VIGA: a one-stop tool for eukaryotic virus identification and genome assembly from next-generation-sequencing data.

Identification of viruses and further assembly of viral genomes from the next-generation-sequencing data are essential steps in virome studies. This study presented a one-stop tool named VIGA (available at https://github.com/viralInformatics/VIGA) for eukaryotic virus identification and genome assembly from NGS data. It was composed of four modules, namely, identification, taxonomic annotation, assembly and novel virus discovery, which integrated several third-party tools such as BLAST, Trinity, MetaCompass and RagTag. Evaluation on multiple simulated and real virome datasets showed that VIGA assembled more complete virus genomes than its competitors on both the metatranscriptomic and metagenomic data and performed well in assembling virus genomes at the strain level. Finally, VIGA was used to investigate the virome in metatranscriptomic data from the Human Microbiome Project and revealed different composition and positive rate of viromes in diseases of prediabetes, Crohn's disease and ulcerative colitis. Overall, VIGA would help much in identification and characterization of viromes, especially the known viruses, in future studies.

Accurate virus identification with interpretable Raman signatures by machine learning.

Rapid identification of newly emerging or circulating viruses is an important first step toward managing the public health response to potential outbreaks. A portable virus capture device, coupled with label-free Raman spectroscopy, holds the promise of fast detection by rapidly obtaining the Raman signature of a virus followed by a machine learning (ML) approach applied to recognize the virus based on its Raman spectrum, which is used as a fingerprint. We present such an ML approach for analyzing Raman spectra of human and avian viruses. A convolutional neural network (CNN) classifier specifically designed for spectral data achieves very high accuracy for a variety of virus type or subtype identification tasks. In particular, it achieves 99% accuracy for classifying influenza virus type A versus type B, 96% accuracy for classifying four subtypes of influenza A, 95% accuracy for differentiating enveloped and nonenveloped viruses, and 99% accuracy for differentiating avian coronavirus (infectious bronchitis virus [IBV]) from other avian viruses. Furthermore, interpretation of neural net responses in the trained CNN model using a full-gradient algorithm highlights Raman spectral ranges that are most important to virus identification. By correlating ML-selected salient Raman ranges with the signature ranges of known biomolecules and chemical functional groups­for example, amide, amino acid, and carboxylic acid­we verify that our ML model effectively recognizes the Raman signatures of proteins, lipids, and other vital functional groups present in different viruses and uses a weighted combination of these signatures to identify viruses.

Detection and discovery of plant viruses in soybean by metagenomic sequencing.

BACKGROUND: Viruses negatively impact soybean production by causing diseases that affect yield and seed quality. Newly emerging or re-emerging viruses can also threaten soybean production because current control measures may not be effective against them. Furthermore, detection and characterization of new plant viruses requires major efforts when no sequence or antibody-based resources are available. METHODS: In this study, soybean fields were scouted for virus-like disease symptoms during the 2016-2019 growing seasons. Total RNA was extracted from symptomatic soybean parts, cDNA libraries were prepared, and RNA sequencing was performed using high-throughput sequencing (HTS). A custom bioinformatic workflow was used to identify and assemble known and unknown virus genomes. RESULTS: Several viruses were identified in single or mixed infections. Full- or nearly full-length genomes were generated for tobacco streak virus (TSV), alfalfa mosaic virus (AMV), tobacco ringspot virus (TRSV), soybean dwarf virus (SbDV), bean pod mottle virus (BPMV), soybean vein necrosis virus (SVNV), clover yellow vein virus (ClYVV), and a novel virus named soybean ilarvirus 1 (SIlV1). Two distinct ClYVV isolates were recovered, and their biological properties were investigated in Nicotiana benthamiana, broad bean, and soybean. In addition to infections by individual viruses, we also found that mixed viral infections in various combinations were quite common. CONCLUSIONS: Taken together, the results of this study showed that HTS-based technology is a valuable diagnostic tool for the identification of several viruses in field-grown soybean and can provide rapid information about expected viruses as well as viruses that were previously not detected in soybean.

Identification and genetic analysis of a totivirus isolated from the Culex tritaeniorhynchus in northern China.

Totiviridae, a viral family of double-stranded RNA (dsRNA) viruses, contain a single dsRNA genome 4.6-7.0 kb in length. Totiviridae were initially only known to infect fungi and other eukaryotes as well as plants, but an increase in totiviruses has been detected in insects, mosquitoes, and bats. Here, we describe the isolation and characterization of a strain belonging to the family Totiviridae isolated from Culex tritaeniorhynchus in Kenli, China, in 2016. We isolated a totivirus from field-collected mosquitoes in China by cell culture in Aedes albopictus C6/36 cells, identified the virus by morphological observation and complete genome sequencing, and characterized it by phylogenetic analysis. Transmission electron microscopy identified icosahedral, non-enveloped virus particles with a mean diameter of 35-40 nm. The genome was 7612 bp in length, including two open reading frames (ORFs). ORF1 (5058 nt) encodes the capsid protein, while ORF2 (2216 nt) encodes the viral RNA-dependent RNA polymerase (RdRp). Nucleotide and amino acid homology analysis of isolate showed higher levels of sequence identity with isolate CTV_NJ2 (China, 2010) with 94.87% nucleic acid identity and 97.32% amino acid identity. The isolate was designated C. tritaeniorhynchus totivirus KL (CTV-KL). This is the first identification of a totivirus in a C. tritaeniorhynchus in northern China. Analysis of the virus's morphology, characteristic and genome organization will further enrich our understanding of the molecular and biological characteristics of dsRNA Totiviridae viruses.

Comparison of third-generation sequencing approaches to identify viral pathogens under public health emergency conditions.

The capability of high-throughput sequencing (HTS) for detection of known and unknown viruses timely makes it a powerful tool for public health emergency response. Third-generation sequencing (TGS) offers advantages in speed and length of detection over second-generation sequencing (SGS). Here, we presented the end-to-end workflows for both Oxford Nanopore MinION and Pacbio Sequel on a viral disease emergency event, along with Ion Torrent PGM as a reference. A specific pipeline for comparative analysis on viral genomes recovered by each platform was assembled, given the high errors of base-calling for TGS platforms. All the three platforms successfully identified and recovered at least 85% Norovirus GII genomes. Oxford Nanopore MinION spent the least sample-to-answer turnaround time with relatively low but enough accuracy for taxonomy classification. Pacbio Sequel recovered the most accurate viral genome, while spending the longest time. Overall, Nanopore metagenomics can rapidly characterize viruses, and Pacbio Sequel can accurately recover viruses. This study provides a framework for designing the appropriate experiments that are likely to lead to accurate and rapid virus emergency response.

Rapid detection of pathogenic virus genome sequence from throat and nasal swab samples using an exhaustive gene amplification method.

Rapid identification of pathogenic agents is important in response to the emergence of biocrime and bioterrorism, to facilitate appropriate confinement and treatment. As the rapid determination system of viral genome sequences (RDV method) using exhaustive gene amplification is useful for rapid identification, we examined whether this method could be applied to forensic samples. To detect pathogenic virus in a cat with suspected viral infections, fluid swab samples were applied to the RDV method. The following steps were performed: viral propagation, extraction of the viral genome, amplification of the first library, fragmentation of the library, amplification of the second library using non-specific primer sets, and direct sequencing of the amplicon. To confirm the viruses detected by this method, we performed conventional PCR using virus-specific primers. We detected pathogenic virus genome sequences from the swab samples and confirmed infection with these viruses. In addition, we directly detected a viral genome sequence from the nasal swab sample without the viral propagation step. The RDV method is infrequently used in forensic analysis. This method is practicable with equipment existing in a normal laboratory and is useful for rapid detection and identification of pathogenic viruses in forensic samples. This method would also be applicable to the detection of bacteria and fungi.

Spectroscopy with computational analysis in virological studies: A decade (2006-2016).

This review presents a retrospective of the studies carried out in the last 10 years (2006-2016) using spectroscopic methods as a research tool in the field of virology. Spectroscopic analyses are sensitive to variations in the biochemical composition of the sample, are non-destructive, fast and require the least sample preparation, making spectroscopic techniques tools of great interest in biological studies. Herein important chemometric algorithms that have been used in virological studies are also evidenced as a good alternative for analyzing the spectra, discrimination and classification of samples. Techniques that have not yet been used in the field of virology are also suggested. This methodology emerges as a new and promising field of research, and may be used in the near future as diagnosis tools for detecting diseases caused by viruses.

An Improved Barcoded Oligonucleotide Primers-based Next-generation Sequencing Approach for Direct Identification of Viral Pathogens in Clinical Specimens.

OBJECTIVE: To provide a feasible and cost-effective next-generation sequencing (NGS) method for accurate identification of viral pathogens in clinical specimens, because enormous limitations impede the clinical use of common NGS, such as high cost, complicated procedures, tremendous data analysis, and high background noise in clinical samples. METHODS: Viruses from cell culture materials or clinical specimens were identified following an improved NGS procedure: reduction of background noise by sample preprocessing, viral enrichment by barcoded oligonucleotide (random hexamer or non-ribosomal hexanucleotide) primer-based amplification, fragmentation-free library construction and sequencing of one-tube mixtures, as well as rapid data analysis using an in-house pipeline. RESULTS: NGS data demonstrated that both barcoded primer sets were useful to simultaneously capture multiple viral pathogens in cell culture materials or clinical specimens and verified that hexanucleotide primers captured as many viral sequences as hexamers did. Moreover, direct testing of clinical specimens using this improved hexanucleotide primer-based NGS approach provided further detailed genotypes of enteroviruses causing hand, foot, and mouth disease (HFMD) and identified other potential viruses or differentiated misdiagnosis events. CONCLUSION: The improved barcoded oligonucleotide primer-based NGS approach is simplified, time saving, cost effective, and appropriate for direct identification of viral pathogens in clinical practice.

Label-free virus identification and characterization using electrochemical impedance spectroscopy.

We demonstrate here the application of electrochemical impedance spectroscopy (EIS) in microfluidic devices for label-free virus identification by means of their specific "signature" and also investigate its feasibility for titer quantitation using two basic approaches. The first one is a method based on identifying so-called "resonance" frequencies manifesting in our microdevices and monitoring their variation as a function of the virus concentration, whereas the second one relies on measuring the relative impedance variation at these "resonance" frequencies. Best results have been obtained for the highest "resonance" frequency (∼80 MHz), which we attribute to be due to both the structure of the microdevice and the extremely small size of the viruses that make their effect significant only at such frequencies. This is a simpler method of determining virus concentration in diluted solutions of purified viruses than the well-established traditional plaque assay titer estimation method, and-since it is based on frequency measurement-could potentially be more accurate.

VirRep: a hybrid language representation learning framework for identifying viruses from human gut metagenomes.

Identifying viruses from metagenomes is a common step to explore the virus composition in the human gut. Here, we introduce VirRep, a hybrid language representation learning framework, for identifying viruses from human gut metagenomes. VirRep combines a context-aware encoder and an evolution-aware encoder to improve sequence representation by incorporating k-mer patterns and sequence homologies. Benchmarking on both simulated and real datasets with varying viral proportions demonstrates that VirRep outperforms state-of-the-art methods. When applied to fecal metagenomes from a colorectal cancer cohort, VirRep identifies 39 high-quality viral species associated with the disease, many of which cannot be detected by existing methods.

High-throughput RNA dataset of viral transcripts associated with chickens from various poultry farms in North and South Kuwait.

Screening of poultry using RNA sequencing could enable the timely detection and identification of emerging viral pathogens, facilitating proactive measures to prevent and control potential outbreaks in the poultry industry. The reported dataset is of reads from RNA-Seq libraries consisting of approximately 130 gigabytes of RNA-sequencing data corresponding to blood, trachea and cloaca of chicken from various farms of North and South Kuwait regions. The sequences were quality-filtered and first mapped with the Chicken reference genome. The unmapped reads were aligned to the viral reference genomes. The aligned data was used for the quantification of viral transcripts across the samples. The RNA sequencing data could be useful for further meta-analysis and to extract valuable insights into the molecular landscape of poultry health. The insights gained from this research can guide the development of targeted diagnostic tools and strategies for effective poultry health management.

Detection of Parvovirus B19 genome in human heart tissue samples.

OBJECTIVE: Identifying viral genomes in human heart tissues is critical for disease diagnosis and assessment of cardiovascular damage. Human heart tissue samples obtained during a biopsy procedure are routinely used to test for the presence of viruses, as guided by clinical manifestations and prognosis. Furthermore, heart tissue samples obtained post-mortem or during a cardiac transplant procedure serve as a valuable research tool, as they allow for an in-depth assessment of cardiac pathology that can aid in our understanding of molecular pathways associated with disease. Because viral nucleic acid constitutes only a small portion of each sample's genetic material, appropriate methods are necessary for positive viral genome identification. RESULTS: Snap-frozen heart tissue samples obtained either post-mortem or during a cardiac transplant procedure were used to develop conditions for detection of Parvovirus B19. Briefly, total DNA was isolated from the heart tissue under varying conditions. A PCR-based assay with Parvovirus B19 specific primers was implemented to detect the presence of the viral genome, followed by Sanger Sequencing. The mechanical disruption of the heart tissue, as well as the cardiac tissue processing methods, had a significant effect on the DNA quality and the ability to detect the Parvovirus B19 genome.

Metavirome Analysis and Identification of Midge-Borne Viruses from Yunnan Province, China, in 2021.

Midges are widely distributed globally and can transmit various human and animal diseases through blood-sucking. As part of this study, 259,300 midges were collected from four districts in Yunnan province, China, to detect the viral richness and diversity using metavirome analysis techniques. As many as 26 virus families were detected, and the partial sequences of bluetongue virus (BTV), dengue virus (DENV), and Getah virus (GETV) were identified by phylogenetic analysis and PCR amplification. Two BTV gene fragments, 866 bps for the VP2 gene of BTV type 16 and 655 bps for the VP5 gene of BTV type 21, were amplified. The nucleotide sequence identities of the two amplified BTV fragments were 94.46% and 98.81%, respectively, with two classical BTV-16 (GenBank: JN671907) and BTV-21 strains (GenBank: MK250961) isolated in Yunnan province. Furthermore, the BTV-16 DH2021 strain was successfully isolated in C6/36 cells, and the peak value of the copy number reached 3.13 × 107 copies/µL after five consecutive BHK-21 cell passages. Moreover, two 2054 bps fragments including the E gene of DENV genotype Asia II were amplified and shared the highest identity with the DENV strain isolated in New Guinea in 1944. A length of 656 bps GETV gene sequence encoded the partial capsid protein, and it shared the highest identity of 99.68% with the GETV isolated from Shandong province, China, in 2017. Overall, this study emphasizes the importance of implementing prevention and control strategies for viral diseases transmitted by midges in China.

Sequence, assembly and count datasets of viruses associated to the pine processionary moth Thaumetopoea pityocampa (Denis & Schiffermüller) (Lepidoptera, Notodontidae) identified from transcriptomic high-throughput sequencing.

The pine processionary moth Thaumetopoea pityocampa is a Lepidopteran pest species occurring in the Western Mediterranean. It causes heavy pine defoliations and it is a public and animal health concern because of its urticating caterpillars. Very little is known about the viruses associated to this species, as only two viruses were described so far. We here present a dataset corresponding to 34 viral transcripts, among which 27 could be confidently assigned to 9 RNA and DNA viral families (Iflaviridae, Reoviridae, Partitiviridae, Permutotetraviridae, Flaviviridae, Rhabdoviridae, Parvoviridae, Baculoviridae and PolyDNAviridae). These transcripts were identified from an original transcriptome assembled for the insect host, using both blast search and phylogenetic approaches. The data were acquired from 2 populations in Portugal and 2 populations in Italy. The transcripts were de novo assembled and used to identify viral sequences by homology searches. We also provide information about the populations and life stages in which each virus was identified. The data produced will allow to enrich the virus taxonomy in Lepidopteran hosts, and to develop PCR-based diagnostic tools to screen colonies across the range and determine the distribution and prevalence of the identified viral species.

Development of a validated molecular analytical method to determine the viral safety of F(AB´)2 products: A novel application for a well-known technique.

The immunotherapy agents derived from horses are biological products that allow the neutralization of clinically relevant immunogens, such as the SARS-CoV-2 virus that causes COVID-19, or the neutralization of toxins present in the venoms of snakes, spiders, and other poisonous animals. Due to their importance, detecting adventitious viruses in equine hyperimmune serum (raw material in industrial processes) is a critical step to support the safety of products for human use, and, in consequence, it is a requirement for commercialization and distribution. The safety of the finished product is based on three complementary approaches: (i) testing of the source material (horse serum) donations, (ii) release of the starting material (i.e., pool of horse serum) based on non-reactivity for a range of human infectious or pathogenic viruses, and (iii) validate (selected) steps of the manufacturing process for their capacity to inactivate and/or remove a wide range of viruses potentially present in the starting material. Orthogonal approaches to reduce viral contamination risk include implementing a reliable and validated system for detecting adventitious viruses. Thus, it is necessary to establish trustworthy and sufficiently sensitive analytical methods to evidence the lack of viruses to assure the safety of the therapeutic product. Therefore, in this research, an analytical method based on end-point Reverse Transcription Polymerase Chain Reaction (RT-PCR) was developed, implemented, and validated in hyperimmune equine serum samples to detect Venezuelan equine encephalitis virus, West Nile virus, and Rabies virus.

Site-Specific Covalent Immobilization of SMA-Stabilized ACE2 for SARS-CoV-2 Recognition and Drug Screening.

Membrane protein (MP)-based biomaterials have a wide range of applications in drug screening, antigen detection, and ligand-receptor interaction analysis. Traditional MP immobilization methods have the disadvantage of disordered protein immobilization orientation, leading to the shielded binding domain and unreliable binding pattern. Herein, we describe a site-specific covalent immobilization of MPs, which utilizes the styrene maleic acid (SMA) detergent-free extraction method of MPs as well as the covalent reaction between His-tag and divinyl sulfone (DVS). As an example, we covalently immobilized angiotensin-converting enzyme 2 (ACE2) on a cell membrane chromatography system (ACE2-His-SMALPs/CMC) in a site-specific manner and verified the specificity and stability of this system. This technique significantly improves the service life compared to the physisorption CMC column. The improved protein immobilization strategies of the ACE2-His-SMALPs/CMC system enable it to effectively recognize SARS-CoV-2 pseudoviral particles as well as detect viral particles in ambient air once combined with an aerosol collector; as a powerful ligand biosensor, the ACE2-His-SMALPs/CMC system was used to screen for compounds with anti-SARS-CoV-2 pseudovirus activity. In conclusion, the optimized MP immobilization strategy has been successfully applied to CMC technology, showing enhanced stability and sensitivity, which can provide an efficient and convenient membrane protein immobilization method for biomaterials.

Viral Metagenomic Data Analyses of Five New World Bat Species from Argentina: Identification of 35 Novel DNA Viruses.

Bats are natural reservoirs of a variety of zoonotic viruses, many of which cause severe human diseases. Characterizing viruses of bats inhabiting different geographical regions is important for understanding their viral diversity and for detecting viral spillovers between animal species. Herein, the diversity of DNA viruses of five arthropodophagous bat species from Argentina was investigated using metagenomics. Fecal samples of 29 individuals from five species (Tadarida brasiliensis, Molossus molossus, Eumops bonariensis, Eumops patagonicus, and Eptesicus diminutus) living at two different geographical locations, were investigated. Enriched viral DNA was sequenced using Illumina MiSeq, and the reads were trimmed and filtered using several bioinformatic approaches. The resulting nucleotide sequences were subjected to viral taxonomic classification. In total, 4,520,370 read pairs were sequestered by sequencing, and 21.1% of them mapped to viral taxa. Circoviridae and Genomoviridae were the most prevalent among vertebrate viral families in all bat species included in this study. Samples from the T. brasiliensis colony exhibited lower viral diversity than samples from other species of New World bats. We characterized 35 complete genome sequences of novel viruses. These findings provide new insights into the global diversity of bat viruses in poorly studied species, contributing to prevention of emerging zoonotic diseases and to conservation policies for endangered species.

Metavirome Analysis of Culex tritaeniorhynchus Reveals Novel Japanese Encephalitis Virus and Chikungunya Virus.

To explore the Culex tritaeniorhynchuses-specific virome, 6400 C. tritaeniorhynchuses were collected in Honghe autonomous prefecture, China. Abundant virus sequences were obtained from 28 viral families using metavirome sequencing. Herein, several viruses in C. tritaeniorhynchuses virome were verified using the PCR technique, which covers Japanese encephalitis virus (JEV), Getah virus, and even Chikungunya virus (CHIKV). Seven JEV gene sequences were amplified successfully, of which JEV-China/CT2016E-1 shared the highest homology with the known JEV sequence isolated in Korea, 1946, with at least 96.1% nucleotide (nt) identity, which belonged to genotype III. Nine CHIKV gene sequences were amplified, which shared the highest with at least 93.0% nt identity with CHIKV from Thailand isolated in 2007, which was assigned to genotype Asian. Remarkably, CHIKV was isolated from C. tritaeniorhynchus in China for the first time. It was initially confirmed that the isolated virus CHIKV-China/CT2016-1 may increase infectivity after passaging in Vero cells from BHK-21 cells. Collectively, our study reveals the diversity, properties, and potential virus susceptibility dynamics of the C. tritaeniorhynchus virome and sheds new perspectives on the viral ecology in other important biological vectors.

The International Virus Bioinformatics Meeting 2022.

The International Virus Bioinformatics Meeting 2022 took place online, on 23-25 March 2022, and has attracted about 380 participants from all over the world. The goal of the meeting was to provide a meaningful and interactive scientific environment to promote discussion and collaboration and to inspire and suggest new research directions and questions. The participants created a highly interactive scientific environment even without physical face-to-face interactions. This meeting is a focal point to gain an insight into the state-of-the-art of the virus bioinformatics research landscape and to interact with researchers in the forefront as well as aspiring young scientists. The meeting featured eight invited and 18 contributed talks in eight sessions on three days, as well as 52 posters, which were presented during three virtual poster sessions. The main topics were: SARS-CoV-2, viral emergence and surveillance, virus-host interactions, viral sequence analysis, virus identification and annotation, phages, and viral diversity. This report summarizes the main research findings and highlights presented at the meeting.