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. Author manuscript; available in PMC: 2015 Oct 26.
Published in final edited form as: Infect Genet Evol. 2014 Oct 6;28:513–523. doi: 10.1016/j.meegid.2014.09.021

Comparative Genomic Analysis of Genogroup 1 (Wa-like) Rotaviruses circulating in the USA, 2006 – 2009

Sunando Roy a, Mathew D Esona a, Ewen F Kirkness b, Asmik Akopov b, J Kyle McAllen b, Mary Wikswo a, Margaret M Cortese a, Daniel C Payne a, Umesh Parashar a, Jon R Gentsch a, Michael D Bowen a,*; the National Rotavirus Strain Surveillance System; the New Vaccine Surveillance System
PMCID: PMC4620586  NIHMSID: NIHMS727345  PMID: 25301114

Abstract

Group A Rotaviruses (RVA) are double stranded RNA viruses that are a significant cause of acute pediatric gastroenteritis. Beginning in 2006 and 2008, respectively, two vaccines, Rotarix™ and RotaTeq®, have been approved for use in the USA for prevention of RVA disease. The effects of possible vaccine pressure on currently circulating strains in the USA and their genome constellations are still under investigation. In this study we report 33 complete RVA genomes (ORF regions) collected in multiple cities across USA during 2006 – 2009, including 8 collected from children with verified receipt of 3 doses of rotavirus vaccine. The strains included 16 G1P[8], 10 G3P[8], and 7 G9P[8]. All 33 strains had a Wa like backbone with the consensus genotype constellation of G(1/3/9)-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1. From maximum likelihood based phylogenetic analyses, we identified 3 to7 allelic constellations grouped mostly by respective G types, suggesting a possible allelic segregation based on the VP7 gene of RVA primarily for the G3 and G9 strains. The vaccine failure strains showed similar grouping for all genes in G9 strains and most genes of G3 strains suggesting that these constellations were necessary to evade vaccine-derived immune protection. Substitutions in the antigenic region of VP7 and VP4 genes were also observed for the vaccine failure strains which could possibly explain how these strains escape vaccine induced immune response. This study helps elucidate how RVA strains are currently evolving in the population post vaccine introduction and supports the need for continued RVA surveillance.

Keywords: Rotavirus, vaccine, failure, allele, VP4, VP7

1. Introduction

Group A Rotaviruses (RVA) are the major cause of acute gastroenteritis in children under 5 years of age and the leading cause of gastroenteritis related deaths (~450,000) in developing countries every year (Estes and Kapikian, 2007; Parashar et al., 2009; Tate et al., 2012). In industrialized countries, RVA associated mortality is minimal yet the financial cost of treatment associated with disease burden is enormous (Payne et al., 2011). The RVA genome is composed of 11 double-stranded RNA (dsRNA) segments which code for 11or 12 proteins in total, six structural proteins VP1-VP4, VP6 and VP7, and five or six nonstructural proteins NSP1-NSP5/6 (Estes and Kapikian, 2007). The VP7 and VP4 proteins form the outer layer of the viral capsid and have been historically used to classify RVA serotypes and genotypes into respective G and P types (Estes and Kapikian, 2007). These proteins have been extensively studied and a number of antigenic epitopes have been characterized. An extended classification system based on all 11 gene segments has been introduced by the Rotavirus Classification Working Group (RCWG) (Matthijnssens et al., 2008b) and this classification system designates genotypes in the format Gx-P[x]-Ix-Rx-Cx-Mx-Ax-Nx-Tx-Ex-Hx for the genes VP7, VP4, VP6, VP1-3, NSP1-5 respectively. Presently there are at least 27 G, 37 P, 16 I, 9 R, 9 C, 8 M, 16 A, 9 N, 12 T, 14 E, and 11 H types (Matthijnssens et al., 2011; Trojnar et al., 2013). The most common genogroup constellations worldwide based on the new classification are Wa like Genogroup 1 (Gx-P[x]-I1-R1-C1-M1-A1-N1-T1-E1-H1) and DS-1 like Genogroup 2 (Gx-P[x]-I2-R2-C2-M2-A2-N2-T2-E2-H2) (Matthijnssens et al., 2008b; Matthijnssens et al., 2012a). The genotype classification for an unknown strain is based on sequence identity cutoffs established by the RCWG and is currently implemented in the RotaC webserver (Maes et al., 2009).

In humans, the most common RVA G/P genotypes worldwide are G1P[8], G2P[4], G3P[8], G4P[8], and G9P[8] (Banyai et al., 2012; Gentsch et al., 2005). Two vaccines RotaTeq® (Merck) and Rotarix™ (GlaxoSmithKline) were introduced in the U.S. in 2006 and 2008, respectively (Cortese et al., 2009). RotaTeq® is a pentavalent human bovine reassortant vaccine which contains four G types (G1, G2, G3 and G4, VP7 gene) along with the P[8] VP4 type on a bovine WC3 (G6P[5]) backbone (Matthijnssens et al., 2010b). On the other hand, Rotarix™ is a human RVA derived G1P[8] strain (Ward, 2009). These vaccines have shown high efficacy in reducing the RVA burden in developed countries after their introduction in various immunization programs (Gray, 2011). Unfortunately the same vaccines have much lower efficacy in some developing countries and this has caused some concern (Armah et al., 2010; Phua et al., 2009; Zaman et al., 2010). In addition it has been proposed that RVA vaccination in several countries may have driven the selection of new predominant genotypes through immune pressure (Carvalho-Costa et al., 2009; Hull et al., 2011; Matthijnssens et al., 2012b; Zeller et al., 2010) though current evidence remains inconclusive. Globally, multiple surveillance networks have been established to study RVA prevalence in various countries (Carvalho-Costa et al., 2011; Hull et al., 2011; Iturriza-Gomara et al., 2009; Kirkwood et al., 2010; Payne et al., 2008). In United States the two main RVA surveillance networks, National Rotavirus Strain Surveillance System (NRSSS) and the New Vaccine Surveillance Network (NVSN) have been established to monitor RVA strain prevalence in multiple parts of the country (Hull et al., 2011; Payne et al., 2008).

RVA genomes show high genomic diversity similar to other known RNA viruses. The diversity is generated by point mutations, reassortment, rearrangement and recombination events (Estes, 2007; Kirkwood et al., 2010). The proteins of RVA are known to evolve at substantially different rates with VP1 and VP2 being highly conserved whereas NSP1 is known to be highly divergent (Matthijnssens et al., 2008a). A recent study measured evolutionary rates of all 11 gene segments for the SA11-H96 strain and found nearly a 100 fold difference in evolutionary substitution rates among the 11 gene segments (Mlera et al., 2013). The evolutionary rates for the VP7 gene of G9 and G12 strains have also been calculated by Mathijnnesens et al to be 1.87 × 10−3 and 1.66 × 10−3 substitutions/site/year respectively (Matthijnssens et al., 2010a). Reassortment occurs when gene segments are exchanged between two different strains of RVA during a co-infection event. Multiple reassortments have been documented between two genogroups and also between different host species, albeit at a lower frequency (Varghese et al., 2004). Animal-to-human cross-transmission and reassortment events between human and animal strains have been suggested as one of the possible reasons for the low vaccine efficacy in developing countries (Martella et al., 2010; Palombo, 2002). Reassortment has also been recently reported between sub-genotypic clusters (Maunula and Von Bonsdorff, 2002; McDonald et al., 2012). Rearrangements events, although infrequent, have been observed in the NSP1 and NSP3 genes of cell culture passaged strains (Kojima et al., 2000). The short electropherotype of DS-1 like RVA strains is the result of naturally-occurring duplication and insertion events in the NSP5 genes (Giambiagi et al., 1994; Gonzalez et al., 1989). Intragenic recombination events are extremely rare and only a few cases have been reported in the VP7 and NSP2 genes (Donker et al., 2011; Phan et al., 2007). There is one report of intergenic recombination in the VP7 gene (Martinez-Laso et al., 2009).

In this study we sequenced complete open reading frames (ORFs) for 33 genogroup 1 strains (16 G1P[8], 10 G3P[8], and 7 G9P[8]) collected from multiple cities across the United States. Maximum likelihood based phylogenetic analysis along with other sequence analysis tools helped identify multiple sub-genotype allelic constellations recently circulating in USA. These sub allelic constellations may enhance our understanding of RVA evolution under vaccine pressure and help identify possible mechanisms of immune escape which result in RVA gastroenteritis in vaccinated individuals.

2. Materials and Methods

2.1 Surveillance Testing and Genotyping

Fecal specimens were collected from children with acute gastroenteritis from 12 sites in the United States during the 2006-2007, 2007-2008, and 2008-2009 RVA seasons. All samples were tested by enzyme immunoassay (EIA) using the Premier® Rotaclone® Rotavirus Detection Kit (Meridian Diagnostics Inc., Cincinnati, OH). At the Centers for Disease Control and Prevention, (CDC), RVA dsRNA was extracted and VP7 and VP4 genotyping was carried out using a two-step amplification method as described previously (Hull et al., 2011).

2.2 Sample Selection

A total of 33 samples were selected for genomic characterization of which 25 were from the NRSSS surveillance network and 8 from the NVSN. The NRSSS samples were selected based upon previous EIA and VP4/VP7 genotyping results and were collected from sites in Boston MA (1 sample), Chicago IL (1) Orlando FL (1), Fort Worth TX (6), Indianapolis IN (2), Long Beach CA (3), Omaha NE (3), San Francisco CA (1), and Seattle WA (7) whereas the NVSN samples were from study sites in Cincinnati OH (1), Nashville TN (1), and Rochester NY (6). Vaccination histories were available only for the children enrolled at NVSN sites. All 8 samples collected at NVSN sites were from children that received 3 doses of RotaTeq® vaccine.

2.3 Sanger Sequencing

Total RNA was extracted from 33 samples using MagNA Pure Compact extraction system with the RNA Isolation kit (Roche Applied Science, Indianapolis IN) and were sent to J. Craig Venter Institute for high-throughput Sanger sequencing. Oligonucleotide primers were designed using an automated primer design tool [PMID 18405373, 23131097]. Primers, with M13 tags added, were designed at intervals along both the sense and antisense strands, and provided amplicon coverage of at least 4-fold (see supplementary material). RT-PCRs were performed with 1 ng of RNA using OneStep RT-PCR kits (Qiagen, Valencia, CA) according to manufacturer's instructions with minor modifications: 1) reactions were scaled down to 1/5 the recommended volumes; 2) the RNA templates were denatured at 95°C for 5 min; and 3) 1.6 U RNase Out (Invitrogen, Carlsbad, CA) was used. The RT-PCR products were sequenced with an ABI Prism BigDye v3.1 terminator cycle sequencing kit (Applied Biosystems, Carlsbad, CA). Raw sequence traces were trimmed to remove any primer-derived sequence as well as low quality sequence, and gene sequences were assembled using Minimus, part of the open-source AMOS project [The AMOS project. http://amos.sourceforge.net]. The gene sequences were then manually edited using ClOE (Closure Editor; JCVI) and ambiguous regions were resolved by additional sequencing when necessary.

2.4 Whole Genome Phylogenetic Analysis

Genotypes for each gene segment were determined using RotaC v2.0 webserver (Maes et al., 2009). For each gene, multiple alignments were made using the MUSCLE algorithm implemented in MEGA 5.1 (Tamura et al., 2011). Maximum likelihood trees were constructed for each gene in PhyML 3.0 using the optimal model for each alignment as identified by jModeltest 2 and approximate Likelihood Ratio Test (aLRT) statistics computed for branch support (Anisimova and Gascuel, 2006; Darriba et al., 2012; Guindon et al., 2010). The best models were selected based on the corrected Akaike Information Criterion and were General Time Reversible (GTR)+I+G (NSP1), GTR+G (NSP2, VP4), Transition model (TIM2)+I (NSP3), Tamura-Nei (TrN)+G (NSP4), Hasegawa-Kishino-Yano (HKY)+G (NSP5), TIM1+I (VP1,VP3), GTR+I (VP2), TrN+I (VP6), HKY+I+G (VP7). . Sub-genotypic clusters were identified as tight phylogenetic clusters with aLRT support greater >75%. Sequences were tested for possible recombination using the Genetic Algorithm Recombination Detection (GARD) algorithm implemented in Datamonkey (Delport et al., 2010; Kosakovsky Pond and Frost, 2005; Kosakovsky Pond et al., 2006; Pond and Frost, 2005). Selection analysis was performed using a combination of Single Likelihood Ancestor Counting (SLAC), Fixed Effects Likelihood (FEL) and Random Effects Likelihood (REL) analysis in Datamonkey (Kosakovsky Pond and Frost, 2005; Pond and Frost, 2005). Substitutions in the VP7, VP8* and VP5* regions were mapped on crystal structures available in PDB (www.pdb.org) using VMD 1.9.1 (Berman et al., 2000; Humphrey et al., 1996). For VP7 we used the RRV crystal 3FMG, for VP8* the Wa crystal 2DWR and for VP5* the RRV crystal 2B4I was used (Aoki et al., 2009; Blanchard et al., 2007; Yoder and Dormitzer, 2006).

2.5 Accession numbers

The nucleotide sequences for the ORFs of the eleven gene segments for each strain were submitted to GenBank (total of 363 sequences). The accession numbers are listed in Table 1.

Table 1.

Accession Numbers for 33 RVA strains determined in this study.

Case ID VP7 VP4 VP6 VP1 VP2 VP3 NSP1 NSP2 NSP3 NSP4 NSP5
RVA/Human-wt/USA/2007719635/2007/G1P[8] JN258368 JN258371 JN258370 JN258364 JN258374 JN258373 JN258372 JN258365 JN258369 JN258367 JN258366
RVA/Human-wt/USA/2007719674/2007/G3P[8] JN258362 JN258360 JN258359 JN258353 JN258363 JN258361 JN258355 JN258354 JN258358 JN258357 JN258356
RVA/Human-wt/USA/2007719685/2007/G1P[8] JN258346 JN258349 JN258348 JN258342 JN258350 JN258351 JN258352 JN258343 JN258347 JN258345 JN258344
RVA/Human-wt/USA/2007719698/2007/G1P[8] HM773774 HM773769 HM773771 HM773766 HM773767 HM773768 HM773770 HM773773 HM773772 HM773775 HM773776
RVA/Human-wt/USA/2007719720/2007/G1P[8] JN258338 JN258340 JN258335 JN258331 JN258341 JN258336 JN258337 JN258332 JN258334 JN258339 JN258333
RVA/Human-wt/USA/2007719739/2007/G1P[8] HM773763 HM773758 HM773760 HM773755 HM773756 HM773757 HM773759 HM773762 HM773761 HM773764 HM773765
RVA/Human-wt/USA/2007719825/2007/G1P[8] HM773752 HM773747 HM773749 HM773744 HM773745 HM773746 HM773748 HM773751 HM773750 HM773753 HM773754
RVA/Human-wt/USA/2007719907/2007/G1P[8] HM773851 HM773846 HM773848 HM773843 HM773844 HM773845 HM773847 HM773850 HM773849 HM773852 HM773853
RVA/Human-wt/USA/2007719945/2007/G1P[8] HM773840 HM773835 HM773837 HM773832 HM773833 HM773834 HM773836 HM773839 HM773838 HM773841 HM773842
RVA/Human-wt/USA/2007744270/2007/G1P[8] HM773829 HM773824 HM773826 HM773821 HM773822 HM773823 HM773825 HM773828 HM773827 HM773830 HM773831
RVA/Human-wt/USA/2007744509/2007/G1P[8] HM773818 HM773813 HM773815 HM773810 HM773811 HM773812 HM773814 HM773817 HM773816 HM773819 HM773820
RVA/Human-wt/USA/2007744510/2007/G1P[8] HM773807 HM773802 HM773804 HM773799 HM773800 HM773801 HM773803 HM773806 HM773805 HM773808 HM773809
RVA/Human-wt/USA/2007769947/2007/G1P[8] JN258401 JN258404 JN258403 JN258397 JN258406 JN258405 JN258407 JN258398 JN258402 JN258400 JN258399
RVA/Human-wt/USA/2008747100/2008/G1P[8] HM773796 HM773791 HM773793 HM773788 HM773789 HM773790 HM773792 HM773795 HM773794 HM773797 HM773798
RVA/Human-wt/USA/2008747106/2008/G1P[8] HM773785 HM773780 HM773782 HM773777 HM773778 HM773779 HM773781 HM773784 HM773783 HM773786 HM773787
RVA/Human-wt/USA/2008747112/2008/G3P[8] HM773719 HM773714 HM773716 HM773711 HM773712 HM773713 HM773715 HM773718 HM773717 HM773720 HM773721
RVA/Human-wt/USA/2008747288/2008/G1P[8] JN258380 JN258383 JN258382 JN258375 JN258385 JN258384 JN258377 JN258376 JN258381 JN258379 JN258378
RVA/Human-wt/USA/2008747307/2008/G9P[8] HM773642 HM773637 HM773639 HM773634 HM773635 HM773636 HM773638 HM773641 HM773640 HM773643 HM773644
RVA/Human-wt/USA/2008747322/2008/G3P[8] HM773741 HM773736 HM773738 HM773733 HM773734 HM773735 HM773737 HM773740 HM773739 HM773742 HM773743
RVA/Human-wt/USA/2008747323/2008/G1P[8] JN258390 JN258393 JN258392 JN258386 JN258396 JN258394 JN258395 JN258387 JN258391 JN258389 JN258388
RVA/Human-wt/USA/2008747329/2008/G3P[8] HM773708 HM773703 HM773705 HM773700 HM773701 HM773702 HM773704 HM773707 HM773706 HM773709 HM773710
RVA/Human-wt/USA/2008747332/2008/G3P[8] HM773697 HM773692 HM773694 HM773689 HM773690 HM773691 HM773693 HM773696 HM773695 HM773698 HM773699
RVA/Human-wt/USA/2008747336/2008/G3P[8] HM773686 HM773681 HM773683 HM773678 HM773679 HM773680 HM773682 HM773685 HM773684 HM773687 HM773688
RVA/Human-wt/USA/2008747337/2008/G3P[8] HM773675 HM773670 HM773672 HM773667 HM773668 HM773669 HM773671 HM773674 HM773673 HM773676 HM773677
RVA/Human-wt/USA/2008747369/2008/G3P[8] HM773664 HM773659 HM773661 HM773656 HM773657 HM773658 HM773660 HM773663 HM773662 HM773665 HM773666
RVA/Human-wt/USA/2008747500/2008/G3P[8] HM773653 HM773648 HM773650 HM773645 HM773646 HM773647 HM773649 HM773652 HM773651 HM773654 HM773655
RVA/Human-wt/USA/2009726997/2009/G3P[8] HM773730 HM773725 HM773727 HM773722 HM773723 HM773724 HM773726 HM773729 HM773728 HM773731 HM773732
RVA/Human-wt/USA/2009727032/2009/G9P[8] HM773587 HM773582 HM773584 HM773579 HM773580 HM773581 HM773583 HM773586 HM773585 HM773588 HM773589
RVA/Human-wt/USA/2009727036/2009/G9P[8] HM773598 HM773593 HM773595 HM773590 HM773591 HM773592 HM773594 HM773597 HM773596 HM773599 HM773600
RVA/Human-wt/USA/2009727047/2009/G9P[8] HM773620 HM773615 HM773617 HM773612 HM773613 HM773614 HM773616 HM773619 HM773618 HM773621 HM773622
RVA/Human-wt/USA/2009727051/2009/G9P[8] HM773631 HM773626 HM773628 HM773623 HM773624 HM773625 HM773627 HM773630 HM773629 HM773632 HM773633
RVA/Human-wt/USA/2009727093/2009/G9P[8] HM534680 HM534675 HM534677 HM534672 HM534673 HM534674 HM534676 HM534679 HM534678 HM534681 HM534682
RVA/Human-wt/USA/2009727098/2009/G9P[8] HM773609 HM773604 HM773606 HM773601 HM773602 HM773603 HM773605 HM773608 HM773607 HM773610 HM773611
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3. Results

Complete ORF sequences were obtained for all 11 genes of 33 strains. Out of the 33 strains sequenced, 16 were G1P[8], 10 were G3P[8], and 7 were G9P[8] RVA strains.. Using RotaC 2.0 webserver, we assigned genotypes to the 11 different gene segments for all 33 RVA samples. All strains were found to be Wa-like genogroup 1 strains and the consensus 11-gene genotype constellation for the 33 RVA samples was G(1/3/9)-P[8]-I1-R1-C1-M1-A1-N1-T1-E1-H1.

To this dataset we added 58 previously published sequences (McDonald et al., 2012) that were from samples collected during 2005 – 2008 from the NVSN site in Nashville (see supplementary material). The samples were all genogroup 1 strains with G1P[8], G3P[8] and G12P[8] genotypes (McDonald et al., 2012). Using the alignments of ORF sequences for each gene segment, we determined the optimal model based upon AICc values. We tested for subgenotype clustering of strains based on maximum likelihood analyses. Sub-genotype clustering was identified by nodes with aLRT support ≥ 75%. The phylogenetic trees for all 11 gene segments are shown in Fig 1(A-K) and the color coding of alleles shown in Figure 2. The VP7 gene clusters are based on the various individual genotypes G1, G3, G9, G12 (Fig 1A). The G1 strains were further divided into three distinct clusters indicating 3 alleles [AI (red), AII (maroon), and AIII (olive)]. The strains in the AI Allele clustered with the prototype G1P[8] strain Wa and the G1 genes of the two vaccines, RotaTeq® and Rotarix™, whereas the AII and AIII strains formed distinct, supported clusters.

Figure 1.

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Maximum likelihood trees with aLRT values showing branch support for the 11 RVA genes. The different alleles are colored in red, green, blue, purple, lime, pink, teal and aqua for Alleles A, B, C, D, E, F, G and H respectively. Doublets and singletons are shown in grey and black, respectively (Fig. 1A) VP7. The Allele A in further divided into three clusters: red strains that mostly cluster with G1 (Wa) strains and maroon and olive strains that forms a distinct clusters from the reference Wa Strain. (1B) VP4; (1C) VP6; (1D) VP1; (1E) VP2; (1F) VP3; (1G) NSP1; (1H) NSP2; (1I) NSP3; (1J) NSP4; (1K) NSP5. To see the individual strains comprising each colored triangle, consult the supplemental figures (see supplementary material).

Figure 2.

Figure 2

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Allelic clusters for the 91 RVA strains. Genes from strains that clustered with Allele A (G1) are shown in red, maroon and olive. Allele B (G3) genes are shown in green and Allele C (G9) strains are shown in blue, Independent clusters are shown in purple (Allele D), lime (Allele E), pink (Allele F), teal (Allele G) and aqua (Allele H). Doublet strains are shown in grey and singleton strains in black.

For the other 10 gene segments the clusters were colored based on association with VP7 genotypes (G1, G3, G9). The Wa-like G1 cluster was Allele A (red), the majority G3 cluster was Allele B (green), and the G9-like cluster was Allele C (blue). Strains that formed separate clusters outside the three designated alleles were separately clustered into Alleles D (purple), E (lime), F (pink), G (teal) and H (aqua). Doublets (pairs of strains) are indicated in gray and singleton and outgroup strains were labelled in black (Fig 1B-K, Fig 2). The analysis (of all 91 sequences) identified 3 to 7 subgenotypic clusters along with a few doublets and single outgroup strains for all 11 gene segments. Similar clustering was observed for most of the G3 and G9 RVA strains in all 11 gene segments (Figure 2). The G1 strains were broadly divided into 3 alleles. Strains 2008747288, 2007719698, 2007744509, 2007744510, except in the NSP3, VP6 and VP7 genes, clustered with the Wa like strains whereas strains 2008747100 and 2008747106 differed in their clustering pattern in the VP6, NSP3 and NSP1 genes only. The other G1 strains from this study did not exhibit a fixed clustering pattern across the 11 gene segments suggesting possible past intra-genotype reassortment events between the alleles.

Out of the 33 strains, 8 were from children known to have received at least one dose of RotaTeq® vaccine and these strains were referred to as vaccine failure (VF) strains. Six VF strains were from Rochester (G9P[8]) and one each (G3P[8]) from Nashville and Cincinnati. Four more G3P[8] VF strains from the McDonald et al. dataset were also included in this analysis. The G9 VF strains showed clustering across all 11 gene segments into Allele C whereas the G3 VF strains clustered primarily with Allele B, with a few exceptions (Fig 2). For strain 2009726997, the NSP4 gene did not cluster with other G3P[8] strains whereas strain VU08-09-22 clustered with Allele C for VP6, NSP1 and NSP4 genes and, for the NSP3 gene, strains not assigned to alleles (Fig 2).

We further tested for positive selection in the ORFs of all strains based on combined SLAC, FEL and REL tests. The number of codons analyzed per ORF is shown in Table 2. No positively selected sites were identified with high confidence (p ≤ 0.1) among the 91 RVA samples (Table 2). All the genes were found to contain sites under strong purifying selection, however, ranging from 38 of 175 sites in NSP4 (21.7%) to 187 of 326 sites (57.1%) in VP7 (Table 2). VP6 exhibited the second highest percentage of sites (49.6%) under purifying selection. The percentage of sites under strong purifying selection ranged from 25.8% (VP2) to 57.1% (VP7) in the structural proteins and 21.7% (NSP4) to 44.2% (NSP1) among the non-structural proteins (Table 2). Tests for recombination were also carried out, but recombination was not detected in any of the 11 genes based on results of GARD analysis.

Table 2.

Results of selection analyses of 11 rotavirus proteins.

Protein No. of sites No. of sites under positive selection No. (%) of sites under purifying selection
NSP1 491 0 217 (44.2)
NSP2 317 0 107 (33.8)
NSP3 315 0 132 (41.9)
NSP4 175 0 38 (21.7)
NSP5 198 0 46 (23.2)
VP1 1088 0 421 (38.9)
VP2 881 0 227 (25.8)
VP3 835 0 246 (29.5)
VP4 776 0 332 (42.8)
VP6 397 0 197 (49.6)
VP7 326 0 187 (57.1)
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Using alignments for the VP4 and VP7 genes, we identified amino acid substitutions in the antigenic regions between the wild type RVA strains and the RotaTeq® and Rotarix™ vaccine strains. For the VP7 protein, the VF strains in our data set were genotype G3/G9 so we compared them to the G3 component of RotaTeq® as no known G9 vaccine component was available. The conservative or non-conservative nature of substitutions was based on the classification proposed by Zhang et al (Zhang, 2000). In the G3 VF strains, a single substitution at position 242 was detected (T242N) that was also present in the G9 VF strains (Fig 3). In G9 VP7 VF strains, substitutions were observed at positions 94, 96, 146, 189, 208, 238 and 242 in antigenic sites A, B, E, C, and F (Fig 3). Positions 94, 96, 189, and 238 are known neutralization escape mutation site (Aoki et al., 2009). In the G9 VP7 protein, we observed a N/S94G substitution, G96T substitution, Q146S substitution, S189Q substitution, Q208I substitution and a N238D substitution . Most of these substitutions are conservative in nature except the Q208I substitution (position 208), which causes change in polarity and thus possibly affecting epitope structure. None of the G1 strains analyzed in this study were VF strains so we could not perform the substitution comparison with the G1 genes of the vaccine strains.

Figure 3.

Figure 3

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Crystal structure of RVA VP7 protein (3FMG). Substitutions at the antigenic site are marked in green and substitutions at reported neutralization escape mutation sites are marked in red.

The VP4 protein, which in the study represented all P[8] strains, was divided into the VP8* and VP5* regions for comparison. In VP8*, positions 106, 108, 113, 120, 145, 150, and 195 show amino acid substitutions out of which positions 113, 145 and 195 are known neutralization escape mutation sites (Fig 4) (Dormitzer et al., 2004; Kobayashi et al., 1990; McKinney et al., 2007; Monnier et al., 2006; Zhou et al., 1994). In the VP8* region, we observed V106I substitution, I108V substitution, N113D substitution, T/M120N substitution, S145G substitution, E150D substitution, and N/D195G substitution in in all the G3 and G9 strains, and some G1 strains. The G1 strains that possessed the above substitutions were the ones that did not cluster with Allele A strains for most of the 11 genes. Most of these changes are conservative in nature except a N113D substitution at position 113 involving a change in charge, M120N at position 120 involving a change in polarity and D195G substitution at position 195 involving a change in charge. Three sites, positions 281, 385 and 604, were observed to have substitutions in the VP5* region (Fig 5). The substitutions were V281I, H/Y385D and L604V respectively. Out of these three substitutions only H/Y385D substitution at position 385 was non-conservative with a change in charge and this position is also a known neutralization escape mutation site (Dormitzer et al., 2004; Kobayashi et al., 1990; Larralde et al., 1991; Matsui et al., 1989). These substitutions were also present in all G3 strains and a few G1 strains in this study suggesting possible vaccine failure phenotypes.

Figure 4.

Figure 4

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Crystal structure of RVA VP8* region (2DWR). Substitutions at the antigenic site are marked in green and substitutions at reported neutralization escape mutation sites are marked in red.

Figure 5.

Figure 5

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Crystal structure of RVA VP5* region (2B4I). Substitutions at the antigenic site are marked in green and substitutions at reported neutralization escape mutation sites are marked in red.

The 12 VF strains in this study shared a common clustering pattern across all 10 (except VP7) genes. The G9P[8] VF strains always clustered with Allele C strains whereas the G3P[8] VF strains primarily clustered with Allele B strains. The 11 gene segments of 4 RVA samples from Fort Worth (2008747329, 2008747332, 2008747336, 2008747337) also shared similar clustering with respect to the G3P[8] VF strains (Fig 2). Vaccination histories were not available for those 4 samples but two of the 4 children were known to be age-eligible for vaccination. The substitutions in the VP7 proteins of the G9P[8] VF strains were unique at 6 of 7 sites when compared with the G3P[8] VF strains and the vaccine strains. Only 1 of 7 substitutions was shared by both the G9 and G3 VF strains. All of the ten substitutions found in the VP4 protein were shared by both G9P[8] and G3P[8] vaccine failure strains. These substitutions were also present, however, in all of the other G3 and G9 strains analyzed in this study and ~73% of the G1 strains.

4. Discussion

In this study we sequenced 33 RVA samples collected post vaccine introduction (2006-2009) from sites across the continental United States. The G1 samples collected were evenly distributed across the 2006 – 2007 and the 2007 – 2008 seasons (none in the 2008 – 2009 season). The majority of the G3 strains were from the 2007 – 2008 season whereas most G9 strains were from the 2008 – 2009 season. Maximum likelihood based phylogenetic clustering identified 3 to 7 distinct allelic clusters across all 11 gene segments. Allelic clusters for most part were defined by the VP7 gene with a few exceptions in some strains. Most G3 and G9 strains formed their own clusters across all 11 genes that also included the G1 alleles AI and AII in most cases. We hypothesize that the G1 strains from this study cluster on the tree with known G3 and G9 strains due to inter-allelic reassortment events as reported previously by McDonald et al. (McDonald et al., 2012). Such reassortment events may lead to constellations that are more favorable to the virus evolution. From the McDonald et al. dataset, which contain a large number of samples from the pre vaccination era (2005 – 2006), we identified 3 G1 alleles circulating in the population. The presence of such mixed allelic G1 reassortants pre vaccine introduction and their rise in numbers post vaccination may suggest that these mixed alleles are possibly selected for under vaccine pressure over older Wa like G1 alleles and can evolve to give rise to potential VF strains (Arista et al., 2006). Arista et al. suggested that the older Wa like lineages became extinct due to immune pressure but this study detected strains circulating in US (Allele AI) which are similar to older Wa-like strains. These strains may provide a reservoir for selection of constellations that may lead to formation of vaccine failure strains. A larger dataset both pre and post vaccination is required to understand the evolution of these mixed allelic G1 reassortants during the pre-vaccine era and their rise in numbers during the post-vaccine era. In this study our allelic calls do not always match with previously reported studies (McDonald et al 2012). This is primarily due to Likelihood based measures that are heavily dependent on the dataset and the models used and hence these strains need to be re-defined based on the current phylogenetic trees.

In this study, we found that the vaccine failure strains have a fixed constellation across the 11 genes. It is possible that these constellations are present due to preferred interactions between proteins coded by these alleles which help in evading vaccination-induced protection in children (McDonald et al., 2009). All the vaccine failure strains also shared one substitution in VP7 gene and 10 substitutions in VP4 gene, which may lead to potential evasion of vaccine induced immunity. Although such fixed constellations and substitutions were observed in other G3 and G9 samples (e.g., G3P[8] strains from Fort Worth), we did not have the vaccination histories to determine whether these strains were also potential VF strains and we know that at least some of the children were too old to have been vaccinated (i.e., born more than 6 months before RotaTeq® vaccine was licensed in the US).

VP4 is an outer capsid component and in this study we found that 42.8% of the amino acid residues in this protein are under strong purifying selection. A previous study found the VP8* region of the P[8] protein associated with genotype G12 contains 103 amino acids under strong purifying selection (Mijatovic-Rustempasic et al., 2014). The VP4 contains epitopes involved in antibody-mediated neutralization (Dormitzer et al., 2004; Kobayashi et al., 1990; Matsui et al., 1989) as well as functional domains involved in virus attachment and entry into host cells (Estes and Kapikian, 2007). It is likely that multiple selective pressures are influencing the evolution of VP4. VP6 also appears to be under strong purifying selection but the processes involved in the evolution of this protein remain to be determined. Previous studies have reported positive selection in the NSP2, NSP4, and VP7 genes (Donker and Kirkwood, 2012; Mijatovic-Rustempasic et al., 2014; Song and Hao, 2009) but in this study we did not find evidence of this process in our data sets for these 3 genes

The VP7 and VP4 proteins form the outer surface structure of the viral capsid, hence their antigenic regions have been well characterized. RVA immunity is known to be both homotypic, heterotypic and polygenic (Desselberger and Huppertz, 2011). To identify sites that could possibly help escape vaccine derived immunity, we looked at the alignments of the antigenic regions of the RVA strains in this study. For the VP7 gene, seven substitutions were observed in all G9 strains out of which four were at known neutralization escape sites (Hoshino et al., 2005; Hoshino et al., 2004). When compared with Rotarix™ and RotaTeq® only one change Q208I was accompanied by a change in polarity observed in the G9 strains. Change in polarity at this site may possibly help the G9 strains escape neutralization although we did not find similar substitution in the G3 vaccine failure strain. Zeller et al. (Zeller et al., 2012) described a N238D change in G3P[8] strains from Belgium that creates a potential N-linked glycosylation site that is absent in the G3 strain of RotaTeq®. All strains in this study, except the G9 strains, have an N at position 238 indicating the presence of this predicted glycosylation site. For the G9 strains, a D at position 238 gives rise to a predicted integrin binding site instead of a glycosylation site. Whereas the glycosylation site is thought to facilitate viral growth in cell culture systems, the function of the integrin binding site is unknown (Graham et al., 2005). The N238D mutation, however, appears in virulent murine RVA strains produced by serial passage of avirulent RVA strains in mice (Tsugawa et al., 2014). It is interesting to note that even the Rotarix™ VP7 protein contains the same glycosylation site at position. Most of the changes at the VP7 neutralization escape sites identified in this study were conservative in nature. The mutations in the G9 strains were unique to the group but the mutation present in G3 strains were present in all G3 and even some G1 strains in this study. In the VP8* region of the VP4 gene, 7 substitutions were observed out of which 4 were non conservative in nature when compared with the Rotarix™ and the RotaTeq® consensus sequences. Other conserved epitope changes at multiple sites have previously been reported recently in strains circulating in the US and Belgium (Mijatovic-Rustempasic et al., 2014; Zeller et al., 2012). The functional relevance of these changes at known epitopes is yet to be determined. With regard to the non-conservative amino acid substitutions in the VP8* region, the N113D substitution at position 113 and D195G substitution at position 195 involve a change in charge, from neutral to negative and negative to neutral, respectively. Both of these sites lie in known neutralization escape sites and differ from the sequences of Rotarix™ and RotaTeq®. The other non-conservative change was at position 120 where an M120N change was accompanied with change in polarity. In the VP5* region there were three positions were substitutions were observed. Out of the 3, H/Y385D substitution at position 385, a neutralization escape site, was non-conservative with a change in charge. Amino acid residues 382 – 400 in the VP5* region also contain a potential membrane interaction loop and may be essential for viral virulence, especially in facilitating viral attachment or penetration (Dormitzer et al., 2004; Trask et al., 2010), In a cell culture-murine model system, a charge change at this position has been shown to be associated with reversion of an avirulent strain to a virulent one (Tsugawa et al., 2014). It is interesting to note that these substitutions are present in all sequences except the Allele A strains. If these substitutions are responsible for neutralization escape, it would suggest that the Allele A strains would gradually be replaced over time by the other reassortant G1 types due to vaccine derived evolutionary pressures. A more detailed analysis with multiple strains from pre vaccination years is necessary to assess whether these substitutions are actively arising under vaccine pressure.

The main limitation of the genetic analysis performed in this study was the closely related nature of the strains that were sampled. All strains shared a common Wa like genogroup 1 backbone with the only difference being in the VP7 gene (G1/G3/G9). The low genetic distance between the genes of the strains sampled may interfere in understanding better the effect of vaccine pressure, geographical distance, and time on the evolution of these virus strains currently circulating in continental US. A more detailed sampling of multiple genotypes with different backbones is currently underway to determine better the effect of vaccine pressures on circulating strains. Also to test the hypothesis that specific amino acid substitutions can lead to immune evasion of vaccine induced immunity, VF strains should be compared to strains from unvaccinated children that are matched by age, site, and date of illness to control for these variables. Such studies are currently underway at CDC.

5. Conclusion

Large scale full genome sequencing initiatives are necessary to understand the changes in circulating strains post introduction of the vaccine. We were able to capture changes in recent circulating strains that could possibly lead to the rise of vaccine failure strains. We were also able to identify inter-allelic reassortment events in currently circulating G1 strains. Such reassortment events have been reported previously, albeit infrequently, (McDonald et al., 2011; McDonald et al., 2012) and can help in producing possibly strains better suited to escape vaccine derived immune pressure. This study highlights the need for further surveillance and other full genome initiatives to study in detail the evolution of RVA strains currently in circulation.

Supplementary Material

supplementary figures
supplementary table

Acknowledgment

We wish to thank Tara Kerin, Slavica Mijatovic-Rustempasic, David Spiro, and Elizabeth Teel for their contributions to this study. We also wish to thank Rashi Gautam for her critical review of the manuscript.

This project has been funded in part with federal funds from the National Institute of Allergy and Infectious Diseases, National Institutes of Health, Department of Health and Human Services under contract number HHSN272200900007C.

Footnotes

Participants in the National Rotavirus Strain Surveillance System include the following: Kathy Dugaw, Seattle Children's Hospital, Seattle, WA; Gail Bloom, Clarian Health Partners, Indianapolis, IN; Paul A. Yam and Sandra Jameson, Children's Memorial Hospital of Omaha, Omaha, NE; Barbara McKee, Long Beach Memorial Medical Center, Long Beach, CA; Ann Marie Riley, Boston Children's Hospital, Boston, MA; Kenneth Thompson, University of Chicago Medical Center, Chicago, IL; Carolyn Wright and W. Lawrence Drew, University of California, San Francisco, UCSF Medical Center at Mount Zion, San Francisco, CA; Jim Dunn, Cook Children's Medical Center, Fort Worth, TX; and Valerie Hoover, Orlando Regional Medical Center, Orlando, FL.

Participants in the New Vaccine Surveillance Network include the following: Peter G. Szilagyi and Geoffrey A. Weinberg, Department of Pediatrics, University of Rochester School of Medicine and Dentistry, Rochester, NY; Mary Allen Staat, Department of Pediatrics, University of Cincinnati College of Medicine, Cincinnati Children's Hospital Medical Center, Cincinnati, OH; Kathryn M. Edwards and James Chappell, Department of Pediatrics, Vanderbilt University Medical Center, Nashville, TN.

Article summary line: Complete genomes of 33 Genogroup 1 (Wa-like) rotavirus strains collected in multiple cities across the USA during 2006 – 2009 were determined and analyzed.

Conflict of Interest Statement

The authors of this study declare that they have no conflict of interest, financial or otherwise, related to this article.

Disclaimer

The findings and conclusions in this report are those of the author(s) and do not necessarily represent the official position of the Centers for Disease Control and Prevention. Names of specific vendors, manufacturers, or products are included for public health and informational purposes; inclusion does not imply endorsement of the vendors, manufacturers, or products by the Centers for Disease Control and Prevention or the US Department of Health and Human Services.

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