Virus Database Research Articles

Respiratory virus behavior: Results of laboratory-based epidemiological surveillance.

Respiratory viruses have clinical and epidemiological importance. With the COVID-19 pandemic, interest has focused on SARS-CoV-2, but as a result, the number of samples available for the differential diagnosis of other respiratory viruses has increased. Cross-sectional study. To describe the epidemiological behavior of respiratory viruses based on a laboratory-based epidemiological surveillance system using data from 2017 to 2023. Univariate, bivariate and multivariate analyses of data from a laboratory database of respiratory viruses detected by multiplex RT‒qPCR were performed. A total of 4,632 samples with positive results for at least 1 respiratory virus, not including influenza or SARS-CoV-2, were analyzed. The most common virus detected was respiratory syncytial virus in 1,467 (26.3%) samples, followed by rhinovirus in 1,384 (24.8%) samples. Most of the samples were from children under 5 years of age. The age-adjusted odds ratio (OR) of death for patients infected with parainfluenza virus 4 was 4.1 (95% confidence interval [95% CI] 2.0-8.2). Respiratory syncytial virus and rhinovirus had the highest frequency and proportion of coinfections, whereas parainfluenza virus 4 was associated with an increased risk of death.

Viral Diversity and Ecological Impact of DNA Viruses in Dominant Tick Species in China.

Ticks are blood-feeding ectoparasites that also transmit various pathogens, posing severe risks to human and animal health. DNA viruses play a crucial role in the microbial ecology of ticks, but their distribution and ecological significance remain largely undetermined. Here, we assembled an extensive catalog encompassing 4320 viral operational taxonomic units (vOTUs) from six main dominant tick species in China, of which 94.8% have not been found in any other environment. To bridge the knowledge gap in tick DNA virus research and provide a crucial resource platform, we developed the Tick DNA Virus Database. This database includes the vOTUs that are known to cause diseases. Most of the predicted vOTUs are associated with dominant bacterial and archaeal phyla. We identified 105 virus-encoded putative auxiliary metabolic genes (AMGs) that are involved in host metabolism and environmental adaptation, potentially influencing ticks through both top-down and bottom-up mechanisms. The identification of microbial communities and antibiotic resistance in wild tick species suggests that wild ticks are reservoirs of antibiotic resistance and potential spreaders of antibiotic resistance. These findings reveal the potential role of tick viruses in ecosystems, highlighting the importance of monitoring tick microbiomes to address global public health challenges.

XAI-driven antivirus in pattern identification of citadel malware

Background and Objective:The constant growth of invasions and information theft by using infected software has always been a problem. According to McAfee labs in 2020, on average, 480 new viruses are created each hour. The means of identifying such threats, categorizing and creating vaccines may not be that fast. Thanks to the increasing processing power and the popularity of artificial intelligence, it is now possible to integrate intelligence on an antivirus engine to enhance its protecting capabilities. And doing so with good algorithms and parameterization can be a key asset in securing one’s environment. In this work we analyze the overall performance of our antivirus and compare it with other state-of-art antiviruses. Methods:In this work, we create an extreme neural network which can perform quick training time and have satisfactory accuracy when classifying unknown files that may or may not be infected with Citadel. Our virus database is built with many examples of well-known infected files, and our results are compared with other intelligent antiviruses created by other companies and/or researchers.The proposed technique stands out as a beneficial practice in terms of efficiency and interpretability; it achieves a very reduced number of neurons through its thorough pruning process. This reduction of dimensionality shrinks the input layer by 98%, enhancing not only data interpretation but also reducing the time required for training. Results:Our antivirus achieves an overall performance of 98.50% when distinguishing harmless and malicious portable executable (PE) programs. To enhance accuracy, we conducted tests under various initial conditions, learning functions, and architectures. Our successful results consumes only 0.19 s of training when using the complete training database and the response time is so immediate that the computer rounds it to 0.00 s. Conclusions:In this work, we conclude that mELM implementations are viable, and their performance can match state-of-the-art ones. It’s training and classification times are among the fastest of the algorithms tested, and the accuracy in detecting Citadel-infected PEs is acceptable.

Exploring the roles of ribosomal peptides in prokaryote-phage interactions through deep learning-enabled metagenome mining

BackgroundMicrobial secondary metabolites play a crucial role in the intricate interactions within the natural environment. Among these metabolites, ribosomally synthesized and post-translationally modified peptides (RiPPs) are becoming a promising source of therapeutic agents due to their structural diversity and functional versatility. However, their biosynthetic capacity and ecological functions remain largely underexplored.ResultsHere, we aim to explore the biosynthetic profile of RiPPs and their potential roles in the interactions between microbes and viruses in the ocean, which encompasses a vast diversity of unique biomes that are rich in interactions and remains chemically underexplored. We first developed TrRiPP to identify RiPPs from ocean metagenomes, a deep learning method that detects RiPP precursors in a hallmark gene-independent manner to overcome the limitations of classic methods in processing highly fragmented metagenomic data. Applying this method to metagenomes from the global ocean microbiome, we uncover a diverse array of previously uncharacterized putative RiPP families with great novelty and diversity. Through correlation analysis based on metatranscriptomic data, we observed a high prevalence of antiphage defense-related and phage-related protein families that were co-expressed with RiPP families. Based on this putative association between RiPPs and phage infection, we constructed an Ocean Virus Database (OVD) and established a RiPP-involving host-phage interaction network through host prediction and co-expression analysis, revealing complex connectivities linking RiPP-encoding prokaryotes, RiPP families, viral protein families, and phages. These findings highlight the potential of RiPP families involved in prokaryote-phage interactions and coevolution, providing insights into their ecological functions in the ocean microbiome.ConclusionsThis study provides a systematic investigation of the biosynthetic potential of RiPPs from the ocean microbiome at a global scale, shedding light on the essential insights into the ecological functions of RiPPs in prokaryote-phage interactions through the integration of deep learning approaches, metatranscriptomic data, and host-phage connectivity. This study serves as a valuable example of exploring the ecological functions of bacterial secondary metabolites, particularly their associations with unexplored microbial interactions.CSrTVep6AzTb_yem78LPYEVideo

First Report of Tobacco Streak Virus in Cannabis sativa in New York.

In 2022, virus-like symptoms were observed in a field of diverse hemp (Cannabis sativa L.) germplasm in Ontario County, New York. Less than 1% of plants exhibited stunting and curled leaves (Figure S1), consistent with tobacco streak virus (TSV) symptoms on other plants (Liu et al. 2022). Most typically, the plants were considerably reduced in overall size, with upwards, adaxial curling along the leaf margin with newer leaves appearing to be the most affected. Fifteen symptomatic plants representing nine accessions were tested for 12 viruses and viroids through Agdia Testing Services (Elkhart, IN). Of these, eight plants representing five accessions including: G 33204 21UO SD ('Cherry Wine S1'), G 33211 21UO SD ('Wife'), G 33225 22CL01 CL ('Candida #2'), G 33270 22UO SD ('Falkowski CBD Mix'), and G 33365 22UO SD ('Queen Dream'), were positive for TSV, a type of Ilarvirus in the Bromoviridae family. Presence of TSV was confirmed through enzyme-linked immunosorbent assay testing. TSV is a positive-sense, single-stranded RNA virus with a wide host range that can be transmitted by thrips, mechanical injury, seed, and pollen (Zambrana-Echevarría et al. 2021). To confirm the presence of TSV, two putatively TSV-infected samples were subjected to RNA-Seq analysis. RNA was extracted using the RNeasy Plant Mini Kit (Qiagen, Aarhus, Denmark) per manufacturer's direction. Stranded RNA libraries were prepared using the Illumina TruSeq Stranded Total RNA with Ribo-Zero Plant kit (San Diego, California, USA). Paired-end 2x150bp sequencing was performed on an Illumina NovaSeq6000 sequencer. RNA-Seq data was trimmed using the fastp program (Chen et al. 2018) with default parameters to remove adapter sequences and low-quality bases. After filtering, 49,696,041 and 56,126,804 paired-end reads were retained from 'Wife' and 'Falkowski CBD Mix' samples, respectively. Filtered RNA-seq reads were mapped to TSV genome accession GCF_000865505.1 using the bowtie2 (Langmead & Salzberg 2012) aligner with default parameters. From 'Wife' and 'Falkowski CBD Mix' samples, 153 and 139 reads mapped to the TSV reference genome. To further validate the presence of TSV reads, RNA-Seq data was analyzed using the Kraken2 pipeline (Wood et al. 2019). Using the Kraken2 virus database, reads associated with TSV (NCBI taxonomy ID: 12317) were identified. This analysis identified 172 and 151 TSV reads from 'Wife' and 'Falkowski CBD Mix,' respectively. Higher numbers of reads identified using the Kraken2 analysis is due to the more permissive k-mer matching approach implemented in Kraken2. Furthermore, we identified several other virus taxa in the samples. Of note, both samples had a high number of reads associated with Amazon lily mild mottle virus with 254,493 and 116,150 reads from 'Wife' and 'Falkowski CBD Mix,' respectively. Among other virus species belonging to Ilarviruses, Cassava Ivorian bacilliform virus and Cowpea chlorotic mottle viruses were detected from both samples. To further validate infection by TSV, samples from both ELISA-positive and ELISA-negative plants were subjected to PCR using the primers and protocol described in Zambrana-Echevarría et al. 2021. Amplification of an approximately 700 base-pair product was observed in the putatively ELISA-positive samples, but not in the ELISA-negative samples. The amplicons were further cloned into the pGEM-T Easy vector (Promega, Madison, WI, U.S.A) using the manufacturer's protocol and sequenced using M13 forward and M13 reverse primers (Functional Biosciences, Madison, WI, U.S.A). Sequencing results indicated considerable similarity to TSV genomes available in GenBank, between 88% and 99%. Raw sequence data generated from this study was deposited in NCBI under the bioproject ID PRJNA1009441. Though it cannot be ruled out that the observed symptoms were caused exclusively by TSV infection due to the high number of other viral reads, the results contribute to the literature that indicates hemp can host TSV and should be considered a potential source of TSV inoculum (Chiginsky et al. 2021). This new inoculum source could cause significant crop damage and economic loss when grown with TSV susceptible row and specialty crops.

First report of strawberry polerovirus 1 in strawberry in Italy.

Strawberry (Fragaria × ananassa Duch.) was introduced in Sicily (Italy) in the 1930s in the small town of Maletto, on the slopes of Etna volcan, where it's currently cultivated in a total area of 30 ha. The French cv. 'Madame Moutot', appreciated for its unique flavor and intense fragrance, was there propagated vegetatively and after decades, the distinctive 'Etna ecotype' originated by adaptation to the peculiar environmental conditions of the area (Milella et al., 2006). In May 2023, in a 0.5 ha "Etna ecotype" strawberry field, virus-like symptoms were observed in approximately 50% of the plants. Symptoms included severe dwarfing, leaf cupping and chlorotic spotting which lead to decline of infected plants. To investigate the etiology of the disease, leaf samples were collected from eight symptomatic plants for analysis by High-Throughput Sequencing (HTS). To this aim, total RNAs were extracted by using the RNeasy PowerPlant Kit (Qiagen, Germany). The RNAs were pooled, depleted of ribosomal RNA (QIAseq FastSelect; Qiagen), and a library was prepared according to the Illumina DNA Prep Kit. Sequencing on a NextSeq2000 instrument at Leibniz Institute DSMZ (Braunschweig, Germany) generated 31,149,784 of paired-end reads (150 nt), which were further analyzed in Geneious Prime version 2023.2 (Biomatters) using a custom workflow for virus discovery and genome assembly. Analysis of the assembled contigs by local BLASTn and BLASTp alignments against a custom plant virus database of NCBI nuclear-core (NC) reference sequences assigned a number of contigs to accession NC_025435, strawberry polerovirus 1 (SPV-1). Reconstruction of the virus genome by assembly of contigs and reads alignment resulted in a nearly complete genome sequence of SPV-1 (GenBank Acc. No. OR989958) showing by BLASTn 98.69% identity to the SPV-1 NC reference sequence, and 98.99 % identity with an isolate from the Czech Republic (GenBank Acc. OL421571). To confirm the presence of SPV-1 in each sample, RT-PCR using specific primers designed in this study SPV-1-CP-1F (5'-TCGAGATACGTCTAGAACTGCAA-3') and SPV-1-CP-1R (5'-GAGAGGCCCCTTCTACCTATTTG-3') targeting the entire 623 bp coat protein (CP) gene was performed. Amplicons of the expected size were obtained in five samples and Sanger-sequenced. The resulting sequences shared 99.85% - 100% of identity to the HTS - derived sequence (GenBank Acc. No. OR989958) through BLASTn analysis. Strawberry mottle virus (SMoV), strawberry mild yellow edge virus (SMYEV) and strawberry crinkle virus (SCV) were detected in the same library in addition to SPV-1 and then confirmed by RT-PCR using specific primers (Martin & Tzanetakis 2013). Strawberry polerovirus 1, related to the genus Polerovirus in the family Solemoviridae, was first reported in strawberries in Canada (Xiang et al. 2015) and was thereafter detected in the United States (Thekke-Veetil & Tzanetakis 2016), Argentina (Luciani et al. 2016), and Nepal (Kuwak et al. 2022). To date, the virus has been reported in Europe only in the Czech Republic (Franova et al. 2021). To our knowledge, this is the first report of SPV-1 in strawberry plants in Italy. Although the correlation between SPV-1 and strawberry decline (SD) is still uncertain (Xiang et al. 2015) transmission of the virus via aphids has recently been demonstrated (Franova et al. 2021). Our report let to hypothesize that its dissemination in Europe can be considered as increasing.

A broad wastewater screening and clinical data surveillance for virus-related diseases in the metropolitan Detroit area in Michigan

BackgroundPeriodic bioinformatics-based screening of wastewater for assessing the diversity of potential human viral pathogens circulating in a given community may help to identify novel or potentially emerging infectious diseases. Any identified contigs related to novel or emerging viruses should be confirmed with targeted wastewater and clinical testing.ResultsDuring the COVID-19 pandemic, untreated wastewater samples were collected for a 1-year period from the Great Lakes Water Authority Wastewater Treatment Facility in Detroit, MI, USA, and viral population diversity from both centralized interceptor sites and localized neighborhood sewersheds was investigated. Clinical cases of the diseases caused by human viruses were tabulated and compared with data from viral wastewater monitoring. In addition to Betacoronavirus, comparison using assembled contigs against a custom Swiss-Prot human virus database indicated the potential prevalence of other pathogenic virus genera, including: Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Bocaparvovirus, Molluscipoxvirus, Parechovirus, Roseolovirus, Lymphocryptovirus, Alphavirus, Spumavirus, Lentivirus, Deltaretrovirus, Enterovirus, Kobuvirus, Gammaretrovirus, Cardiovirus, Erythroparvovirus, Salivirus, Rubivirus, Orthohepevirus, Cytomegalovirus, Norovirus, and Mamastrovirus. Four nearly complete genomes were recovered from the Astrovirus, Enterovirus, Norovirus and Betapolyomavirus genera and viral species were identified.ConclusionsThe presented findings in wastewater samples are primarily at the genus level and can serve as a preliminary “screening” tool that may serve as indication to initiate further testing for the confirmation of the presence of species that may be associated with human disease. Integrating innovative environmental microbiology technologies like metagenomic sequencing with viral epidemiology offers a significant opportunity to improve the monitoring of, and predictive intelligence for, pathogenic viruses, using wastewater.

Globally distributed bacteriophage genomes reveal mechanisms of tripartite phage-bacteria-coral interactions.

Reef-building corals depend on an intricate community of microorganisms for functioning and resilience. The infection of coral-associated bacteria by bacteriophages can modify bacterial ecological interactions, yet very little is known about phage functions in the holobiont. This gap stems from methodological limitations that have prevented the recovery of high-quality viral genomes and bacterial host assignment from coral samples. Here, we introduce a size fractionation approach that increased bacterial and viral recovery in coral metagenomes by 9-fold and 2-fold, respectively, and enabled the assembly and binning of bacterial and viral genomes at relatively low sequencing coverage. We combined these viral genomes with those derived from 677 publicly available metagenomes, viromes, and bacterial isolates from stony corals to build a global coral virus database of over 20,000 viral genomic sequences spanning four viral realms. The tailed bacteriophage families Kyanoviridae and Autographiviridae were the most abundant, replacing groups formerly referred to as Myoviridae and Podoviridae, respectively. Prophage and CRISPR spacer linkages between these viruses and 626 bacterial metagenome-assembled genomes and bacterial isolates showed that most viruses infected Alphaproteobacteria, the most abundant class, and less abundant taxa like Halanaerobiia and Bacteroidia. A host-phage-gene network identified keystone viruses with the genomic capacity to modulate bacterial metabolic pathways and direct molecular interactions with eukaryotic cells. This study reveals the genomic basis of nested symbioses between bacteriophage, bacteria, and the coral host and its endosymbiotic algae.

RNA virus diversity in rodents.

Many zoonotic disease emergencies are associated with RNA viruses in rodents that substantially impact public health. With the widespread application of meta-genomics and meta-transcriptomics for virus discovery over the last decade, viral sequences deposited in public databases have expanded rapidly, and the number of novel viruses discovered in rodents has increased. As important reservoirs of zoonotic viruses, rodents have attracted increasing attention for the risk of potential spillover of rodent-borne viruses. However, knowledge of rodent viral diversity and the major factors contributing to the risk of zoonotic epidemic outbreaks remains limited. Therefore, this study analyzes the diversity and composition of rodent RNA viruses using virus records from the Database of Rodent-associated Viruses (DRodVir/ZOVER), which covers the published literatures and records in GenBank database, reviews the main rodent RNA virus-induced human infectious diseases, and discusses potential challenges in this field.

Genome analysis of viruses of Phenuiviridae, Betaflexiviridae and Bromoviridae, and apple scar skin viroid in pear by high-throughput sequencing revealing host expansion of a rubodvirus and an ilarvirus

Pear (Pyrus spp.) is an important perennial fruit crop of India. During May 2022, pear leaf samples were collected from the orchard of ICAR-Indian Agricultural Research Institute, Regional Station, Dhanda, Shimla, Himachal Pradesh, India. RNA sequencing of two pooled samples, Pe1 and Pe2, was done using NovaSeq 6000. Host unaligned reads were de novo assembled into contigs and annotated through BLAST using the virus database. Near complete genome sequences of apple rubbery wood virus 1 (ARWV-1), apple necrotic mosaic virus (ApNMV), citrus virus A (CiVA), apple stem grooving virus (ASGV), apple stem pitting virus (ASPV), apple chlorotic leaf spot virus (ACLSV), and a genetic variant of ASGV named as ASGV-Shimla, and a partial sequence of apple scar skin viroid (ASSVd) were assembled. ARWV-1 and ApNMV belong to the genus Rubodvirus and Ilarvirus having tripartite negative sense and positive sense single stranded RNA genomes, respectively, and their presence in pear trees was observed for the first time indicating the host expansion. Presence of CiVA, ASGV and ACLSV in pear in India was also recorded for the first time in India. The fragments per kilobase of transcript per million reads mapped estimation showed the dominance of ASPV and CiVA in Pe1 and Pe2, respectively. Single nucleotide variants (SNVs) analysis revealed that ASPV had the highest number of SNVs (477), while ACLSV had the lowest number of SNVs (1). The presence of ARWV-1, ApNMV, CiVA, ASPV, ASGV, ACLSV, ASGV-Shimla, and ASSVd was also confirmed in pear samples through Sanger sequencing. The present study widens our understanding of the pear virome and host range expansion of viruses in the genus Rubodvirus and Ilarvirus. This information will be useful in biological study of these viruses and virus indexing programs in pear.

Detection and molecular analysis of shallot latent virus infecting Allium sativum in Zimbabwe

The prevalence of phytoviruses threatens food security worldwide. A number of factors can contribute to phytoviruses remaining unidentified, including lack of resources and ignorance of their existence. This study aimed to identify and understand the molecular characteristics and phylogeny of shallot latent virus infecting garlic (Allium sativum) in Zimbabwe. Leaf samples, collected from garlic farms in and around Harare Metropolitan Province, Zimbabwe in 2015, 2016 and 2020, were tested for the presence of shallot latent virus (SLV) using DAS ELISA. 89 % of the samples tested positive for SLV. High throughput sequencing (HTS) was subsequently used to recover the genome of the virus isolate. RNA was extracted from SLV-positive samples and used in ribo-depleted RNA-Seq on an Illumina platform. Both de novo and reference assembly were used to generate the full-length genome of the SLV isolate q23-Manresa, accession number MG657357, infecting garlic in Zimbabwe. Its non-recombinant genome consists of 8423 nucleotides excluding the polyA tail. Three relationships were observed from the phylogenetic analyses of the isolate q23-Manresa to homologous non-recombinant SLV isolates identified in different parts of the world depending on the portion of the genome selected. The information generated in this study will contribute towards building a database of garlic-infecting viruses and developing surveillance strategies.

Effect of wastewater collection and concentration methods on assessment of viral diversity

Monitoring of potentially pathogenic human viruses in wastewater is of crucial importance to understand disease trends in communities, predict potential outbreaks, and boost preparedness and response by public health departments. High throughput metagenomic sequencing opens an opportunity to expand the capabilities of wastewater surveillance. However, there are major bottlenecks in the metagenomic enabled wastewater surveillance, including the complexities in selecting appropriate sampling and concentration/virus enrichment methods as well as in bioinformatic analysis of complex samples with low human virus concentrations. To evaluate the abilities of two commonly used sampling and concentration methods in virus identification, virus communities concentrated with Virus Adsorption-Elution (VIRADEL) and PolyEthylene Glycol (PEG) precipitation were compared for three interceptor sites. Results indicated that more viral reads were obtained by the VIRADEL concentration method, with 2.84 ± 0.57 % viral reads in the sample. For samples concentrated with PEG, the average proportion of viral reads in the sample was 0.63 ± 0.19 %. In all wastewater samples, bacteriophage affiliated with the families Siphoviridae, Myoviridae and Podoviridae were found to be the abundant populations. Comparison against a custom Swiss-Prot human virus database indicated that the relatively abundant human viruses (average proportions in human virus community greater than 1.00 %) in samples concentrated with the VIRADEL method were Orthopoxvirus, Rhadinovirus, Parapoxvirus, Varicellovirus, Hepatovirus, Simplexvirus, Molluscipoxvirus, Parechovirus, Lymphocryptovirus, and Spumavirus. In samples concentrated with the PEG method, fewer human viruses were found to be relatively abundant. These were Orthopoxvirus, Rhadinovirus, Varicellovirus, Simplexvirus, Molluscipoxvirus, Lymphocryptovirus, and Betacoronavirus. Contigs of Betacoronavirus, which contains severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), were identified in VIRADEL and PEG samples. Our study demonstrates the feasibility of using metagenomics in wastewater surveillance as a first screening tool and the need for selecting the appropriate virus concentration methods and optimizing bioinformatic approaches in analyzing metagenomic data of wastewater samples.

Comparative genomics of spike, envelope, and nucleocapsid protein of severe acute respiratory syndrome coronavirus 2.

Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2) upsurge sprang up in Wuhan, China, in late December 2019. Due to the exceptionally high mutation frequency, comparative genomics of viruses isolated throughout time and in various geographical locations are crucial. To better understand how SARS-CoV-2 heterogeneity has changed around the globe, this research was conducted. Nucleotide and protein sequences of SARS-CoV-2, SARS-CoV, and bat SARS-like CoV were extracted from the NCBI Virus database. The Wuhan SARS-CoV-2 variant was used as a reference. Molecular Evolutionary Genetics Study performed the phylogenetic analysis, while the Genome Detective Coronavirus Typing Tool performed the mutational analysis. The evolutionary research has revealed that bats are the primary host for coronavirus evolution and the origin of the formation of SARS-CoV and SARS-CoV-2. Numerous mutations have been discovered in the spike, envelope, and nucleocapsid protein. The current research findings may have an implication that facilitates the development of prospective immunization candidates/small pharmacological compounds targeting COVID-19.

Enhancing biosecurity against virus disease threats to Australian grain crops: current situation and future prospects

Australia is a major grain exporter, and this trade makes an important contribution to its economy. Fortunately, it remains free of many damaging virus diseases and virus vectors found elsewhere. However, its crop biosecurity is under increasing pressure from global ecological, climatic, and demographic challenges. Stringent biosecurity and plant health programs safeguard Australian grain production from damaging virus and virus vector incursions entering via different pathways. These programs formerly relied upon traditional testing procedures (indicator hosts, serology, PCRs) to intercept incoming virus-contaminated plant material. Recently, the integration of rapid genomic diagnostics innovation involving High Throughput Sequencing (HTS) smart tools into sample testing schedules is under exploration to improve virus testing accuracy, efficiency, and cost effectiveness under diverse circumstances. This process includes evaluating deployment of Illumina and Oxford Nanopore Technology shotgun sequencing. It also includes evaluating targeted viral genome HTS and virus vector metabarcoding approaches. In addition, using machine learning and deep learning capacities for big data analyses and remote sensing technologies will improve virus surveillance. Tracking damaging virus variants will be improved by surveillance networks which combine virus genomic-surveillance systems with an interoperable virus database. Sequencing Australian virus specimen collections will help ensure the accuracy of virus identifications based solely on genetic information. Enhancing routine diagnosis and data collection using these innovations will improve post entry virus interception and background virus and vector surveillance. This will help reduce the frequency of new incursions, improve virus management during eradication, containment and other plant health activities, and achieve more profitable Australian grain production.

Navigating the Landscape: A Comprehensive Review of Current Virus Databases.

Viruses are abundant and diverse entities that have important roles in public health, ecology, and agriculture. The identification and surveillance of viruses rely on an understanding of their genome organization, sequences, and replication strategy. Despite technological advancements in sequencing methods, our current understanding of virus diversity remains incomplete, highlighting the need to explore undiscovered viruses. Virus databases play a crucial role in providing access to sequences, annotations and other metadata, and analysis tools for studying viruses. However, there has not been a comprehensive review of virus databases in the last five years. This study aimed to fill this gap by identifying 24 active virus databases and included an extensive evaluation of their content, functionality and compliance with the FAIR principles. In this study, we thoroughly assessed the search capabilities of five database catalogs, which serve as comprehensive repositories housing a diverse array of databases and offering essential metadata. Moreover, we conducted a comprehensive review of different types of errors, encompassing taxonomy, names, missing information, sequences, sequence orientation, and chimeric sequences, with the intention of empowering users to effectively tackle these challenges. We expect this review to aid users in selecting suitable virus databases and other resources, and to help databases in error management and improve their adherence to the FAIR principles. The databases listed here represent the current knowledge of viruses and will help aid users find databases of interest based on content, functionality, and scope. The use of virus databases is integral to gaining new insights into the biology, evolution, and transmission of viruses, and developing new strategies to manage virus outbreaks and preserve global health.

An ARMS-Multiplex PCR Targeting SARS-CoV-2 Omicron Sub-Variants.

As of November 2021, the SARS-CoV-2 Omicron variant had made its appearance, gradually replacing the predominant Delta variant. Since its emergence, the Omicron variant has been continuously evolving through more than 500 strains, most of which belong to five sub-variants known as BA.1, BA.2, BA.3, BA.4, and BA.5. The aim of this study was to develop a multiplex polymerase chain reaction (PCR) that will be able to distinguish the basic sub-variants of Omicron in a rapid and specific way. Full genome sequences of Omicron strains with high frequency and wide geographical distribution were retrieved by the NCBI Virus and ENA databases. These sequences were compared to each other in order to locate single nucleotide polymorphisms common to all strains of the same sub-variant. These polymorphisms should also be capable of distinguishing Omicron sub-variants not only from each other but from previously circulating variants of SARS-CoV-2 as well. Thus, specific primers targeting characteristic polymorphisms of the four Omicron main branches BA.1, BA.2, BA.4, and BA.5 were designed according to the principles of the amplification refractory mutation system (ARMS) and with the ability to react under multiplex PCR conditions. According to our results, the ARMS-multiplex PCR could successfully distinguish all Omicron sub-variants that carry the corresponding mutations.

Misclassified: identification of zoonotic transition biomarker candidates for influenza A viruses using deep neural network.

Introduction: Zoonotic transition of Influenza A viruses is the cause of epidemics with high rates of morbidity and mortality. Predicting which viral strains are likely to transition from their genetic sequence could help in the prevention and response against these zoonotic strains. We hypothesized that features predictive of viral hosts could be leveraged to identify biomarkers of zoonotic viral transition. Methods: We trained deep learning models to predict viral hosts based on the virus mRNA or protein sequences. Our multi-host dataset contained 848,630 unique nucleotide sequences obtained from the NCBI Influenza Virus and Influenza Research Databases. Each sequence, representing one gene from one viral strain, was classified into one of the three host categories: Avian, Human, and Swine. Trained models were analyzed using various neural network interpretation methods to identify interesting candidates for zoonotic transition biomarkers. Results: Using mRNA sequences as input led to higher prediction accuracies than amino acids, suggesting that the codon sequence contains information relevant to viral hosts that is lost during protein translation. UMAP visualization of the latent space of our classifiers showed that viral sequences clustered according to their host of origin. Interestingly, sequences from pandemic zoonotic viral strains localized at the margins between hosts, while zoonotic sequences incapable of Human-to-Human transmission localized with non-zoonotic viruses from the same host. In addition, host prediction for pandemic zoonotic sequences had low prediction accuracy, which was not the case for the other zoonotic strains. This supports our hypothesis that ambiguously predicted viral sequences bear features associated with cross-species infectivity. Finally, we compared misclassified sequences to well-classified ones to extract interesting candidates for zoonotic transition biomarkers. While features varied significantly between pairs of species and viral genes, several codons were conserved in Swine-to-Human and Avian-to-Human misclassified sequences, and in particular in the NA, HA, and NP genes, suggesting their importance for zoonosis in Humans. Discussion: Analysis of viral sequences using neural network interpretation approaches revealed important genetic differences between zoonotic viruses with pandemic potential, compared to non-zoonotic viral strains or zoonotic viruses incapable of Human-to-Human transmission.

Human SARS CoV-2 spike protein mutations in West Africa

Background: The COVID-19 pandemic was caused by the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), first detected in Wuhan, Hubei province, China in December 2019. The virus rapidly spread worldwide, with mutations in various parts of its genetic material affecting its transmissibility and infectivity. Objective: This study addressed some of the mutations present in the human SARS-CoV-2 spike proteins relative to Wuhan-Hu-1 reference sequence from China, according to different countries from West Africa. Methods: The SARS-CoV-2 spike protein sequences were obtained from the National Center for Biotechnology Information virus database in the FASTA format on November12,2021. The multiple sequence alignment of the proteins was carried out by MAFFT version 7 online. The human SARS-CoV-2 spike protein sequences from selected West African countries were analyzed by comparing them with the reference SARS-CoV-2 protein sequence from Wuhan-Hu-1, China. Results: Out of 148 spike protein sequences analyzed, 137 proteins had one or more mutations. A total of 486 mutations were observed corresponding to 47 distinct mutation sites. In the analysis of the spike proteins in the study, it was observed that the Receptor Binding Domain which is involved in the interactions with human angiotensin-converting enzyme-2 (ACE-2) receptor causing infection leading to the COVID-19 disease had 8 distinct mutation sites. The D614G mutation is the most common in the SARS-CoV-2 spike protein observed so far among all the West African countries examined in this study and thus the most predominant. In this study, we examined spike proteins not associated with mutations, the distribution of mutations in spike proteins, mutation density in different regions of the spike protein sequence, spike protein sequences with multiple mutations and the Human SARS-CoV-2 spike protein mutation in West Africa and implications for vaccination and drug development purposes. Conclusion: The identified mutations in SARS-CoV-2 are significant for infection prevention, control, and public health interventions. Further studies are imperative to understand the mutations in the virus's spike proteins to guide vaccine development and antiviral drug designs. Investigations should also be conducted to determine the infectivity of emerging variants in West Africa and their response to vaccines and available drugs to address public health concerns on vaccination and drug design goals

In Silico Approach to Construct the 3D Structures of Spike Glycoproteins of Novel Variants of Severe Acute Respiratory Syndrome Coronavirus 2

Objective: This study aims in constructing a three-dimensional modeled Spike glycoprotein structure of novel variants of SARS CoV-2. Methods: The protein models were constructed using SWISS-Model online tool. The constructed protein models were submitted in online database called Protein Model Database (PMDB) for public access to the structures. Results: A total of 70 protein sequences of Spike glycoprotein of novel variants of SARS CoV-2 were retrieved from NCBI virus database and were subjected for sequence similarity search and homology model construction. The constructed models were subjected for Ramachandran plot analysis to validate the quality of the structures. A total of 40 structures were considered to be of significant quality and were submitted to the online database PMDB. Conclusion: These predicted structures would help greatly in identification and drug design. This would greatly help in drug development and personalized drug treatment against different variants of the pathogen. This database would significantly support the structure-based computational drug design applications toward personalized medicine against the variants of concern of SARS CoV-2.

History of advances in genetic engineering of viruses before COVID-19 pandemic.

On December 31, 2019, the World Health Organization's China Country Office was alerted to cases of pneumonia of unknown cause detected in Wuhan City, Hubei Province of China. Due to the fact that to date, the question of the origin of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has not been resolved yet, the author analyzed the main advances in the development of genetic engineering of viruses that took place before the onset of the COVID-19 pandemic. The first artificial genetically modified viruses could appear in nature in the mid-1950s. The technique of nucleic acid hybridization was developed by the end-1960s. In the late 1970s, a method called the "reverse genetics" emerged to synthesize ribonucleic acid and deoxyribonucleic acid molecules. In the early 1980-s, it became possible to combine the genes of different viruses and insert the genes of one virus into the genome of another virus. Since that time, the production of vector vaccines began. At present, by modern technologies one can assemble any virus based on the nucleotide sequence available in the virus database or designed by a computer as a virtual model. Scientists around the world are invited to answer the call of Neil Harrison and Jeffrey Sachs of Columbia University, for a thorough and independent investigation into the origin of SARS-CoV-2. Only a full understanding of the origin of the new virus can minimize the likelihood of a similar pandemic in the future.