www.elsevier.com/locate/meegid

Infection, Genetics and Evolution 5 (2005) 231–237

HIV-1 genetic variants circulation in the North of Angola

A. Abecasisa,*, D. Paraskevisb, M. Epalangac, M. Fonsecad, F. Buritye,J. Bartolomeuc, A.P. Carvalhoa, P. Gomesa, A.-M. Vandammeb, R. Camachoa

aLaboratorio de Virologia, Servico de Imuno-hemoterapia, Hospital de Egas Moniz,

Rua da Junqueira, 126, 1349-019 Lisboa, PortugalbLaboratory for Clinical and Epidemiological Virology, Rega Institute for Medical Research,

Katholieke Universiteit Leuven, Minderbroedersstraat 10, B-3000 Leuven, BelgiumcServico Nacional de Sangue de Angola, Angola

dPosto Medico da FANA, Luanda, AngolaeHospital Militar Principal de Luanda, Luanda, Angola

Received 14 January 2004; accepted 7 July 2004

Available online 2 December 2004

Abstract

Few molecular epidemiological data on HIV-1 in Angola are available. In this study, we analysed 37 pol sequences from patients originated

from Luanda and Cabinda in Angola. It was our objective to investigate the circulation of different HIV-1 subtypes in this country. We found a

high HIV-1 genetic diversity. The predominant subtypes were C and F, while subtypes A, D, G and H were also detected. Three sequences

were untypable and may possibly belong to new subtypes or recombinants of unknown subtypes. Moreover, 13 recombinant sequences were

found, most of them with very complex patterns including untypable fragments.

# 2004 Elsevier B.V. All rights reserved.

Keywords: HIV-1 genetic variants; HIV-1 subtypes; Recombinant sequences

1. Introduction

HIV-1 sequences isolated worldwide have been divided

into three main groups: group M (major), group O (outlier)

and group N (new). Group M viruses, which are responsible

for the global pandemic, are classified into 9 pure subtypes

(A–D, F–H, J and K) and 15 circulating recombinant forms

(CRFs). (Los Alamos Database: http://www.hiv.lanl.gov/

content/index; Kuiken et al., 2002; Carr et al., 1998). The

virus genome is characterised by a high genetic variability,

especially in the env gene.

The different HIV-1 groups originate from Africa,

probably through separate zoonotic transmissions from

chimpanzees (Pan troglodytes troglodytes) (Gao et al.,

1999). The HIV-1 group M pandemic was probably sparked

in part due to profound social upheavals in post-colonial

Africa (Laurent and Delaporte, 2001). The high degree of

* Corresponding author.

E-mail address: a_abecasis@portugalmail.com (A. Abecasis).

1567-1348/$ – see front matter # 2004 Elsevier B.V. All rights reserved.

doi:10.1016/j.meegid.2004.07.007

HIV-1 genetic diversity described in West-Central Africa

countries (all pure subtypes and many different complex

recombinants have been found there), as well as the fact that

this area is the habitat of Pan troglodytes troglodytes suggest

that the HIV-1 pandemic originated there (Gao et al., 1999;

Bikandou et al., 2000; Massanga et al., 1996; Mokili et al.,

2002; Taniguchi et al., 2002; Vidal et al., 2000, 2003; Vergne

et al., 2003; Wilbe et al., 2002). The highest genetic diversity

has been described in the Democratic Republic of Congo

(DRC), so far, thus, suggesting that the HIV-1 group M

epidemic originated in this area.

Angola is located in Central Africa, bordering the

Democratic Republic of Congo (2511 km), Republic of the

Congo (201 km), Namibia (1376 km) and Zambia

(1110 km) (Fig. 1). At the end of 2001, the total population

of Angola was estimated to be 13,527,000 people (UNAIDS,

2002). The capital of Angola is Luanda. Its total population

has increased significantly since the independence in 1975,

due to the return of a huge number of people who were

escaping the fighting by migrating to the countryside. Their

A. Abecasis et al. / Infection, Genetics and Evolution 5 (2005) 231–237232

Fig. 1. Map of Angola, with the location of Luanda and Cabinda, where the

samples were collected (adapted from Diciopedia, 2003).

number has been estimated to be approximately 3.2 million

people—based on an aerial survey of the province conducted

in 2000 (http://www.iss.co.za/). Cabinda is a discontiguous

province of Angola, which is separated from the rest of the

country by a DRC’s corridor to the sea. The total population

of Cabinda is not officially known but is estimated to be

approximately 1.5 million people (http://www.cabinda.net/).

Several surveys have been conducted in Angola, but

limited information is available on the epidemic’s advance.

In Luanda, HIV infection rates among women attending

antenatal clinics have been rising from 0.3% in 1986 to 8.6%

in 2001. In Cabinda, the infection rate in antenatal women

increased from 6.8% in 1992 to 8.5% in 1996 (no recent data

is available). Furthermore, a 2001 survey conducted in sex

workers in Luanda indicated a HIV prevalence of 33% in

this group. A similar survey conducted in military personnel

indicated a HIV prevalence of 3.2%. In the 2003 UNAIDS

update, Angola is considered a cause of concern, despite the

low HIV levels detected to date in comparison with other

Sub-Saharan countries. Due to huge population movements

at the end of the civil war, a sudden eruption of the epidemic

was feared. Furthermore, thousands of refugees returned to

the country from neighbouring countries with high

prevalence of HIV infection (UNAIDS, 2003, 2002).

Until now, limited data is available about the HIV-1

molecular epidemiology in Angola. In a preliminary study in

2001, where 35 samples from patients originated from

Luanda were analysed for HIV-1 drug resistance testing, 14

patients were found infected with recombinant virus;

whereas subtype D was the most prevailing subtype

(Epalanga et al., 2001). More recently, preliminary data

were reported by Bartolo et al. (2003), who studied a group

of 32 samples, from Cabinda and Luanda to investigate the

genetic diversity of HIV-1 in Angolan patients. Among

them, five patients were infected with recombinant virus,

while subtype A was more frequent (10 samples) than the

other subtypes. Both studies suggest that the molecular

epidemiology of HIV-1 in Angola resembles the high HIV-1

genetic heterogeneity described in DRC; where all known

subtypes and complex recombinants co-circulate (Vidal

et al., 2000).

2. Materials and methods

2.1. Patients

Thirty seven samples were selected randomly from a

group of 210 HIV-1 seropositive samples that were collected

from patients in Angola. The samples originated from

Cabinda (n = 17) and Luanda (n = 20). A fragment of the pol

gene, containing codons 1–99 of protease and codons 1–335

of reverse transcriptase (RT), was sequenced using the

ViroSeq 2.5 genotyping kit (Abbott) with the automatic

sequencer ABI System 3100.

2.2. Sequence analysis

The sequences from Angola were aligned with repre-

sentative sequences of subtypes A–D, F–H, J and K (Kuiken

et al., 2002) using Clustal W (Thompson et al., 1994).

Manual editing was performed with BioEdit (http://

www.mbio.ncsu.edu/BioEdit/bioedit.html) and DAMBE

(Xia and Xie, 2001).

An initial analysis was performed with Simplot v3.2

(Lole et al., 1999), using a sliding window and step size of

400 and 50 bp, respectively, and maximum likelihood

estimated distances (F84 model with transition/transversion

of 2.0), using reference sequences SE7253, U455 and

92UG037 (subtype A), HXB2 and RF (subtype B), 92BR025

and 96BW0502 (subtype C), ELI and NDK (subtype D),

VI850 and 93BR020-1 (subtype F), SE6165 and HH8793-

12-1 (subtype G), VI991 and VI997 (subtype H), SE7887

and SE7022 (subtype J) and EQTB11C and MP535 (subtype

K). In case the recombination pattern, according to the

bootscanning analysis, resembled one of the known CRF’s,

these sequences were also included in a subsequent

bootscanning analysis. Subtypes were assigned based on

this analysis only when the results were unambiguous,

defined as >75% bootstrap support over almost the entire

region. When this criterion was not fulfilled, putative

recombination breakpoints were estimated by further

analysis.

2.3. Phylogenetic analysis

For sequences for which the bootscanning plot did not

show a clear picture (see criteria described above), the

putative recombination pattern was further confirmed by

phylogenetic analysis using TreePuzzle 5.0 (Schmidt et al.,

2002), with the Tamura-Nei substitution model including

gamma-distributed rate heterogeneity among sites. Frag-

ments with discordant phylogenetic history, according to

bootscanning analysis, were analysed separately. For

sequences or any partial fragments that show evidence to

be more closely related to CRFs, phylogenetic analysis was

repeated including also CRF sequences.

Moreover, we performed phylogenetic analyses using a

Bayesian method as implemented in MrBayes v3.0 software

A. Abecasis et al. / Infection, Genetics and Evolution 5 (2005) 231–237 233

(Huelsenbeck and Ronquist, 2001), using the general time

reversible (GTR) evolutionary model with gamma-distrib-

uted rate heterogeneity among sites. Trees were generated

including either only sequences classified as pure subtypes

or a selected set of recombinant sequences to investigate

further the relationship among them. For Bayesian

inference, four Markov chains were run for 2 � 106

generations with a burnin = 2 � 105.

3. Results

3.1. Epidemiological data

The 37 sequences reported here were obtained in the

context of resistance genotyping. The samples from which

the sequences were obtained were part of a larger set

(n = 210) collected in Luanda and Cabinda, for seropreva-

lence studies. The samples were randomly collected at the

respective clinical sites and were subsequently sent to our

lab, for subtyping and resistance genotyping purposes. The

original study population included samples from infected

blood donors, infected mothers from an obstetric clinic and

soldiers presenting for army duty. No details could be

obtained as to the distribution of these risk factors in our

small set of samples.

3.2. Assignment of pure subtypes within the

analysed pol region

The gap-stripped alignment extended over the entire

protease (PRO) and part of the reverse transcriptase region,

corresponding to nt 2253–3463 of HXB2 (accession number

K03455). HIV-1 subtype classification was based on

bootscanning plots and further confirmed by phylogenetic

analysis using Bayesian inference. Fig. 2a shows the

Bayesian tree with all the 21 sequences clustering with

the respective subtype reference sequences with high

posterior probabilities. Thus, within the dataset of 37

sequences, 2 sub-subtype A1 sequences (Ang277 and

Ang185), 6 subtype C sequences (Ang157, Ang180,

Ang182, Ang192, Ang194 and Ang205), 4 subtype D

sequences (Ang176, Ang190, Ang199 and Ang220), 7

subtype F sequences (Ang181, Ang186, Ang187, Ang188,

Ang200, Ang202 and Ang226), 1 subtype G sequence

(Ang216) and 1 subtype H sequence (Ang198) were found.

Thus, the subtype distribution was, 18.9% F, 16.2% C,

10.8% D, 5.4% A, 2.7% G and 2.7% H. Table 1 summarizes

the subtype distribution found in Luanda and Cabinda, as

well as the overall subtype distribution. The remaining 16

sequences, 6 from Luanda and 10 from Cabinda, were not

sufficiently supported as belonging to a single subtype along

the entire bootscanning plot and thus were further analysed

for any evidence of recombination (see Section 2). Their

putative recombination breakpoints were estimated manu-

ally. A summary of this analysis is presented in Table 2. Two

sequences from Cabinda (Ang209 and Ang219) were not

included in this table, since their bootscanning plots were

too complex to identify putative breakpoints.

3.3. Detailed analysis of sequences unclassified by

bootscanning

The 14 sequences, listed in Table 2, were further analysed

using TreePuzzle. The samples Ang209 and Ang219 showed

very complex bootscanning plots and putative recombina-

tion breakpoints could not be identified by this method. On

the other hand, using Bayesian scanning, which is a newly

developed tool (Paraskevis et al., 2003) for exploring

recombination, the picture was clearer than bootscanning

plots. Subsequent phylogenetic analysis further confirmed

Bayesian scanning results (data reported elsewhere). The

results of this additional analysis suggest that these

sequences are two distinct recombinants but both consist

of subtype A and G fragments and fragments that show no

similarity to any of the previous HIV-1 subtypes (untypable).

The results of the other 14 samples are summarized in

Table 2.

Sequences Ang158, Ang189 and Ang201 have similar

breakpoint patterns. The first non-recombinant fragment

was untypable, but according to phylogenetic analysis, all

three sequences clustered together (data not shown). The

second fragment belonged to subtype H. The three

sequences were, therefore, assigned U/H recombinants.

These three sequences were further analysed by constructing

a Bayesian tree with pure subtypes only and with these three

sequences. They all three clustered together, confirming

their close epidemiological relationship (Fig. 2b).

Ang211 was also assigned a U/H recombinant, but the

recombination breakpoint was different from the previous

sequences.

One sequence (Ang159) showed a U/A2/U recombina-

tion pattern, with breakpoints located approximately at 300

and 750 bp. The first and third fragments clustered with

subtype G and A reference sequences, respectively, although

not supported with a high number of puzzling steps.

Sequence Ang191 is a U/H/U recombinant. The first

fragment clusters with A1, and the third with A2, but neither

of these clustering was significantly supported.

Two sequences showed close relation with CRF05_DF,

although only Ang222 was confirmed to be CRF05_DF.

Regarding Ang206, the only confirmed CRF05_DF frag-

ment was 700–1210 bp.

Sequence Ang223 strongly suggests being a A1/

CRF06_CPX/K recombinant with recombination break-

points at 350 and 700 bp, despite the fact that the reliability

of the analysis of the first fragment is only 72%, which may

be due to the short length of the fragment.

The pattern of recombination of sequence Ang218 was

confirmed, in part. In the bootscanning analysis, the recom-

bination pattern A/CRF04_CPX is suggested, whereas

A. Abecasis et al. / Infection, Genetics and Evolution 5 (2005) 231–237234

subsequent phylogenetic analysis confirmed only the

clustering of the second part with CRF04.

In spite of suggesting a G/A recombinant sequence

Ang160 was unclassified, since phylogenetic analysis did

not confirm to the initial findings. For Ang184, the G/H

pattern suggested by bootscanning analysis was confirmed

only for the second fragment belonging to subtype H.

Bootscanning analysis suggested that sequence Ang214

is a D/B recombinant, however, in the Bayesian phyloge-

Fig. 2. Bayesian tree including: (a) all the query sequences that were classified as

201. All the reference sequences of the pure subtypes A–D, F–H, J and K as indicate

generation of these trees was MrBayes v3.0, using the general time reversible (GT

site. Four Markov chains were run for 2 � 106 generations, with burnin = 2 � 1

netic tree both fragments clustered significantly with

subtype D. Therefore, these sequence was classified as

subtype D.

Finally although sequence Ang217, did not produce

a clear bootscanning plot picture, phylogenetic analysis

in regions 1–400, 401–750 and 751–1210 showed that

all these fragments clustered with sub-subtype A2, although

not supported with high levels of support for the last

fragment.

pure subtypes in the analysed region; (b) query sequences Ang158, 189 and

d in the Section 2 were included in the alignments. The software used for the

R) evolutionary model with gamma-distributed rates heterogeneity among

05.

A. Abecasis et al. / Infection, Genetics and Evolution 5 (2005) 231–237 235

Fig. 2. (Continued ).

Table 1

The pol subtype distribution in Luanda (n = 20), Cabinda (n = 17) and in the

complete analysed group of samples (n = 37)

Subtype Luanda Cabinda Total

n % n % n %

A 1 5.0 1 5.9 2 5.4

C 5 25.0 1 5.9 6 16.2

D 3 15.0 2 11.8 5 13.5

F 4 20.0 3 17.6 7 18.9

G 0 0.0 1 5.9 1 2.7

H 1 5.0 0 0.0 1 2.7

CRF’s 0 0.0 1 5.9 1 2.7

Untypable 1 5.0 0 0.0 1 2.7

Recombinants 5 25.0 8 47.0 13 35.1

20 100.0 17 100.0 37 100.0

4. Discussion and conclusions

We present here the first extended study on the HIV-1

group M subtype distribution in two major cities of Angola,

Luanda and Cabinda. We performed subtype classification

and characterization of the recombination pattern of a

dataset of 37 HIV-1 pol sequences. Although the sequences

were produced for the purpose of drug resistance testing, the

samples were collected for epidemiological purposes and

can therefore be considered representative for the epidemic

in these two cities. The distribution of subtypes, recombi-

nants and unclassified sequences are listed in Table 1, and

are similar in the two cities. Interestingly, an extremely

high genetic variation was found similar to that in other

A. Abecasis et al. / Infection, Genetics and Evolution 5 (2005) 231–237236

Table 2

Bootscanning and TreePuzzle analysis results of the recombinant sequences and/or sequences in which bootstrap values were <75% in part of the region

Putative parent

subtypes

Putative

recombination

breakpoints

First

fragment

SV (%) Second

fragment

SV (%) Third

fragment

SV (%)

Ang158 U/H 350 U (Ang189, resp Ang201) 67, resp 68 H (Ang189) 98 – –

Ang159 G/U/A 300, 750 U – A2 86 U –

Ang160 G/A 450 U – U – – –

Ang184 G/H 300 U – H 94 – –

Ang189 U/H 350 U (Ang158, resp Ang201) 67, resp 68 H (Ang158) 98 – –

Ang191 A1/H/A2 650, 1050 U – H 83 U –

Ang201 U/H 350 U (Ang158, resp Ang189) 67, resp 68 H (Ang158, Ang189) 95 – –

Ang206 D/U/CRF05_DF 400, 700 U – U – CRF05_DF 86

Ang211 U/H 500 U – H 87 – –

Ang214 D/B 750 D 89 D 85 – –

Ang217 A/U/A 400, 750 A2 84 A2 88 U –

Ang218 A/CRF04_CPX 300 U – CRF04_CPX 84 – –

Ang222 D/F 500 D, CRF05_DF 75 CRF05_DF 81 – –

Ang223 A/CRF06_CPX/K 350, 700 U CRF06_CPX 86 K 86

Sequences were divided in two or three fragments, according to the recombination pattern found in the bootscanning analysis. The borders of the fragments are

listed in the Putative recombination Breakpoints column. The six columns on the right show the sequences with which the query sequence clustered, and the

respective support value obtained in the TreePuzzle analysis. Fragments were assigned untypable (U) when support values were <75%. Close clustering

between samples from this study is indicated between brackets. The nt 1–1210 in the analysed sequence correspond to nt 2253–3463 of the complete HIV-1

genome HXB2 sequence (Accession number K03455). SV, support values.

West-Central Africa countries (DRC, Cameroon, Congo,

Chad and Central African Republic) (Bikandou et al., 2000;

Massanga et al., 1996; Mokili et al., 2002; Taniguchi et al.,

2002; Vidal et al., 2000, 2003; Vergne et al., 2003; Wilbe

et al., 2002). Previous preliminary data already suggested a

high HIV-1 genetic diversity in Angola (Epalanga et al.,

2001; Bartolo et al., 2003), however, in those studies

different prevalences were reported. The most prevalent

subtype in our study is F, based on 37 samples collected for

epidemiological purposes, whereas subtype D was the most

prevalent subtype reported in the preliminary study by

Epalanga et al, in a set of 35 samples collected in Luanda for

drug resistance testing, and the preliminary data by Bartolo

et al. indicate subtype A as the most prevalent one in a set of

32 samples from Luanda and Cabinda collected for

epidemiological purposes. Clearly more representative data

need to be collected to be able to properly monitor the

molecular epidemiology in Angola.

However, our findings suggest a genetic diversity in

Angola that is similar to the one observed in the Democratic

Republic of Congo. Therefore, we can speculate that the

HIV-1 epidemic in Angola is old, co-evolving with the

epidemics in neighbouring countries such as the DRC,

where most probably the virus originated through a cross-

species transmission from chimpanzees (Gao et al., 1999);

or that the high genetic heterogeneity observed in Angola

has been transmitted through contacts with those neighbour-

ing countries.

We also noted that for some complex recombinants,

such as Ang209 and Ang219, the methods used here

(bootscanning analysis) might not always be satisfactory to

characterize the recombination patterns. New methods

may be needed, such as the Bayesian scanning methodo-

logy that showed to be more efficient to identify the

recombination pattern for two of our samples (Paraskevis

et al., 2005).

We would suggest performing additional representative

sampling and sequence analysis in Angola, in order to better

understand the molecular epidemiology in this part of

Africa. Such information is essential for the development of

vaccines strategies.

Acknowledgments

A.A. was supported by a Associacao Portuguesa para o

Estudo Clınico da SIDA (APECS) and Gilead Sciences Lda.

fellowship. D.P. was supported by a Marie Curie fellowship

from the European Commission (QLK2-CT2001-51062).

This work was partly supported by the Flemish Fonds voor

Wetenschappelijk Onderzoek (FWO G.0288.01).

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