Institute of Virology, University of Veterinary Medicine, Veterinärplatz 1, A-1210 Vienna, Austria
Correspondence
Dieter Klein
dieter.klein{at}vu-wien.ac.at
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ABSTRACT |
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Sequences reported in this study are deposited under the GenBank accession numbers: AF531031 AF531076 and AY196330 AY196343.
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MAIN TEXT |
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As the success of a vaccine could be hampered by the occurrence of highly divergent virus variants, the genetic diversity of FIV field strains circulating in all regions where vaccination is planned should be determined (Pistello et al., 1997). This knowledge should also allow the adaptation of vaccines to regionally prevalent subtypes, if development of a global FIV vaccine should be impossible.
The extensive genetic variation observed in FIV also has a direct impact on PCR-based methods which are increasingly used for diagnosis and monitoring of FIV infection (Leutenegger et al., 1999; Hosie et al., 2002
). Furthermore, PCR assays to distinguish vaccinated from infected cats will gain importance with the advent of the first commercially available FIV vaccine (Uhl et al., 2002
). In general, these methods are highly influenced by variations in the target sequences, which usually increase with genetic distance (Klein et al., 1999
, 2001
).
To gain insight into the genetic diversity of FIV in Central Europe, we sampled EDTA-blood from 30 FIV-positivedomestic cats derived from Austria, Germany, Switzerland and Italy. FIV infection was initially determined by PCR and in 27 of 30 cases additionally by ELISA (Table 1). Partial proviral gag and env genes were amplified with primers FIV-1026F (5'-GGC ATA TCC TAT TCA AAC AG-3') and FIV-1700R (5'-AAG AGT TGC ATT TTA TAT CC-3') (Cammarota et al., 1996
) for gag, and FIV-7316F (5'-ATA CCA AAA TGT GGA TGG TG-3') and FIV-7868R (5'-TGC AAG ACC AAT TTC CAG CA-3') for env (sequences kindly provided by M. Pistello, University of Pisa, Italy). The env sequences of samples DEBAd59 and ATNOd16 were amplified by nested PCR using FIV-7224F (5'-GTA CAG ACC CAT TAC AAA TC-3') and FIV-8000R (5'-CTG CCA CTG GGT TAT ACC AA-3') as outer and FIV-7316F/FIV-7868R as inner primers. After purification, the amplicons were directly sequenced on both strands, using PCR primers. In the case of strain DEFRd68, repeated PCR and sequencing experiments did not result in a clean sequence. Therefore, the PCR product was cloned into a commercial vector (TA Cloning kit; Invitrogen) and six positive clones were sequenced. The clonal sequences varied by a P-value of 01·3 % sequence diversity (for comparison, the sequence closest to these clones differed from them by 4·95·7 % sequence diversity). Finally, a consensus sequence for DEFRd68 was derived which was used for phylogenetic analysis.
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To estimate the phylogenetic signal contained in the gag and env alignments, likelihood mapping (Strimmer & von Haeseler, 1997) was performed using TREE-PUZZLE (Strimmer & von Haeseler, 1996
). With this method, the percentage of completely resolved quartet trees from a representative fraction of all possible quartets in a data set can be taken as a measure for the phylogenetic signal contained in an alignment. As a result, both alignments appeared to be highly informative, revealing 87·0 % in env and 86·6 % in gag of all analysed quartets being completely resolved.
As none of the most commonly used models for phylogenetic inference is principally superior to the others (Graur & Li, 2000), distance (Saitou & Nei, 1987
), parsimony (Fitch, 1977
) and maximum-likelihood (Felsenstein, 1981
; Strimmer & von Haeseler 1996
) analyses were performed for phylogenetic tree construction. To determine the substitution models that would best fit our data sets for maximum-likelihood and neighbour-joining analyses, a likelihood ratio test (Swofford et al., 1996
) was performed using PAUP* (version 4.0b10; Swofford, 2002
). In the gag alignment, the TamuraNei model (Tamura & Nei, 1993
) with gamma-distributed rates (TN93+
) resulted in a likelihood estimate not significantly worse than the general time reversible model with estimated gamma-distribution and proportion of invariant sites (GTR+
+I), which is the most complicated model implicated in the program. In contrast, the likelihood ratio test favoured a submodel of the GTR+
+I model in env with three different substitution rates: one for both possible transitions, one for three of the four possible transversions and one for A
C changes. Consequently, the TN93+
model was used to construct quartet puzzling trees (Strimmer & von Haeseler, 1996
) as well as neighbour-joining trees (Saitou & Nei, 1987
) based on the gag alignment, whereas the same tree-building algorithms were used, assuming the special GTR+
+I model for the env alignment. Parsimony analyses were performed on both data sets using the heuristic search algorithm. All described tree constructions were performed using PAUP*, and MEGA 2.1 (Kumar et al., 2001
) was used to calculate neighbour-joining trees.
The tree topologies resulting from the different calculations were highly similar within each data set. Representative maximum-likelihood trees (Fig. 1) and neighbour-joining trees (Fig. 2
) are shown. Upon comparison, trees derived from the different proviral regions investigated showed highly concordant topologies (Figs 1 and 2
). All Central European sequences reported in this paper grouped into either subtype A or B of FIV. Within clade B, several subclades were consistently observed among both data sets. According to the origin of the virus strains, we termed these subclades B-main, Austria-1, Austria-2, Austria-3 and Portugal. A single Austrian strain (ATVId23) did not fall into either of these subgroups and might represent a prototype of another subclade of subtype B, as is suggested by the long branch that separates it from the other strains. Only two Austrian strains (ATESb20 and ATESd03) cluster with B-main. Interestingly, both of them were isolated from cats which, according to the owners, were born in Spain but were taken to Austria later in their life (Table 1
). The close proximity of these strains is especially intriguing, based on the fact that the samples were collected at different time points in distinct parts of Austria. Moreover, they displayed reasonable diversity from all other Austrian sequences, as they grouped with cluster B-main. Therefore, we consider it very likely that both cats had actually been infected in Spain. Unfortunately, there are no Spanish FIV-sequences available, and thus comparison with Spanish strains was not possible. Both Italian strains reported here (ITROd76 and ITROd78) were grouped together extremely closely as well, but in this case close epidemiological linkage is very likely as both samples are derived from a population of feral cats in Rome. The occurrence of subtype B strains of FIV in Germany has been suggested by heteroduplex mobility analysis (Bachmann et al., 1997
). Accordingly, two German strains (DEBWa06 and DEBEd72) fell into this subtype. All other German FIV strains belonged to subtype A, together with both Swiss sequences and a single Austrian strain. Formation of a highly supported subclade (Germany-1) consisting of two German strains was observed in subtype A. In gag but not in env, the single Austrian clade A strain ATVId02 also grouped to this cluster.
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Moreover, a separation of clade B from clades C and D was not supported in neighbour-joining analyses of the env data (Fig. 2b). To test whether inter-subtype recombination could be the reason for this observation as well as for the discordant grouping of DEBEd72 and Maryland strains, gag and env sequences were concatenated, and bootscanning (Salminen et al., 1995
) was performed using SIMPLOT (Lole et al., 1999
). USIL2489_7B, Petaluma, BM3070 and Shizuoka served as reference sequences for the four subtypes included. However, no significant signs of recombination were observed among our data. In the absence of recombination and significant differences in phylogenetic content, the observed discrepancies might be due to the different evolutionary constraints effective on the gag and env genes, respectively (Pistello et al., 1997
; Rigby et al., 1993
). In the presented data sets, roughly 90 % of substitutions occurring in gag were estimated to be synonymous in comparison to about 50 % synonymous substitutions in env. Synonymous substitutions are generally believed to better display the true evolutionary history, as they are theoretically not influenced by selective pressure (Graur & Li, 2000
). The positive selection pressure on env might account for the observed differences in our data. However, a detailed description of FIV phylogeny and recombination frequency would necessitate the analysis of full-length genomes by analogy to the HIV-1 nomenclature proposal (Robertson et al., 1999
).
This work provides the first evidence that FIV of subtype B is predominant and highly divergent in Austria. Each of the described Austrian clusters within clade B consists of strains derived from different provinces of Austria (Table 1). Moreover, strains from the same provinces group into different subclades. Therefore these clusters represent real subclades rather than artefacts based on a common origin of the cats. Only a single subtype A strain was detected in Austria. In contrast, subtype A seems to occur more frequently in Germany. Our findings are in accordance with work by other groups, who found clade A and less frequently, clade B strains in Germany (Bachmann et al., 1997
) and a high prevalence of clade B FIV in Italy (Pistello et al., 1997
). However, more detailed screening studies would be necessary to precisely determine the prevalence of the occurring subtypes in Austria and Germany. The success of a vaccine might be largely dependent on the type and variety of circulating strains, which can differ substantially from region to region. In the light of the first commercial FIV-vaccine, it is even more important to consider the existing variety beforehand to prevent vaccination failure. Likewise, as new PCR-based diagnostic tools gain importance in the fields of diagnostics and research, knowledge about the genetic diversity and the compilation of new sequence data provide a valuable tool for the design of sensitive assays.
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ACKNOWLEDGEMENTS |
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Received 29 July 2002;
accepted 23 December 2002.
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