# In-Depth Characterization of Full-Length Archived Viral Genomes after Nine Years of Posttreatment HIV Control

Pauline Trémeaux, Frédéric Lemoine, Adeline Mélard, Marine Gousset, Faroudy Boufassa, Sylvie Orr, Valérie Monceaux, Olivier Gascuel, Olivier Lambotte, Laurent Hocqueloux, et al.

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Pauline Trémeaux, Frédéric Lemoine, Adeline Mélard, Marine Gousset, Faroudy Boufassa, et al. In-Depth Characterization of Full-Length Archived Viral Genomes after Nine Years of Posttreatment HIV Control. Microbiology Spectrum, 2023, 11 (1), 10.1128/spectrum.03267-22. pasteur-04296534

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# In-Depth Characterization of Full-Length Archived Viral Genomes after Nine Years of Posttreatment HIV Control

Pauline Trémeaux,ª,ᵇ,ᶜ* Frédéric Lemoine,ᵈ,ᵉ Adeline Mélard,ª,ᵇ Marine Gousset,ª,ᵇ Faroudy Boufassa,ᵇ Sylvie Orr,ᵇ

Valérie Monceaux,ᶜ Olivier Gascuel,ᵈ,ᵉ Olivier Lambotte,ᵇ Laurent Hocqueloux,ᶜ Asier Saez-Cirion,ᶜ Christine Rouzioux,ª

Véronique Avettand-Fenoel,ª,ᵇ,ᶜ for the CODEX/VISCONTI ANRS Cohort Study Groups

**ABSTRACT** In the search for control of human immunodeficiency virus type 1 (HIV-1) infection without antiretroviral therapy, posttreatment controllers (PTCs) are models of HIV remission. To better understand their mechanisms of control, we characterized the HIV blood reservoirs of 8 PTCs (median of 9.4 years after treatment interruption) in comparison with those of 13 natural HIV infection controllers (HICs) (median of 18 years of infection) and with those of individuals receiving efficient antiretroviral therapy initiated during either primary HIV infection (PHIs; n = 8) or chronic HIV infection (CHIs; n = 6). This characterization was performed with single-genome amplification and deep sequencing. The proviral diversity, which reflects the history of past viral replication, was lower in the PTCs, PHIs, and aviremic HICs than in the blipper HICs and CHIs. The proportions of intact and defective proviruses among the proviral pool in PTCs were not significantly different from those of other groups. When looking at the quantities of proviruses per million peripheral blood mononuclear cells (PBMCs), they had similar amounts of intact proviruses as other groups but smaller amounts of defective proviruses than CHIs, suggesting a role of these forms in HIV pathogenesis. Two HICs but none of the PTCs harbored only proviruses with deletion in *nef*; these attenuated strains could contribute to viral control in these participants. We show, for the first time, the presence of intact proviruses and low viral diversity in PTCs long after treatment interruption, as well as the absence of evolution of the proviral quasispecies in subsequent samples. This reflects low residual replication over time. Further data are necessary to confirm these results.

**IMPORTANCE** Most people living with HIV need antiretroviral therapy to control their infection and experience viral relapse in case of treatment interruption, because of viral reservoir (proviruses) persistence. Knowing that proviruses are very diverse and most of them are defective in treated individuals, we aimed to characterize the HIV blood reservoirs of posttreatment controllers (PTCs), rare models of drug-free remission, in comparison with spontaneous controllers and treated individuals. At a median time of 9 years after treatment interruption, which is unprecedented in the literature, we showed that the proportions and quantities of intact proviruses were similar between PTCs and other individuals. Unlike 2/7 spontaneous controllers who harbored only *nef*-deleted proviruses, which are attenuated strains, which could contribute to

Editor Takamasa Ueno, Kumamoto University

Copyright © 2023 Trémeaux et al. This is an open-access article distributed under the terms of the Creative Commons Attribution 4.0 International license.

Address correspondence to Véronique Avettand-Fenoel, veronique.avettand@aphp.fr.

*Present address: Pauline Trémeaux, CHU de Toulouse Purpan, Laboratoire de Virologie, Toulouse, France.

The authors declare no conflict of interest.

Received 22 August 2022

Accepted 13 December 2022

Published 24 January 2023

<footnote>ªUniversité Paris Cité, Faculté de Médecine, Paris, France</footnote>

<footnote>ᵇINSERM U1016, CNRS UMR8104, Institut Cochin, Paris, France</footnote>

<footnote>ᶜAP-HP, Laboratoire de Virologie, Hôpital Cochin, Paris, France</footnote>

<footnote>ᵈInstitut Pasteur, Université de Paris, Unité Bio-informatique Evolutive, Paris, France</footnote>

<footnote>ᵉInstitut Pasteur, Université de Paris, Hub Bioinformatique et Biostatistiques, Paris, France</footnote>

<footnote>ᵈInstitut CESP U1018, Université Paris Sud, Le Kremlin Bicêtre, France</footnote>

<footnote>ᵉInstitut de Systématique, Evolution, Biodiversité (ISYEB), UMR 7205-CNRS, Muséum National d'Histoire Naturelle, SU, EPHE UA, Paris, France</footnote>

<footnote>ᵇAP-HP, Hôpital Bicêtre, UMR1184, Université Paris Saclay, Inserm, CEA, Le Kremlin Bicêtre, France</footnote>

<footnote>ᶜService des Maladies Infectieuses et Tropicales, CHR d'Orléans—La Source, Orléans, France</footnote>

<footnote>Institut Pasteur, HIV Inflammation et Persistance, Paris, France</footnote>

<footnote>ᵈAP-HP, Laboratoire de Microbiologie Clinique, Hôpital Necker-Enfants Malades, Paris, France</footnote>
their control, no such case was observed in PTCs. Furthermore, PTCs displayed low vi-
ral genetic diversity and no evolution of their reservoirs, indicating very low residual
replication, despite the presence of intact proviruses.

**KEYWORDS** posttreatment HIV controller, HIV reservoirs, provirus, defective proviruses, next-generation sequencing, posttreatment HIV controllers, ultradeep sequencing, proviruses

Human immunodeficiency virus type 1 (HIV-1) infection became a chronic disease in patients under long-term antiretroviral therapy (ART) to control viral replication. Because of the existence of viral reservoirs, most people living with HIV-1 (PWH) experience viral rebound following antiretroviral treatment interruption (TI), whether they have been treated since the primary infection (primary HIV infection patient [PHI]) or the chronic stage (chronic HIV infection patient [CHI]), with rates of 87% and 96%, respectively, at 6 months after TI (1). Nevertheless, in rare cases, viral replication remains controlled for several years after ceasing ART. Most of these individuals, known as posttreatment controllers (PTCs), have been treated since primary infection, such as in the French ANRS-VISCONTI cohort (2). They differ from the rare individuals, known as natural HIV infection controllers (HICs), who maintain low or undetectable viral loads without treatment (<1%) (3, 4). In this context, current research on HIV remission aims at finding therapeutic alternatives that do not require the lifelong intake of ART. As PTCs constitute models of HIV infection control without ART, a better understanding of the viral and host parameters responsible for this control may help with the development of therapeutic strategies benefiting all PWH.

In HICs, an overrepresentation of protective HLA alleles, such as HLA-B*27 and B*57, has been observed, as well as a high cytotoxic CD8 T cell response (3). This has not been observed in PTCs, who instead present high expression of HLA-B*35, an allele associated with a faster progression toward AIDS in the absence of ART (2, 3). Contrary to HICs, PTCs also often exhibit symptomatic primary infection (1, 2), and these differences suggest that different mechanisms might occur in PTCs (4). Viral characteristics might also contribute to the mechanism of control of HIV infection in these two groups. For example, both PTCs and HICs have a small viral reservoir, as reflected by their particularly low levels of blood HIV DNA (2, 5, 6) or cell-associated HIV RNA (7). However, although necessary, a small reservoir size does not appear to be sufficient to induce viral control, as most individuals treated since the primary infection display low levels of total HIV DNA (8) but less than 10% of them might become PTCs after TI (1, 2, 9). The quality of the total HIV DNA, determined by considering the proportions of intact versus defective genomes within the proviral pool in these persons, could be important. Indeed, previous studies have shown that during ART-controlled infection, most of the HIV DNA corresponds to defective genomes containing large deletions, frame-shifts, or apolipoprotein B mRNA-editing catalytic polypeptide-like (APOBEC)-induced hypermutations (10–13). Regarding HICs and PTCs, data on their proviral landscape is very limited, but one hypothesis is that a lower proportion and/or level of intact genomes might contribute to the control of infection. Genetic diversity is another viral factor that might contribute to the control of infection: a low diversity might facilitate the control by the immune system, while a higher one might help in escaping it. Regarding HICs, Jiang et al. recently showed that they were characterized by low levels of intact HIV DNA in specific integration sites (14). In HICs, viral genetic diversity appears correlated to the level of viral replication (15, 16). Information concerning PTCs is limited to a study by Sharaf et al. that included PTCs with a generally shorter period of control than those of the ANRS-VISCONTI cohort. These PTCs displayed lower intact proviral loads than noncontrollers (NCs), although with similar overall proportions (17). Their proviral landscape had not evolved at a median of 1.4 years after TI. It is currently unclear whether PTCs maintain a low diversity several years after treatment interruption, similar
to PHIs (18), or whether this diversity increases after several years, similar to most untreated individuals.

In the present study, we aimed to investigate the proviral genome landscape in a group of PTCs with durable control of infection. To this end, we determined (i) the viral genetic diversity and (ii) the presence and proportions of intact and defective archived HIV genomes in blood samples from PTCs several years after TI, in comparison with those of HICs and of two groups of patients receiving efficient ART (since primary infection [PHIs] and since chronic infection [CHIs]).

## RESULTS

**Patients and samples.** To study the contribution of viral factors to HIV remission, we studied the archived HIV genomes in blood samples from four groups of PWH, including 8 early-treated PTCs from the ANRS-VISCONTI cohort (2), 13 HICs from the French multicenter ANRS-CODEX cohort (19), 8 PHIs, and 6 CHIs (Table 1). All PTCs had been treated during primary infection (<3 months after infection) and for a median time of 4.0 years (range, 1.1 to 16.8 years) (Table 1). The median time between the TI and the studied-sample date was 9.4 years (range, 1.2 to 13.8 years), and the median blood HIV DNA load was 1.96 log copies/10⁶ peripheral blood mononuclear cells (PBMCs) (range, 0.52 to 2.60 log copies/10⁶ PBMCs). Three PTCs had a second blood sample analyzed, with a median time of 5.2 years between the sampling dates. Except for the longitudinal part of the study, only the first sample of each PTC was included. HICs had been infected by HIV for a median time of 18 years at the time of sampling (range, 7 to 29 years), without ART. Their median blood HIV DNA load was 2.30 log copies/10⁶ PBMCs (Table 1). The PHI and CHI groups included PWH with undetectable viremia under ART initiated either during primary infection or the chronic stage, respectively. Treatment of the PHI group was initiated as early as that of the PTC group (Table 1), and these patients had been under efficient ART for a median time of 5.2 years at the time of sampling. Individuals in the CHI group had initiated ART at a median time of 3.8 years after the diagnosis (range, 2.5 to 13.3 years), and they had been treated for a median time of 9.2 years at the time of sampling.

**PTCs, PHIs, and aviremic HICs have lower viral diversity than CHIs.** To study the genetic diversity of the archived HIV genomes together with the presence of stop codons/hypermutations in the blood samples from the different groups of PWH, we first performed the sequencing of the reverse transcriptase (RT) region of the pol gene. Although this region is not the most variable in the HIV genome, it is one of those most commonly targeted by APOBEC (20) and, thus, appeared to be an acceptable compromise to study both diversity and genetic defects induced by APOBEC. RT gene diversity analysis was performed on blood samples from 8 PTCs, 10 HICs, 8 PHIs, and 6 CHIs (Table S1 in the supplemental material). A total of 25,154 RT sequences were obtained for the 32 samples (median sequencing depth [interquartile range [IQR]]], 180 [54 to 719]), including 24,091 nondefective sequences. Given that there is no "gold standard" method to express the genetic diversity of viral quasispecies (21), we used several indexes, including mean branch length, entropy, number of alleles per nucleotide site, and *p*-distance, to compare the proviral diversity. Overall, these indexes were correlated with each other (Fig. 1) and gave concordant results for comparison between groups (Fig. 2). The diversities were similar among the PTC and PHI groups, regardless of the index used, and significantly lower in median values than those of the CHI group, although heterogeneity was observed among each group of PWH. Of note, PTC 073001 had the highest genetic diversity among the PTC group, which can be explained by a history of past viral replication after mother-to-child transmission and before a sustained period of control over the last decade (22). The HIC group displayed no significant difference from PHIs and PTCs nor from CHIs, probably because of the high interindividual variability in this group. We thus defined subgroups among HICs: "aviremic" individuals (HIC-a) had more than 50% of their viral loads from the 5 years before the sample date below 50 copies/mL and none above 400 copies/mL, and "blippers" (HIC-b group) did not meet those criteria (19). The median blood HIV DNA
<table><caption>TABLE 1 Patient characteristics<sup>a</sup></caption><thead><tr><th rowspan="2">Group</th><th rowspan="2">Individual</th><th rowspan="2">Former ID<sup>b</sup></th><th rowspan="2">HLA allele</th><th rowspan="2">Age at diagnosis (yrs)</th><th rowspan="2">Yr of HIV diagnosis</th><th rowspan="2">Plasma HIV RNA peak (log copies/mL)<sup>c</sup></th><th rowspan="2">Sample yr</th><th rowspan="2">Duration of ART (yrs)</th><th colspan="4">Value on the sample date for:</th><th rowspan="2">CD4 T-cell count/µL</th><th rowspan="2">Remarks</th></tr><tr><th>Time since TI (yrs)</th><th>Plasma HIV RNA (copies/mL)<sup>d</sup></th><th>Total HIV DNA (log copies/10<sup>6</sup> PBMCs)</th></tr></thead><tbody><tr><td rowspan="3">PTC</td><td>180001<sup>e</sup></td><td>OR1</td><td>B'35/B'49</td><td>31</td><td>1996</td><td>4.32</td><td>2011</td><td>6.7</td><td>8.7</td><td>2</td><td>2.19</td><td>NA</td><td></td><td></td></tr><tr><td>180002<sup>e</sup></td><td>OR2</td><td>B'35/B'45</td><td>31</td><td>2001</td><td>6.79</td><td>2017</td><td>13.9</td><td>&lt;8</td><td>2</td><td>1.88</td><td>1,019</td><td></td><td></td></tr><tr><td>180003<sup>e</sup></td><td>OR3</td><td>B'14/B'49</td><td>31</td><td>1996</td><td>3.38 (after PEP)</td><td>2015</td><td>2.2</td><td>7.5</td><td>2</td><td>1.82</td><td>528</td><td></td><td></td></tr><tr><td></td><td>098001</td><td>LY1</td><td>B'07/B'57</td><td>55</td><td>2001</td><td>4.87</td><td>2010</td><td>1.9</td><td>7.2</td><td>6</td><td>1.25</td><td>701</td><td></td><td></td></tr><tr><td></td><td>070001</td><td></td><td>B'35/B'53</td><td>41</td><td>1996</td><td>3.26</td><td>2014</td><td>16.8</td><td>1.2</td><td>107</td><td>2.60</td><td>1,709</td><td></td><td></td></tr><tr><td></td><td>041001</td><td>KPV</td><td>B'15/B'38</td><td>38</td><td>1998</td><td>5.68</td><td>2014</td><td>2.4</td><td>13.8</td><td>3</td><td>&lt;0.78</td><td>682</td><td></td><td></td></tr><tr><td></td><td>200001</td><td></td><td>B'13/B'35</td><td>37</td><td>2001</td><td>3.03</td><td>2011</td><td>1.1</td><td>8.9</td><td>200</td><td>&lt;2.15</td><td>658</td><td></td><td></td></tr><tr><td></td><td>073001</td><td>Case A</td><td>B'15/B'41</td><td>0<sup>f</sup></td><td>1996 or early 1997</td><td>6.34</td><td>2015</td><td>5.5</td><td>12.0</td><td>2</td><td>2.23</td><td>727</td><td></td><td></td></tr><tr><td></td><td>Median (IQR)</td><td></td><td>34 (31-38)</td><td></td><td></td><td>4.60 (3.35-5.85)</td><td></td><td>4.0 (1.9-6.7)</td><td>9.4 (7.4-12.5)</td><td>8 (3-11)</td><td>1.96 (1.82-2.19)</td><td>692 (561-751)</td><td></td><td></td></tr><tr><td rowspan="7">HIC-a</td><td>CODa1</td><td></td><td>B'14/B'27</td><td>46</td><td>1993</td><td>4.00</td><td>2014</td><td>No ART</td><td></td><td>3</td><td>2.18</td><td>405</td><td></td><td></td></tr><tr><td>CODa2</td><td></td><td>B'13/B'70</td><td>23</td><td>1991</td><td>2.48</td><td>2014</td><td>No ART</td><td></td><td>3</td><td>2.46</td><td>844</td><td></td><td></td></tr><tr><td>CODa3</td><td></td><td>B'51/B'39</td><td>33</td><td>1996</td><td>&lt;2.70</td><td>2014</td><td>No ART</td><td></td><td>&lt;2</td><td>2.15</td><td>1,184</td><td></td><td></td></tr><tr><td>CODa4</td><td></td><td>B'14/B'27</td><td>33</td><td>1985</td><td>&lt;3.00</td><td>2014</td><td>No ART</td><td></td><td>&lt;2</td><td>2.26</td><td>834</td><td></td><td></td></tr><tr><td>CODa5</td><td></td><td>B'05/B'70</td><td>40</td><td>2008</td><td>1.85</td><td>2015</td><td>No ART</td><td></td><td>71</td><td>1.98</td><td>757</td><td></td><td></td></tr><tr><td>CODa6</td><td></td><td>B'17/B'70</td><td>26</td><td>2008</td><td>&lt;1.60</td><td>2018</td><td>No ART</td><td></td><td>&lt;2</td><td>2.30</td><td>1,108</td><td></td><td></td></tr><tr><td>Median (IQR)</td><td></td><td>33 (28-38)</td><td></td><td></td><td>2.59 (2.01-2.93)</td><td></td><td></td><td></td><td>3 (1-3)</td><td>2.22 (2.16-2.29)</td><td>839 (776-1,042)</td><td></td><td></td></tr><tr><td rowspan="6">HIC-b</td><td>CODb1</td><td></td><td>B'14/B'49</td><td>45</td><td>2004</td><td>2.03</td><td>2015</td><td>No ART</td><td></td><td>742</td><td>2.91</td><td>868</td><td></td><td></td></tr><tr><td>CODb2</td><td></td><td>B'14/B'27</td><td>49</td><td>1988</td><td>2.98</td><td>2014</td><td>No ART</td><td></td><td>156</td><td>2.50</td><td>487</td><td></td><td></td></tr><tr><td>CODb3</td><td></td><td>B'16/B'17</td><td>27</td><td>1995</td><td>2.90</td><td>2014</td><td>No ART</td><td></td><td>428</td><td>2.79</td><td>463</td><td></td><td></td></tr><tr><td>CODb4</td><td></td><td>B'08/B'27</td><td>23</td><td>2002</td><td>2.63</td><td>2015</td><td>No ART</td><td></td><td>280</td><td>2.54</td><td>607</td><td></td><td></td></tr><tr><td>CODb5</td><td></td><td>B'52/B'52</td><td>21</td><td>1996</td><td>2.58</td><td>2014</td><td>No ART</td><td></td><td>245</td><td>2.29</td><td>546</td><td></td><td></td></tr><tr><td>CODb6</td><td></td><td>B'07/B'57</td><td>29</td><td>1998</td><td>2.74</td><td>2014</td><td>No ART</td><td></td><td>16</td><td>2.14</td><td>550</td><td></td><td></td></tr><tr><td></td><td>Median (IQR)</td><td></td><td>B'12/B'42</td><td>54</td><td>2009</td><td>2.09</td><td>2017</td><td>No ART</td><td></td><td>87</td><td>2.74</td><td>450</td><td></td><td></td></tr><tr><td rowspan="2">All HICs</td><td>Median (IQR)</td><td></td><td>29 (25-47)</td><td></td><td></td><td>2.63 (2.34-2.82)</td><td></td><td></td><td></td><td>245 (122-354)</td><td>2.54 (2.40-2.77)</td><td>546 (475-579)</td><td></td><td></td></tr><tr><td>Median (IQR)</td><td></td><td>33 (26-45)</td><td></td><td></td><td>2.63 (2.09-2.90)</td><td></td><td></td><td></td><td>71 (3-245)</td><td>2.30 (2.18-2.54)</td><td>607 (487-844)</td><td></td><td></td></tr></tbody></table>

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<table><caption>TABLE 1 (Continued)</caption><thead><tr><th rowspan="2">Group</th><th rowspan="2">Individual</th><th rowspan="2">Former ID<sup>b</sup></th><th rowspan="2">HLA allele</th><th rowspan="2">Age at diagnosis (yrs)</th><th rowspan="2">Yr of HIV diagnosis</th><th rowspan="2">Plasma HIV RNA peak (log copies/mL)<sup>c</sup></th><th rowspan="2">Sample yr</th><th rowspan="2">Duration of ART (yrs)</th><th rowspan="2">Time since TI (yrs)</th><th colspan="2">Value on the sample date for:</th><th rowspan="2">CD4 T-cell count/µL</th><th rowspan="2">Remarks</th></tr><tr><th>Plasma HIV RNA (copies/mL)<sup>d</sup></th><th>Total HIV DNA (log copies/10<sup>6</sup> PBMCs)</th></tr></thead><tbody><tr><td rowspan="10">PHI</td><td>PHI1</td><td>B*40/B*51</td><td>50</td><td>2005</td><td>4.93</td><td>2010</td><td>4.9</td><td>2010</td><td>ART ongoing</td><td>10</td><td>1.86</td><td>941</td><td></td></tr><tr><td>PHI2</td><td>B*44/B*47</td><td>36</td><td>1999</td><td>3.82</td><td>2013</td><td>13.8</td><td>2013</td><td>ART ongoing</td><td>10</td><td>1.95</td><td>985</td><td></td></tr><tr><td>PHI3</td><td>B*39/B*40</td><td>34</td><td>2007</td><td>5.57</td><td>2010</td><td>3.3</td><td>2010</td><td>ART ongoing</td><td>3</td><td>1.72</td><td>748</td><td></td></tr><tr><td>PHI4</td><td>B*27/B*40</td><td>32</td><td>2003</td><td>4.89</td><td>2008</td><td>5.4</td><td>2008</td><td>ART ongoing</td><td>4</td><td>2.1</td><td>690</td><td></td></tr><tr><td>PHI5</td><td>B*49/B*53</td><td>43</td><td>2007</td><td>6.18</td><td>2010</td><td>3.2</td><td>2010</td><td>ART ongoing</td><td>3</td><td>2.02</td><td>1,156</td><td></td></tr><tr><td>PHI6</td><td>B*0/B*56</td><td>36</td><td>2005</td><td>4.61</td><td>2012</td><td>6.2</td><td>2012</td><td>ART ongoing</td><td>2</td><td>2.02</td><td>836</td><td></td></tr><tr><td>PHI7</td><td>B*15/B*51</td><td>42</td><td>2008</td><td>6.38</td><td>2012</td><td>3.3</td><td>2012</td><td>ART ongoing</td><td>2</td><td>2.20</td><td>742</td><td></td></tr><tr><td>PHI8</td><td>B*35/B*49</td><td>42</td><td>1998</td><td>&gt;5.90</td><td>2012</td><td>13.5</td><td>2012</td><td>ART ongoing</td><td>3</td><td>1.43</td><td>847</td><td></td></tr><tr><td>Median (IQR)</td><td></td><td>39 (36-42)</td><td></td><td></td><td>5.25 (4.82-5.97)</td><td></td><td>5.2 (3.3-8.0)</td><td></td><td>3 (3-5)</td><td>1.99 (1.83-2.04)</td><td>842 (747-952)</td><td></td></tr><tr><td rowspan="6">CHI</td><td>CHI1</td><td>NA</td><td>40</td><td>2003</td><td>5.39</td><td>2014</td><td>8.7</td><td>2014</td><td>ART ongoing</td><td>&lt;20</td><td>2.76</td><td>824</td><td></td></tr><tr><td>CHI2</td><td>NA</td><td>28</td><td>2005</td><td>5.15</td><td>2015</td><td>6.2</td><td>2015</td><td>ART ongoing</td><td>&lt;20</td><td>3.09</td><td>1,410</td><td></td></tr><tr><td>CHI3</td><td>NA</td><td>21</td><td>1994</td><td>2.30</td><td>2015</td><td>17.0</td><td>2015</td><td>ART ongoing</td><td>&lt;20</td><td>2.88</td><td>1,087</td><td></td></tr><tr><td>CHI4</td><td>NA</td><td>40</td><td>2007</td><td>5.24</td><td>2014</td><td>4.5</td><td>2014</td><td>ART ongoing</td><td>&lt;20</td><td>3.50</td><td>1,075</td><td></td></tr><tr><td>CHI5</td><td>NA</td><td>27</td><td>1994</td><td>4.73</td><td>2014</td><td>13.6</td><td>2014</td><td>ART ongoing</td><td>&lt;20</td><td>2.72</td><td>1,036</td><td></td></tr><tr><td>CHI6</td><td>NA</td><td>18</td><td>1991</td><td>4.91</td><td>2013</td><td>9.6</td><td>2013</td><td>ART ongoing</td><td>&lt;20</td><td>2.84</td><td>652</td><td></td></tr><tr><td>Median (IQR)</td><td></td><td>28 (23-37)</td><td></td><td></td><td>5.03 (4.78-5.22)</td><td></td><td>9.2 (6.8-12.6)</td><td></td><td></td><td></td><td>2.86 (2.78-3.04)</td><td>1,056 (877-1,084)</td></tr></tbody></table>

<footnote><sup>a</sup>ART, antiretroviral therapy; TI, treatment interruption; CHI, chronic stage; HIC, natural HIV controller; NA, not available; PEP, postexposure prophylaxis; PHI, primary infection stage; PTC, posttreatment controller; IQR, interquartile range. HIC-a (aviremic) individuals were defined as having more than 50% of their viral loads from the 5 years before the sample date below 50 copies/mL and none above 400 copies/mL, while HIC-b (blipper) individuals did not meet those criteria.</footnote>

<footnote><sup>b</sup>Former identification number (ID) from the initial description of the ANRS-VISCONTI cohort (2), except for "case A," a mother-to-child transmission, 6-week prophylaxis at birth, ART initiated at 3 months of age (22).</footnote>

<footnote><sup>c</sup>Value before ART initiation or between the diagnosis and the inclusion in the cohort for the HIC group.</footnote>

<footnote><sup>d</sup>Quantified using an ultrasensitive technique, except for the CHI group or in case of a positive result with the regular technique.</footnote>

<footnote><sup>e</sup>A second sample was analyzed for 3 PTCS, identified as 180001b, 180002b, and 180003b on the further data.</footnote>
<figure><img src="image_5.png" /><figcaption>**FIG 1** Correlation of the genetic diversity indexes. Viral diversity was calculated by several indexes and based on 24,091 nondefective *RT* sequences from 32 individuals: the mean branch length, the mean number of alleles per nucleotide site, the mean entropy, and the mean *p*-distance. A random sampling of 20 sequences without replacement was performed to calculate these indexes, except for the mean branch length; the final results are the mean values of 1,000 repetitions. Correlations between all diversity indexes and between each diversity index and the HIV DNA viral load (log copies/10⁶ PBMCs) were calculated using Spearman's coefficients and considered significant when the *P* value was <0.05.</figcaption></figure>

loads were 2.22 and 2.54 log copies/10⁶ PBMCs for the HIC-a and the HIC-b groups, respectively (Table 1). The median times since infection were similar between sub-groups. PHIs and PTCs showed proviral genetic diversities similar to that of the HIC-a group. In addition, the PHI and HIC-a groups displayed lower genetic diversities than the HIC-b group, but the difference between PTCs and the HIC-b group was not significant. There was no difference in genetic diversity between the HIC-b and CHI groups. Finally, all diversity indexes but entropy were significantly correlated with the HIV DNA load (*P* < 0.05) (Fig. 1). Overall, our results indicate that there was no difference in genetic diversity among the PTC, PHI, and HIC-a groups, that each of these groups had a lower diversity than the CHI group, and that genetic diversity was correlated with the total HIV DNA load.

**PTCs have proportions of intact proviruses similar to those of other groups.** To evaluate the prevalence of stop codons and hypermutations, we first considered the sequences of the *RT* gene used for the HIV DNA diversity analysis. These defects were detected in 25%, 20%, 25%, and 33% of individuals from the PTC, HIC, PHI, and CHI groups, respectively (Table S1). In order to further explore the defectiveness of proviruses, we expanded the sequencing target length to nearly the full-length genome (from the 5' long terminal repeat [LTR] to the 3'LTR, 8.9 kb) and characterized the other types of genetic defects (large deletion, premature stop codon, and Ψ/MSD defect in the 5' LTR) (Fig. 3A). Besides intact and defective HIV genomes, sequences with only a defect in the *nef* gene were classified as "attenuated strains", since the virus can replicate in the absence of the accessory Nef protein, although with decreased infectivity (23). Because the quantity of biological material was limited, the complete HIV DNA genome analysis could only be performed on samples from 5 PTCs, 7 HICs, 6 PHIs, and 6 CHIs (for two additional PTC and two additional PHI participants, fewer than seven full-genome sequences were obtained, and these were excluded from analyses) (Table S2). A total of 491 complete HIV DNA sequences were then obtained for the 24 samples (median number of sequences per sample [IQR], 21 [18 to 24]).

Overall, intact proviruses were detected in PBMCs for 3/5 PTCs, and their median proportion within the proviral pool (0.04) (Fig. 4A) and median quantity (1.21 log copies/10⁶ PBMCs) (Fig. S1B) were not significantly different from those of other groups, although substantial heterogeneity of these values was observed between patients in
<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

p-value < 0.08
p-value < 0.05
p-value < 0.01

**FIG 2** Viral diversity of HIV DNA based on the *RT* gene estimated by different indexes. A 700-bp amplicon on the *RT* gene was amplified in HIV DNA genomes and sequenced using a 454 GS Junior. Sequences were aligned with Clustal, and phylogenetic trees were constructed with PhyML. Viral diversity was calculated by several indexes and based on 24,091 nondefective *RT* sequences. The indexes used were the branch length of the phylogenetic tree (samples with fewer than 4 nondefective haplotypes were excluded) (A), the entropy (B), the number of alleles per nucleotide site (C), and the *p*-distance (D). A random sampling of 20 sequences without replacement was performed for indexes B to D; the final results are the mean values of 1,000 repetitions. The mean value for each group is depicted with a colored horizontal line. The diversity was compared among groups using Wilcoxon tests. Significant differences (P < 0.05) are depicted with continuous lines above the graph, while trends (P < 0.05 and P < 0.08) are depicted with dotted lines. HICs were divided into two subgroups: HIC-a (aviremic) individuals had more than 50% of their viral loads from the 5 years before the sample date below 50 copies/mL and none above 400 copies/mL, while HIC-b (blippers) individuals did not meet those criteria.

each group (Fig. 4). For two PTCs, four HICs, and three CHIs, we could not detect intact provirus in the samples analyzed (Table S2), while this was not the case for PHIs. Large deletions were the most frequent defect observed in PTCs, similar to other groups of PWH, followed by both hypermutations and frameshifts (Fig. 3B). We observed a trend toward a higher proportion and number of genomes with a defect in only the *nef* gene in the HIC group compared to the proportion and number in the PTC group (P = 0.066) (Fig. 4C and Fig. S1D), due to the presence of a similar *nef* partial deletion in every proviral sequence of two HIC participants (CODa5 and CODb1) (Table 1). Some of these
<figure><img src="image_8.png" /><figcaption>**FIG 3** Identification of intact sequences and the different types of defective sequences and their proportions. HIV DNA genomes were amplified from the 5'LTR to the 3'LTR after limiting dilution and sequenced using a MiSeq instrument. Complete genomic sequences were assembled using Spades. (A) Process of identification of genetically defective and intact proviruses. A sequential approach was used. Premature stop codons due to hypermutations and frameshifts were detected using pairwise alignment implemented in Goalign. MSD defects were visually identified by alignment of genomic sequences and comparison to HIV compendium sequences. (B) Mean proportions of each type of HIV DNA genome in each group of patients: *N* is the number of patients in the group, and *n* is the mean number of full-length sequences per individual.</figcaption></figure>

proviruses had other defects, such as large deletions. This suggests that viral factors— i.e., a less fit virus—could participate in the control of infection in these two HICs. This phenomenon was not observed in PTCs. Some PWH from the PHI, CHI, and HIC groups displayed small proportions of proviruses with *nef* defects (4 to 7%), but none had a similar profile of an attenuated HIV strain. The proportion of defective proviruses among the proviral pool and their quantity per million PBMCs were significantly larger in the CHI group than in the PHI group (Fig. 4B and Fig. S1C). This appeared to be mostly explained by the large quantities of HIV DNA sequences harboring large deletions and of those harboring hypermutations in CHIs (Fig. 4D and E and Fig. S1). On the other hand, CHIs had a trend toward a lower proportion of sequences with frame-shifts than PHIs (Fig. 4F); this suggests that the different genetic defects could appear at different stages of the infection and then be modulated by the dynamics of cells harboring HIV during infection. The quantities of defective proviruses were also significantly larger in CHIs than in HICs and PTCs (Fig. S1C). Globally, the quantity of defective HIV DNA was highly correlated with the total HIV DNA load (r = 0.968; *P* < 0.0001).

Notably, we observed identical proviral sequences (assumed to be clones [24]) for both intact and defective genomes in several participants within each group (Fig. S2), suggesting that the clonal expansion of HIV-infected cells was not dependent on the "intact" or "defective" characteristic of their provirus and could be linked to homeostatic proliferation or antigen-driven proliferation (25).

Overall, our data indicate that the control of infection in PTCs does not seem to be related to a smaller proportion or quantity of intact proviruses in these individuals than in other PWH.

**Long-term outcome of the PTC proviral landscape.** As we had access to a second sample taken 4 to 6 years after the initial sample for three individuals from the PTC group, we next investigated whether their proviral landscape had evolved or not. Two of these participants (180001 and 180002) maintained total control of viremia during the whole follow-up (ultrasensitive plasma HIV RNA loads of <8 and <10 copies/mL, respectively), while the third (180003) had begun to relapse (plasma HIV RNA load of 1,278 copies/mL) and resumed ART immediately after this sample was obtained (Table 1). One of the three individuals (180001) appeared to have a decrease in the
<figure><img src="image_9.png" /><figcaption>**FIG 4** Proportions of each type of full-length HIV DNA genome. HIV DNA genomes were amplified from the 5'LTR to the 3'LTR and sequenced using a MiSeq instrument. Complete genomic sequences were assembled using Spades. Genetic defects were sequentially identified as follows: large deletions (D), APOBEC-induced hypermutations (E), frameshifts (F), and defects in the 9'/MSD regions of the 5'LTR (G). Sequences with a defect in the nef gene only were considered attenuated strains (C), and the remaining sequences were inferred to be intact (A). The mean value for each group is depicted with a colored horizontal line. The proportions of each type of provirus were compared among groups using Wilcoxon tests. Significant differences (P < 0.05) are depicted with continuous lines above the graphs, while trends (P values between 0.05 and 0.08) are depicted with dotted lines. (A) The median proportions (P) of intact proviruses were 2% in CHIs, 0% in HICs, 22% in PHIs, and 4% in PTCs. (B) The median proportions of defective proviruses (sum of large deletions, hypermutations, frameshifts, and 5'LTR defects) were 96% in CHIs, 67% in HICs, 75% in PHIs, and 96% in PTCs. (C) The median proportions of proviruses with defects in the nef gene only (attenuated strains) were 0% in CHIs, 6% in HICs, 2% in PHIs, and 0% in PTCs. (D) The median proportions of proviruses with large deletions were 82% in CHIs, 56% in HICs, 49% in PHIs, and 60% in PTCs. (E) The median proportions of proviruses with hypermutations were 11% in CHIs, 0% in HICs, 4% in PHIs, and 5% in PTCs. (F) The median proportions of proviruses with frameshifts were 0% in CHIs, 0% in HICs, 8% in PHIs, and 4% in PTCs. (G) The median proportions of proviruses with 5'LTR defects were 0% in all four groups.</figcaption></figure>

proportion of intact proviruses, while the other two had no or little evolution of this proportion (Fig. 5 and Table S2). Details concerning the genetic defects are presented in Table S2. Phylogenetic trees of the full-length HIV DNA sequences of these 3 PTCs showed that proviral sequences from the two time points were mixed (Fig. 6), indicating that there had been no or very little evolution of the viral strains and no selective pressure. This reflects the effective control of viral replication during a long period of remission after TI.

DISCUSSION

In the hope of inducing remission of HIV infection without the necessity for lifelong intake of antiretroviral therapy, a better understanding of the factors associated with the control of infection in PTCs, who represent models of remission, is needed. A characteristic of PTCs is a small reservoir size, which appears to be a necessary but insufficient criterion. Indeed, only a minority of individuals with a small reservoir size keep the control of infection in the case of TI (3). We describe here for the first time the viral diversity and the proportions of intact and defective proviruses in PTCs almost a
<figure><img src="image_10.png" /><figcaption>**FIG 5** Changes in the proportions of intact full-length HIV DNA genomes for individuals with a second sample available 4 to 6 years after the initial sample. The median proportion of intact proviruses was compared between the two time points using a Wilcoxon test.</figcaption></figure>

decade after TI, with ultradeep sequencing technologies providing an in-depth characterization of archived genomes constituting the HIV reservoir.

One hypothesis was that low viral diversity could contribute to, and be the result of, the control of HIV infection. In our study, the PTC, PHI, and HIC-a groups presented similarly low genetic diversities, whereas those of the HIC-b and CHI groups were higher, consistent with the past viral replication. Concordantly, De Azevedo et al. showed that proviral diversity was higher in viremic controllers (with persistent viremia at 80 to 2,000 copies/mL) than in elite controllers (persistent undetectable viral loads) (16). The link between viral diversity and history of viremia is also reinforced by the significant correlation in our study between the diversity indexes and the total HIV DNA load: previous studies showed that when measured in situations of controlled infection, this biomarker of persistence reflects the history of HIV infection and cumulative viremia (5, 26). Based on this correlation, our data indicate that no or very little viral replication occurred in the HIC-a group or in the PTCs for all the years since TI. This low viral diversity reflects the sustained control of viral replication since early infection. Of note, our study also reveals substantial variability in the genetic proviral diversity among PTCs, as previously observed for other groups of PWH.

The similar results between PTCs and PHIs call into question the predictive value of viral genetic diversity for virologic control or breakthroughs. Previous studies are discordant concerning this potential predictive value. Pernas et al. showed no significant difference in *gag* gene diversity but a higher diversity of the *env* gene in cases of loss of natural control than in persistent control (27). In contrast, De Azevedo et al. found no predictive value of *env* diversity for virologic breakthroughs (28). In our study, *RT* (*pol* gene) viral diversity was not predictive of a breakthrough in the four following years in HICs or in PTCs (data not shown). Unfortunately, we did not have enough biological material to study the viral diversity of the *env* gene, which might have been more informative. In contrast, viral blips were previously shown to be predictive for the loss of control in PTCs and HICs (29, 30) and for the time before rebound after TI in early-treated individuals (9). Plasma viral loads thus appear to be better predictors of future breakthroughs than viral diversity of HIV DNA, which takes longer to be archived.

Our study also explored the proportions of intact and defective proviruses among the proviral pool during different contexts of controlled HIV infection and provided the first complete genome analysis of HIV DNA in both PTCs and HICs. Of
<figure><img src="image_11.png" /><figcaption>**FIG 6** Phylogenetic trees of all nearly full-length HIV DNA genomic sequences for 3 PTCs. Individual trees of proviruses from the 3 PTCs who had two blood samples taken after TI. HIV DNA genomes were amplified from the 5'LTR to the 3'LTR and sequenced using a MiSeq instrument. Complete genomic sequences were assembled using Spades and aligned with MAFFT, and the phylogenetic tree was inferred with PhyML. Black squares represent sequences from the first samples, and red squares those from the second samples. Blue stars indicate identical sequences assumed to be clones. 180001 (A); 180002 (B); 180003 (C).</figcaption></figure>

note, the HICs for whom we obtained viral genome sequences in this study had a higher median HIV DNA level than the 202 HICs analyzed in the national ANRS-CODEX cohort (6). A peculiarity of the HIC group was the presence of a partial *nef* deletion in every proviral sequence of two HICs, which could be associated with a decrease in viral infectivity (23, 31). Our finding of *nef* defects in all sequenced pro-viruses suggests that either the founder virus might have been an attenuated strain in these cases or the cells harboring nonattenuated proviruses were progressively eliminated by the immune response and these proviruses with defects in *nef* became largely predominant. Concordantly, previous reports showed that several cases of spontaneous control of HIV infection were linked to the presence of atte-nuated viral strains harboring a truncated or deficient protein, in particular Env, Vif, or Nef (32-34). This characteristic for only two of the seven HICs, as well as the high interindividual heterogeneity of results observed within this group, highlight the plethora of mechanisms that could contribute to HIV control. No *nef* deletion was observed in PTCs in our results, suggesting that posttreatment and natural control may rely upon distinct mechanisms, although both groups have a small blood HIV
reservoir (35). The lack of Nef-deficient proviruses in the PTC group should be con-
firmed in more individuals.

When studying the complete HIV DNA genome of PTCs, we showed that they had
low proportions of intact genomes in samples taken at a median of 9.4 years after TI,
not different from the proportions observed in other groups. These data suggest that
other factors play a role in the viral control. High heterogeneity of the proportions of
intact proviruses was observed among PTCs (0% to 36%), as observed in other groups
of PWH. In their study, Sharaf et al. used single-genome amplification and next-genera-
tion sequencing (NGS) to analyze samples from before TI from 10 PTCs and 16 NCs
who experienced viral rebound after TI (17). The proportions of intact genomes before
TI were similar in both groups (median [range], 1.4% [0 to 42%] and 4.1 [0 to 32%] in
the future PTCs and NCs, respectively, out of a median [range] of 27 [3 to 73] proviral
sequences per individual for PTCs and 50 [12 to 120] for NCs). Our results show that
this status is maintained for several years after TI. Sharaf's study also revealed that
PTCs have a genetically intact proviral reservoir 7-fold lower than that of NCs in abso-
lute values before TI. This smaller number of intact viral genomes resulted from lower
total HIV DNA loads in PTCs than in NCs. In our study, several years after TI, the quan-
tity of intact proviruses was not different than that observed in aviremic PWH on ART
or in HICs. Only the number of defective proviruses was lower in PTCs than in CHIs,
similar to PHIs. As PTCs had been treated since the primary infection and well con-
trolled afterwards, there was no opportunity for viral evolution and accumulation of
proviruses with defects. Defective proviruses can contribute to HIV pathogenesis (5) by
the production of viral RNAs and proteins/antigens that continuously stimulate the
immune system (36, 37) or to infectious viruses after complementation, even if this
process is probably less efficient than production by intact proviral genomes (38). This
could partly explain the facts that the total HIV DNA load, which is correlated to a high
level of defective proviruses, is a clinically relevant marker (5) and that a reduced num-
ber of defective proviruses could be beneficial.

Based on the presence of some proviral sequences with strict identity, assumed to
be clones with identical integration sites (24), we showed that clonal cell expansion
contributed to the persistence of both intact and defective proviruses, as previously
described (11, 39).

Interestingly, the comparison of samples taken 4 to 6 years later (i.e., 11.8 to
15.2 years after TI) from the three PTCs in our study showed no or little evolution of
the proviral landscape, either in the proportions of intact and defective genomes or in
the viral sequences themselves, as shown by the intermingled sequences on the phylo-
genetic tree. These results suggested that the stability of the proviral landscape in
PTCs between the period before TI and 1.4 years after TI that was previously described
(17) is prolonged for more than 10 years after TI. These data suggest that the blood
proviral landscape in PTCs is preserved early by ART and does not seem to evolve after
TI due to effective control of HIV. Nevertheless, as all PHIs do not become PTCs in the
case of TI (4), despite their similar proviral characteristics, host factors most probably
predominate in the control of infection in cases of HIV remission. One recently sug-
gested hypothesis is the control of viral replication by particularly efficient natural killer
(NK) cells in association with HLA-Bw4 and HLA-C2 killer immunoglobulin-like receptor
(KIR) ligands (40). In ART-treated PWH, Einkauf et al. recently showed that proviruses
integrated in nongenic chromosomal regions were transcribed less that those in genic
regions and that transcriptionally active proviruses underwent a negative selection
over time, except in the case of clonal expansion (41). Such a study of integration sites
of intact and defective proviruses in PTCs could provide further information on their
reservoirs. We can hypothesize that the NK immune response in PTCs could have con-
tributed to the selection of cells harboring either intact proviruses integrated in non-
genic regions or defective proviruses. Control in PTCs could then be associated with a
"block and lock" mechanism, which could be effective in the presence of small quanti-
ties of intact proviruses. The noticeable interindividual heterogeneity shown for the
first time among PTCs for all the biomarkers we studied points out that several mechanisms of control could exist and that a single strategy for cure might not fit all PWH.

One limitation of this study is the relatively small number of sequences analyzed because of the low HIV DNA loads. The complexity of TI and the rarity of posttreatment control limit large studies on PTCs. Very few cohorts include PTCs with such a long period of time after TI, making the data from the ANRS-VISCONTI cohort very valuable. Recent data have indicated that the proportions of defective proviruses could differ between blood and tissues and that viruses that rebounded after TI could have come from diverse anatomical compartments (42). Further studies on lymphoid tissues and on animal models could be informative of the global proviral landscape in remission, including integration sites, and help in approaching the complexity of viral control.

To conclude, the present study provides for the first time an in-depth characterization of the proviral landscape in PTCs nearly a decade after TI and compares it to that of HICs. Our results show that the PTC group presents similarly small proportions and quantities of intact proviruses as the other groups examined in the study. Although host/immune factors most probably play a role in posttreatment control, the particularly small blood HIV reservoirs and the low frequencies of intact proviruses in PTCs could facilitate the control of infection in these patients. Furthermore, the low viral diversity and the absence of evolution in the landscape of the HIV DNA quasispecies after TI confirm the slow dynamics of HIV infection in PTCs. This and other studies in PTCs should help in designing strategies to achieve sustained viral remission in the absence of ART.

## MATERIALS AND METHODS

**Patients and samples.** PTCs from the ANRS-VISCONTI cohort (2) who had available frozen blood cells (5 to 8 million PBMCs) were included (n = 8). A second time point was analyzed when a subsequent sample was available (n = 3). The criteria for inclusion in the cohort were HIV-1 infection, pretherapeutic plasma viral load above 2,000 copies/mL, ART maintained for at least 12 months, and viral load below 400 copies/mL in two consecutive samples more than 1 year after TI. Natural HIV controllers were selected from the French multicenter ANRS-CODEX cohort (19) based on the availability of samples (n = 13). The criteria for inclusion in the cohort were as follows: HIV-1 infection with a follow-up time longer than 5 years, the last five plasma HIV RNA viral loads lower than 400 copies/mL, and no ART received. The PHI and CHI groups were selected from outpatients' follow-up at Orleans Hospital. The PHI (n = 8) group was constituted of patients receiving ART continuously for more than 3 years that was initiated in primary infection and considered effective on the basis of controlled viral load (<50 copies/mL) for more than 2 years. The CHI group (n = 6) was constituted of patients receiving ART initiated in chronic infection and with plasma viral load peaks similar to those observed for the PHI group. None had reached the AIDS stage. All participants gave informed consent. The VISCONTI study and the CODEX cohort were approved by the ethics review committees of Ile de France VII. The study concerning other patients was approved by the Tours ethics review committee. All analyses were carried out retrospectively on cryopreserved blood cells.

**Virological quantifications.** Routine HIV RNA viral loads were quantified with the commercial assay available in each clinical center. Ultrasensitive HIV RNA quantifications were performed on 2 to 10 mL of plasma using either a generic HIV real-time PCR assay (Biocentric) or an adaptation of the COBAS Ampliprep/COBAS TaqMan HIV-1 test version 2 (Roche Diagnostics) (6). Total HIV DNA loads were quantified prospectively in the cohorts using the GENERIC HIV DNA real-time PCR assay (Biocentric), as previously described (6, 43).

**PCR and NGS analyses.** (i) **RT gene.** Viral genetic diversity, together with the presence of stop codons/hypermutations, was analyzed based on an amplicon from the *RT* region of the *pol* gene (20). Amplification was carried out as previously described by the ANRS French resistance group (HXB2 coordinates of the amplicon, 2609 to 3292) (44), with an adapted nested PCR including the multiplex identifier (MID) of the 454 GS Junior instrument (Roche Diagnostics). Deep sequencing of the *RT* amplicon was performed using GS Junior sequencing XL+ kits, which provided reads up to 800 bp long, following the manufacturer's instructions. The 8E5/LAV cell line was included as a control.

**(ii) Near-full-length-genome sequencing.** Supplemental data on the proportion of each type of genetic defect and the global proportions of intact and defective proviruses were obtained based on a complete genome analysis. For single-genome analyses (SGAs), limiting dilution conditions, determined separately for each sample, were used for the first PCR in order to avoid the preferential amplification of short fragments and to allow the study of viral haplotypes. HIV DNA was then amplified from the 5'LTR to the 3'LTR with nested PCR using PrimeSTAR GXL DNA polymerase (TaKaRa) and previously described primers (36). The following PCR conditions were applied: 98°C for 10 min, followed by 98°C for 10 s, 58°C or 60°C (for the first and second PCR, respectively) for 15 s, and 68°C for 9 min for 40 cycles, and then 10°C indefinitely. The PCR mixture volume was 50 µL. Five microliters of the first PCR mixture was used in the second-round PCR. Positive nested PCR products were identified by electrophoresis on a 1%
agarose gel and purified with either a QIAquick PCR Purification Kit or a QIAquick Gel Extraction Kit (Qiagen). Library preparations were performed using a Nextera DNA Flex Library Prep Kit, and paired-end sequencing (2 × 250 bp) was performed using a MiSeq Reagent Nano Kit on a MiSeq instrument (Illumina) following the manufacturer's instructions. As a quality control, we performed the same PCRs with limiting dilution on an 8E5/LAV cell line, which was sequenced three times in the first Illumina run for repeatability verification and then once in each run for reproducibility assessment.

**Bioinformatics analyses.** (i) **454 data.** Reads were analyzed with the Roche software AVA. After passing quality filters, haplotypes were aligned with Clustal using HXB2 as a reference and submitted to the online Los Alamos HIV Database Hypermut tool for the identification of hypermutated sequences (45).

To estimate the viral diversity, the mean branch length was calculated for each participant using Gotree (46) after construction of a phylogenetic tree using PhyML 3.3.2018062 (47) (options -m GTR -f m -c 4 -a e -o trl), including nondefective sequences only. To avoid creating bias in the results because of the variability in the number of reads obtained for each sample, we used a rarefaction approach to calculate the different diversity indexes (16). A random sampling of 20 sequences without replacement was performed 1,000 times; the final values are the means of these 1,000 repetitions. With this approach, we calculated the mean number of alleles (or variants) per nucleotide site, the mean entropy, and the *p*-distance.

(ii) **Illumina data.** Quality control of FASTQ files was performed using FastQC version 0.11.8 and MultiQC version 1.7 (48). After masking parts of the HXB2 reference genome corresponding to the pri-mers, reads were mapped to HXB2 using Minimap2 version 2.14 (49) with the option "-ax splice." SAM files were converted to BAM files and indexed using SAMtools version 1.9 (50). In parallel, sequences were assembled using Spades version 3.11.1 (51) at different coverage cutoffs (going from 0 to 200) with the options "--cov-cutoff <cutoff> --careful". Premature stop codons due to hypermutations and frameshifts were detected in HIV genes extracted from these assembled sequences using pairwise alignment implemented in Goalign version 0.3.0-alpha (46).

To build the phylogenetic tree, sequences were first aligned with MAFFT version 7.313 (52). Then, sequences having more than 80% gaps and alignment columns having at least one gap were removed using Goalign version 0.3.1 (command goalign clean). The final alignment contained 192 sequences of 6,376 nucleotides. This alignment was reformatted into Phylip format (command goalign reformat phy-lip), and duplicate sequences were temporarily removed (command goalign dedup). The phylogenetic tree was then inferred with PhyML version 3.3.20180621 (options -m GTR -f m -c 4 -a e -o trl), and duplicate sequences were reintroduced into the inferred tree using Goalign version 0.3.1 (command Goalign repopulate). The final tree was then uploaded to iTOL along with its annotations produced with table2itol (https://github.com/mgoeker/table2itol).

**Quality controls for the NGS analyses.** To verify the reproducibility of the NGS and bioinformatic analyses, the 8E5/LAV cell line was included as a control in both *RT* and full-genome analyses. All *RT* sequences belonged to a unique haplotype, harboring no hypermutations or stop codon mutations (data not shown). For the full-genome analysis, the exact same sequence was found for the assembled 8E5/LAV contig of every run and of the three replicates of the first run, validating the NGS process. Phylogenetic trees of all *RT* sequences and all complete genome sequences confirmed the absence of cross-contamination between samples (data not shown).

**Statistics.** Statistical analyses were performed using RStudio software (version 1.0.136). Variables were compared between groups using Wilcoxon tests. *P* values of <0.05 were considered significant. Correlations were determined using Spearman's correlation coefficients. Samples with an insufficient number of sequences obtained (<20 sequences or <4 haplotypes for the *RT* amplicon; <7 sequences for the full-length genome) were excluded (Tables S1 and S2). HIV DNA and HIV RNA viral loads above or below the limits of quantification were set to the threshold values for statistical analyses.

**Data availability.** *RT* haplotype sequences are available in GenBank under accession numbers OP994861 to OP995430. Full-length HIV DNA sequences are available in GenBank under accession numbers OP994351 to OP994860.

## SUPPLEMENTAL MATERIAL

Supplemental material is available online only.

**SUPPLEMENTAL FILE 1, PDF file, 1.6 MB.**

## ACKNOWLEDGMENTS

We thank the participants and clinicians who participated in this study and the RHIVIERA consortium for helpful discussions.

The ANRS-CODEX/VISCONTI cohort is sponsored by the French National Agency for Research on AIDS and Viral Hepatitis (ANRS). This work was supported by the ANRS (grant to V.A.-F.) and a National Institutes of Health grant (NIH grant no. P01-A131365-01 to A.S.-C.). The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

The members of the ANRS-VISCONTI study group are as follows: Faroudy Boufassa and Sylvie Orr (CMG, Hôpital Bicêtre, Le Kremlin Bicêtre); Firouzé Bani-Sadr, Maxime
Hentzien, Jean-Luc Berger, and Isabelle Kmiec (Maladies Infectieuses, CHU—Hôpital Robert Debré, Reims); Gilles Pichancourt and Safa Nasri (Hémato-Oncologie, Centre Hospitalier Henri Duffaut, Avignon); Gilles Hittinger, Véronique Lambry, and Anne-Cécile Beaudrey (Maladies Infectieuses, CHITS Hôpital Sainte Musse, Toulon); Gilles Pialoux, Julie Chas, Christia Palacios, and Anne Adda (Maladies Infectieuses, Hôpital Tenon, Paris); Jean Paul Viard and Marie-Josée Dulucq (Centre de Diagnostic et Thérapeutique, Hôtel Dieu, Paris); Laurence Weiss, Marina Karmochkine, and Mohamed Meghadecha (Service d'Immunologie Clinique, Hôpitaux Universitaires Paris Centre— Hôtel Dieu, Paris); Dominique Salmon-Ceron and Marie-Pierre Piétri (Unité Fonctionnelle de Pathologie Infectieuse, Hôtel Dieu, Paris); Philippe Blanche (Médecine Interne, Hôpital Cochin, Paris); Jean-Michel Molina, Olivier Taulera, Diane Ponscarme, and Jeannine Delgado Bertaut (Maladies Infectieuses, Saint-Louis, Paris); Djamila Makhloufi, Matthieu Godinot, and Valérie Artizzu (Immunologie Clinique, Hôpital Edouard Herriot, Lyon); Patrick Miailhes, Laurent Cotte, Sophie Pailhes, Anne Conrad, Ludovic Karkowski, and Stanislas Ogoudjobi (Maladies Infectieuses et Tropicales, Hôpital de la Croix Rousse, Lyon); Yazdan Yazdanpanah, Sophie Matheron, and Cindy Godard (Maladies Infectieuses, Bichat, Paris); Louis Bernard, Frédéric Bastides, and Olivier Bourgault (Maladies Infectieuses, Hôpital Bretonneau, Tours); Christine Jacomet and Emilie Goncalves (Maladies Infectieuses, Hôpital Gabriel-Montpied, Clermont-Ferrand); Pascal Chavanet, Lionel Piroth, and Sandrine Gohier (Infectiologie, CHU François Mitterrand, Dijon); Agnès Meybeck, Thomas Huleux, and Pauline Cornavin (Maladies Infectieuses, Hôpital Gustave Dron, Tourcoing); Yasmine Debab and David Théron (Maladies Infectieuses et Tropicales, Hôpital Charles Nicolle, Rouen); and Thierry Prazuck, Laurent Hocqueloux, and Barbara De Dieuleveult (Maladies Infectieuses, Hôpital de La Source, Orléans). The members of the ANRS-CODEX Study Group are as follows: Jean-Pierre Faller and Patricia Eglinger (Service des Maladies Infectieuses, CH de Belfort-Montbéliard, Belfort); Pascal Roblot and David Plainchamp (Service de Médecine Interne, CHU Poitiers-La Milétrie, Poitiers); Hugues Aumaitre and Martine Malet (Service des Maladies Infectieuse et Tropicales, CH de Perpignan, Perpignan); Christine Rouger, Gérard Rémy, and Isabelle Kmiec (Service des Maladies Infectieuses, CHU Reims-Hôpital Robert Debré, Reims); Jean-Luc Delassus (Service de Médecine Interne, CHI Ballanger, Aulnay Sous-Bois); Alain Devidas (Service d'Hématologie, CH Sud-Francilien—Hôpital Gilles de Corbeil, Corbeil-Evry); Eric Froguel and Sylvie Tassi (Service de Médecine Interne-Maladies Infectieuses, CH de Marne la Vallée, Jossigny); Philippe Genet and Juliette Gerbe (Service Hématologie-Immunologie, Centre Hospitalier Victor Dupouy, Argenteuil); Olivier Patey and Richier Laurent (Service des Maladies Infectieuses et Tropicales, CHI Villeneuve Saint Georges, Villeneuve Saint Georges); Marie-Christine Drobacheff and Aurélie Proust (Service de Dermatologie, Hôpital Saint-Jacques, Besançon); Helder Gil (Service de Médecine Interne, CHU de Besançon, Besançon); Laurence Gérard and Eric Oksenhendler (Service d'Immunopathologie Clinique, Hôpital Saint Louis, Paris); Jean-Michel Molina, Caroline Lascoux, and Sylvie Parlier (Service de Maladies Infectieuses et Tropicales, Hôpital Saint Louis, Paris); Frédéric Lucht and Véronique Ronat (Service de Maladie Infectieuse, Hôpital Bellevue, Saint Etienne); Michel Dupon, Hervé Dutronc, Séverine Le Puil, and Didier Neau (Service des Maladies Infectieuses, CHU—Hôpital Pellegrin, Bordeaux); Patrick Mercié (Service Tropicales, CHU— Hôpital Saint André, Bordeaux); Philippe Morlat, Sabrina Caldato, Jean-Luc Schmit, and Nathalie Decaux (Service de Médecine Interne et Maladies Tropicales, CHU—Hôpital Saint André, Bordeaux); Jean-Pierre Bru and Gaëlle Clavere (Service des Maladies Infectieuses, Centre Hospitalier Annecy, Annecy); Olivier Lambotte, Jean-François Delfraissy, Cécile Goujard, and Katia Bourdic (Service de Médecine Interne AP-HP—CHU de Bicêtre, Le Kremlin Bicêtre); Daniel Vittecoq and Claudine Bolliot (Service des Maladies Infectieuses AP-HP—CHU de Bicêtre, Le Kremlin Bicêtre); Thierry Lambert (Consultation d'Hématologie, AP-HP—CHU de Bicêtre, Le Kremlin Bicêtre); Jean-François Bergmann and Maguy Parrinello (Service de Médecine Interne A, Hôpital Lariboisière, Paris); Gilles Pichancourt (Service Hématologie, Hôpital Henri Duffaut, Avignon); Yves Welker (Service de Maladies
Infectieuses, CHI de Poissy—Saint Germain en Laye, Saint Germain en Lay); Alain Lafeuillade and Gisèle Philip (Service d'Infectiologie, CHITS Hopital Sainte Musse, Toulon); Christophe Rapp and Melle Lerondel (Service des Maladies Infectieuses, Hôpital d'Instruction des Armées Bégin, Saint Mandé); Pierre de Truchis and Berthe Huguette (Département de Médecine Aigue Spécialisée, Hôpital Raymond Poincaré, Garches); Vincent Jeantils and Fatouma Mchangama (Unité de Maladies Infectieuses, Hôpital Jean Verdier, Bondy); Paul Henri Consigny and Fatima Touam (Consultation de Maladies Infectieuses, Centre Médical de l'Institut Pasteur, Paris); Gilles Pialoux and Sophie le Nagat (Service des Maladies Infectieuses, Hôpital Tenon, Paris); Olivier Bouchaud and Patricia Honoré (Service de Médecine Interne et Endocrinologie, Hôpital Avicenne, Bobigny); François Boué and Mariem Raho-Moussa (Service de Médecine Interne, Hôpital Antoine Béclère, Clamart); Jean-Paul Viard, Agnès Cros, Dominique Salmon-Céron, Marie-Pierre Pietri, Laurence Weiss, and Lio Collias (Consultation d'Immunologie Clinique et Infectiologie, Hôpital Hôtel Dieu, Paris); David Zucman, Olivier Blétry, and Dominique Bornarel (Service de Médecine Interne, Hôpital Foch, Suresnes); Emmanuel Mortier and Zeng Feng (Service de Médecine Interne, Hôpital Louis Mourier, Colombes); Jean-Daniel Lelièvre (Service d'Immunologie Clinique, Hôpital Henri Mondor, Créteil); Christine Katlama, Yasmine Dudoit, Anne Simon, and Catherine Lupin (Service des Maladies Infectieuses, Hôpital Pitié-Salpêtrière, Paris); Pierre-Marie Girard and Michèle Pauchard (Service des Maladies Infectieuses, Hôpital Saint Antoine, Paris); Sylvie Abel and André Cabié (Service de Maladies Infectieuses et Tropicales, Hôpital Pierre Zobda-Quitman, Fort de France, Martinique); Pascale Fialaire, Jean-Marie Chennebault, and Sami Rehaiem (Service des Maladies Infectieuses et Tropicales, CHU Angers, Angers); Luc de Saint Martin, Pascale Perfezou, and Jean-Charles Duthe (Service de Pneumologie, CHU de Brest, Brest); Pierre Weinbreck and Claire Genet (Service des Maladies Infectieuses, CHU de Limoges, Limoges); Djamila Makhloufi and Florence Garnier (Service d'Immunologie Clinique, HCL—Hôpital Edouard Herriot, Lyon); Patrick Miailhes and Stanislas Ogoudjobi (Service de Maladies Infectieuses et Tropicales, HCL—Hôpital Edouard Herriot, Lyon); Isabelle Poizot-Martin, Olivia Fauche, and Alena Ivanova (Service Hématologie-CISIH, Hôpital Sainte Marguerite, Marseille); Patrick Philibert and Mame Penda Sow (Consultation de Médecine Interne, Hôpital Européen Marseille, Marseille); Patrick Yeni, Sophie Matheron, and Cyndi Godard (Service des Maladies Infectieuses, Hôpital Bichat Claude Bernard, Paris); François Raffi and Hervé Hüe (Service de Médecine Interne, Hôpital de l'Hôtel Dieu, Nantes); Philippe Perré (Service de Médecine Interne Post-Urgence, Centre Hospitalier Départemental, La Roche sur Yon); Pierre Marie Roger and Aline Joulie (Service des Maladies Infectieuses, CHU—Hôpital l'Archet, Nice); Éric Rosenthal (Service Médecine Interne, CHU—Hôpital l'Archet, Nice); Christian Michelet, Faouzi Souala, and Maja Ratajczak (Service des Maladies Infectieuses, CHU—Hôpital Pontchaillou, Rennes); Marialuisa Partisani and Patricia Fischer (HUS—Hôpital Civil, Strasbourg); Louis Bernard and Pascale Nau (Service des Maladies Infectieuses, CHRU—Hôpital Bretonneau, Tours); Pierre Delobel and Florence Balsarin (Service des Maladies Infectieuses, CHU—Hôpital Purpan, Toulouse); Marc De Lavaissiere (Service Médecine Interne, CHG de Montauban, Montauban); Renaud Verdon and Philippe Feret (Service des Maladies Infectieuses, CHU—Hôpital de la Côte de Nacre, Caen); Christine Jacomet (Service des Maladies Infectieuse, CHU Gabriel Montpied, Clermont Ferrand); Lionel Piroth and Sandrine Gohier (Service de Maladies Infectieuses et Tropicales, CHU—Hôpital du Bocage, Dijon); Pascale Leclercq and Sylvie Gerberon (Service Médecine Aigue Spécialisée, CHU—Hôpital Albert Michallon, Grenoble); Agnés Meybeck and Raphaël Biekre (Service des Maladies Infectieuses, CH—Hôpital Gustave Dron, Tourcoing); Thierry May and Marie-Pierre Bouillon (Service de Maladies Infectieuses et Tropicales, CHU Nancy, Nancy); François Caron, Yasmine Debab, and David Theron (Service de Maladies Infectieuses et Tropicales, CHU—Hôpital Charles Nicolle, Rouen); Marc Gatifosse (Service de Médecine Interne, CH René Arbeltier, Coulommiers); Martin Martinot and Anne Pachart (Service de Maladies Infectieuses-Médecine Interne, Hôpitaux Civils de Colmar, Colmar); Patrice Poubeau (Service de Pneumo-Phtisiologie, Centre Hospitalier Sud Réunion—Hôpital de St Pierre, Saint Pierre, La Réunion); Catherine Gaud (Service Immunologie Clinique, Centre
Hospitalier Félix Guyon, Ile de la Réunion); Agnès Uludag (Service de Médecine Interne, Hôpital Beaujon, Clichy); Philippe Arsac and Lydia Bouaraba (Service de Médecine Interne, CHR Orléans—Hôpital Porte Madeleine, Orléans); Laurent Hocqueloux and Barbara de Dieulevault (Service de Maladies Infectieuses et Tropicales, Hôpital Orléans la Source, Orléans); Isabelle De Lacroix Szmania and Laurent Richier (Service des Médecine Interne, Centre Hospitalier Intercommunal, Créteil); Vincent Daneluzzi (Service de Médecine A, CASH—Hôpital Max Fourestier, Nanterre); Elisabeth Rouveix (Service de Médecine Interne 2, Hôpital Ambroise Paré, Boulogne); Geneviève Beck-Wirth (Service d'Hématologie Clinique VIH, Centre Hospitalier de Mulhouse, Mulhouse); Philippe Romand (Service de Pneumologie, CHI Les Hôpitaux du Léman, Thonon les Bains); Laurent Blum and Martine Deschaud (Service Médecine-Gastroentérologie, Centre Hospitalier René Dubos, Pontoise); Christophe Michau (Service de Médecine Interne, Centre Hospitalier de Saint Nazaire, Saint Nazaire); Christian Bernard and Florence Salaun (Service de Médecine Interne, CHR Metz Thionville—Hôpital Notre Dame de Bon Secours, Metz); Philippe Muller (Service de Dermatologie, Hôpital Beauregard, Thionville); Yves Poinsignon (Service de Médecine Interne, Hôpital Prosper Chubert, CHBA, Vannes); Annie Lepretre and Martine Deschaud (Service de Médecine Interne, Hôpital Simone Veil, Eaubonne); Albert Sotto and Régine Donceso (Service des Maladies Infectieuses et Tropicales, CHU Caremeau, Nîmes); Pascale Perdezou and Jean Charles Duthé (Service de Pneumologie, CH de Cornouaille—Hôpital Laennec, Quimper); Mathilde Aurore Niault and Virginie Mouton-Rioux (Service d'Hématologie, Maladie Infectieuses, CH Bretagne Sud, Lorient); Jean-Philippe Talarmin and Jean Charles Duthé (Service Médecine Interne, CH de Cornouaille—Hôpital Laennec, Quimper); Mathilde Dupont and Stéphane Natur (Service des Maladies Infectieuses et Tropicales, CH Saint Malo, Saint Malo); and Hikombo Hitoto and Ali Mahamadou Ibrahim (Service de Maladies Infectieuses et Tropicales, Centre Hospitalier Le Mans, Le Mans).

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