Technologies for the Detection and Analysis of Noroviruses: Comparison
View Latest Version
Please note this is a comparison between Version 2 by Catherine Yang and Version 1 by Shih-Yen Chen.

Human noroviruses (HuNoVs) belong to the genus of norovirus in the family of Caliciviridae and are the predominant cause of epidemic and sporadic cases of acute gastroenteritis around the world. Norovirus has a positive-strand RNA genome of approximately 7.5 kb, which contains three open reading frames (ORF). 

  • human noroviruses
  • genetics-based systems
  • evolution
  • recombination

1. Nested Polymerase Chain Reaction (PCR) with Sanger Sequencing

The genotyping of norovirus has been performed via nested PCR, which uses genogroup-specific primer pairs to amplify of the VP1 region in complementary DNA (cDNA) samples to generate a template for Sanger sequencing (Table 1) [37][1]. Primer pairs for nested PCR have been specifically designed to amplify the VP1 sequence encoding the N-terminal domain and the shell domain of the capsid, and the resulting amplicon can be subjected to Sanger sequencing to identify the norovirus genotype in the samples [37][1]. Given its ability to provide sequence information, this method is widely used in clinical laboratories to monitor the evolution of norovirus.
Table 1.
Summary of technologies used for the detection of noroviruses.
Techniques Detection Principles Advantages Disadvantages Time Cost Application Ref.
Nested PCR plus Sanger sequencing Amplification of the VP1 region for Sanger sequencing Highly sensitive, more high-quality and cost-effective than NGS Time-consuming and labor-intensive Moderately fast Inexpensive Provides sequence information and monitors evolution [37][1]
RT-qPCR PCR-based (nuclear acid amplification) Highly sensitive; rapid results; compatible with various sample types Lower resolution than sequencing; susceptible to contamination Rapid Inexpensive Rapid detection and surveillance

Known genogroup identification		 [40][2]
RT-dPCR PCR-based, microfluidic droplet platform Improved sensitivity, precision, accuracy, and multiplexing compared to qPCR More time-consuming and expensive than conventional PCR; technique expertise Moderately fast Inexpensive Absolute quantification of norovirus [49][3]
EIA Antibody-based (VLP antibodies) Rapid screening; simple and cost-effective

Kits detect several different norovirus genotypes		 Limited sensitivity and specificity

Reliance on antibodies

Escapes recognition from antigenic changes		 Rapid Inexpensive Combined with RT-qPCR

Negative samples should be confirmed a second time		 [55][4]
NGS/TGS Target and metagenomic sequencing Highly sensitive and accurate

High-throughput and comprehensive		 Time-consuming, high-cost

Requires high-quality samples		 Lengthy Expensive Genetic diversity and evolution

Recombination or synergism information		 [57,58,59][5][6][7]
Aptamers Synthetic oligonucleotides bind to target molecules (such as antibody-based molecules) Faster and affordable

More stable than antibodies

Easy to modify and develop novel aptamers		 Limited sensitivity and specificity

Temperature affects binding capacity		 Rapid Inexpensive High-throughput screening and diagnostics of emerging norovirus strains [63,64,65][8][9][10]
Reverse genetics Generates viral genomic RNA transcripts within a host cell Eliminates interference from heterologous viruses

Ensures the quality of RNA transcripts		 Time-consuming and requires technical expertise

Requires particular plasmid vectors and bacterial strains		 Lengthy Expensive Viral genomic structure, virus–host interaction and pathogenesis, vaccine development [75,76,77,78][11][12][13][14]
Abbreviations: RT-qPCR, reverse-transcription quantitative polymerase chain reaction assays; dPCR, digital polymerase chain reaction; EIA, enzyme immunoassay; NGS, next-generation sequencing; TGS, third-generation sequencing.

2. Reverse-Transcription Quantitative Polymerase Chain Reaction Assays (RT-qPCR)

RT-qPCR assays are standard molecular diagnostics for detecting norovirus RNA in clinical specimens (Table 1) [38,39,40][2][15][16]. The advantages of RT-qPCR include its ability to detect norovirus RNA from various sample types, high sensitivity, and capacity for the identification of genogroups [40][2]. RT-qPCR can probe norovirus RNA from stool [40][2], water [41][17], food [42][18], and even environmental samples [43][19], which is important for evaluating potential transmission routes. Additionally, since norovirus is a highly contagious virus, the particle number for infection can be as low as 18–1000 copies [44][20]. RT-qPCR can detect as few as 10 copies of norovirus RNA and provide information on the viral load [45][21]. Furthermore, RT-qPCR uses different primer sets to detect specific genogroups [37][1], making it an efficient tool for identifying norovirus genogroups. However, compared to the nested PCR with Sanger sequencing method, RT-qPCR has a lower resolution and can only provide information on norovirus genogroups. In summary, RT-qPCR is an extraordinary technology for the rapid detection of norovirus and providing information on the viral load in samples. In addition, norovirus RT-qPCR assays have been incorporated into several emerging technology platforms, such as digital PCR and microfluidic multiplex PCR [46,47,48][22][23][24]. In particular, the microfluidic, multiplex PCR platform was developed for the detection of multiple gastrointestinal pathogens [47,48][23][24].

3. Digital Polymerase Chain Reaction (dPCR)

To improve the detection methods for low-level pathogen densities in samples, digital PCR is an alternative approach to quantitative detection from DNA. Digital PCR works by partitioning a unique sample into thousands of individual reactions running in parallel. Digital PCR can amplify target molecules that are calculated using Poisson statistics and do not need external reference standards. Two different digital platforms, the micro/nanofluidic-based and droplet-based approaches, are utilized for detection. The most widely studied platforms are the microfluidic-based BiomarkTM HD system (Fluidigm, South San Francisco, CA, USA) and the droplet-based QX100TM and QX 200TM Droplet Digital PCR (Bio-Rad, Hercules, CA, USA) (Table 1) [49][3]. Currently, it is impossible to perform a one-step digital RT-PCR (RT-dPCR) reaction using viral RNA. Compared to traditional quantitative PCR (qPCR), which has an insufficient sensitivity to quantify viruses, RT-dPCR allows for the quantification of norovirus GII and offers improved sensitivity compared to qPCR [49][3]. Several studies have reported the use of digital PCR to detect HuNoV RNA in samples from shellfish. Droplet dPCR (ddPCR) has greater precision in terms of quantification than RT-qPCR [50][25]. The application of ddPCR can provide accurate viral quantification for further risk analysis to ensure the safety of products on the market [51,52][26][27]. Triplex ddPCR can also perform simultaneous quantifications of norovirus GI and GII and hepatitis A virus in food, drinking water, and fecal samples, suggesting that ddPCR has greater sensitivity, accuracy, and anti-interference performance features than RT-qPCR [46][22]. Recently, a novel microfluidic-based ddPCR chip was developed for the absolute quantitative detection of HuNoV. The chip is based on digital PCR, and the sample solution is divided into microdroplets through microfluidic technology. The chip has a comparable sensitivity to ddPCR and may provide an alternative method for the detection of HuNoV due to its advantages of a high throughput and high sensitivity [53,54][28][29].

4. Enzyme Immunoassay (EIA)

The enzyme immunoassay (EIA) is the most common test for the rapid detection of pathogens in clinical practice. These EIAs can be applied in large-scale clinical and epidemiological studies. EIAs require antibodies to detect various norovirus genogroups and/or genotypes. Thus, EIAs are based on polyclonal or monoclonal antibodies used to monitor different virus-like particles (VLPs). Previous studies have demonstrated that the sensitivity and specificity of norovirus EIAs vary according to diagnostic goals (Table 1) [55][4]. Commercial norovirus EIAs are available for the examination of minute amounts of stool taken as samples. However, the sensitivity of EIA is lower than that of the other tests; therefore, EIA is only suitable for use as a companion test together with other tests, such as RT-qPCR, to increase the detection efficiency. A previous report showed that a positive signal of EIA was 4.20 × 108 copies/g of fecal sample, which is equal to a cycle threshold value (CT value) of 25.6 based on the standard curve. Thus, fifty percent of GII samples might be false negatives based on EIA but show positive results with a CT value higher than 26.5 [55][4]. In addition, during the first 48 h of a norovirus outbreak, the viral load in fecal samples ranges from 107 to 108 copies/g [56][30]. This information suggests that samples collected later than 48 h after the onset of symptoms could yield negative results using the EIA method. However, additional studies are needed to evaluate the limits of detection of other genotypes. The advantage of the EIA method is that the kit has successfully detected 18 of the 21 norovirus genotypes evaluated. In summary, the EIA norovirus kit may be useful for the rapid screening of fecal samples collected during a norovirus outbreak of acute gastroenteritis, but the negative samples should be confirmed using a second technique, such as RT-PCR.

5. Next-Generation Sequencing (NGS)

Next-generation sequencing technologies offer a promising means to provide complete genome information for norovirus, which is important for investigating genetic diversity among strains, establishing evolutionary patterns, and tracing transmission chains in outbreak events. There are two NGS methods that can be used for analyzing the complete genome of norovirus: targeted sequencing [57,58][5][6] and metagenomic sequencing (Table 1) [59][7]. Targeted sequencing is based on the enrichment of sequences of interest through capture probes or primers to provide robust information on the genetic diversity of regions of interest [57,58][5][6]. The mutation frequency of norovirus is very high. Targeted sequencing can provide a precise mutation rate for specific regions in each sample, owing to the depth of targeted sequencing of specific regions [57,58][5][6]. In contrast to targeted sequencing, metagenomic sequencing provides genome information on all viruses in the sample rather than information on regions of interest from a specific virus. Metagenomic sequencing can help to study the relationships between co-infected norovirus strains, such as recombination or synergism [59][7].
A new strategy using a combination of NGS and third-generation sequencing (TGS) to provide highly accurate sequence information for isolated noroviruses was described [60][31]. The TGS platform Oxford Nanopore Technology can read up to 100 kilobases on a single DNA molecule and is an ideal method for evaluating recombination events and identifying of subgenomic sequences [60][31]. By combining the advantages of NGS and TGS, weit can gain deeper insight into the genetic evolution of norovirus.

6. Aptamer-Based Detection of Specific Genotypes

Aptamers are mostly single-strand DNA or RNA oligonucleotides, such as antibodies, that can form structures to interact with specific molecules [61][32]. They are artificially synthesized using an in vitro technology known as the Systematic Evolution of Ligands by Exponential Enrichment (SELEX) (Table 1) [62][33]. Previous studies have developed several aptamer candidates that can specifically bind to GII.4, GII.3, and GII.7, respectively [63[8][9][10],64,65], and can also bind to different VLPs corresponding to various GI and GII HuNoV strains [66][34], suggesting that aptamers have significant potential for the development of genotype-specific assays and extraction methods that could be useful for the rapid identification of norovirus strains and enrichment of viral particles for further analysis [63,64,65,66][8][9][10][34]. However, like antibody-based methods, the sensitivity of aptamer detection or enrichment technologies might decrease over time because of the rapid mutation rate of noroviruses. In contrast to antibodies, the processes for the development of novel aptamers are faster and more affordable [67[35][36],68], suggesting that it is possible to cyclically select aptamers for the detection of emerging strains. Moreover, aptamer-based point-of-care detection is evolving, and lateral flow immunochromatographic assays and paper-based microfluidic devices have been developed for HuNoV detection [69,70][37][38]. The microfluidic device utilizes the fluorescence of the 6-FAM-labeled aptamer quenched by multi-walled carbon nanotubes (MWCNT) and graphene oxide (GO), which have potential for the rapid in situ visual determination of noroviruses [70][38].

7. Reverse Genetics Techniques

The HuNoV genome is a positive-sense, single-stranded RNA (+ssRNA) of ∼7.6 kb with three ORFs: ORF1, which encodes a nonstructural polyprotein, and ORF2 and ORF3, which encode the major and minor capsid proteins VP1 and VP2, respectively [71][39]. The absence of an in vitro framework hinders the study of the HuNoV life cycle, leading to a focus on utilizing other caliciviruses and murine norovirus (MNV) that can be cultured in mammalian cells [72][40]. A 3′ coterminal polyadenylated subgenomic RNA is created inside infected cells. Genomic and subgenomic RNAs have similar nucleotide arrangement patterns at their 5′ ends, which are covalently connected to the nonstructural protein VPg at the 5′ ends in HuNoVs, as has been demonstrated for MNV [73,74][41][42]. Nonstructural proteins are communicated from genomic RNA and form an RNA replication complex that creates new genomic RNA particles, as observed in subgenomic RNAs encoding VP1, VP2, and the interesting protein called VF1 during MNV infection of cells [8][43]. The capsid is gathered, and viral RNA is encapsidated before descendants’ discharge after the articulation of the underlying proteins from subgenomic RNA particles [8][43].
Reverse genetics for positive-strand RNA viruses infections depends on the gathering of full-length cDNA clones in a plasmid vector or, for larger viruses such as coronaviruses, in bacterial or yeast artificial chromosome vectors (BAC and YAC) and their engendering in microorganisms or yeast [75][11]. Fusion with the bacteriophage T7 or SP6 promoter enables the cell-free production of viral RNA with T7 or SP6 RNA polymerases. The fusion of a eukaryotic ubiquitous promoter, rather than T7 or SP6 promoters, induces the generation of viral RNA from transfected DNA via endogenous cell RNA polymerase II [76][12]. Reverse genetics techniques have generally been utilized in the RNA virology field, engendering full-length cDNA clones, especially for larger viruses with some popular arrangements among microscopic organisms (Table 1) [77,78][13][14]. A few methodologies have been developed to overcome these issues, including the utilization of extremely low-copy-number plasmids, change of enigmatic locales, production of full-length DNA formats for in vitro RNA recorded via the in vitro ligation of DNA fragments, and the cotransfection of a combination of covering DNA fragments with the principal section containing the eukaryotic articulation advertiser upstream of the viral 5′ untranslated region (5′ UTR) sequence [79,80][44][45]. Though useful for some positive-strand RNA viruses, these methodologies have either not been fruitful or not been attempted for most RNA viruses. They frequently require the development of customized conditions, such as the utilization of particular plasmid vectors and bacterial strains, the restricted selection of sections due to explicit areas of limitation destinations, and the need for large arrangement covers.

References

  1. Kojima, S.; Kageyama, T.; Fukushi, S.; Hoshino, F.B.; Shinohara, M.; Uchida, K.; Natori, K.; Takeda, N.; Katayama, K. Genogroup-specific PCR primers for detection of Norwalk-like viruses. J. Virol. Methods 2002, 100, 107–114.
  2. Ramanan, P.; Espy, M.J.; Khare, R.; Binnicker, M.J. Detection and differentiation of norovirus genogroups I and II from clinical stool specimens using real-time PCR. Diagn. Microbiol. Infect. Dis. 2017, 87, 325–327.
  3. Monteiro, S.; Santos, R. Nanofluidic digital PCR for the quantification of Norovirus for water quality assessment. PLoS ONE 2017, 12, e0179985.
  4. Costantini, V.; Grenz, L.; Fritzinger, A.; Lewis, D.; Biggs, C.; Hale, A.; Vinjé, J. Diagnostic Accuracy and Analytical Sensitivity of IDEIA Norovirus Assay for Routine Screening of Human Norovirus. J. Clin. Microbiol. 2010, 48, 2770–2778.
  5. Cotten, M.; Petrova, V.; Phan, M.V.; Rabaa, M.A.; Watson, S.J.; Ong, S.H.; Kellam, P.; Baker, S. Deep sequencing of norovirus genomes defines evolutionary patterns in an urban tropical setting. J. Virol. 2014, 88, 11056–11069.
  6. Brown, J.R.; Roy, S.; Ruis, C.; Yara Romero, E.; Shah, D.; Williams, R.; Breuer, J. Norovirus Whole-Genome Sequencing by SureSelect Target Enrichment: A Robust and Sensitive Method. J. Clin. Microbiol. 2016, 54, 2530–2537.
  7. Fonager, J.; Stegger, M.; Rasmussen, L.D.; Poulsen, M.W.; Rønn, J.; Andersen, P.S.; Fischer, T.K. A universal primer-independent next-generation sequencing approach for investigations of norovirus outbreaks and novel variants. Sci. Rep. 2017, 7, 813.
  8. Schilling-Loeffler, K.; Rodriguez, R.; Williams-Woods, J. Target Affinity and Structural Analysis for a Selection of Norovirus Aptamers. Int. J. Mol. Sci. 2021, 22, 8868.
  9. Moore, M.D.; Escudero-Abarca, B.I.; Suh, S.H.; Jaykus, L.A. Generation and characterization of nucleic acid aptamers targeting the capsid P domain of a human norovirus GII.4 strain. J. Biotechnol. 2015, 209, 41–49.
  10. Beier, R.; Pahlke, C.; Quenzel, P.; Henseleit, A.; Boschke, E.; Cuniberti, G.; Labudde, D. Selection of a DNA aptamer against norovirus capsid protein VP1. FEMS Microbiol. Lett. 2014, 351, 162–169.
  11. Arias, A.; Ureña, L.; Thorne, L.; Yunus, M.A.; Goodfellow, I. Reverse genetics mediated recovery of infectious murine norovirus. J. Vis. Exp. 2012, 64, e4145.
  12. Hulo, C.; de Castro, E.; Masson, P.; Bougueleret, L.; Bairoch, A.; Xenarios, I.; Le Mercier, P. ViralZone: A knowledge resource to understand virus diversity. Nucleic Acids Res. 2011, 39, D576–D582.
  13. Almazán, F.; Sola, I.; Zuñiga, S.; Marquez-Jurado, S.; Morales, L.; Becares, M.; Enjuanes, L. Coronavirus reverse genetic systems: Infectious clones and replicons. Virus Res. 2014, 189, 262–270.
  14. Aubry, F.; Nougairède, A.; Gould, E.A.; de Lamballerie, X. Flavivirus reverse genetic systems, construction techniques and applications: A historical perspective. Antivir. Res. 2015, 114, 67–85.
  15. Schmid, M.; Oehme, R.; Schalasta, G.; Brockmann, S.; Kimmig, P.; Enders, G. Fast detection of Noroviruses using a real-time PCR assay and automated sample preparation. BMC Infect. Dis. 2004, 4, 15.
  16. Hoehne, M.; Schreier, E. Detection of Norovirus genogroup I and II by multiplex real-time RT- PCR using a 3′-minor groove binder-DNA probe. BMC Infect. Dis. 2006, 6, 69.
  17. Rutjes, S.A.; van den Berg, H.H.; Lodder, W.J.; de Roda Husman, A.M. Real-time detection of noroviruses in surface water by use of a broadly reactive nucleic acid sequence-based amplification assay. Appl. Environ. Microbiol. 2006, 72, 5349–5358.
  18. Park, Y.; Cho, Y.H.; Jee, Y.; Ko, G. Immunomagnetic separation combined with real-time reverse transcriptase PCR assays for detection of norovirus in contaminated food. Appl. Environ. Microbiol. 2008, 74, 4226–4230.
  19. Rodríguez, R.A.; Thie, L.; Gibbons, C.D.; Sobsey, M.D. Reducing the effects of environmental inhibition in quantitative real-time PCR detection of adenovirus and norovirus in recreational seawaters. J. Virol. Methods 2012, 181, 43–50.
  20. Glass, R.I.; Parashar, U.D.; Estes, M.K. Norovirus gastroenteritis. N. Engl. J. Med. 2009, 361, 1776–1785.
  21. Jothikumar, N.; Lowther, J.A.; Henshilwood, K.; Lees, D.N.; Hill, V.R.; Vinjé, J. Rapid and sensitive detection of noroviruses by using TaqMan-based one-step reverse transcription-PCR assays and application to naturally contaminated shellfish samples. Appl. Environ. Microbiol. 2005, 71, 1870–1875.
  22. Han, Y.; Wang, J.; Zhang, S.; Yang, S.; Wang, X.; Han, Y.; Shen, Z.; Xu, X. Simultaneous quantification of hepatitis A virus and norovirus genogroup I and II by triplex droplet digital PCR. Food Microbiol. 2022, 103, 103933.
  23. Gyawali, P.; Croucher, D.; Hewitt, J. Preliminary evaluation of BioFire FilmArray(®) Gastrointestinal Panel for the detection of noroviruses and other enteric viruses from wastewater and shellfish. Environ. Sci. Pollut. Res. Int. 2018, 25, 27657–27661.
  24. Buss, S.N.; Leber, A.; Chapin, K.; Fey, P.D.; Bankowski, M.J.; Jones, M.K.; Rogatcheva, M.; Kanack, K.J.; Bourzac, K.M. Multicenter evaluation of the BioFire FilmArray gastrointestinal panel for etiologic diagnosis of infectious gastroenteritis. J. Clin. Microbiol. 2015, 53, 915–925.
  25. Persson, S.; Eriksson, R.; Lowther, J.; Ellström, P.; Simonsson, M. Comparison between RT droplet digital PCR and RT real-time PCR for quantification of noroviruses in oysters. Int. J. Food Microbiol. 2018, 284, 73–83.
  26. Polo, D.; Schaeffer, J.; Fournet, N.; Le Saux, J.C.; Parnaudeau, S.; McLeod, C.; Le Guyader, F.S. Digital PCR for Quantifying Norovirus in Oysters Implicated in Outbreaks, France. Emerg. Infect. Dis. 2016, 22, 2189–2191.
  27. Tan, D.M.; Lyu, S.L.; Liu, W.; Zeng, X.Y.; Lan, L.; Qu, C.; Zhuge, S.Y.; Zhong, Y.X.; Xie, Y.H.; Li, X.G. Utility of Droplet Digital PCR Assay for Quantitative Detection of Norovirus in Shellfish, from Production to Consumption in Guangxi, China. Biomed. Environ. Sci. 2018, 31, 713–720.
  28. Qin, Z.; Xiang, X.; Xue, L.; Cai, W.; Gao, J.; Yang, J.; Liang, Y.; Wang, L.; Chen, M.; Pang, R.; et al. Development of a novel RAA-based microfluidic chip for absolute quantitative detection of human norovirus. Microchem. J. 2021, 164, 106050.
  29. Xu, D.; Zhang, W.; Li, H.; Li, N.; Lin, J.-M. Advances in droplet digital polymerase chain reaction on microfluidic chips. Lab Chip 2023, 23, 1258–1278.
  30. Chan, M.C.W.; Sung, J.J.Y.; Lam, R.K.Y.; Chan, P.K.S.; Lee, N.L.S.; Lai, R.W.M.; Leung, W.K. Fecal Viral Load and Norovirus-associated Gastroenteritis. Emerg. Infect. Dis. 2006, 12, 1278–1280.
  31. Flint, A.; Reaume, S.; Harlow, J.; Hoover, E.; Weedmark, K.; Nasheri, N. Genomic analysis of human noroviruses using combined Illumina-Nanopore data. Virus Evol. 2021, 7, veab079.
  32. Stoltenburg, R.; Reinemann, C.; Strehlitz, B. SELEX—A (r)evolutionary method to generate high-affinity nucleic acid ligands. Biomol. Eng. 2007, 24, 381–403.
  33. Zou, X.; Wu, J.; Gu, J.; Shen, L.; Mao, L. Application of Aptamers in Virus Detection and Antiviral Therapy. Front. Microbiol. 2019, 10, 1462.
  34. Escudero-Abarca, B.I.; Suh, S.H.; Moore, M.D.; Dwivedi, H.P.; Jaykus, L.-A. Selection, Characterization and Application of Nucleic Acid Aptamers for the Capture and Detection of Human Norovirus Strains. PLoS ONE 2014, 9, e106805.
  35. Conrad, R.C.; Giver, L.; Tian, Y.; Ellington, A.D. In vitro selection of nucleic acid aptamers that bind proteins. Methods Enzymol. 1996, 267, 336–367.
  36. Kulbachinskiy, A.V. Methods for selection of aptamers to protein targets. Biochemistry 2007, 72, 1505–1518.
  37. Li, H.-Y.; Jia, W.-N.; Li, X.-Y.; Zhang, L.; Liu, C.; Wu, J. Advances in detection of infectious agents by aptamer-based technologies. Emerg. Microbes Infect. 2020, 9, 1671–1681.
  38. Weng, X.; Neethirajan, S. Aptamer-based fluorometric determination of norovirus using a paper-based microfluidic device. Microchim. Acta 2017, 184, 4545–4552.
  39. Asanaka, M.; Atmar, R.L.; Ruvolo, V.; Crawford, S.E.; Neill, F.H.; Estes, M.K. Replication and packaging of Norwalk virus RNA in cultured mammalian cells. Proc. Natl. Acad. Sci. USA 2005, 102, 10327–10332.
  40. Katayama, K.; Hansman, G.S.; Oka, T.; Ogawa, S.; Takeda, N. Investigation of norovirus replication in a human cell line. Arch. Virol. 2006, 151, 1291–1308.
  41. Robilotti, E.; Deresinski, S.; Pinsky, B.A. Norovirus. Clin. Microbiol. Rev. 2015, 28, 134–164.
  42. Chaudhry, Y.; Nayak, A.; Bordeleau, M.E.; Tanaka, J.; Pelletier, J.; Belsham, G.J.; Roberts, L.O.; Goodfellow, I.G. Caliciviruses differ in their functional requirements for eIF4F components. J. Biol. Chem. 2006, 281, 25315–25325.
  43. Daughenbaugh, K.F.; Wobus, C.E.; Hardy, M.E. VPg of murine norovirus binds translation initiation factors in infected cells. Virol. J. 2006, 3, 33.
  44. Hall, R.A.; Nisbet, D.J.; Pham, K.B.; Pyke, A.T.; Smith, G.A.; Khromykh, A.A. DNA vaccine coding for the full-length infectious Kunjin virus RNA protects mice against the New York strain of West Nile virus. Proc. Natl. Acad. Sci. USA 2003, 100, 10460–10464.
  45. Cockrell, A.S.; Beall, A.; Yount, B.; Baric, R. Efficient Reverse Genetic Systems for Rapid Genetic Manipulation of Emergent and Preemergent Infectious Coronaviruses. Methods Mol. Biol. 2017, 1602, 59–81.
More
© Text is available under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/)
Video Production Service
Feedback