Disease progression and evolution of the HIV-1 env gene in 24 infected infants

https://doi.org/10.1016/j.meegid.2007.10.009Get rights and content

Abstract

We have studied the relationship between disease progression and HIV-1 evolution in 24 infants classified as rapid or non-rapid progressors, during nearly the entire disease progression cycle from infection to AIDS. Specifically, we examined the temporal relationship between clinical status and changes in genetic diversity, divergence, selection and recombination at the C2V3C3 region of the env gene during a period of 3 years. Statistical analyses were performed using linear mixed models that are particularly well-suited for longitudinal studies in which repeated measures are taken from the same patients. We did not observe significant differences in genetic diversity or overall substitution rates between clinical categories. However, the nonsynonymous substitution rate per nonsynonymous site (dN) evolved differently between groups. Changes in dN explained the evolutionary slowdown of the dN/dS ratio in the rapid progressors, while in non-rapid progressors the dN/dS ratio continuously increased through time. The number of positively selected sites had limited power for predicting disease progression. Recombination rate estimates were different among groups, although not significantly in the linear mixed models analysis. They showed some power predicting clinical categories and, interestingly, they were significantly correlated with the frequency of positively selected sites. Overall, the results obtained confirm that viral adaptation in the C2V3C3 region of the env gene is related to disease progression, although the statistical characterization of such pattern seems rather difficult.

Introduction

The broad intrapatient genetic diversity characteristic of the human immunodeficiency virus type 1 (HIV-1) infection is usually assumed to be the result of positive selection, especially at the env gene ( Ross and Rodrigo, 2002, Seibert et al., 1995, Williamson, 2003, Yamaguchi-Kabata and Gojobori, 2000). Early HIV-1 studies suggested that progression to AIDS results from virus adaptation to the host environment (Nowak et al., 1991, Nowak et al., 1996, Wolinsky et al., 1996). Since then, some studies have found a positive relationship between levels of genetic (antigenic) diversity and the rate of disease progression (Strunnikova et al., 1995, Strunnikova et al., 1998), whereas others have found the opposite pattern (Ganeshan et al., 1997, Wolinsky et al., 1996). These apparently contradictory results likely arose because many of these analyses failed to distinguish between adaptive and selectively neutral changes, which is key to understand the interaction between the virus and its host (Williamson, 2003). When this distinction is taken into account, and more patients are compared, it seems clear that positive selection is more prevalent in patients with slow progression rates to AIDS, because their viral population shows higher adaptation rates due to a stronger immune response (Ross and Rodrigo, 2002; although see Viscidi, 1999, Williamson, 2003, Zanotto et al., 1999). Moreover, it has been suggested that an evolutionary slowdown occurs in late infection, caused by the collapse of the immune system, rather than by a reduction in the viral replication rate due to cellular exhaustion (Lemey et al., 2007, Williamson et al., 2005). To further complicate this picture, some studies have shown the occurrence of convergent evolution and the persistence of selection acting at the same sites over long periods of time in patients with slow (Ross and Rodrigo, 2002) and fast progression rates (Strunnikova et al., 1995), while others have failed to observe these patterns (Williamson, 2003), perhaps reflecting the influence of anti-retroviral therapy (Ganeshan et al., 1997, Potter et al., 2006), random genetic drift (Shriner et al., 2004) and recombination (Anisimova et al., 2003) on the distribution of positive selected variants. Moreover, a high portion of the variation at the V3 region of the env gene seems to be neutral (Nielsen and Yang, 1998). Finally, it has been shown that selection in the HIV-1 env gene, though intense, can be context-dependent (Templeton et al., 2004).

Studying the evolutionary relationship of HIV-1 and its host and characterizing the distinct adaptation patterns in different parts of the HIV-1 genome that interact with the immune system will be key to elucidate how HIV-1 overwhelms the immune system and leads to AIDS (Williamson et al., 2005). In this study, we examine in detail the evolution of HIV-1 in 24 infants classified on the basis of progression to AIDS. For that purpose, we have sequenced the C2V3C3 region of the HIV-1 env gene in longitudinal samples (three to seven per patient) obtained from each infant during a period of 3 years. The C2V3C3 region of the env gene is very suitable to study viral adaptation because it is key for entrance of HIV-1 into host cells and is a target of the immune response to HIV-1. The main objective of this study was therefore to decipher the temporal relationship between disease progression and diversity, divergence, selection, and recombination in the HIV-1 envelope gene. Uniquely, because we have sampled infants, we were able to study nearly the entire disease progression cycle – from infection to AIDS – whereas most studies on adults can only begin sampling long after infection and often only shortly before AIDS.

Section snippets

Study population

The study participants were a subset of infants with HIV-1 perinatal infection enrolled in The New York City Perinatal HIV Transmission Collaborative Study, which is an observational cohort study of HIV infected infants born at seven New York City health care institutions since 1986. The enrollment criteria and study protocol design are described in detail elsewhere (Abrams et al., 1995, Thomas et al., 1994). Infants had a medical history, physical examination and phlebotomy done at birth and

Results

The GTR + I + G model was selected as the best-fit model of nucleotide substitution for the combined data set (all patients) (πA = 0.4121, πC = 0.1814, πG = 0.2121, and πT = 0.1943; rCT = 5.3938, rCG = 0.5097, rAT = 0.7055, rAG = 4.0379, and rAC = 1.5957; α = 0.9762 and proportion of invariable sites I = 0.0482). This model is often selected for the HIV-1 env gene (Posada and Crandall, 2001). Upon inspection of the ML tree, we inferred cross-contamination for samples P14.2.3 and P14.2.15, which were eliminated from

Discussion

The study of infected infants provides a comprehensive view of how HIV-1 genetic diversity fluctuates over the entire course of infection leading to AIDS. Most HIV-1 studies are on adults and they only sample at the onset of AIDS, which is well down the timeline from initial infection. Our data have the unique aspect of exploring early infection stages, since the infant's initial samplings were taken close to birth. Similar with other studies (Ganeshan et al., 1997; Shankarappa et al., 1999,

Acknowledgements

This work was supported by NIH grants R01-HD34350 (KAC, RPV) and R01-GM66276 (KAC, DP) and Brigham Young University (EK). DP was supported grant BFU2004-02700 of the Spanish Ministry of Education and Science and by the “Ramon y Cajal” programme of the Spanish government. ACR is currently funded by an Isidro Parga Pondal research fellowship from Xunta de Galicia (Spain). We thank Jing Gu, Samantha Crowe, James Demma and Imran Fatani for generation of sequence data and Emilio Rolán-Alvarez for

References (65)

  • A. Carvajal-Rodriguez et al.

    Recombination favors the evolution of drug resistance in HIV-1 during antiretroviral therapy

    Infect. Genet. Evol.

    (2007)
  • S.J. Potter et al.

    Genetic analyses reveal structured HIV-1 populations in serially sampled T lymphocytes of patients receiving HAART

    Virology

    (2006)
  • G.A. Watterson

    On the number of segregating sites in genetical models without recombination

    Theor. Popul. Biol.

    (1975)
  • E.J. Abrams et al.

    Neonatal predictors of infection status and early death among 332 infants at risk of HIV-1 infection monitored prospectively from birth. New York City Perinatal HIV Transmission Collaborative Study Group

    Pediatrics

    (1995)
  • H. Akaike

    A new look at the statistical model identification

    IEEE Trans. Autom. Control

    (1974)
  • C.L. Althaus et al.

    Stochastic interplay between mutation and recombination during the acquisition of drug resistance mutations in human immunodeficiency virus type 1

    J. Virol.

    (2005)
  • M. Anisimova et al.

    Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites

    Genetics

    (2003)
  • A. Carvajal-Rodriguez et al.

    Recombination estimation under complex evolutionary models with the coalescent composite likelihood method

    Mol. Biol. Evol.

    (2006)
  • R. Chakraborty et al.

    Nef gene sequence variation among HIV-1-infected African children

    HIV Med.

    (2006)
  • K.A. Crandall et al.

    Parallel evolution of drug resistance in HIV: failure of nonsynonymous/synonymous substitution rate ratio to detect selection

    Mol. Biol. Evol.

    (1999)
  • E.L. Delwart et al.

    Genetic relationships determined by a DNA heteroduplex mobility assay: analysis of HIV-1 env genes

    Science

    (1993)
  • Drummond, A.J., Rambaut, A., 2006. BEAST...
  • C.T. Edwards et al.

    Population genetic estimation of the loss of genetic diversity during horizontal transmission of HIV-1

    BMC Evol. Biol.

    (2006)
  • S. Ganeshan et al.

    Human immunodeficiency virus type 1 genetic evolution in children with different rates of development of disease

    J. Virol.

    (1997)
  • B.T. Grenfell et al.

    Unifying the epidemiological and evolutionary dynamics of pathogens

    Science

    (2004)
  • S. Guindon et al.

    A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood

    Syst. Biol.

    (2003)
  • J.P. Huelsenbeck et al.

    A Dirichlet process model for detecting positive selection in protein-coding DNA sequences

    Proc. Natl. Acad. Sci. U.S.A.

    (2006)
  • P. Kellam et al.

    Retroviral recombination can lead to linkage of reverse transcriptase mutations that confer increased zidovudine resistance

    J. Virol.

    (1995)
  • P. Lemey et al.

    Synonymous substitution rates predict HIV disease progression as a result of underlying replication dynamics

    PLoS Comput. Biol.

    (2007)
  • S.L. Liu et al.

    Divergent patterns of progression to AIDS after infection from the same source: human immunodeficiency virus type 1 evolution and antiviral responses

    J. Virol.

    (1997)
  • S.L. Liu et al.

    Selection for human immunodeficiency virus type 1 recombinants in a patient with rapid progression to AIDS

    J. Virol.

    (2002)
  • G.A.T. McVean et al.

    A coalescent based-method for detecting and estimating recombination from gene sequences

    Genetics

    (2002)
  • A. Morris et al.

    Mosaic structure of the human immunodeficiency virus type 1 genome infecting lymphoid cells and the brain: evidence for frequent in vivo recombination events in the evolution of regional populations

    J. Virol.

    (1999)
  • S.V. Muse et al.

    A likelihood approach for comparing synonymous and nonsynonymous nucleotide substitution rates, with application to the chloroplast genome

    Mol. Biol. Evol.

    (1994)
  • R. Nájera et al.

    Genetic recombination and its role in the development of the HIV-1 pandemic

    AIDS

    (2002)
  • R. Nielsen et al.

    Likelihood methods for detecting positively selected amino acid sites and applications to the HIV-1 envelope gene

    Genetics

    (1998)
  • M.A. Nowak et al.

    Antigenic diversity threshold and the development of AIDS

    Science

    (1991)
  • M.A. Nowak et al.

    HIV-1 evolution and disease progression

    Science

    (1996)
  • J.C. Pinheiro et al.

    Mixed-effects Models in S and S-PLUS

    (2000)
  • S.K. Pond et al.

    Site-to-site variation of synonymous substitution rates

    Mol. Biol. Evol.

    (2005)
  • S.L.K. Pond et al.

    Not so different after all: a comparison of methods for detecting amino acid sites under selection

    Mol. Biol. Evol.

    (2005)
  • S.L.K. Pond et al.

    Datamonkey: rapid detection of selective pressure on individual sites of codon alignments

    Bioinformatics

    (2005)
  • Cited by (21)

    • Subtle differences in selective pressures applied on the envelope gene of HIV-1 in pregnant versus non-pregnant women

      2018, Infection, Genetics and Evolution
      Citation Excerpt :

      To estimate selective pressure, we computed ω in all patients based on the entire sequence of the C1-C3 Env segment. Results highlighted overall conservation of the env gene (median ω < 1) in both groups of patients, compatible with a certain degree of purifying selection, which is in agreement with previous reports in non-pregnant adults and children (Carvajal-Rodríguez et al., 2008; Chaillon et al., 2012; Choisy et al., 2004; Leal et al., 2007; Zhang et al., 2010). We then examined the pattern of selection in detail in pregnant and non-pregnant patients.

    • Untangling the influences of unmodeled evolutionary processes on phylogenetic signal in a forensically important HIV-1 transmission cluster

      2014, Molecular Phylogenetics and Evolution
      Citation Excerpt :

      Site-specific likelihood differences also show strong variation between spatially proximate sites in support for mono- vs. paraphyly of CC07’s viral lineages (Fig. 3), although we have not quantitatively compared this distribution to expectations under the inferred pattern of recombination. Strong positive selection is known to occur in env, creating the potential for similar selective environments in different host individuals to drive convergence of env sequences in unrelated lineages (Holmes et al., 1992; Strunnikova et al., 1995; Nielsen and Yang, 1998; Ross and Rodrigo, 2002; Edwards et al., 2006; Carvajal-Rodríguez et al., 2008). Similar to recombination, convergence should produce strong variation in preferred topologies across sites.

    • The evolution of HIV: Inferences using phylogenetics

      2012, Molecular Phylogenetics and Evolution
      Citation Excerpt :

      This exceptional diversity has been examined to infer geographical distribution and dispersion patterns (Lemey et al., 2003; Robbins et al., 2003) and thereby test hypotheses associated with molecular epidemiology (Holmes et al., 1995; Salemi et al., 2008). Phylogenetics has been key to identifying patterns and mechanisms of natural selection (Lemey et al., 2007; Pond et al., 2008; Poon et al., 2010; Templeton et al., 2004), including the intra- and inter-host adaptive forces that shape the evolution of the virus (Carvajal-Rodríguez et al., 2008; Keele et al., 2008a; Salazar-González et al., 2008; Shankarappa et al., 1999), which is essential for effective vaccine development (Frahm et al., 2008). The first applications of phylogenetics to the study of HIV date from the early 1990s and were aimed at inferring the origins of HIV-1 and the classification of HIV into different types (1 and 2), groups (M, N, O within HIV-1), and subtypes (A–D, F–H, and J and K within Group M of HIV-1) (Huet et al., 1990; Fig. 1).

    View all citing articles on Scopus

    Note: Nucleotide sequence data reported in this paper are available in the GenBank database under the accession numbers: AY823998AY824179, AY824250AY824290, AY824329AY824409, and AY824472AY824946. These sequences were submitted as part of an independent analysis of the data set.

    View full text