Evolutionary Rate of E2 Genes of Classical Swine Fever Virus in China

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Evolutionary Rate of E2 Genes of Classical Swine Fever Virus in China
Zhang, H.,* Cao, H.W., Wu, Z.J. and Cui, Y.D.
College of Biological Science and Technology, HeiLongJiang BaYi Agricultural University, DaQing 163319, China
* Corresponding author: Zhang H.: Tel: (086) 0459-6819290; Fax: (086) 0459-6819290; E-mail: huazi8541@sina.com
AB ST RAC T
Classical swine fever (CSF) is caused by classical swine fever virus (CSFV), a member of the genus Pestivirus of the family Flaviviridae, and engender important economic ramifications. Our previous study reported that both CSFV Group 1 and Group 2 were both contributed to the epidemic of CSF in mainland China, and showed the trend of switch from Group 1 to Group 2. In order to investigate the relationship between epidemiological trend and evolutionary rate of two Groups, the E2 glycoprotein gene (located in 25082697) of 68 CSFVs isolated from mainland China during 1982-2009 were aligned, and Bayesian Markov Chain Monte Carlo (MCMC) analysis was performed. The results indicated that the mean evolutionary rate of Group 2 (3.6861×10-3 substitutions per site per year (subs/site/year)) evolved much faster than Group 1 (4.9852×10-4 subs/site/year). We presumed that the differences in evolutionary rates of two groups likely implied that Group 2 possessed higher mutation rate and experienced higher selection pressure, however the real mechanism for the diversity in the evolutionary rate requires further investigation. Key words: classical swine fever virus, envelope glycoprotein E2, evolutionary rate, MCMC, selection pressure
INTRODUCTION
Classical swine fever (CSF, alias hog cholera) is a serious infectious disease of pigs, which is notifiable to the World Organization for Animal Health (OIE) and to the European Union (EU) (1). CSF is a devastating disease that poses one of the greatest risks to the swine industry and cause great economic loss in China, with continuing sporadic outbreaks in several different provinces of the mainland (2). Classical swine fever virus (CSFV), bovine viral diarrhea virus type I and type II (BVDV-I and BVDV-II) and border disease virus (BDV) belong to the Pestivirus genus of the Flaviviridae family (3). CSFV is a small (40-60 nm in diameter) enveloped positive-stranded RNA virus and contains a genome about 12.3 kb. CSFV genomes have a large open reading frame (ORF) flanked by highly conserved 5’ non-translational region (5’-NTR) and 3’-NTR, and ORF codes for a unique polyprotein of about 3898 amino acids (Npro-C-Erns-E1-E2-p7-NS2-NS3-NS4A-NS4B-NS5AIsrael Journal of Veterinary Medicine  Vol. 66 (4)  December 2011
NS5B) (4). The polyprotein gives rise to autoprotease (Npro), four structural proteins (C, Erns, E1 and E2), and seven nonstructural proteins (p7, NS2, NS3, NS4A, NS4B, NS5A and NS5B) upon processing by cellular and viral proteases (5). E2 gene, together with NS5B and 5’-NTR were used for evolutionary analysis and resulted in the same resolution (Fig 1) (2, 6, 7). Envelope protein E2 is the major envelope glycoprotein exposed on the outer surface of the virion and represents an important target for induction of the immune response during infection (8). There are four antigenic domains in the N-terminal half of E2, (A, B, C and D), with three subdomains (A1, A2 and A3) in domain A. Domains B and C as well as subdomain A1 are neutralizing but only subdomain A1 is conserved (9). The 190 nt in this variable region of N-terminal is extensively used for evolutionary analysis (7, 10). Despite intense immunization and even eradication efClassical Swine Fever in China
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NS N 5’
pro
struct. proteins C E
ms
nonstr. proteins (NS) NS2-3 NS4A NS4B NS5A NS5B 3’
E1
E2 p7
421 nt 150 nt 5’ non translated region
671 nt 190 nt E2 major glycoprotein gene
449 nt 409 nt NS5B polymerase gene
Fig 1. The CSFV genome structure and three variable regions (E2, NS5B and 5’NTR) could be used for evolutionary analysis. (Tajen from Paton et al., 2000, Vet. Microbiol. 137-157).
forts, the total number of outbreaks reported by Chinese veterinary laboratories has increased during the last twenty years (11, 12). Phylogenetic analysis indicates that CSFV could be classified into three Groups (Group 1, 2 and 3) (13). Our previous study reported that the Chinese traditional isolates mainly fall into groups one or two: Group 1 comprises mainly the modified live vaccines and many highly virulent strains and group 2 mainly recent and moderately virulent isolates. Both CSFV Group 1 and Group 2 have contributed to the epidemic of CSF in mainland China, with a trend of switch from Group 1 to Group 2 (2). The epidemiology of CSFV is important and there is a need to investigate its epidemiological status and the relationship between epidemiological trend and evolutionary rate of two groups. In particular the evolutionary rate between two genotypes of CSFV remains elusive. Thus an understanding the evolutionary rate of the glycoprotein E2 of CSFV could possibily provide clues for the epidemiological characterization, as well as reveal the possible evolutionary strategies that different genotypes of CSFVs have adopted.
website (http://www.ncbi.nlm.nih.gov/), EMBL website (http://www.ebi.ac.uk/embl/) and EU reference laboratory for CSFV database in Hannover (http://viro08.tiho-hannover.de/eg/csf/startCSF.cgi), respectively. All CSFV isolate datasets are listed in Table 1.
Estimation of evolutionary rate
MATERIALS AND METHODS
Virus sequences
The 190 nt of E2 sequences (located in 2518-2707) of 68 representative CSFV isolates were retrieved form GeneBank
Evolutionary rate of E2 genes of classical swine fever virus were represented with nucleic acid substitution rates and were analyzed independently. The E2 gene sequences of CSFV isolates from China were compiled and aligned using Clustal X software (version 1.83) (14), and then the best-fitting model of nucleotide substitution for each dataset was determined using jModeltest (version 3.7) (15). Firstly, the best-fitting models were determined as HasegawaKishino-Yano (HKY) model for Group 1 and the General Time Reversible with Gamma (GTR+G) model for Group 2, respectively (Table 2). Secondly, the variable-rate relaxed molecular clock models were determined best-fitting to Group 1 and Group 2. Thirdly, Bayesian Markov Chain Monte Carlo approach (MCMC, the BEAST package, version 1.5.1) (16) was used to estimate the viral substation rates. The final calculated results were viewed by Tracer software (in Tracer 1.4, http://beast.bio.ed.ac.uk/Tracer). Mean values are expressed as well as 95% high probability density intervals (HPD).
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Table 1. The CSFVs Group 1 and Group 2 Accession No. EF421652 EF421651 EF421639 EF421649 DQ127910 EF421653 EF421654 EF421665 EF421664 EF421646 EF421648 EF421663 EF421660 EF421661 EF421659 EF421658 FJ157213 EF421656 EF421979 EF421645 EF421644 EF421642 EF421666 EF421700 FJ456870 FJ456871 FJ456867 FJ456868 EF683627 FJ607780 FJ977628 EF421655 EF421688 EF683612
Years Subgroup Accession No. 1982 1.1 EF421690 1998 1.1 EF421691 1996 1.1 EF421692 2001 1.1 EF421693 2004 1.1 EF421667 2006 1.1 EF421669 2006 1.1 AF143088 1998 1.1 EF421676 1999 1.1 EF421678 2002 1.1 EF421681 1995 1.1 EF421694 1998 1.1 EF421695 2002 1.1 EF683635 2002 1.1 EF683620 1998 1.1 EF421696 1998 1.1 EF421698 2006 1.1 EF421699 2006 1.1 EF369431 1998 1.1 EF369444 2006 1.1 EF369429 1999 1.1 EF369439 1995 1.1 FJ157210 1999 1.1 FJ157211 1999 2.1 EF421682 2004 2.1 EF421685 2005 2.1 EF014334 2006 2.1 EF421708 2007 2.1 EF421709 2007 2.1 AF143082 2008 2.1 AF143083 2009 2.1 EF421710 2002 2.1 EF421980 2002 2.1 EF421707 2007 2.1 EF421983
Years Subgroup 2000 2.1 1999 2.1 2005 2.1 1997 2.1 2000 2.1 2001 2.1 1998 2.1 2002 2.1 1998 2.1 1999 2.1 1998 2.1 1999 2.1 2005 2.1 2007 2.1 1998 2.1 1999 2.1 2000 2.1 2004 2.1 2004 2.1 2005 2.1 2006 2.1 2006 2.1 2006 2.1 1996 2.1 1999 2.1 2002 2.2 1995 2.2 1997 2.2 1997 2.2 1998 2.2 1984 2.2 1998 2.2 1999 2.2 1986 2.3
Table 2. The best-fitting substitution model of CSFV Group 1 and 2 Group 1 Model HKY 383.9895 383.4146 383.4476 383.451 380.4132 379.8645 380.0103 379.5507 -lnL 863.9791 864.8293 864.8952 866.902 864.8263 865.729 866.0207 867.1013 AIC 5.9245 6.7747 6.8407 8.8474 6.7718 7.6744 7.9661 9.0468 Delta 0.0122 0.0080 0.0077 0.0028 0.0080 0.0051 0.0044 0.0026 0.0 0.0 0.0 0.0
Weight cumWeight 0.9609 0.9768 0.9846 0.9969 0.9689 0.9896 0.994 0.9994 1.0 1.0 1.0 1.0 1.0 1.0
HKY+G HKY+I+G GTR GTR+I
HKY+I
2
GTR+G GTR+I+G HKY HKY+I
HKY+G 1055.7944 2297.5889 35.3691 HKY+I+G 1055.946 2299.8921 37.6722 GTR GTR+I
1068.6414 2321.2827 59.0629 1055.319 2296.638 34.4182
GTR+G 1036.9003 2267.8006 GTR+I+G 1037.6774 2271.3549
1052.2368 2296.4736 34.2538 0.0 1039.948 2273.896 11.6762 0.0020 5.5808 9.1351 0.0429 0.0072
0.9566 0.998
The less AIC value reflects the more fitting substitution model. HasegawaKishino-Yano (HKY) model and the General Time Reversible with Gamma (GTR+G) model were determined as the best-fitting substitution model of CSFV of Group 1 and 2 (highlighted with bold), respectively. -lnL: negative log likelihood; AIC: akaike information criterion; delta: AIC difference; weight: AIC weight; cumWeight: cumulative AIC weight.
Sixty eight CSFV isolates (23 Group 1 isolates and 45 Group isolates) from the mainland China were used for evolutionary rate analysis.
RESULTS AND DISCUSSION
The respective evolutionary rate of Group 1 and Group 2 are shown in Table 3, and mean nucleotide substitution rate with 95% HPD are displayed in Fig 2. Our previous study reported that both CSFV Group 1 and Group 2 were both contributed to the epidemic of CSF in mainland China (2). However, it is noteworthy that Group 2 of CSFV’s, with a evolutionary rate of 3.6861×10-3 subs/site/
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year (95% HPD 2.0816×10-3-5.5134×10-3), was approximately seven times that of Group 1 with a mean substitution rate of 4.9852×10-4 subs/site/year (95% HPD 3.1189×10-51.1018×10-3). Compared with Group 2, 95% HPD values span for Group 1 dataset was larger than Group 2, which was probably caused by the comparatively fewer sequences (23 isolates in Group 1). CSFV Group 2 evolved much faster than Group 1, which indicated that Group 2 would be predominant in whole CSFV isolates and acquire superiority in the evolutionary process against the host immune pressure and environmental selection pressure. This was in accordance with our previous report that Group 2 evolved for a much farther distance than Group 1. The higher substitution rates in Group 2 may imply the trend of switch from Group 1 to 2, which was directly supported by our phylogenetic analysis and previous reports (2), and could further explain why Group 2 viruses more extensively in many provinces of China.
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Frequency
200 150 100 50
-5E-4
Frequency
300 200 100 0
0
0
5E-4
Fig 2. Mean substitution rate with 95% HPD (highest probability density) in Group 1 (left) and Group 2 (right). Table 3. Rates of CSFV nucleotide substitution in Group 1 and Group 2 Nucleotide substation rate CSFV Mean 95% HPD Group sequences substitution rate (highest probability density) 1 23 4.9852×10-4 3.1189×10-5-1.1018×10-3 -3 2 45 3.6861×10 2.0816×10-3-5.5134×10-3
meanRate
1E-3
1.5E-3
2E-3
2.5E-3
0
1E-3
2E-3 3E-3
meanRate
4E-3
5E-3
6E-3
7E-3 8E-3
9E-3
In brief, our work may be helpful to better understand the elevated evolutionary rates of CSFVs, however, the real mechanism behind the diversity in the evolutionary rate needs further investigation.
ACKNOWLEDGEMENT
The study was supported by the Technology Research Foundation of Education Department of HeiLongJiang Province, China. Fund No. (12511352).
During the evolutionary process of CSFV, many factors would affect viral phylogeny including the immunological status of animals, the presence of wild reservoirs, inefficient vaccination campaigns as well as socio-economic factors (17). When the host immune defense change the viral population had to compete with the immune system adapting to keep track with the viral changes (18). Pigs have been vaccinated with the attenuated lapinized vaccine in China since mid1950s. The vaccine strains of CSFV was classified into group 1 of highly virulent fatal strains and Group 2 consisting of moderately virulent isolates were responsible for the rising incidence of subacute and chronic CSF outhe breaks (19). On the basis of the evidences, we presume that resistance against the host immune pressure would cause Group 2 to optimize its evolutionary strategy. An increased evolutionary rate under the constant selection pressure would be is beneficial for the virus to escape the host immune response (20).
REFERENCES
1. Camargos, M.F., Pereda, A., Stancek, D., Rocha, M.A., dos Reis, J.K.P., Greiser-Wilke, I. and Leite, R.C.: Molecular characterization of the env gene from Brazilian field isolates of Bovine Leukemia Virus. Virus Genes 34: 343-350, 2007. 2. Zhang, H., Wang, Y.H., Cao, H.W. and Cui, Y.D.: Phylogenetic analysis of E2 genes of classical swine fever virus in China. Isr J Vet Med 65: 151-155, 2010. 3. Fan, Y.F., Zhao, Q., Zhao, Y., Wang, Q., Ning, Y.B. and Zhang, Z.Q.: Complete genome sequence of attenuated low-temperature Thiverval strain of classical swine fever virus. Virus Genes 36: 531-538, 2008. 4. Singh, V.K., Saikumar, G., Bandyopadhyay, S.K. and Paliwal, O.P.: Phylogenetic analysis of classical swine fever virus (CSFV) by cloning and sequencing of partial 5 ' non-translated genomic region. Indian Journal of Animal Sciences 74: 1093-1097, 2004. 5. Blacksell, S.D., Khounsy, S., Boyle, D.B., Greiser-Wilke, I., Gleeson, L.J., Westbury, H.A. and Mackenzie, J.S.: Phylogenetic analIsrael Journal of Veterinary Medicine  Vol. 66 (4)  December 2011
164
Zhang
Research Articles
6. 7.
8.
9.
10.
11.
12.
ysis of the E2 gene of classical swine fever viruses from Lao PDR. Virus Research 104: 87-92, 2004. Tu, C.C., Lu, Z.J., Li, H.W., Yu, X.L., Liu, X.T., Li, Y.H., Zhang, H.Y. and Yin, Z.: Phylogenetic comparison of classical swine fever virus in China. Virus. Res. 81: 29-37, 2001. Paton, D.J., McGoldrick, A., Greiser-Wilke, I., Parchariyanon, S., Song, J.Y., Liou, P.P., Stadejek, T., Lowings, J.P., Bjorklund, H. and Belak, S.: Genetic typing of classical swine fever virus. Vet. Micr. 73: 137-157, 2000. Montesino, R., Toledo, J.R., Sanchez, B., Zamora, Y., Barrera, M., Royle, L., Rudd, P.M., Dwek, R.A., Harvey, D.J. and Cremata, J.A.: N-Glycosylation Pattern of E2 Glycoprotein from Classical Swine Fever Virus. Journal of Proteome Research 8: 546555, 2009. Qi, Y., Liu, L.C., Zhang, B.Q., Shen, Z., Wang, J. and Chen, Y.H.: Characterization of antibody responses against a neutralizing epitope on the glycoprotein E2 of classical swine fever virus. Archives of Virology 153: 1593-1598, 2008. Chen, N., Hu, H.X., Zhang, Z.F., Shuai, J.B., Jiang, L.L. and Fang, W.H.: Genetic diversity of the envelope glycoprotein E2 of classical swine fever virus: Recent isolates branched away from historical and vaccine strains. Vet. Micr. 127: 286-299, 2008. Liu, L.H., Xia, H.Y., Belak, S. and Widen, F.: Development of a primer-probe energy transfer real-time PCR assay for improved detection of classical swine fever virus. Journal of Virological Methods 160: 69-73, 2009. Huang, Y.L., Pang, V.F., Pan, C.H., Chen, T.H., Jong, M.H.,
13. 14.
15. 16. 17. 18. 19. 20.
Huang, T.S. and Jeng, C.R.: Development of a reverse transcription multiplex real-time PCR for the detection and genotyping of classical swine fever virus. Journal of Virological Methods 160: 111-118, 2009. Paton, D.J. and Greiser-Wilke, I.: Classical swine fever - an update. Research in Veterinary Science 75: 169-178, 2003. Thompson, J.D., Gibson, T.J., Plewniak, F., Jeanmougin, F. and Higgins, D.G.: The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res 25: 4876-82, 1997. Posada, D. and Crandall, K.A.: Modeltest: testing the model of DNA substitution. Bioinformatics 14: 817-818, 1998. Drummond, A.J. and Rambaut, A.: BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7: 214, 2007. Duffy, S., Shackelton, L.A. and Holmes, E.C.: Rates of evolutionary change in viruses: patterns and determinants. Nature Reviews Genetics 9: 267-276, 2008. Moennig, V., Floegel-Niesmann, G. and Greiser-Wilke, I.: Clinical signs and epidemiology of classical swine fever: A review of new knowledge. Vet. J. 165: 11-20, 2003. He, C.Q., Ding, N.Z., Chen, J.G. and Li, Y.L.: Evidence of natural recombination in classical swine fever virus. Virus Research 126: 179-185, 2007. Wonnemann, H., Floegel-Niesmann, G., Moennig, V. and Greiser-Wilke, I.: Genetic typing of classical swine fever virus isolates from Germany. Dtsch. Tierarztl. Wochenschr. 108: 252256, 2001.
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