microbiology, and possible future aspects for the development of medical sciences.

From Clinical Specimen to Whole Genome Sequencing of A(H3N2) Influenza Viruses: A Fast and Reliable High-Throughput Protocol

(1) Background: Over the last few years, there has been growing interest in the whole genome sequencing (WGS) of rapidly mutating pathogens, such as influenza viruses (IVs), which has led us to carry out in-depth studies on viral evolution in both research and diagnostic settings. We aimed at describing and determining the validity of a WGS protocol that can obtain the complete genome sequence of A(H3N2) IVs directly from clinical specimens. (2) Methods: RNA was extracted from 80 A(H3N2)-positive respiratory specimens. A one-step RT-PCR assay, based on the use of a single set of specific primers, was used to retro-transcribe and amplify the entire IV type A genome in a single reaction, thus avoiding additional enrichment approaches and host genome removal treatments. Purified DNA was quantified; genomic libraries were prepared and sequenced by using Illumina MiSeq platform. The obtained reads were evaluated for sequence quality and read-pair length. (3) Results: All of the study specimens were successfully amplified, and the purified DNA concentration proved to be suitable for NGS (at least 0.2 ng/µL). An acceptable coverage depth for all eight genes of influenza A(H3N2) virus was obtained for 90% (72/80) of the clinical samples with viral loads >105 genome copies/mL. The mean depth of sequencing ranged from 105 to 200 reads per position, with the majority of the mean depth values being above 103 reads per position. The total turnaround time per set of 20 samples was four working days, including sequence analysis. (4) Conclusions: This fast and reliable high-throughput sequencing protocol should be used for influenza surveillance and outbreak investigation.

Research progress on detection techniques for point-of-care testing of foodborne pathogens

The global burden of foodborne disease is enormous and foodborne pathogens are the leading cause of human illnesses. The detection of foodborne pathogenic bacteria has become a research hotspot in recent years. Rapid detection methods based on immunoassay, molecular biology, microfluidic chip, metabolism, biosensor, and mass spectrometry have developed rapidly and become the main methods for the detection of foodborne pathogens. This study reviewed a variety of rapid detection methods in recent years. The research advances are introduced based on the above technical methods for the rapid detection of foodborne pathogenic bacteria. The study also discusses the limitations of existing methods and their advantages and future development direction, to form an overall understanding of the detection methods, and for point-of-care testing (POCT) applications to accurately and rapidly diagnose and control diseases.

A Novel Approach of Antiviral Drugs Targeting Viral Genomes

Outbreaks of viral diseases, which cause morbidity and mortality in animals and humans, are increasing annually worldwide. Vaccines, antiviral drugs, and antibody therapeutics are the most effective tools for combating viral infection. The ongoing coronavirus disease 2019 pandemic, in particular, raises an urgent need for the development of rapid and broad-spectrum therapeutics. Current antiviral drugs and antiviral antibodies, which are mostly specific at protein levels, have encountered difficulties because the rapid evolution of mutant viral strains resulted in drug resistance. Therefore, degrading viral genomes is considered a novel approach for developing antiviral drugs. The current article highlights all potent candidates that exhibit antiviral activity by digesting viral genomes such as RNases, RNA interference, interferon-stimulated genes 20, and CRISPR/Cas systems. Besides that, we introduce a potential single-chain variable fragment (scFv) that presents antiviral activity against various DNA and RNA viruses due to its unique nucleic acid hydrolyzing characteristic, promoting it as a promising candidate for broad-spectrum antiviral therapeutics.

Influenza A, Influenza B, and SARS-CoV-2 Similarities and Differences – A Focus on Diagnosis

In late December 2019, the first cases of viral pneumonia caused by an unidentified pathogen were reported in China. Two years later, SARS-CoV-2 was responsible for almost 450 million cases, claiming more than 6 million lives. The COVID-19 pandemic strained the limits of healthcare systems all across the world. Identifying viral RNA through real-time reverse transcription-polymerase chain reaction remains the gold standard in diagnosing SARS-CoV-2 infection. However, equipment cost, availability, and the need for trained personnel limited testing capacity. Through an unprecedented research effort, new diagnostic techniques such as rapid diagnostic testing, isothermal amplification techniques, and next-generation sequencing were developed, enabling accurate and accessible diagnosis. Influenza viruses are responsible for seasonal outbreaks infecting up to a quarter of the human population worldwide. Influenza and SARS-CoV-2 present with flu-like symptoms, making the differential diagnosis challenging solely on clinical presentation. Healthcare systems are likely to be faced with overlapping SARS-CoV-2 and Influenza outbreaks. This review aims to present the similarities and differences of both infections while focusing on the diagnosis. We discuss the clinical presentation of Influenza and SARS-CoV-2 and techniques available for diagnosis. Furthermore, we summarize available data regarding the multiplex diagnostic assay of both viral infections.

Genome characterization and mutation analysis of human influenza A virus in Thailand

The influenza A viruses have high mutation rates and cause a serious health problem worldwide. Therefore, this study focused on genome characterization of the viruses isolated from Thai patients based on the next-generation sequencing technology. The nasal swabs were collected from patients with influenza-like illness in Thailand during 2017-2018. Then, the influenza A viruses were detected by reverse transcription-quantitative polymerase chain reaction and isolated by MDCK cells. The viral genomes were amplified and sequenced by Illumina MiSeq platform. Whole genome sequences were used for characterization, phylogenetic construction, mutation analysis and nucleotide diversity of the viruses. The result revealed that 90 samples were positive for the viruses including 44 of A/H1N1 and 46 of A/H3N2. Among these, 43 samples were successfully isolated and then the viral genomes of 25 samples were completely amplified. Finally, 17 whole genomes of the viruses (A/H1N1, n=12 and A/H3N2, n=5) were successfully sequenced with an average of 232,578 mapped reads and 1,720 genome coverage per sample. Phylogenetic analysis demonstrated that the A/H1N1 viruses were distinguishable from the recommended vaccine strains. However, the A/H3N2 viruses from this study were closely related to the recommended vaccine strains. The nonsynonymous mutations were found in all genes of both viruses, especially in HA and NA genes. The nucleotide diversity analysis revealed negative selection in the PB1, PA, hemagglutinin (HA) and neuraminidase (NA) genes of the A/H1N1 viruses. High-throughput data in this study allow for genetic characterization of circulating influenza viruses which would be crucial for preparation against pandemic and epidemic outbreaks in the future.

A Therapeutically Active Minibody Exhibits an Antiviral Activity in Oseltamivir-Resistant Influenza-Infected Mice via Direct Hydrolysis of Viral RNAs

Emerging Oseltamivir-resistant influenza strains pose a critical public health threat due to antigenic shifts and drifts. We report an innovative strategy for controlling influenza A infections by use of a novel minibody of the 3D8 single chain variable fragment (scFv) showing intrinsic viral RNA hydrolyzing activity, cell penetration activity, and epidermal cell penetration ability. In this study, we examined 3D8 scFv’s antiviral activity in vitro on three different H1N1 influenza strains, one Oseltamivir-resistant (A/Korea/2785/2009pdm) strain, and two Oseltamivir-sensitive (A/PuertoRico/8/1934 and A/X-31) strains. Interestingly, the 3D8 scFv directly digested viral RNAs in the ribonucleoprotein complex. scFv’s reduction of influenza viral RNA including viral genomic RNA, complementary RNA, and messenger RNA during influenza A infection cycles indicated that this minibody targets all types of viral RNAs during the early, intermediate, and late stages of the virus’s life cycle. Moreover, we further addressed the antiviral effects of 3D8 scFv to investigate in vivo clinical outcomes of influenza-infected mice. Using both prophylactic and therapeutic treatments of intranasal administered 3D8 scFv, we found that Oseltamivir-resistant H1N1-infected mice showed 90% (prophylactic effects) and 40% (therapeutic effects) increased survival rates, respectively, compared to the control group. The pathological signs of influenza A in the lung tissues, and quantitative analyses of the virus proliferations supported the antiviral activity of the 3D8 single chain variable fragment. Taken together, these results demonstrate that 3D8 scFv has antiviral therapeutic potentials against a wide range of influenza A viruses via the direct viral RNA hydrolyzing activity.

Next-Generation Sequencing for Confronting Virus Pandemics

Virus pandemics have happened, are happening and will happen again. In recent decades, the rate of zoonotic viral spillover into humans has accelerated, mirroring the expansion of our global footprint and travel network, including the expansion of viral vectors and the destruction of natural spaces, bringing humans closer to wild animals. Once viral cross-species transmission to humans occurs, transmission cannot be stopped by cement walls but by developing barriers based on knowledge that can prevent or reduce the effects of any pandemic. Controlling a local transmission affecting few individuals is more efficient that confronting a community outbreak in which infections cannot be traced. Genetic detection, identification, and characterization of infectious agents using next-generation sequencing (NGS) has been proven to be a powerful tool allowing for the development of fast PCR-based molecular assays, the rapid development of vaccines based on mRNA and DNA, the identification of outbreaks, transmission dynamics and spill-over events, the detection of new variants and treatment of vaccine resistance mutations, the development of direct-acting antiviral drugs, the discovery of relevant minority variants to improve knowledge of the viral life cycle, strengths and weaknesses, the potential for becoming dominant to take appropriate preventive measures, and the discovery of new routes of viral transmission.

Composition and Dynamics of H1N1 and H7N9 Influenza A Virus Quasispecies in a Co-infected Patient Analyzed by Single Molecule Sequencing Technology

A human co-infected with H1N1 and H7N9 subtypes influenza A virus (IAV) causes a complex infectious disease. The identification of molecular-level variations in composition and dynamics of IAV quasispecies will help to understand the pathogenesis and provide guidance for precision medicine treatment. In this study, using single-molecule real-time sequencing (SMRT) technology, we successfully acquired full-length IAV genomic sequences and quantified their genotypes abundance in serial samples from an 81-year-old male co-infected with H1N1 and H7N9 subtypes IAV. A total of 26 high diversity nucleotide loci was detected, in which the A-G base transversion was the most abundant substitution type (67 and 64%, in H1N1 and H7N9, respectively). Seven significant amino acid variations were detected, such as NA:H275Y and HA: R222K in H1N1 as well as PB2:E627K and NA: K432E in H7N9, which are related to viral drug-resistance or mammalian adaptation. Furtherly, we retrieved 25 H1N1 and 22 H7N9 genomic segment haplotypes from the eight samples based on combining high-diversity nucleotide loci, which provided a more concise overview of viral quasispecies composition and dynamics. Our approach promotes the popularization of viral quasispecies analysis in a complex infectious disease, which will boost the understanding of viral infections, pathogenesis, evolution, and precision medicine.

Influenza polymerase inhibitor resistance: Assessment of the current state of the art - A report of the isirv Antiviral group

It is more than 20 years since the neuraminidase inhibitors, oseltamivir and zanamivir were approved for the treatment and prevention of influenza. Guidelines for global surveillance and methods for evaluating resistance were established initially by the Neuraminidase Inhibitor Susceptibility Network (NISN), which merged 10 years ago with the International Society for influenza and other Respiratory Virus Diseases (isirv) to become the isirv-Antiviral Group (isirv-AVG). With the ongoing development of new influenza polymerase inhibitors and recent approval of baloxavir marboxil, the isirv-AVG held a closed meeting in August 2019 to discuss the impact of resistance to these inhibitors. Following this meeting and review of the current literature, this article is intended to summarize current knowledge regarding the clinical impact of resistance to polymerase inhibitors and approaches for surveillance and methods for laboratory evaluation of resistance, both in vitro and in animal models. We highlight limitations and gaps in current knowledge and suggest some strategies for addressing these gaps, including the need for additional clinical studies of influenza antiviral drug combinations. Lessons learned from influenza resistance monitoring may also be helpful for establishing future drug susceptibility surveillance and testing for SARS-CoV-2.

Whole-genome-based phylogenomic analysis of the Belgian 2016-2017 influenza A(H3N2) outbreak season allows improved surveillance

Seasonal influenza epidemics are associated with high mortality and morbidity in the human population. Influenza surveillance is critical for providing information to national influenza programmes and for making vaccine composition predictions. Vaccination prevents viral infections, but rapid influenza evolution results in emerging mutants that differ antigenically from vaccine strains. Current influenza surveillance relies on Sanger sequencing of the haemagglutinin (HA) gene. Its classification according to World Health Organization (WHO) and European Centre for Disease Prevention and Control (ECDC) guidelines is based on combining certain genotypic amino acid mutations and phylogenetic analysis. Next-generation sequencing technologies enable a shift to whole-genome sequencing (WGS) for influenza surveillance, but this requires laboratory workflow adaptations and advanced bioinformatics workflows. In this study, 253 influenza A(H3N2) positive clinical specimens from the 2016–2017 Belgian season underwent WGS using the Illumina MiSeq system. HA-based classification according to WHO/ECDC guidelines did not allow classification of all samples. A new approach, considering the whole genome, was investigated based on using powerful phylogenomic tools including beast and Nextstrain, which substantially improved phylogenetic classification. Moreover, Bayesian inference via beast facilitated reassortment detection by both manual inspection and computational methods, detecting intra-subtype reassortants at an estimated rate of 15 %. Real-time analysis (i.e. as an outbreak is ongoing) via Nextstrain allowed positioning of the Belgian isolates into the globally circulating context. Finally, integration of patient data with phylogenetic groups and reassortment status allowed detection of several associations that would have been missed when solely considering HA, such as hospitalized patients being more likely to be infected with A(H3N2) reassortants, and the possibility to link several phylogenetic groups to disease severity indicators could be relevant for epidemiological monitoring. Our study demonstrates that WGS offers multiple advantages for influenza monitoring in (inter)national influenza surveillance, and proposes an improved methodology. This allows leveraging all information contained in influenza genomes, and allows for more accurate genetic characterization and reassortment detection.

Evaluation of the added value of viral genomic information for predicting severity of influenza infection

BACKGROUND

The severity of an influenza infection is influenced by both host and viral characteristics. This study aims to assess the relevance of viral genomic data for the prediction of severe influenza A(H3N2) infections among patients hospitalized for severe acute respiratory infection (SARI), in view of risk assessment and patient management.

METHODS

160 A(H3N2) influenza positive samples from the 2016-2017 season originating from the Belgian SARI surveillance were selected for whole genome sequencing. Predictor variables for severity were selected using a penalized elastic net logistic regression model from a combined host and genomic dataset, including patient information and nucleotide mutations identified in the viral genome. The goodness-of-fit of the model combining host and genomic data was compared using a likelihood-ratio test with the model including host data only. Internal validation of model discrimination was conducted by calculating the optimism-adjusted area under the Receiver Operating Characteristic curve (AUC) for both models.

RESULTS

The model including viral mutations in addition to the host characteristics had an improved fit ([Formula: see text]=12.03, df = 3, p = 0.007). The optimism-adjusted AUC increased from 0.671 to 0.732.

CONCLUSIONS

Adding genomic data (selected season-specific mutations in the viral genome) to the model containing host characteristics improved the prediction of severe influenza infection among hospitalized SARI patients, thereby offering the potential for translation into a prospective strategy to perform early season risk assessment or to guide individual patient management.

Nanopore metagenomic sequencing of influenza virus directly from respiratory samples: diagnosis, drug resistance and nosocomial transmission, United Kingdom, 2018/19 influenza season

BackgroundInfluenza virus presents a considerable challenge to public health by causing seasonal epidemics and occasional pandemics. Nanopore metagenomic sequencing has the potential to be deployed for near-patient testing, providing rapid infection diagnosis, rationalising antimicrobial therapy, and supporting infection-control interventions.AimTo evaluate the applicability of this sequencing approach as a routine laboratory test for influenza in clinical settings.MethodsWe conducted Oxford Nanopore Technologies (Oxford, United Kingdom (UK)) metagenomic sequencing for 180 respiratory samples from a UK hospital during the 2018/19 influenza season, and compared results to routine molecular diagnostic standards (Xpert Xpress Flu/RSV assay; BioFire FilmArray Respiratory Panel 2 assay). We investigated drug resistance, genetic diversity, and nosocomial transmission using influenza sequence data.ResultsCompared to standard testing, Nanopore metagenomic sequencing was 83% (75/90) sensitive and 93% (84/90) specific for detecting influenza A viruses. Of 59 samples with haemagglutinin subtype determined, 40 were H1 and 19 H3. We identified an influenza A(H3N2) genome encoding the oseltamivir resistance S331R mutation in neuraminidase, potentially associated with an emerging distinct intra-subtype reassortant. Whole genome phylogeny refuted suspicions of a transmission cluster in a ward, but identified two other clusters that likely reflected nosocomial transmission, associated with a predominant community-circulating strain. We also detected other potentially pathogenic viruses and bacteria from the metagenome.ConclusionNanopore metagenomic sequencing can detect the emergence of novel variants and drug resistance, providing timely insights into antimicrobial stewardship and vaccine design. Full genome generation can help investigate and manage nosocomial outbreaks.

Deepening of In Silico Evaluation of SARS-CoV-2 Detection RT-qPCR Assays in the Context of New Variants

For 1 year now, the world is undergoing a coronavirus disease-2019 (COVID-19) pandemic due to the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). The most widely used method for COVID-19 diagnosis is the detection of viral RNA by RT-qPCR with a specific set of primers and probe. It is important to frequently evaluate the performance of these tests and this can be done first by an in silico approach. Previously, we reported some mismatches between the oligonucleotides of publicly available RT-qPCR assays and SARS-CoV-2 genomes collected from GISAID and NCBI, potentially impacting proper detection of the virus. In the present study, 11 primers and probe sets investigated during the first study were evaluated again with 84,305 new SARS-CoV-2 unique genomes collected between June 2020 and January 2021. The lower inclusivity of the China CDC assay targeting the gene N has continued to decrease with new mismatches detected, whereas the other evaluated assays kept their inclusivity above 99%. Additionally, some mutations specific to new SARS-CoV-2 variants of concern were found to be located in oligonucleotide annealing sites. This might impact the strategy to be considered for future SARS-CoV-2 testing. Given the potential threat of the new variants, it is crucial to assess if they can still be correctly targeted by the primers and probes of the RT-qPCR assays. Our study highlights that considering the evolution of the virus and the emergence of new variants, an in silico (re-)evaluation should be performed on a regular basis. Ideally, this should be done for all the RT-qPCR assays employed for SARS-CoV-2 detection, including also commercial tests, although the primer and probe sequences used in these kits are rarely disclosed, which impedes independent performance evaluation.

A main event and multiple introductions of SARS-CoV-2 initiated the COVID-19 epidemic in Greece

Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a novel coronavirus responsible for the coronavirus disease 2019 (COVID-19) pandemic. Chains of infections starting from various countries worldwide seeded the outbreak of COVID-19 in Athens, capital city of Greece. A full-genome analysis of isolates from Athens' hospitals and other healthcare providers revealed the variety of SARS-CoV-2 that initiated the pandemic before lockdown and passenger flight restrictions. A dominant variant, encompassing the G614D amino acid substitution, spread through a major virus dispersal event, and sporadic introductions of rare variants characterized the local initiation of the epidemic. Mutations within the genome highlighted the genetic drift of the virus as rare variants emerged. An important variant contained a premature stop codon in orf7a leading to the truncation of a possibly important for viral pathogenesis domain. This study may serve as a reference for resolving future lines of infection in the area, especially after resumption of passenger flight connections to Athens and Greece during summer of 2020.

Conventional and Nanotechnology-Based Sensing Methods for SARS Coronavirus (2019-nCoV)

Ongoing pandemic coronavirus (COVID-19) has affected over 218 countries and infected 88,512,243 and 1,906,853 deaths reported by Jan. 8, 2021. At present, vaccines are being developed in Europe, Russia, USA, and China, although some of these are in phase III of trials, which are waiting to be available for the general public. The only option available now is by vigorous testing, isolation of the infected cases, and maintaining physical and social distances. Numerous methods are now available or being developed for testing the suspected cases, which may act as carriers of the virus. In this review, efforts have been made to discuss the conventional as well as fast, rapid, and efficient testing methods developed for the diagnosis of 2019-nCoV.Testing methods can be based on the sensing of targets, which include RNA, spike proteins and antibodies such as IgG and IgM. Apart from the development of RNA targeted PCR, antibody and VSV pseudovirus neutralization assay along with several other diagnostic techniques have been developed. Additionally, nanotechnology-based sensors are being developed for the diagnosis of the virus, and these are also discussed.

Genomic-informed pathogen surveillance in Africa: opportunities and challenges

The ongoing COVID-19 pandemic has highlighted the need to incorporate pathogen genomics for enhanced disease surveillance and outbreak management in Africa. The genomics of SARS-CoV-2 has been instrumental to the timely development of diagnostics and vaccines and in elucidating transmission dynamics. Global disease control programmes, including those for tuberculosis, malaria, HIV, foodborne pathogens, and antimicrobial resistance, also recommend genomics-based surveillance as an integral strategy towards control and elimination of these diseases. Despite the potential benefits, capacity remains low for many public health programmes in Africa. The COVID-19 pandemic presents an opportunity to reassess and strengthen surveillance systems and potentially integrate emerging technologies for preparedness of future epidemics and control of endemic diseases. We discuss opportunities and challenges for integrating pathogen genomics into public health surveillance systems in Africa. Improving accessibility through the creation of functional continent-wide networks, building multipathogen sequencing cores, training a critical mass of local experts, development of standards and policies to facilitate best practices for data sharing, and establishing a community of practice of genomics experts are all needed to use genomics for improved disease surveillance in Africa. Coordination and leadership are also crucial, which the Africa Centres for Disease Control and Prevention seeks to provide through its institute for pathogen genomics.

Can molecular dynamics explain decreased pathogenicity in mutant camphecene-resistant influenza virus?

ABSTARCTThe development of new anti-influenza drugs remains an active area, and efforts in this direction will likely continue far into the future. In this paper, we present the results of a theoretical study explaining the mechanisms behind the antiviral activity of camphor derivatives. These include camphecene and a number of its analogues. The compounds tested can inhibit hemagglutinin (HA) by binding to it at two possible sites. Moreover, the binding site located at the site of proteolysis is the most important. Serial passaging of influenza in the presence of camphecene leads to the formation of mutation-associated resistance. Specifically, camphecene causes a significant mutation in HA (V615L). This substitution likely reduces the affinity of the compound for the binding site due to steric restriction of the positioning of camphecene in the binding cavity. Molecular dynamics (MD) simulation results show that the mutant HA is a more stable structure in terms of thermodynamics. In other words, launching conformational rearrangements preceding the transition from pre- to post-fusion requires more energy than in wild type HA. This may well explain the lower virulence seen with the camphecene-resistant strain.

RNA Secondary Structure as a First Step for Rational Design of the Oligonucleotides towards Inhibition of Influenza A Virus Replication

Influenza is an important research subject around the world because of its threat to humanity. Influenza A virus (IAV) causes seasonal epidemics and sporadic, but dangerous pandemics. A rapid antigen changes and recombination of the viral RNA genome contribute to the reduced effectiveness of vaccination and anti-influenza drugs. Hence, there is a necessity to develop new antiviral drugs and strategies to limit the influenza spread. IAV is a single-stranded negative sense RNA virus with a genome (viral RNA—vRNA) consisting of eight segments. Segments within influenza virion are assembled into viral ribonucleoprotein (vRNP) complexes that are independent transcription-replication units. Each step in the influenza life cycle is regulated by the RNA and is dependent on its interplay and dynamics. Therefore, viral RNA can be a proper target to design novel therapeutics. Here, we briefly described examples of anti-influenza strategies based on the antisense oligonucleotide (ASO), small interfering RNA (siRNA), microRNA (miRNA) and catalytic nucleic acids. In particular we focused on the vRNA structure-function relationship as well as presented the advantages of using secondary structure information in predicting therapeutic targets and the potential future of this field.

An Overview on SARS-CoV-2 (COVID-19) and Other Human Coronaviruses and Their Detection Capability via Amplification Assay, Chemical Sensing, Biosensing, Immunosensing, and Clinical Assays

A novel coronavirus of zoonotic origin (SARS-CoV-2) has recently been recognized in patients with acute respiratory disease. COVID-19 causative agent is structurally and genetically similar to SARS and bat SARS-like coronaviruses. The drastic increase in the number of coronavirus and its genome sequence have given us an unprecedented opportunity to perform bioinformatics and genomics analysis on this class of viruses. Clinical tests like PCR and ELISA for rapid detection of this virus are urgently needed for early identification of infected patients. However, these techniques are expensive and not readily available for point-of-care (POC) applications. Currently, lack of any rapid, available, and reliable POC detection method gives rise to the progression of COVID-19 as a horrible global problem. To solve the negative features of clinical investigation, we provide a brief introduction of the general features of coronaviruses and describe various amplification assays, sensing, biosensing, immunosensing, and aptasensing for the determination of various groups of coronaviruses applied as a template for the detection of SARS-CoV-2. All sensing and biosensing techniques developed for the determination of various classes of coronaviruses are useful to recognize the newly immerged coronavirus, i.e., SARS-CoV-2. Also, the introduction of sensing and biosensing methods sheds light on the way of designing a proper screening system to detect the virus at the early stage of infection to tranquilize the speed and vastity of spreading. Among other approaches investigated among molecular approaches and PCR or recognition of viral diseases, LAMP-based methods and LFAs are of great importance for their numerous benefits, which can be helpful to design a universal platform for detection of future emerging pathogenic viruses.

Crippling life support for SARS-CoV-2 and other viruses through synthetic lethality

With the rapid global spread of SARS-CoV-2, we have become acutely aware of the inadequacies of our ability to respond to viral epidemics. Although disrupting the viral life cycle is critical for limiting viral spread and disease, it has proven challenging to develop targeted and selective therapeutics. Synthetic lethality offers a promising but largely unexploited strategy against infectious viral disease; as viruses infect cells, they abnormally alter the cell state, unwittingly exposing new vulnerabilities in the infected cell. Therefore, we propose that effective therapies can be developed to selectively target the virally reconfigured host cell networks that accompany altered cellular states to cripple the host cell that has been converted into a virus factory, thus disrupting the viral life cycle.

Use of Whole Genome Sequencing Data for a First in Silico Specificity Evaluation of the RT-qPCR Assays Used for SARS-CoV-2 Detection

The current COronaVIrus Disease 2019 (COVID-19) pandemic started in December 2019. COVID-19 cases are confirmed by the detection of SARS-CoV-2 RNA in biological samples by RT-qPCR. However, limited numbers of SARS-CoV-2 genomes were available when the first RT-qPCR methods were developed in January 2020 for initial in silico specificity evaluation and to verify whether the targeted loci are highly conserved. Now that more whole genome data have become available, we used the bioinformatics tool SCREENED and a total of 4755 publicly available SARS-CoV-2 genomes, downloaded at two different time points, to evaluate the specificity of 12 RT-qPCR tests (consisting of a total of 30 primers and probe sets) used for SARS-CoV-2 detection and the impact of the virus' genetic evolution on four of them. The exclusivity of these methods was also assessed using the human reference genome and 2624 closely related other respiratory viral genomes. The specificity of the assays was generally good and stable over time. An exception is the first method developed by the China Center for Disease Control and prevention (CDC), which exhibits three primer mismatches present in 358 SARS-CoV-2 genomes sequenced mainly in Europe from February 2020 onwards. The best results were obtained for the assay of Chan et al. (2020) targeting the gene coding for the spiking protein (S). This demonstrates that our user-friendly strategy can be used for a first in silico specificity evaluation of future RT-qPCR tests, as well as verifying that the former methods are still capable of detecting circulating SARS-CoV-2 variants.