Influence of CD4 + T cell counts on viral evolution in HIV-infected individuals undergoing...

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Virology 330 (20

Influence of CD4+ T cell counts on viral evolution in HIV-infected

individuals undergoing suppressive HAART

Eric Lorenzoa,*, Maria C. Colona, Sharilyn Almodovara, Irvin M. Maldonadoa, Sandra Gonzaleza,

Sonia E. Costaa, Martin D. Hilla, Rafael Mendozab, Gladys Sepulvedab, Richard Yanagiharac,

Vivek Nerurkarc, Rakesh Kumara, Yasuhiro Yamamuraa, Walter A. Scottd, Anil Kumara

aAIDS Research Program, Ponce School of Medicine, Ponce 00732, Puerto RicobDepartment of Health Immunology Clinic, Ponce 00731, Puerto Rico

cRetrovirology Research Laboratory, University of Hawaii at Manoa, Hawaii 96816, USAdDepartment of Biochemistry and Molecular Biology, University of Miami 33124, USA

Received 19 June 2004; returned to author for revision 6 August 2004; accepted 3 September 2004

Available online 14 October 2004

Abstract

We analyzed the viral C2–V4 envelope diversity, glycosylation patterns, and dS/dN ratios of plasma HIV-1 in an attempt to better

understand the complex interaction between viral quasispecies and the host-selective pressures pre- and post-HAART. Phylogenetic analysis

of the envelope gene of five patients revealed monophyletic clustering in patients with higher CD4+ T cell counts and sequence intermingling

in those with lower CD4+ T cells in relation to the stage of HAART. Our analyses also showed clear shifts in N-linked glycosylation patterns

in patients with higher CD4+ T cells, suggesting possible distinct immunological pressures pre- and post-HAART. The relative preponderance

of synonymous/nonsynonymous changes in the envelope region suggested a positive selection in patients with higher CD4+ T cells, whereas

lack of evidence for positive selection was found in the patients with lower CD4+ T cells. An exception to the last analysis occurred in the

only patient who reached complete viral suppression, maybe due to drug pressure exerted over the pol gene that may obscure the immune

pressure/selection at the envelope in this analysis. All these indications may suggest that even when HAART generates viral suppression,

quasispecies evolve in the envelope gene probably resulting from host-selective pressure.

D 2004 Elsevier Inc. All rights reserved.

Keywords: HIV; Envelope; HAART; CD4+ T cell counts; Phylogeny; N-linked glycosylation; Synonymous and nonsynonymous nucleotide substitution

Introduction

Human immunodeficiency virus type 1 (HIV-1) repli-

cation is characterized by a high degree of viral sequence

variation, primarily due to mutations introduced by the

error-prone reverse transcriptase that leads into development

of distinct viral quasispecies. Therefore, even in a single

individual, the virus exists as highly related, although

genetically distinct quasispecies (Kuiken et al., 1993;

0042-6822/$ - see front matter D 2004 Elsevier Inc. All rights reserved.

doi:10.1016/j.virol.2004.09.015

* Corresponding author. AIDS Research Program, Molecular Virology

Laboratory, Department of Biochemistry, Ponce School of Medicine, PO

Box 7004, Ponce, 00732, Puerto Rico. Fax: +1 787 841 1040.

E-mail address: [email protected] (E. Lorenzo).

Lorenzo et al., 2004; Malim and Emerman, 2001; Nowak

et al., 1991). Phylogenetic methodologies have been

extensively used to reconstruct an evolutionary history of

these diverse viral quasispecies (DeBry et al., 1993; Hillis et

al., 1994; Lorenzo et al., 2001, 1996; Ou et al., 1992). A

critical consequence of HIV-1 variability has been deter-

mined to be high degree of viral sequence diversity in the

envelope gene that results in the co-receptor usage shift.

HIV-1 co-receptor usage has been shown to be an important

determinant of viral tropism and pathogenesis. During acute

infection, the virus uses CCR5 co-receptor (R5) in vivo,

whereas later in the infection, CXCR4-utilizing virus (X4)

appears mixed with R5 quasispecies (Connor et al., 1997;

Stevenson, 2003). The emergence of X4 utilizing strains

04) 116–126

http:\\www.hiv-web.lanl.gov


E. Lorenzo et al. / Virology 330 (2004) 116–126 117

presages cell depletion and clinical deterioration (Philpott et

al., 2001; Stevenson, 2003). Genetic analysis of patient viral

populations such as the study presented here has been

extensively used to gain information on the pathogenesis of

the infection as well as to clarify in vivo evolution of HIV-1

(Delwart et al., 1997; Shankarappa et al., 1999). Never-

theless, the exact nature and significance of the mechanisms

that govern intra-host evolution and pathogenesis remain

largely unknown.

The HIV evasive ability to counter the immune system

has also been associated in part with both the rapid

variability of the HIV envelope protein sequence and the

masking of epitopes by glycosylation (Nara et al., 1991;

Quinones-Kochs et al., 2002; Wei et al., 2003). The N-

glycosylation sites are significant for the binding of

carbohydrates to the viral envelope to mask viral protein

epitopes from the immune response, and thus enabling the

HIV-1 to escape neutralization. Indeed, one of the most

important functions of N-linked glycosylation is protection

of otherwise accessible neutralization epitopes of the viral

envelope from neutralizing antibodies (Nab) (Bolmstedt et

al., 1996). Recently, it has been shown that mutations in N-

linked glycosylation sites rendered a neutralization antibody

sensitive virus to be completely resistant to pre-existing

neutralizing antibodies (Stipp et al., 2000; Wei et al., 2003).

This pattern of escape led these researchers to postulate an

bevolving glycan shieldQ mechanism of neutralization

escape in which selected changes in glycosylation patterns

prevent Nab but not receptor binding (Wei et al., 2003). This

evolving glycosylation pattern of the envelope gene

represents a new mechanism contributing to HIV-1 persis-

tence in the face of a dynamic antibody repertoire. Although

the number of N-linked glycosylation sites varies with the

strain of HIV-1, there are usually 24 such potential sites in

the envelope gene (Quinones-Kochs et al., 2002), and their

somewhat conserved locations suggest generally strong and

persistent selective pressures. Clear changes in these

glycosylation sites will suggest shifts in immune pressure

(Kemal et al., 2003; Wei et al., 2003).

The majority of positive selection in the HIV-1 has been

found to occur in the envelope region of the genome, as

opposed to the gag or pol region (Choisy et al., 2004).

Positive selection in the HIV-1 env gene has been

demonstrated by comparisons of the abundance of non-

synonymous (dN) and synonymous (dS) pairwise variability

in the DNA sequence (Bonhoeffer et al., 1995; Nielsen,

1999). The relative ratio of nonsynonymous and synon-

ymous changes in the HIV env gene seems to be generated

by a balance between selective pressure placed on the virus

quasispecies mainly by the immune system, which favors

amino acid diversification, and the negative selection

against missense mutation that breaks the structural con-

straints of the functional Env protein (Anastassopoulou et

al., 2003; Shankarappa et al., 1999).

Patients under HAART have been extensively followed

for the emergence of drug-resistance by sequencing pol and

identifying the associated mutations (Demeter et al., 1998;

Gallant et al., 2003; Little et al., 2002; Tirado et al., 2004;

Unal et al., 1996). However, there is only limited

information available regarding the evolution of other viral

genes in patients on HAART. Interestingly, the envelope

gene, one of the most immunogenic regions of the HIV-1, is

linked to numerous viral characteristics including trans-

mission, viral entry, co-receptor usage, tropism, and immune

escape (Rangel et al., 2003). However, few research studies

have been focused in the envelope gene of the HIV-1 after

the advent of HAART. In an effort to improve our

understanding of the complex interaction between viral

quasispecies and the host-selective immune pressure, we

analyzed the env gene viral diversity, glycosylation patterns,

and selective pressures in plasma pre- and post-HAART.

Results

We sequenced and analyzed HIV-1 C2–V4 env of 148

clones from plasma virus in five patients who were sampled

before receiving any antiretroviral drug therapy (time 1) and

after achieving viral suppression due to the therapeutic

regimen (time 2) (Fig. 1). Patients A and B were clinically

classified as categories A and B (CDC, 1993), respectively,

with N400 CD4+ T cell counts; and patients C, D, and E

were category C with CD4+ T cell counts b200 cells/ml

blood, at the time of enrollment. All participants exhibited

viral suppression 6–10 months after commencement of

HAART. Patients A and E showed emergence of rebound-

ing virus after initial suppression (time 3), whereas patients

B, C, and D maintained undetectable plasma viral loads

throughout study (Table 1). Viral sequences at second time

point for patient A are unavailable for this study due to the

limited volume of plasma accessible for the amplification of

HIV-1 RNA. We observed T-tropic variants during

advanced disease of patients C and E, in agreement with

Kreisberg et al. (2001) and Schuitemaker et al. (1992).

Utilizing most stringent genotyping method (Jensen et al.,

2003), we observed disappearance of these T-tropic variants

after HAART, in agreement with Philpott et al. (2001) and

Skrabal et al. (2003).

Phylogenetic reconstructions pre- and post-HAART

Phylogenetic analysis by the NJ method of the plasma

quasispecies in the five HIV-1-infected participants showed

monophyletic groups that were separated from nucleotide

sequences of the other patients with 100% bootstrap values,

excluding the possibility of laboratory contamination (Fig.

2). There was a correlation between the clustering tendency

of sequences and the CD4+ T cell count profile in four of five

patients. NJ phylogenetic reconstruction provided evidence

of clear temporal clustering of the C2–V4 env sequences pre-

and post-HAART in patients A, B, and C. On the other hand,

sequence intermingling was observed in patients D and E in

E. Lorenzo et al. / Virology 330 (2004) 116–126118

Fig. 1. Representative inferred amino acid sequence alignment of partial HIV-1 env sequences spanning the C2–V4 region from plasma-derived clones in five

patients. Labels are showed to the left of each sequence; letter and number indicate patient ID and time point, respectively, number at the end indicates clone

number. The consensus sequence for each patient is shown on the top line of each set of sequences, with regions of HIV env indicated. Amino acid changes are

indicated relative to the consensus sequence of each patient as generated by BioEdit. Dots, dashes, and X indicate identical amino acid sequences, deletions,

and frameshift mutations respectively. Identical clones within each patient are not shown.


Table 1

Clinical profile of the HIV-1 infected individuals before and after receiving HAART

Patient Sampling date HAART regimen Plasma HIV-1 RNA

(copies/ml)

CD4+ T lymphocyte

counts (cells/l)

CDC*

A 05/08/02 none 53,317 670 A1

12/18/02 ZDV, 3TC, ABV b50 1247

10/15/03 ZDV, 3TC, ABV 1067 1115

B 09/04/02 none 8784 482 B2

07/04/03 ZDV, 3TC, ABV 89 435

C 06/17/03 none N100,000 79 C3

02/02/04 LPV/RIT, TNV, 3TC 129 394

D 08/01/02 none 52,527 45 C3

02/13/03 EFV, d4T, 3TC 66 146

E 03/18/02 none N75,000 12 C3

09/03/02 IDV, RIT, 3TC/ZDV 68 116

12/04/02 IDV, RIT, 3TC/ZDV 1132 123

IDV, indinavir; RIT, ritonavir; 3TC, lamivudine; ZDV, zidovudine; EFV, efivarenz, d4T, stavudine; LPV, lopinavir; TNV, tenofivir; ABV, abacavir.* Clinical status of patients in the first visit, according to the Centers for Disease Control and Prevention classification system (CDC, 1993).


the time points prior to and subsequent to antiretroviral

therapy. These sequences, however, were related enough to

cluster within sequences from the same person. Conversely,

patient C showed temporal phylogenetic clustering even with

79 CD4+ T lymphocyte counts, which is the highest of the

clinically C-categorized participants. These observations

agree with recent findings of Kemal et al. (2003), who

reported intermingled envelope sequences of plasma and

genital tract of females with CD4+ T cell depletion.

Bottleneck evolution in the HIV-1 env C2–V4 region

We analyzed 480 bp of sequence spanning the C2–V4

env region for the five patients. To determine the presence

or absence of bottleneck evolution (Ibanez et al., 2000),

the sequence diversity was determined as the mean of the

nucleotide distances in each time point per patient, shown

in Table 2. All patients showed V4% sequence diversity

within each time point. Highly homogeneous virus (b1%

nucleotide distance) was found in plasma of patients B and

C before receiving HAART. We found a slight conver-

gence in the clone sequences after HAART-induced viral

suppression (time 2), in comparison to the treatment-naive

time points (time 1). More homogeneous virus (b2%

nucleotide diversity) appeared in those patients that

showed partial failure to the therapeutic regimen (patients

A and E), after suppressing the virus below or very close

to the detection limit. Patient E showed a resistant virus

that was slightly more homogeneous when compared to

the baseline virus, whereas in the patient A, the genomic

restriction was fourfold. This difference could be attributed

to the degree of suppression attained by the patients.

Although it seems insignificant that patient A reached viral

loads b50 copies/ml during suppressive HAART and

patient E reached a viral load of 68 copies/ml, this

numerical difference could be important to set hypothetical

thresholds for the occurrence of bottleneck evolution in the

HIV-1 envelope.

Synonymous and nonsynonymous nucleotide substitution

changes in HIV-1 envelope before HAART and during

suppressed plasma viremia

We determined selection pressure on HIV-1 quasispecies

by analyzing the synonymous (silent) and nonsynonymous

(amino acid-changing) nucleotide substitution patterns.

Positive selection is indicated by the dominance of the rate

of nonsynonymous nucleotide substitutions over the rate of

synonymous substitutions. The mean values of nucleotide

substitutions per synonymous site (dS) and nonsynonymous

site (dN) of all pairwise sequence comparisons between

time-points (Frost et al., 2001) were calculated as shown in

Table 3. We found b1 mean values in patients with higher

CD4+ T cell counts (patients B and C), suggesting positive

selection, whereas lack of evidence for positive selection

was found in patients D and E (those with lower CD4+ T

cell counts). In an attempt to validate this observation, we

performed nonparametric statistical treatment by grouping

patients according to their CD4+ T cell counts and their

continuous suppressive status (thus, patient A was excluded

from this analysis). As anticipated, we found statistical

correlation between CD4+ T cell counts and positive

selection (see Table 4).

Contrary to the expected results, patient A, who is the only

participant who achieved complete viral suppression (b50

copies/ml), showed lack of positive selection at the level of

envelope gene (as well as patients D and E), probably due to

the drug pressure exerted over the pol gene that may eclipse

the immune pressure/selection at the envelope.

Changes in the C2–V4 env N-glycosylation patterns

pre- and post-HAART

Changes in the N-linked glycosylation sites suggest

shifts in terms of the HIV-1 specific immune responses. The

C2–V4 region contains more than 12 potential N-linked

glycosylation sites (see Fig. 3). As expected, our analyses

Fig. 2. Phylogenetic reconstruction of HIV-1 plasma-derived gp120 env C2–V4 nucleotide sequences generated by the neighbor-joining (NJ) method. Numbers

at branch nodes refer to bootstrap values (1000 repetitions). Letters and number correspond to the patient ID and time point, respectively. The number at the end

refers to the clone number. Identical clones were eliminated from this analysis.


Table 2

Nucleotide distances of plasma-derived clone sequences of five patients

before and after receiving HAART

Patient Sampling

time

Mean diversity F SD Wilcoxon’s signed

rank test*

A 1 0.037 F 0.024 b0.001

3 0.010 F 0.010

B 1 0.006 F 0.003 0.005

2 0.004 F 0.004

C 1 0.007 F 0.007 0.031

2 0.003 F 0.002

D 1 0.004 F 0.014 0.003

2 0.033 F 0.012

E 1 0.033 F 0.020 0.012

2 0.035 F 0.013

3 0.022 F 0.011

Diversity was determined by using MEGA with Kimura 2-parameter. SD,

standard deviation.* P value.


showed that in patients with higher CD4+ T cell counts

(patients A–C), there was a clear shift in terms of

glycosylation sites before and during HAART, suggesting

selective immune pressures. Conversely, in patients E and

D, there was indication of poor selective immune pressure

patients, consistent with their lower CD4+ T cell counts.

Discussion

The present study characterized different quasispecies of

the virus in five HIV-infected individuals. The gene we

analyzed codes for part of the envelope, which is not the

target of HAART regimes of our cohort, implying that we

are primarily measuring the result of a selective pressure

other than HAART. Our results demonstrate the possibility

of involvement of immune pressure in the selection of viral

variants that has been shown by several studies. However,

this is the first indication that during HAART viral evolution

is influenced by not only drug pressure but also immune

pressure in patients with higher CD4+ counts. This

Table 3

Mean synonymous and nonsynonymous nucleotide substitution changes in differ

Patient Sampling

time

Mean dS F SD Wilcoxon’s

signed rank test*

Mean dN

A 1 0.060 F 0.029 0.890 0.400 F3 0.072 F 0.043 0.042 F

B 1 0.013 F 0.005 0.007 0.009 F2 0.015 F 0.006 0.031 F

C 1 0.152 F 0.007 b0.001 0.007 F2 0.038 F 0.010 0.051 F

D 1 0.075 F 0.021 0.081 0.035 F2 0.066 F 0.020 0.031 F

E 1 0.054 F 0.026 0.221 0.037 F2 0.0478 F 0.020 0.37 F3 0.573 F 0.994 b0.001 0.028 F

The frequencies of synonymous substitutions per synonymous site (dS) and no

Synonymous/Nonsynonymous Analysis Program (SNAP) from Los Alamos HIV* P value.

conclusion is based on unambiguous difference in the

envelope sequence in patients having higher CD4+ T cell

counts compared to those who had lower CD4+ T

lymphocyte counts. Our conclusion is also supported by

possible correlation between CD4+ T cell counts in

phylogenetic clustering, dS/dN ratio (an indicator of positive

selection), and changes N-linked glycosylation sites.

Phylogenetic analyses of these plasma sequences

revealed monophyletic clustering of pre- and post-HAART

in patients A, B, and C (higher CD4+ T cell counts).

However, patients D and E (lowest CD4+ T cell counts) did

not cluster in relation to time points. These results suggest

that although all patients experienced a noticeable viral

suppression due to HAART’s pressure over the pol gene,

only the ones with the higher CD4+ T lymphocytes were

able to mount an effective/selective immune pressure over

the envelope gene. This new selective pressure was able to

generate a related, although clearly distinct viral population

within few months. This finding is at least, in principle,

consistent with a recent report that showed women with

monophyletic HIV-1 genomic clusters per compartment

(plasma and vaginal) had consistently higher CD4+ T

counts, while those with lower CD4+ T cell counts display

intermingled quasispecies between compartments (Kemal et

al., 2003). In addition, our findings are in general agreement

with recent studies suggesting that specific immune

responses to HIV (and SIV in model system) are inversely

correlated with disease progression, and that the presence

and help of CD4+ T cells is essential to the disease control

(Garber et al., 2004; Kaech and Ahmed, 2003; Moir et al.,

2003; Rosenberg et al., 1997).

Our analyses also revealed clear shifts in glycosylation

sites in patients A, B, and C. The number of glycosylation

sites is conserved among different HIV strains. Sequence

changes altering potential glycosylation sites have been

shown to play an extremely important role in providing the

capacity to escape from immune recognition (Back et al.,

1994; Cheng-Mayer et al., 1999; Wei et al., 2003). Differ-

ences in glycosylation sites suggest the evolution of two

ent time points

F SD Wilcoxon’s

signed rank test

Mean dS/dN F SD Wilcoxon’s

signed rank test

0.020 0.611 1.930 F 1.315 0.360

0.020 1.635 F 0.555

0.004 0.007 1.866 F 1.059 0.011

0.003 0.400 F 0.207

0.005 b0.001 3.560 F 2.346 b0.001

0.004 0.600 F 0.212

0.010 0.205 2.280 F 0.856 0.728

0.009 2.458 F 1.498

0.016 0.211 1.838 F 1.464 0.014

0.015 1.536 F 0.870

0.016 b0.001 1.555 F 0.4848 0.064

nsynonymous per nonsynonymous site (dN) were estimated by using the

sequence database, http://hiv-web.lanl.gov. SD, standard deviation.


Table 4

Mean of synonymous and nonsynonymous nucleotide substitution changes between time points 1 and 2

Group Time

points

Mean

dS F SD

Wilcoxon’s

signed

rank test

Mean

dN F SD

Wilcoxon’s

signed

rank test

Mean

dS/dN F SD

Wilcoxon’s

signed

rank test

Higher CD4

(Patients B and C)

1 0.015 F 0.007 b0.001 0.007 F 0.005 b0.001 3.332 F 2.281 b0.001

2 0.027 F 0.014 0.042 F 0.011 0.536 F 0.247

Lower CD4

(Patients D and E)

1 0.056 F 0.026 0.070 0.037 F 0.016 0.461 1.880 F 1.422 0.018

2 0.059 F 0.022 0.033 F 0.012 2.106 F 1.369

Patient A was excluded from this analysis because of the unavailability of data for time point 2. SD, standard deviation.


separate sets of sequences under distinct immune pressures

before and after HAART. Just as in the previous analysis,

patients D and E (lowest CD4+ counts) did not show clear

shifts in glycosylation sites suggesting lack of an effective

immune pressure on the env gene.

In addition, patients B and C in this study showed a dS/dNratio of b1, suggesting continued positive selection in these

patients, whereas dS/dN ratio (N1) in patients D and E

suggested lack of positive selection. This analysis measures

the variations of the synonymous per nonsynonymous ratio

(dS/dN), which provides a measure at the molecular level of

the selection intensity among amino acid sites (Anastasso-

poulou et al., 2003; Nielsen and Yang, 1998). It has been

suggested that changes in the strength of the immune

response may not result in predictable changes in the dS/dNratio if the selection coefficient is on the same order of

magnitude as the effective population size. Nevertheless,

observations of temporal changes in the dS/dN ratio alone

may still provide partial information about the status of the

immune system (Frost et al., 2001; Nielsen, 1999). The

reason why patient A did not show the expected positive

selection pressure is not fully understood. However, patient

A is the only patient in our study that achieved a viral load

b50 and developed fourfold decrease in genomic diversity

from pre- to post-HAART. At the same time patient A,

together with patient E, is one of the two patients that

exhibited emergence of rebounding virus, and the only in

which we were unable to study the lowest viral load after

therapy started. The time point analyzed in this case is one

in which the viral load is increasing during HAART, which

normally indicates the selection of a resistant virus. This

drug selection is indeed applied to the pol gene, and we

believe it may be eclipsing the immune pressure/selection

applied at the env gene.

Based on the diversity values of our patients’ viral

sequences before and after HAART, we were not able to

observe any clear viral genomic diversity restriction or

bottleneck evolution in HIV-1 env gene except in patient A.

This might be attributed to the fact that other patients never

achieved undetectable viremia (b50 copies/ml), which might

be important for narrowing the viral diversity in patients on

HAART. Another potentially important implication of the

present study is that establishment of HAART resistance may

be followed by faster virus rebound in patients with low

CD4+ T cell counts than in patients with high CD4+ T cell

counts. The future attempts should be directed towards

characterization of the virus emerging after a prolonged and

complete suppression, which may help in identification of

source of virus replication during HAART, and whether viral

rebound is faster in patients with low CD4+ T cell counts.

Materials and methods

Study subjects

Five HIV-1 infected informed-consenting individuals,

aged from 34 to 56 years were enrolled for the study. Blood

samples were collected from all five patients before

commencement of antiretroviral therapy. They achieved

and maintained almost complete viral suppression after the

initiation of the antiretroviral regimen. In this study, we

analyzed samples pre-HAART (Time 1), during plasma viral

suppression (Time 2) and occasionally during the virolog-

ical failure to the therapy (Time 3). Plasma HIV-1 viral load

measurement was carried out using the standard (detection

limit, 400 copies/ml) and ultrasensitive (detection limit, 50

copies/ml) Amplicor HIV-1 Monitor test (Roche Molecular

Systems, Inc., Branchburg, NJ). CD4+ T cells were

quantified by flow cytometry analyses using a FACSScan

(BD Biosciences, San Jose, CA). The clinical characteristics

of the patients are shown in Table 1.

Genetic characterization of HIV-1 env C2–V4 from plasma

HIV-1 RNA was isolated from plasma by using the

QIAmp Viral RNA Mini Kit (QIAGEN, Inc, Valencia, CA)

following the manufacturer’s indications. For the analysis of

plasma HIV-1 RNAwith viral loads b200 copies/ml, 3 ml of

plasma was applied to the column of the same kit. In order

to amplify the HIV-1 C2–V4 env region, nested PCR was

performed by using the OneStep RT-PCR Kit and HotStar

Taq DNA Polymerase (QIAGEN, Inc) with the external

primer pair ED12 and ED31 (5V-AGTGCTTCCTGCTGCT-CCCAAGAACCCAAG-3V and 5VCCTCAGTCATTAC

ACCAGGCCTGTCCAAAG-3Vrespectively) and the inter-

nal primer pair CV3-R and CV3-F (5V-TGATGGGAGGGG-TATACATT-3V and 5V-CTGTTAAATGGCAGTCTAGC-3Vrespectively). The final amplicon (525 bp) was electro-

phoresed with a low molecular weight marker in 1.2%

agarose, stained with ethidium bromide, and visualized

under UV light for determination of molecular weight.

Fig. 3. Graph of the fraction of N-linked glycosylation sites at each position in the alignment of amino acid sequences from patients A–E. Potential N-

glycosylation sites were determined by using the N-Glycosite tool from Los Alamos HIV sequence database, http://hiv-web.lanl.gov.


Cloning and sequencing of HIV-1 C2–V4 envelope gene

from plasma

PCR products were ligated and cloned according to the

TOPO TA Cloning Kit protocol (Invitrogen, Carlsbad, CA).

Plasmid DNA was purified by using QIAprep Spin

Miniprep columns (QIAGEN, Inc.). A total of 148 clones

were sequenced with M13 primers using Big-Dye termi-

nator chemistry according to manufacturer’s recommenda-

tions in an Applied Biosystems 3100 Genetic Analyzer

(Applied Biosystems, Foster City, CA).

Sequence analysis

All nucleotide sequences analyses were carried out on

a 480 bp fragment of the env gene spanning the C2–V4

region. Nucleotide sequences were aligned with BioEdit

version 5.0.9 (Hall, 1999) and later hand edited.



Phylogenetic reconstructions were generated by the

neighbor-joining (NJ) method (with Kimura two-parame-

ter model and a transition/transversion ratio of 2.0) in

1000 bootstrapped data sets as implemented in the

MEGA version 2.1 (Kumar et al., 2001). The final

graphical output was created with TreeView. Pairwise

nucleotide sequence distance was computed by using

MEGA. The frequencies of synonymous substitutions per

synonymous site (dS) and nonsynonymous per nonsynon-

ymous site (dN) were estimated by using the SNAP tool

from the Los Alamos HIV sequence database, http://hiv-

web.lanl.gov. Potential N-linked glycosylation sites were

determined by using the N-glycosite tool from the Los

Alamos HIV Sequence database. Data were subjected to

nonparametric statistical treatment using Wilcoxon signed

rank test included in the SPSS Version 12.0 software

package (SPSS, Inc., Chicago).

Acknowledgments

We are grateful to the patients for their voluntary

participation in this study. We also thank the Epidemiology

and Biostatistics Core Program at Ponce School of Medicine.

This work was financially supported by National Institutes

of Health grants NIGMS-MBRS (S06-GM08239), NHLBI/

K0-1 (HLO-4371) and NCRR-RCMI (G12RR03050).

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