Skip to main content
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems
  • Log in
  • My alerts
  • My Cart

Main menu

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Minireviews
    • JVI Classic Spotlights
    • Archive
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About JVI
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
  • ASM
    • Antimicrobial Agents and Chemotherapy
    • Applied and Environmental Microbiology
    • Clinical Microbiology Reviews
    • Clinical and Vaccine Immunology
    • EcoSal Plus
    • Infection and Immunity
    • Journal of Bacteriology
    • Journal of Clinical Microbiology
    • Journal of Microbiology & Biology Education
    • Journal of Virology
    • mBio
    • Microbiology and Molecular Biology Reviews
    • Microbiology Resource Announcements
    • Microbiology Spectrum
    • Molecular and Cellular Biology
    • mSphere
    • mSystems

User menu

  • Log in
  • My alerts
  • My Cart

Search

  • Advanced search
Journal of Virology
publisher-logosite-logo

Advanced Search

  • Home
  • Articles
    • Current Issue
    • Accepted Manuscripts
    • COVID-19 Special Collection
    • Minireviews
    • JVI Classic Spotlights
    • Archive
  • For Authors
    • Submit a Manuscript
    • Scope
    • Editorial Policy
    • Submission, Review, & Publication Processes
    • Organization and Format
    • Errata, Author Corrections, Retractions
    • Illustrations and Tables
    • Nomenclature
    • Abbreviations and Conventions
    • Publication Fees
    • Ethics Resources and Policies
  • About the Journal
    • About JVI
    • Editor in Chief
    • Editorial Board
    • For Reviewers
    • For the Media
    • For Librarians
    • For Advertisers
    • Alerts
    • RSS
    • FAQ
  • Subscribe
    • Members
    • Institutions
Genetic Diversity and Evolution

Evidence for both Intermittent and Persistent Compartmentalization of HIV-1 in the Female Genital Tract

Batsirai M. Mabvakure, Bronwen E. Lambson, Kavisha Ramdayal, Lindi Masson, Dale Kitchin, Mushal Allam, Salim Abdool Karim, Carolyn Williamson, Jo-Ann Passmore, Darren P. Martin, Cathrine Scheepers, Penny L. Moore, Gordon W. Harkins, Lynn Morris
Guido Silvestri, Editor
Batsirai M. Mabvakure
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
bFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Batsirai M. Mabvakure
Bronwen E. Lambson
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
bFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Kavisha Ramdayal
cSouth African MRC Bioinformatics Capacity Development Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lindi Masson
dInstitute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Dale Kitchin
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Mushal Allam
eSequencing Core Facility, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Mushal Allam
Salim Abdool Karim
fCentre for the AIDS Programme of Research in South Africa (CAPRISA), KwaZulu-Natal, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Carolyn Williamson
dInstitute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
fCentre for the AIDS Programme of Research in South Africa (CAPRISA), KwaZulu-Natal, South Africa
gNational Health Laboratory Service, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jo-Ann Passmore
dInstitute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
fCentre for the AIDS Programme of Research in South Africa (CAPRISA), KwaZulu-Natal, South Africa
gNational Health Laboratory Service, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Darren P. Martin
dInstitute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Cathrine Scheepers
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
bFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Penny L. Moore
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
bFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
fCentre for the AIDS Programme of Research in South Africa (CAPRISA), KwaZulu-Natal, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Penny L. Moore
Gordon W. Harkins
cSouth African MRC Bioinformatics Capacity Development Unit, South African National Bioinformatics Institute, University of the Western Cape, Cape Town, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Lynn Morris
aCentre for HIV and STIs, National Institute for Communicable Diseases of the National Health Laboratory Service, Johannesburg, South Africa
bFaculty of Health Sciences, University of the Witwatersrand, Johannesburg, South Africa
fCentre for the AIDS Programme of Research in South Africa (CAPRISA), KwaZulu-Natal, South Africa
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Lynn Morris
Guido Silvestri
Emory University
Roles: Editor
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
DOI: 10.1128/JVI.00311-19
  • Article
  • Figures & Data
  • Info & Metrics
  • PDF
Loading

ABSTRACT

HIV-1 has been shown to evolve independently in different anatomical compartments, but studies in the female genital tract have been inconclusive. Here, we examined evidence of compartmentalization using HIV-1 subtype C envelope (Env) glycoprotein genes (gp160) obtained from matched cervicovaginal lavage (CVL) and plasma samples over 2 to 3 years of infection. HIV-1 gp160 amplification from CVL was achieved for only 4 of 18 acutely infected women, and this was associated with the presence of proinflammatory cytokines and/or measurable viremia in the CVL. Maximum likelihood trees and divergence analyses showed that all four individuals had monophyletic compartment-specific clusters of CVL- and/or plasma-derived gp160 sequences at all or some time points. However, two participants (CAP177 and CAP217) had CVL gp160 diversity patterns that differed from those in plasma and showed restricted viral flow from the CVL. Statistical tests of compartmentalization revealed evidence of persistent compartment-specific gp160 evolution in CAP177, while in CAP217 this was intermittent. Lastly, we identified several Env sites that distinguished viruses in these two compartments; for CAP177, amino acid differences arose largely through positive selection, while insertions/deletions were more common in CAP217. In both cases these differences contributed to substantial charge changes spread across the Env. Our data indicate that, in some women, HIV-1 populations within the genital tract can have Env genetic features that differ from those of viruses in plasma, which could impact the sensitivity of viruses in the genital tract to vaginal microbicides and vaccine-elicited antibodies.

IMPORTANCE Most HIV-1 infections in sub-Saharan Africa are acquired heterosexually through the genital mucosa. Understanding the properties of viruses replicating in the female genital tract, and whether these properties differ from those of more commonly studied viruses replicating in the blood, is therefore important. Using longitudinal CVL and plasma-derived sequences from four HIV-1 subtype C-infected women, we found fewer viral migrations from the genital tract to plasma than in the opposite direction, suggesting a mucosal sieve effect from the genital tract to the blood compartment. Evidence for both persistent and intermittent compartmentalization between the genital tract and plasma viruses during chronic infection was detected in two of four individuals, perhaps explaining previously conflicting findings. In cases where compartmentalization occurred, comparison of CVL- and plasma-derived HIV sequences indicated that distinct features of viral populations in the CVL may affect the efficacy of microbicides and vaccines designed to provide mucosal immunity.

INTRODUCTION

Globally, there were almost two million new HIV-1 infections during 2017, with the majority occurring among women in sub-Saharan Africa via vaginal intercourse (1). HIV-1 subtype C is the predominant circulating genetic subtype in southern Africa, where the epidemic is mostly concentrated (1). It is not well understood whether viral populations in the female genital tract are genetically distinct from those in the blood compartment and, if so, how these populations emerge and evolve over time. Such studies on the properties of HIV populations in the female genital tract are important for the design of effective microbicides and vaccines that have the potential to reduce vaginal HIV transmissions in this region (2).

Compartmentalization is well described in HIV infection mostly using envelope (Env) glycoprotein sequences (gp160), which encompass the most diverse regions of HIV-1 genomes (3, 4). A number of factors may favor compartmentalization, including barriers between tissues, differential host cell availability, tissue-specific immune selection pressures, varying viral replication rates in compartments, and random genetic drift (3, 5). As a result, compartmentalized viral populations often possess tissue-specific phenotypic characteristics distinct from those of plasma viruses, including differences in cell tropism, the extent of glycosylation, and drug resistance (3). Compartmentalization is well described in the cerebrospinal fluid and the central nervous system, where it has been reported to affect responses to treatment and is associated with various brain complications (6–11). Independent viral populations in different compartments may produce variants with advantageous phenotypes for viral proliferation compared to parental strains (12). There is also convincing evidence that the semen constitutes a distinct compartment where locally produced HIV lineages evolve under selection pressures different from those in the blood (13–17). Relative to blood-derived viral populations, semen-derived populations show less diversity, decreased levels of positive selection, decreased CXCR4 coreceptor utilization, and altered glycosylation patterns (18). These differences may be at least in part attributable to an enrichment of cytokines and chemokines in the seminal tracts of HIV-infected men that promote T cell activation and viral replication (19).

Studies of HIV compartmentalization in the female genital tract have shown evidence of tissue-specific differences in some, but not all, studied women (20–30). In certain individuals, compartmentalization was shown to be associated with distinct viral features, including coreceptor usage, numbers of N-linked glycosylation sites, levels of neutralization resistance, and diversity (22, 25, 28, 29, 31). The temporal scope of most of these studies has largely been limited by the use of cross-sectional sampling. However, investigations that used more advanced computational and statistical analyses failed to find evidence of compartmentalization and have suggested that such studies can be biased by monotypic and low-diversity sequences (32, 33). A more recent study showed that there was higher HIV-1 Env sequence diversity in the vaginal tract early in infection than there was in the blood (34). This suggested the possibility of either restrictions in the movement of viruses from the genital tract to the systematic blood compartment or differences in HIV evolution within these respective compartments (34). However, this study utilized only the C2-V3-C3 region of Env and might have missed other tissue-specific signatures elsewhere in Env. The only detailed study of HIV compartmentalization in the female genital tract that examined complete gp160 sequences analyzed only a small number of sequences and did not include longitudinal samples from the same individuals (27).

In this study, we amplified longitudinally sampled complete HIV-1 subtype C gp160 envelope sequences from cervicovaginal lavage (CVL) and plasma samples and analyzed these for evidence of compartmentalization using various statistical methods. We present evidence for the existence of separate populations that are maintained over time in the genital tract and plasma compartments of some study participants. These participants showed an asymmetric pattern of viral migrations between the genital tract and plasma with fewer movements to the plasma compartment, suggesting a mucosal sieve. We conclude that compartmentalization may occur in some individuals, yielding viruses in the genital tract that are genetically distinct from those in the plasma.

RESULTS

HIV-1 gp160 amplification from the female genital tract over time.CVL samples were obtained from 18 women enrolled in the CAPRISA acute infection study in Durban, South Africa, within 2 to 15 weeks of HIV-1 infection (Table 1). Women were not menstruating at the time of sample collection, and there was no evidence of macroscopic blood contamination in CVL samples. Most samples were found to have low numbers of erythrocytes, typical of normal mucosal vascularization (35). All participants had detectable plasma viral loads (VL), but only two (CAP177 and CAP217) had detectable CVL viral loads (Table 1). Statistical analyses showed that the difference in CVL VL between those with amplifiable gp160 and those without approached significance (P = 0.0659). Full-length gp160 Env sequences were successfully amplified from the CVL samples from these two participants plus two others (CAP261 and CAP270) who had CVL viral loads of less than 50 copies/ml.

View this table:
  • View inline
  • View popup
TABLE 1

List of 18 CAPRISA individuals who donated early-infection CVL samples used in this studya

Longitudinal CVL samples from 2.5 to 3.5 years following acute infection were used to isolate additional sequences from these four participants. CVL viral loads were detectable in at least one time point in all cases (Table 2). Amplicons were obtained from the CVL supernatants at all seven sampling time points for CAP270, while fewer time points yielded amplicons for CAP177, CAP217, and CAP261 (5/10, 4/9, and 3/6 time points, respectively). The total number of sequences from CVL varied from 1 to 19 per time point and totaled 42 to 62 over time for each participant (Table 2). Similar numbers of HIV-1 gp160 Env sequences from plasma were obtained for all participants at matching time points.

View this table:
  • View inline
  • View popup
TABLE 2

Longitudinal CVL samples from four CAPRISA donors where gp160 was successfully amplified at acute infection

Association between CVL cytokine levels and gp160 amplification during acute infection.We investigated whether there was a correlation between Env amplification from CVL and local immune activation in the genital tract by measuring cytokine levels (36, 37). CVL samples from acute infection were available from 14 of the 18 participants for this analysis. Participants were grouped according to the concentrations of 20 cytokines measured in CVL using unsupervised hierarchical clustering. Three of the four participants with amplifiable gp160 clustered together on the heatmap, suggesting an association with higher concentrations of cytokines (Fig. 1A). Statistical analysis revealed that the proinflammatory cytokine cluster was significantly associated with CVL gp160 amplification (P = 0.024 by Mann-Whitney U test) (Fig. 1B).

FIG 1
  • Open in new tab
  • Download powerpoint
FIG 1

Association between cytokine levels, STIs, and gp160 amplification in CVL at acute infection. (A) Heat map showing CVL cytokine levels, HIV gp160 PCR results, sexually transmitted infections (STIs), and bacterial vaginosis (BV). Participants with amplifiable CVL gp160 are shown in boldface. (B) Confirmatory factor analysis was used to group cytokines according to biological functions and generate factor scores for each cytokine group for each participant. Mann-Whitney U test was used to evaluate differences in factor scores between women with amplifiable gp160 (Pos) and those without (Neg). Lines indicate medians. P values of <0.05 were considered statistically significant and are shown in boldface.

Sexually transmitted infections (STIs) and bacterial vaginosis (BV) frequently result in genital tract inflammation and also increase HIV replication rates in the female genital tract via proinflammatory signaling pathways (38–40). We therefore investigated if the ability to amplify gp160 in the genital tract was related to the presence of STIs and BV. Eight of the 14 participants had evidence of an active STI (Fig. 1A), including the three participants from whom CVL gp160 was amplified. This included CAP177 (Neisseria gonorrhoeae positive), CAP261 (herpes simplex virus 2 PCR positive), and CAP217 (Mycoplasma genitalium positive), who all had infections known to be associated with increased HIV shedding (41–44). However, the presence of an STI was not associated with gp160 amplification (P = 0.5804 by Fisher's exact test). Although all four participants with amplifiable gp160 had BV, 6/10 participants from whom gp160 was not amplifiable also had BV, and the difference was not statistically significant (P = 0.2507 by Fisher's exact test).

We next performed logistic regression to further evaluate the relationship between inflammation and amplification. STIs, BV, and CVL VL were not significantly associated with proinflammatory cytokines (P = 0.296, P = 0.212, and P = 0.141, respectively). However, despite the small sample size, proinflammatory cytokines remained significantly associated with amplification after adjusting for STIs and CVL VL (P = 0.0357 and P = 0.0303, respectively) and approached significance after adjusting for BV (P = 0.0507). Thus, although proinflammatory cytokine production may be influenced by STIs, BV, and CVL VL, this analysis suggests that inflammation was associated with viral amplification regardless of the cause.

Analysis of compartmentalization in plasma and CVL samples.To determine if sequences in the CVL differed from those in plasma, we constructed maximum likelihood trees to identify monophyletic clades comprised of sequences sharing common phenotypic characteristics and ancestry. For all four participants the plasma and CVL sequences were largely intermingled on the trees, although there was some evidence of sequences grouping together by time point and compartment (Fig. 2). This raised the possibility of compartmentalization in these individuals.

FIG 2
  • Open in new tab
  • Download powerpoint
FIG 2

Maximum likelihood trees of CVL and plasma Env sequences from four donors constructed in PhyML. Plasma and CVL sequences are indicated by filled and open circles, respectively, and the circle color represents the different time points. Node support greater than 0.348 is represented by black diamonds. The number of sequences included is shown in parentheses.

We next performed statistical tests for evidence of compartmentalization using Bayesian tip-association significance testing (BaTS) (45). We first analyzed all sequences from all time points (range, 40 to 82 sequences per compartment) and then repeated the analysis with identical sequences removed (range, 22 to 49 sequences per compartment) to rule out the possibility of inaccurate inferences resulting from localized replication (Table 3). There was strong evidence of compartmentalization in CAP177 and CAP217 regardless of whether identical sequences were included or not (Table 3 and Fig. 3A). The monophyletic clade size statistic for CVL was significantly higher than that for plasma for both CAP177 and CAP217, providing more support for genital tract compartmentalization. This was consistent with the hypothesis that viruses move less frequently from the genital tract to the plasma compartment than they do in the opposite direction. There was no detectable compartmentalization in CAP261, with or without identical sequences included in the analysis, while for CAP270 the evidence was lost when identical sequences were removed, suggesting that bursts of local replication can account for the observed compartmentation in this participant (Table 3 and Fig. 3A).

View this table:
  • View inline
  • View popup
TABLE 3

Compartmentalization tests using data sets with monotypic sequences included and excludeda

FIG 3
  • Open in new tab
  • Download powerpoint
FIG 3

Statistical analysis of compartmentalization using BaTS. (A) Analysis of all sequences for each of the 4 participants with or without identical sequences removed. (B) Longitudinal analysis of sequences from 2 participants with evidence of compartmentalization. Each dot represents an independent statistical test for compartmentalization. Circles indicate cases where at least 2 tests were significant (P < 0.05) for that compartment. Blue and red represent CVL and plasma, respectively. The time points and numbers of sequences used in this analysis are shown in Tables 3 and 4.

Having confirmed evidence of compartmentalization in CAP177 and CAP217, we next determined whether this changed during the course of infection by analyzing the data at the four sampling time points per participant that yielded the highest numbers of sequences (range, 11 to 40 sequences per time point) (Table 4). We identified compartment-specific clusters at all time points in CAP177 and at the first and last time points in CAP217 (9 and 190 weeks) (Fig. 3B). We also observed significantly higher monophyletic clade size statistics for CVL than for plasma, providing more support for genital tract compartmentalization than for plasma compartmentalization. In summary, the Bayesian statistical analyses suggested compartmentalization in two of the four participants: in CAP177, where it was persistent, and in CAP217, where it was intermittent.

View this table:
  • View inline
  • View popup
TABLE 4

Longitudinal compartmentalization tests for CAP177 and CAP217 using BaTSa

HIV migration between genital tract and plasma compartments.We next compared viral migration between the plasma and CVL samples of the four individuals to assess the role of restricted viral migration as a cause of compartmentalization. To do this, we estimated the numbers of distinct migration events during the histories of the sampled viruses using Markov jumps in Bayesian evolutionary analyses by sampling trees (BEAST) (46, 47). The sequence phylogenies from all four individuals yielded evidence of more viral migration events from the plasma to the genital tract compartment (Markov counts from 16 to 23) than from the genital tract to the plasma compartment (Fig. 4). This was particularly evident for the CAP177 and CAP217 sequence phylogenies, both of which displayed evidence of only two instances of viruses moving from the genital tract to plasma (i.e., two Markov counts) during the evolutionary histories of all the sampled viruses. In contrast, the CAP261 and CAP270 phylogenies displayed evidence of eight and nine genital tract to plasma migration events, respectively. There was good statistical support for the occurrence of at least some movements from the genital tract to plasma, as indicated by the Bayes factors (BFs) (Fig. 4). Specifically, in all of the participants other than CAP270, the BFs for CVL to plasma movements was >5, indicating that there was approximately greater than 5 times more support for the occurrence of these movements than for their absence. These data suggest a mucosal sieve effect of viral movements from the genital tract to plasma, which is more severe in individuals with evidence of compartmentalization.

FIG 4
  • Open in new tab
  • Download powerpoint
FIG 4

Viral migration events between CVL and plasma compartments. Migration events estimated as Markov counts in BEAST and the Bayes factor (BF) support for the movements between anatomical compartments are shown. Bayes factor values of >5 indicate statistical support for the movements.

Comparison of evolutionary differences between sequences in plasma and CVL.As compartmentalization may arise due to differential viral population diversification in tissues, we estimated and compared the average pairwise genetic distances between the sequences sampled at each of the time points in the separate compartments. We observed differences in diversity patterns between plasma- and CVL-derived sequences for CAP177 and CAP217 over the course of infection (Fig. 5A). This suggested that these two compartments exerted distinct pressures resulting in differential viral population diversification. CAP261 displayed higher viral sequence diversity in CVL than plasma at all time points (P = 0.0422 by two-way analysis of variance [ANOVA] test), but this did not result in detectable viral compartmentalization. CAP270 showed similar diversity patterns and levels in both compartments.

FIG 5
  • Open in new tab
  • Download powerpoint
FIG 5

Comparison of viral evolution in plasma and CVL compartments of four individuals. (A) Longitudinal Env sequence diversity analyses in plasma and CVL (shown in red and blue, respectively) of four individuals. The average nucleotide pairwise distances were estimated in MEGA6. (B) Evolutionary rates and time of the most recent common ancestor (tMRCA) for plasma and CVL sequences estimated in BEAST using sequences from all time points. CAP177 showed clear differences between CVL- and plasma-derived sequences and is highlighted with an asterisk.

We next assessed whether compartmentalization was a result of differences in evolutionary rates and the ancestry of the viral lineages in the separate anatomical compartments using BEAST (48). We used all sequences obtained at all available time points for these analyses. In three of the four participants, no differences in either estimated nucleotide substitution rates or estimated times to most recent common ancestors (tMRCAs) were noted between the CVL and plasma sequences (Fig. 5B). However, for CAP177, the estimated nucleotide substitution rates and the tMRCA of plasma-derived sequences were significantly different from those of the CVL-derived sequences, as indicated by the 95% high posterior density (HPD) intervals that did not overlap (Fig. 5B, asterisk). In addition, for both CAP177 and CAP261 the estimated tMRCA for all sequences was greater than the actual time of infection, confirming that these individuals were likely to have been initially infected by multiple variants (49, 50, and unpublished data). In summary, these findings show that differences in nucleotide substitution rates and tMRCA of plasma- and CVL-derived gp160 sequences were only observed in viruses infecting CAP177, the participant displaying the strongest evidence of compartmentalization.

Comparison of CVL and plasma amino acid sequences in participants with evidence of compartmentalization.We next compared amino acids in the Env sequences at all sites in the nonoverlapping regions to identify compartment-specific differences between the plasma- and CVL-derived viruses. Using the highlighter tool on the HIV LANL website (51), we identified a total of 43 and 31 amino acid residues in CAP177 and CAP217 Env sequences that were either more or less common in CVL-derived viruses than in plasma-derived viruses, by a margin of 40% to 100%. We performed the comparisons using plasma and CVL sequences at time points that showed evidence of compartmentalization. The relative frequencies of synonymous and nonsynonymous substitutions within the codons encoding these amino acids estimated using the FUBAR (52) and MEME (53) natural selection detection methods suggested that these amino acid differences were a consequence of positive selection in CAP177 and both positive selection and insertions/deletions in CAP217 (Fig. 6). These amino acid differences resulted in charge differences at similar positions in the Envs of the plasma- and CVL-derived sequences, suggesting that different amino acids are preferred at these sites in the different compartments. In CAP217, insertions were more common in the V1V2 regions of CVL-derived sequences than they were in plasma-derived sequences (data not shown). These amino acid differences also increased with time in both participants (Fig. 6). When we compared the distribution of these sites on the Env of both participants, they were mostly in the V4 and C4 regions of CAP177 Env sequences and in the V1V2 regions of CAP217 Env sequences. In summary, these results suggest that the compartmentalization observed in CAP177 and CAP217 was associated with distinct, possibly compartment-specific, selection acting at gp160 codon sites and/or the differential accumulation in gp160 of insertions and deletions in CVL-derived and plasma-derived viruses.

FIG 6
  • Open in new tab
  • Download powerpoint
FIG 6

Identification of HIV-1 Env glycoprotein sites that distinguish CVL and plasma sequences in individuals with evidence of compartmentalization. (A) Number of sites that are different between plasma and CVL sequences are shown in gray (P value of ≤0.05), positive selection on those sites estimated in FUBAR and MEME are in black, insertions/deletions (INDELS) on the sites are shown in green, and the amino acid differences that resulted in charge changes are shown in purple. (B and C) Distribution of the amino acid differences on the glycoprotein Envs over time. The bars are colored according to time point.

DISCUSSION

Our study provides evidence of compartmentalization of HIV-1 subtype C in the genital tract in two of four women studied. Using multiple analytical approaches, we showed that compartmentalization could be persistent or intermittent. Furthermore, we identified Env features in viruses from the genital tract that differentiated them from those found in plasma.There was evidence of restricted migrations of viruses from the genital tract to plasma in all four cases, which was more pronounced in individuals with compartmentalization. These data suggest that the female genital tract and the plasma can, in some cases, act as separate compartments, each with a virus population that evolves with a degree of independence from the other compartment. This highlights the fact that compartmentalization can occur in individuals to different degrees, which could impact the evolutionary dynamics of HIV-1, which vary from person to person (54).

Studies focusing on the detection and characterization of viral populations in the female genital tract have proven difficult due to challenges in collecting genital tract samples and the generally low viral loads in this compartment (34, 55–57). We made use of CVL samples that were collected at multiple time points from women in the CAPRISA cohort enrolled during acute HIV-1 infection and monitored through to chronic infection (36). Although sampling by means of CVL yields a good representation of a large genital tract area, the high degree of genital fluid dilution likely contributed to our failure to amplify Env from most of the CVL samples. Other studies that have had greater success amplifying HIV sequences from the female genital tract have made use of swabs or endocervical cytobrushes (56, 58–61). However, these methods capture only the viral population at the specific site in the cervix from which samples were taken and cannot be used to study cytokine levels. The use of CVL samples allowed us to discover that amplification of gp160 was significantly associated with levels of proinflammatory cytokines in the female genital tract. Furthermore, all four women from which viral sequences in CVL samples were amplifiable at the acute infection stage had clinical or laboratory evidence of an STI and/or detectable CVL viral loads. Local immune activation associated with STIs often results in an influx of leukocytes, elevated cytokine concentrations, and increased HIV shedding that may have favored Env amplification (61, 62).

We used a combination of genetic distance-based methods, Bayesian methods, and natural selection analyses of sequences sampled from plasma and the genital tract to detect and characterize compartmentalization of viral populations at these sites. Previous studies have used approaches such as genetic diversity and phylogenetic analyses to infer compartmentalization (23, 24, 27, 30), but as shown here, it is difficult to achieve robust conclusions based on the results from a single analytical approach. Until recently, previous compartmentalization studies did not account for low diversity and monotypic sequences which could occur because of local viral replication (32, 33). We accounted for these potentially confounding effects by repeating analyses with identical sequences removed and ensuring that almost equal numbers of single-genome amplification (SGA)-derived gp160 sequences were analyzed from CVL and plasma at matched time points. The numbers of sequences examined impacted the analyses in one participant (CAP270): time points with the most sequences (19 to 20 sequences at 9 and 190 weeks) showed strong statistical support compared to the time points with the lowest number of sequences (6 in plasma and 5 in CVL at 60 and 110 weeks), a finding that is probably attributable to the statistical power to detect compartmentalization increasing with increasing numbers of sampled sequences. In CAP177, however, compartmentalization was detectable at all time points regardless of the number of sequences examined. We confirmed evidence of compartmentalization with a combination of approaches that examined different aspects of viral evolution and identified individual-specific residues in Env that differentiated CVL-derived viruses from plasma-derived viruses.

Evidence of HIV compartmentalization between the female genital tract and plasma was strongly supported in two of the four participants. In CAP177, compartmentalization was persistent, with evidence for restricted viral movements from the genital tract to the plasma found at all four time points up to 186 weeks postinfection. In CAP217, compartmentalization was only detected at the first time point and at 190 weeks postinfection and not at the other two time points. Intermittent compartmentalization of HIV populations between the plasma and female genital tract has not been observed previously but has been reported between the male genital tract and the blood (16). CAP177 and CAP217 were the only two individuals who had detectable levels of virus in CVL at acute infection, suggesting that local viral replication and diversification favored subsequent compartmentalization of the genital tract HIV population from that in the blood.

Two of the study participants, CAP261 and CAP270, displayed no convincing evidence of compartmentalization, in that both CVL and plasma populations displayed similar patterns of diversity, indistinguishable evolutionary rates, and tMRCA estimates. There were also similar numbers of migration events detected in both directions between the genital tract and plasma. Other studies have similarly reported the lack of compartmentalization between the female genital tract and blood (20, 22, 27). By studying longitudinal samples, we have further shown that compartmentalization can occur sporadically in some individuals.

Regardless of whether there was strong evidence of compartmentalization, all four participants consistently showed higher numbers of virus migration events from the plasma to the genital tract compartment. Low levels of virus in the CVL may have limited our ability to detect migration events from the CVL compartment. However, diversity rather than viral population size has been shown to be a key factor in detecting compartmentalization (18, 25, 63). Here, we show that the levels of diversity were similar in both compartments despite the higher viral levels in plasma, which enabled us to quantify migration events in both directions.

The Env amino acid composition of the two individuals with evidence of compartmentalization showed distinctive differences that may have impacted properties of the protein, such as its charge distribution. Such differences have been reported to significantly alter key virologic properties, including cellular tropism and transmission (64). We speculate that the transmitted/founder (T/F) viruses in these individuals had properties that favored the genital tract over the plasma compartment. Individuals with no compartmentalization may have had T/F viruses with amino acid properties that were equally well adapted to the plasma and genital tract compartments. Persistent compartmentalization was associated with distinct evolutionary rates and tMRCA differences between the plasma and CVL-derived sequences, whereas intermittent compartmentalization was associated with more subtle evolutionary differences. A recent study showing that early HIV-1 viruses from the endocervix had higher degrees of genetic diversity than those from blood is consistent with the independent evolution of viruses in the female genital tract and/or the presence of a mucosal sieve effect between these two compartments (34).

In conclusion, compartmentalization of HIV populations between the female genital tract and plasma likely does occur in some individuals despite frequent movements of viruses from the blood to the female genital tract. Our data indicate that in cases where compartmentalization occurs, distinct genetic features of viral Env populations in the genital tract may impact the efficacy of microbicides and vaccines designed to provide mucosal immunity.

MATERIALS AND METHODS

Participants.This study made use of participants from the CAPRISA 002 Acute Infection study, a cohort of 245 uninfected high-risk women, which was established in KwaZulu-Natal in 2004 (65). The parent study was reviewed and approved by the research ethics committees of the University of KwaZulu-Natal (E013/04), the University of Cape Town (025/2004), and the University of the Witwatersrand (MM040202). All participants provided written informed consent for sample storage for research purposes. Ethics approval for this substudy was obtained from the University of the Witwatersrand (M160340).

Stored plasma and CVL samples from 18 women (ages 18 to 59 years) collected during acute HIV infection were selected for this study. The time of infection was defined as the midpoint between the last HIV-1 antibody-negative test and the first HIV-1 antibody-positive test or estimated to be 14 days prior to a positive RNA PCR assay result when the HIV-1 enzyme immunoassay (EIA) was negative. Plasma and CVL samples were collected at multiple matched time points from acute to chronic HIV infection (2 to 190 weeks postinfection).

Collection of CVL samples.The cervix was bathed with 10 ml of phosphate-buffered saline before aspirating the fluid from the posterior fornix. This was repeated with the same fluid 2 to 3 times. The collected fluid was centrifuged at 400 × g for 10 min to fractionate the cellular component from the supernatant. The supernatant was aliquoted and stored at −70°C. CVL samples were not collected during menstruation, and supernatants with macroscopic blood contamination were not used. The presence of microscopic blood was detected with Roche Cobas combur dipsticks, which detect 5 to 10 erythrocytes/µl (1+ score) to 250 erythrocytes/µl (4+ score). Viral load was measured in the 1-ml CVL supernatants with NucliSENS EasyQ HIV1, version 1.2, which has a limit of detection of 50 copies per ml.

Isolation of HIV RNA from CVL supernatant and plasma.Two different extraction procedures were tested to isolate viral RNA from CVL, either VitalVirus followed by QIAamp viral RNA Minikit (VitalVirus+QIAamp) or QIAamp viral RNA Minikit on its own. The µMACS VitalVirus HIV isolation kit (Miltenyi Biotec, Bergisch Gladbach, Germany) captures virus particles with magnetic microbeads that bind to host-derived CD44 in the viral envelope. Viral RNA was then isolated from the captured concentrated, intact virions with the QIAamp viral RNA Minikit (Qiagen, Hilden, Germany).

Using the QIAamp viral RNA Minikit, RNA was isolated from 0.2 to 1.75 ml CVL supernatant or from 140 µl plasma. When sample volumes exceeded 0.6 ml, the supernatant was centrifuged at 23,000 × g for 1 h at 4°C and the supernatant was discarded, except for 140 µl in the base of the tube. In order to ensure that all PCR products had been amplified from cDNA and not DNA, during RNA purification an on-column DNase digestion step (RNase-free DNase set; Qiagen) was added to the QIAamp procedure. The QIAamp extraction procedure on its own yielded more amplicons from CVL than VitalVirus+QIAamp, so the former was used for all subsequent amplifications.

SGA and gp160 sequencing.Viral RNA was reverse transcribed to cDNA using SuperScript III reverse transcriptase (Invitrogen, Carlsbad, CA) and the env primer OFM19 (66). The complete env was amplified in a nested PCR. In order to ensure that env genes were amplified from single cDNA copies, cDNA prepared from plasma was diluted before PCR until fewer than 30% of reactions were positive. In most cases, it was not necessary to dilute the CVL cDNA, as few reactions were positive. Amplicons were directly sequenced using the ABI PRISM BigDye Terminator cycle sequencing ready reaction kit (Applied Biosystems, Foster City, CA) and resolved on an ABI 3100 automated genetic analyzer. The full-length env sequences were assembled and edited using Sequencher v.4.5 software (Gene Codes, Ann Arbor, MI). Amplicons with double peaks or interrupted reading frames were not included in the sequence analysis.

Measurement of cytokines.The concentrations of 20 cytokines were measured in CVL samples from acute infection using Luminex multiplex flow-cytometric assays. After thawing, CVL samples were prefiltered by centrifugation using 0.2-μm cellulose acetate filters (Sigma, USA). Concentrations of eotaxin/CCL11, fractalkine/CX3CL1, granulocyte colony-stimulating factor (G-CSF), interleukin-1α (IL-1α), IL-8/CXCL8, IL-12p40, IL-15, monocyte chemotactic protein 1 (MCP-1)/CCL2, macrophage inflammatory protein 1α (MIP-1α)/CCL3, MIP-1β/CCL4, RANTES/CCL5, and soluble CD40 ligand (sCD40L) were measured using human cytokine LINCOplex kits (LINCO Research, MO, USA) according to the manufacturer’s protocol. The sensitivity of these kits ranged between 0.3 and 18.3 pg/ml for each of the 12 cytokines measured. Concentrations of IL-1β, IL-2, IL-6, IL-7, IL-10, IL-12p70, granulocyte macrophage (GM)-CSF, and tumor necrosis factor alpha (TNF-α) were measured in CVL using high-sensitivity human cytokine LINCOplex kits. The sensitivity ranged between 0.01 and 0.48 pg/ml for each of the 8 cytokines measured with high sensitivity. Data were collected using the Bio-Plex suspension array reader (Bio-Rad Laboratories Inc.), and a 5 PL regression formula was used to calculate sample concentrations from the standard curves. Data were analyzed using Bio-Plex manager software (version 4). Cytokine concentrations that were below the lower limit of detection of the assay were reported as the midpoint between the lowest concentration measured for each cytokine and zero.

Multivariate statistical analyses were performed using STATA (StataCorp, Texas, USA), and a hierarchical clustering analysis was performed using R. Confirmatory factor analysis was used to group cytokines according to biological functions and to generate factor scores for each participant. Factor scores are linear combinations of the concentrations of each cytokine in a-factor, weighted according to their factor loadings. Cytokines were grouped as proinflammatory (IL-1α, IL-1β, IL-6, IL-12p40, IL-12p70, and TNF-α), hematopoietic (G-CSF and GM-CSF), chemokines (IL-8, fractalkine, eotaxin, MCP-1, MIP-1α, MIP-1β, and RANTES), anti-inflammatory (IL-10), and adaptive immune mediators (IL-2, IL-7, IL-15, and sCD40L). Factor scores were compared using Mann-Whitney U test, and P values of <0.05 were considered statistically significant.

Sequence alignments.Envelope (env) nucleotide sequences from each participant were initially aligned with ClustalO (67) using HXB2 as the reference sequence. Sequence alignments were then codon aligned using the Se-Al v2.0a11 (http://tree.bio.ed.ac.uk/software/seal/) sequence alignment editor to avoid the inclusion of DNA encoding frame shifts and mistranslated sequences that would affect downstream analyses.

Phylogenetic analyses.Pairwise genetic distances between sequences were calculated using MEGA, v6 (68), and the statistical tests for significance (P < 0.05) were performed using a two-way ANOVA method with a Sidak’s multiple-comparison test. Maximum likelihood trees were constructed using PHYML (69) implemented in Recombination Detection Program (70). All sequences were analyzed in Data Analysis in Molecular Biology and Evolution (DAMBE), v7, software, and no evidence of nucleotide substitution saturation was found (71). Maximum clade credibility (MCC) trees were produced for CVL and plasma sequences in BEAST, v1.10.4, using best-fit demographic and clock models selected by path sampling and stepping-stone methods (47, 48, 72). The phylogenetic trees were viewed in FigTree (http://tree.bio.ed.ac.uk/software/figtree).

Bayesian analysis of viral compartmentalization.Posterior distributions containing 1,000 trees for both plasma and CVL sequences were constructed in BEAST for all time points and used as input for the BaTS analysis (45). Time points that only had sequences from one compartment type and identical sequences or low-diversity sequences that could inflate the appearance of structure were excluded in subsequent BaTS analyses. The BaTS analysis performs statistical analyses for evidence of lineage movements between locations (the female genital tract and blood plasma) indicative of compartmentalization using the association index (AI), Fitch parsimony score (PS) (also known as the Slatkin Maddison test), and the maximum exclusive single-state clade (MC) tests (45). Evidence of compartmentalization was inferred when significant results for at least two of the three statistical methods were obtained.

Analysis of HIV migration between CVL and plasma compartments.Phylogeography analyses of viral movements between CVL and plasma were performed in BEAST, v1.10.4 (47). The direction of viral flow was determined by applying a discrete diffusion asymmetric model with a Bayesian stochastic search variable selection (BSSVS) and Bayes factor tests to identify the most statistically supported viral movements between the two compartments (73, 74). The average number of migration events between the genital tract and plasma compartments was estimated by reconstructing the state change counts using Markov jumps (46). Bayes factor support of >5 was considered significant statistical evidence for viral movement between compartments (73).

Identifying amino acid differences in viruses from different compartments.Amino acid sites in CVL-derived sequences that were different from those in plasma-derived sequences were identified using the Highlighter tool (http://www.hiv.lanl.gov/). The consensuses of plasma-derived sequences were used to identify amino acid sites that were different from those found in the CVL-derived sequences. Only codons in the nonoverlapping regions of the Env were analyzed. The frequencies of any differences per site and the percent differences were then calculated. Sites that were evolving under positive selection were detected using the Fast Unbiased Bayesian Approximation (FUBAR) and Mixed Effects Model of Evolution (MEME) methods implemented in HyPhy (52, 53, 75).

ACKNOWLEDGMENTS

We thank participants in the CAPRISA cohort for their commitment to this study and the clinic and laboratory staff at CAPRISA for sample collection. We thank staff and students at NICD and UCT for generating the SGAs. We are grateful for funding from the Department of Science and Technology (DST) of South Africa, the South African Medical Research Council, the Poliomyelitis Research Foundation (PRF), and the CAPRISA Centre of Excellence program. B.M. and P.L.M. are supported by the South African Research Chairs Initiative (SARChI) of the DST and the National Research Foundation (NRF) of South Africa (grant no. 98341).

FOOTNOTES

    • Received 22 February 2019.
    • Accepted 27 February 2019.
    • Accepted manuscript posted online 6 March 2019.
  • Copyright © 2019 American Society for Microbiology.

All Rights Reserved.

REFERENCES

  1. 1.↵
    UNAIDS. 2018. Global HIV & AIDS statistics–2018 fact sheet. UNAIDS, Geneva, Switzerland.
  2. 2.↵
    1. Joseph SB,
    2. Swanstrom R,
    3. Kashuba ADM,
    4. Cohen MS
    . 2015. Bottlenecks in HIV-1 transmission: insights from the study of founder viruses. Nat Rev Microbiol 13:414–425. doi:10.1038/nrmicro3471.
    OpenUrlCrossRefPubMed
  3. 3.↵
    1. Blackard JT
    . 2012. HIV compartmentalization: a review on a clinically important phenomenon. Curr HIV Res 10:133–142. doi:10.2174/157016212799937245.
    OpenUrlCrossRefPubMedWeb of Science
  4. 4.↵
    1. Gantner P,
    2. Ghosn J
    . 2018. Genital reservoir: a barrier to functional cure? Curr Opin HIV AIDS 13:1. doi:10.1097/COH.0000000000000486.
    OpenUrlCrossRef
  5. 5.↵
    1. Frost SD,
    2. Dumaurier MJ,
    3. Wain-Hobson S,
    4. Brown AJ
    . 2001. Genetic drift and within-host metapopulation dynamics of HIV-1 infection. Proc Natl Acad Sci U S A 98:6975–6980. doi:10.1073/pnas.131056998.
    OpenUrlAbstract/FREE Full Text
  6. 6.↵
    1. Power C,
    2. McArthur JC,
    3. Johnson RT,
    4. Griffin DE,
    5. Glass JD,
    6. Perryman S,
    7. Chesebro B
    . 1994. Demented and nondemented patients with AIDS differ in brain-derived human immunodeficiency virus type 1 envelope sequences. J Virol 68:4643–4649.
    OpenUrlAbstract/FREE Full Text
  7. 7.↵
    1. Ohagen A,
    2. Devitt A,
    3. Kunstman KJ,
    4. Gorry PR,
    5. Rose PP,
    6. Korber B,
    7. Taylor J,
    8. Levy R,
    9. Murphy RL,
    10. Wolinsky SM,
    11. Gabuzda D
    . 2003. Genetic and functional analysis of full-length human immunodeficiency virus type 1 env genes derived from brain and blood of patients with AIDS. J Virol 77:12336–12345. doi:10.1128/JVI.77.22.12336-12345.2003.
    OpenUrlAbstract/FREE Full Text
  8. 8.↵
    1. Ritola K,
    2. Robertson K,
    3. Fiscus SA,
    4. Hall C,
    5. Swanstrom R
    . 2005. Increased human immunodeficiency virus type 1 (HIV-1) env compartmentalization in the presence of HIV-1-associated dementia. J Virol 79:10830–10834. doi:10.1128/JVI.79.16.10830-10834.2005.
    OpenUrlAbstract/FREE Full Text
  9. 9.↵
    1. Dunfee RL,
    2. Thomas ER,
    3. Gorry PR,
    4. Wang J,
    5. Taylor J,
    6. Kunstman K,
    7. Wolinsky SM,
    8. Gabuzda D
    . 2006. The HIV Env variant N283 enhances macrophage tropism and is associated with brain infection and dementia. Proc Natl Acad Sci U S A 103:15160–15165. doi:10.1073/pnas.0605513103.
    OpenUrlAbstract/FREE Full Text
  10. 10.↵
    1. Harrington PR,
    2. Schnell G,
    3. Letendre SL,
    4. Ritola K,
    5. Robertson K,
    6. Hall C,
    7. Burch CL,
    8. Jabara CB,
    9. Moore DT,
    10. Ellis RJ,
    11. Price RW,
    12. Swanstrom R
    . 2009. Cross-sectional characterization of HIV-1 env compartmentalization in cerebrospinal fluid over the full disease course. AIDS 23:907–915. doi:10.1097/QAD.0b013e3283299129.
    OpenUrlCrossRefPubMedWeb of Science
  11. 11.↵
    1. Stefic K,
    2. Chaillon A,
    3. Bouvin-Pley M,
    4. Moreau A,
    5. Braibant M,
    6. Bastides F,
    7. Gras G,
    8. Bernard L,
    9. Barin F
    . 2017. Probing the compartmentalization of HIV-1 in the central nervous system through its neutralization properties. PLoS One 12:e0181680. doi:10.1371/journal.pone.0181680.
    OpenUrlCrossRef
  12. 12.↵
    1. Brown RJP,
    2. Peters PJ,
    3. Caron C,
    4. Gonzalez-Perez MP,
    5. Stones L,
    6. Ankghuambom C,
    7. Pondei K,
    8. McClure CP,
    9. Alemnji G,
    10. Taylor S,
    11. Sharp PM,
    12. Clapham PR,
    13. Ball JK
    . 2011. Intercompartmental recombination of HIV-1 contributes to env intrahost diversity and modulates viral tropism and sensitivity to entry inhibitors. J Virol 85:6024–6037. doi:10.1128/JVI.00131-11.
    OpenUrlAbstract/FREE Full Text
  13. 13.↵
    1. Zhu T,
    2. Wang N,
    3. Carr A,
    4. Nam DS,
    5. Moor-Jankowski R,
    6. Cooper DA,
    7. Ho DD
    . 1996. Genetic characterization of human immunodeficiency virus type 1 in blood and genital secretions: evidence for viral compartmentalization and selection during sexual transmission. J Virol 70:3098–3107.
    OpenUrlAbstract/FREE Full Text
  14. 14.↵
    1. Byrn RA,
    2. Zhang D,
    3. Eyre R,
    4. McGowan K,
    5. Kiessling AA
    . 1997. HIV-1 in semen: an isolated virus reservoir. Lancet 350:1141. doi:10.1016/S0140-6736(97)24042-0.
    OpenUrlCrossRefPubMedWeb of Science
  15. 15.↵
    1. Coombs RW,
    2. Speck CE,
    3. Hughes JP,
    4. Lee W,
    5. Sampoleo R,
    6. Ross SO,
    7. Dragavon J,
    8. Peterson G,
    9. Hooton TM,
    10. Collier AC,
    11. Corey L,
    12. Koutsky L,
    13. Krieger JN
    . 1998. Association between culturable human immunodeficiency virus type 1 (HIV‐1) in semen and HIV‐1 RNA levels in semen and blood: evidence for compartmentalization of HIV‐1 between semen and blood. J Infect Dis 177:320–330. doi:10.1086/514213.
    OpenUrlCrossRefPubMedWeb of Science
  16. 16.↵
    1. Gupta P,
    2. Leroux C,
    3. Patterson BK,
    4. Kingsley L,
    5. Rinaldo C,
    6. Ding M,
    7. Chen Y,
    8. Kulka K,
    9. Buchanan W,
    10. McKeon B,
    11. Montelaro R
    . 2000. Human immunodeficiency virus type 1 shedding pattern in semen correlates with the compartmentalization of viral quasi species between blood and semen. J Infect Dis 182:79–87. doi:10.1086/315644.
    OpenUrlCrossRefPubMedWeb of Science
  17. 17.↵
    1. Kariuki SM,
    2. Selhorst P,
    3. Ariën KK,
    4. Dorfman JR
    . 2017. The HIV-1 transmission bottleneck. Retrovirology 14:22. doi:10.1186/s12977-017-0343-8.
    OpenUrlCrossRef
  18. 18.↵
    1. Pillai SK,
    2. Good B,
    3. Pond SK,
    4. Wong JK,
    5. Strain MC,
    6. Richman DD,
    7. Smith DM
    . 2005. Semen-specific genetic characteristics of human immunodeficiency virus type 1 env. J Virol 79:1734–1742. doi:10.1128/JVI.79.3.1734-1742.2005.
    OpenUrlAbstract/FREE Full Text
  19. 19.↵
    1. Anderson JA,
    2. Ping L-H,
    3. Dibben O,
    4. Jabara CB,
    5. Arney L,
    6. Kincer L,
    7. Tang Y,
    8. Hobbs M,
    9. Hoffman I,
    10. Kazembe P,
    11. Jones CD,
    12. Borrow P,
    13. Fiscus S,
    14. Cohen MS,
    15. Swanstrom R
    . 2010. HIV-1 populations in semen arise through multiple mechanisms. PLoS Pathog 6:e1001053. doi:10.1371/journal.ppat.1001053.
    OpenUrlCrossRefPubMed
  20. 20.↵
    1. Poss M,
    2. Rodrigo AG,
    3. Gosink JJ,
    4. Learn GH,
    5. de Vange Panteleeff D,
    6. Martin HL,
    7. Bwayo J,
    8. Kreiss JK,
    9. Overbaugh J
    . 1998. Evolution of envelope sequences from the genital tract and peripheral blood of women infected with clade A human immunodeficiency virus type 1. J Virol 72:8240–8251.
    OpenUrlAbstract/FREE Full Text
  21. 21.↵
    1. Wright TC,
    2. Subbarao S,
    3. Ellerbrock TV,
    4. Lennox JL,
    5. Evans-Strickfaden T,
    6. Smith DG,
    7. Hart CE
    . 2001. Human immunodeficiency virus 1 expression in the female genital tract in association with cervical inflammation and ulceration. Am J Obstet Gynecol 184:279–285. doi:10.1067/mob.2001.108999.
    OpenUrlCrossRefPubMedWeb of Science
  22. 22.↵
    1. Chomont N,
    2. Hocini H,
    3. Grésenguet G,
    4. Brochier C,
    5. Bouhlal H,
    6. Andréoletti L,
    7. Becquart P,
    8. Charpentier C,
    9. de Dieu Longo J,
    10. Si-Mohamed A,
    11. Kazatchkine MD,
    12. Bélec L
    . 2007. Early archives of genetically-restricted proviral DNA in the female genital tract after heterosexual transmission of HIV-1. AIDS 21:153–162. doi:10.1097/QAD.0b013e328011f94b.
    OpenUrlCrossRefPubMed
  23. 23.↵
    1. Ellerbrock TV,
    2. Lennox JL,
    3. Clancy KA,
    4. Schinazi RF,
    5. Wright TC,
    6. Pratt‐Palmore M,
    7. Evans-Strickfaden T,
    8. Schnell C,
    9. Pai R,
    10. Conley LJ,
    11. Parrish‐Kohler EE,
    12. Bush TJ,
    13. Tatti K,
    14. Hart CE
    . 2001. Cellular replication of human immunodeficiency virus type 1 occurs in vaginal secretions. J Infect Dis 184:28–36. doi:10.1086/321000.
    OpenUrlCrossRefPubMedWeb of Science
  24. 24.↵
    1. Sullivan ST,
    2. Mandava U,
    3. Evans-Strickfaden T,
    4. Lennox JL,
    5. Ellerbrock TV,
    6. Hart CE
    . 2005. Diversity, divergence, and evolution of cell-free human immunodeficiency virus type 1 in vaginal secretions and blood of chronically infected women: associations with immune status. J Virol 79:9799–9809. doi:10.1128/JVI.79.15.9799-9809.2005.
    OpenUrlAbstract/FREE Full Text
  25. 25.↵
    1. Kemal KS,
    2. Foley B,
    3. Burger H,
    4. Anastos K,
    5. Minkoff H,
    6. Kitchen C,
    7. Philpott SM,
    8. Gao W,
    9. Robison E,
    10. Holman S,
    11. Dehner C,
    12. Beck S,
    13. Meyer WA,
    14. Landay A,
    15. Kovacs A,
    16. Bremer J,
    17. Weiser B
    . 2003. HIV-1 in genital tract and plasma of women: compartmentalization of viral sequences, coreceptor usage, and glycosylation. Proc Natl Acad Sci U S A 100:12972–12977. doi:10.1073/pnas.2134064100.
    OpenUrlAbstract/FREE Full Text
  26. 26.↵
    1. De Pasquale MP,
    2. Leigh Brown AJ,
    3. Uvin SC,
    4. Allega-Ingersoll J,
    5. Caliendo AM,
    6. Sutton L,
    7. Donahue S,
    8. D'Aquila RT
    . 2003. Differences in HIV-1 pol sequences from female genital tract and blood during antiretroviral therapy. J Acquir Immune Defic Syndr 34:37–44. doi:10.1097/00126334-200309010-00005.
    OpenUrlCrossRefPubMedWeb of Science
  27. 27.↵
    1. Philpott S,
    2. Burger H,
    3. Tsoukas C,
    4. Foley B,
    5. Anastos K,
    6. Kitchen C,
    7. Weiser B
    . 2005. Human immunodeficiency virus type 1 genomic RNA sequences in the female genital tract and blood: compartmentalization and intrapatient recombination. J Virol 79:353–363. doi:10.1128/JVI.79.1.353-363.2005.
    OpenUrlAbstract/FREE Full Text
  28. 28.↵
    1. Andreoletti L,
    2. Skrabal K,
    3. Perrin V,
    4. Chomont N,
    5. Saragosti S,
    6. Gresenguet G,
    7. Moret H,
    8. Jacques J,
    9. Longo JDD,
    10. Matta M,
    11. Mammano F,
    12. Belec L
    . 2007. Genetic and phenotypic features of blood and genital viral populations of clinically asymptomatic and antiretroviral-treatment-naive clade A human immunodeficiency virus type 1-infected women. J Clin Microbiol 45:1838–1842. doi:10.1128/JCM.00113-07.
    OpenUrlAbstract/FREE Full Text
  29. 29.↵
    1. Tirado G,
    2. Jove G,
    3. Reyes E,
    4. Sepulveda G,
    5. Yamamura Y,
    6. Singh DP,
    7. Kumar A
    . 2005. Differential evolution of cell-associated virus in blood and genital tract of HIV-infected females undergoing HAART. Virology 334:299–305. doi:10.1016/j.virol.2005.01.030.
    OpenUrlCrossRefPubMedWeb of Science
  30. 30.↵
    1. Adal M,
    2. Ayele W,
    3. Wolday D,
    4. Dagne K,
    5. Messele T,
    6. Tilahun T,
    7. Berkhout B,
    8. Mayaan S,
    9. Pollakis G,
    10. Dorigo-Zetsma W
    . 2005. Evidence of genetic variability of human immunodeficiency virus type 1 in plasma and cervicovaginal lavage in Ethiopian women seeking care for sexually transmitted infections. AIDS Res Hum Retroviruses 21:649–653. doi:10.1089/aid.2005.21.649.
    OpenUrlCrossRefPubMedWeb of Science
  31. 31.↵
    1. Kemal KS,
    2. Burger H,
    3. Mayers D,
    4. Anastos K,
    5. Foley B,
    6. Kitchen C,
    7. Huggins P,
    8. Schroeder T,
    9. Picchio G,
    10. Back S,
    11. Gao W,
    12. Meyer IIW,
    13. Weiser B
    . 2007. HIV‐1 drug resistance in variants from the female genital tract and plasma. J Infect Dis 195:535–545. doi:10.1086/510855.
    OpenUrlCrossRefPubMed
  32. 32.↵
    1. Bull M,
    2. Learn G,
    3. Genowati I,
    4. McKernan J,
    5. Hitti J,
    6. Lockhart D,
    7. Tapia K,
    8. Holte S,
    9. Dragavon J,
    10. Coombs R,
    11. Mullins J,
    12. Frenkel L
    . 2009. Compartmentalization of HIV-1 within the female genital tract Is due to monotypic and low-diversity variants not distinct viral populations. PLoS One 4:e7122. doi:10.1371/journal.pone.0007122.
    OpenUrlCrossRefPubMed
  33. 33.↵
    1. Bull ME,
    2. Heath LM,
    3. McKernan-Mullin JL,
    4. Kraft KM,
    5. Acevedo L,
    6. Hitti JE,
    7. Cohn SE,
    8. Tapia KA,
    9. Holte SE,
    10. Dragavon JA,
    11. Coombs RW,
    12. Mullins JI,
    13. Frenkel LM
    . 2013. Human immunodeficiency viruses appear compartmentalized to the female genital tract in cross-sectional analyses but genital lineages do not persist over time. J Infect Dis 207:1206–1215. doi:10.1093/infdis/jit016.
    OpenUrlCrossRefPubMed
  34. 34.↵
    1. Klein K,
    2. Nickel G,
    3. Nankya I,
    4. Kyeyune F,
    5. Demers K,
    6. Ndashimye E,
    7. Kwok C,
    8. Chen P-L,
    9. Rwambuya S,
    10. Poon A,
    11. Munjoma M,
    12. Chipato T,
    13. Byamugisha J,
    14. Mugyenyi P,
    15. Salata RA,
    16. Morrison CS,
    17. Arts EJ
    . 2018. Higher sequence diversity in the vaginal tract than in blood at early HIV-1 infection. PLoS Pathog 14:e1006754. doi:10.1371/journal.ppat.1006754.
    OpenUrlCrossRef
  35. 35.↵
    1. González-Alonso J,
    2. Mortensen SP,
    3. Dawson EA,
    4. Secher NH,
    5. Damsgaard R
    . 2006. Erythrocytes and the regulation of human skeletal muscle blood flow and oxygen delivery: role of erythrocyte count and oxygenation state of haemoglobin. J Physiol 572:295–305. doi:10.1113/jphysiol.2005.101121.
    OpenUrlCrossRefPubMedWeb of Science
  36. 36.↵
    1. Roberts L,
    2. Passmore J-A,
    3. Mlisana K,
    4. Williamson C,
    5. Little F,
    6. Bebell LM,
    7. Walzl G,
    8. Abrahams M-R,
    9. Woodman Z,
    10. Abdool Karim Q,
    11. Abdool Karim SS
    . 2012. Genital tract inflammation during early HIV-1 infection predicts higher plasma viral load set point in women. J Infect Dis 205:194–203. doi:10.1093/infdis/jir715.
    OpenUrlCrossRefPubMed
  37. 37.↵
    1. Alonso A,
    2. Lasseigne BN,
    3. Williams K,
    4. Nielsen J,
    5. Ramaker RC,
    6. Hardigan AA,
    7. Johnston B,
    8. Roberts BS,
    9. Cooper SJ,
    10. Marsal S,
    11. Myers RM
    . 2017. aRNApipe: a balanced, efficient and distributed pipeline for processing RNA-seq data in high performance computing environments. Bioinformatics 33:btx023.
    OpenUrl
  38. 38.↵
    1. Ferreira VH,
    2. Nazli A,
    3. Khan G,
    4. Mian MF,
    5. Ashkar AA,
    6. Gray-Owen S,
    7. Kaul R,
    8. Kaushic C
    . 2011. Endometrial epithelial cell responses to coinfecting viral and bacterial pathogens in the genital tract can activate the HIV-1 LTR in an NFκB- and AP-1-dependent manner. J Infect Dis 204:299–308. doi:10.1093/infdis/jir260.
    OpenUrlCrossRefPubMed
  39. 39.↵
    1. Deese J,
    2. Masson L,
    3. Miller W,
    4. Cohen M,
    5. Morrison C,
    6. Wang M,
    7. Ahmed K,
    8. Agot K,
    9. Crucitti T,
    10. Abdellati S,
    11. Van Damme L
    . 2015. Injectable progestin-only contraception is associated with increased levels of pro-inflammatory cytokines in the female genital tract. Am J Reprod Immunol 74:357–367. doi:10.1111/aji.12415.
    OpenUrlCrossRefPubMed
  40. 40.↵
    1. Cohen CR,
    2. Lingappa JR,
    3. Baeten JM,
    4. Ngayo MO,
    5. Spiegel CA,
    6. Hong T,
    7. Donnell D,
    8. Celum C,
    9. Kapiga S,
    10. Delany S,
    11. Bukusi EA
    . 2012. Bacterial vaginosis associated with increased risk of female-to-male HIV-1 transmission: a prospective cohort analysis among African couples. PLoS Med 9:e1001251. doi:10.1371/journal.pmed.1001251.
    OpenUrlCrossRefPubMed
  41. 41.↵
    1. Ghys PD,
    2. Fransen K,
    3. Diallo MO,
    4. Ettiègne-Traoré V,
    5. Coulibaly I-M,
    6. Yeboué KM,
    7. Kalish ML,
    8. Maurice C,
    9. Whitaker JP,
    10. Greenberg AE,
    11. Laga M
    . 1997. The associations between cervicovaginal HIV shedding, sexually transmitted diseases and immunosuppression in female sex workers in Abidjan, Côte dʼIvoire. AIDS 11:F85–F93. doi:10.1097/00002030-199712000-00001.
    OpenUrlCrossRefPubMedWeb of Science
  42. 42.↵
    1. McClelland RS,
    2. Wang CC,
    3. Overbaugh J,
    4. Richardson BA,
    5. Corey L,
    6. Ashley RL,
    7. Mandaliya K,
    8. Ndinya-Achola J,
    9. Bwayo JJ,
    10. Kreiss JK
    . 2002. Association between cervical shedding of herpes simplex virus and HIV-1. AIDS 16:2425–2430. doi:10.1097/00002030-200212060-00007.
    OpenUrlCrossRefPubMedWeb of Science
  43. 43.↵
    1. Gatski M,
    2. Martin DH,
    3. Theall K,
    4. Amedee A,
    5. Clark RA,
    6. Dumestre J,
    7. Chhabra P,
    8. Schmidt N,
    9. Kissinger P
    . 2011. Mycoplasma genitalium infection among HIV-positive women: prevalence, risk factors and association with vaginal shedding. Int J STD AIDS 22:155–159. doi:10.1258/ijsa.2010.010320.
    OpenUrlCrossRefPubMedWeb of Science
  44. 44.↵
    1. Manhart LE,
    2. Mostad SB,
    3. Baeten JM,
    4. Astete SG,
    5. Mandaliya K,
    6. Totten PA
    . 2008. High Mycoplasma genitalium organism burden is associated with shedding of HIV‐1 DNA from the cervix. J Infect Dis 197:733–736. doi:10.1086/526501.
    OpenUrlCrossRefPubMedWeb of Science
  45. 45.↵
    1. Parker J,
    2. Rambaut A,
    3. Pybus OG
    . 2008. Correlating viral phenotypes with phylogeny: accounting for phylogenetic uncertainty. Infect Genet Evol 8:239–246. doi:10.1016/j.meegid.2007.08.001.
    OpenUrlCrossRefPubMedWeb of Science
  46. 46.↵
    1. Minin VN,
    2. Suchard MA
    . 2008. Counting labeled transitions in continuous-time Markov models of evolution. J Math Biol 56:391–412. doi:10.1007/s00285-007-0120-8.
    OpenUrlCrossRefPubMedWeb of Science
  47. 47.↵
    1. Suchard MA,
    2. Lemey P,
    3. Baele G,
    4. Ayres DL,
    5. Drummond AJ,
    6. Rambaut A
    . 2018. Bayesian phylogenetic and phylodynamic data integration using BEAST 1.10. Virus Evol 4:1–5.
    OpenUrlCrossRef
  48. 48.↵
    1. Drummond AJ,
    2. Rambaut A
    . 2007. BEAST: Bayesian evolutionary analysis by sampling trees. BMC Evol Biol 7:214. doi:10.1186/1471-2148-7-214.
    OpenUrlCrossRefPubMed
  49. 49.↵
    1. Anthony C,
    2. York T,
    3. Bekker V,
    4. Matten D,
    5. Selhorst P,
    6. Ferreria R-C,
    7. Garrett NJ,
    8. Karim SSA,
    9. Morris L,
    10. Wood NT,
    11. Moore PL,
    12. Williamson C
    . 2017. Cooperation between strain-specific and broadly neutralizing responses limited viral escape and prolonged the exposure of the broadly neutralizing epitope. J Virol 91:e00828-17. doi:10.1128/JVI.00828-17.
    OpenUrlAbstract/FREE Full Text
  50. 50.↵
    1. Mabvakure BM,
    2. Scheepers C,
    3. Garrett N,
    4. Abdool Karim S,
    5. Williamson C,
    6. Morris L,
    7. Moore PL
    . 5 March 2019. Positive selection at key residues in the HIV Envelope distinguishes broad and strain-specific plasma neutralizing antibodies. J Virol. doi:10.1128/JVI.01685-18.
    OpenUrlCrossRef
  51. 51.↵
    1. Keele BF,
    2. Giorgi EE,
    3. Salazar-Gonzalez JF,
    4. Decker JM,
    5. Pham KT,
    6. Salazar MG,
    7. Sun C,
    8. Grayson T,
    9. Wang S,
    10. Li H,
    11. Wei X,
    12. Jiang C,
    13. Kirchherr JL,
    14. Gao F,
    15. Anderson JA,
    16. Ping L-H,
    17. Swanstrom R,
    18. Tomaras GD,
    19. Blattner WA,
    20. Goepfert PA,
    21. Kilby JM,
    22. Saag MS,
    23. Delwart EL,
    24. Busch MP,
    25. Cohen MS,
    26. Montefiori DC,
    27. Haynes BF,
    28. Gaschen B,
    29. Athreya GS,
    30. Lee HY,
    31. Wood N,
    32. Seoighe C,
    33. Perelson AS,
    34. Bhattacharya T,
    35. Korber BT,
    36. Hahn BH,
    37. Shaw GM
    . 2008. Identification and characterization of transmitted and early founder virus envelopes in primary HIV-1 infection. Proc Natl Acad Sci U S A 105:7552–7557. doi:10.1073/pnas.0802203105.
    OpenUrlAbstract/FREE Full Text
  52. 52.↵
    1. Murrell B,
    2. Moola S,
    3. Mabona A,
    4. Weighill T,
    5. Sheward D,
    6. Kosakovsky Pond SL,
    7. Scheffler K
    . 2013. FUBAR: a fast, unconstrained Bayesian approximation for inferring selection. Mol Biol Evol 30:1196–1205. doi:10.1093/molbev/mst030.
    OpenUrlCrossRefPubMedWeb of Science
  53. 53.↵
    1. Murrell B,
    2. Wertheim JO,
    3. Moola S,
    4. Weighill T,
    5. Scheffler K,
    6. Kosakovsky Pond SL
    . 2012. Detecting individual sites subject to episodic diversifying selection. PLoS Genet 8:e1002764. doi:10.1371/journal.pgen.1002764.
    OpenUrlCrossRefPubMed
  54. 54.↵
    1. Pybus OG,
    2. Rambaut A
    . 2009. Evolutionary analysis of the dynamics of viral infectious disease. Nat Rev Genet 10:540–550. doi:10.1038/nrg2583.
    OpenUrlCrossRefPubMedWeb of Science
  55. 55.↵
    1. Cu-Uvin S,
    2. DeLong AK,
    3. Venkatesh KK,
    4. Hogan JW,
    5. Ingersoll J,
    6. Kurpewski J,
    7. De Pasquale MP,
    8. D'Aquila R,
    9. Caliendo AM
    . 2010. Genital tract HIV-1 RNA shedding among women with below detectable plasma viral load. AIDS 24:2489–2497. doi:10.1097/QAD.0b013e32833e5043.
    OpenUrlCrossRefPubMed
  56. 56.↵
    1. Coombs RW,
    2. Wright DJ,
    3. Reichelderfer PS,
    4. Burns DN,
    5. Cohn J,
    6. Cu-Uvin S,
    7. Baron PA,
    8. Cohen MH,
    9. Landay AL,
    10. Lewis S,
    11. Kovacs A
    , Women’s Health Study 001 Team. 2001. Variation of human immunodeficiency virus type 1 viral RNA levels in the female genital tract: implications for applying measurements to individual women. J Infect Dis 184:1187–1191. doi:10.1086/323660.
    OpenUrlCrossRefPubMedWeb of Science
  57. 57.↵
    1. Homans J,
    2. Christensen S,
    3. Stiller T,
    4. Wang C-H,
    5. Mack W,
    6. Anastos K,
    7. Minkoff H,
    8. Young M,
    9. Greenblatt R,
    10. Cohen M,
    11. Strickler H,
    12. Karim R,
    13. Spencer LY,
    14. Operskalski E,
    15. Frederick T,
    16. Kovacs A
    . 2012. Permissive and protective factors associated with presence, level, and longitudinal pattern of cervicovaginal HIV shedding. J Acquir Immune Defic Syndr 60:99–110. doi:10.1097/QAI.0b013e31824aeaaa.
    OpenUrlCrossRefPubMed
  58. 58.↵
    1. Hart CE,
    2. Lennox JL,
    3. Pratt-Palmore M,
    4. Wright TC,
    5. Schinazi RF,
    6. Evans-Strickfaden T,
    7. Bush TJ,
    8. Schnell C,
    9. Conley LJ,
    10. Clancy KA,
    11. Ellerbrock TV
    . 1999. Correlation of human immunodeficiency virus type 1 RNA levels in blood and the female genital tract. J Infect Dis 179:871–882. doi:10.1086/314656.
    OpenUrlCrossRefPubMedWeb of Science
  59. 59.↵
    1. Kovacs A,
    2. Wasserman SS,
    3. Burns D,
    4. Wright DJ,
    5. Cohn J,
    6. Landay A,
    7. Weber K,
    8. Cohen M,
    9. Levine A,
    10. Minkoff H,
    11. Miotti P,
    12. Palefsky J,
    13. Young M,
    14. Reichelderfer P
    , DATRI Study Group, WIHS Study Group. 2001. Determinants of HIV-1 shedding in the genital tract of women. Lancet 358:1593–1601. doi:10.1016/S0140-6736(01)06653-3.
    OpenUrlCrossRefPubMedWeb of Science
  60. 60.↵
    1. Kovacs A,
    2. Chan LS,
    3. Chen ZC,
    4. Meyer WA,
    5. Muderspach L,
    6. Young M,
    7. Anastos K,
    8. Levine AM
    . 1999. HIV-1 RNA in plasma and genital tract secretions in women infected with HIV-1. J Acquir Immune Defic Syndr 22:124–131. doi:10.1097/00126334-199910010-00003.
    OpenUrlCrossRefPubMedWeb of Science
  61. 61.↵
    1. Andréoletti L,
    2. Grésenguet G,
    3. Chomont N,
    4. Matta M,
    5. Quiniou Y,
    6. Si-Mohamed A,
    7. Bélec L
    . 2003. Comparison of washing and swabbing procedures for collecting genital fluids to assess shedding of human immunodeficiency virus type 1 (HIV-1) RNA in asymptomatic HIV-1-infected women. J Clin Microbiol 41:449–452. doi:10.1128/JCM.41.1.449-452.2003.
    OpenUrlAbstract/FREE Full Text
  62. 62.↵
    1. Mitchell C,
    2. Hitti J,
    3. Paul K,
    4. Agnew K,
    5. Cohn SE,
    6. Luque AE,
    7. Coombs R
    . 2011. Cervicovaginal shedding of HIV type 1 is related to genital tract inflammation independent of changes in vaginal microbiota. AIDS Res Hum Retroviruses 27:35–39. doi:10.1089/aid.2010.0129.
    OpenUrlCrossRefPubMedWeb of Science
  63. 63.↵
    1. Faria NR,
    2. Suchard MA,
    3. Rambaut A,
    4. Lemey P
    . 2011. Toward a quantitative understanding of viral phylogeography. Curr Opin Virol 1:423–429. doi:10.1016/j.coviro.2011.10.003.
    OpenUrlCrossRefPubMed
  64. 64.↵
    1. Blackard JT,
    2. Cohen DE,
    3. Mayer KH
    . 2002. Human immunodeficiency virus superinfection and recombination: current state of knowledge and potential clinical consequences. Clin Infect Dis 34:1108–1114. doi:10.1086/339547.
    OpenUrlCrossRefPubMedWeb of Science
  65. 65.↵
    1. van Loggerenberg F,
    2. Mlisana K,
    3. Williamson C,
    4. Auld SC,
    5. Morris L,
    6. Gray CM,
    7. Abdool Karim Q,
    8. Grobler A,
    9. Barnabas N,
    10. Iriogbe I,
    11. Abdool Karim SS
    . 2008. Establishing a cohort at high risk of HIV infection in South Africa: challenges and experiences of the CAPRISA 002 acute infection study. PLoS One 3:e1954. doi:10.1371/journal.pone.0001954.
    OpenUrlCrossRefPubMed
  66. 66.↵
    1. Salazar-Gonzalez JF,
    2. Bailes E,
    3. Pham KT,
    4. Salazar MG,
    5. Guffey MB,
    6. Keele BF,
    7. Derdeyn CA,
    8. Farmer P,
    9. Hunter E,
    10. Allen S,
    11. Manigart O,
    12. Mulenga J,
    13. Anderson JA,
    14. Swanstrom R,
    15. Haynes BF,
    16. Athreya GS,
    17. Korber BTM,
    18. Sharp PM,
    19. Shaw GM,
    20. Hahn BH
    . 2008. Deciphering human immunodeficiency virus type 1 transmission and early envelope diversification by single-genome amplification and sequencing. J Virol 82:3952–3970. doi:10.1128/JVI.02660-07.
    OpenUrlAbstract/FREE Full Text
  67. 67.↵
    1. Sievers F,
    2. Wilm A,
    3. Dineen D,
    4. Gibson TJ,
    5. Karplus K,
    6. Li W,
    7. Lopez R,
    8. McWilliam H,
    9. Remmert M,
    10. Soding J,
    11. Thompson JD,
    12. Higgins DG
    . 2014. Fast, scalable generation of high-quality protein multiple sequence alignments using Clustal Omega. Mol Syst Biol 7:539–539. doi:10.1038/msb.2011.75.
    OpenUrlCrossRef
  68. 68.↵
    1. Tamura K,
    2. Stecher G,
    3. Peterson D,
    4. Filipski A,
    5. Kumar S
    . 2013. MEGA6: molecular evolutionary genetics analysis version 6.0. Mol Biol Evol 30:2725–2729. doi:10.1093/molbev/mst197.
    OpenUrlCrossRefPubMedWeb of Science
  69. 69.↵
    1. Guindon S,
    2. Delsuc F,
    3. Dufayard J-F,
    4. Gascuel O
    . 2009. Estimating maximum likelihood phylogenies with PhyML. Methods Mol Biol 537:113–137. doi:10.1007/978-1-59745-251-9_6.
    OpenUrlCrossRefPubMedWeb of Science
  70. 70.↵
    1. Martin DP,
    2. Murrell B,
    3. Golden M,
    4. Khoosal A,
    5. Muhire B
    . 2015. RDP4: detection and analysis of recombination patterns in virus genomes. Virus Evol 1:vev003. doi:10.1093/ve/vev003.
    OpenUrlCrossRefPubMed
  71. 71.↵
    1. Xia X
    . 2018. DAMBE7: new and improved tools for data analysis in molecular biology and evolution. Mol Biol Evol 35:1550–1552. doi:10.1093/molbev/msy073.
    OpenUrlCrossRefPubMed
  72. 72.↵
    1. Drummond AJ,
    2. Suchard MA,
    3. Xie D,
    4. Rambaut A
    . 2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol Biol Evol 29:1969–1973. doi:10.1093/molbev/mss075.
    OpenUrlCrossRefPubMedWeb of Science
  73. 73.↵
    1. Lemey P,
    2. Rambaut A,
    3. Drummond AJ,
    4. Suchard MA
    . 2009. Bayesian phylogeography finds its roots. PLoS Comput Biol 5:e1000520. doi:10.1371/journal.pcbi.1000520.
    OpenUrlCrossRefPubMed
  74. 74.↵
    1. Kass RE,
    2. Raftery AE
    . 1995. Bayes factors. J Am Stat Assoc 90:773–795. doi:10.1080/01621459.1995.10476572.
    OpenUrlCrossRefPubMedWeb of Science
  75. 75.↵
    1. Pond SLK,
    2. Muse SV
    . 2005. HyPhy: hypothesis testing using phylogenies, p 125–181. In Statistical methods in molecular evolution. Springer-Verlag, New York, NY.
PreviousNext
Back to top
Download PDF
Citation Tools
Evidence for both Intermittent and Persistent Compartmentalization of HIV-1 in the Female Genital Tract
Batsirai M. Mabvakure, Bronwen E. Lambson, Kavisha Ramdayal, Lindi Masson, Dale Kitchin, Mushal Allam, Salim Abdool Karim, Carolyn Williamson, Jo-Ann Passmore, Darren P. Martin, Cathrine Scheepers, Penny L. Moore, Gordon W. Harkins, Lynn Morris
Journal of Virology May 2019, 93 (10) e00311-19; DOI: 10.1128/JVI.00311-19

Citation Manager Formats

  • BibTeX
  • Bookends
  • EasyBib
  • EndNote (tagged)
  • EndNote 8 (xml)
  • Medlars
  • Mendeley
  • Papers
  • RefWorks Tagged
  • Ref Manager
  • RIS
  • Zotero
Print

Alerts
Sign In to Email Alerts with your Email Address
Email

Thank you for sharing this Journal of Virology article.

NOTE: We request your email address only to inform the recipient that it was you who recommended this article, and that it is not junk mail. We do not retain these email addresses.

Enter multiple addresses on separate lines or separate them with commas.
Evidence for both Intermittent and Persistent Compartmentalization of HIV-1 in the Female Genital Tract
(Your Name) has forwarded a page to you from Journal of Virology
(Your Name) thought you would be interested in this article in Journal of Virology.
CAPTCHA
This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
Share
Evidence for both Intermittent and Persistent Compartmentalization of HIV-1 in the Female Genital Tract
Batsirai M. Mabvakure, Bronwen E. Lambson, Kavisha Ramdayal, Lindi Masson, Dale Kitchin, Mushal Allam, Salim Abdool Karim, Carolyn Williamson, Jo-Ann Passmore, Darren P. Martin, Cathrine Scheepers, Penny L. Moore, Gordon W. Harkins, Lynn Morris
Journal of Virology May 2019, 93 (10) e00311-19; DOI: 10.1128/JVI.00311-19
del.icio.us logo Digg logo Reddit logo Twitter logo CiteULike logo Facebook logo Google logo Mendeley logo
  • Top
  • Article
    • ABSTRACT
    • INTRODUCTION
    • RESULTS
    • DISCUSSION
    • MATERIALS AND METHODS
    • ACKNOWLEDGMENTS
    • FOOTNOTES
    • REFERENCES
  • Figures & Data
  • Info & Metrics
  • PDF

KEYWORDS

compartmentalization
cytokines
evolution
genital tract immunity
human immunodeficiency virus
phylogenetic analysis

Related Articles

Cited By...

About

  • About JVI
  • Editor in Chief
  • Editorial Board
  • Policies
  • For Reviewers
  • For the Media
  • For Librarians
  • For Advertisers
  • Alerts
  • RSS
  • FAQ
  • Permissions
  • Journal Announcements

Authors

  • ASM Author Center
  • Submit a Manuscript
  • Article Types
  • Ethics
  • Contact Us

Follow #Jvirology

@ASMicrobiology

       

 

JVI in collaboration with

American Society for Virology

ASM Journals

ASM journals are the most prominent publications in the field, delivering up-to-date and authoritative coverage of both basic and clinical microbiology.

About ASM | Contact Us | Press Room

 

ASM is a member of

Scientific Society Publisher Alliance

 

American Society for Microbiology
1752 N St. NW
Washington, DC 20036
Phone: (202) 737-3600

Copyright © 2021 American Society for Microbiology | Privacy Policy | Website feedback

Print ISSN: 0022-538X; Online ISSN: 1098-5514