Genetic diversity and molecular epidemiology of respiratory syncytial virus over four consecutive seasons in South Africa: identification of new subgroup A and B genotypes

Marietjie Venter1, Shabir A. Madhi2, Caroline T. Tiemessen1 and Barry D. Schoub1

National Institute for Virology, Private bag X4, 2131 Sandringham, South Africa1
Pediatric Infectious Disease Research Unit, University of the Witwatersrand, South Africa2

Author for correspondence: Marietjie Venter. Fax +27 11 3214212. e-mail Mariav{at}NIV.ac.za


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The molecular epidemiology of respiratory syncytial virus (RSV) was studied over four consecutive seasons (1997–2000) in a single tertiary hospital in South Africa: 225 isolates were subgrouped by RT–PCR and the resulting products sequenced. Subgroup A predominated in two seasons, while A and B co-circulated approximately equally in the other seasons. The nucleotide sequences of the C-terminal of the G-protein were compared to sequences representative of previously defined RSV genotypes. South African subgroup A and subgroup B isolates clustered into four and five genotypes respectively. One new subgroup A and three new subgroup B genotypes were identified. Different genotypes co-circulated in every season. Different circulation patterns were identified for group A and B isolates. Subgroup A revealed more variability and displacement of genotypes while subgroup B remained more consistent.


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Respiratory syncytial virus (RSV) is a major cause of acute lower respiratory tract infections (ALRTI) in infants and young children in both developed and developing countries (Selwyn, 1990 ). Two major antigenic groups, subgroups A and B, have been identified (Mufson et al., 1988 ; Anderson et al., 1985 ). The existence of distinct lineages within the subgroups has been demonstrated at both antigenic and nucleotide levels (reviewed by Cane & Pringle, 1995b ; reviewed by Sullender, 2000 ). The G-protein is the most divergent both between and within the two subgroups (Johnson et al., 1987 ) and appears to accumulate amino acid changes with time, suggesting evolution under selective pressure (Cane & Pringle, 1995a ). G-protein variability is concentrated in the ectodomain, which consists of two hypervariable regions separated by a conserved 13 amino acid motif (Cane et al., 1991 ; Sullender et al., 1991 ). The second variable region, which makes up the C-terminal region of the G-protein, has been reported to provide a reliable proxy for the entire G-gene variability (Peret et al., 1998 ) and has subsequently been used in phylogenetic analysis for molecular epidemiological studies and to assign isolates from North America to genotypes (Peret et al., 1998 , 2000 ).

Most studies on RSV G-protein variability have been based on subgroup A isolates (Cane et al., 1991 , 1999 ; Garcia et al., 1994 ; Cane & Pringle, 1995a ; Cane, 1997 ), with little information available on subgroup B isolates (Sullender et al., 1990 , 1991 ; Coggins et al., 1998 ; Martinez et al., 1999 ), and few studies on both subgroups (Coggins et al., 1998 ; Peret et al., 1998 , 2000 ; Choi & Lee, 2000 ). Our knowledge of the molecular epidemiology of RSV has so far been based mainly on studies done in the developed world with few reports from Africa (Cane et al., 1999 ; Roca et al., 2001 ). No data are available about the molecular epidemiology over consecutive seasons from sub-Saharan Africa, which has one of the severest HIV/AIDS epidemics in the world (Lepage et al., 1998 ).

In this report we examine the molecular epidemiology and evolutionary pattern of RSV over four consecutive epidemics among children in a tertiary academic hospital serving Soweto in South Africa. We report on the co-circulation pattern and genetic variability of both subgroup A and B isolates, and compare the relatedness of RSV isolates from South Africa with genotypes identified thus far from North America as well as RSV sequences from the rest of the world available on the GenBank.

RSV-positive nasal pharyngeal aspirates (NPA) from children (0–60 months), hospitalized for ALRTI at Chris Hani-Baragwanath hospital (Soweto, South Africa), were stored at -80 °C over four consecutive years (1997–2000). A total of 225 specimens out of 1187 RSV-positive isolates (18·9%) were selected systematically from every month RSV was isolated (January–November, 1997–2000) for subtyping: 44 from 1997 (42%); 69 from 1998 (22%); 55 from 1999 (15%) and 57 from 2000 (14%). RNA was isolated from NPA as described before (Madhi et al., 2001 ) and subgrouped by RT–PCR (Madhi et al., 2001 ; Sullender et al., 1993 ) followed by an additional nesting step to improve DNA yields for sequencing. Of the 225 isolates, 144 belonged to subgroup A and 81 to subgroup B. During 1997 subgroup A and B co-circulated approximately equally, while subgroup A predominated during 1999 (74%) and 2000 (89%). Subgroup A has been reported to predominate in three out of four seasons in other geographical areas (Hall et al., 1990 ). Although subgroup A was clearly dominant in two of the seasons we studied, subgroup B played at least an equally significant role in the other two seasons, suggesting an important role for both subgroups in South African epidemics.

The nucleotide sequence of 270 nucleotides at the C terminus of the G protein gene was determined for 65 subgroup A and 38 subgroup B isolates, spanning each of the four RSV seasons, using fluorescent dye-terminators on an ABI 377 sequencer (Perkin-Elmer Applied Biosystems). This corresponds to nucleotides 649–918 of prototype strain A2 (subgroup A) and nucleotides 652–921 of prototype strain 18537 (subgroup B) G-protein genes (Johnson et al., 1987 ). Unique sequences were selected from each year (45 subgroup A and 35 subgroup B isolates) for phylogenetic analysis (Fig. 1). Subgroups were genotyped separately by phylogenetic comparisons with sequences previously assigned to specific genotypes (Peret et al., 1998 , 2000 ) and by comparison to various other sequences from around the world (Fig. 1). Authenticity of new genotypes was tested by performing Blast searches with representatives of each cluster formed by South African sequences and including the closest related sequences identified in GenBank in the phylogenetic analysis. Sequences were arbitrarily considered a genotype if they clustered together with bootstrap values of 70–100%. After analysis of our data we further refined these criteria to isolates with a pairwise-distance (p-distance) of less than 0·07 to all other members in the same phylogenetic cluster. One sequence of each of two subgroup A and the two subgroup B clusters of sequences identified in Mozambique in 1999 were also included in the analysis (Roca et al., 2001 ), since Mozambique is the closest geographical region to our study site where sequencing data are available.



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Fig. 1. Maximum parsimony (MP) trees of South African RSV subgroup A and B nucleotide sequences. The phylograms were the best trees under the Kishino–Hasegawa test and were drawn with PAUP version 4.0b4a (D. L. Swofford). The trees were midpoint rooted using minimum F-value optimization and drawn to scale with the bar indicating one change. Bootstrap probabilities obtained from a 50% majority rule consensus tree are shown at the branch nodes. Only values of>70 are indicated. For bootstrap evaluation under MP assumption, sequences were added randomly and one tree was held at each step (100 replicates and 100 bootstrap replicates), applying the tree bisection–reconnection branch-swapping algorithm. Where relevant, the number of identical isolates from one year is indicated in brackets. South African isolates (1997–2000) are indicated by SA97–SA00. Reference sequences for each genotype assigned by Peret et al. (1998 , 2000 ) (GA1–GA7) and (GB1–4) were obtained from GenBank: from the USA (NY, New York; Al, Alabama; MO, Missouri; Tx, Texas; CN, Canada) (Peret et al., 2000 ); CH (Rochester, New York) (Peret et al., 1998 ). Additional sequences from around the world were included in the comparison by selecting representatives of distinct clusters found in previous studies and selecting isolates from GenBank that gave the best hits in Blast searches with each of the South African clusters: WV (West Virginia) (Sullender et al., 1991 ); Birmingham, UK (RSB) (Cane et al., 1994 ); Montevideo, Uruguay (MON) (Garcia et al., 1994 ; Martinez et al., 1999 ); Madrid, Spain (MAD) (Garcia et al., 1994 ; Martinez et al., 1999 ); Seoul, Korea (Sel) (Choi & Lee, 2000 ); Mozambique (MOZ) (Roca et al., 2001 ). Prototype strains for subgroup A: strain A2 (Australia) (Wertz et al., 1985 ); subgroup B: Swed8-60 (Sweden) (Sullender et al., 1991 ); USA (18537) (Johnson et al., 1987 ); B1 (Karron et al., 1997 ). The genotype assignment is indicated at the right by brackets. Phylogenetic analyses were also carried out by MP and distance methods of Phylip version 3.5c (Felsenstein, 1993 ), Minimum evolution [MEGA version 2 (Kumar et al., 2001 )] and quartet maximum likelihood reconstruction (Tree Puzzle version 4.0; Strimmer & von Haeseler, 1996 )) (data not shown).

 
South African subgroup A isolates clustered into four groups with bootstrap values of 70–100% (Fig. 1A). Three of these grouped with previously assigned genotypes, GA5, GA7 and GA2. South African GA2 isolates grouped separately to other GA2 sequences, and clustered with isolate WV12342 (Sullender et al., 1998 ). Isolate SA98V173 and isolate Moz/9/99 from Mozambique grouped separately to all GA2 sequences. The fourth group was distinct from any of the previously identified genotypes, and was therefore named SAA1 (South Africa A1). The Mozambique isolates clustered with GA2 and GA5. The p-distances determined between and within the genotypes are shown in Table 1(A). The average intergenotypic p-distances between the South African subgroup A isolates ranged from 0·076 (SAA1 and GA7) and 0·098 (GA2 and GA5); p-distances between individual sequences within each genotype ranged from 0·001 to 0·059. The closest related sequence in GenBank to the SAA1 sequences was isolate Sel91242 from Korea (1993) (Choi & Lee, 2000 ), which has p-values ranging between 0·026 and 0·059 with SAA1 isolates; however, significant bootstrap statistics could not be obtained when it was included in the phylogenetic analysis.


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Table 1. Average genetic p-distances between and within subgroup A and B genotypes

 
South African subgroup B isolates clustered into five groups (Fig. 1B), two of these with previously identified genotypes GB3 and GB4. However, as predicted by Peret et al. (2000) we found that the current classification scheme would have to be expanded to accommodate all the South African isolates. One group of sequences clearly grouped with the previously assigned genotype GB4. However, although some South African isolates clustered with the GB3 reference sequences, these could not be supported by significant bootstrap statistics. GB3 isolates formed various subgenotypes with intergenotypic p-distances of up to 0·058, which may give rise to separate genotypes in future studies. The remaining three South African clusters were distinct from the previously assigned genotypes and were named SAB1, SAB2 and SAB3. Mozambiquen isolates grouped with GB3 and SAB2. The average intergenotypic p-distances between South African subgroup B isolates ranged from 0·046 (GB3 and SAB3) to 0·132 (GB4 and SAB2) (Table 1B). The SAB2 sequences (SA99V800 and SA99V1325) grouped with isolate MOZ198/99 (Mozambique 1999) (Roca et al., 2001 ) and Sel93366 (Korea 1993) but not with any of the genotypes identified by Peret et al. (2000) . SAB3 was most closely related to GB3 with p-distances ranging from 0·021 to 0·062 between individual sequences, but did not cluster with significant bootstrap values to any of the GB3 sequences. In GenBank, the sequence most closely related to the SAB3 isolates was Mad11-92 from Madrid (Martinez et al., 1999 ), which has p-distances of 0·021 to 0·03 with SAB3; however, it clustered separately to the SAB3 isolates when included in the phylogenetic analysis. SAB2 has an average intergenotypic p-distance of 0·069 with SAB3. Distances between individual sequences in these groups of up to 0·145 and insignificant bootstrap statistics placed them in different genotypes. No sequences could be identified in GenBank that clustered with the SAB1 isolates.

These results suggest that SAA1, SAB1, SAB3 and SAB2 are new genotypes of which the three former have so far been identified only in South Africa. South African RSV isolates also clustered with three previously assigned subgroup A and two subgroup B genotypes, confirming the notion that RSV variants can spread worldwide, but also that RSV evolution is dynamic, with new variants appearing in individual communities (Garcia et al., 1994 ; Cane & Pringle, 1992 ). Comparison of the Mozambiquen isolates to South African isolates also suggests transfer between communities, as all genotypes identified in Mozambique occurred in the same year in South Africa although at low frequencies. Neither prototype strain A2 nor B1, currently used for the production of experimental vaccines, clustered with any of the South African isolates. The reference sequences (Peret et al., 1998 , 2000 ) were useful for assigning the South African isolates to genotypes; however, we suggest that a standardized method for genotyping of RSV would allow more effective comparison of viruses circulating worldwide.

Sequence divergence was higher at the amino acid level than at nucleotide level, confirming previous findings (Sullender et al., 1991 ; Cane & Pringle, 1995a ; Martinez et al., 1999 ). The predicted amino acid sequences of isolates in the different genotypes were compared to prototype strains A2 and B1 for subgroup A and B, respectively (Fig. 2). Genotype-specific amino acid substitutions could be identified, a phenomenon previously described (Peret et al., 1998 ). The G-protein of South African isolates (relative to prototype strains A2 and B1) consisted of 297 (SAA1) or 298 (GA7) amino acids, or both (GA2 and GA5), for subgroup A, and 295 (GB4, SAB1 and SAB2) or 292, 295 and 299 (GB3 and SAB3) amino acids for subgroup B. Subgroup A isolates used the UAG stop codon in either nucleotide position 259 or 262. Subgroup B isolates used either the UAA or the UAG stop codons in positions 241, 250 or 262. Changes in stop codon usage are thought to be associated with antigenic variation in RSV escape mutants that recognize strain-specific epitopes (Melero et al., 1997 ). The mean proportion of nucleotide substitutions that resulted in amino acid changes among South African isolates was 70·8 and 67% for subgroups A and B, respectively, suggesting positive selection, possibly due to immunological pressure. Collectively, this suggests immune evasion by RSV that could be accomplished through epitope changes. Although the significance of this for the development of effective vaccines remains to be determined, it may be necessary to use more recently isolated strains from different areas for vaccine production.



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Fig. 2. Amino acid alignment of the second variable region of the G-protein for subgroup A (A) and subgroup B (B) South African isolates and reference sequences of the different genotypes. Alignments are shown relative to prototype sequences A2 and B1, respectively.

 
Different genotypes co-circulated each year, with certain genotypes becoming dominant and then declining before being replaced with a different dominant genotype. Some genotypes were found throughout the 4 years of study (GA5, GB3 and SAB3), while others were only found at a low frequency in some seasons (GA7, SAB1 and SAB2). Different circulation patterns were identified for subgroup A and B genotypes. More diversity was found among subgroup A isolates during the 4 year study period than in subgroup B, supporting findings by Choi & Lee (2000) . Subgroup A showed a gradual build-up and then replacement of dominant genotypes, e.g. GA5 (1997) was replaced by SAA1 (1998), which was then replaced by GA2 (1999). GA2 predominated for more than one season, increasing from 42% (1999) to 78% (2000). Subgroup B was more consistent, and two subgroup B genotypes (GB3 and SAB3) remained co-dominant throughout all 4 years, constituting 78% of subgroup B isolates over the study period. It has been suggested that this higher variability may be advantageous to subgroup A and could contribute to its higher worldwide predominance (Hall et al., 1990 ; Coggins et al., 1998 ). Previous studies on subgroup A isolates have reported that a new genotype becomes dominant each year (Peret et al., 2000 ; Cane et al., 1994 ). Although this was true for the first 3 years of our study, the same genotype, GA2, remained dominant during the last 2 years (1999 and 2000). This suggests that successful variants may be able to persist and remain dominant for more than one season. Most other studies had only limited data about subgroup B strains making it difficult to identify epidemiological patterns among subgroup B isolates.

In summary, we have reported the first molecular epidemiological study of RSV over consecutive seasons in Southern Africa and identified four new genotypes. The high percentages of nucleotide changes that resulted in amino acid changes suggest a strong selective pressure in both RSV subgroups. Evidence of different circulation patterns between subgroup A and B viruses over consecutive seasons was found. Subgroup A revealed more variability and displacement of genotypes while subgroup B remained more consistent. These findings provide additional information regarding RSV evolution and strain circulation worldwide and may contribute to future vaccine development.


   Acknowledgments
 
The study was supported by a grant from the Poliomyelitis Research Foundation, South Africa. We thank Amelia Buys, Michelle Morgan and Areeva Oliver at the National Institute for Virology and Archana Manchaat from the South African Institute for Medical Research for respiratory virus diagnosis, and Drs Karen Petersen and Anas Madhi for assisting in sample collection.


   Footnotes
 
The GenBank accession numbers of the sequences reported in this paper are AF348802AF348826.


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Received 2 March 2001; accepted 17 May 2001.