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Multiple independent lineages of HIV-1 persist in breast milk and plasma

Gray, Rebecca Ra,b; Salemi, Marcoa,b; Lowe, Amandaa; Nakamura, Kyle Jc,d; Decker, William Dc; Sinkala, Mosese; Kankasa, Chipepof; Mulligan, Connie Jg; Thea, Donald Mh; Kuhn, Louisei; Aldrovandi, Gracec,d,*; Goodenow, Maureen Ma,j,*

doi: 10.1097/QAD.0b013e328340fdaf
Basic Science

Design: The origin and evolution of HIV-1 in breast milk is unclear, despite the continuing significance of this tissue as a transmitting compartment. To elucidate the evolutionary trajectory of viral populations in a transient mucosal compartment, longitudinal sequences of the envelope glycoprotein (gp120) region from plasma and breast milk spanning the first year after delivery were analyzed in six women infected by HIV-1 subtype C.

Methods: Multiple phylogenetic algorithms were used to elucidate the evolutionary history and spatial structure of virus populations between tissues.

Results: Overall persistent mixing of viral sequences between plasma and breast milk indicated that breast milk is not a distinct genetic viral compartment. Unexpectedly, longitudinal phylogenies showed multiple lineages defined by long branches that included virus from both the breast milk and the plasma. Plasma was unlikely the anatomical origin of the most recent common ancestor (MRCA) in at least three of the patients, although in other women, the temporal origin of the MRCA of the viral populations following delivery occurred well before the onset of breast milk production.

Conclusions: These findings suggest that during pregnancy/lactation, a viral variant distinct from the plasma virus initially seeds the breast milk, followed by subsequent gene flow between the plasma and breast milk tissues. This study indicates the potential for reactivation or reintroduction of distinct lineages during major immunological disruptions during the course of natural infection.

aDepartment of Pathology, Immunology and Laboratory Medicine, USA

bEmerging Pathogens Institute, University of Florida, Gainesville, Florida, USA

cChildren's Hospital of Los Angeles, USA

dUSC Keck School of Medicine, Los Angeles, California, USA

eLusaka District Health Management Team, Zambia

fUniversity Teaching Hospital, University of Zambia, Lusaka, Zambia

gDepartment of Anthropology, University of Florida, Gainesville, Florida, USA

hBoston University School of Public Health, Boston, Massachusetts, USA

iColumbia University, New York, New York, USA

jFlorida Center for AIDS Research, University of Florida, Gainesville, Florida, USA.

*G.A. and M.M.G. contributed equally to the writing of the manuscript.

Received 30 June, 2010

Revised 23 September, 2010

Accepted 27 September, 2010

Correspondence to Maureen M. Goodenow, PhD, 2033 Mowry Road, PO Box 103633, Gainesville, FL 32610-3633, USA. E-mail:

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HIV-1 rapidly evolves as a quasispecies, targeting CD4+ cells, primarily macrophages and T-lymphocytes [1]. Because CD4+ cells are distributed throughout the body, viral variants may replicate and evolve independently in anatomical tissues or compartments without contributing to systemic flow of viral genes [2]. Tissues and cells may also act as viral reservoirs if viral variants circulating earlier in infection are archived and replication is restricted [2–4].

Breast milk is a transient mucosal tissue considered a potential compartment for virus based on physiology of mammary tissue and development of lactation. Breastfeeding remains a major route of maternal transmission of HIV-1 to infants in the developing world, infecting about 14% of infants born to antiretroviral therapy naive mothers [5]. Breast tissue is not only an important transmitting tissue, but also provides a distinct biological site for milk production. Lactating mammary tissue is part of a common mucosal immune system and provides a source of cells, antibodies, and diverse immune factors distinct from those in the circulation [6]. Mammary tissue remodeling begins during the second trimester of pregnancy when cells from the gut lymphoid system home to breast tissue (lactogenesis I). Initially, tight junctions between epithelial cells are permeable, allowing immune cells and plasma proteins from the blood to enter the breast milk directly via the paracellular pathway [7]. The paracellular pathway closes at the time of delivery, and remains blocked until weaning is initiated or inflammation occurs [8], which often corresponds with a concomitant rise in breast milk sodium levels. If HIV-1-infected cells were also blocked from passing between breast milk and plasma during exclusive breast feeding, the viral population in the breast milk may diverge from virus in the plasma, leading to the evolution of ‘breast milk variant(s)’ of virus. The breast milk may also present a unique environment that could select for specific viral variants. Breast milk is an immunologically distinct tissue composed mainly of lymphocytes and macrophages that likely derive from the gut lymphoid tissue [9–13] and appear at the highest concentration during early lactation [14,15]. Although T lymphocytes constitutes less than 10% of the total cell population in breast milk, the magnitude and breadth of the breast milk T-cell repertoire are higher than in peripheral blood and include specificities distinct from circulating plasma T cells [16].

Despite the biological plausibility of a breast milk compartment for virus, only a small number of studies have investigated HIV-1 compartmentalization in breast milk with conflicting results, perhaps reflecting complexities of interpretation of cross-sectional studies, analysis of several different subtypes (HIV-1A, G, B/D), a range of sampling times postpartum (1–12 weeks or 1 year), and/or various analytical methods applied to different regions of the env gene [17–19]. A recent analysis, which was the most comprehensive to date, of cross-sectional breast milk and plasma samples found no evidence for virus compartmentalization immediately postpartum [20]. We designed a novel longitudinal study to examine the evolution of HIV-1 subtype C env glycoprotein (gp120) gene in breast milk and plasma from six women who transmitted virus to their infants either perinatally or through breastfeeding. The goal was to define the relationship of the circulating virus with that in milk and determine how viral populations changed over time.

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Patients and methods


Samples were from participants in the Zambia Exclusive Breastfeeding Study who were therapy naive except for a single dose of nevirapine at the time of labor [21]. Three right and left breast milk and plasma samples from the first-year postpartum from six women (1–6) were analyzed. Three patients presumably transmitted in utero, as their infants were PCR-positive at birth [denoted as ‘in-utero transmitter (IUT)’], whereas three transmitted through breast milk (infants negative prior to PCR-positive at 40 days, denoted as ‘breast milk transmitter’) [22]. Five women had low CD4 T cells (<200 cells/μl) and all had 4 log10 to more than 5 log10 plasma viral levels at the time of delivery (Table 1). All women reported exclusively breastfeeding for 4 months with no mastitis, elevated sodium levels, or other clinical problems during the study.

Table 1

Table 1

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Sequence generation and analysis

Breast milk samples were processed at the site within 4 h of collection. Aliquots of whole breast milk (1 ml) were centrifuged twice at 23 600 × g for 60 min at 4°C to remove the cell fraction. Overall, breast milk samples had only less than 10–1000 cells/μl. Roche Amplicor Ultrasensitive HIV-1 Monitor assay (Roche, Basel, Switzerland) was used as previously described, with an additional third spin performed to remove any remaining cells [23]. RNA was extracted from plasma and breast milk (including a DNase step), reverse transcribed to cDNA, and used as template for amplification of the V1–V5 region of the envelope gp120 gene as previously described [24]. This protocol ensured that no proviral DNA was present in the final template. Two independent amplifications were performed for most samples. Products were cloned and sequenced in the Genome Sequence Service Laboratory at the University of Florida. Sequences have been submitted to Genbank (accession numbers pending). Sequences (∼1000) were classified as subtype C using the Rega subtyping tool ( Alignments of V1–V5 sequences were performed manually using BioEdit v.7.0 and MEGA v.4.0 [25], gap-stripped, and analyzed to identify recombinant sequences [26] that were removed to reduce distortion of phylogenetic relationships. Coreceptor use was inferred using the position specific scoring matrix (PSSM) algorithm specific for HIV-1 subtype C [27].

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Phylogenetic analysis

Coalescent theory provides a solid theoretical framework to study the ancestral relationships of individuals sampled from a population [28], including gene flow patterns and time to most recent common ancestor (TMRCA). Bayesian methodology allows use of prior information in analyses, as well as estimation of probability distributions for each parameter of interest. In this study, the TMRCA (median and 95% high posterior density intervals) were estimated in a Bayesian coalescent framework implemented using the BEAST software package 1.5 [29] with a relaxed molecular clock and a general time reversible with gamma distributed rate variation across sites (GTR+G) model of nucleotide substitution. A particular advantage of the BEAST algorithm is the use of heterogeneous samples to estimate evolutionary parameters under both a strict and relaxed molecular clock [30–32]. For each dataset, the maximum clade credibility (MCC) tree was selected from the posterior tree distribution using the program TreeAnnotator version 1.5. The programs are thoroughly described and available for download at Maximum likelihood trees were inferred using the GTR+G model, without the assumption of the molecular clock, using PhyML [33]. Genetic diversity and divergence calculations were performed with a maximum likelihood-correction model implemented in MEGA v.4.0 [25] and compared using a random-block analysis of variance in GraphPad (GraphPad Software Inc., La Jolla, California, USA).

Population structure among viruses from different tissues at different time points was assessed by a modified Hudson test [34] (implemented at with a Bonferroni-corrected α-value of 0.001. A parsimony analysis was used to infer the most likely tissue for each internal node of the MCC trees, and compartmentalization was tested by the Slatkin and Maddison test for gene flow [35] using the MacClade version 4 program [36].

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Structure index

A tree structure index was developed to quantify how close the observed tree topology is to a theoretical topology displaying perfect compartmentalization. Under complete structure sequences sampled from tissue t i are not intermixed with sequences sampled from tissue t j (ij), and all sequences sampled from t i share the same common ancestor. Given n tissues, each sequence was assigned a state corresponding to the anatomical origin (i) (i = 1, 2, … n). A matrix with equal weights between n tissues was then constructed. Using the MCC tree, the ancestral state of each internal node was estimated using maximum parsimony, and the number of steps (changed from one tissue to another) on the tree was counted [steps observed (S obs)]. Then, a set of 10 000 random trees was generated using the random-joining method, and for each random tree the number of steps was counted. The lower 95% count from this distribution was used as the upper limit of the expected number of steps on a nonrandom tree [steps maximum (S max)]. The minimum number of steps (S min) on a perfectly structured tree is simply n − 1. The structure index is (S maxS obs)/(S maxS min) and scaled from 0 (random structure) to 1 (complete structure) (manuscript in preparation).

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Phylogenetic reconstruction of virus populations over time

Reconstruction of evolution by phylogenetic trees was performed to determine the population structure of virus in breast milk with respect to virus in peripheral blood. A total of 769 nonrecombinant sequences from plasma, right, and left breast milk sampled at three time points during the first-year postpartum was analyzed for six women, three who were IUT (Fig. 1a–c) and three by breast milk (Fig. 1d–f). In all individuals, virus populations were organized into multiple major lineages with posterior branch probabilities higher than 0.7 (branches are scaled in time). Moreover, major lineages in each tree were composed of viral sequences from plasma and right, and/or left breast milk (Fig. 1a–f). To confirm the trends observed in the Bayesian MCC trees, maximum likelihood trees inferred under a nonclock model also revealed similar major phylogenetic patterns with deep lineages and clustering of sequences from different tissues within lineages (data not shown).

Fig. 1

Fig. 1

Even though shallow lineages composed of sequences from only one type of tissue were identified occasionally in every patient, overall tree structures indicated that viruses in breast milk and plasma displayed little temporal structure, but were generally mixed over the course of time. No persistent independent evolution of breast milk virus, as predicted by a compartmentalization scenario, was apparent. Virus populations displayed no phylogenetic structure between breast milk and plasma, which is most consistent with a model of panmixia (complete gene flow).

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Estimated time and tissue of origin of the most recent common ancestor

A particular strength of the Bayesian analysis used in this study is the ability to estimate the timing of internal nodes in the phylogeny, which by definition are ancestral and existed prior to the sampled sequences. This methodology, therefore, does not require the actual ancestral sequences to be included. A reasonable expectation for the origin of virus in breast milk was that virus(es) were introduced no earlier than lactogenesis, 4–5-months prepartum. The time of the most recent common ancestor (MRCA) (i.e., the root of the tree indicated by a circle in Fig. 1), estimated by using a relaxed molecular clock with the Bayesian framework, ranged from 9 to 111 months before delivery (Fig. 1a–f). The lower confidence limit was about 4–6 months, close to the onset of breast milk production for three patients (6IUT, 4BM, and 3BM). In contrast, the lower confidence limit in the other three patients was between 17 and 45 months before delivery.

The anatomical origin for the MRCA of the divergent lineages within each individual was inferred. Among women who transmitted during labor and delivery, the anatomical origin of the divergent lineages was ambiguous for two women (1IUT and 6IUT), whereas plasma virus was the source in one case (2IUT). In contrast, among the three women who transmitted by breast milk, the most parsimonious tissue of origin for the MRCA was breast milk. As the breast milk was not an anatomical site until a few months before birth, results suggest that the origin of the divergent viral lineages must have been in an unsampled tissue.

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Spatial structure

HIV-1 compartmentalization is defined by viral variants that replicate and evolve independently in anatomical tissues or compartments without contributing to systemic flow of viral genes [2]. Compartmentalization would be evident in the phylogeny as several distinct clades, each containing most (or all) the sequences from a specific tissue. Although trees failed to indicate that breast milk was a virus compartment, a suite of analytical tools to more rigorously test the hypothesis was applied [20]. A traditional phylogenetic measure of compartmentalization, the modified Slatkin–Maddison test, was applied to viruses in two tissues (breast milk vs. plasma) or three tissues (right breast milk, left breast milk, and plasma) (Table 2). In all patients, the number of changes was less than the lower 5% value of expected changes under the random distribution model. Although a traditional interpretation of the result is that the sequences demonstrate significant compartmentalization, this statistic fails to provide any quantification on the extent of compartmentalization.

Table 2

Table 2

To quantify compartmentalization, a novel statistic, the tree structure index, was developed. The structure index quantifies how close the observed tree topology is to a theoretical topology displaying perfect compartmentalization. The structure index is scaled from 0 (complete absence of compartmentalization) to 1 (perfect compartmentalization). When breast milk and plasma virus were compared, structure index ranged from 14 to 50% among the patients, indicating little evidence for compartmentalization (Table 2). When three tissues (left and right breast, and plasma) were considered, no additional information was revealed. Overall, spatial structuring of sequences between different tissues that might indicate viral compartmentalization was weak and observed sporadically and stochastically, consistent with a largely panmictic population.

Population structure was subsequently evaluated by a nonphylogenetic method that considered both time and tissue of sampling. Even though significant population structure between breast milk and plasma viruses was identified occasionally in all patients, no trend persisted over time (Table 2). Results suggest that a restricted virus population may develop transiently in one or the other breast milk sample, although viruses from each breast milk sample are largely shared with contemporaneous plasma, similar to results from tree phylogenies.

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Diversity and divergence of virus populations

Nucleotide diversity for all sequences in each tissue was similar in 1IUT, 6IUT, and 4BM, but significantly different between plasma and breast milk in 2IUT, 5BM, and 3BM (Fig. 2a). Divergence from the MRCA was also different between plasma and breast milk for 2IUT and 5BM (Fig. 2b), reflecting deep lineages of multiple viral populations. Analysis of diversity/divergence for each time point uncovered no additional information (data not shown). Overall, using a simple measure of mean diversity/divergence failed to capture the complexity of the underlying population structure.

Fig. 2

Fig. 2

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Population expansion

The number of lineages inferred to be present during the entire prepartum period on the basis of the MCC tree was calculated for each patient and reported as the proportion of the total number of lineages present at delivery (Fig. 3a). In five patients, the number of lineages expanded exponentially during the 6 months immediately prepartum, a time frame corresponding with the onset of lactogenesis I. In one patient (5BM), the period of expansion appears much earlier, although the confidence interval associated with the estimated time to the MRCA for this individual spanned 184 months; therefore, increase in the number of lineages could have occurred much closer to the time of pregnancy/lactation.

Fig. 3

Fig. 3

To assess the possibility that the population expansion resulted from a change in coreceptor usage, the PSSM algorithm was used to infer R5 or X4 coreceptor preference for each sequence. Envelopes predicted to use the X4 coreceptor were found in all patients (Fig. 3b). In four patients, viruses predicted to use X4 composed less than 10% of viruses from only one time point. In contrast, 100% of viruses in both tissues from patient 4BM were classified as X4 at all time points, whereas in patient 2IUT, predicted X4 envelopes represented 90% of plasma sequences and 70% of breast milk sequences across time (P < 0.05). Overall, the expansion of viral populations was independent of changes in coreceptor genotype.

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Although numerous tissues, including semen [37,38], brain and cerebrospinal fluid [39–42], and genital tract [43–47], have been proposed to serve as viral compartments, cross-sectional study designs and low viral diversity in many tissues [48] confound interpretation and make conclusive assignment of viral population structure problematic. Novel aspects of our study of viral compartmentalization include longitudinal and simultaneously sampled populations of high levels of virus, which provide significant advantages to establishing the persistence of evolutionary trends. Results clearly show that any compartmentalization between breast milk and plasma is evident only sporadically and stochastically. Overall, the evolutionary pattern of viral populations in the breast milk fails to meet criteria for a virologic compartment. A model of panmixia (complete gene flow) between the breast milk and plasma over the first-year postpartum best explains the results. The exchange of virus between tissues, which begins immediately after birth [20], thus persists throughout the first year. As none of the women in our study showed elevated sodium levels or evidence of epithelial barrier breakdown, ongoing migration of the virus between the breast milk and the plasma via the paracrine pathway is unlikely, indicating that other intra-cellular pathways are involved.

Unexpected results from this longitudinal study include the persistence of strong population structure (multiple deep lineages) in both plasma and breast milk virus, the time of the MRCA preceding the onset of lactogenesis I, and the origin of the MRCA in the breast milk for all of the BM transmitters. Because breast milk becomes an actual site for viral replication only during lactogenesis, the original infecting virus cannot have derived from this tissue; yet, results are inconsistent with a recent origin from the plasma virus. Taken together, the findings implicate virus(es) from a different tissue (not sampled in this study) that migrate to the breast milk and establish an infection at this site.

One potential anatomical origin of the initial breast milk viral lineage is infected epithelial cells in the mammary gland [49], as in the case of mouse mammary tumor virus [50]; however, epithelial cells lack the CD4 receptor and probably do not comprise a significant portion of HIV-1-infected cells. A more likely origin of HIV-1 in breast milk is infected cells from gut-associated lymphoid tissue (GALT) [16,51,52]. Cellular markers indicate that T cells in human breast milk migrate from tissues other than the peripheral blood mononuclear cells [53–55], whereas both rodent and human studies show that some lymphocytes in breast milk originate from the gut [9–13]. The predominant lymphocytes in the breast milk are CCR5-expressing memory CD4 T cells [55], although macrophages are also a major cell type in breast milk [56], and a likely source in breast milk of human T-cell lymphotrophic virus-1 infection [57]. Even though a majority of infected lymphocytes turn over within days [58,59], macrophages survive HIV-1 infection for weeks to months [60], express CXCR4 and CCR5 coreceptors [61], and play a prominent role as a HIV-1 reservoir in the gastrointestinal mucosa [62]. Significantly, viruses predicted to use the CXCR4 coreceptor were found in breast milk tissue in five of the six patients. Therefore, GALT-derived macrophages or T cells infected with an early HIV variant may migrate to the breast during lactogenesis and establish an infection. Subsequently, these newly introduced variants migrate to the periphery, in which a distinct set of viral variants is also circulating. The exchange of distinct viral variants between the breast milk and the plasma would result in the mixture of multiple divergent lineages with no compartmentalization.

Under this hypothesis, proviral DNA in breast milk cells, recently introduced from a different tissue, would be expected to show a high divergence with respect to the plasma virus. Unfortunately, the cellular fraction of breast milk was not available for the samples in this study. However, in a recent cross-sectional study of plasma, breast milk RNA and DNA population sequences of the reverse transcriptase and protease genes, median genetic distances between cell-free and cell-associated viruses in breast milk were greater than between plasma and cell-free virus [63]. These results are consistent with the hypothesis that distinct viral lineages in breast milk are introduced from unsampled anatomical sites through cellular migration.

The only difference among patients who had transmitted through labor and delivery vs. breastfeeding was the inferred tissue origin of the MRCA: breast milk for all three breast milk transmitters and either plasma or undetermined for the IUT transmitters. However, distinctions between transmitting groups should be interpreted with caution due to the small number of individuals. Although a natural comparison population would be women who breastfed for a substantial period and failed to transmit during either IUT or breastfeeding, breast milk viral load [64] and viral DNA [65] are strongly correlated with transmission; therefore, a lack of detectable virus limits the possibility to study viral evolution. Unfortunately, limited samples from the infants rendered the analysis of transmitted viral variants impractical. All women were at an advanced stage of disease, as evidenced by the detection of putative X4 viruses and low CD4 cell counts. Although the reported frequency of infection by HIV-1 subtype C X4 variants varies from 0 to 30% depending on geographic location, the frequency appears to be higher in Africa in more recent studies, possibly suggesting an evolving epidemic on this continent [66–69].

Results from our study demonstrate that breast milk, similar to other transmitting tissues, does not provide a compartment for virus during the relatively short time of lactation. In general, evidence that any transmitting tissue provides a restricted source of viral genes/compartment is weak [48,70]. In fact, the brain is the only anatomical site clearly shown to act as a viral compartment/reservoir [39–42,71], although as a nontransmitting tissue the impact of this viral population on new infections is probably limited. Although there is no doubt that long-lived cellular sources of virus must exist by virtue of the emergence of an early variant after cessation of antiretroviral therapy [72–74], conclusive identification of the source is unclear. The diverse lineages that emerge during lactation/pregnancy could arise from the same long-lived cellular population involved in posttherapy viral dynamics, or an entirely different anatomical site. Future studies including more individuals/anatomical sites are necessary to investigate the possibility that divergent virus populations emerge during immunological perturbations during the course of natural infection.

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The study was supported by grants from the National Institutes of Health (NIH) Eunice Kennedy Shriver National Institute of Child Health and Human Development, (R01 HD39611, R01 HD40777), the National Institute of Allergy and Infectious Disease (R01 AI065265), the National Cancer Institute (T-32 CA09126) and the International Maternal Pediatric Adolescent AIDS Clinical Trials Group U01 AI068632; the University of Florida Stephany W. Holloway University Chair for AIDS Research; the Laura McClamma Endowment for Pediatric Immune Deficiency; the Florida Center for AIDS Research; and the Center for Research in Pediatric Immune Deficiency. G.M.A. is recipient of the Elizabeth Glaser Pediatric AIDS Foundation (EGPAF) Scientist Award.

R.R.G., C.J.M., G.A., and M.M.G. conceived of the study design. R.R.G., A.L., and K.J.N. generated data. W.D.D., M. Sinkala, C.K., C.J.M., D.M.T., and L.K. assisted in interpretation of data. R.R.G. and M. Salemi designed the analysis plan, performed the analyses, and developed novel analysis methods. R.R.G. and M.M.G. wrote the manuscript.

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1. Goodenow M, Collman R. HIV-1 coreceptor preference is distinct from target cell tropism: a dual-parameter nomenclature to define viral phenotypes. J Leukoc Biol 2006; 80:965–972.
2. Nickle DC, Jensen MA, Shriner D, Brodie SJ, Frenkel LM, Mittler JE, et al. Evolutionary indicators of human immunodeficiency virus type 1 reservoirs and compartments. J Virol 2003; 77:5540–5546.
3. Kieffer T, Finucane M, Nettles R, Quinn T, Broman K, Ray S, et al. Genotypic analysis of HIV-1 drug resistance at the limit of detection: virus production without evolution in treated adults with undetectable HIV loads. J Infect Dis 2004; 189:1452–1465.
4. Persaud D, Pierson T, Ruff C, Finzi D, Chadwick K, Margolick J, et al. A stable latent reservoir for HIV-1 in resting CD4(+) T lymphocytes in infected children. J Clin Invest 2000; 105:995–1003.
5. Aldrovandi G, Kuhn L. What infants and breasts can teach us about natural protection from HIV infection. J Infect Dis 2010; 202(Suppl 3):S366–S370.
6. Brandtzaeg P. The mucosal immune system and its integration with the mammary glands. J Pediatr 2010; 156:S8–S15.
7. Neville MC, Neifert MR. Lactation: physiology, nutrition, and breastfeeding. New York: Plenum Press; 1983.
8. Neville MC, Allen JC, Archer PC, Casey CE, Seacat J, Keller RP, et al. Studies in human lactation: milk volume and nutrient composition during weaning and lactogenesis. Am J Clin Nutr 1991; 54:81–92.
9. Allardyce R, Shearman D, McClelland D, Marwick K, Simpson A, Laidlaw R. Appearance of specific colostrum antibodies after clinical infection with Salmonella typhimurium. BMJ 1974; 3:307–309.
10. Fishaut M, Murphy D, Neifert M, McIntosh K, Ogra P. Bronchomammary axis in the immune response to respiratory syncytial virus. J Pediatr 1981; 99:186–191.
11. Goldblum R, Ahlstedt S, Carlsson B, Hanson L, Jodal U, Lidin-Janson G, et al. Antibody-forming cells in human colostrum after oral immunisation. Nature 1975; 257:797–798.
12. Roux M, McWilliams M, Phillips-Quagliata J, Weisz-Carrington P, Lamm M. Origin of IgA-secreting plasma cells in the mammary gland. J Exp Med 1977; 146:1311–1322.
13. Weisz-Carrington P, Roux M, McWilliams M, Phillips-Quagliata J, Lamm M. Organ and isotype distribution of plasma cells producing specific antibody after oral immunization: evidence for a generalized secretory immune system. J Immunol 1979; 123:1705–1708.
14. Georgeson JC, Filteau SM. Physiology, immunology, and disease transmission in human breast milk. AIDS Patient Care STDS 2000; 14:533–539.
15. Goldman AS. The immune system of human milk: antimicrobial, antiinflammatory and immunomodulating properties. Pediatr Infect Dis J 1993; 12:664–671.
16. Sabbaj S, Edwards B, Ghosh M, Semrau K, Cheelo S, Thea D, et al. Human immunodeficiency virus-specific CD8(+) T cells in human breast milk. J Virol 2002; 76:7365–7373.
17. Becquart P, Chomont N, Roques P, Ayouba A, Kazatchkine MD, Belec L, et al. Compartmentalization of HIV-1 between breast milk and blood of HIV-infected mothers. Virology 2002; 300:109–117.
18. Becquart P, Courgnaud V, Willumsen J, Van de Perre P. Diversity of HIV-1 RNA and DNA in breast milk from HIV-1-infected mothers. Virology 2007; 363:256–260.
19. Henderson GJ, Hoffman NG, Ping LH, Fiscus SA, Hoffman IF, Kitrinos KM, et al. HIV-1 populations in blood and breast milk are similar. Virology 2004; 330:295–303.
20. Heath L, Conway S, Jones L, Semrau K, Nakamura K, Walter J, et al. Restriction of HIV-1 genotypes in breast milk does not account for the population transmission genetic bottleneck that occurs following transmission. PLoS One 2010; 5:e10213.
21. Kuhn L, Aldrovandi G, Sinkala M, Kankasa C, Semrau K, Mwiya M, et al. Effects of early, abrupt weaning on HIV-free survival of children in Zambia. N Engl J Med 2008; 359:130–141.
22. Fox M, Brooks D, Kuhn L, Aldrovandi G, Sinkala M, Kankasa C, et al. Reduced mortality associated with breast-feeding-acquired HIV infection and breast-feeding among HIV-infected children in Zambia. J Acquir Immune Defic Syndr 2008; 48:90–96.
23. Ghosh M, Kuhn L, West J, Semrau K, Decker D, Thea D, et al. Quantitation of human immunodeficiency virus type 1 in breast milk. J Clin Microbiol 2003; 41:2465–2470.
24. Tuttle DL, Anders CB, Aquino-De Jesus MJ, Poole PP, Lamers SL, Briggs DR, et al. Increased replication of nonsyncytium-inducing HIV type 1 isolates in monocyte-derived macrophages is linked to advanced disease in infected children. AIDS Res Hum Retroviruses 2002; 18:353–362.
25. Tamura K, Dudley J, Nei M, Kumar S. MEGA4: Molecular Evolutionary Genetics Analysis (MEGA) software version 4.0. Mol Biol Evol 2007; 24:1596–1599.
26. Salemi M, Gray R, Goodenow M. An exploratory algorithm to identify intra-host recombinant viral sequences. Mol Phylogenet Evol 2008; 49:618–628.
27. Jensen M, Coetzer M, van 't Wout A, Morris L, Mullins J. A reliable phenotype predictor for human immunodeficiency virus type 1 subtype C based on envelope V3 sequences. J Virol 2006; 80:4698–4704.
28. Kingman J. The coalescent. Stochastic Process Appl 1982; 13:235–248.
29. Drummond AJ, Rambaut A. BEAST: bayesian evolutionary analysis by sampling trees. BMC Evol Biol 2007; 7:214.
30. Drummond AJ, Nicholls GK, Rodrigo AG, Solomon W. Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics 2002; 161:1307–1320.
31. Drummond AJ, Pybus OG, Rambaut A, Forsberg R, Rodrigo AG. Measurably evolving populations. Trends Ecol Evol 2003; 18:481–488.
32. Drummond A, Ho S, Phillips M, Rambaut A. Relaxed phylogenetics and dating with confidence. PLoS Biol 2006; 4:e88.
33. Guindon S, Delsuc F, Dufayard J, Gascuel O. Estimating maximum likelihood phylogenies with PhyML. Methods Mol Biol 2009; 537:113–137.
34. Achaz G, Palmer S, Kearney M, Maldarelli F, Mellors JW, Coffin JM, et al. A robust measure of HIV-1 population turnover within chronically infected individuals. Mol Biol Evol 2004; 21:1902–1912.
35. Slatkin M, Maddison WP. A cladistic measure of gene flow inferred from the phylogenies of alleles. Genetics 1989; 123:603–613.
36. Maddison WP, Maddison DR. MacClade version 4: analysis of phylogeny and character evolution. Sunderland, MA: Sinauer Associates; 2003.
37. Kiessling A, Fitzgerald L, Zhang D, Chhay H, Brettler D, Eyre R, et al. Human immunodeficiency virus in semen arises from a genetically distinct virus reservoir. AIDS Res Hum Retroviruses 1998; 14(Suppl 1):S33–S41.
38. Coombs R, Speck C, Hughes J, Lee W, Sampoleo R, Ross S, et al. 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 1998; 177:320–330.
39. Chang J, Jozwiak R, Wang B, Ng T, Ge Y, Bolton W, et al. Unique HIV type 1 V3 region sequences derived from six different regions of brain: region-specific evolution within host-determined quasispecies. AIDS Res Hum Retroviruses 1998; 14:25–30.
40. Donaldson Y, Bell J, Holmes E, Hughes E, Brown H, Simmonds P. In vivo distribution and cytopathology of variants of human immunodeficiency virus type 1 showing restricted sequence variability in the V3 loop. J Virol 1994; 68:5991–6005.
41. Salemi M, Lamers SL, Yu S, de Oliveira T, Fitch WM, McGrath MS. Phylodynamic analysis of human immunodeficiency virus type 1 in distinct brain compartments provides a model for the neuropathogenesis of AIDS. J Virol 2005; 79:11343–11352.
42. Ohagen A, Devitt A, Kunstman KJ, Gorry PR, Rose PP, Korber B, et al. 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 2003; 77:12336–12345.
43. Poss M, Rodrigo A, Gosink J, Learn G, de Vange Panteleeff D, Martin HJ, et al. Evolution of envelope sequences from the genital tract and peripheral blood of women infected with clade A human immunodeficiency virus type 1. J Virol 1998; 72:8240–8251.
44. Ping LH, Cohen MS, Hoffman I, Vernazza P, Seillier-Moiseiwitsch F, Chakraborty H, et al. Effects of genital tract inflammation on human immunodeficiency virus type 1 V3 populations in blood and semen. J Virol 2000; 74:8946–8952.
45. Pillai SK, Good B, Pond SK, Wong JK, Strain MC, Richman DD, et al. Semen-specific genetic characteristics of human immunodeficiency virus type 1 env. J Virol 2005; 79:1734–1742.
46. Kemal KS, Foley B, Burger H, Anastos K, Minkoff H, Kitchen C, et al. HIV-1 in genital tract and plasma of women: compartmentalization of viral sequences, coreceptor usage, and glycosylation. Proc Natl Acad Sci U S A 2003; 100:12972–12977.
47. Philpott S, Burger H, Tsoukas C, Foley B, Anastos K, Kitchen C, et al. Human immunodeficiency virus type 1 genomic RNA sequences in the female genital tract and blood: compartmentalization and intrapatient recombination. J Virol 2005; 79:353–363.
48. Bull M, Learn G, Genowati I, McKernan J, Hitti J, Lockhart D, et al. Compartmentalization of HIV-1 within the female genital tract is due to monotypic and low-diversity variants not distinct viral populations. PLoS One 2009; 4:e7122.
49. Toniolo A, Serra C, Conaldi PG, Basolo F, Falcone V, Dolei A. Productive HIV-1 infection of normal human mammary epithelial cells. AIDS 1995; 9:859–866.
50. Minamishima I, Ueda K, Minematsu T, Minamishima Y, Umemoto M, Take H, et al. Role of breast milk in acquisition of cytomegalovirus infection. Microbiol Immunol 1994; 38:549–552.
51. Kourtis AP, Butera S, Ibegbu C, Beled L, Duerr A. Breast milk and HIV-1: vector of transmission or vehicle of protection? Lancet Infect Dis 2003; 3:786–793.
52. Manning LS, Parmely MJ. Cellular determinants of mammary cell-mediated immunity in the rat. I: The migration of radioisotopically labeled T lymphocytes. J Immunol 1980; 125:2508–2514.
53. Bertotto A, Castellucci G, Fabietti G, Scalise F, Vaccaro R. Lymphocytes bearing the T cell receptor gamma delta in human breast milk. Arch Dis Child 1990; 65:1274–1275.
54. Ullrich R, Schieferdecker HL, Ziegler K, Riecken EO, Zeitz M. Gamma delta T cells in the human intestine express surface markers of activation and are preferentially located in the epithelium. Cell Immunol 1990; 128:619–627.
55. Bertotto A, Gerli R, Fabietti G, Crupi S, Arcangeli C, Scalise F, et al. Human breast milk T lymphocytes display the phenotype and functional characteristics of memory T cells. Eur J Immunol 1990; 20:1877–1880.
56. Goldman AS, Chheda S, Garofalo R. Evolution of immunologic functions of the mammary gland and the postnatal development of immunity. Pediatr Res 1998; 43:155–162.
57. Takeuchi H, Takahashi M, Norose Y, Takeshita T, Fukunaga Y, Takahashi H. Transformation of breast milk macrophages by HTLV-I: implications for HTLV-I transmission via breastfeeding. Biomed Res 2010; 31:53–61.
58. Ho D, Neumann A, Perelson A, Chen W, Leonard J, Markowitz M. Rapid turnover of plasma virions and CD4 lymphocytes in HIV-1 infection. Nature 1995; 373:123–126.
59. Markert M, Hicks C, Bartlett J, Harmon J, Hale L, Greenberg M, et al. Effect of highly active antiretroviral therapy and thymic transplantation on immunoreconstitution in HIV infection. AIDS Res Hum Retroviruses 2000; 16:403–413.
60. Aquaro S, Bagnarelli P, Guenci T, De Luca A, Clementi M, Balestra E, et al. Long-term survival and virus production in human primary macrophages infected by human immunodeficiency virus. J Med Virol 2002; 68:479–488.
61. Goodenow MM, Rose SL, Tuttle DL, Sleasman JW. HIV-1 fitness and macrophages. J Leukoc Biol 2003; 74:657–666.
62. Smith P, Meng G, Salazar-Gonzalez J, Shaw G. Macrophage HIV-1 infection and the gastrointestinal tract reservoir. J Leukoc Biol 2003; 74:642–649.
63. Andreotti M, Galluzzo C, Guidotti G, Germano P, Altan A, Pirillo M, et al. Comparison of HIV type 1 sequences from plasma, cell-free breast milk, and cell-associated breast milk viral populations in treated and untreated women in Mozambique. AIDS Res Hum Retroviruses 2009; 25:707–711.
64. Semrau K, Ghosh M, Kankasa C, Sinkala M, Kasonde P, Mwiya M, et al. Temporal and lateral dynamics of HIV shedding and elevated sodium in breast milk among HIV-positive mothers during the first 4 months of breast-feeding. J Acquir Immune Defic Syndr 2008; 47:320–328.
65. Rousseau CM, Nduati RW, Richardson BA, John-Stewart GC, Mbori-Ngacha DA, Kreiss JK, et al. Association of levels of HIV-1-infected breast milk cells and risk of mother-to-child transmission. J Infect Dis 2004; 190:1880–1888.
66. Raymond S, Delobel P, Mavigner M, Ferradini L, Cazabat M, Souyris C, et al. Prediction of HIV type 1 subtype C tropism by genotypic algorithms built from subtype B viruses. J Acquir Immune Defic Syndr 2010; 53:167–175.
67. Cecilia D, Kulkarni S, Tripathy S, Gangakhedkar R, Paranjape R, Gadkari D. Absence of coreceptor switch with disease progression in human immunodeficiency virus infections in India. Virology 2000; 271:253–258.
68. Connell B, Michler K, Capovilla A, Venter W, Stevens W, Papathanasopoulos M. Emergence of X4 usage among HIV-1 subtype C: evidence for an evolving epidemic in South Africa. AIDS 2008; 22:896–899.
69. Ping L, Nelson J, Hoffman I, Schock J, Lamers S, Goodman M, et al. Characterization of V3 sequence heterogeneity in subtype C human immunodeficiency virus type 1 isolates from Malawi: underrepresentation of X4 variants. J Virol 1999; 73:6271–6281.
70. Kemal K, Burger H, Mayers D, Anastos K, Foley B, Kitchen C, et al. HIV-1 drug resistance in variants from the female genital tract and plasma. J Infect Dis 2007; 195:535–545.
71. Zhang L, Rowe L, He T, Chung C, Yu J, Yu W, et al. Compartmentalization of surface envelope glycoprotein of human immunodeficiency virus type 1 during acute and chronic infection. J Virol 2002; 76:9465–9473.
72. Chomont N, El-Far M, Ancuta P, Trautmann L, Procopio F, Yassine-Diab B, et al. HIV reservoir size and persistence are driven by T cell survival and homeostatic proliferation. Nat Med 2009; 15:893–900.
73. Chun T, Carruth L, Finzi D, Shen X, DiGiuseppe J, Taylor H, et al. Quantification of latent tissue reservoirs and total body viral load in HIV-1 infection. Nature 1997; 387:183–188.
74. Finzi D, Hermankova M, Pierson T, Carruth L, Buck C, Chaisson R, et al. Identification of a reservoir for HIV-1 in patients on highly active antiretroviral therapy. Science 1997; 278:1295–1300.

breast milk; compartment; evolution; HIV-1; phylogeny; reservoir

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