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RNA Viruses

RNA viruses are a diverse group of viruses that use ribonucleic acid (RNA) as their genetic material.
These viruses can infect a wide range of hosts, including humans, animals, and plants, and are responsible for many important diseases.
RNA viruses replicate their genomes through an RNA-dependent RNA polymerase, a unique enzyme that is essential for their life cycle.
Theis group includes well-known viruses such as influenza, HIV, and SARS-CoV-2, as well as many emerging and re-emerging pathogens.
Understanding the biology and epidemiology of RNA viruses is crucial for developing effective prevention and treatment strategies.
Reseraching RNA viruses is a dynamic and rapidly evolving field that requires the use of cutting-edge tools and techniques to ensure reproducible and accurate results.

Most cited protocols related to «RNA Viruses»

1
Calibrating Molecular Clock Models
In the above discussion on rate models, it was assumed that it is possible to estimate absolute rates of evolution and the variance in absolute rates. In fact, even under a molecular clock assumption, the divergence times and the overall substitution rate can only be separately estimated if there is a source of external calibration information. In the framework described here, this information can come from one of three sources: (1) Prior information on the age of internal nodes: In a phylogenetic context, calibration information is often obtained by assigning the age of a known fossil to a particular internal node [
2 ]. Uncertainty in the association between an internal node and the fossil record can be accommodated by providing a prior probability distribution for the age of the node. Previous studies have used a uniform distribution with upper and lower bounds on the age [
54 (link)], although other distributions may be suitable [
35 (link)]. In the above Results section, we presented examples in which calibration times are treated with parametric prior distributions (normal and lognormal). Assigning an age to a particular node is only possible when the tree itself is assumed to be known and fixed, a limitation of previous relaxed-clock implementations [
15 (link),
17 (link),
54 (link)]. In the framework presented here, the tree itself is being sampled and thus we cannot define the age of a particular internal node. Instead we specify the age, or the prior distribution of age, for the most recent common ancestor of a set of taxa. Every time a new tree is proposed in the MCMC chain, the most recent common ancestor of the specified taxa is located in the tree, and the prior probability of the age of this node is used to assess the acceptance probability of the proposed tree. (2) Known ages of the sequences: Recently it has also been demonstrated that calibrations can be associated with the sequences at the tips of the tree if they are sampled at significantly different times [
29 (link),
30 (link),
66 ] with respect to their rate of evolution. Again, there may be uncertainty in calibration dates [
67 (link)]. The RNA virus data in this study provide examples of this form of calibration information. (3) A strong prior on the substitution rate: If the mean substitution rate is known from a previous study on independent data, then this can be incorporated as prior knowledge. In the simplest case this can be achieved by fixing the rate of evolution to a known value. It is also straightforward to sample the rate from a parametric distribution obtained from a previous (independent) analysis [
68 (link),
69 (link)]. If there is no prior information about the mean substitution rate, then it can be fixed to 1, resulting in time being in units of substitutions per site.
All of these forms of calibration information can be incorporated into our MCMC implementation either on their own or in any combination, as appropriate.
Drummond A.J., Ho S.Y., Phillips M.J, & Rambaut A. (2006). Relaxed Phylogenetics and Dating with Confidence. PLoS Biology, 4(5), e88.
Publication 2006
Biological Evolution RNA Viruses Trees
2
Generating Comprehensive Sequence Datasets for Metagenomics
To generate training and testing datasets, sequences representing bacteria, archaea, plasmids, and viruses were downloaded from the National Center for Biotechnology Information (NCBI) RefSeq and Genbank databases (accessed July 2019) (Additional File 1: Table S1). For bacteria/archaea, 181 genomes were chosen by selecting from diverse phylogenetic groups. Likewise, a total of 1452 bacterial plasmids were chosen. For viruses, NCBI taxids associated with viruses that infect bacteria or archaea were used to download reference virus genomes, which were then limited to only sequences above 3 kb. This included viruses with both DNA and RNA genomes, though RNA genomes must first be converted to complementary DNA. Sequences not associated with genomes, such as partial genomic regions, were identified according to sequence headers and removed. This resulted in 15,238 total viral partial and complete genomes. To be consistent between all sequences acquired from NCBI, proteins and genes were predicted using Prodigal (-p meta, v2.6.3) [50 (link)]. All sequences were split into non-overlapping, non-redundant fragments between 3 and 15 kb to simulate metagenome-assembled scaffolds. These simulated scaffolds are hereafter called fragments and were used throughout training and testing VIBRANT. For RNA virus detection, 33 viral (bacteriophage) genomes from NCBI RefSeq and 37 from Krishnamurthy et al. were used [51 (link)], and for archaeal virus detection, all genomes were acquired from NCBI RefSeq. The RNA and archaeal viral genomes were represented in both the training and testing datasets as genomic fragments, and recall evaluation was performed on whole genomes. These were the only datasets in which training and evaluation datasets were semi-redundant. See Supplemental Methods (Additional File 16) for additional datasets and sequences used.
Integrated viruses are common in both bacteria and archaea. To address this for generating a dataset devoid of viruses, PHASTER (accessed July 2019) was used to predict putative integrated viruses in the 181 bacteria/archaea genomes. Using BLASTn [52 (link)], any fragments that had significant similarity (at least 95% identity, at least 3 kb coverage, and e-value < 1e−10) to the PHASTER predictions were removed as contaminant virus sequence. The new bacteria/archaea dataset was considered depleted of proviruses but not entirely devoid of contamination. Next, the datasets for bacteria/archaea and plasmids were annotated with KEGG, Pfam, and VOG HMMs (hmmsearch (v3.1), e-value < 1e−5) [53 (link)] to further remove contaminant virus sequence (see next section for details of HMMs). Plasmids were included because it was noted that the dataset appeared to contain virus sequences, possibly due to misclassification of episomal proviruses as plasmids. Using manual inspection of the KEGG, Pfam, and VOG annotations, any sequence that clearly belonged to a virus was removed. Manual inspection was guided first by the number of KEGG, Pfam, and VOG annotations and then by the annotations themselves. For example, sequences with more VOG than KEGG or Pfam annotations were inspected and removed if multiple viral hallmark genes were found or if the majority of annotations represented viral-like genes. The final datasets consisted of 400,291 fragments for bacteria/archaea, 14,739 for plasmids, and 111,963 for viruses. Total number of fragments for all datasets used can be found in Additional File 2: Table S2.
Kieft K., Zhou Z, & Anantharaman K. (2020). VIBRANT: automated recovery, annotation and curation of microbial viruses, and evaluation of viral community function from genomic sequences. Microbiome, 8, 90.
Publication 2020
Archaea Archaeal Viruses Bacteria Bacteriophages DNA, Complementary DNA, Viral DNA Viruses Episomes Genes Genes, Viral Genome Genome, Archaeal Hypertelorism, Severe, With Midface Prominence, Myopia, Mental Retardation, And Bone Fragility Mental Recall Metagenome Plasmids Proteins Proviruses RNA Viruses Satellite Viruses Viral Genome Virus
3
Viral Marker Gene Annotation Pipeline
Annotations were determined based on HMM searches against a custom database of 1,000 taxonomically informative HMMs from the VOG database (http://vogdb.org/). These HMMs were selected for major bacterial and archaeal viral groups with consistent genome length and at least ten representative genomes, including: Caudovirales, CRESS-DNA and Parvoviridae, Autolykiviridae, Fusello- and Guttaviridae, Inoviridae, Ligamenvirales Ampulla- Bicauda- and Turriviridae, Microviridae and Riboviria. For each group, VOGs found in ≥10% of the group members and never detected outside of this group were considered as marker genes. All CheckV reference genomes were annotated based on the clade with the most HMM hits. Overall, 96.4% of HMM hits were to a single viral taxon.
Nayfach S., Camargo A.P., Schulz F., Eloe-Fadrosh E., Roux S, & Kyrpides N.C. (2020). CheckV assesses the quality and completeness of metagenome-assembled viral genomes. Nature Biotechnology, 39(5), 578-585.
Publication 2020
Bacteria Brassicaceae Caudovirales Genetic Markers Genome Genome, Archaeal Guttaviridae Hypertelorism, Severe, With Midface Prominence, Myopia, Mental Retardation, And Bone Fragility Inoviridae Microviridae Parvoviridae RNA Viruses
4
Optimized mNGS Workflow for Sensitive CSF Pathogen Detection
We developed standard operating procedures (SOPs) in the clinical laboratory for processing and analyzing CSF samples by mNGS. Each of the “wet lab” and bioinformatics processing steps was optimized to ensure sensitive and accurate organism detection (Schlaberg et al. 2017a (link)). The mNGS assay workflow was performed as follows (Fig. 1), with a more detailed description provided in the Supplemental Methods. Briefly, each CSF sample was first subjected to bead-beating to lyse organisms (Fig. 1A), followed by addition (“spiking”) of T1 (DNA) and MS2 (RNA) bacteriophages as an internal control (IC). Total nucleic acid was then extracted and split into two aliquots for construction of separate DNA and RNA libraries. Microbial sequences were enriched by antibody-based removal of methylated host DNA (for DNA libraries) or DNase treatment (for RNA libraries), followed by transposon-based library construction (Fig. 1B). Each sequencing run on an Illumina HiSeq instrument included up to eight samples, along with a negative “no template” control consisting of elution buffer, intended to allow for sensitive detection of contamination, and a positive control consisting of a mixture of seven representative pathogenic organisms (RNA virus, DNA virus, Gram-positive bacterium, Gram-negative bacterium, fungus, mold, and parasite).
Sequence analysis was performed using the SURPI+ computational pipeline (Fig. 1C; Supplemental Methods), an automated clinical version of the previously published SURPI (“sequence-based ultrarapid pathogen identification”) research pipeline (Naccache et al. 2014 (link)). Receiver-operator curve analyses were performed as part of the accuracy study to determine optimal threshold values for organism detection (Supplemental Methods), using 95 clinical CSF samples with established microbiological results. These pre-established thresholds were then finalized and used for all subsequent clinical mNGS runs. Each mNGS run was analyzed by experienced laboratory physicians (S.M. and C.Y.C.), and results were generated for five categories per sample (RNA virus, DNA virus, bacteria, fungi, and parasite). Run quality control (QC) metrics included a minimum of 5 million reads per library, ≥100 reads per million for the IC T1 and MS2 phages in the DNA and RNA libraries, respectively, and positive qualitative detection of each of the seven organisms in the PC.
Miller S., Naccache S.N., Samayoa E., Messacar K., Arevalo S., Federman S., Stryke D., Pham E., Fung B., Bolosky W.J., Ingebrigtsen D., Lorizio W., Paff S.M., Leake J.A., Pesano R., DeBiasi R., Dominguez S, & Chiu C.Y. (2019). Laboratory validation of a clinical metagenomic sequencing assay for pathogen detection in cerebrospinal fluid. Genome Research, 29(5), 831-842.
Publication 2019
Bacteria Biological Assay Buffers Clinical Laboratory Techniques Deoxyribonucleases DNA Library DNA Viruses Fungi Fungus, Filamentous Gram-Positive Bacteria Gram Negative Bacteria Immunoglobulins Jumping Genes Nucleic Acids Parasites Pathogenicity Phage MS2 Physicians RNA Phages RNA Viruses Sequence Analysis
5
Viral Genotyping Protocol with Robust References
Initial studies were designed to assess the ability of the reference strains (initially selected from strains curated at the RNA Virus Database (17 (link)) (http://virus.zoo.ox.ac.uk/rnavirusdb/), Los Alamos HIV (http://www.hiv.lanl.gov) and HCV Sequence Databases (http://www. hcv.lanl.gov) to accurately classify a set of well-classified (gold standard) genomic sequences. Individual NJ trees were constructed for each test genome together with its appropriate reference set. Phylogenetic analyses were performed separately on each complete HIV-1, HCV and HBV genome, as well as on sub-genomic regions of HTLV-1, HPV and HHV8. Test sequences in the ‘gold standard’ dataset were considered to be accurately classified if they clustered within a known genotype, or sub-genotype, with a bootstrap value >70%. Fragments as large as 1000 nt in length were successfully genotyped using our genotyping tools. Reference alignments of complete and sub-genomic gold standard sequences that gave a bootstrap value of >95% were deemed suitable for routine use (16 (link)).
As with all genotyping tools, the accuracy and consistency of the data is dependent on the selection of appropriate reference sequences. To overcome the limitations of other commonly used methods that employ a single reference sequence or a consensus reference sequence (SIMPLOT, RIP and NCBI-genotyping tools), we used sets of carefully selected, full-length viral genomes to represent each individual subtype and recombinant virus. The initial step in the selection of reference strains involved the screening of published data to identify highly divergent, but equidistant, genomes that were representative of the diversity within a given subtype or CRF. The selected sequences were then aligned, edited and subjected to phylogenetic analysis using NJ, Bayesian and ML methods (18–20 ). Sequences that gave similar topologies using all three tree construction methods were retained for further analysis of their sub-genomic regions. In this phase of the evaluation, the sub-genomic regions were assessed using consecutive windows of fixed, but increasing, sizes, ranging from 200 to 2000 nt. The process began with an initial window size of 200 nt and was repeated with subsequent windows until all segments of the genome were classified with a bootstrap value of ≥70%.
Alcantara L.C., Cassol S., Libin P., Deforche K., Pybus O.G., Van Ranst M., Galvão-Castro B., Vandamme A.M, & de Oliveira T. (2009). A standardized framework for accurate, high-throughput genotyping of recombinant and non-recombinant viral sequences. Nucleic Acids Research, 37(Web Server issue), W634-W642.
Publication 2009
Consensus Sequence Genetic Profile Genome Gold HIV-1 Human Herpesvirus 8 Human T-lymphotropic virus 1 RNA Viruses Strains Trees Viral Genome Virus

Most recents protocols related to «RNA Viruses»

1
Retroviral Vectors for Gene Modification
Not available on PMC !

Example 2

Another example of a suitable vector is a retroviral vector. Retroviruses are RNA viruses that contain an RNA genome. The gag, pol, and env genes are flanked by long terminal repeat (LTR) sequences (or their corresponding proteins). The 5′ and 3′ LTR sequences promote transcription and polyadenylation of mRNAs.

The retroviral vector may provide a regulable transactivating element, an internal ribosome reentry site (IRES), a selection marker, and a target heterologous gene operated by a regulable promoter.

Alternatively, multiple sequences may be expressed under the control of multiple promoters. Finally, the retroviral vector may contain cis-acting sequences necessary for reverse transcription and integration. Upon infection, the RNA is reverse transcribed to DNA that integrates efficiently into the host genome. The recombinant retrovirus of this invention is genetically modified in such a way that some of the retroviral, infectious genes of the native virus have been removed and in certain instances replaced instead with a target nucleic acid sequence for genetic modification of the cell. The sequences may be exogenous DNA or RNA, in its natural or altered form.

US11859168B2. Electroporation, developmentally-activated cells, pluripotent-like cells, cell reprogramming and regenerative medicine (2024-01-02). None [US]. Inventors: Christopher B. Reid [US], Melissa Braga [US], Lilian N. Santamaria [US], Ashley N. Wickrema [US], Marinne D. Wickrema [US], Anthony Hao Dinh [US], Yaman Eksioglu [US], Mat Hoang Ho [US].
Patent 2024
Base Sequence Cells Cloning Vectors Electroporation Gene Editing Genes Genes, env Genes, Viral Genome Infection Internal Ribosome Entry Sites Long Terminal Repeat Polyadenylation Proteins Retroviridae Retroviridae Infections Reverse Transcription Ribosomes RNA, Messenger RNA Viruses Transcription, Genetic
2
Identification of Insect-Specific Viruses in Rice Planthopper
R. dorsalis adults were collected from rice fields in Luoding city, Guangdong Province, China from 2018, and propagated on TN-1 rice seedlings in cages at 25 ± 1 °C with 75 ± 5% relative humidity and 16-h light/8-h dark. High-throughput sequencing was used for identification of insect-specific viruses from this R. dorsalis population. Total RNA was extracted from R. dorsalis adults in TRIzol reagent according to the manufacturer’s instructions. High quality RNAs were selected for construction of small RNAs and transcriptomic libraries, which were sequenced using an Illumina NovaSeq 6000 platform in Novogene Co., Ltd, China. Low-quality reads and adapter sequences were removed from the raw reads to obtain clean reads. The clean reads were assembled, and the assembled contigs were analyzed using BLASTx searches in the nonredundant protein database available in NCBI. BLAST results were then checked carefully to screen potential viral sequences.
A new positive-sense single-stranded RNA virus was screened and identified using RT-PCR assays, and then named as RdFV. The primers used in RT-PCR assays were shown in Supplementary Table 1. Full length of RdFV genome sequences were analyzed by NCBI ORF finder online. Phylogeny was analyzed based on comparison of RdRp amino acid sequences with counterparts in insect or plant virgavirus lineages using Bayesian inference in MrBayes 3.2.6 under the rtREV+F + G4+I model56 (link). This model was determined using the Bayesian information criterion by ModelFinder57 (link). Markov chains were run for 2,000,000 generations, sampling every 100 generations. The sufficient sampling and parameter convergence were checked using Tracer 1.71, after discarded the first 25% samples as burn-in. The Bayesian 50% majority rule consensus tree was visualized in FigTree 1.4.4.
Wan J., Liang Q., Zhang R., Cheng Y., Wang X., Wang H., Zhang J., Jia D., Du Y., Zheng W., Tang D., Wei T, & Chen Q. (2023). Arboviruses and symbiotic viruses cooperatively hijack insect sperm-specific proteins for paternal transmission. Nature Communications, 14, 1289.
Publication 2023
Adult Amino Acid Sequence Biological Assay CAGE1 protein, human Gene Expression Profiling Genome Humidity Insecta Insect Viruses Light Oligonucleotide Primers Oryza sativa Plants Reverse Transcriptase Polymerase Chain Reaction RNA RNA Viruses Seedlings Trees trizol
3
Antibody Purification and Viral Inactivation
Antibody purification was performed as previously described7 ,10 . Briefly, triton x-100 and RNase were added to patient plasma at a final concentration of 0.5% and 0.5 mg/ml, respectively, and incubated for 30 min to inactivate enveloped RNA viruses. 20 µL protein G magnetic resin (lytic solutions) was washed and resuspended in PBS and added to 50 µL of inactivated plasma. Serum-resin mixture was incubated for three hours at 4 °C with shaking. The resin was washed with PBS and resuspended in 90 µL 100 mM glycine pH 2.7 for 5 min. The supernatant was extracted and added to 10 µL sterile 1 M Tris pH 8.0. Yeast adsorption was performed as previously described7 ,10 . Briefly, empty vector (pDD003) yeast was induced by culture in 1:10 SDO-Ura:SGO-Ura for 18 h. 108 induced yeast were washed with PBE (PBS with 0.5% BSA and 0.5 mM EDTA), resuspended with 100 µL purified IgG, and incubated for three hours at 4 °C with shaking. Yeast-depleted IgG was eluted from the Yeast-IgG mixture through 0.45 um filter plates by centrifugation at 3000g for 3 min.
Jaycox J.R., Lucas C., Yildirim I., Dai Y., Wang E.Y., Monteiro V., Lord S., Carlin J., Kita M., Buckner J.H., Ma S., Campbell M., Ko A., Omer S., Lucas C.L., Speake C., Iwasaki A, & Ring A.M. (2023). SARS-CoV-2 mRNA vaccines decouple anti-viral immunity from humoral autoimmunity. Nature Communications, 14, 1299.
Publication 2023
Adsorption Centrifugation Cloning Vectors Edetic Acid G-substrate Glycine Immunoglobulins Patients Plasma Resins, Plant Ribonucleases RNA Viruses Serum Sterility, Reproductive Triton X-100 Tromethamine Yeast, Dried
4
Virus Isolation and Identification from Mosquito Samples
Virus isolation was performed using C6/36 Aedes albopictus cells. Mosquito homogenates were centrifuged at 4°C for 20 min at 12,000 rpm in a high-speed refrigerated centrifuge, and 40 μL of supernatant was aspirated and inoculated into a single layer of C6/36 cells in a 24-well plate and grown for 1 day (2 wells/sample). Two wells per plate of cell controls were set up and incubated at 32°C. Cytopathic effects (CPE) were observed and recorded continuously for 4–7 days. Isolates with obvious or suspected CPE were freeze-thawed once and transferred to 25-cm2 cell bottles for blind transmission to 3–6 generations. Viral isolates with regular CPE were freeze-thawed once and then aspirated into a freezing tube at −40°C for identification. During virus isolation, the group of C6/36 Aedes albopictus cell without mosquito supernatant was cultured as negative control.
Virus-specific RT-PCR was performed to identify the viral isolates. The viral nucleic acid was extracted using the ZYBIO Magnetic Beads Virus DNA/RNA Extraction Kit (ZYBIO, Chongqing, China) and the QIAamp® Viral RNA Mini Kit (Qiagen, Hilden, Germany) and reverse transcribed using M-MLV Reverse Transcriptase (Promega, Madison, WI, United States). Based on the literature, we synthesized PCR, detection, and Sanger sequencing primers (Supplementary Table S2) for a variety of arboviruses, such as flaviviruses, alphaviruses, and viruses in the family Reoviridae, and then designed primers from newly discovered viral sequences from Yunnan and Guangxi provinces published in recent years (GoTaq® Green Master Mix, Promega). Next, next-generation sequencing (NGS) was performed to detect viruses in the isolates with CEP, but negative for RT-PCR using the designed primers. A sequencing library was constructed using the NEBNext Ultra II Directional RNA Library Prep Kit (Illumina, San Diego, CA, United States). The library was subsequently sequenced on an Illumina NovaSeq 6000 (PE150) sequencing platform. Trimmomatic v0.36 (Bolger et al., 2014 (link)) was used to remove low-quality and short reads, and SPAdes v3.13.0 (Nurk et al., 2013 (link)) was used for metagenomic assembly. Blastn and Blastx were used to search for viral contigs. PCR detection and Sanger sequencing were performed using redesigned primers based on the viruses detected in samples with unknown viruses.
Tian F., He J., Shang S., Chen Z., Tang Y., Lu M., Huang C., Guo X, & Tong Y. (2023). Survey of mosquito species and mosquito-borne viruses in residential areas along the Sino–Vietnam border in Yunnan Province in China. Frontiers in Microbiology, 14, 1105786.
Publication 2023
Aedes Alphavirus Arboviruses Culicidae Cytopathogenic Effect, Viral DNA Library DNA Viruses Flavivirus isolation Metagenome Nucleic Acids Oligonucleotide Primers Promega Reoviridae Reverse Transcriptase Polymerase Chain Reaction RNA, Viral RNA-Directed DNA Polymerase RNA Viruses Transmission, Communicable Disease Virus Visually Impaired Persons Yunnan orbivirus
5
Propagation and Titration of RNA Viruses
Vero, Vero E6, Vero.DogSLAMtag, which is stably expressing a CDV receptor, canine SLAM (Seki et al., 2003 (link); Sakai et al., 2013 (link)), MDCK and 293T cells were grown in Dulbecco’s Modified Eagle’s Medium (DMEM; catalog number 041-30081, Wako, Osaka, Japan) supplemented with 5% heat-inactivated fetal bovine serum (FBS), 100 U/ml penicillin, and 100 μg/ml streptomycin (catalog number 15140122, Thermo Fisher Scientific, Waltham, MA). In some cases, an antibiotic for Mycoplasma spp., BIOMYC-3 (catalog number PK-CC03-038-1D, Takara Bio, Shiga, Japan), was added to the culture medium at 100-fold dilution. The working stocks of RNA viruses were prepared as described and were aliquoted and stored at −80°C.
Lymphocytic choriomeningitis virus (LCMV) strain WE (Genbank Accession Numbers LC413283 and LC413284) was propagated in Vero cells at a multiplicity of infection (MOI) of 0.01. The culture supernatants were harvested at 4 days post-infection. The infectious dose was determined using Vero cells with the standard 50% tissue culture infectious dose (TCID50) assay, with visualization of infection on the wells in a 96-well plate by an indirect immunofluorescence assay (IFA), as described previously (Taniguchi et al., 2020 (link)).
Severe fever with thrombocytopenia syndrome virus (SFTSV) strain YG-1 (Genbank Accession Numbers AB817979, AB817987, and AB817995) was propagated in Vero cells at an MOI of 0.01. The culture supernatants were harvested at full cytopathic effect (CPE). The infectious dose was determined with the standard TCID50 assay, with visualization of infection on the wells in a 96-well plate by an IFA, as described previously (Takahashi et al., 2014 (link)).
Influenza A virus (IAV) strain H1N1 A/PR/8/34 (Genbank Accession Numbers LC662537, LC662538, LC662539, LC662540, LC662541, LC662542, LC662543, and LC662544) purchased from ATCC was propagated in MDCK cells with the addition of 1.0 μg/ml trypsin (catalog number 207-19183, Fujifilm Wako Pure Chemical Corporation, Osaka, Japan) in DMEM and passaged twice at an MOI of 0.01. The culture supernatants were harvested 3 days post-infection, and the infectious dose was determined using MDCK cells with the standard TCID50 assay in a 96-well plate.
Canine distemper virus (CDV) strain CYN07-dV (Genbank Accession Number AB687720) was propagated in Vero.DogSLAMtag cells at an MOI of 0.01. The cells and culture supernatants were harvested at full CPE and frozen and thawed twice, which is necessary to release the cell-associated virus into the culture supernatant. The samples were centrifuged at 1,000 ×g for 10 min, and the infectious dose was determined with the standard TCID50 assay in a 96-well plate.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) strain 2019-nCoV/Japan/TY/WK-521/2020 (GISAID ID: EPI_ISL_408667) was propagated in VeroE6 cells stably expressing transmembrane serine protease TMPRSS2 (VeroE6/TMPRSS2) (Matsuyama et al., 2020 (link)) at an MOI of 0.1. The culture supernatants were harvested at full CPE, and the infectious dose was determined using VeroE6/TMPRSS2 cells with the standard TCID50 assay in a 96-well plate.
Pteropine orthoreovirus (PRV) strain Miyazaki-Bali/2007 (Genbank Accession Numbers AB908278.1, AB908279.1, AB908280.1, AB908281.1, AB908282.1, AB908283.1, AB908284.1, AB908285.1, AB908286.1, and AB908287.1) was propagated in 293T cells at an MOI of 0.001. The culture supernatants were harvested at full CPE and titrated using Vero cells with the standard TCID50 assay in a 96-well plate.
Misu M., Yoshikawa T., Sugimoto S., Takamatsu Y., Kurosu T., Ouji Y., Yoshikawa M., Shimojima M., Ebihara H, & Saijo M. (2023). Rapid whole genome sequencing methods for RNA viruses. Frontiers in Microbiology, 14, 1137086.
Publication 2023
Antibiotics AT-001 Biological Assay Canine Distemper Canis familiaris Cell Culture Techniques Cells Culture Media Cytopathogenic Effect, Viral Distemper Virus, Canine Eagle Fetal Bovine Serum Fluorescent Antibody Technique, Indirect Freezing HEK293 Cells Infection Influenza A virus Lymphocytic choriomeningitis virus Madin Darby Canine Kidney Cells Mycoplasma Orthoreoviruses Penicillins PRSS1 protein, human Receptors, Virus RNA Viruses SARS-CoV-2 Satellite Viruses Serine Proteases Severe Fever with Thrombocytopenia Syndrome Bunyavirus Strains Streptomycin Technique, Dilution Tissues TMPRSS2 protein, human Vero Cells

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More about "RNA Viruses"

Ribonucleic acid (RNA) viruses are a diverse and dynamic group of pathogens that utilize RNA as their genetic material.
These versatile microorganisms can infect a wide range of hosts, including humans, animals, and plants, and are responsible for numerous critical diseases.
The RNA virus life cycle is centered around a unique enzyme called the RNA-dependent RNA polymerase, which is essential for their replication and propagation.
This captivating field of study encompasses well-known viruses such as influenza, HIV, and SARS-CoV-2, as well as emerging and re-emerging infectious agents.
Understanding the complex biology and epidemiology of RNA viruses is crucial for developing effective prevention and treatment strategies, as well as for advancing our understanding of these enigmatic microbes.
Researchers in this dynamic field utilize cutting-edge tools and techniques, such as the NucleoSpin RNA Virus kit, Quick-RNA Viral Kit, QIAamp Viral RNA Mini Kit, QIAamp Viral RNA kit, LightCycler Multiplex RNA Virus Master, Quick-DNA/RNA Viral Kit, RNeasy Mini Kit, NucleoSpin RNA Virus, and TIANamp Virus DNA/RNA Kit, to ensure reproducible and accurate results.
These state-of-the-art solutions empower scientists to delve deeper into the mysteries of RNA viruses, paving the way for groundbreaking discoveries and advancements in the fight against these pervasive pathogens.
Whether you're investigating influenza, HIV, SARS-CoV-2, or any other RNA virus, PubCompare.ai is your go-to resource for streamlining your research and maximizing your impact.
This cutting-edge AI-driven platform seamlessly searches through the latest literature, pre-prints, and patents to help you identify the most effective protocols and products for your needs.
Experience the future of virus research with PubCompare.ai and unlock your full potential in this dynamic and rapidly evolving field.