This article has Open Peer Review reports available.
Codon pairs of the HIV-1 vif gene correlate with CD4+ T cell count
© Bizinoto et al.; licensee BioMed Central Ltd. 2013
Received: 14 March 2012
Accepted: 26 March 2013
Published: 11 April 2013
The human APOBEC3G (A3G) protein activity is associated with innate immunity against HIV-1 by inducing high rates of guanosines to adenosines (G-to-A) mutations (viz., hypermutation) in the viral DNA. If hypermutation is not enough to disrupt the reading frames of viral genes, it may likely increase the HIV-1 diversity. To counteract host innate immunity HIV-1 encodes the Vif protein that binds A3G protein and form complexes to be degraded by cellular proteolysis.
Here we studied the pattern of substitutions in the vif gene and its association with clinical status of HIV-1 infected individuals. To perform the study, unique vif gene sequences were generated from 400 antiretroviral-naïve individuals.
The codon pairs: 78–154, 85–154, 101–157, 105–157, and 105–176 of vif gene were associated with CD4+ T cell count lower than 500 cells per mm3. Some of these codons were located in the 81LGQGVSIEW89 region and within the BC-Box. We also identified codons under positive selection clustered in the N-terminal region of Vif protein, between 21WKSLVK26 and 40YRHHY44 regions (i.e., 31, 33, 37, 39), within the BC-Box (i.e., 155, 159) and the Cullin5-Box (i.e., 168) of vif gene. All these regions are involved in the Vif-induced degradation of A3G/F complexes and the N-terminal of Vif protein binds to viral and cellular RNA.
Adaptive evolution of vif gene was mostly to optimize viral RNA binding and A3G/F recognition. Additionally, since there is not a fully resolved structure of the Vif protein, codon pairs associated with CD4+ T cell count may elucidate key regions that interact with host cell factors. Here we identified and discriminated codons under positive selection and codons under functional constraint in the vif gene of HIV-1.
KeywordsHIV-1 Epistasis APOBEC Vif Hypermutation Positive selection Co-evolution
The APOBEC (apolipoprotein B mRNA-editing catalytic polypeptide) gene family includes several members, APOBEC1, APOBEC2, APOBEC3 and APOBEC4 that have cytidine deaminase activity [1–3]. Notably, two genes of APOBEC3 (APOBEC3G and APOBEC3F) have been linked to innate immunity, and their ability to restrain retroviral infections has been widely recognized [4, 5]. APOBEC3G (A3G) induces cytidine deamination (C→U) in the negative strand of HIV-1 during reverse transcription, hence inducing substitutions of guanosines for adenosines (G→A) in the positive strand of the viral DNA. This mechanism is known as hypermutation and may cause the appearance of stop codons followed by the complete loss of reading frames of the viral genes. HIV-1 counteracts A3G activity through ubiquitination of this host protein through the activity of Vif proteins. Vif proteins assemble with viral-specific E3 ubiquitin ligase through its interaction with cellular Cullin5 (Cul5)-ElonginB-ElonginC proteins, inducing ubiquitination of A3G and consequent degradation by the proteasomal complex [6–10]. Hypermutation is not enough to curb HIV-1 infection because proviruses with varying amounts of G→A mutations are commonly observed in the host genome [11–13]. Furthermore, the polymorphisms in the vif gene have been associated with more or less efficacy to neutralize A3G . For these reasons, it has been hypothesized that when G→A mutations are ineffective in neutralizing viral genomes, the side effect is that A3G can actually promote HIV-1 diversification [14, 15].
The interaction between the cellular A3G and the vif gene of HIV likely emerged from a process of co-adaptation due to recurrent retroviral infections during the evolutionary history of primates [2, 16]. Specifically, the repeated encounters with retroviruses probably promoted the fixation of the allelic variants in the genes of the human family of the APOBEC [17–20].
Recently, we found that A3G polymorphisms are mostly unrelated with CD4+ T cell counts of HIV-1 infected Brazilians . Thus, population-based studies may provide conflicting results regarding the overall effect of A3G-vif interactions [5, 21–23]. To gain more insights on the A3G-HIV interaction, we used codon-based approaches to determine the function of amino acid substitutions of Vif protein. The study was made through the analysis of 400 vif gene sequences obtained from HIV-1 infected drug-naïve individuals.
HIV-1 infected individuals
This study was approved by the Ethics Committee of the Federal University of São Paulo and by the Brazilian Ministry Health; all biological samples were obtained in full accordance with signed informed consent forms.
Proviral DNA was extracted from heparinized peripheral blood obtained from 400 HIV-1 infected individuals that were drug-naïve (not receiving any antiretroviral therapy) and asymptomatic when samples were collected. From each patient one unique sequence of HIV-1 vif gene was generated, then our study focused on the diversity of the virus at the population level. The study group represented almost equally the male (55.5%) and female (45.5%) populations and was composed of three ethnics groups: white (49.2%), mulatto (41.6%) and black (9.2%) individuals. The CD4 counts (cells/mm3) ranged from 20 to 5362 and the virus load ranged from 80 to 7.8 x 107 (RNA copies/ml of plasma). HIV-1-infected individuals sampled from São Paulo city between 1989 and 2006 comprised our target population. These individuals were enrolled in the AIDS program of the Brazilian Ministry of Health.
PCR and sequencing of the vif gene of HIV-1
The vif sequence was amplified by a nested PCR. The primers were designed to cover the entire vif gene, according to the reference sequence HXB2 (HIV Sequence Database). The first round was performed with the primers, Platinum Taq DNA Polymerase, 10X Reaction Buffer, MgCl2 (Invitrogen, USA) and deoxyribonucleotide triphosphates (dNTP; GE Healthcare, USA). The second-round PCR was carried out using 5 μl of the first-round product and internal primers. Amplified vif DNA was purified and then sequenced using the BigDye Terminator kit, version 3.1 (Applied Biosystems/Perkin Elmer, Foster City, CA). The samples were electrophoresed on an ABI 3130 genetic analyzer, and the sequencing data were analyzed using ABI software Sequencing Analysis Software.
Sequences Analysis. Nucleotide and protein sequence analyses and edits were performed using the Sequencher DNA Sequence Assembly Software (Gene Codes Corporation, USA).
Hypermutation detection in the integrase gene of HIV-1
We used a previously described approach to detect the presence of hypermutation in the PCR products of the integrase gene of HIV-1 . Briefly, the PCR products were initially analyzed on 1% agarose gels to confirm amplification. After that, a second electrophoresis was performed with HA yellow (9 μL/mL) incorporated into the agarose gel solution at 65°C and pH 7.5. The electrophoresis was performed at 80 V in 0.5× Tris-borate-EDTA (TBE) for 150 min. The HA yellow gel was visualized after immersion in a solution of ethidium bromide, using the Geldoc-it TS Imaging Systems BioImaging (UVP, Cambridge, CA, EUA). HA yellow is a compound consisting of the DNA ligand, bisbenzamide, covalently linked to polyethylene glycol (PEG) (Resolve-It Kit - Vector Laboratories, Burlingname, CA, USA). Bisbenzamide binds preferentially to AT-rich regions in the DNA and, when coupled to PEG, retards DNA mobility during gel electrophoresis according to the AT content. We used three distinct samples that independently amplified as negative (no hypermutation) and positive controls (hypermutated). The hypermutation statuses of the controls were confirmed by bacterial cloning followed by sequencing.
Sequence alignment and phylogenetic inference
Initially, the sequences of the vif gene of HIV-1 were aligned using the ClustalX program . Sequences with stop codons and hypermutations were excluded from the analyses. We used the Hypermut software (http://www.hiv.lanl.gov/content/sequence/HYPERMUT/hypermut.html).
After this editing process, the sequences were manually aligned using the SE-AL program, version 2.0 (Department of Zoology, Oxford University; http://evolve.zoo.ox.ac.uk/software/). To construct maximum likelihood (ML) trees, we used the HKY model , as implemented in the PhyML software . These trees were used mainly to the selective regimen analysis.
Association of HIV vif gene and CD4+ cell counts
We investigated whether individual codons or pairs of codons in vif gene were associated with levels of CD4+ T cell counts. To do that linear regression and permutation tests were used. The log-transformed CD4 counts were regressed on the amino acids or amino acid pairs. To account for multiplicity, we generated 1000 sets of samples under the null hypothesis of no association by permuting the CD4+T counts. The p-values obtained by the log likelihood ratio statistics were contrasted with the null distribution of minimum p-values among amino acid positions with SNPs and pairs of these positions.
Covariation among codons based on phylogenies
A Bayesian Graph method (BGM) was used to explore covariation among amino acids in codons of the vif gene taking into account the phylogenetic information of the sequences . Therefore, BGM considers the potential bias due to the founder effect and relaxes the assumption of pairwise associations. BMG reconstructs the maximum likelihood of evolutionary history of the extant sequences, and then it analyzes the joint probability distribution of substitution events among sites in the sequences through a Bayesian graph model. The method was used to detect co-evolving sites in vif. The analyses were performed assuming a GTR model , and sites with a marginal posterior probability of 0.85 were considered to be under epistasis. The analysis was performed on the Datamonkey web server (http://www.datamonkey.org).
Detection of selective pressure
We used a codon-based maximum likelihood method to estimate the selection pressures of the vif sequences. This approach estimates the likelihood of distinct models of codon evolution and computes the ratio (d N /d S =ω) of the number of nonsynonymous (d N ) and synonymous (d S ) substitution rates between sites considering the phylogenetic relationships of the sequences.
The nonsynonymous/synonymous rate ratio (ω) determines selective pressures at protein level. When selection (neutral) has no effect on the fitness the nonsynonymous and the synonymous mutations will occur at the same rates (d N =d S ).
Situations where nonsynonymous mutations are deleterious, negative (purifying) selection will reduce their rate of fixation (d N <d S ). If nonsynonymous mutations raise the fitness, their rate will be increased by positive selection (d N >d S ).
We used the following codon models. The one-ratio model (M0) assumes a single ω for all sites in the alignment and is the simplest model. The neutral model (M1) allows for different proportions of conserved sites (ω0=0) and neutral sites (ω1=1), both estimated from the data. Model 1 is the null hypothesis to test for positive selection. The selection model (M2) extends M1 and incorporates an additional class of sites with ω ratios assuming values higher than one (ω2 > 1). Significant evidence for positive selection is provided if M2 significantly reject the null hypotheses, M0 and M1, and if the favored models contain a class of codons with ω > 1. Statistical significance can be compared using a standard likelihood ratio test (LRT). These models are implemented in the CODEML program from the PAML v.4 package (http://abacus.gene.ucl.ac.uk/software/paml.html) .
Diversity of vif gene
To characterize the sequences of the HIV-1 vif gene from Brazilians, we analyzed the nucleotide and amino acid substitutions on a site-by-site basis. The overall nucleotide distance of 235 subtype B isolates in the alignment of 581 nucleotides was 0.031±0.004. The translated Vif sequence of 192 amino acids identified 22 singletons, 53 conserved and 138 variable sites. In general the amino acid composition was relatively conserved among subtypes in Brazil and all regions with biological functions were equally conserved. The genetic diversity was estimated assuming the HKY85 model and the analysis were performed using Mega 4.0 software .
Pairs of codons in vif gene associated with CD4+ cells
Coevolving sites in the vif gene
By using a posterior probability of 0.85, the BGM analysis detected three pairs of codons (i.e., 80–83, 80–86 and 83–144) where amino acids were coevolving in vif gene. These sites were not the same epistatic sites identified by regression/permutation, although they were concentrated in a specific genomic region of vif between sites 78 to 86 and within the BC-box (see blue dashed lines in the Figure 1 and magenta dotted lines in the Figure 3). However when we reduced the threshold of the posterior distribution to 0.5, various other sites were indicated to be under epistasis, including those identified by the permutation analysis.
Adaptive mutations in the vif gene
While hypermutation induced by A3G activity is a natural barrier against retroviruses it is not enough to restrain HIV-1 infection. Sometimes, A3G activity can actually increase HIV-1 diversification [14, 15] because G-to-A hypermutation is not always effective to neutralize all viral genomes within a specific host. Our results suggest that the diversity in the HIV-1 vif gene is highly associated with adaptation to the host proteins, mainly to increase interaction with cellular components (i.e., elongins and A3G and A3F) to induce APOBEC3 proteasomal degradation.
Particularly, codons under positive selection were more concentrated in a region between the 21WKSLVK26 and 40YRHHY44 motifs (i.e., 31, 33, 37 and 39). Interestingly, the N-terminal region of Vif protein binds selectively HIV-1 genomic RNA  and sites in this region have DNA/RNA binding properties and also interact with A3G/F [35, 36]. Additionally, a study showed that the charge of amino acids located between 21WKSLVK26 and 40YRHHY44 motifs that are essential for maintaining the ability of vif to bind A3G . Furthermore, it has been shown that the N-terminal region of Vif protein is highly structured, in contrast to the unstructured and flexible C-terminal [41–43]. Likely, the organized N-terminal structure of Vif functions as a connector that binds to A3G/F proteins and DNA/DNA molecules. On the other hand, positively selected sites detected in the C-terminal region of Vif protein were more dispensed. They were found within the BC-Box and Cullin-Box (i.e., 127), which both assemble with cellular components to induce A3G proteasomal degradation [6, 43–45]. Positive selection was also detected in the vicinity of the PPLP motif (i.e., 159), which controls multimerization of Vif proteins . We also found one codon under positive selection (i.e., 168) in a region of Vif protein involved in the interaction with Gag, NCp7 and with the cellular membrane . It is worth to note that in the N-terminal region of Vif protein sites under positive selection are clustered between the 21WKSLVK26 and 40YRHHY44 motifs whereas in the C-terminal they tend to be dispersed (see Figure 1). Since Vif protein is highly structured at the N-terminal region, contrasting with the unstructured C-terminal [41, 42]. Therefore the N-terminal portion of Vif protein tends to be more protected while the C-terminal is solvent exposed and prone to immune recognition. Consequently adaptive evolution in vif gene could be related with the host immune surveillance against viral proteins. However, there are various positively selected sites outside CTL epitope regions. Additionally, wide vif sequence intervals in which many CTL epitopes have been empirically detected show no evidence of positive selection. Furthermore, selection driven by antibody evasion or host cell adaptation is rarely detected by population-based analysis [38, 48, 49]. Indeed, our results showing a distinct pattern of distribution of positively selected sites between N and C terminals of Vif protein mirrors the structural organization of this viral protein. For these reasons, positive selection detected in vif codons likely emerged as an adaptive response to optimize HIV-1 RNA recognition and neutralization of A3G/F in the population.
The comparison of amino acids of vif sequences revealed a limited variability in regions related with A3G/F activity, such as the regions 14DRMR17 and 40YRHHY44, which are important for vif-induced degradation of A3G [40, 50]. This conservation of vif motifs may indicate a significant evolutionary constraint that has been operating on this viral gene even among distinct lineages. Indeed, we found that most codons (60%) of vif gene are predominantly under purifying selection, and perhaps this pattern is needed to preserve its biological function during the viral life cycle. Likewise, HIV-1 nef gene is similarly under strong purifying selection [37, 51]. Nevertheless, Nef is a multifunctional protein, and this feature can be observed by its plasticity, represented by extensive polymorphism and amino acid length variations that can be detected both in population samples and in the viral population within a single individual as well.
In addition, an attempt was made to establish the influence of the patients’ statuses on the selective regimen of HIV-1. In a previous population-level studies, we observed that CD4+ T cell counts higher than 200 cells/μl were associated with increased dN/dS values in the env gene of HIV-1 subtype B [48, 49, 52]. For this reason, we measured the intensity of positive selection in the vif gene from datasets categorized into three distinct levels of CD4 counts (>200; 200–400 and <400). We found no difference in the mean dN/dS among these data sets (3.65, 3.85 and 3.09 respectively).
Perhaps our most remarkable finding was the identification of five pairs of codons (i.e., 78–154, 85–154, 101–157, 105–157, and 105–176 pairs) in the vif gene and their association with CD4+ cell levels lower than 500 cells per mm3. In each pair (epistatic codons) distinct amino acids combination were associated with distinct levels of CD4+ cells (see Figure 2 for a details). Notably, these pairs of codons were located mainly in the C-terminal of Vif protein (see Figure 1). It has been shown that the mutation 105QLI107 to 105AAV107 reduces the infectivity of HIV by 2% . The amino acids between the 154th and 157th positions of the vif gene comprise the BC-box, the region that binds cellular elongin B and C to form complexes that trigger the ubiquitination and proteasomal degradation of the A3G proteins . Since codons 154 and 157 are located in the alpha-helix of the BC-box, it is likely that certain amino acids in these sites may affect the interaction with the cellular elongin B and C complex and thereby affect the efficacy of Vif-induced A3G proteasomal degradation. In addition, the 161PPLP164 motif is fundamental to vif multimerization and interaction with cellular proteins [41, 44, 46]. Remarkably, proline-to-alanine substitutions in the 161PPLP164 motif have no effect to the vif structure although it decreased the ability this protein to form oligomers . These findings suggest that domains in the C-terminal of Vif protein fold independently of each other and the flexibility of these domains is required to interact directly with distinct cellular counterparts [41, 42]. Thus, we postulate that epistatic effect observed in pairs of codons, indicate electrostatic interaction of certain pairs of amino acids required to Vif activity.
The presence of co-evolving sites was further investigated using a Bayesian graph model that explores associations between codon sites and accounts for the phylogenetic sign of the sequences. The results indicated that amino acids at sites 80–83, 80–86 and 83–144 of vif co-evolve in phylogenies constructed with vif gene of the HIV-1. Interestingly, although both methods did not indicate the same sites, these results corroborate the identification of a region between sites 78 to 86 of HIV-1 vif gene that has many sites co-evolving with codons located within the BC-box.
The host-virus interaction between A3G and vif are likely to affect AIDS in many instances. Conversely, the adaptive evolution in the HIV-1 vif gene is mainly explained by a response optimized to neutralize A3G activity. Co-evolution detected in some codons suggests that regions of the Vif protein are highly constrained and may have important function to the virus activity. Here, we identified and discriminated codons under positive selection and codons under functional constraint in the vif gene of HIV-1.
We would like to express our sincere gratitude to all patients who contributed to this study. The authors also extend their gratitude to the AIDS program of the Brazilian Ministry Health for providing access to patient information and blood samples. This work was supported by the Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP, Foundation for the Support of Research in the State of São Paulo; grant no. 06/50109-5) and by the Japan Society for the Promotion of Science (SPS KAKENHI) Grant-in-Aid for Scientific Research (B) 19300094.
- Henriet S, Richer D, Bernacchi S, Decroly E, Vigne R, Ehresmann B, Ehresmann C, Paillart JC, Marquet R: Cooperative and specific binding of Vif to the 5' region of HIV-1 genomic RNA. J Mol Biol. 2005, 354 (1): 55-72. 10.1016/j.jmb.2005.09.025.View ArticlePubMedGoogle Scholar
- Chiu YL, Greene WC: The APOBEC3 cytidine deaminases: an innate defensive network opposing exogenous retroviruses and endogenous retroelements. Annu Rev Immunol. 2008, 26: 317-353. 10.1146/annurev.immunol.26.021607.090350.View ArticlePubMedGoogle Scholar
- Sheehy AM, Gaddis NC, Choi JD, Malim MH: Isolation of a human gene that inhibits HIV-1 infection and is suppressed by the viral Vif protein. Nature. 2002, 418 (6898): 646-650. 10.1038/nature00939.View ArticlePubMedGoogle Scholar
- Esnault C, Heidmann O, Delebecque F, Dewannieux M, Ribet D, Hance AJ, Heidmann T, Schwartz O: APOBEC3G cytidine deaminase inhibits retrotransposition of endogenous retroviruses. Nature. 2005, 433 (7024): 430-433. 10.1038/nature03238.View ArticlePubMedGoogle Scholar
- Pace C, Keller J, Nolan D, James I, Gaudieri S, Moore C, Mallal S: Population level analysis of human immunodeficiency virus type 1 hypermutation and its relationship with APOBEC3G and vif genetic variation. J Virol. 2006, 80 (18): 9259-9269. 10.1128/JVI.00888-06.View ArticlePubMedPubMed CentralGoogle Scholar
- Kobayashi M, Takaori-Kondo A, Miyauchi Y, Iwai K, Uchiyama T: Ubiquitination of APOBEC3G by an HIV-1 Vif-Cullin5-Elongin B-Elongin C complex is essential for Vif function. J Biol Chem. 2005, 280 (19): 18573-18578. 10.1074/jbc.C500082200.View ArticlePubMedGoogle Scholar
- Marin M, Rose KM, Kozak SL, Kabat D: HIV-1 Vif protein binds the editing enzyme APOBEC3G and induces its degradation. Nat Med. 2003, 9 (11): 1398-1403. 10.1038/nm946.View ArticlePubMedGoogle Scholar
- Sheehy AM, Gaddis NC, Malim MH: The antiretroviral enzyme APOBEC3G is degraded by the proteasome in response to HIV-1 Vif. Nat Med. 2003, 9 (11): 1404-1407. 10.1038/nm945.View ArticlePubMedGoogle Scholar
- Yu X, Yu Y, Liu B, Luo K, Kong W, Mao P, Yu XF: Induction of APOBEC3G ubiquitination and degradation by an HIV-1 Vif-Cul5-SCF complex. Science. 2003, 302 (5647): 1056-1060. 10.1126/science.1089591.View ArticlePubMedGoogle Scholar
- Zhang W, Chen G, Niewiadomska AM, Xu R, Yu XF: Distinct determinants in HIV-1 Vif and human APOBEC3 proteins are required for the suppression of diverse host anti-viral proteins. PLoS One. 2008, 3 (12): e3963-10.1371/journal.pone.0003963.View ArticlePubMedPubMed CentralGoogle Scholar
- Armitage AE, Katzourakis A, de Oliveira T, Welch JJ, Belshaw R, Bishop KN, Kramer B, McMichael AJ, Rambaut A, Iversen AK: Conserved footprints of APOBEC3G on Hypermutated human immunodeficiency virus type 1 and human endogenous retrovirus HERV-K(HML2) sequences. J Virol. 2008, 82 (17): 8743-8761. 10.1128/JVI.00584-08.View ArticlePubMedPubMed CentralGoogle Scholar
- Kijak GH, Janini LM, Tovanabutra S, Sanders-Buell E, Arroyo MA, Robb ML, Michael NL, Birx DL, McCutchan FE: Variable contexts and levels of hypermutation in HIV-1 proviral genomes recovered from primary peripheral blood mononuclear cells. Virology. 2008, 376 (1): 101-111. 10.1016/j.virol.2008.03.017.View ArticlePubMedGoogle Scholar
- Land AM, Ball TB, Luo M, Pilon R, Sandstrom P, Embree JE, Wachihi C, Kimani J, Plummer FA: Human immunodeficiency virus (HIV) type 1 proviral hypermutation correlates with CD4 count in HIV-infected women from Kenya. J Virol. 2008, 82 (16): 8172-8182. 10.1128/JVI.01115-08.View ArticlePubMedPubMed CentralGoogle Scholar
- Jern P, Russell RA, Pathak VK, Coffin JM: Likely role of APOBEC3G-mediated G-to-A mutations in HIV-1 evolution and drug resistance. PLoS Pathog. 2009, 5 (4): e1000367-10.1371/journal.ppat.1000367.View ArticlePubMedPubMed CentralGoogle Scholar
- Sadler HA, Stenglein MD, Harris RS, Mansky LM: APOBEC3G Contributes to HIV-1 Variation Through Sublethal Mutagenesis. J Virol. 2010, 84 (14): 7396-7404. 10.1128/JVI.00056-10.View ArticlePubMedPubMed CentralGoogle Scholar
- Conticello SG, Thomas CJ, Petersen-Mahrt SK, Neuberger MS: Evolution of the AID/APOBEC family of polynucleotide (deoxy)cytidine deaminases. Mol Biol Evol. 2005, 22 (2): 367-377.View ArticlePubMedGoogle Scholar
- Conticello SG: The AID/APOBEC family of nucleic acid mutators. Genome Biol. 2008, 9 (6): 229-10.1186/gb-2008-9-6-229.View ArticlePubMedPubMed CentralGoogle Scholar
- Di Rienzo A, Hudson RR: An evolutionary framework for common diseases: the ancestral-susceptibility model. Trends Genet. 2005, 21 (11): 596-601. 10.1016/j.tig.2005.08.007.View ArticlePubMedGoogle Scholar
- Jern P, Stoye JP, Coffin JM: Role of APOBEC3 in genetic diversity among endogenous murine leukemia viruses. PLoS Genet. 2007, 3 (10): 2014-2022.View ArticlePubMedGoogle Scholar
- Sawyer SL, Emerman M, Malik HS: Ancient adaptive evolution of the primate antiviral DNA-editing enzyme APOBEC3G. PLoS Biol. 2004, 2 (9): E275-10.1371/journal.pbio.0020275.View ArticlePubMedPubMed CentralGoogle Scholar
- Bizinoto MC, Leal E, Diaz RS, Janini LM: Loci polymorphisms of the APOBEC3G gene in HIV type 1-infected Brazilians. AIDS Res Hum Retroviruses. 2011, 27 (2): 137-141. 10.1089/aid.2010.0146.View ArticlePubMedGoogle Scholar
- An P, Bleiber G, Duggal P, Nelson G, May M, Mangeat B, Alobwede I, Trono D, Vlahov D, Donfield S: APOBEC3G genetic variants and their influence on the progression to AIDS. J Virol. 2004, 78 (20): 11070-11076. 10.1128/JVI.78.20.11070-11076.2004.View ArticlePubMedPubMed CentralGoogle Scholar
- Do H, Vasilescu A, Diop G, Hirtzig T, Heath SC, Coulonges C, Rappaport J, Therwath A, Lathrop M, Matsuda F: Exhaustive genotyping of the CEM15 (APOBEC3G) gene and absence of association with AIDS progression in a French cohort. J Infect Dis. 2005, 191 (2): 159-163. 10.1086/426826.View ArticlePubMedGoogle Scholar
- Janini M, Rogers M, Birx DR, McCutchan FE: Human immunodeficiency virus type 1 DNA sequences genetically damaged by hypermutation are often abundant in patient peripheral blood mononuclear cells and may be generated during near-simultaneous infection and activation of CD4(+) T cells. J Virol. 2001, 75 (17): 7973-7986. 10.1128/JVI.75.17.7973-7986.2001.View ArticlePubMedPubMed CentralGoogle Scholar
- Thompson JD, Gibson TJ, Plewniak F, Jeanmougin F, Higgins DG: The CLUSTAL_X windows interface: flexible strategies for multiple sequence alignment aided by quality analysis tools. Nucleic Acids Res. 1997, 25 (24): 4876-4882. 10.1093/nar/25.24.4876.View ArticlePubMedPubMed CentralGoogle Scholar
- Hasegawa M, Kishino H, Yano T: Dating of the human-ape splitting by a molecular clock of mitochondrial DNA. J Mol Evol. 1985, 22 (2): 160-174. 10.1007/BF02101694.View ArticlePubMedGoogle Scholar
- Guindon S, Gascuel O: A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. Syst Biol. 2003, 52 (5): 696-704. 10.1080/10635150390235520.View ArticlePubMedGoogle Scholar
- Poon AF, Lewis FI, Pond SL, Frost SD: An evolutionary-network model reveals stratified interactions in the V3 loop of the HIV-1 envelope. PLoS Comput Biol. 2007, 3 (11): e231-10.1371/journal.pcbi.0030231.View ArticlePubMedPubMed CentralGoogle Scholar
- Lio P, Goldman N: Models of molecular evolution and phylogeny. Genome Res. 1998, 8 (12): 1233-1244.PubMedGoogle Scholar
- Yang Z: PAML 4: phylogenetic analysis by maximum likelihood. Mol Biol Evol. 2007, 24 (8): 1586-1591. 10.1093/molbev/msm088.View ArticlePubMedGoogle Scholar
- Tamura K, Dudley J, Nei M, Kumar S: MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol. 2007, 24 (8): 1596-1599. 10.1093/molbev/msm092.View ArticlePubMedGoogle Scholar
- Balaji S, Kalpana R, Shapshak P: Paradigm development: comparative and predictive 3D modeling of HIV-1 Virion Infectivity Factor (Vif). Bioinformation. 2006, 1 (8): 290-309. 10.6026/97320630001290.View ArticlePubMedPubMed CentralGoogle Scholar
- Anisimova M, Nielsen R, Yang Z: Effect of recombination on the accuracy of the likelihood method for detecting positive selection at amino acid sites. Genetics. 2003, 164 (3): 1229-1236.PubMedPubMed CentralGoogle Scholar
- Martins Lde O, Leal E, Kishino H: Phylogenetic detection of recombination with a Bayesian prior on the distance between trees. PLoS One. 2008, 3 (7): e2651-10.1371/journal.pone.0002651.View ArticlePubMedGoogle Scholar
- Bernacchi S, Henriet S, Dumas P, Paillart JC, Marquet R: RNA and DNA binding properties of HIV-1 Vif protein: a fluorescence study. J Biol Chem. 2007, 282 (36): 26361-26368. 10.1074/jbc.M703122200.View ArticlePubMedGoogle Scholar
- Mercenne G, Bernacchi S, Richer D, Bec G, Henriet S, Paillart JC, Marquet R: HIV-1 Vif binds to APOBEC3G mRNA and inhibits its translation. Nucleic Acids Res. 2010, 38 (2): 633-646. 10.1093/nar/gkp1009.View ArticlePubMedGoogle Scholar
- Cavalieri E, Florido C, Leal E, Machado DM, Camargo M, Diaz RS, Janini LM: Intrahost and interhost variability of the HIV type 1 nef gene in Brazilian children. AIDS Res Hum Retroviruses. 2009, 25 (11): 1129-1140. 10.1089/aid.2009.0061.View ArticlePubMedGoogle Scholar
- Lemey P, Rambaut A, Pybus OG: HIV evolutionary dynamics within and among hosts. AIDS Rev. 2006, 8 (3): 125-140.PubMedGoogle Scholar
- Poon AF, Swenson LC, Dong WW, Deng W, Kosakovsky Pond SL, Brumme ZL, Mullins JI, Richman DD, Harrigan PR, Frost SD: Phylogenetic analysis of population-based and deep sequencing data to identify coevolving sites in the nef gene of HIV-1. Mol Biol Evol. 2010, 27 (4): 819-832. 10.1093/molbev/msp289.View ArticlePubMedGoogle Scholar
- Chen G, He Z, Wang T, Xu R, Yu XF: A patch of positively charged amino acids surrounding the human immunodeficiency virus type 1 Vif SLVx4Yx9Y motif influences its interaction with APOBEC3G. J Virol. 2009, 83 (17): 8674-8682. 10.1128/JVI.00653-09.View ArticlePubMedPubMed CentralGoogle Scholar
- Bernacchi S, Mercenne G, Tournaire C, Marquet R, Paillart JC: Importance of the proline-rich multimerization domain on the oligomerization and nucleic acid binding properties of HIV-1 Vif. Nucleic Acids Res. 2011, 39 (6): 2404-2415. 10.1093/nar/gkq979.View ArticlePubMedGoogle Scholar
- Marcsisin SR, Narute PS, Emert-Sedlak LA, Kloczewiak M, Smithgall TE, Engen JR: On the solution conformation and dynamics of the HIV-1 viral infectivity factor. J Mol Biol. 2011, 410 (5): 1008-1022. 10.1016/j.jmb.2011.04.053.View ArticlePubMedPubMed CentralGoogle Scholar
- Stanley BJ, Ehrlich ES, Short L, Yu Y, Xiao Z, Yu XF, Xiong Y: Structural insight into the human immunodeficiency virus Vif SOCS box and its role in human E3 ubiquitin ligase assembly. J Virol. 2008, 82 (17): 8656-8663. 10.1128/JVI.00767-08.View ArticlePubMedPubMed CentralGoogle Scholar
- Donahue JP, Vetter ML, Mukhtar NA, D'Aquila RT: The HIV-1 Vif PPLP motif is necessary for human APOBEC3G binding and degradation. Virology. 2008, 377 (1): 49-53. 10.1016/j.virol.2008.04.017.View ArticlePubMedPubMed CentralGoogle Scholar
- He Z, Zhang W, Chen G, Xu R, Yu XF: Characterization of conserved motifs in HIV-1 Vif required for APOBEC3G and APOBEC3F interaction. J Mol Biol. 2008, 381 (4): 1000-1011. 10.1016/j.jmb.2008.06.061.View ArticlePubMedGoogle Scholar
- Yang S, Sun Y, Zhang H: The multimerization of human immunodeficiency virus type I Vif protein: a requirement for Vif function in the viral life cycle. J Biol Chem. 2001, 276 (7): 4889-4893. 10.1074/jbc.M004895200.View ArticlePubMedGoogle Scholar
- Wissing S, Galloway NL, Greene WC: HIV-1 Vif versus the APOBEC3 cytidine deaminases: an intracellular duel between pathogen and host restriction factors. Mol Aspects Med. 2010, 31 (5): 383-397. 10.1016/j.mam.2010.06.001.View ArticlePubMedPubMed CentralGoogle Scholar
- Leal E, Janini M, Diaz RS: Selective pressures of human immunodeficiency virus type 1 (HIV-1) during pediatric infection. Infect Genet Evol. 2007, 7 (6): 694-707. 10.1016/j.meegid.2007.07.008.View ArticlePubMedGoogle Scholar
- Leal E, Casseb J, Hendry M, Busch MP, Diaz RS: Relaxation of adaptive evolution during the HIV-1 infection owing to reduction of CD4+ T cell counts. PLoS One. 2012, 7 (6): e39776-10.1371/journal.pone.0039776.View ArticlePubMedPubMed CentralGoogle Scholar
- Russell RA, Pathak VK: Identification of two distinct human immunodeficiency virus type 1 Vif determinants critical for interactions with human APOBEC3G and APOBEC3F. J Virol. 2007, 81 (15): 8201-8210. 10.1128/JVI.00395-07.View ArticlePubMedPubMed CentralGoogle Scholar
- Walker PR, Ketunuti M, Choge IA, Meyers T, Gray G, Holmes EC, Morris L: Polymorphisms in Nef associated with different clinical outcomes in HIV type 1 subtype C-infected children. AIDS Res Hum Retroviruses. 2007, 23 (2): 204-215. 10.1089/aid.2006.0080.View ArticlePubMedGoogle Scholar
- Diaz RS, Leal E, Sanabani S, Sucupira MC, Tanuri A, Sabino EC, Janini LM: Selective regimes and evolutionary rates of HIV-1 subtype B V3 variants in the Brazilian epidemic. Virology. 2008, 381 (2): 184-193. 10.1016/j.virol.2008.08.014.View ArticlePubMedGoogle Scholar
- Simon JH, Sheehy AM, Carpenter EA, Fouchier RA, Malim MH: Mutational analysis of the human immunodeficiency virus type 1 Vif protein. J Virol. 1999, 73 (4): 2675-2681.PubMedPubMed CentralGoogle Scholar
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2334/13/173/prepub
This article is published under license to BioMed Central Ltd. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.