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High-resolution melting (HRM) for genotyping bovine ephemeral fever virus (BEFV)
Accepted Manuscript Title: High-resolution melting (HRM) for genotyping Bovine Ephemeral Fever Virus (BEFV) Author: Oran Erster Rotem Stram Shopia Menasherow Marisol Rubistein-Giuni Binyamin Sharir Evgeni Kchinich Yehuda Stram PII: DOI: Reference:
S0168-1702(16)30473-7 http://dx.doi.org/doi:10.1016/j.virusres.2016.11.030 VIRUS 97019
To appear in:
Virus Research
Received date: Revised date: Accepted date:
25-7-2016 6-11-2016 24-11-2016
Please cite this article as: Erster, Oran, Stram, Rotem, Menasherow, Shopia, RubisteinGiuni, Marisol, Sharir, Binyamin, Kchinich, Evgeni, Stram, Yehuda, High-resolution melting (HRM) for genotyping Bovine Ephemeral Fever Virus (BEFV).Virus Research http://dx.doi.org/10.1016/j.virusres.2016.11.030 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
High-resolution melting (HRM) for genotyping Bovine Ephemeral Fever Virus (BEFV) Oran Erster1, Rotem Stram2, Shopia Menasherow1, Marisol Rubistein-Giuni1, Binyamin Sharir3, Evgeni Kchinich1 and Yehuda Stram1 1
Molecular Virology Unit, Virology Division, Kimron Veterinary Institute, Bet-Dagan, 50250
Israel 2
German Research Center for Artificial Intelligence, Knowledge Management Group, Berlin,
Germany 3
HaChaklait, P.O Box 3039, Caesarea, Israel.
Corresponding Author: Yehuda Stram Molecular Virology Unit, Virology Division, Kimron Veterinary Institute, Bet-Dagan, 50250 Israel Phone: +972 3 9681 697 Fax: +972 3 9681 788 E. mail: [email protected]
Highlights
Genotyping of BEFV by HRM based on the GC content of the amplified fragment. Each assay relies on the use of one pair of primers. The test is constructed using our newly developed algorithm. The test enables the designation of the origin of each isolates. This algorithm can also be applicable for genotyping of other viruses or genes.
Abstract In recent years there have been several major outbreaks of bovine ephemeral disease in the Middle East, including Israel. Such occurrences raise the need for quick identification of the viruses responsible for the outbreaks, in order to rapidly identify the entry of viruses that do not belong to the Middle-East BEFV lineage. This challenge was met by the development of a high-resolution method (HRM) assay. The assay is based on the viral G gene sequence and generation of an algorithm that calculates and evaluates the GC content of various fragments. The algorithm was designed to scan 50- to 200-base-long segments in a sliding-window manner, compare and rank them using an Order of Preference by Similarity (TOPSIS) to Ideal Solution technique for order preference by similarity to ideal solution technique, according to the differences in GC content of homologous fragments. Two fragments were selected, based on a match to the analysis criteria, in terms of size and GC content. These fragments were successfully used in the analysis to differentiate between different virus lineages, thus facilitating assignment of the viruses' geographical origins. Moreover, the assay could be used for, differentiating between field virus from vaccine strain (DIVA). The new algorithm may therefore be useful for development of improved genotyping studies for other viruses and possibly other microorganisms.
Key words: HRM analysis, Bovine ephemeral fever virus, Genotyping, GC content
1.0 Introduction Bovine ephemeral fever virus (BEFV) is a noncontagious arthropod-borne virus belonging to the genus Ephemerovirus in the family Rhabdoviridae. Similarly to other members of this family, BEFV exhibits a bullet-shaped morphology (Delte-Porta & Brown, 1979). Its genome is 14,900 bases long: a single-strand (ss) RNA in the negative polarity encoding five structural proteins – N, a nucleoprotein; P, a polymerase-associate protein; M, a matrix protein; L, a viral RNA polymerase-associate protein; and G, a surface glycoprotein – together with GNS, a non-structural glycoprotein, and four open reading frames (ORFs) – , and Walker et al., 1991, 1992; McWilliam et al., 1997; Dhillon et al., 2000; Amos-Ritchie et al., 2014; Joubert et al., 2014). BEF is an important viral disease of cattle and water buffalo in tropical, subtropical, and temperate climatic zones; it was reported in Africa, Asia including the Middle East, and Australia, but has never been documented in Europe or North and South America (Wang, et al., 2001; Kirkland, 2002; Yeruham et al., 2002, 2003; Venter et al., 2003). The cattle disease, which is also known as three-day sickness, is characterized by stiffness, acute febrile reactions, lameness, and spontaneous recovery within 3 days (Nandi & Negi, 1999; Kirkland, 2002). In spite of its short duration, the disease can cause heavy economic losses, due to decreased milk production and lowered fertility in bulls, as well as fatality in severe cases (Nandi & Negi, 1999; Yeruham et al., 2003). The virus is suspected to be transmitted by insects, and it has been isolated from a variety of insect vectors, including midges and mosquitoes (Davies & Walker, 1974). However, thus far, no insect vectors have been identified in controlled experiments. Recently, four major outbreaks occurred in Israel, the first starting in 1999 among dairycattle herds in the Jordan Valley, from where it then spread to the Mediterranean coastal plain (Yeruham et al., 2002, 2003). The second outbreak started in 2004 and was much more widespread, covering most of Israel's Mediterranean Coastal Plain; the third, in 2010, covered the interior plain, and recently, in 2014-15, disease outbreaks were also recorded in the interior valley east of Haifa (unpublished data). The High-Resolution Method (HRM) is a post-PCR analysis that enables direct characterization of DNA amplicons by producing DNA melt-curve profiles that can discriminate among nucleic acids according to sequence differences such as SNPs and small deletions. The technique enables mutation scanning, methylation, and genotyping (Garritano et al., 2009; Sarker et al. 2014; Amornpisutt et al. 2015; Naze et al. 2015; Sady et al. 2015). It is precise and accurate, and it is a nondestructive method that allows
performance of downstream post-amplification procedures, e.g., gel electrophoresis or sequencing, following melt analysis (Druml & Cichna-Markl, 2014). Melt-curve evaluation of qPCR products is usually performed to ensure primer specificity; typically it covers a temperature range of 65–95°C in 0.5°C increments. In HRM experiments, data is generally collected at narrower temperature increments than under standard melt-curve protocols, commonly 0.2 to 0.1°C. Use of a highly concentrated saturation dye, e.g., LC Green PLUS, EvaGreen, SYTO9 or ResoLight, makes it possible to saturate every single nucleotide of the double-stranded DNA by intercalating the dye so as to label the PCR product along its entire length, thereby ensuring that all melting domains are detected (Reed et al., 2007 ; Erali et al., 2008; Druml & Cichna-Markl 2014). HRM analysis software is used to identify areas of stable pre- and post-melt fluorescence intensity from the HRM curve. In light of the large number of recent BEF outbreaks in the Middle East, it was important to develop a technique that would rapidly identify origins of newly emerging viruses – for two reasons. First, to promptly determine whether a circulating virus is a local one or a new arrival, and then to determine its geographical origin. These data are obtainable because newly introduced viruses will have a greater chance to overcome the currently used vaccine than the local endemic virus. The second reason is to meet the need to distinguish between vaccine strains and field virus if the vaccine strain was not prepare from a local virus. The analysis is based on testing the melting profile of homologous fragments from different samples that contain sufficient lineage-dependent GC content for HRM analysis. In order to identify regions that meet these requirements, an algorithm was developed and employed, that aimed to find fragments that are suitable for using in the assay, based on their GC content. In this study, by taking advantage of the algorithm, two suitable fragments were selected and used to identify virus lineage.
2.0 Materials and Methods 2.1 Viruses All Israeli viruses used were obtained from infected cattle. All other isolates – from Turkey, Australia, and Japan – were obtained as RNA or cDNA extractions.
2.2 RNA extraction RNA was extracted from infected blood samples with the Viral Gene-spin kit (http://www.intronbio.com/Intro.asp) according to the manufacturer's instructions.
2.3 cDNA synthesis The Verso cDNA kit (Fisher, https://www.thermofisher.com/order/catalog/product/ AB1453A) was used for cDNA synthesis, using 500 ng of total RNA according to the manufacturer's instructions.
2.4 Cloning of reference BEFV protein G sequences and Generation of control protein G gene RNA segment The BEFV Protein G gene segment corresponding to region 750 to 1359 was amplified using the primers 5’- CTAATACGACTCACTATAGGGACCAAACAGAATCTGACT TCC-3’ (FWD control), and 5’-GATATTCCTCTATTCCCTCG-3’ (REV control). The underlined part corresponds to the T7 promoter sequence. The corresponding G gene regions from all studied isolates were cloned and sequenced. The PCR product of the control amplicon of isolate ISR2014 and the Australian vaccine were gel-purified and used as a template for synthesis of RNA control template, using the MEGAscript T7 Transcription Kit (Fisher, https://www.thermofisher.com/order/catalog/product/AM1334), according to the manufacturer’s instructions. These products were then used as reference amplicons to evaluate the efficiency and sensitivity of the RT-quantitative PCR procedure. For the HRM calibration procedure, standard DNA amplicon concentrations of each isolate were used, so that the Cq difference between all samples will not exceed 4-5 cycles.
2.5 qPCR and HRM analysis The RT-quantitative PCRs were performed with the SensiFast HRM mix (Bioline, www.bioline.com/us/ sensifast -hrm-kit.html). The reaction mix preparation was as follows: 2x SensiFast HRM mix - 5L, template – 3L, primers – 0.4M final of each, ddH2O – to a final volume of 10L. Reaction conditions for the 1140-1351 amplicon were
as follows: 95C for 0:30 min, 44x [95°C for 0:05 min, 60C for 0:30 min + Plate Read], Melt Curve: 65C to 95C, increment 0.5C,0:05 + Plate Read. Reaction conditions for the 1234-1340 amplicon were as follows: 95°C for 2:00 min, 44x [ 95°C for 0:05 min, 60°C for 0:10 min, 72.0°C for 0:15 min, Plate Read], Melt Curve: 70.0°C to 85.0°C, Increment 0.1°C for 0:01 min + Plate Read. Reaction conditions for the 79-140 amplicon were as follows: 95°C for 2:00 min, 44x [95°C for 0:05 min, 60°C for 0:15 min, 72°C for 0:15 min, Plate Read], Melt Curve: 70°C to 85°C, Increment 0.1°C for 0:01 min + Plate Read. All reactions were carried out with the CFX 96 apparatus (Bio-Rad, Hercules, CA, USA) and analyzed with the Bio-Rad CFX Manager Precision Melt Program (Bio-Rad).
2.6 Bioinformatics 2.6.1 Primer designand in silico PCR Primers for conventional and quantitative PCR were designed using Primer3 (http://bioinfo.ut.ee/primer3-0.4.0/) and were tested in silico using the Geneious package (http://www.geneious.com/) with BEFV G gene sequences.
2.6.2 GC analysis algorithm The algorithm was implemented in the Java programming language (Oracle, CA, USA). It was compiled, tested, and run on the Eclipse Luna software (Eclipse Foundation, Ottawa, Canada) under a Windows 7 environment.
2.6.3 Additional programs For sequence analysis and reaction design, two main sets of programs were used: Geneious (Biomatters, Auckland, New Zealand) and the European Molecular Biology Open Software Suite (EMBOSS). In addition, the ClustalW2 Multiple Homology Analysis tools (http://www.ebi.ac.uk/Tools/msa/clustalw2/) were used. Phylogenetic and molecular evolutionary analyses were conducted with the MEGA software, version 6.0 (Tamura et al., 2013). Design and analysis of the real-time PCR and HRM tests were performed using the Bio-Rad CFX Manager and Precision programs (http://www.bio-rad.com/en-il/sku/).
3.0 Results The G genes from isolates obtained in recent outbreaks were sequenced and subjected to phylogenetic analysis, which showed that the Israeli viruses and those from Turkey shared a common lineage, designated "Mediterranean", and which differed from the Australian and the Far-East lineages (Fig. 1). Genotyping of BEFV was performed by means of the HRM method, using the viral G gene sequence. This genotyping was based on the gene's ability to tolerate mutations without losing viability, demonstrating its ability to withstand the hostile host's immune system environment. The same properties of the G gene are also the basis for phylogenetic studies of the virus. For the assay, the following primer pair, amplifing the 1140-1292 amplicon, was first tested for sensitivity and specificity: BEFHRMf-1140 BEFHRMr-1273
5'-GAATCATTATGGGATMGGATC-3'
at
position
1140
and
5'-CCTCCTGCTGGTGCTGTTTC-3' at position 1273 of acc.
KJ729108. Sensitivity was tested with a series of tenfold dilutions of 1 ng of viral rRNA carrying the qPCR amplicon (Stram et al., 2004), a nd was able to detect 5x100–5x101 viral genomes per 1 ml (Fig. 2A). Specificity was tested by using various viral genomes as template, including Peste des Petits Ruminants (PPRV), Bovine Herpes 1 (BoH1) Bovine Viral Diarrhea Virus (BVDV) and Rabies virus, a Rhabdovrirus (Fig. 2B). All examined viruses except the BEFV control were negative; the BHV-1 sample with Ct of 37.5 gave, for all practical purposes, a negative result (Fig. 2B). To test the capability of the detection system to differentiate between viruses from different origins, the HRM analysis was applied to isolates from Israel, Turkey, East Asia, and Australia (Fig. 1C). The assay revealed distinct differences in Tm between the viruses – differences that were consistent with their various places of isolation or, in other words, with their lineages as revealed in the phylogenetic tree (Kato et al., 2009). The Israeli isolates from 2005 and 2014 had the lowest Tm, of 76.2–76.50°C, those with the next-lowest Tm, of 77.90– 78.10°C, were those from the Asia region (Japan and Taiwan). The Turkish isolates had Tm values of 79.4–79.30°C, and the Australian isolates had the highest assayed Tm, of 79.40–79.60°C. The HRM results are fully consistent with the respective GC contents of the isolates (Table 1). Moreover, these findings parallel the complete G gene phylogenetic analysis, in the sense that each of the HRM-tested isolates, except for the Turkish ones, fell into its corresponding position in the phylogenetic analysis. Surprisingly, the Turkish isolates showed similar Tm values to the Australian ones (79.4–79.6°C), in contrast to the complete gene phylogenetic analysis results, which placed the Turkish isolates in the
Mediterranean group, far from the Australian ones (Fig. 1). Supporting the HRM results is the phylogenetic analysis that was applied to the amplicon sequences; this is in agreement with that of the full G gene except for the Turkish isolate, which this analysis showed to belong with the Australian isolates. Although the reaction design described above provided partial differentiation between BEFV isolates, it did not distinguish between all the various isolates. Therefore, better regions within the G sequence, more suitable for this task, needed to be identified. To facilitate systematic identification of optimal regions within a given sequence, an algorithm was developed especially for this work; it was able to determine, compare and evaluate the differences in GC percentages among homologous sequences from various isolates (Table 1). The newly developed algorithm grouped the isolates according to their origin, and located fragments of various sizes, in the range of 50–200 bases, that displayed the widest difference in GC content between the various groups of viruses. The ranking of each of the selected fragments was calculated with the TOPSIS method (Hwang & Yoon, 1981), with 70% weighting given to diversity and 30% to fragment size (Table 2). The analysis identified two regions suitable for the assay: one located at the 5' end of the gene, between positions 100 and 200, and another between positions 1000 and 1400. Two fragments, located at each of the above mentioned regions, were selected according to their GC content, size, and the suitability of their ends to serve as primers. Each of the selected fragments contained highly conserved sequences at both ends. The first examined fragment was a 93-base sequence, 1234-1360 amplicon, located at position 1273 of the G gene. The primers BEFVHRMf-1234 5'-GAAACAGCRCCRGCAGGAGG at position 1273 and BEFVHRMr-1340 5'-TATATWGATTTTGTATGCA at position 1273, (in acc. KJ729108), as shown in Table 2, row 2, were highly homologous among isolates from all endemic regions. The reaction was sufficiently sensitive to detect between 101 and 102 viral genomes per 5L (Figure 2A). The specificity of the reaction was also established, yielding negative results with all tested viruses (Fig. 3B). The assay revealed distinct differences between the viruses – differences that were consistent with their geographic origin, or with their lineages, as shown in the virus phylogenetic tree, based on the protein G sequence. In this assay, the Israeli isolates from 2005 and 2014 exhibited the lowest Tm, of 76.2 to 76.50°C, while the next-lowest Tm, of 77.90 to 78.10°C was found among isolates from the Far-East Asia region (Japan and
Taiwan). The Turkish isolates showed Tm values of 79.40 to 79.30°C and the Australian isolates had the highest assayed Tm, of 79.40 to 79.60°C. These HRM results are fully consistent with the GC contents of the respective isolates (Fig. 3C). Moreover, these findings match the phylogenetic analysis, as each of the HRM-tested isolates fell into its corresponding position in the phylogenetic tree (Fig. 1). The second fragment (79-160 amplicon) a 81 bases-long at position 120, was also tested with BEFHRM79F-ACAACGTTTAAATGAATTG at position 79 and BEFHRM120R- 5' TGTGGTCTAC AAATCTTATT at position 181 of the gene (acc. KJ729108) primers. As with the previously described assays, both sensitivity (Fig. 4A) and specificity (Fig. 4B) were tested: the assay was able to detect 100–101 genomes per 10L reaction, and it did not react with any viral sample tested, other than BEFV (Fig. 3A, B). The HRM analysis yielded similar, but not identical results, where the Tm’s of the Israeli isolates, ISR 2005 and ISR 2014, were close to each other, ranging from 75.6 and 75.90C respectively. The Tm of the Turkish isolate, TRK 2008 was 76.10C, and the Tm’s of the Japanese JPN 88and 3E12 and the Australian Vacc Strain were 76.40C (Fig. 3C). Both experiments showed ability to differentiate between the various isolates in accordance with their origin.
The Tm values ranged from 75.6°C for isolates from Israel 2005 to 76.4°C representing isolates from Japan. The analysis demonstrated that it could discriminate between different isolates according to their place of isolation, and did so in full consistency with the phylogenetic tree (Kato et al. 2009; Zheng and Qiu 2012).
4.0 Discussion The aim of this study was to implement the HRM technique for genotyping BEFV by means of a simple and rapid assay that would be able to classify any new isolate and determine its origin. In the current era of global climate change and increased international mobility, there is always a chance that exotic viruses will be introduced into new territories, let alone an exotic BEFV that could break down existing vaccines, exposing the local herd to the disease. To address this challenge, the assay described herein was developed, and was able to distinguish between BEFV isolates from differing origins. The new algorithm developed in this study was instrumental for the success of the approach. The viral G gene was selected for the test because there are ample sequence data of this gene, and it is routinely used for phylogenetic analyses (Kato et al., 2009; Zheng & Qiu, 2012). Moreover, the virus envelop protein G glycoprotein is under constant
immunological evolutionary pressure, to constantly undergo changes, in order to adapt to an ever-changing host immune environment, making it an ideal target for genotyping. The GC content-based genotyping procedure is based on the assumption that viruses undergo a different evolutionary process in each environment, thereby creating an evolutionary signature unique to that environment, which is reflected in different virus lineages, each unique to a specific geographic location. The first fragment that was tested in the present study – a fragment at position 1140–1234 in the G gene, was selected due to the presence of conserved flanking regions. This allows the amplification of this region from isolates of multiple origins (Fig. 1). The HRM analysis that was applied demonstrated the validity of the approach. This analysis revealed that each lineage created a distinct pattern that was unique to its origin (Fig. 3). Surprisingly, when isolates from Turkey were tested using this fragment, their patterns were indistinguishable from those of the Australian isolates (Fig. 3), indicating that the Turkish and the Australian amplicon contained similar GC contents. This result is in sharp contrast to their respective positions in the phylogenetic analysis, which placed the Turkish isolates in the Middle-East lineage (Fig. 1). To evaluate this outcome, the amplicon of one of the Turkish isolates was sequenced and was found to be highly homologous to the Australian isolates (Data not shown). This result motivated the development of an algorithm that would provide a rational approach for selecting fragments suitable for the analysis. The new algorithm that was developed can calculate the GC percentages of fragments of various sizes – 50 to 200 bases in the present study – grouped according to geographical origin, and can evaluate the differences in GC contents among the groups. Once this is done, all the tested fragments are ranked by means of the TOPSIS procedure, according to the minimal GC differences between the groups, and also according to fragment size. Applying the algorithm ensured a complete coverage of the possibilities, as set by the ranking parameters, and an automated decision-making process for choosing the appropriate fragment (Table 2). In addition to choosing the allocated fragments according to mere differences in their GC contents, further factors need to be considered.
It is equally important to choose a
fragment that bears sequences suitable for primers at both ends. The ends of the fragments should display sequences that are highly conserved among all relevant viruses, as they should be able to amplify the selected fragment from all the various isolates that represent all virus lineages. Another aspect – and not the least important – is minimizing the effect of
the primers on the Tm. This is because primers that carry too many changes among the different isolates will greatly affect the analysis, and will not yield a genuine Tm value, as primers can constitute more than 50% of the entire fragment. The primers used in the present study exhibited minimal changes: the first set showed only one change in each of the two pairs (Fig. 2A, B), thereby exerting only a marginal influence on the melting profiles of the fragments. Even so, one should not disregard the possibility of future changes in these regions. The first fragment that was selected on the basis of the GC algorithm was a 93 bases long sequence, located at position 1234, with optimal size for HRM (Mao et al., 2007), revealing at least 2% difference among the various lineages (Table 2). As discussed above, the selected primers showed high homology at both ends with all tested fragments (data not shown). The results of the assay demonstrated its capacity to distinguish between the different isolates and to arrange them in accordance with their origins. The HRM results (Fig. 2) are highly consistent with the preliminary assumptions made in developing the assay. The Tm values of each group are unique to that group; for example, the Australian isolates from 1985 to 2012 have Tm values at the opposite extremes are in the range of 74.5 and 74.7°C(Israeli isolates) and 77.50–77.60°C (Australian group) Importantly, all the Tm values exhibited by each of the groups are fully consistent with the GC-content analysis, as presented in Table 1. The use of an algorithm-aided selected fragment for the HRM analysis overcame the drawback associated with the previous HRM assay, thus enabling distinction between the Turkish and the Australian isolates; each appears separate (Fig. 4). To show the strengths of the algorithm, a second fragment at a different region, starting at position 79, was chosen and tested (Fig. 4). It is clear that the developed algorithm is appropriate for the task of evaluating GC content, and also for comparing and ranking it, according to the priority set by the user. In order to further establish the strength of the algorithm, a second fragment suitable for the analysis was selected (Fig. 4), located at a separate GC variable region with a different 5' location. The HRM results resembled those of the first region in the sense that the different isolates were clearly distinguished (Fig. 3). In both assays the actual HRM curves were formed as predicted, with viruses belonging to a group sharing the lowest GC content showed low Tm values, etc., and the other groups conformed to a pattern that enabled distinction among all the diverse virus lineages. An important advantage of this assay is its ability to assign any new virus to a geographical region. This feature is becoming important, particularly in the present era of climate
change and ease of traveling, both of which increase the likelihood of introduction of newly emerging viruses into countries beyond their original geographical zone. The prime example of this phenomenon was the recent emergence of Bluetongue (BT) and Schmallenberg viruses in Europe a few years ago. Recently it was demonstrated that the 2012-CP3-Turkey isolate belong to the exotic ChinaTaiwan lineage (Ting et al. 2015).
This strongly indicates that this isolate – or its
vector/virus – was displaced from its region of origin China-Taiwan, to Turkey, most probably as a result of commercial, marine, or air transportation. Thus emphasizing the need for using adequate means for the detection of the emergence of new exotic viruses. In summary, the data described in this work resulting from a combination of a unique algorithm with HRM analysis, offer a novel, fast and accurate method for genotyping the BEFV and possibly other viruses (Joubert et al. 2014).
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Brenner, J. 2004. Detection and quantitation of Akabane and Aino viruses by multiplex real-time reverse-transcriptase PCR. J Virol Meth 116, 147-154. Tatem, A. J., Baylis, M., Mellor, P. S., Purse, B. V., Capela, R., Pena, I., Rogers, D. J. 2003. “Prediction of Bluetongue Vector Distribution in Europe and North Africa Using Satellite Imagery.” Veterinary Microbiology 97:13–29. Ting, Lu Walker, P. J., Byrne, K. A., Cybinski, D. H., Doolan, D.L., Wang, Y. H. 1991. Proteins of bovine ephemeral fever virus. J. Gen. Virol. 72 :67-74.Walker, P. Yeruham I, Braverman Y, Yadin H, Van Ham M, Chai D, Tiomkin D, Frank D.E. 2002. pidemiologicalinvestigations of outbreaks of bovine ephemeral fever in Israel. Vet Rec. 151:117-121 Yeruham, I., Braverman, Y., Yadin, H., Van Ham, M., Chai, D., Tiomkin, D., Frank, D. 2002. Epidemiological investigations of outbreaks of bovine ephemeral fever in Israel. Veterinary. Record. 151, 117-–121. Zheng, Fuying and Changqing Qiu. 2012. “Phylogenetic Relationships of the Glycoprotein Gene of Bovine Ephemeral Fever Virus Isolated from Mainland China, Taiwan, Japan, Turkey, Israel and Australia.” Virology journal 9: 268.
6.0 Legends for Tables and figures
Table 1. GC content and melt points for each sample in the 1234 reaction. GC content was calculated using the Geneious software. The melt points were measured following the amplification reaction.
Table 2. The potential HRM fragments identified by the algorithm. All the potential segments as displayed by the algorithm, sorted according to their TOPSIS score. The first and second column specify the segment by its size and starting position respectively, the third column presents the minimal difference in GC content in percentage between all geographical groups, and the fourth column is the TOPSIS score of the segment. The bold and underlined fragments were used in the HRM tests.
Fig. 1. Phylogenetic analysis of BEFV based on the complete G gene sequence. Analysis was performed by using Neighbor Joining with Tamura's 3-parameter model, with 1000 bootstrap repetitions. Acc. Numbers are next to each isolate.
Fig. 2. Genotyping of BEFV by HRM analysis applied to the 1140-1351 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as standard curve of tenfold dilutions of rRNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV, and FMDV cDNA. C. HRM analysis for two Israeli, two Australian and one Turkish isolates, performed as described in Materials and Methods.
Fig. 3. Genotyping of BEFV by HRM analysis applied to the algorithm-selected 12731360 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as standard curve of tenfold dilutions of the RNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV and FMDV. C. HRM analysis done as described in Materials and Methods.
Fig. 4. Genotyping of BEFV by HRM analysis applied at the fragment at 120-181 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as a standard curve of tenfold dilutions of the rRNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV and FMDV. C. HRM analysis done as described in Materials and Methods.
Table 1.
Isolate ISR 2004 ISR 2014 AUS 51933 BB7721 (VAC) TRK 2008 TRK 2012 JPN 88-1 JPN 3E12
% GC 41.6 41.6 50.6 50.6 46.8 46.8 45.5 45.5
Melt point 0C 76.50 76.50 79.60 79.60 79.30 79.30 78.10 78.10
Accession number JN833632 JN833634
Submitted KF679416 GQ229451 KC788421 AB462034 AB985267
Table 1. Fragment No. 1 2 3 4 5 6 7 8 9 // 460 461 462 463 464 465 466 467 468 469 470 // 1018
Window Size 97 93 93 93 93 91 91 86 85
Position 1155 1234 1227 1228 1229 1233 1232 1241 1232
Min. difference % 2 2 2 2 2 2 2 2 2
Score 0.806167295 0.794207144 0.794207144 0.794207144 0.794207144 0.788361636 0.788361636 0.774135835 0.771356593
93 93 93 93 93 93 93 93 93 93 93
1231 1232 79 1140 1141 1142 1143 1144 1145 1146 1156
1 1 1 1 1 1 1 1 1 1 1
0.092341488 0.092341488 0.09234148 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488
70
1245
1
0
S0168-1702(16)30473-7 http://dx.doi.org/doi:10.1016/j.virusres.2016.11.030 VIRUS 97019
To appear in:
Virus Research
Received date: Revised date: Accepted date:
25-7-2016 6-11-2016 24-11-2016
Please cite this article as: Erster, Oran, Stram, Rotem, Menasherow, Shopia, RubisteinGiuni, Marisol, Sharir, Binyamin, Kchinich, Evgeni, Stram, Yehuda, High-resolution melting (HRM) for genotyping Bovine Ephemeral Fever Virus (BEFV).Virus Research http://dx.doi.org/10.1016/j.virusres.2016.11.030 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
High-resolution melting (HRM) for genotyping Bovine Ephemeral Fever Virus (BEFV) Oran Erster1, Rotem Stram2, Shopia Menasherow1, Marisol Rubistein-Giuni1, Binyamin Sharir3, Evgeni Kchinich1 and Yehuda Stram1 1
Molecular Virology Unit, Virology Division, Kimron Veterinary Institute, Bet-Dagan, 50250
Israel 2
German Research Center for Artificial Intelligence, Knowledge Management Group, Berlin,
Germany 3
HaChaklait, P.O Box 3039, Caesarea, Israel.
Corresponding Author: Yehuda Stram Molecular Virology Unit, Virology Division, Kimron Veterinary Institute, Bet-Dagan, 50250 Israel Phone: +972 3 9681 697 Fax: +972 3 9681 788 E. mail: [email protected]
Highlights
Genotyping of BEFV by HRM based on the GC content of the amplified fragment. Each assay relies on the use of one pair of primers. The test is constructed using our newly developed algorithm. The test enables the designation of the origin of each isolates. This algorithm can also be applicable for genotyping of other viruses or genes.
Abstract In recent years there have been several major outbreaks of bovine ephemeral disease in the Middle East, including Israel. Such occurrences raise the need for quick identification of the viruses responsible for the outbreaks, in order to rapidly identify the entry of viruses that do not belong to the Middle-East BEFV lineage. This challenge was met by the development of a high-resolution method (HRM) assay. The assay is based on the viral G gene sequence and generation of an algorithm that calculates and evaluates the GC content of various fragments. The algorithm was designed to scan 50- to 200-base-long segments in a sliding-window manner, compare and rank them using an Order of Preference by Similarity (TOPSIS) to Ideal Solution technique for order preference by similarity to ideal solution technique, according to the differences in GC content of homologous fragments. Two fragments were selected, based on a match to the analysis criteria, in terms of size and GC content. These fragments were successfully used in the analysis to differentiate between different virus lineages, thus facilitating assignment of the viruses' geographical origins. Moreover, the assay could be used for, differentiating between field virus from vaccine strain (DIVA). The new algorithm may therefore be useful for development of improved genotyping studies for other viruses and possibly other microorganisms.
Key words: HRM analysis, Bovine ephemeral fever virus, Genotyping, GC content
1.0 Introduction Bovine ephemeral fever virus (BEFV) is a noncontagious arthropod-borne virus belonging to the genus Ephemerovirus in the family Rhabdoviridae. Similarly to other members of this family, BEFV exhibits a bullet-shaped morphology (Delte-Porta & Brown, 1979). Its genome is 14,900 bases long: a single-strand (ss) RNA in the negative polarity encoding five structural proteins – N, a nucleoprotein; P, a polymerase-associate protein; M, a matrix protein; L, a viral RNA polymerase-associate protein; and G, a surface glycoprotein – together with GNS, a non-structural glycoprotein, and four open reading frames (ORFs) – , and Walker et al., 1991, 1992; McWilliam et al., 1997; Dhillon et al., 2000; Amos-Ritchie et al., 2014; Joubert et al., 2014). BEF is an important viral disease of cattle and water buffalo in tropical, subtropical, and temperate climatic zones; it was reported in Africa, Asia including the Middle East, and Australia, but has never been documented in Europe or North and South America (Wang, et al., 2001; Kirkland, 2002; Yeruham et al., 2002, 2003; Venter et al., 2003). The cattle disease, which is also known as three-day sickness, is characterized by stiffness, acute febrile reactions, lameness, and spontaneous recovery within 3 days (Nandi & Negi, 1999; Kirkland, 2002). In spite of its short duration, the disease can cause heavy economic losses, due to decreased milk production and lowered fertility in bulls, as well as fatality in severe cases (Nandi & Negi, 1999; Yeruham et al., 2003). The virus is suspected to be transmitted by insects, and it has been isolated from a variety of insect vectors, including midges and mosquitoes (Davies & Walker, 1974). However, thus far, no insect vectors have been identified in controlled experiments. Recently, four major outbreaks occurred in Israel, the first starting in 1999 among dairycattle herds in the Jordan Valley, from where it then spread to the Mediterranean coastal plain (Yeruham et al., 2002, 2003). The second outbreak started in 2004 and was much more widespread, covering most of Israel's Mediterranean Coastal Plain; the third, in 2010, covered the interior plain, and recently, in 2014-15, disease outbreaks were also recorded in the interior valley east of Haifa (unpublished data). The High-Resolution Method (HRM) is a post-PCR analysis that enables direct characterization of DNA amplicons by producing DNA melt-curve profiles that can discriminate among nucleic acids according to sequence differences such as SNPs and small deletions. The technique enables mutation scanning, methylation, and genotyping (Garritano et al., 2009; Sarker et al. 2014; Amornpisutt et al. 2015; Naze et al. 2015; Sady et al. 2015). It is precise and accurate, and it is a nondestructive method that allows
performance of downstream post-amplification procedures, e.g., gel electrophoresis or sequencing, following melt analysis (Druml & Cichna-Markl, 2014). Melt-curve evaluation of qPCR products is usually performed to ensure primer specificity; typically it covers a temperature range of 65–95°C in 0.5°C increments. In HRM experiments, data is generally collected at narrower temperature increments than under standard melt-curve protocols, commonly 0.2 to 0.1°C. Use of a highly concentrated saturation dye, e.g., LC Green PLUS, EvaGreen, SYTO9 or ResoLight, makes it possible to saturate every single nucleotide of the double-stranded DNA by intercalating the dye so as to label the PCR product along its entire length, thereby ensuring that all melting domains are detected (Reed et al., 2007 ; Erali et al., 2008; Druml & Cichna-Markl 2014). HRM analysis software is used to identify areas of stable pre- and post-melt fluorescence intensity from the HRM curve. In light of the large number of recent BEF outbreaks in the Middle East, it was important to develop a technique that would rapidly identify origins of newly emerging viruses – for two reasons. First, to promptly determine whether a circulating virus is a local one or a new arrival, and then to determine its geographical origin. These data are obtainable because newly introduced viruses will have a greater chance to overcome the currently used vaccine than the local endemic virus. The second reason is to meet the need to distinguish between vaccine strains and field virus if the vaccine strain was not prepare from a local virus. The analysis is based on testing the melting profile of homologous fragments from different samples that contain sufficient lineage-dependent GC content for HRM analysis. In order to identify regions that meet these requirements, an algorithm was developed and employed, that aimed to find fragments that are suitable for using in the assay, based on their GC content. In this study, by taking advantage of the algorithm, two suitable fragments were selected and used to identify virus lineage.
2.0 Materials and Methods 2.1 Viruses All Israeli viruses used were obtained from infected cattle. All other isolates – from Turkey, Australia, and Japan – were obtained as RNA or cDNA extractions.
2.2 RNA extraction RNA was extracted from infected blood samples with the Viral Gene-spin kit (http://www.intronbio.com/Intro.asp) according to the manufacturer's instructions.
2.3 cDNA synthesis The Verso cDNA kit (Fisher, https://www.thermofisher.com/order/catalog/product/ AB1453A) was used for cDNA synthesis, using 500 ng of total RNA according to the manufacturer's instructions.
2.4 Cloning of reference BEFV protein G sequences and Generation of control protein G gene RNA segment The BEFV Protein G gene segment corresponding to region 750 to 1359 was amplified using the primers 5’- CTAATACGACTCACTATAGGGACCAAACAGAATCTGACT TCC-3’ (FWD control), and 5’-GATATTCCTCTATTCCCTCG-3’ (REV control). The underlined part corresponds to the T7 promoter sequence. The corresponding G gene regions from all studied isolates were cloned and sequenced. The PCR product of the control amplicon of isolate ISR2014 and the Australian vaccine were gel-purified and used as a template for synthesis of RNA control template, using the MEGAscript T7 Transcription Kit (Fisher, https://www.thermofisher.com/order/catalog/product/AM1334), according to the manufacturer’s instructions. These products were then used as reference amplicons to evaluate the efficiency and sensitivity of the RT-quantitative PCR procedure. For the HRM calibration procedure, standard DNA amplicon concentrations of each isolate were used, so that the Cq difference between all samples will not exceed 4-5 cycles.
2.5 qPCR and HRM analysis The RT-quantitative PCRs were performed with the SensiFast HRM mix (Bioline, www.bioline.com/us/ sensifast -hrm-kit.html). The reaction mix preparation was as follows: 2x SensiFast HRM mix - 5L, template – 3L, primers – 0.4M final of each, ddH2O – to a final volume of 10L. Reaction conditions for the 1140-1351 amplicon were
as follows: 95C for 0:30 min, 44x [95°C for 0:05 min, 60C for 0:30 min + Plate Read], Melt Curve: 65C to 95C, increment 0.5C,0:05 + Plate Read. Reaction conditions for the 1234-1340 amplicon were as follows: 95°C for 2:00 min, 44x [ 95°C for 0:05 min, 60°C for 0:10 min, 72.0°C for 0:15 min, Plate Read], Melt Curve: 70.0°C to 85.0°C, Increment 0.1°C for 0:01 min + Plate Read. Reaction conditions for the 79-140 amplicon were as follows: 95°C for 2:00 min, 44x [95°C for 0:05 min, 60°C for 0:15 min, 72°C for 0:15 min, Plate Read], Melt Curve: 70°C to 85°C, Increment 0.1°C for 0:01 min + Plate Read. All reactions were carried out with the CFX 96 apparatus (Bio-Rad, Hercules, CA, USA) and analyzed with the Bio-Rad CFX Manager Precision Melt Program (Bio-Rad).
2.6 Bioinformatics 2.6.1 Primer designand in silico PCR Primers for conventional and quantitative PCR were designed using Primer3 (http://bioinfo.ut.ee/primer3-0.4.0/) and were tested in silico using the Geneious package (http://www.geneious.com/) with BEFV G gene sequences.
2.6.2 GC analysis algorithm The algorithm was implemented in the Java programming language (Oracle, CA, USA). It was compiled, tested, and run on the Eclipse Luna software (Eclipse Foundation, Ottawa, Canada) under a Windows 7 environment.
2.6.3 Additional programs For sequence analysis and reaction design, two main sets of programs were used: Geneious (Biomatters, Auckland, New Zealand) and the European Molecular Biology Open Software Suite (EMBOSS). In addition, the ClustalW2 Multiple Homology Analysis tools (http://www.ebi.ac.uk/Tools/msa/clustalw2/) were used. Phylogenetic and molecular evolutionary analyses were conducted with the MEGA software, version 6.0 (Tamura et al., 2013). Design and analysis of the real-time PCR and HRM tests were performed using the Bio-Rad CFX Manager and Precision programs (http://www.bio-rad.com/en-il/sku/).
3.0 Results The G genes from isolates obtained in recent outbreaks were sequenced and subjected to phylogenetic analysis, which showed that the Israeli viruses and those from Turkey shared a common lineage, designated "Mediterranean", and which differed from the Australian and the Far-East lineages (Fig. 1). Genotyping of BEFV was performed by means of the HRM method, using the viral G gene sequence. This genotyping was based on the gene's ability to tolerate mutations without losing viability, demonstrating its ability to withstand the hostile host's immune system environment. The same properties of the G gene are also the basis for phylogenetic studies of the virus. For the assay, the following primer pair, amplifing the 1140-1292 amplicon, was first tested for sensitivity and specificity: BEFHRMf-1140 BEFHRMr-1273
5'-GAATCATTATGGGATMGGATC-3'
at
position
1140
and
5'-CCTCCTGCTGGTGCTGTTTC-3' at position 1273 of acc.
KJ729108. Sensitivity was tested with a series of tenfold dilutions of 1 ng of viral rRNA carrying the qPCR amplicon (Stram et al., 2004), a nd was able to detect 5x100–5x101 viral genomes per 1 ml (Fig. 2A). Specificity was tested by using various viral genomes as template, including Peste des Petits Ruminants (PPRV), Bovine Herpes 1 (BoH1) Bovine Viral Diarrhea Virus (BVDV) and Rabies virus, a Rhabdovrirus (Fig. 2B). All examined viruses except the BEFV control were negative; the BHV-1 sample with Ct of 37.5 gave, for all practical purposes, a negative result (Fig. 2B). To test the capability of the detection system to differentiate between viruses from different origins, the HRM analysis was applied to isolates from Israel, Turkey, East Asia, and Australia (Fig. 1C). The assay revealed distinct differences in Tm between the viruses – differences that were consistent with their various places of isolation or, in other words, with their lineages as revealed in the phylogenetic tree (Kato et al., 2009). The Israeli isolates from 2005 and 2014 had the lowest Tm, of 76.2–76.50°C, those with the next-lowest Tm, of 77.90– 78.10°C, were those from the Asia region (Japan and Taiwan). The Turkish isolates had Tm values of 79.4–79.30°C, and the Australian isolates had the highest assayed Tm, of 79.40–79.60°C. The HRM results are fully consistent with the respective GC contents of the isolates (Table 1). Moreover, these findings parallel the complete G gene phylogenetic analysis, in the sense that each of the HRM-tested isolates, except for the Turkish ones, fell into its corresponding position in the phylogenetic analysis. Surprisingly, the Turkish isolates showed similar Tm values to the Australian ones (79.4–79.6°C), in contrast to the complete gene phylogenetic analysis results, which placed the Turkish isolates in the
Mediterranean group, far from the Australian ones (Fig. 1). Supporting the HRM results is the phylogenetic analysis that was applied to the amplicon sequences; this is in agreement with that of the full G gene except for the Turkish isolate, which this analysis showed to belong with the Australian isolates. Although the reaction design described above provided partial differentiation between BEFV isolates, it did not distinguish between all the various isolates. Therefore, better regions within the G sequence, more suitable for this task, needed to be identified. To facilitate systematic identification of optimal regions within a given sequence, an algorithm was developed especially for this work; it was able to determine, compare and evaluate the differences in GC percentages among homologous sequences from various isolates (Table 1). The newly developed algorithm grouped the isolates according to their origin, and located fragments of various sizes, in the range of 50–200 bases, that displayed the widest difference in GC content between the various groups of viruses. The ranking of each of the selected fragments was calculated with the TOPSIS method (Hwang & Yoon, 1981), with 70% weighting given to diversity and 30% to fragment size (Table 2). The analysis identified two regions suitable for the assay: one located at the 5' end of the gene, between positions 100 and 200, and another between positions 1000 and 1400. Two fragments, located at each of the above mentioned regions, were selected according to their GC content, size, and the suitability of their ends to serve as primers. Each of the selected fragments contained highly conserved sequences at both ends. The first examined fragment was a 93-base sequence, 1234-1360 amplicon, located at position 1273 of the G gene. The primers BEFVHRMf-1234 5'-GAAACAGCRCCRGCAGGAGG at position 1273 and BEFVHRMr-1340 5'-TATATWGATTTTGTATGCA at position 1273, (in acc. KJ729108), as shown in Table 2, row 2, were highly homologous among isolates from all endemic regions. The reaction was sufficiently sensitive to detect between 101 and 102 viral genomes per 5L (Figure 2A). The specificity of the reaction was also established, yielding negative results with all tested viruses (Fig. 3B). The assay revealed distinct differences between the viruses – differences that were consistent with their geographic origin, or with their lineages, as shown in the virus phylogenetic tree, based on the protein G sequence. In this assay, the Israeli isolates from 2005 and 2014 exhibited the lowest Tm, of 76.2 to 76.50°C, while the next-lowest Tm, of 77.90 to 78.10°C was found among isolates from the Far-East Asia region (Japan and
Taiwan). The Turkish isolates showed Tm values of 79.40 to 79.30°C and the Australian isolates had the highest assayed Tm, of 79.40 to 79.60°C. These HRM results are fully consistent with the GC contents of the respective isolates (Fig. 3C). Moreover, these findings match the phylogenetic analysis, as each of the HRM-tested isolates fell into its corresponding position in the phylogenetic tree (Fig. 1). The second fragment (79-160 amplicon) a 81 bases-long at position 120, was also tested with BEFHRM79F-ACAACGTTTAAATGAATTG at position 79 and BEFHRM120R- 5' TGTGGTCTAC AAATCTTATT at position 181 of the gene (acc. KJ729108) primers. As with the previously described assays, both sensitivity (Fig. 4A) and specificity (Fig. 4B) were tested: the assay was able to detect 100–101 genomes per 10L reaction, and it did not react with any viral sample tested, other than BEFV (Fig. 3A, B). The HRM analysis yielded similar, but not identical results, where the Tm’s of the Israeli isolates, ISR 2005 and ISR 2014, were close to each other, ranging from 75.6 and 75.90C respectively. The Tm of the Turkish isolate, TRK 2008 was 76.10C, and the Tm’s of the Japanese JPN 88and 3E12 and the Australian Vacc Strain were 76.40C (Fig. 3C). Both experiments showed ability to differentiate between the various isolates in accordance with their origin.
The Tm values ranged from 75.6°C for isolates from Israel 2005 to 76.4°C representing isolates from Japan. The analysis demonstrated that it could discriminate between different isolates according to their place of isolation, and did so in full consistency with the phylogenetic tree (Kato et al. 2009; Zheng and Qiu 2012).
4.0 Discussion The aim of this study was to implement the HRM technique for genotyping BEFV by means of a simple and rapid assay that would be able to classify any new isolate and determine its origin. In the current era of global climate change and increased international mobility, there is always a chance that exotic viruses will be introduced into new territories, let alone an exotic BEFV that could break down existing vaccines, exposing the local herd to the disease. To address this challenge, the assay described herein was developed, and was able to distinguish between BEFV isolates from differing origins. The new algorithm developed in this study was instrumental for the success of the approach. The viral G gene was selected for the test because there are ample sequence data of this gene, and it is routinely used for phylogenetic analyses (Kato et al., 2009; Zheng & Qiu, 2012). Moreover, the virus envelop protein G glycoprotein is under constant
immunological evolutionary pressure, to constantly undergo changes, in order to adapt to an ever-changing host immune environment, making it an ideal target for genotyping. The GC content-based genotyping procedure is based on the assumption that viruses undergo a different evolutionary process in each environment, thereby creating an evolutionary signature unique to that environment, which is reflected in different virus lineages, each unique to a specific geographic location. The first fragment that was tested in the present study – a fragment at position 1140–1234 in the G gene, was selected due to the presence of conserved flanking regions. This allows the amplification of this region from isolates of multiple origins (Fig. 1). The HRM analysis that was applied demonstrated the validity of the approach. This analysis revealed that each lineage created a distinct pattern that was unique to its origin (Fig. 3). Surprisingly, when isolates from Turkey were tested using this fragment, their patterns were indistinguishable from those of the Australian isolates (Fig. 3), indicating that the Turkish and the Australian amplicon contained similar GC contents. This result is in sharp contrast to their respective positions in the phylogenetic analysis, which placed the Turkish isolates in the Middle-East lineage (Fig. 1). To evaluate this outcome, the amplicon of one of the Turkish isolates was sequenced and was found to be highly homologous to the Australian isolates (Data not shown). This result motivated the development of an algorithm that would provide a rational approach for selecting fragments suitable for the analysis. The new algorithm that was developed can calculate the GC percentages of fragments of various sizes – 50 to 200 bases in the present study – grouped according to geographical origin, and can evaluate the differences in GC contents among the groups. Once this is done, all the tested fragments are ranked by means of the TOPSIS procedure, according to the minimal GC differences between the groups, and also according to fragment size. Applying the algorithm ensured a complete coverage of the possibilities, as set by the ranking parameters, and an automated decision-making process for choosing the appropriate fragment (Table 2). In addition to choosing the allocated fragments according to mere differences in their GC contents, further factors need to be considered.
It is equally important to choose a
fragment that bears sequences suitable for primers at both ends. The ends of the fragments should display sequences that are highly conserved among all relevant viruses, as they should be able to amplify the selected fragment from all the various isolates that represent all virus lineages. Another aspect – and not the least important – is minimizing the effect of
the primers on the Tm. This is because primers that carry too many changes among the different isolates will greatly affect the analysis, and will not yield a genuine Tm value, as primers can constitute more than 50% of the entire fragment. The primers used in the present study exhibited minimal changes: the first set showed only one change in each of the two pairs (Fig. 2A, B), thereby exerting only a marginal influence on the melting profiles of the fragments. Even so, one should not disregard the possibility of future changes in these regions. The first fragment that was selected on the basis of the GC algorithm was a 93 bases long sequence, located at position 1234, with optimal size for HRM (Mao et al., 2007), revealing at least 2% difference among the various lineages (Table 2). As discussed above, the selected primers showed high homology at both ends with all tested fragments (data not shown). The results of the assay demonstrated its capacity to distinguish between the different isolates and to arrange them in accordance with their origins. The HRM results (Fig. 2) are highly consistent with the preliminary assumptions made in developing the assay. The Tm values of each group are unique to that group; for example, the Australian isolates from 1985 to 2012 have Tm values at the opposite extremes are in the range of 74.5 and 74.7°C(Israeli isolates) and 77.50–77.60°C (Australian group) Importantly, all the Tm values exhibited by each of the groups are fully consistent with the GC-content analysis, as presented in Table 1. The use of an algorithm-aided selected fragment for the HRM analysis overcame the drawback associated with the previous HRM assay, thus enabling distinction between the Turkish and the Australian isolates; each appears separate (Fig. 4). To show the strengths of the algorithm, a second fragment at a different region, starting at position 79, was chosen and tested (Fig. 4). It is clear that the developed algorithm is appropriate for the task of evaluating GC content, and also for comparing and ranking it, according to the priority set by the user. In order to further establish the strength of the algorithm, a second fragment suitable for the analysis was selected (Fig. 4), located at a separate GC variable region with a different 5' location. The HRM results resembled those of the first region in the sense that the different isolates were clearly distinguished (Fig. 3). In both assays the actual HRM curves were formed as predicted, with viruses belonging to a group sharing the lowest GC content showed low Tm values, etc., and the other groups conformed to a pattern that enabled distinction among all the diverse virus lineages. An important advantage of this assay is its ability to assign any new virus to a geographical region. This feature is becoming important, particularly in the present era of climate
change and ease of traveling, both of which increase the likelihood of introduction of newly emerging viruses into countries beyond their original geographical zone. The prime example of this phenomenon was the recent emergence of Bluetongue (BT) and Schmallenberg viruses in Europe a few years ago. Recently it was demonstrated that the 2012-CP3-Turkey isolate belong to the exotic ChinaTaiwan lineage (Ting et al. 2015).
This strongly indicates that this isolate – or its
vector/virus – was displaced from its region of origin China-Taiwan, to Turkey, most probably as a result of commercial, marine, or air transportation. Thus emphasizing the need for using adequate means for the detection of the emergence of new exotic viruses. In summary, the data described in this work resulting from a combination of a unique algorithm with HRM analysis, offer a novel, fast and accurate method for genotyping the BEFV and possibly other viruses (Joubert et al. 2014).
5.0 References Amornpisutt, R., Proungvitaya, S., Jearanaikoon, P., Limpaiboon, T. 2015. DNA methylation level of OPCML and SFRP1: A potential diagnostic biomarker of cholangiocarcinoma. Tumor Biol 49, 73–78. Conraths, F. J., Peters ,M., Beer M. 2012. “Schmallenberg Virus, a Novel Orthobunyavirus Infection in Ruminants in Europe: Potential Global Impact and Preventive Measures. NZ Vet J. 61, 63-67. Dhillon, J., Cowley, J. A, Wang, Y., Walker, P. J. 2000. RNA polymerase (L) gene and genome terminal sequences of ephemeroviruses,bovine ephemeral fever virus and Adelaide River virus indicate a close relationship to vesiculoviruses. Virus Research.2462000 70, 87-–95 Druml, B, Cichna-Markl, M. 2014. “High Resolution Melting (HRM) Analysis of DNA Its Role and Potential in Food Analysis.” Food Chemistry 158:245–54. Erali, M., Voelkerding, K. V., Wittwer, C. T. 2008. “High Resolution Melting Applications for Clinical Laboratory Medicine.” Experimental and Molecular Pathology 85, 50–58. Garigliany, M. M., Bayrou, C., Kleijnen, D., Cassart, D., Jolly, S., Linden, A., Desmecht, D. 2012. “Schmallenberg Virus: A New Shamonda/Sathuperi-like Virus on the Rise in Europe.” Antiviral Research 95, 82–87. Garritano, S., Gemignani, F., Voegele, C., Nguyen-Dumont, T., Le Calvez-Kelm, F., De Silva, D., Lesueur, F., Landi, S., Tavtigian, S. V. 2009. “Determining the Effectiveness of High Resolution Melting Analysis for SNP Genotyping and Mutation Scanning at the TP53 Locus.” BMC genetics 10:5. Hsieh, Y. C., Wang, S. Y., Lee, Y. F., Chen, S. H., Mak, P, O., Chu, C. Y. 2006. “DNA Sequence Analysis of Glycoprotein G Gene of Bovine Ephemeral Fever Virus and Development of a Double Oil Emulsion Vaccine against Bovine Ephemeral Fever.” The Journal of veterinary medical science 68, 543–48. Joubert, D. A., Blasdell, K. R., Audsley, M. D., Trinidad. L., Monaghan, P., Dave, K. A., Lieu, K. G., Amos-Ritchie ,R., Jans, DA., Moseley, G. W., Gorman, J. J., Walker P. J. 2014 . Bovine ephemeral fever rhabdovirus α1 protein has viroporin-like properties and binds importin β1 and importin 7. J Virol. 88:1591-603. Joubert,D. A., Blasdell, K. R., Audsley, M. D., Trinidad, L., Monaghan, P., Dave, K. A., Lieu, K. G., Amos-Ritchie, R., Jans, D. A., et al. 2014. “Bovine Ephemeral Fever Rhabdovirus 1 Protein Has Viroporin-Like Properties and Binds Importin 1
and Importin 7.” Journal of Virology 88, 591–1603. Kato, T., Aizawa, M., Takayoshi, K., Kokuba, T., Yanase, T., Shirafuji, H., Tsuda, T., Yamakawa, M. 2009. “Phylogenetic Relationships of the G Gene Sequence of Bovine Ephemeral Fever Virus Isolated in Japan, Taiwan and Australia.” Veterinary Microbiology 137(3-4):217–23. Kirkland, P. D., 2002. Akabane and bovine ephemeral fever virus infections. Vet. Clin. North Am. Food Anim. PractVeterinary Clinics of North America: Food Animals Practice. 18, 501-–514 Mao, F, Leung, W. Y., Xin, X. 2007. “Characterization of EvaGreen and the Implication of Its Physicochemical Properties for qPCR Applications.” BMC biotechnology 7:76. McWilliam,S. M., Kongsuwan, K., Cowley, J. A., Byrne, K. A., Walker. P. J. 1997 . Genome organization and transcription strategy in the complex GNS-L intergenic region of bovineephemeral fever rhabdovirus. J Gen Virol. 78 :1309-1317. Mehlhorn, H, Walldorf, V., Klimpel, S., Jahn, B., Jaeger, F., Eschweiler, J., Hoffmann, B., Beer, M. 2007. “First Occurrence of Culicoides ObsoletusTransmitted Bluetongue Virus Epidemic in Central Europe.” Parasitology Research 101, 219–28. Nandi, S, Negi,B.S. 1999. Bovine ephemeral fever: a review. Comparative I mmunology,266Microbiology and Infectious Diseases. 1999;22:, 81-–91 Naze, F., Desvars, A., Picardeau, M., Bourhy, P., Michault, A. 2015. “Use of a New High Resolution Melting Method for Genotyping Pathogenic Leptospira Spp.” Plos One 10(7):e0127430. Reed, G. H., J. O. Kent, and C. T. Wittwer. 2007. “High-Resolution DNA Melting Analysis for Simple and Efficient Molecular Diagnostics 1.” Pharmacogenomics 8. 6:597–608. Sady, H., Al-Mekhlafi, H. M., Ngui, R., Atroosh, W. M., Al-Delaimy, A. K., Nasr, N. A., Dawaki, S., Abdulsalam, A. M., Ithoi, I., Lim, Y. A., Chua, K. H., Surin, J. 2015. “Detection of Schistosoma Mansoni and Schistosoma Haematobium by RealTime PCR with High Resolution Melting Analysis.” International Journal of Molecular Sciences 16:16085–103. Sarker, S., Ghorashi, S. A., Forwood, J. K., Raidal, S. R. 2014. “Rapid Genotyping of Beak and Feather Disease Virus Using High-Resolution DNA Melt Curve Analysis.” Journal of Virological Methods 208:47–55. Stram. Y., Kuznetzova. L., Guini, M., Rogel, A., Meirom, R., Chai ,D., Yadin. H.,
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6.0 Legends for Tables and figures
Table 1. GC content and melt points for each sample in the 1234 reaction. GC content was calculated using the Geneious software. The melt points were measured following the amplification reaction.
Table 2. The potential HRM fragments identified by the algorithm. All the potential segments as displayed by the algorithm, sorted according to their TOPSIS score. The first and second column specify the segment by its size and starting position respectively, the third column presents the minimal difference in GC content in percentage between all geographical groups, and the fourth column is the TOPSIS score of the segment. The bold and underlined fragments were used in the HRM tests.
Fig. 1. Phylogenetic analysis of BEFV based on the complete G gene sequence. Analysis was performed by using Neighbor Joining with Tamura's 3-parameter model, with 1000 bootstrap repetitions. Acc. Numbers are next to each isolate.
Fig. 2. Genotyping of BEFV by HRM analysis applied to the 1140-1351 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as standard curve of tenfold dilutions of rRNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV, and FMDV cDNA. C. HRM analysis for two Israeli, two Australian and one Turkish isolates, performed as described in Materials and Methods.
Fig. 3. Genotyping of BEFV by HRM analysis applied to the algorithm-selected 12731360 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as standard curve of tenfold dilutions of the RNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV and FMDV. C. HRM analysis done as described in Materials and Methods.
Fig. 4. Genotyping of BEFV by HRM analysis applied at the fragment at 120-181 amplicon of the viral G gene. A. Sensitivity analysis of the reaction presented as a standard curve of tenfold dilutions of the rRNA carrying the HRM amplicon. B. Specificity of the reaction as tested with Rabies virus, BHV-1, PPRV and FMDV. C. HRM analysis done as described in Materials and Methods.
Table 1.
Isolate ISR 2004 ISR 2014 AUS 51933 BB7721 (VAC) TRK 2008 TRK 2012 JPN 88-1 JPN 3E12
% GC 41.6 41.6 50.6 50.6 46.8 46.8 45.5 45.5
Melt point 0C 76.50 76.50 79.60 79.60 79.30 79.30 78.10 78.10
Accession number JN833632 JN833634
Submitted KF679416 GQ229451 KC788421 AB462034 AB985267
Table 1. Fragment No. 1 2 3 4 5 6 7 8 9 // 460 461 462 463 464 465 466 467 468 469 470 // 1018
Window Size 97 93 93 93 93 91 91 86 85
Position 1155 1234 1227 1228 1229 1233 1232 1241 1232
Min. difference % 2 2 2 2 2 2 2 2 2
Score 0.806167295 0.794207144 0.794207144 0.794207144 0.794207144 0.788361636 0.788361636 0.774135835 0.771356593
93 93 93 93 93 93 93 93 93 93 93
1231 1232 79 1140 1141 1142 1143 1144 1145 1146 1156
1 1 1 1 1 1 1 1 1 1 1
0.092341488 0.092341488 0.09234148 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488 0.092341488
70
1245
1
0