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. 2007 Oct 10;131(2):121–131. doi: 10.1016/j.virusres.2007.08.014

Positive natural selection in the evolution of human metapneumovirus attachment glycoprotein

Abinash Padhi 1,⁎, Bindhu Verghese 1
PMCID: PMC7114232  PMID: 17931731

Abstract

Human metapneumovirus (hMPV), a newly discovered virus of the family Paramyxoviridae, has been associated with upper and lower respiratory tract infections in different age groups in many countries. The putative attachment (G) glycoprotein of this virus was previously reported to have shown more extensive nucleotide and deduced amino acid sequence polymorphism than any other genomic regions of this virus, leading to four sub-lineages. Using a maximum likelihood-based codon substitution model of sequence evolution, here we report that sequences of extracellular domain of 8 amino acid sites in lineage 1a, and 3 amino acid sites each in lineage 1b, 2a, and 2b have a higher rate of nonsynonymous substitutions (dN) than the synonymous substitutions (dS) with a posterior probability above 0.95, thus suggesting the evidence of adaptive evolution driven by Darwinian selection. Although it is unclear whether these amino acid adaptations are driven by differential immune pressure or some other factors, identification of these positively selected amino acid sites would help in better screening using epitope mapping technology to identify and localize the sites that can be recognized by the immune system. We also observed surprisingly higher nucleotide substitution rates per site, per year for each lineage of hMPV than the rates that were previously reported for the human respiratory syncytial virus, suggesting rapid evolutionary dynamics of hMPV.

Keywords: Human metapneumovirus, Attachment glycoprotein, Phylogeny, Adaptive evolution, Substitution rate, Evolutionary dynamics

Human metapneumovirus (hMPV) of the family Paramyxoviridae and subfamily Pneumoviridae was first discovered in The Netherlands from infants and children suffering from acute respiratory tract disease (van den Hoogen et al., 2001). Since then considerable progress has been made in identification and characterization (Cote et al., 2003, Mackay et al., 2003, Ebihara et al., 2004, Maertzdorf et al., 2004, Skiadopoulos et al., 2004, Hamelin and Boivin, 2005, Leung et al., 2005, Gray et al., 2006a, Gray et al., 2006b, Ulbrand et al., 2006, van den Hoogen, 2007) as well as in understanding its genetic diversity (Bastien et al., 2003, Bastien et al., 2004, Biacchesi et al., 2003, Ishiguro et al., 2004, Peret et al., 2004, Carr et al., 2005, Ludewick et al., 2005, Galiano et al., 2006, Boivin et al., 2007). To date this virus has been identified in many countries from different age groups and reported to cause upper respiratory tract infections, flu-like infections, and has also been associated with lower respiratory tract infections (van den Hoogen et al., 2001, Stockton et al., 2002, Biacchesi et al., 2003, Bastien et al., 2003, Bastien et al., 2004, Ishiguro et al., 2004, Peret et al., 2004, Carr et al., 2005, Ludewick et al., 2005, Fouchier et al., 2005, Regev et al., 2006, Galiano et al., 2006, Kahn, 2006, Gray et al., 2006a, Gray et al., 2006b), a pattern similar to that reported for human respiratory syncytial virus (HRSV). Although comparative genome mapping analyses suggested that this virus has structural and functional similarities with HRSV (Kahn, 2006), recent studies reported that the attachment (G) glycoprotein of these paramimyxoviruses exhibit extensive nucleotide and amino acid variation, with most differences located in the extracellular domain (Peret et al., 2004, Kahn, 2006). Therefore, G-protein has been widely used to infer evolutionary relationships among the isolates from different geographic regions (e.g., Peret et al., 2004, Ishiguro et al., 2004). Although phylogenetic analyses of hMPVs from the complete nucleotide coding sequences revealed the existence of two major lineages of hMPVs (Ishiguro et al., 2004), recent analyses based on G-protein phylogeny revealed the existence of two minor sub-groups within each major lineage (Peret et al., 2004). Despite the knowledge of identification and characterization of hMPVs, the possible mechanism by which hMPV G-proteins have evolved is poorly understood.

Earlier studies on the molecular evolution of HRSV G-protein reported that certain amino acid sites that correspond to sites of O-glycosylation, or amino acid sites that were previously described as monoclonal antibody-induced in vitro escape mutants, are under positive selection and thus showed strong association between these positively selected sites and the mapped neutralizing epitopes (Zlateva et al., 2004). Recently, Zhang et al. (2006) also reported that certain amino acid sites in severe acute respiratory syndrome (SARS) coronavirus (CoV) are evolved by positive Darwinian selection. These lines of evidence suggest an interesting evolutionary pattern of the respiratory viruses. At the genomic level, whether a gene, or a particular amino acid within a gene, is under relaxed selection or remains functionally constrained throughout evolution can be detected by comparing the rate of nonsynonymous nucleotide substitutions per nonsynonymous site (dN) with that of synonymous substitutions per synonymous site (dS) (Hughes and Nei, 1989). If dN/dS (hereafter referred as ω) is greater than one, then positive selection is said to be operating. Alternatively, if ω  < 1, the gene is under strong purifying selection and presumed to be functionally constrained.

Identifying genes that have evolved by adaptation is central to understanding molecular evolution. However, not all amino acid differences observed among the closely related sequences from ecologically/geographically isolated strains are adaptive (e.g., Zlateva et al., 2004). Therefore, analyzing patterns of amino acid substitutions would provide insight into understanding protein adaptation by identifying candidate codon sites on which positive selection has been operating. Identifying the positively selected amino acid sites would also help in further immunization studies. Maximum likelihood (ML)-based codon substitution models, which account for variable ω ratios among codon sites and detect codon sites that are subjected to positive selection (Yang et al., 2000), have been widely used in detecting positive selection in a number of respiratory viral groups (e.g., Zlateva et al., 2004, Zhang et al., 2006). Here we used Yang et al's (2000) ML codon substitution models to test whether there was evidence at the nucleotide sequence level that a subset of amino acid sites in G-protein of hMPV sequences that represent each subgroup has been under positive selection. In addition, we used a Bayesian MCMC approach implemented in BEAST version 1.4.4 (Drummond and Rambaut, 2006) that utilize the number and temporal distribution of genetic differences among viruses sampled at different times (Drummond et al., 2002, Drummond et al., 2006) to estimate the evolutionary change for each lineage.

A total of 144 published unique nucleotide coding sequences of G-protein representing four sub-lineages (1a = 46, 1b = 40, 2a = 38, 2b = 20) were retrieved from GenBank (Table 1 ). Sequences were aligned using Mesquite version 1.2 (Maddison and Maddison, 2006), DAMBE version 4.5.2 (Xia, 2000, Xia and Xie, 2001), and BioEdit version 7.0.5.3 (Hall, 1999) software packages. To infer phylogenetic relationship among these strains of hMPVs, we reconstructed a neighbor joining tree from their predicted amino acid sequence data with p-distance implemented in MEGA version 3.1 (Kumar et al., 2004). Using the same program, nodal supports were estimated with 10,000 nonparametric bootstrap replicates. For selection analyses, we reconstructed unrooted ML trees for each lineage from their respective nucleotide sequence data using the appropriate nucleotide substitution model identified by the hierarchical likelihood ratio test implemented in Modeltest version 3.5 (Posada and Crandall, 1998). PHYML version 2.4.4 (Guindon and Gascuel, 2003) was used to conduct ML analyses.

Table 1.

GenBank accession number, strain name, country of origin, and the year of isolation of 144 unique hMPV G-protein sequences used in the study

GenBank No. Strain name Country of origin Year of Isolation Source Group
AF371337 00-1 The Netherlands   van den Hoogen et al. (2001) 1a
AY296015 FL/4/01 The Netherlands 2001 van den Hoogen et al. (2001) 1a
AY296016 FL/3/01 The Netherlands 2001 van den Hoogen et al. (2001) 1a
AY296017 FL/8/01 The Netherlands 2001 van den Hoogen et al. (2001) 1a
AY296018 FL/10/01 The Netherlands 2001 van den Hoogen et al. (2001) 1a
AY296019 NL/10/01 The Netherlands 2001 van den Hoogen et al. (2001) 1a
AY296020 NL/2/02 The Netherlands 2002 van den Hoogen et al. (2001) 1a
AY327802 201-7182 Australia GenBank 1a
AY327803 201-4199 Australia – GenBank 1a
AY327804 Q01-6410 Australia – GenBank 1a
AY327805 Q01-7262 Australia – GenBank 1a
AY327806 Q01-6346 Australia – GenBank 1a
AY327807 Q01-7292 Australia – GenBank 1a
AY327808 Q01-7252A Australia – GenBank 1a
AY327809 Q01-7292 Australia – GenBank 1a
AY327810 Q016297 Australia – GenBank 1a
AY485232 hMPV13-2000 Canada 2000 Peret et al. (2004) 1a
AY485235 hMP V193-2002 Canada 2002 Peret et al. (2004) 1a
AY485236 hMPV22-2001 Canada 2001 Peret et al. (2004) 1a
AY485238 hMPV23-2001 Canada 2001 Peret et al. (2004) 1a
AY485251 hMPV81-1999 Canada 1999 Peret et al. (2004) 1a
AY485254 hMPV86316-2002 Canada 2002 Peret et al. (2004) 1a
AY485255 hMPV88448-2002 Canada 2002 Peret et al. (2004) 1a
AY485256 hMPV88470-2002 Canada 2002 Peret et al. (2004) 1a
AY530092 JPS03-180 Japan 2003 Ishiguro et al. (2004) 1a
AY574225 CAN34-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574226 CAN40-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574228 CAN97-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574231 CAN187-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574237 CAN216-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574243 CAN464-02 Canada 2002 Ishiguro et al. (2004) 1a
AY574244 CAN532-02 Canada 2002 Ishiguro et al. (2004) 1a
AY848881 RSA/39/01 South Africa 2001 Ludewick et al. (2005) 1a
AY848882 RSA/1/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848885 RSA/4/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848887 RSA/17/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848889 RSA/31/01 South Africa 2001 Ludewick et al. (2005) 1a
AY848890 RSA/33/01 South Africa 2001 Ludewick et al. (2005) 1a
AY848893 RSA/8/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848896 RSA/3/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848897 RSA/10/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848901 RSA/14/02 South Africa 2002 Ludewick et al. (2005) 1a
AY848903 RSA/34/01 South Africa 2001 Ludewick et al. (2005) 1a
DQ312444 IA3-2002 USA 2002 Gray et al., 2006a, Gray et al., 2006b 1a
DQ362949 Arg/1/03 Argentina 2003 Galiano et al. (2006) 1a
DQ362950 Arg/2/02 Argentina 2002 Galiano et al. (2006) 1a
AY296021 NL/17/00 The Netherlands 2000 van den Hoogen et al. (2004) 1b
AY296022 NL/1/81 The Netherlands 1981 van den Hoogen et al. (2004) 1b
AY296023 NL/1/93 The Netherlands 1993 van den Hoogen et al. (2004) 1b
AY296025 NL/3/93 The Netherlands 1993 van den Hoogen et al. (2004) 1b
AY296026 NL/1/95 The Netherlands 1995 van den Hoogen et al. (2004) 1b
AY296028 NL/13/96 The Netherlands 1996 van den Hoogen et al. (2004) 1b
AY296029 NL/22/01 The Netherlands 2001 van den Hoogen et al. (2004) 1b
AY296030 NL/24/01 The Netherlands 2001 van den Hoogen et al. (2004) 1b
AY296032 NL/29/01 The Netherlands 2001 van den Hoogen et al. (2004) 1b
AY296033 NL/302 The Netherlands 2002 van den Hoogen et al. (2004) 1b
AY485234 hMPV17-2000 Canada 2000 Peret et al. (2004) 1b
AY485250 hMPV80-1999 Canada 1999 Peret et al. (2004) 1b
AY530090 JPS03-176 Japan 2003 Ishiguro et al. (2004) 1b
AY530091 JPS03-178 Japan 2003 Ishiguro et al. (2004) 1b
AY530093 JPS03-187 Japan 2003 Ishiguro et al. (2004) 1b
AY530095 JPS03-240 Japan 2003 Ishiguro et al. (2004) 1b
AY574227 CAN58-02 Canada 2002 Bastien et al. (2004) 1b
AY574229 CAN164-02 Canada 2002 Bastien et al. (2004) 1b
AY574230 CAN182-02 Canada 2002 Bastien et al. (2004) 1b
AY574234 CAN197-02 Canada 2002 Bastien et al. (2004) 1b
AY574235 CAN208-02 Canada 2002 Bastien et al. (2004) 1b
AY574236 CAN215-02 Canada 2002 Bastien et al. (2004) 1b
AY574241 CAN348-02 Canada 2002 Bastien et al. (2004) 1b
AY848910 RSA/27/00 South Africa 2000 Ludewick et al. (2005) 1b
AY848911 RSA/7/00 South Africa 2000 Ludewick et al. (2005) 1b
AY848912 RSA/26/00 South Africa 2000 Ludewick et al. (2005) 1b
AY848914 RSA/7/01 South Africa 2000 Ludewick et al. (2005) 1b
AY848915 RSA/20/00 South Africa 2000 Ludewick et al. (2005) 1b
AY848916 RS A/20/01 South Africa 2001 Ludewick et al. (2005) 1b
AY848917 RSA/49/00 South Africa 2000 Ludewick et al. (2005) 1b
AY848919 RSA/44/00 South Africa 2000 Ludewick et al. (2005) 1b
DQ270215 BJ1819 China 2000 GenBank 1b
DQ312449 IA-8-2003 USA 2003 Gray et al. (2006a) 1b
DQ270217 BJ1824 China – GenBank 1b
DQ312458 IA-17-2003 USA 2003 Gray et al. (2006a) 1b
DQ312462 IA21-2004 USA 2004 Gray et al. (2006a) 1b
DQ312463 IA22-2004 USA 2004 Gray et al. (2006a) 1b
DQ312464 IA23-2004 USA 2004 Gray et al. (2006a) 1b
DQ362952 Arg/3/00 Argentina 2000 Galiano et al. (2006) 1b
NC_004148 CAN97-83 Canada 1997 Biacchesi et al. (2003) 1b
AY296040 NL/1/94 The Netherlands 1994 van den Hoogen et al. (2004) 2a
AY296041 NL/1/82 The Netherlands 1982 van den Hoogen et al. (2004) 2a
AY296042 NL/1/96 The Netherlands 1996 van den Hoogen et al. (2004) 2a
AY296044 NL/9/00 The Netherlands 2000 van den Hoogen et al. (2004) 2a
AY296045 NL/3/01 The Netherlands 2001 van den Hoogen et al. (2004) 2a
AY296046 NL/4/01 The Netherlands 2001 van den Hoogen et al. (2004) 2a
AY296047 UK/5/01 UK 2001 van den Hoogen et al. (2004) 2a
AY297748 CAN98-75 Canada 1998 Biacchesi et al. (2003) 2a
AY485243 hMPV73-1998 Canada 1998 Peret et al. (2004) 2a
AY485244 hMPV74-1998 Canada 1998 Peret et al. (2004) 2a
AY485245 hMPV75-1998 Canada 1998 Peret et al. (2004) 2a
AY485246 hMPV76-1998 Canada 1998 Peret et al. (2004) 2a
AY485247 hMPV77-1998 Canada 1998 Peret et al. (2004) 2a
AY485248 hMPV78-1998 Canada 1998 Peret et al. (2004) 2a
AY485249 hMPV79-1998 Canada 1998 Peret et al. (2004) 2a
DQ270219 BJ1921 China – GenBank 2a
DQ270220 BJ2034 China – GenBank 2a
DQ270221 BJ4879 China – GenBank 2a
DQ270222 BJ4944 China – GenBank 2a
DQ270223 BJ5128 China – GenBank 2a
DQ270224 BJ5129 China – GenBank 2a
DQ312443 IA2-2002 USA 2002 Gray et al. (2006a) 2a
DQ312457 IA16-2003 USA 2003 Gray et al. (2006a) 2a
DQ312460 IA19-2003 USA 2003 Gray et al. (2006a) 2a
DQ393715 Peru1-2002 USA 2002 Gray et al. (2006b) 2a
DQ843658 BJ1816 China – GenBank 2a
AY848861 RSA/4/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848862 RSA/71/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848864 RSA/37/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848865 RSA/16/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848866 RSA/12/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848868 RSA/29/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848869 RSA/58/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848875 RSA/54/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848878 RSA/23/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848879 RSA/90/00 South Africa 2000 Ludewick et al. (2005) 2a
AY848880 RSA/93/00 South Africa 2000 Ludewick et al. (2005) 2a
DQ312453 IA12-2003 USA 2003 Gray et al. (2006a) 2a
AY296034 NL/1/99 The Netherlands 1999 van den Hoogen et al. (2004) 2b
AY296035 NL/11/00 The Netherlands 2000 van den Hoogen et al. (2004) 2b
AY296036 NL/12/00 The Netherlands 2000 van den Hoogen et al. (2004) 2b
AY296037 NL/5/01 The Netherlands 2001 van den Hoogen et al. (2004) 2b
AY296038 NL/9/01 The Netherlands 2001 van den Hoogen et al. (2004) 2b
AY296039 NL/21/01 The Netherlands 2001 van den Hoogen et al. (2004) 2b
AY485242 hMPV33-2001 Canada 2001 Peret et al. (2004) 2b
AY485252 hMPV82-1997 Canada 1997 Peret et al. (2004) 2b
AY530089 JPS02-76 Japan 2002 Ishiguro et al. (2004) 2b
DQ312445 IA4-2002 USA 2002 Gray et al. (2006a) 2b
DQ312446 IA5-2002 USA 2002 Gray et al. (2006a) 2b
DQ312448 IA7-2003 USA 2003 Gray et al. (2006a) 2b
DQ312454 IA13-2003 USA 2003 Gray et al. (2006a) 2b
DQ312455 IA14-2003 USA 2003 Gray et al. (2006a) 2b
DQ312461 IA20-2003 USA 2003 Gray et al. (2006a) 2b
DQ393716 Peru2-2002 Peru 2002 Gray et al. (2006b) 2b
DQ393717 Peru3-2003 Peru 2003 Gray et al. (2006b) 2b
DQ393718 Peru4-2003 Peru 2003 Gray et al. (2006b) 2b
DQ393719 Peru5-2003 Peru 2003 Gray et al. (2006b) 2b
AY530094 JPS03-194 Japan  2003 Ishiguro et al. (2004)  2b
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Overall substitution rate (nucleotide substitutions per site per year) of each lineage was estimated using the Bayesian skyline model, with both relaxed (variable) molecular clock (with uncorrelated lognormal model) and strict clock implemented in the BEAST version 1.4.4 (Drummond and Rambaut, 2006). This model employs a Bayesian MCMC approach and utilize the number and temporal distribution of genetic differences among viruses sampled at different times (Drummond et al., 2002, Drummond et al., 2006). Bayesian skyline plots with 10 grouped intervals were reconstructed to infer demographic history (Drummond et al., 2005). Phylogenies were evaluated using a chain length of 30 million states under the HKY85 + Γ4 substitution model and with uncertainty in the data reflected in the 95% high-probability density (HPD) intervals. Convergence of trees was checked using Tracer version 1.3 (Rambaut and Drummond, 2006).

To determine the synonymous and nonsynonymous sequence divergence distribution pattern across the entire coding region of each lineage (Fig. 1 ), we used a sliding window approach (window size = 6, step = 1) implemented in DNAsp version 4.0 (Rozas et al., 2003).

Fig. 1.

Fig. 1

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NJ tree inferred from 144 amino acid sequences of human metapneumovirus G glycoprotein representing four lineages. Nodal support is mentioned at the base of the node. The sliding window analyses of respective lineages show the synonymous and nonsynonymous divergence.

To assess whether positive selection is operating in any codon sites, we used the alignment and ML trees of respective lineages as input for the CODEML program of PAML version 3.15 (Yang, 1997). The PAML program incorporates six different codon substitution models that account for variable ω for each codon site. The six codon substitution models are: M0 (one-ratio), M1a (nearly neutral), M2a (positive selection), M7 (β distribution; 0 ≤  ω  ≤ 1), M8 (β  +  ω  > 1: continuous) (Yang et al., 2000), and M8a (β  +  ω  = 1) (Swanson et al., 2003). The M0 model estimates overall ω for the data. The M1a model estimates a single parameter, p 0, with ω 0  = 0, and the remaining sites with frequency p 1 (p 1  = 1 −  p 0) assuming ω 1  = 1. The M2a model adds a class of positively selected sites with frequency p 2 (where p 2  = 1 −  p 1  −  p 0) with ω 2 estimated from the data. In the M7 model, ω follows a beta distribution and is allowed to vary between 0 and 1, and two parameters (p and q) of the beta distribution are estimated from the data. In the M8 model, a proportion, p 0 , of sites have ω drawn from the beta distribution and the remaining sites with proportion p 1 are positively selected (ω 1  > 1). The LRTs between nested models were conducted by comparing twice the difference in log-likelihood values (2lnΔl) against a χ 2-distribution with degrees of freedom equal to the difference in the number of parameters between models (Yang, 1997). Three LRTs were conducted. The first comparison was made between M1a, which allows for two site classes (0 <  ω  < 1, ω  = 1), and M2a, which allows three site classes (0 <  ω  < 1, ω  = 1 or ω  > 1). The second comparison was between M7 and M8, and the last comparison was between M8 and M8a, in which ω for M8a was constrained to 1. In all LRTs good evidence for positive selection is found if the LRT indicates that models that allow for selection (i.e. M2a and M8; alternative models) are significantly better than their respective null models (M1a, M7 and M8a) (Yang, 1997). Posterior probabilities of the inferred positively selected sites were estimated by the Bayes empirical Bayes (BEB) approach that takes sampling errors into account (Yang et al., 2005).

Consistent with earlier studies (Peret et al., 2004), G-protein based phylogeny in the present study has also revealed the existence of multiple lineages of this virus (Fig. 1). All four lineages showed some degree of spatial structure; however, few strains in each lineage did not show any spatial structure, indicating extensive viral gene flow across the regions in a given epidemic season. Relatively weak temporal structure across the regions further suggested that either certain strains can remain stable for more than one epidemic season (e.g., HRSV, Zlateva et al., 2004, Zlateva et al., 2005), or mutations might not have occurred in a linear fashion with the preservation of changes in the circulating viral strains. Thus, virus genotypes would frequently appear and disappear along with new mutations in the populations. However, HRSV (Zlateva et al., 2004, Zlateva et al., 2005) showed a strong correlation between the accumulation of genetic divergence and the isolation date of the sequences. Based on the relaxed clock assumption, the evolutionary rate of each major lineage of hMPVs (1 and 2; Table 2 ) are 5.18 × 10−3 and 6.49 × 10−3  substitutions/site/year, respectively. Although these rates are compatible with the substitution rates reported for influenza viruses (Chen and Holmes, 2006), these rates are higher than the estimates of HRSV (HRSV A: 1.83 × 10−3, Zlateva et al., 2004; HRSV B: 1.95 × 10−3, Zlateva et al., 2005; HRSV-BA: 3 × 10−3  substitutions/site/year, Trento et al., 2006; HRSV-A: 2.6 × 10−3, HRSV-B: 3.5 × 10−3, Matheson et al., 2006) and other paramyxoviruses (e.g., measles: Woelk et al., 2002). These discrepancies in the evolutionary rates could be associated with the differential selective pressures targeting different genomic regions. For example, the presence of a greater number of adaptively evolved amino acid sites in the gene can cause an accelerated rate of evolution. As a consequence, the overall evolutionary rate is expected to be higher (Trento et al., 2006). Both major lineages of hMPVs showed interesting population dynamics (Fig. 2 ). The times to the most recent common ancestor for lineage 1 and 2 are 49.452 (29.08–70.8) and 26.091 (21–36.651) years, respectively. While the population size of lineage 1 recently declined, the lineage 2 population size did not show any declining trend. This contrast in the population size could be associated with fitness of the virus.

Table 2.

Mean nucleotide substitution rates (95% HPD interval in parenthesis) in hMPV G-gene estimated using Bayesian MCMC approach, with both relaxed and strict clock

Lineage Relaxed clock
 Strict clock
Substitution rate (×10−3 substitutions/site/year) Likelihood score Substitution rate (×10−3 substitutions/site/year) Likelihood score
1a 4.58 (2.400–7.048) −2250.481 4.152 (2.235–6.196) −2256.156
1b 5.344 (3.995–6.898) −2946.824 4.817 (3.809–5.889) −2975.021
2a 6.139 (4.318–7.825) −2530.280 5.275 (3.733–6.798) −2556.508
2b 7.865 (4.060–11.63) −1840.066 3.795 (2.687–7.625) −1868.507
1(a + b) 5.182 (3.761–6.781) −4689.161 4.621 (3.639–5.647) −4702.717
2(a + b) 6.494 (4.599–8.438) −3783.320 4.770 (3.555–6.012) −3833.563
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Estimates with relaxed clock are better fit to the data.

Fig. 2.

Fig. 2

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Skyline plots estimated from Bayesian MCMC analyses of hMPV G-protein sequences belong to lineage 1(a + b) and lineage 2(a + b). Population size (in Y-axis) is expressed in logarithmic scale. The solid line shows the median estimate of population size (Ne × g) throughout the given time period. The grey area gives the 95% HPD interval of these estimates.

Despite the weak temporal and spatial structure, viral strains belonging to lineage 1a (Australia, Canada, The Netherlands, South Africa, USA, Argentina, and Japan) and 1b (Canada, The Netherlands, South Africa, USA, Japan, China, and Argentina) have a wider geographic spread than the strains belonging to lineage 2a (Canada, UK, The Netherlands, USA, China, and South Africa) and 2b (The Netherlands, Canada, USA, Peru, and Japan), indicating that fitness of the viral strains might have played a crucial role in the uneven distribution across the wide geographic regions. The extensive polymorphisms of the hMPV G-gene may have resulted from mutations occurring during virus propagation in cell culture; however, Peret et al. (2004) reported identical sequences of the same viral strain after multiple passages, and thus, the observed variation in the G-gene of hMPVs due to multiple passages is more unlikely. However, it is unclear whether the hMPV G-gene experienced differential selection pressures, or all the deduced amino acid sites evolved due to stochastic mutational processes? Sliding window analyses of each lineage revealed that in the majority of regions synonymous divergence exceeds the corresponding nonsynonymous divergence, thus suggesting that the G-gene of hMPV is influenced by purifying selection (Fig. 1). However, a few coding regions in all the lineages showed relatively higher nonsynonymous divergence than synonymous divergence, therefore indicating the pervasive role of positive selection in certain amino acid sites. To identify the codon sites that are positively selected, we performed ML-based codon substitution analyses. Consistent with sliding window results, the M0 model revealed that the average ω for each lineage is less than one (Table 3 ), thus suggesting each lineage experienced purifying selection. However, comparison of the models that assume positive selection (M2a, M8) with the models (M1a, M7, and M8a) that assume no positive selection, detected approximately 6%, 1.3%, 7.3%, and 3% positively selected codons in lineage 1a, 1b, 2a, and 2b, respectively (Table 3). There are eight positively selected sites (site 93, 105, 106, 154, 158, 171, 173, and 188) with posterior probability ≥0.95 within lineage 1a, whereas lineage 1b (site 146, 183, and 196) and lineage 2a (85, 232, and 239) each have three positively selected sites with posterior probability ≥0.95. Lineage 2b has only two positively selected sites (site 100 and 105) with posterior probability ≥0.95. Except site 105, which is positively selected in lineage 1a and 2b, none of the positively selected sites are overlapping among the lineages. It is unclear whether these positively selected sites are associated with the fitness of this virus. Research with monoclonal antibodies has shown that the hMPV F-protein carries neutralizing epitopes (Skiadopoulos et al., 2004, Ulbrand et al., 2006); therefore, antigenic variation due to immune selection in the hMPV F-protein is more likely. Although, the overall excess of synonymous substitutions at the hMPV G-protein indicates that host immune selection might not be the dominant selective force, the findings of several hotspots of nonsynonymous substitutions in this protein suggests that host immune selection might also play a role in maintaining diversity. Recent study has shown that a majority of the neutralizing epitopes in the HRSV G-gene is strongly associated with positively selected sites, and some of the positively selected sites correspond to the sites of O-glycosylation (Zlateva et al., 2004). Like HRSV, although all the positively selected codons of hMPV G-gene are located in the extracellular domain and some of them correspond to sites of O-glycosylation, the putative role is still unclear for these positively selected sites, as is whether some of these positively selected sites are associated with the region of antigenic determinants. We intended to map these positively selected sites with the HRSV G-protein to see whether the same sites were also positively selected in HRSV (Zlateva et al., 2004, Zlateva et al., 2005); however, the predicted G-gene amino acid sequences of the two viruses could not be aligned (van den Hoogen et al., 2002, Kahn, 2006). Although a vast majority of codon sites (>95% in most cases) are shown to have been under purifying selection, significantly higher ω values (>1) at certain codon sites (Table 3) indicate the hMPV G-gene is under positive selection. Identification of these positively selected amino acid sites would help in better screening using epitope mapping technology to identify and localize the sites that can be recognized by the immune system. Knowledge of sites that have adaptively evolved can greatly cut the cost of these screening processes and thereby help in developing better immunization techniques (Mes and van Putten, 2007).

Table 3.

Test for variable selection pressures on different codons based on ML-based codon substitution models of Yang et al. (2000)

Model Free parameters Parameter estimates Likelihood scores Model comparison (2Δl, d.f., p) Positively selected sites ω ± S.E.
Lineage 1a
 M0: One-ratio 1 ω = 0.6152 −2510.069374 None
 M1a: Nearly neutral 1 ω0 = 0.1, ω1 = 1, (p0 = 0.62, p1 = 0.38) −2473.399503 Not allowed



 M2a: Positive selection 3 ω0 = 0, ω1 = 1, ω2 = 7.31; (p0 = 0.62, p1 = 0.32, p2 = 0.06) −2444.710131 (M1a vs. M2a), 57.378744, d.f. = 2, p = 0.0000 93-H(0.989) 7.523 ± 1.614
105-Y (0.987) 7.504 ± 1.640
106-F (1.000) 7.595 ± 1.464
143-K (0.748) 5.832 ± 3.077
154-P (1.000) 7.594 ± 1.466
155-R(0.667) 5.263 ± 3.239
158-S (0.980) 7.456 ± 1.718
171-R(0.958) 7.323 ± 1.953
173-T (0.971) 7.380 ± 1.805
176-T (0.583) 4.674 ± 3.305
188-T (0.973) 7.393 ± 1.788



 M7: β 2 p = 0.1085, q = 0.1183 −2474.985643 Not allowed



 M8: β + ωs > 1 4 p0 = 0.94, p1 = 0.06, p = 0.36716, q = 0.47347, ω = 6.83 −2444.453952 (M7 vs. M8), 61.063382, d.f. = 2, p = 0.0000 93-H (0.993) 7.265 ± 1.428
105Y (0.993) 7.264 ± 1.426
106-F (1.000) 7.307 ± 1.332
143-K (0.814) 6.055 ± 2.779
154-P (1.000) 7.306 ± 1.332
155-R (0.744) 5.575 ± 3.020
156-T (0.649) 4.762 ± 2.999
158-S (0.990) 7.242 ± 1.468
171-R(0.970) 7.119 ± 1.718
173-T (0.989) 7.228 ± 1.480
176-T (0.664) 5.028 ± 3.191
188-T (0.991) 7.239 ± 1.460



 M8a: β + ωs = 1 3 p0 = 0.62, p1 = 0.38, p = 11.37, q = 99, ω = 1 −2473.400411 (M8 vs. M8a), 57.892918, d.f. = 1, p = 0.0000 Not allowed



Lineage 1b
 M0: One-ratio 1 ω = 0.4649 −3088.137934 None
 M1a: Nearly neutral 1 ω0 = 0.166, ω1 = 1, (p0 = 0.72, p1 = 0.28) −3048.588195 Not allowed



 M2a: Positive selection 3 ω0 = 0.179, ω1 = 1, ω2 = 9.729; (p0 = 0.696, p1 = 0.289, p2 = 0.013) −3028.791341 (M1a vs. M2a), 39.593708, d.f. = 2, p = 0.0000 146-P (1.00) 8.326 ± 1.713
183-F (1.00) 8.325 ± 1.714
196-L (0.999) 8.316 ± 1.732



 M7: β 2 p = 0.393, q = 0.546 −3054.125576 Not allowed



 M8: β + ωs > 1 4 p0 = 0.89, p1 = 0.11p = 1.777, q = 4.03, ω = 2.84 −3034.377594 (M7 vs. M8), 39.495964, d.f. = 2, p = 0.0000 146-P (1.000) 5.183 ± 1.880
157-F (0.718) 3.601 ± 2.137
183-F (1.000) 5.183 ± 1.880
196-L (0.999) 5.181 ± 1.882
199-S (0.573) 2.935 ± 2.110



 M8a: β + ωs = 1 3 p0 = 0.72, p1 = 0.28, p = 19.98, q = 99, ω = 1 −3048.6126 (M8 vs. M8a), 28.470012, d.f. = 1, p = 0.0000 Not allowed



Lineage 2a
 M0: One-ratio 1 ω = 0.6898 −2927.296491 None
 M1a: Nearly neutral 1 ω0 = 0.248, ω1 = 1, (p0 = 0.565, p1 = 0.435) −2913.654666 Not allowed



 M2a: Positive selection 3 ω0 = 0.382, ω2 = 4.487; (p0 = 0.69, p1 = 0.23, p2 = 0.073) −2898.698295 (Mla vs. M2a), 29.912742, d.f. = 2, p = 0.0000 85-L (1.000) 5.340 ± 1.570
93-Q (0.888) 4.839 ± 2.038
105-L (0.878) 4.694 ± 1.966
109-S(0.913) 4.898 ± 1.899
113-L (0.732) 3.959 ± 2.193
121-P (0.510) 2.849 ± 2.078
180-L (0.535) 3.024 ± 2.228
202-S (0.508) 2.890 ± 2.196
232-Y (0.989) 5.295 ± 1.627
239-P (0.975) 5.226 ± 1.690



 M7: β 2 p = 0.606, q = 0.379 −2917.092133 Not allowed



 M8: β + ωs > 1 4 p0 = 0.89, p1 = 0.11, p = 28.418, q = 31.77, ω = 3.65 −2898.947133 (M7 vs. M8), 36.29, d.f. = 2, p = 0.0000 85-L (1.000) 5.381 ± 1.324
93-Q (0.900) 4.945 ± 1.872
105-L (0.920) 4.988 ± 1.751
109-S (0.939) 5.093 ± 1.673
113-L (0.777) 4.282 ± 2.179
121-P (0.528) 3.028 ± 2.275
180-L (0.546) 3.173 ± 2.375
202-S (0.519) 3.038 ± 2.358
232-Y (0.992) 5.351 ± 1.376
239-P (0.983) 5.306 ± 1.439



 M8a: β + ωs = 1 3 p0 = 0.57, p1 = 0.43, p = 33.25, q = 99, ω = 1 −2913.719868 (M8 vs. M8a), 29.54547 d.f. = 1, p = 0.0000 Not allowed



Lineage 2b
 M0: One-ratio 1 ω = 0.7065 −1855.459267 None
 M1a: Nearly neutral 1 ω0 = 0, ω1 = 1, (p0 = 0.49, p1 = 0.51) 840.547215 Not allowed



 M2a: Positive selection 3 ω0 = 0, ω1 = 1, ω2 = 10.0195; (p0 = 0.45, p1 = 0.52, p2 = 0.03) −1829.903873 (M1a vs. M2a), 21.286684, d.f. = 2, p = 0.00002 100-E (0.999) 7.607 ± 2.041
105-P (0.971) 7.432 ± 2.288
109-P (0.911) 6.994 ± 2.703
213-R (0.682) 5.477 ± 3.516



 M7: β 2 p = 0.00517, q = 0.005 −1840.570751 Not allowed



 M8: β + ωs > 1 4 p0 = 0.97, p1 = 0.03, p = 0.005, q = 0.005, ω = 9.6 830.002479 (M7 vs. M8), 21.136554, d.f. = 2, p = 0.00003 100-E (1.000) 6.823 ± 2.093
105-P (0.985) 6.745 ± 2.196
109-P (0.958) 6.561 ± 2.375
114-Y (0.515) 3.679 ± 3.226
116-G (0.572) 4.071 ± 3.293
162-E (0.606) 4.080 ± 3.052
201-T (0.500) 3.579 ± 3.206
213-R (0.770) 5.424 ± 3.159
220-P (0.629) 4.385 ± 3.236



 M8a: β + ωs = 1 3 p0 = 0.49, p1 = 0.51, p = 0.005, q = 2.785, ω = 1 840.547213 (M8 vs. M8a), 21.089468, d.f. = 1, p = 0.0000 Not allowed
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Null models (M1a, M7, and M8a) are compared with their respective alternative models (M2a, M8) that allow ω > 1. Proportion of positively selected sites and their corresponding ω-values in M2a and M8 models are in bold. The posterior probability of each positively selected amino acid site is in parenthesis. Posterior probabilities are estimated based on Bayes Empirical bayes analyses (Yang et al., 2005).

Acknowledgements

We thank the University of Tulsa for providing facilities to carry out this work and Dr. Peggy S.M. Hill for editing and comments for improving the manuscript. We thank two anonymous reviewers for the helpful comments on the earlier version of the manuscript.

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