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Article Multiple Origins of Virus Persistence during Natural Control of HIV Infection Graphical Abstract Authors Eli A. Boritz, Samuel Darko, Luke Swaszek, ..., Stephen H. Hughes, Steven G. Deeks, Daniel C. Douek Correspondence [email protected] In Brief HIV persistence in people who can spontaneously control the infection involves different mechanisms within distinct anatomic and functional compartments. Highlights d In HIV controllers, both TFH and non-TFH lymph node CD4 T cells contain HIV d Lymph node viruses in both TFH and non-TFH have attributes of active replication d Rare, recently infected cells that produce virus upon stimulation circulate in blood d Archival proviruses predominant in clonally expanded blood cells can be inducible Boritz et al., 2016, Cell 166, 1004–1015 August 11, 2016 Published by Elsevier Inc. http://dx.doi.org/10.1016/j.cell.2016.06.039 Accession Numbers KX390978 KX394124 GSE83482 Article Multiple Origins of Virus Persistence during Natural Control of HIV Infection Eli A. Boritz,1 Samuel Darko,1 Luke Swaszek,1 Gideon Wolf,1 David Wells,2 Xiaolin Wu,2 Amy R. Henry,1 Farida Laboune,1 Jianfei Hu,1 David Ambrozak,3 Marybeth S. Hughes,4 Rebecca Hoh,5 Joseph P. Casazza,3 Alexander Vostal,3 Daniel Bunis,1 Krystelle Nganou-Makamdop,1 James S. Lee,1 Stephen A. Migueles,6 Richard A. Koup,3 Mark Connors,6 Susan Moir,6 Timothy Schacker,8 Frank Maldarelli,7 Stephen H. Hughes,7 Steven G. Deeks,5 and Daniel C. Douek1,* 1Human Immunology Section, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA Biomedical Research, Inc., Frederick National Laboratory for Cancer Research, Frederick, MD 21702, USA 3Immunology Laboratory, Vaccine Research Center, NIAID, NIH, Bethesda, MD 20892, USA 4Thoracic and Gastrointestinal Oncology Branch, NCI, NIH, Bethesda, MD 20892, USA 5Department of Medicine, University of California, San Francisco, San Francisco, CA 94110, USA 6Laboratory of Immunoregulation, NIAID, NIH, Bethesda, MD 20892, USA 7HIV Dynamics and Replication Program, NCI, NIH, Frederick, MD 21702, USA 8Program in HIV Medicine, Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA *Correspondence: [email protected] http://dx.doi.org/10.1016/j.cell.2016.06.039 2Leidos SUMMARY Targeted HIV cure strategies require definition of the mechanisms that maintain the virus. Here, we tracked HIV replication and the persistence of infected CD4 T cells in individuals with natural virologic control by sequencing viruses, T cell receptor genes, HIV integration sites, and cellular transcriptomes. Our results revealed three mechanisms of HIV persistence operating within distinct anatomic and functional compartments. In lymph node, we detected viruses with genetic and transcriptional attributes of active replication in both T follicular helper (TFH) cells and nonTFH memory cells. In blood, we detected inducible proviruses of archival origin among highly differentiated, clonally expanded cells. Linking the lymph node and blood was a small population of circulating cells harboring inducible proviruses of recent origin. Thus, HIV replication in lymphoid tissue, clonal expansion of infected cells, and recirculation of recently infected cells act together to maintain the virus in HIV controllers despite effective antiviral immunity. INTRODUCTION During chronic HIV infection, multiple mechanisms combine to ensure the persistence of virus-infected CD4 T cells despite innate and adaptive antiviral responses. Foremost among these is ongoing virus replication, which by itself can maintain an infected CD4 T cell pool in the absence of antiretroviral therapy (ART) (Ho et al., 1995). Even under ART, however, HIV-infected CD4 T cells remain detectable in blood and lymphoid tissue. This may partly reflect the persistence of memory cells that harbor replicationcompetent proviruses for long periods without expressing them (Chun et al., 1997a, 1997b; Finzi et al., 1997, 1999; Hermankova et al., 2003; Wong et al., 1997). That such cells can show a resting memory phenotype has led to their identification as a latent reservoir and has spurred development of ‘‘shock and kill’’ HIV cure strategies (Archin et al., 2012; Rasmussen et al., 2014; Routy et al., 2012; Søgaard et al., 2015; Spivak et al., 2014). Nevertheless, recent studies have also demonstrated clonal expansion of HIV-infected CD4 T cells under ART (Cohn et al., 2015; Maldarelli et al., 2014; Simonetti et al., 2016; Wagner et al., 2014), raising questions about the intrinsic properties of infected cells in this setting (Kim and Siliciano, 2016). The further characterization of mechanisms by which HIV-infected CD4 T cells persist under different conditions in vivo has thus emerged as a key research goal. Here, we investigated the mechanisms that maintain HIV in vivo through a detailed genetic analysis of virus sequences from CD4 T cell subsets in blood and lymphoid tissue. We chose people with natural control of the virus for this study. These individuals, termed HIV controllers, represent a rare group whose HIV-specific immune responses enable them to control the virus without ART (Migueles and Connors 2015; Walker and Yu, 2013). Despite evidence of ongoing virus replication in HIV controllers not receiving ART (Boufassa et al., 2014; Chun et al., 2013; Fukazawa et al., 2015; Hatano et al., 2013; Mens et al., 2010; O’Connell et al., 2010; Salgado et al., 2010), prior work has shown fewer CD4 T cells containing HIV DNA (Julg et al., 2010) and replication-competent HIV (Blankson et al., 2007) in HIV controllers than in non-controllers. We reasoned that this would allow us to sample more of the total virus population in these individuals and therefore obtain a comprehensive view of the infected CD4 T cell pool. Thus, we used sequencing not only to help infer mechanisms of HIV persistence during natural virologic control, but also to elucidate cellular processes that may maintain the virus both in HIV controllers and in non-controllers. RESULTS Distribution of HIV among Blood CD4 T Cell Subsets in HIV Controllers We enrolled 14 HIV controllers, defined by plasma HIV RNA levels <1,000 copies/ml during chronic infection without ART, 1004 Cell 166, 1004–1015, August 11, 2016 Published by Elsevier Inc. 105 0.313 V907 103 S1270 102 S1349 S1475 101 S1492 100 TCM TTM TEM 104 TN TCM TTM TEM S1495 S1541 0.001 0.079 0.688 0.844 S1548 0.009 0.563 S1788 LIR01 103 LIR02 102 LIR03 101 LIR04 100 Non-controllers -1 10 TN TCM TTM TEM TN TCM TTM TEM 102 101 100 V016 V257 V621 V667 V723 V965 Figure 1. HIV DNA and RNA Levels in Circulating CD4 T Cell Subsets from HIV Controllers (A) HIV DNA copies detected by FCA per 106 TN, TCM, TTM, or TEM cell equivalents. The participant color code at right applies to all figures. Horizontal bars indicate median values in all figures. (B) Numbers of HIV-infected TN, TCM, TTM, and TEM cells per milliliter of blood, calculated by adjusting values in (A) for CD4 counts and proportions of CD4 T cells in each subset. (C) Copies of unspliced (circles) and spliced (diamonds) HIV RNAs in TCM, TTM, and TEM cells from HIV controllers, measured by qRT-PCR and normalized to values in (A). Undetectable values are plotted at the assay’s limit of detection (LOD) with open symbols. Wilcoxon signed-rank test p values are shown. In (A) and (B), all Wilcoxon signed-rank test p values for comparisons between TN and memory subsets in HIV controllers are <0.0001, and MannWhitney p values for comparisons between HIV controllers and non-controllers are <0.001 for all cell subsets. In (C), all Wilcoxon signed-rank test p values for comparisons of unspliced or spliced RNA between subsets are >0.05. See also Figures S1 and S2. infected cell, we also found that the TEM and TTM subsets accounted for most of the infected CD4 T cells in blood in HIV controllers (Figure 1B), with a median 72.6% of total HIV DNA copies in TEM cells and a median 21.2% in TTM cells. Although we hypothesized that this characteristic distribution in HIV controllers reflected greater HIV expression and replication within TEM- and TTM-like cells in vivo, qRT-PCR revealed low or undetectable levels of unspliced and spliced HIV RNA in all CD4 T cell subsets from these individuals (Figure 1C). We also found no correlation across individual HIV controllers between the level of HIV genomic DNA in each subset and the absolute count of each subset in blood (TCM, Spearman r = 0.200, p = 0.492; TTM, r = 0.477, p = 0.087; TEM, r = 0.033, p = 0.916), as might have been expected with ongoing, active replication and resulting cell depletion. Open symbols indicate LOD 10-1 U ns pl Sp . lic ed 10-2 TCM TTM U ns pl Sp . lic ed HIV DNA copies/mL 0.035 HIV controllers V912 B Copies/HIV DNA copy 0.438 0.219 104 TN C 0.025 0.268 U ns pl Sp . lic ed HIV DNA copies/106 cells A TEM as well as six non-controllers with plasma HIV RNA levels >10,000 copies/ml off ART (Table S1). Participants had been documented HIV seropositive for a median of 15.5 years, with a median of 18 years in the controller group (range 4–30) and 6 years in the non-controller group (range 2–29; Mann-Whitney p = 0.1040 for controllers versus non-controllers). Seven of 14 controllers and two of six non-controllers carried protective class I major histocompatibility complex (MHC) alleles including multiple HLA-B57 subtypes and HLA-B2703. Blood CD4 T cell counts were higher in the controllers than in the non-controllers (Mann-Whitney p = 0.0064). We first characterized naive (TN), central memory (TCM), transitional memory (TTM), and effector memory (TEM) CD4 T cells in blood as hosts for the virus in these individuals by quantifying HIV nucleic acids in cell subsets sorted by fluorescence-activated cell sorting (FACS) (Figure S1). In HIV controllers, fluorescence-assisted clonal amplification (FCA; Figure S2) revealed that TEM and TTM cells were more likely to contain HIV DNA ex vivo than were TCM cells (Figure 1A). By adjusting for absolute cell numbers and assuming one copy of HIV DNA per HIV DNA Sequence Analysis in Blood CD4 T Cell Subsets in HIV Controllers To clarify the roles of circulating CD4 TCM, TTM, and TEM cells as hosts for the virus in HIV controllers, we sequenced the single-template PCR products derived by FCA from these cell subsets and plasma virions. Compared to 608 HIV sequences from the non-controllers, the 1,279 sequences from the HIV controllers showed two striking patterns (compare Figures S3 and S4). First, blood CD4 T cell-associated HIV sequences in each HIV controller differed markedly from that individual’s plasma virus sequences. HIV sequences in blood CD4 T cells Cell 166, 1004–1015, August 11, 2016 1005 Figure 2. HIV DNA Sequence Analysis in Circulating CD4 T Cell Subsets from HIV Controllers 1 plasma virus match No plasma virus match 60 (A) Number of distinct HIV DNA sequences detected in blood CD4 T cells from each HIV controller, with number of sequences matching one or more plasma virus in red. (B) Average genetic distances between plasma HIV RNA sequences and HIV DNA sequences in TCM, TTM, or TEM cells in HIV controllers and non-controllers. Mann-Whitney p values are shown. (C) Phylogenetic analysis of all sequences in the study, with labels colored by participant. The arrow shows one clade in which G-to-A hypermutated sequences from multiple participants are intermingled. (D) Genetic compartmentalization between HIV DNA sequences in TCM, TTM, or TEM cells and plasma viruses in HIV controllers and non-controllers, as determined by Slatkin-Maddison testing with Bonferroni correction. Only 13 participants are shown for TCM cells because participant S1270 had no detectable HIV DNA in TCM cells. Fisher’s exact test p values for comparisons between controllers and non-controllers are shown. (E) Normalized Shannon diversities of plasma viruses and HIV DNA sequences in TCM, TTM, and TEM cells from HIV controllers and non-controllers. MannWhitney p values for comparisons between controllers and non-controllers are in black. Wilcoxon signed-rank test p values for comparisons between subsets in HIV controllers are in green. All Wilcoxon signed-rank test p values for comparisons between subsets in non-controllers are >0.05. See also Figures S3 and S4. 40 20 0 V9 1 V9 2 S1 07 2 S1 70 3 S1 49 4 S1 75 4 S1 92 4 S1 95 5 S1 41 5 S1 48 7 LI 88 R0 LI 1 R LI 02 R LI 03 R0 4 Distinct HIV seqs. A Participant ID HIV distance to plasma B 0.7271 0.5704 0.2599 C C C 0.15 0.10 0.05 0.00 NC TCM NC TTM 0.04 LI LI R0 LIR0 R01_ 1_ 32 33 31 1_9 30 22 21 20 19 18 17 13 12 11 3 1LI LILIR R01 LI SSS12 _15 R01 R SSS1SSSS1111112 70 01 _4 LI _5 _8 _7 _1 12 2222277770 _2 _6 _2 _3 001 _5 R801 _6 264879R 5LI 01 RLI 55 01234567841 SSS127S277770000____5 01 _1 _2 SSS1S1SSSS1S1S1S11111122021720_07270_4_7___13456891123340123456789013679012358946123456789 R_1 40016 LI LILIRRLI LI 12122122217222172722777S00000350_14__427 LIR _2 R LI 01 7727070707007070070_010____711171150S 01 LI RR01 01_5 R_3 3 01 R LI _6 01 _3 _409 _4 01 01 R _5 _4 _3 01 _0__8_02_72___34567_81_1721_11276348771326712538049790458124569404151227 01 _4 _8 _5 9172654_4 _5 8_5 _5 3934586057 51438542417401901367851742352863152049_33 0_43 3 136 97 9 S13 1827 71392V _ 1 V912VV_991112225__1V 4 V912_82 39 1V912_62 _2 2V912_119 19 V912_128 V912_115 V912_92 V912_108 V912_54 V912_104 V912_109 V912_77 V912_121 V912_110 9 V912_111 V912_71 1 V912_114 2 V912_116 V912_118 _32 33 4 V912_12 37 35 _102 _90 _100 _88 60 8_52 _87 V912_136 V912_13 8_56 3 8_58 8_46 V912_1 8_10 S1548 45 9 43 8 4 S1548 V912_9 S154 S154 V912_1 S154 V912_ V912_ V912_7 54 57 61 62 64 73 5 38 77 82 2 36 29 8 48_ 105 8_70 4 3 0 8_12 7 3S15 48_ 48_ 48_ 8_11 S15 48_ S154 92 89 86 85 8_68 S154 84 8_10 8_10 80 S15 S15 53 48 47 24 45 48_ S154 44 16 41 15 75 S154 42 S154 48_ 48_1 S15S15 48_23 _33 48_ S15 S15 S15 548 S1 9 S15 _66 _93 _79 _11 _78 548 _76 _71 51 _67 40 39 _55 34 31 548 8_49 S1 8_ 548 548 S1 54 54 S1 8_ 37060 S1 54 10 S1 S18_ 54 8_ 74 5197 43 12 8_ 54 20 S1 35 54 21547 16 8_ 10 63 8_ 8_ 54 8_ 8_ S1 81 S1 69 8_ 54 8_ 54 37 50 54 8_ 54 54 S1 21594304629 691 54 96 S1 23 54 92 S1 83 91 8_ 28 89 8_ 88 11 S1 54 87 18 S1 S1 9876543214001626 86 85 8_ S1 73 8_ 11 96 59 S1 8_ 10 9_ 54 94 54 8_ S1 55___111 13 9_ 54 21 9_ 54 14 8_ 8_ 54 S1 _4 34 S1 9_ 1 5_5 _4 9_ 54 _4 27 _9 8_ S1 34 S1 54 54 34 25 8_ 98 2489 S1 34 49921532976543109867654 S1 _3 34 S1S1 54 49 49 _3 8_ _2 12 15 _545235567901235614 17 S1 S1 8_ 19 54 22 8_ 24 26 S1 27 54 49 13 8_ 13 S1 8_ 95 S1 4949 54 S129511191__4_84_2292111110877665232102987543210832198765432109 S1 _1 54 _7 _4 S 8_ S _1 S13 _2 _9 S1 54 54 8_99 S1 _2 S1 _3 5 _ 1 17 _3453789013579012345 54 09SS 49 S873S13 S1 9849 S1 49 49 913 S1 49 499___56676789012467890123 5214_S9995555____1105_7964857 13 13 404S_2 S154 _1 13 13 _3 SS _3 1133344449999____7889494S59_111114444449999995555_592_15103 S _2 _1 _3 249 SSS13 49 49 49 49 13 49 _1 SSS111111333333444499 1S41 SSSSSSSS111111144449199545_ 13 13 S S13 13 SSSS 13 49 SSS 11 S SSS4S4 138 _5 S SS11 49S V912_8 14 06 V912_35 3 6 7 4 V9 91 12 2_ _3 30 3 2 V912_31 V V912_29 V912_28 V912_7 V912_6 V912_5 V912_4 V912_2 V912_3 V912_67 V912_140 V912_94 V912_107 V912_99 V912_90 V912_88 V912_138 V912_89 V912_75 V912_58 V912_65 V912_95 V912_12 V912_1 V912_1 V912_5 V912_5 V912_1 V912_6 V912_1 V912_ 01 244 902 36 V912_ 13 146 155 V912_ 157 162 168 V912_ 170 171 176 V912 180 V912 181 _190 _196 V912_197 _85 _192 V912 _195 _185 _178 V912 _158 V912 _148 V912 _144 _78 _63 _142 _69 V91 2_61 V91 V91 2_76 V91 2_79 2_11 V91 2_12 V91 2_1 2_1 2_9 V91 2_5 7 3972 2_4 00 V91 V91 03 7 2_4 6 2 2_1 V91 2_3 1 2_6 V91 0 2_1 2 9 86 V91 2_9 2_8 23 2_7 41 3 V912_5 2_6 1 2_5 V9 2 0 V9 6 12_ 5 2 V9 1 12_ 49 0 48 V9 47 12_ 26 25 V9 24 12 23 22 _2 V9V9 21 12 _1 0 12 9 _1 7 6 _7 V9 5 12 _1 1 V9 V9 0_1 12 _8 05 V9 12 7_1 12 V9 _1 12 V9 12 _1 V9 43 65 45 47 12 _1 V9 49 50 12 V9 51 _1 52 53 V9 12 _1 54 56 59 V9 12 _1 60 61 V9 63 12 _1 64 66 67 12_1 69 V912 72 _182 73 12 74 75 77 79 _1 86 87 88 _1 89 91 93 94 98 LIR 01_1 4 91921_21_8V41912_183 0 8V V912_V C NC TEM 55 87_ 4_466 827629827V 7_7__163__14276 37 6666767667V7_7_ 7_3 VVV6V6V66666 25184251310926_99603616362774__43563 VV 77_7__6_15_4V73454V 9536 73_6 6666666666V766776720_6_77_7_6546_4_V VVVV 667_266V6_23766 678901234567 012345678901 VV6V 7V67_6V7_2986954291430825 ____8_9911118901011234562347567120372689067890 V66V 3 8 13 7 81 0 4 00 _ 1 0_2 ___7 _7 35_ 54 6 785575 _8 _2 _6 _8 _4 _1 _9 _55_ _8 278346759_4 _9 _7 _1 6 47 _1 222277777770000000____1 VV7V_643614 75 947 775 93 75 _6 714 75 _6 _7 94 _7 _9 75 775 _4 _1 _2 _8 _2 92_95 _5 S1 14 _7 75 75 14 S14 75 _6 S1 SSSSS111111112222277 V_4676SSS1S 14 S1492_ 75 114 SS14 90 75 91 92S14 89 S 88 87 75 86 14 14 84 2_ 83 SSS 1 6174 SS 82 _7 81 14 80 2_ S75 64 63 62 49 14 61 2_ S14 60 S1492_ 59 58 17 49 75 33 2_ 57 36 34 56 67_ 55 S1 SS14 54 2_ 49 53 52 51 S1 50 5_ 2_ 49 49 48 32 21 44 S1 46 2__47 49 54 51 2 56 49 3_6V103127 S14 _46 _44 S1 _43 47 18 _42 19 20 _41 49 5_ 25 _38 26 S1 _37 27 30 2792_ 492 5_ _33 32 35 _29 37 38 39 S1 45 5_ 48 70V6__7645 47 492 52 S1 55 10 S14 58 47 60 92_ 61 S1 66 5_ 47 68 70 80 35 3 5_ S1 5_5_ 30 45 S14 6_V656 S1 5_ S1 47 68 67 78 S1 57 92_ 5_ 26 15 40 4747 92_ 47 92_ 65 13 92_ 92_ 73 75 23 S14 7 92_ 64 47S1 85 S1 20 6V7 77 S14 S1 92_ 21 1 S14 82_9 4 92_ S1 S14 S14 82_72 92_ S14 47 92_ 5_ 22 S15_ 92_4 50 S14 2_31 92_1 42 S14 2_69 S14 2_76 S14 V6 2_39 2_79 S14 4731 2_28 S1 5_ 2_34 S14 S149 S149 2_36 2_1 S149 S149 2_22 S149 S149 2_74 S149 2_16 475_ S1 _71 S149 2_10 2_6 _2 _3 S149 _5 _12 72 _17 S1492 111 S147 06 S1492 _24 10 _25 66 17 70 S1548_3 S1 S1548_ 27 S1492 S1548_12 S1492_ S1548_1 92_19 S1548_1 809 LIR04_1 LIR01_ 6 7 S1548_1 S1475_ S1270_13 S1270_13 LIR04_106 V965_116 LIR04_170 LIR04_164 S1495_145 S1475_69 S1475_94 S1475_78 LIR01_52 LIR04_25 LIR03_38 LIR04_168 LIR04_31 LIR03_182 LIR04_163 LIR03_180 LIR03_36 LIR03_69 LIR03_78 V016_74 V016_127 V016_52 V016_128 V016_89 V016_91 LIR02_145 LIR02_155 LIR02_110 LIR02_98 LIR02_78 LIR02_48 LIR02_47 LIR02_22 LIR02_111 LIR02_215 LIR02_118 LIR02_144 LIR02_70 LIR02_65 LIR02_136 LIR02_43 LIR02_44 LIR02_45 LIR02_91 LIR02_194 LIR02_53 LIR02_54 LIR02_94 LIR02_108 LIR02_80 LIR02_28 LIR02_93 LIR02_10 LIR02_21 LIR02_11 LIR02_85 LIR02_6 904 LIR02_2 631 LIR02_8 5 LIR02_1 LIR02_1 LIR02_1 LIR02_ LIR02_ 792 60 LIR02_ 48 152 75 LIR02_ 161 LIR02 130 LIR02_ LIR02 LIR02 LIR02 127 _86 LIR02 31 _137 LIR02 _153 _96 _197 LIR02 LIR02 _141 LIR02 _101 LIR0 _19 _73 LIR0 _5 _7 2_14 _105 2_21 2_32 2_46 LIR0 2_88 2_11 LIR0 LIR0 2_15 LIR0 2_19 LIR0 LIR 2_21 LIR LIR0 2_99 2_90 2 2_2 2_14 LIR 4 2_1 02_ 9 02_ 2_5 2_1 18 20 13 61 02_ 63 56 95 74 02_11 7 04 84 114 95 119 140 LIR 196 LIR LIR LIR LIR 02_ LIR LIR 02_ 02_ LIR LIR 02_ 02_ LIR 142 02_ LIR LIR 02_ 51 192 LIR 17 162 02_ LIR 71 02_ 116 02_ 11 02_ LIR 27 169 206 LIR 02 178 _1 LIR 23 12102_ 128 LIR LIR 02_ _7 212 97 _5 02 16 _2 LIR 02 LIR 24 LIR 02 _3 02_26 5 _6 02 9 02 LIR 0 LIR LIR LIR _1 _1 02_ _7 4 02 6 _1 183 LIR 02 _7 74 2 LIR _13 _1 106 02 02 _2 _2 02 02 80 _7 619 _6 LIR LI 07 39 LIR 02 _1 07 _1 _6 _1 LI 7 LILILI _8 R0 02 _1 147 03 00 LI 02 _2 2 R0 1 35 LI 3 22 R0 9 02 64 _1 LI R0 2_ 93 R0 R0 03 _1 14 _2 LIR LILI 2_ LI R LI R0 _2 R 90 2_ 17 2_ 13 20 LI 2_ 02 R0 02 2_ 25 02 RR0 2_ 30 2_ 45 57 LI 58 1 59 2_ 21 R 60 49 02LI 62 LI 12 _4 _1 64 10 _1 67 2_ 02 _2 R 68 14 15 715 02 R 20 98 375 _1 8 _9 221 59 _8 _1 R 02 _3 8109 LILI 02 _4 57 _1 R81 LI _1 RLILI 02 20987650 09 29 R_1 33 LI 76 84 85 02 86 LI 87 88 0291 _1 89 R R R02 VR _1 56 02 _1 82 V62 02 02 25 66V 34 _3 _4 32 _5 _1 LI_6 VVV66VVV6V626VV _1 21R 62121_2_149 43 1V 67 212626211_ 68 902 70 77 6221VV __66616_22_2161_11212_19_67_40915 _1 VVVV6VV6VV2616V61V 2V226_11711073411__2_7151426_32432 79 6V22621V 61221_16_61_6_212_2_311_1_2111185_4321401753128621723057 LIR 1V12_890112970__0479887172097 02LI 3 6 5 6 8 _1 0 1 V 0 R66 VVV6 VVVV6V66260819 02RLI LI _1 R38 VVVVV66626V2V6V6V22626221_16 02 02 _1_1 _2 VVVVV666V66V66V266V2V26221611221V116__16V_62_26321621121211_2_1_1_1___11723653452309 LIR LI 72 13 6222211121216_V1_221V_912_6_41494120218__1_1_822_012865484 02 2602 _1 1V1____97V6_V_6161625_0311203194_127851563 _1 65 73 58 6_2821191041263262_261491_9 036 13_952 211_7_3120 110 _1623 68 52 SS1 SS S14 SS11 SS14 SSSSSS1S11SSS4SSS11111S494S49511SSS11S441441999 14 S1S S1141414149 444995_4149149455_ S14 95 S SS S_2 SSSS95 14 14 S S95 14 14 1158 194SSSSSSSS1111144944499594459955_95_959_955_15555____49_215496955795__9_55__121_25043 495 14 _1 S 14 14 SSSS 95 14 495 S 14 14 95 SS 14 14 14 9_1 14 5_1 9_1151464S4S11444999955_1_2_1223_728_5011234556347890123456783415_268_721504986309 S 17 95 95 14 95 95 _1 5_1 95 _3 14 95 95 95 95 _90 _2 _1 _2 _1 _1 95 LIR 86 1432123_4456789911955415439__99555_____34789023435917234562712945689017 60171220558046 _2 460 _2 95 LIR _2 _1 SS _2 _1 57 03 05 10 88 S 18 30 14 _1 LIR 31 03_2 34 S1 42 85 23 14680 03 38 _8 44 S LIR 53 37 S1 14 S 7 03 40 85 LIR 95 14 14 S1 S1 00 S14 03 49 S1 16 S1 LIR 15 _274 8 6_9259653_4_125346789034567890123890 S1 95 49 S1 14 S1 03 S1 13 14 12 LIR 11 _2 _1 95 49 95 10 S1 5_ 95 49 S1 08 03 49 49 LIR 84 S1 49 _2 _1 5_ 72 S1 49 49 69 49 95 LIR 03 68 S1 67 5_ _2 31 S1 _1 58 _2 18 49 _9 5_ 5_ _1 LIR 49 57 5_ 5_ 03 51 18 62 49 49 55 5_ 11 42 S1 _1 44 49 49 LIR 36 5_ 5_ 43 _9 49 39 03 25 38 22 19 05 03_ LIR 20 5_ 2 37 _1 59 49 18 81 30 5_ 28 24 93 27 72 LIR 90 71 26 70 5_ 03_ 25 5_ 50 98 36 55_ 24 289 6532492 35 19 LIR 119 23 22 756 117 22 20 11 23 11 114 5_ 1 26 18 03_ 110 17 52 23 109 LIR 24 107 03_ 106 104 25 LIR 8613 102 24 37 0 100 1 03_ 4124 3 LIR 5 99 6 8 97 0 96 9 03_ 93 LIR 92 91 90 03_ LIR 89 88 87 85 LIR 03_ 84 83 LIR0 82 81 03_ 80 LIR0 79 76 72 3_6 68 LIR0 67 3_5 3_4 6 LIR0 3_45 5 3_41 4 3_37 1 3_31 LIR0 9 3_30 3_27 LIR0 LIR0 3_24 LIR0 3_19 3_18 LIR0 LIR03 LIR03 3_11 3_10 3_4 3_3 LIR03 3_63 3 15 _108 LIR03 _86 _171 LIR03 LIR03 _112 _209 LIR03 _155 _77 LIR03_ _152 _134 LIR03_ _136 LIR03_ _116 LIR03_ 150 LIR03_ 145 146 LIR03_ 103 95 16 LIR03_1 132 140 LIR03_1 73 48 LIR03_15 LIR03_94 41 47 LIR03_73 35 LIR03_75 LIR03_50 LIR03_48 LIR03_42 6 LIR03_98 LIR03_133 LIR03_111 LIR03_142 LIR03_23 LIR03_207 LIR03_32 LIR03_71 LIR03_105 LIR03_74 LIR03_131 LIR03_170 LIR03_46 LIR03_43 LIR03_153 LIR03_28 LIR03_206 LIR03_186 LIR03_22 LIR03_33 LIR03_191 LIR03_165 LIR03_34 LIR03_15 LIR03_40 LIR03_5 LIR03_8 LIR03_11 LIR03_44 LIR03_52 LIR03_53 LIR03_54 LIR03_55 LIR03_59 LIR03_121 LIR03_122 LIR03_162 LIR03_166 LIR03_187 LIR03_189 LIR03_190 LIR03_192 LIR03_193 LIR03_194 LIR03_196 9 10 LIR03_197 LIR03_200 LIR03_203 LIR03_205 29 LIR03_204 LIR03_62 9 LIR03_15 LIR03_188 LIR03_70 18 LIR03_25 LIR03_2 13 LIR03_7 56 57 LIR03_6 60 LIR03_1 LIR03_ 202 LIR03_ 61 _163 _35 _179 _164 _12 _14 71 LIR03_ _195 _198 3_17 LIR03_ _201 3_20 LIR03_ _199 3_21 LIR03 0 3_26 LIR03 3_29 3_17 LIR03 LIR03 LIR03 3_39 _1 LIR0 3_47 3_58 LIR03 3_16 LIR0 LIR0 LIR03 LIR0 16 0.044 S17 S SS1 S1 S S 17S S1 17 S178 78 17_5 88 S1 88 78 S1 88 78 8_ 882356_3 _4 78 _3 S1 S1 _3 S178 _2 8_S1 _6 8_ S1 _7 78 8_ S1 33 788_ 50 8_ 78 78 S1 S1 S178 77 5789_2921 78 583416 8_ 73 8_20 S1 78 8_ S1 78 8_ S1 78 S1 8_ 8_ 78 V9 60 21 S1 78 18 69 8_ 78 S1 11 61 V9 8_ 78 62 8_ 58 V9 78 57 S113 8_ 54 07 46 S1 44 78 8_ 41 8_ 40 V9 78 68 07 34 V9 30 8_ 26 07 59 22 8_ _1 76 7878 19 V9 67 10 17 42 V9 15 49 8_ _1 07 51 47 07 38 _9 18 74 V907_ 24 _5 16 V9 72 23 8_37 V9 07 71 12 V9 70 07 8_ 65 22 _1 V9 43 66 V9 _1 468_ V9 3 _9 07 _1 07 0 07 _1 V9 V9 36 1 07 _4 07 00 07 _3 _9 01 _3 124 V9 _1 _8 V9 07_ 4 4514 07_ V9 _2 607_ _7 _1 V9 5 V90 195 V9 19 V9 07_ 07_ V90 V90 07_ 21 90 98 07_ V90 07_ V907_71 V90 V90 7_1 993 HXB2 513 7_1 7_1 V907 _74 7_9 _73 615 7_4 7_1 2 20 23 _47 V907 02 17 V907_2 V907_23 V90 _45 _44 V90 7V90 _43 V907 V90 _42 _39 7_3 V90 _37 7_1 V90 _34 9 V90 7_7 7_6 V90 7_3 7_6 7_2 V907_40 7_3 7_4 866 V90 7_3 V90 7_7 7_1 23 4 V907 1003 V90 9 V90 7_1 072 7_1 V90 7_4 7_3 7_27 _19 7_28 7_25 06 7_18 8 V907_21 V907_ _20 V907_ 22 26 51 52 V907_ 53 V907_5 54 55 V907_6 56 57 58 9 V907_65 0 V907_66 1 V907_67 2 V907_75 3 4 V907_76 V907_77 V907_78 V907_79 V907_80 V907_81 V907_82 V907_83 V907_84 V907_85 V907_86 V907_87 V907_88 V907_89 V016_122 V907_91 V V907_92 0110 1661 6__6 V907_115 _18_ 1184 021 7 V907_107 8 3 0V VV016_100 0V V 01 16 6_ _6 48 0_ 18 64 _4 79 0 2 VV 0V 1 6 S1 54 SS1S1_ 54 1S_1 SSSS115S12885 5524S SSSSSS11111155555544414541S514S1_411155S1LIRL 0LIR4 11_5SS111115555544441111____11_780_41415 LLLIR S1SS S 4 4 IR LLIR SSS1S1S IR IR 0_0 15S151S IR S15155115SS553S1141925515554_44448111111_1_____5_566677347567890123456789039118_605_1L51IR 8_40003444041400_43_441_71 SS1S 1S5551414541551411_4514_4_144_114114_1S _1151415571__333480280136012 15 SSS15 ___11__130543281 15 S 441144_191293__115365__22971_12_924545184320_14_4762_1123641990134567 15 41 15 41 SSS15 15 41 _21_65187643 77609685542931746 _904 _5 4141 _8 41 _9 9 _1_9 6 _1 00987421098724 _1 01 02 03 04 11 12 13 17 14 S1 10 S7S11 5544 11__ 1100 568 1_ 54 S1 # of participants D 94583866 731 1 ___98543_21_6452234531019_7__18717656 _8 2 222111212_1_182911_6271_2121_11 57 2322 VVV6V66V66V226266V1612V_V62V166 _57_V V 5725 VV6V V2V 4 _5 71047247 57 V2 __57432_182_1226305 22 55577575_7_1671825_1_185913_1579763_421846_254039367641 45 VVV2V2V5275227527_752_75_4752_75_2775__7657_7686_71_70_5 5677_4_36 2VV 2725_724528_538 3V V225V225V 5_532172_5 VVV2VVVV 2V725V25V7_25977V55_721397_05483293747_565_967_17436V 5_077_707623V V7525V5_2275575763752_57_72_7_752V7_5_572_675_277V 527__27 V5V 222V 2VV 2252V 2 540916 7 V5_2V918653 13 40 39 V2VVVVV2VV 3 38 35 28 _97 24 37 22 47 1_865 17 80 7 _1 11 98 10 842 4531 45 14 15 10 7V9 655_ 8 5210 43 96 5_ 5_ 5_ 16 99 3 65 34 19 62 311 5_ 90 V9 65 65 5_ 7_7 36 292 _5 5_ 5_ 96 10 65_1 5_ _8 VVV9V 96 96 5_ V9 _2 V965 912 96 5_ 5_ 3_7 8 21 72 V9 _1 96 96 265 65 _1 85 _2 5_ 6112 5_ _5 96 48V9 60 _43 87_1 96 65 _3 4 V96 65 5_ _9 _8 30 09 96 515 83 _7 96 8_8 16 5_1 VV _4 V9 0 26_3 65 469 41 7 _8065 65 V9 5 VVV _8 _4 767 _4 _7 7 _6 V9 35 _1 V9 _7 _6 9 V0 _2 65 _1 _2 _5 30 _1 65 _6 16_ _1 _2 _8 _3 46 65 _5 V96 VV96 106 V9 _9 _70_1 6_60 _8 7 96 65 V9 65 65 65 _6 6_9 V9 _5 82 65 65 _7 16_ 6_4 V _3 12 65 65 1 V0 65 65 65 16 65 65 65 V9 109 65 V9 6_2 64 16_ 16_ 65 V9 V01 6 V9 65 V0 65 79 V9 V9 V9 16_ 65 65 4 25 V9 6_2 6_1 _5 V9 5V9 6V0 9 V9 V01 V9 V0 V0 3 V9 87 16_ 6_1 16_ V9 V9 V9 V9V9 V9 V0 02 4 6_1 V01 6_2 _7 00 V9 9_6 0 V01 65 7 04 V9 05 3_7 V0 8 V0 6_2 6_7 V01 23 9_1 8 _1 01 _6 16_5V016_ V01 65 _4 6_3 65 _6 1 _1 V9 6_1 _6 V01 9 6_4 0021 _5 _5 65 65 _1 V01 6_6 1 V9 V9 65 65 14 6_1 65 V01 6_8 1 V0 65 65 V01 6_5 V9 6_73 V9 6_1 V01 V9 V9 V9 6_2 V01 V01 V9 6_11 V9 _42 654_9 6_32 V01 6_68 _58 _77 _3 _95 V016 _15 V96_5 V01 V01 _93 65 V016 _81 V016 V016 V016 65_2 _59 _65_108 V016 _40 V016 _69 _54 V9V9 V016 V016 111 V016 V016 V016 V016 _71 119 V016_ 75 36 120 53 V016 101 118 V016_ 17 V016_ 28 9 V016_ V016_ 17 V016_ V016_9 27 V016_1 V016_5 636 V016_9 V016_6 V016_7 V016_8 V016_10 V016_70 V016_90 V016_33 V016_63 V016_94 V016_55 V016_96 V016_8 V016_50 V016_115 V016_22 V016_34 V016_10 V016_31 V016_45 V016_102 V016_92 V016_116 V016_76 V016_30 V016_21 101616_6_6 VV016_113 41_1 8 0V 9 010 V0V0 55244 184 V 8 3 1061_6_3 3_94 0 3_91 2 3_87 3 3_85 V72 3_8 3_7 8 5 3_5 V72 1 3_4 0 3_3 8 V72 3 3_3 763 432 V72 3_2 V72 3_5 3_3 3_1 3_4 10 V72 1 2 V72 3_2 V72 7 3_7 3_6 9 3_8 3_1 3_2 3_1 33 56 V72 V72 V72 61 3_2 V72 62 V72 74 V72 95 23_ 82 65 V72 66 23_ V7 45 6_7 _7 23_ _1 23_ _1 897 V7 _4 23 1 23_ 69 _4 473 V7 V7 23 _2 90 _8 23 23 40 _7 V7 V7 _8 6 23 _2 5_6 23 _2 23 _4 V7 98_6 5_9 V7 _6 _1 23 31 V7V7 23 8783747 V7 _9 V7 23 _7 _9 _2 23 _1 _3 _1 23 23 V7 V7 _4 _1 _6 491 V7 23 2_7 23 23 _3 23 _8 _6 V7 _3 _4 V7 23 2 0_5 V7 23 _5 _8 7654985 V7 V7 23 23 23 99_1 9 0 V7 79 23 V7 23 _5 54 V7 V7 45 V7 2323 43 _6 2323 _1 23 42 23 41 _8 _6 V7 36 V7 _5 V7 _9 _3 12_4 31 _1 _9 8_4 29 0_9 23 V7 28 V7 V7 V7 23 V7 23 V7 16871421907854 _1 23 623 V7 23 23 _4 23 238_5 8V7 23 04 23 _1 V7 _8 V7 V7 _7 _8 23 04 _1_9 V7 R _7 V7 V7 _9 V7 23 V7 07V7 23 V7_7 _3 04 23 R _2 _5 23 LI V7 _1 832127 0404 _6 78420956905 04 R _5 V7V7 _1 23_5 _6 04 V7V7 RR R LI 23 67 V723 LI 30 _5 04 04 _9 _8 R _2 LILI _5 00 V7 LI _6 04 _1 _7 04 20 R 3573854172 R _5 _1 LI _1 RR04 04 04 51 R 161411 LILI 04 LI R 39 235_1 04 R _1_0_8 04 04 82248_3864 5 04 R04 3 _1 RR 1204 4_4_1 LILI V7_4 R LI LI R 23 LI 040IR 41__0846173_440035685401 03 47_253125621 52932_7336104086 04 LI LIR LI _8 RR _3 LILI V7 LI IR 0IR LLIR 4000_4_4_01_4_714_52763167064_640637118_23828590334206_044814__1161_937491784716489514892456170170_0810244740__404_41_ LI04 0L0L04IR LIR 45310IR 0IR0 101_145_45380_52540__4_14_0_IR LIR LLLIR IR L0IR 140IR 040 IR 0_440414000__440441064___480__1IR IR LIR L IR IR 44L71LL16LIR 404_00__44_0441_00_024L4000IR 4LL__IR L92IR 0IRIR 11L96IR L0L4IR IR IR LLLIR L00IR L004IR 692520IR IRIR054044_4__L IR LIR LIRLLLLLLIR LIR LIR 0LL40LIR IR IR4__9314L_IR IR LLLIR LIR 06400 IR LL_IR 9IR 14410 LLLIR LIR 0IR 6 0 _L1IR _ IR 044LL 2_0_6L5143 0LL144IR IR0 IR 4L_0IR LLIR L0IR 7 LIR_L7 04 LIR 0.157 0.002 12 Compart. v. plas. Not compart. v. plas. 8 4 0 C NC C NC C NC TCM TTM TEM 0.0012 E 0.3396 <0.0001 0.0001 0.0015 0.0002 C C 0.1786 HIV diversity 1.0 0.5 0.0 C NC TCM NC TTM NC TEM 1006 Cell 166, 1004–1015, August 11, 2016 C NC Plasma from HIV controllers rarely matched plasma viruses (Figure 2A). Although genetic distances among HIV sequences might be expected to be greater in non-controllers than in controllers due to higher levels of virus replication in non-controllers, the genetic distances between cell-associated virus DNA sequences and plasma viruses in controllers were as great as those in non-controllers (Figure 2B). The large genetic distances observed in controllers were not due to dual infections because sequences from all study participants were genetically clustered by participant (Figure 2C). Moreover, whereas HIV DNA sequences in blood cells from non-controllers were genetically intermingled with plasma viruses, HIV DNA sequences in blood cells from controllers were frequently compartmentalized from plasma viruses (Figure 2D). This was especially true in the TEM subset, where compartmentalization from plasma viruses was seen in 13/14 controllers but only in one of six noncontrollers. In addition to genetic divergence from plasma viruses, HIV DNA sequences in blood cells from controllers showed large clusters of identical sequences not commonly seen in non-controllers. As measured by normalized Shannon diversity, which increases with the proportion of unique sequences in a population, HIV DNA sequences were less diverse in controllers than in noncontrollers within each CD4 T cell subset (Figure 2E). This was true despite similar levels of diversity in plasma viruses from the two groups (Figure 2E). Clusters of identical sequences were particularly prominent in TEM cells from controllers, with lower HIV diversity in TEM cells than in TTM or TCM cells (Figure 2E). Diversity of HIV DNA sequences in non-controllers was similar among TCM, TTM, and TEM subsets (Figure 2E). Thus, among memory CD4 T cell subsets in HIV controllers, the TEM subset accounted for most of the infected cells in blood but generally harbored proviruses that were transcriptionally quiescent, markedly distinct from plasma viruses, and rich in clusters of identical sequences. 0.0001 A Figure 3. Clonality of Cells and HIV DNA Sequences in Circulating CD4 T Cell Subsets from HIV Controllers E 0.0001 0.0001 TCR diversity 1.0 NSD1 (88.8%) 0.5 0.0 TCM B TTM TEM 0.2188 0.0007 0.0001 0.6875 0.0001 0.2188 HIV distance to MRCA 0.14 0.12 0.10 MED26 (2.6%) 0.05 0.00 Plas. TCM TTM TEM Controllers Non-controllers 0.05 F C 15 1 plasma virus match No plasma virus match POLM (95.5%) 10 5 0 V9 1 V9 2 S1 07 2 S1 70 3 S1 49 4 S1 75 4 S1 92 4 S1 95 5 S1 41 5 S1 48 7 LI 88 R0 LI 1 R LI 02 R LI 03 R0 4 HIV seq. clusters Plas. TCM TTM TEM Participant ID HIV seq. cluster distance to plasma D 0.15 r = 0.4190 P = <0.0001 (A) Normalized Shannon diversities of T cell receptor beta (TCRB) sequences from TCM, TTM, and TEM cells in HIV controllers. Wilcoxon signed-rank test p values are shown. (B) Average genetic distances of plasma virus and TCM, TTM, and TEM cell-associated HIV DNA sequences from most recent common ancestral (MRCA) sequences in HIV controllers and noncontrollers. Wilcoxon signed-rank test p values are shown. (C) Number of recurrent HIV DNA sequences detected in circulating CD4 T cells of each HIV controller, with number of distinct sequences matching one or more plasma virus sequence in red. (D) Correlation between the abundance in blood of each recurrent HIV DNA sequence in circulating CD4 T cells from HIV controllers (x axis) and the average genetic distance of that sequence to plasma viruses (y axis). Each symbol represents one distinct sequence and is colored by participant. Spearman r and p values are shown. (E and F) HIV DNA sequences associated with expanded cellular clones in HIV controllers V907 (E) and S1349 (F), illustrated using dashed borders within phylogenetic trees. Gene locus names corresponding to the HIV integration sites in these expanded clones are shown. Each number in parentheses represents the percentage of all copies of HIV DNA in blood CD4 T cells from the individual deriving from the indicated HIV integrant. Sequences from participant V907 showing G-to-A hypermutation and associated with expanded cellular clones are shown as detached branches; other hypermutated sequences are omitted for clarity. The large sequence cluster in participant S1349 is shown separated from the tree for ease of viewing; an arrowhead shows the position of this sequence on the tree. See also Table S2. 0.10 0.02 0.05 0.00 10-1 100 101 102 103 HIV seq. cluster copies/mL blood HIV Clonality in Blood CD4 T Cell Subsets from HIV Controllers Based on these results, we hypothesized that each cluster of identical HIV DNA sequences represented one CD4 T cell clone harboring a single HIV provirus amplified in vivo through cell proliferation. We also hypothesized that the TEM subset might be enriched for recurrent HIV sequences because memory CD4 T cells undergoing clonal expansion in vivo tend to differentiate into TEM cells. To test this, we first compared the clonotypic diversity of the three memory CD4 T cell subsets using T cell receptor beta chain (TCRB) deep sequencing. We found that TCRB diversity decreased progressively along the putative pathway of differentiation from TCM to TTM to TEM (Figure 3A), consistent with the hypothesis. We evaluated the alternative explanation for clusters of identical HIV DNA sequences in blood cells, whereby sequences closely related to the actively replicating virus pool and matching over the region we sequenced might accumulate through bursts of virus replication. Using plasma viruses as a genetic surrogate for actively replicating viruses, we observed the opposite pattern. In general, HIV sequences from blood TCM, TTM, and TEM cells in HIV controllers were ancestral to plasma viruses (Figure 3B). Sequences occurring at least twice rarely matched any plasma virus sequence (Figure 3C). Moreover, recurrent sequences that accounted for higher copy numbers in blood (i.e., occurred in Plasma TCM TTM TEM Cell 166, 1004–1015, August 11, 2016 1007 TEM A 14 9 3 10 28 TTM 10 25 TCM TTM TCM B TEM CXCR5 + + - - - - - - CCR6 - + - + - + - - + CD57 - - - - - - + - V912_9 V912_25 V912_26 V912_47 V907_25 V907_16 S1475_18 S1492_23 S1492_42 S1495_30 S1495_14 S1495_32 S1495_43 S1548_44 S1548_24 S1548_31 S1548_28 S1548_34 S1548_22 S1548_48 S1548_43 HIV DNA copies/mL C 0.5431 0.0002 0.0256 <00001 104 more cells) were genetically more distant from plasma viruses (Figure 3D), with average genetic distances to plasma viruses frequently >5%. This suggested greater expansion among older HIV-infected CD4 T cell clones in HIV controllers, which was not apparent in sequences from non-controllers (Spearman r = 0.2706, p = 0.2117; data not shown). Therefore, recurrent HIV DNA sequences in blood CD4 T cells from HIV controllers had genetic attributes of expanded cellular clones rather than virus replicative bursts. We used HIV integration site analysis to prove the presence of clonally expanded, HIV-infected cells in blood from HIV controllers. Although too few infected cells to permit this analysis were available from some participants, we identified two HIV integration sites in clonally expanded cells for participant V907 and one such site for participant S1349. We then linked recurrent env sequences with their integration sites by PCR from the forward env primer to the integration site. Sequencing the env portions of these amplicons confirmed that clusters of identical sequences detected by FCA arose from expanded CD4 T cell clones (Figures 3E and 3F). These clones accounted for 91.3% and 95.5% of all amplifiable env DNA copies in blood CD4 T cells from these participants. Therefore, integration site analysis in HIV controllers confirmed both the presence of clonally expanded, HIV-infected cells and the predominance of these cells within the circulating, HIV-infected CD4 T cell pool. We next characterized further the recurrent HIV DNA sequences detected in blood cells within the full HIV controller cohort. Excluding the six of 105 such sequences with <1% genetic distance from plasma viruses as possible replicative bursts, we analyzed the remaining 99 as coming from presumptive expanded clones (Table S2). These sequences were relatively abundant in blood, together accounting for between 32.7% and 96.8% of HIV DNA sequences in circulating CD4 T cells from each individual, at levels ranging between 0.32 and 1368.61 copies/ml for each sequence. Twenty-two of these sequences (22.2%) contained one or more stop codon associated with G-to-A hypermutation, and an additional sequence contained a frameshift in gp120. The remaining 76 sequences (76.8%) contained neither stop codons nor frameshifts over the region of env sequenced (HXB2 bases 7011–7502). We found 32 (32.3%) of these sequences in more than one memory CD4 T cell subset (Figure 4A) and many of these in multiple subsets within TCM, TTM, and TEM defined by the markers CCR6, CXCR5, and CD57 (Figure 4B). Therefore, confirmed and 103 102 1 10 100 C NC Repeat HM C NC Singlet HM C NC Repeat no mut. C NC Singlet no mut. Figure 4. Subset Distribution and Genetic Attributes of HIV DNA Sequences in Circulating CD4 T Cells (A) Subset distribution of HIV sequences from presumptive expanded CD4 T cell clones in HIV controllers. 1008 Cell 166, 1004–1015, August 11, 2016 (B) Distribution of HIV DNA sequences from presumptive expanded clones across subsets within TCM, TTM, and TEM populations defined by CXCR5, CCR6, and CD57. Each row represents one sequence, labeled by participant and a unique number. Yellow indicates that the sequence was detected in the given subset. Italics indicate G-to-A hypermutated sequences. (C) Levels of HIV DNA sequences in circulating CD4 T cells from HIV controllers and non-controllers categorized according to the number of occurrences (Repeat, >1 occurrence; Singlet, one occurrence) and the presence or absence of G-to-A hypermutation (HM, hypermutation detected; no mut., no lethal genetic defect detected). To allow display of these wide-ranging values—including several values of zero—on a logarithmic scale, each plotted value represents the measured value + 1. Mann-Whitney p values are shown. Sequences with lethal genetic defects other than hypermutation were rarely detected. See also Table S2. presumptive HIV-infected CD4 T cell clones in blood from HIV controllers showed evidence of in vivo maturation and functional differentiation. Finally, although repeated and hypermutated sequences accounted for a strikingly high proportion of all HIV DNA copies in blood CD4 T cells from HIV controllers, equal or higher absolute numbers of these sequences were detected in blood CD4 T cells from non-controllers (Figure 4C). Inducible Proviruses in Blood CD4 T Cells from HIV Controllers Because some expanded HIV DNA sequences may have been lethally mutated outside the region we sequenced, we tested whether CD4 T cells harboring these sequences could produce virions by stimulating them through the T cell receptor and then sequencing RNA from virions released in culture. Although these experiments revealed no virion production from most presumptive expanded clones (Figure S5, open bars), we recovered virion RNA matching two recurrent DNA sequences from TEM cells in participant S1270 (Figure S5, filled bars; Figure 5A, x-y plots, filled circles). One of these DNA sequences was highly expanded, divergent from plasma viruses, and close to the most recent common ancestor (MRCA), consistent with an expanded clone carrying an archival provirus. The other appeared to be more recent (arrowhead) but contained a frameshift in gp120. Importantly, while abundant virion production was again detected from cells harboring the latter sequence in a repeat experiment, this was not the case for cells harboring the former sequence, even though this sequence occurred within many more cells in the culture (Figure 5B). Therefore, although virion production was occasionally inducible from proviruses bearing genetic signatures of expanded cellular clones, the inducibility of a given provirus was not always uniform among the cells that harbored it. Importantly, we also detected a second class of inducible viruses with a distinct genetic signature in these experiments. In participants S1495, V912, and S1349, we found multiple induced viruses that had not been detected as recurrent DNA sequences in separate aliquots of the same cell populations (stars in Figure 5A, x-y plots). All but one of these ‘‘unique induced’’ viruses were closely related to plasma viruses and divergent from ancestral sequences, suggesting recent in vivo infection of the cells producing them. Assuming that recurrent virion RNA copies of unique induced sequences represented progeny virions from one cell, we calculated that cells harboring these proviruses accounted for 0.19%–1.48% of all HIV-infected, circulating memory CD4 T cells from the individuals in whom they were detected (Figure 5A, hemispheres). Of note, unique induced viruses were detected in all circulating memory CD4 T cell subsets and were found mainly in the two HIV controllers with the highest plasma viremia. Overall, therefore, inducible proviruses in circulating memory CD4 T cells from HIV controllers fell into two distinct categories: expanded, archival proviruses in TEM cells, and proviruses of recent origin in rare TCM, TTM, and TEM cells. Lymphoid Tissue Viruses in HIV Controllers To help determine the origin of circulating CD4 T cells harboring unique induced viruses in HIV controllers, we characterized HIV in lymph node (LN) from four study participants (Table S3). Three of these four had detectable plasma viremia and showed high levels of HIV DNA in LN CD4 T cells. In these viremic HIV controllers, the highest levels of HIV DNA were observed in germinal center (GC) and non-germinal center (non-GC) TFH cells (Figure 6A). These TFH subsets accounted for 73.1%–86.3% of the infected CD4 T cells in LN (Figure 6D). However, HIV-infected cells were also detected in LN TCM, CD57+, and TEM subsets, at levels that were higher than in TCM, TTM, and TEM cells from blood (Figure 6A). HIV DNA in both follicular and non-follicular LN memory CD4 T cells was also associated with higher HIV RNA levels than was HIV DNA in blood cells (Figures 6B and 6C). Detection of cell-associated HIV RNA by in situ hybridization using intact LN tissue samples confirmed that HIV RNA+ LN cells were present both inside and outside follicles in these individuals (Figure 6E). To clarify the relationship of HIV in TFH and non-TFH LN cells to viruses in blood cells and plasma, we analyzed HIV DNA sequences in LN cell subsets. We found that sequences from GC and non-GC TFH cells in the three viremic controllers (n = 113 sequences) were more closely related to plasma viruses than were HIV DNA sequences from blood cells (Figure 7A, left panels). In two participants, sequences in TFH cells were also significantly further from the MRCA than were blood cell-associated sequences. Although recurrent HIV DNA sequences were observed in TFH cells, these sequences too were closely related to plasma viruses and divergent from ancestral sequences, thus distinguishing them from recurrent HIV DNA sequences in blood cells. Importantly, analysis of 145 additional sequences from non-TFH TCM and TEM LN cells in these individuals showed a close relationship with viruses in TFH cells (Figure 7A, right panels, green symbols). By contrast, the sequences from circulating TCM, TTM, and TEM cells were significantly more distant from viruses in TFH cells (Figure 7A, right panels, red symbols). Thus, among CD4 T cells of a given maturation phenotype, we identified sharp distinctions in the genetic characteristics and transcriptional activity of cell-associated HIV populations detected in different anatomic sites. Whole-transcriptome sequencing and principal component analysis (PCA) of cell subsets from these sites revealed that LN TEM cells had a transcriptional profile that was related to that of TFH cells and distinct from that of circulating CD4 TEM cells (Figure 7B). Finally, in one HIV controller with undetectable plasma viremia, levels of LN cell-associated HIV DNA were nearly undetectable (Table S3). In this individual, only a single, G-to-A-hypermutated copy of HIV was detected among all LN CD4 T cells studied, with no HIV DNA found in >2 3 104 TFH and GC TFH (Figure S6I). Flow cytometry confirmed the expected distribution of LN CD4 T cells among TN, TFH, and other memory subsets in this individual (Figures S6A–S6H). Furthermore, plasma virus sequences from this individual showed a relatively high average intragroup pairwise genetic distance (Figure S6J) and an average divergence from MRCA that was the highest out of all 20 participants (Figure S6K). Therefore, HIV-infected CD4 T cells were very rare in LN from one HIV controller even though plasma viruses showed genetic markers of diversification and ongoing evolution. This individual also showed TCM cell-associated HIV DNA sequences in blood that were more genetically distant from plasma viruses than were TEM-associated sequences. Among all 14 HIV controllers Cell 166, 1004–1015, August 11, 2016 1009 Dist. to plasma NN Dist. to plasma NN Dist. to plasma NN Dist. to plasma NN Dist. to plasma NN A 0.08 Participant S1495 pVL 525 copies/mL HIV DNA 53.2 copies/mL Uniq. ind. 0.79 cell/mL 0.04 0.00 0.00 0.04 0.08 0.09 0.06 Participant V912 pVL 442 copies/mL 0.03 HIV DNA 93.5 copies/mL Uniq. ind. 0.76 cell/mL 0.00 0.00 0.06 0.12 0.04 Participant S1788 pVL 41 copies/mL HIV DNA 8.3 copies/mL Uniq. ind. LOD 0.010 cell/mL 0.02 0.00 0.00 0.02 0.04 0.02 Participant S1349 pVL <40 copies/mL HIV DNA 188.1 copies/mL Uniq. ind. 0.36 cell/mL 0.01 0.00 0.00 0.01 0.02 0.06 Participant S1270 pVL <40 copies/mL HIV DNA 83.7 copies/mL Uniq. ind. LOD 0.006 cell/mL 0.03 0.00 0.00 0.03 0.06 Distance to MRCA B Plasma TTM cell DNA TEM cell DNA Virion Expt. 1 Virion Expt. 2 Panels A, x-y plots Type of virus sequence Cell repeat, >102 copies/mL Cell repeat, 10-102 copies/mL Cell repeat, 1-10 copies/mL Cell repeat, 10-1-1 copy/mL Cell singlet Unique induced virion RNA Induced virion CD4 T cell subset TCM TTM TEM Panels A, hemispheres Unique induced All other HIV DNA 1010 Cell 166, 1004–1015, August 11, 2016 0.02 Figure 5. RNA Sequences of Virions Induced from Circulating TCM, TTM, and TEM Cells in HIV Controllers (A) x-y plots: proximity of each HIV DNA sequence from circulating CD4 T cells or virions induced from TCM, TTM, and TEM cells to the participant’s MRCA (x axis) and nearest genetic neighbor (NN) from plasma virus (y axis). HIV DNA sequences detected once are shown as gray dots; recurrent HIV DNA sequences are shown as black circles scaled by the abundance of the sequence; and sequences detected in induced virion RNA but not in DNA from a second aliquot of cells (i.e., ‘‘unique induced’’ viruses) are shown as stars. Where an induced virion RNA sequence matched a recurrent HIV DNA sequence from blood cells, the circle corresponding to that DNA sequence is filled. The arrow shows one sequence from participant S1270 containing a lethal deletion within gp120. For alignment production, this deletion was filled with the participant’s consensus sequence; the measured genetic distance of this sequence to the plasma virus NN is therefore an underestimate. Hemispheres: quantities of unique induced proviruses and all other HIV DNA sequences in circulating CD4 T cells from HIV controllers. Plots are scaled to show relative levels of HIV DNA in circulating CD4 T cells from the five participants. For participants with undetectable unique induced viruses from blood cells, the LOD of this measurement is shown. (B) Sequences in virions induced from blood cells in participant S1270. Cyan indicates sequences from an initial experiment; magenta indicates sequences from a repeat experiment. Sequences in which relative insertions were excised or deletions filled in alignment production are shown with gray arrows. See also Figure S5. 0.0012 0.0007 HIV DNA copies/ 106 cells 105 104 0.0004 104 103 102 0.0004 3 10 102 Follic. Other Blood LN LN 101 100 Follic. Other Blood LN LN 0.5245 0.0079 C 104 0.0004 Panels A-C TCM TTM TEM CD57 Non-GC TFH GC TFH 103 102 101 100 10-1 Follic. Other Blood LN LN TCM CD57 Non-GC TFH GC TFH TEM 50 0 LI R0 2 LI R0 3 LI R0 4 % HIV DNA copies D 100 Follicular Extrafollicular Participant LIR03 Participant LIR02 E studied, the relative genetic proximity of TCM-associated HIV DNA sequences to plasma viruses was directly associated with plasma viremia (Figure S7). DISCUSSION 10-1 101 Spliced RNA copies/ DNA copy 0.3566 0.0002 B Unspl. RNA copies/ DNA copy A In this study, we investigated the mechanisms of virus persistence in HIV controllers using a combination of genetic analyses to track HIV replication and the persistence of HIV-infected cells in vivo. We found that the populations of HIV-infected CD4 T cells in blood and lymphoid tissue from these individuals differed markedly from one another. The infected cell pool in blood largely comprised archival proviruses within highly differentiated cells that appeared to be clonally expanded and that occasionally expressed virions when stimulated. In sharp contrast, the lymphoid tissue was often rich in TFH and other memory CD4 T cells bearing HIV genetic markers of recent infection and containing abundant virus transcripts. Despite these differences, however, we also detected rare circulating CD4 T cells that inducibly expressed HIV proviruses with the genetic signature of an actively replicating virus pool. These cells link the infected populations from blood and lymphoid tissue and may thus reflect the hematogenous dissemination of newly infected cells. Therefore, our findings suggest a single model in which HIV persists despite natural virologic control by three interrelated mechanisms: (1) ongoing infection of cells in lymphoid tissue, (2) survival and recirculation of some of these cells, and (3) long-term persistence of proviruses in clonally expanded cells. Our results support this model through key advances in several areas. Consistent with previous studies of SIV-infected macaques and HIV-infected long-term nonprogressors (Fukazawa et al., 2015; Perreau et al., 2013), we detected viruses with genetic and transcriptional markers of active replication most abundantly within PD1high, TFH-enriched cell populations in hosts who control the virus spontaneously. However, by using single-copy sequence analysis to identify this virus population, we were also able to detect its dissemination to extrafollicular LN cells. This implies either HIV transmission across follicle boundaries or differentiation of infected TFH cells into non-TFH cells. Furthermore, the genetic similarity among plasma viruses, viruses in LN cells, and unique induced viruses from blood cells suggests that some infected LN cells survive their initial encounter with infectious virus long enough to recirculate. We also identified blood TEM cells that appeared to be clonally expanded as a source of archival virus in HIV controllers. Our finding that inducible proviruses of recent origin were present but rare amid the excess of archival proviruses in highly differentiated, clonally expanded blood cells explains the large genetic 50 M Figure 6. HIV DNA and RNA Levels in LN CD4 T Cell Subsets (A) Levels of HIV DNA measured by FCA in LN non-GC TFH and GC TFH; nonfollicular LN subsets (CD57+ subset collected only for participant LIR02); and blood TCM, TTM, and TEM subsets. (B and C) Copies of unspliced (B) and spliced (C) HIV RNAs in LN memory CD4 T cell subsets, measured by qRT-PCR and normalized to values in (A). Each cell subset is shown with a unique shape and colored by participant. Undetectable values are plotted at the assay LOD with open symbols. (A)–(C) include results from blood CD4 TCM, TTM, and TEM subsets that are also shown in Figure 1. Mann-Whitney p values are shown. (D) The percentage of all HIV DNA copies in LN memory CD4 T cells from each participant detected in each subset. (E) HIV RNA+ LN cells detected by in situ hybridization using 35S-labeled riboprobes in two study participants. White arrows indicate examples of HIV RNA+ cells. Some such cells were associated with areas of diffusely increased signal corresponding to the follicular dendritic cell network (follicular); others were outside such areas (extrafollicular). See also Figures S6 and S7 and Table S3. Cell 166, 1004–1015, August 11, 2016 1011 0.02 EM T TM T CM CM 0.00 0.06 T 0.03 0.04 T 0.03 0.00 0.00 0.06 EM Plasma P <0.0001 MRCA P = 0.0035 All P < 0.05 T 0.06 Distance to TFH NN Distance to plasma NN Figure 7. Analysis of HIV DNA Sequences and Host Gene Expression in LN CD4 T Cell Subsets from HIV Controllers Participant LIR02 A EM TM T T CM 0.00 0.10 T 0.05 0.03 CM 0.00 0.00 0.06 T 0.05 All P < 0.05 0.09 EM Plasma P <0.0001 MRCA P = 0.1349 T 0.10 Distance to TFH NN Distance to plasma NN Participant LIR03 EM T TM T CM 0.00 0.08 T 0.04 0.02 CM 0.00 0.00 0.04 T 0.04 All P < 0.05 0.06 EM Plasma P = 0.0008 MRCA P = 0.0036 T 0.08 Distance to TFH NN Distance to plasma NN Participant LIR04 Distance to MRCA Panels A, left B LN/PB TN 0.2 Blood cell DNA sequences Repeat, 10-102 copies/mL Repeat, 10-1-1 copy/mL Singlet PC2 (0.014) Repeat, 1-10 copies/mL GC/non-GC TFH 0.1 TFH cell DNA sequences (GC and non-GC) Repeat, High rel. abund. Repeat, Mod. rel. abund. PB TTM 0.0 LN TEM -0.1 PB TEM -0.2 -0.134 -0.132 Panels A, right -0.128 PC1 (0.939) Repeat, Low rel. abund. Singlet -0.130 Panel B PB TEM PB TN LN TEM Lymph node LN TN Non-GC TFH Blood PB TTM GC TFH 1012 Cell 166, 1004–1015, August 11, 2016 (A) Left: proximity of each HIV DNA sequence from LN GC and non-GC TFH cells to each participant’s MRCA (x axis) and plasma virus NN sequence (y axis). HIV DNA sequences from blood cells are shown as in Figure 5; HIV DNA sequences from GC and non-GC TFH cells are shown as green-filled circles scaled by their relative abundance in LN. Sequences from GC and non-GC TFH cells were compared to those from blood cells for genetic distance to plasma virus NN and MRCA sequences. Mann-Whitney p values for these comparisons are shown. Right: proximity of each HIV DNA sequence from non-TFH TCM and TEM LN cells and TCM, TTM, and TEM blood cells to the NN sequence from GC and non-GC TFH cells. All Mann-Whitney p values for comparisons between LN cell subsets and blood cell subsets are <0.05. (B) PCA of transcriptomes from blood (PB) and LN CD4 T cell subsets. Clusters of symbols representing samples of the same cell subset from multiple study participants are demarcated with dashed boundaries. See also Figures S6 and S7 and Table S3. distance between HIV sequences in blood cells and plasma observed previously in controllers (Bailey et al., 2006; O’Connell et al., 2010). Finally, although prior studies have found expanded clones of HIV-infected cells ex vivo (Cohn et al., 2015; Maldarelli et al., 2014; Wagner et al., 2014), virus production has been shown previously from only one clone in one individual (Maldarelli et al., 2014; Simonetti et al., 2016) and never in an HIV controller. Although CD4 T cell clonal proliferation may involve transcriptional processes that elicit HIV expression and thus select for lethal mutations among expanded proviruses, the dissociation of virion production from cellular stimulation supported by our findings provides one mechanism for proliferative self-renewal of HIV-producing CD4 T cells in vivo. The heterogeneity that we observed among HIV-infected TEM cells from HIV controllers was also noteworthy. Most HIV DNA sequences in circulating TEM cells appeared to be associated with expanded cellular clones. We propose that this reflects the basic biology of TEM cells, which may also harbor infected cells that have clonally expanded in ART-treated individuals (von Stockenstrom et al., 2015). The relatively high levels of HIV DNA we found in blood TEM cells distinguish HIV controllers from ART-treated individuals (Chomont et al., 2009) and may stem from higher levels of virus replication and immune activation (Hunt et al., 2008, 2011; Krishnan et al., 2014) stimulating HIV-infected cells to proliferate and differentiate in HIV controllers. At the same time, by sampling lymphoid tissue or virions induced from blood cells instead of blood cell DNA, we uncovered viruses of recent origin in rare TEM cells. Therefore, it appears that both archival and actively replicating virus populations persist within TEM cells in HIV controllers, but by distinct mechanisms. Importantly, lack of CD27 expression represents an inclusive definition for the TEM subset, and finer distinctions among subsets of CD27– cells may yield additional insights in future studies. Furthermore, the lifespan of circulating CD27– cells carrying inducible, recently acquired proviruses remains to be determined. Nonetheless, these considerations make clear that targeting less differentiated TCM and TTM cells is unlikely to eliminate all potentially infectious proviruses in HIV controllers. Despite these diverse mechanisms of persistence, we detected profound imprints of effective antiviral defenses among HIV DNA sequences from HIV controllers. In peripheral blood, restricted replication of the virus was associated with a predominance of recurrent sequences within clonally expanded cells, a scarcity of cell-associated virus transcripts, and a small number of cells harboring unique induced viruses. While expanded G-to-A hypermutant viruses were abundant in circulating infected cells from some HIV controllers, this most likely reflects a predominance of non-replicating proviruses in these individuals, rather than excess activity of APOBEC3G (Abdel-Mohsen et al., 2013). In lymphoid tissue, the enrichment for recently infected cells containing abundant HIV transcripts within TFH populations is consistent with a key role for virus-specific CD8+ T cells in suppressing HIV replication outside follicles (Fukazawa et al., 2015). In fact, we documented this effect in individuals lacking major protective HLA-B alleles, suggesting that the suppression of extrafollicular virus replication may occur widely among HIV controllers. Finally, we propose that the relationship between plasma viremia and the genetic proximity of blood TCM- associated HIV DNA sequences to plasma viruses in HIV controllers reflects reduced dissemination of recently infected CD4 T cells in individuals with greater virologic control. When ongoing virus replication is very limited, rare recently infected cells— more readily detected by sequencing in the TCM subset than in the more heavily expanded TTM and TEM subsets—may occur too rarely for detection in a single blood sample. Taken to an extreme, the limited dissemination of recently infected CD4 T cells in blood may prevent the virus from spreading throughout the lymphoid tissue compartment, as for one participant in our study. Thus, in rare cases, natural antiviral responses may restrict the regional anatomic distribution of the virus. Our findings reflect in vivo properties of HIV-infected CD4 T cell populations that may be generalizable to all infected individuals. Of particular interest is the uncertain significance of expanded CD4 T cell clones as barriers to cure. On the one hand, the rarity of virion production from expanded proviruses in our study mirrors results in ART-treated individuals, calling into question whether this mechanism alone could account for the near certainty of rebound viremia upon ART interruption. On the other hand, the recent temporal clustering of unique induced proviruses in our study suggests that newly infected cells recirculating from lymphoid tissue may disappear quickly if not maintained by clonal expansion. Complicating attempts to resolve these findings, however, is the evident difficulty of eliciting virus expression from some inducible proviruses in HIV controllers, as shown previously in ART-treated non-controllers (Ho et al., 2013). In addition to preventing full characterization of inducible proviruses ex vivo, this difficulty may reflect natural heterogeneity in the cellular response to stimulation that serves to protect some proviruses from antiviral defenses in vivo. Therefore, while our findings support the role of the B cell follicle in ongoing HIV replication in HIV controllers, we also demonstrate extrafollicular mechanisms that could maintain and disseminate the virus even if its replication inside follicles were disrupted. Were any approach to a functional or sterilizing cure to succeed either in HIV controllers or in non-controllers, it would need to target these multiple distinct cellular processes. EXPERIMENTAL PROCEDURES Peripheral Blood Mononuclear Cell and LN Samples Participants were recruited from UCSF and NIAID and gave informed consent for all procedures. Studies were approved by the UCSF and NIAID institutional review boards. Peripheral blood mononuclear cells (PBMCs) were isolated from blood or leukapheresis by density gradient centrifugation. LN excisional biopsy samples were sectioned and filtered to generate single-cell suspensions. Fluorescence-Activated Cell Sorting Viable PBMCs were stained and sorted on a FACSAria (BD). Subset definitions were as shown in Figure S1 for PBMCs and in Figure S6 for LN cells. Nucleic Acid Extraction RNA and DNA were extracted in separate fractions from sorted cells lysed in RNAzol RT (MRC), according to the manufacturer’s instructions. Recovery of HIV Virion RNA Virion RNA was extracted from whole plasma or pelleted virions using the QiaAmp vRNA mini kit (QIAGEN), according to the manufacturer’s instructions. Cell 166, 1004–1015, August 11, 2016 1013 Fluorescence-Assisted Clonal Amplification for Single-Copy HIV Quantification and Sequencing Cell DNA or reverse-transcribed HIV virion RNA was amplified at limiting dilution in replicate PCR wells using primers targeting HXB2 positions 6908–7517, with SYBR green I as marker of double-stranded DNA (dsDNA). Amplification was detected by real-time fluorescence and confirmed by melt curve (Figure S2). Single copies of HIV DNA were enumerated for each sample by limiting dilution calculations. Amplified env products were reamplified by nested PCR and Sanger sequenced. Because all primers in these PCRs targeted regions within the HIV genome, the resulting sequence data were considered to reflect all HIV DNA copies in samples from cells, including both integrated and unintegrated forms. Quantification of HIV RNAs Cellular total RNA samples were tested for HIV RNA by qRT-PCR for unspliced (gag) RNA or transcripts spliced between the SD1 and SA4 sites (Purcell and Martin 1993). Copies of RNA were enumerated using standard curves generated from dilutions of synthetic RNAs. HIV Sequence Analysis Sanger sequence reads defining single HIV sequences spanning HXB2 base positions 7011–7502 were edited, analyzed for diversity by subset within each participant, aligned by participant, and subjected to phylogenetic analysis after identification and removal of G-to-A hypermutated sequences. T Cell Receptor Beta Gene Deep Sequencing Sequencing and annotation of expressed TCRB genes were performed as described (Gros et al., 2014). The normalized Shannon diversity was calculated for the set of TCRB sequences from each CD4 T cell subset by the same method used for populations of HIV sequences (see Supplemental Experimental Procedures), determining the maximum Shannon diversity for each sample based on the number of cells used in library preparation. HIV Integration Site Deep Sequencing Integration site analysis was performed as described (Maldarelli et al., 2014). Sequencing of Viruses Induced In Vitro Sorted TCM, TTM, and TEM cells were stimulated in culture through the T cell receptor in the presence of antiretrovirals, and virions were pelleted from culture supernatants for RNA extraction after 4 and 8 days of culture. Virion RNA was reverse transcribed and amplified for single-copy sequencing by FCA. In Situ Hybridization Hybridization of 35S-labeled riboprobes for the detection of HIV RNA+ cells in LN tissue slices available from two study participants was performed as described (Rothenberger et al., 2015). Whole-Transcriptome Sequencing Messenger RNA libraries were constructed as described (Sandler et al., 2014) and sequenced in 2-3-75-base, paired-end runs on an Illumina HiSeq. Highquality reads were mapped to the Hg19 reference using Tophat (v.2.0.8) with a reference annotation (Ensembl ‘‘Homo_sapiens.GRCh37.74.gtf’’). Samples with low map rates were discarded. Transcript abundance was determined with Cufflinks (v2.1.1). PCA was performed using ‘‘princomp’’ in the R ‘‘stats’’ package. The abundance of each transcript was log transformed before PCA. To limit the influence of low transcript abundance levels, the level of each transcript was set to 1 if the measured level was <1. ACCESSION NUMBERS The accession numbers for the HIV Sanger sequencing data reported in this paper are GenBank: KX390978-KX394124 The accession number for the whole transcriptome sequencing data reported in this paper is GEO: GSE83482. The accession number for the TCR deep sequencing data reported in this paper is NCBI Short Read Archive: SRP076794. The accession number for the HIV integration site sequencing reported in this paper can be found by searching the NCI HIV Dynamics and Replication program website at https://rid.ncifcrf.gov/index.php using the paper’s PubMed ID. 1014 Cell 166, 1004–1015, August 11, 2016 SUPPLEMENTAL INFORMATION Supplemental Information includes Supplemental Experimental Procedures, seven figures, and four tables and can be found with this article online at http://dx.doi.org/10.1016/j.cell.2016.06.039. AUTHOR CONTRIBUTIONS Conceptualization, E.A.B. and D.C.D.; Methodology, E.A.B., X.W., J.P.C., T.S., and D.C.D.; Investigation, E.A.B., S.D., L.S., G.W., D.W., X.W., A.R.H., F.L., D.A., A.V., D.B., and K.N.-M.; Formal Analysis, S.D. and J.H.; Resources, M.H., R.H., S.A.M., M.C., S.M., and S.G.D.; Writing – Original Draft, E.A.B. and D.C.D.; Writing–Review and Editing, E.A.B., S.H.H., and D.C.D.; Supervision, R.A.K., F.M., S.H.H., S.G.D., T.S., and D.C.D. ACKNOWLEDGMENTS We thank the study participants for their involvement in the study. We thank S. Kosakovsky-Pond for help with phylogenetic analysis and C. Petrovas for helpful discussions. D.C.D. and E.A.B. are funded by the NIH Intramural Research Program. D.C.D. is also funded by the NIAID Division of AIDS and the NIH Office of AIDS Research. Additional funding came from AIDS Vaccine Discovery grant OPP1032325 from the Bill and Melinda Gates Foundation (to R.A.K.), the Delaney AIDS Research Enterprise (AI096109 to S.G.D.), NIAID K24 (AI069994 to S.G.D.), the UCSF/Gladstone Institute of Virology & Immunology CFAR (P30 AI027763 to S.G.D.), and federal funds from the NCI (to F.M. and S.H.H.). Received: February 25, 2016 Revised: May 9, 2016 Accepted: June 20, 2016 Published: July 21, 2016 REFERENCES Abdel-Mohsen, M., Raposo, R.A., Deng, X., Li, M., Liegler, T., Sinclair, E., Salama, M.S., Ghanem, Hel.-D., Hoh, R., Wong, J.K., et al. (2013). Expression profile of host restriction factors in HIV-1 elite controllers. Retrovirology 10, 106. Archin, N.M., Liberty, A.L., Kashuba, A.D., Choudhary, S.K., Kuruc, J.D., Crooks, A.M., Parker, D.C., Anderson, E.M., Kearney, M.F., Strain, M.C., et al. (2012). Administration of vorinostat disrupts HIV-1 latency in patients on antiretroviral therapy. Nature 487, 482–485. 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Recovery of replication-competent HIV despite prolonged suppression of plasma viremia. Science 278, 1291–1295. Cell 166, 1004–1015, August 11, 2016 1015 Supplemental Figures A E 24.1 CD4 SSC-A 71.0 FSC-A CD8 B F 85.5 FSC-H SSC-A 99.9 FSC-A Lineage dump C G TN 23.7 CD3 CD27 74.5 Viability dump DP 16.0 TEM 43.2 CD45RO D H TCM 47.9 CCR7 CD14/CD11c 99.4 CD4 TTM 41.3 SSC-A Figure S1. Gating for Fluorescence-Activated Cell Sorting of CD4 T Cell Subsets from Blood, Related to Figure 1 (A–F) Leukocytes (A) not part of multi-cell conjugates (B) that were viable and stained with the T cell marker CD3 (C) but not myeloid cell markers CD14 and CD11c (D), the cytotoxic T cell marker CD8 (E), or lineage dump markers including CD20, CD56, and TCR-gd (F) were divided by CD27 and CD45RO staining and collected as TN (G, top-left gate) or TEM (G, bottom gate) subsets. (H) Cells that were double-positive (DP; G, top-right gate) for CD27 and CD45RO were further divided by CCR7 staining (H) into TCM (top) and TTM (bottom) subsets. Both CD4high and CD4low cells (E) were included in sorted subsets to ensure collection of any cells with CD4 downregulation due to active HIV infection and Nef activity. Numbers on plots represent percentages of plotted cells falling within the gates shown. Cell 166, 1004–1015, August 11, 2016 S1 Fluorescence A Cycle # Deriv. Fluorescence B Temperature C M- - + - - + - - - - - - - - - - + + - - ++ - + M- + - - - - - + -+ - ++ - - - - - + - - + - M+ - - + - - - ++ - ++ - - + - - - - - - - + M+ -+ - - - - - - - - - - - + - - + - - - + - - D HIV DNA copies detected 50 40 30 20 10 0 FCA gag Figure S2. Fluorescence-Assisted Clonal Amplification, Related to Figure 1 Cell-associated HIV DNA or plasma virion cDNA was plated in 384-well plates at an estimated 0.3 copies/well and amplified by PCR using primers flanking a fragment of the env gene including HXB2 base positions 6908-7517, in the presence of SYBR Green I as a marker of dsDNA. (A and B) Wells showing fluorescence amplification (A) and amplicon melting temperatures between 76.0-82.0 C (B) were considered to be positive. (legend continued on next page) S2 Cell 166, 1004–1015, August 11, 2016 (C) Specificity of FCA analyzed by agarose gel electrophoresis. Lanes corresponding to FCA wells from (A) and (B) that contained amplification products with melting temperatures in the target range are indicated with ‘‘+’’ symbols. M, molecular weight marker. Gel images were cropped to include only the relevant size range. Results are shown for a sample consisting of linearized HIV plasmid diluted into HIV-negative PBMC DNA at 1 copy per 1,000 cell equivalents. (D) The sensitivity of FCA was similar to the sensitivity of HIV gag taqman PCR for single copies of HIV in equal aliquots of this sample run in 96 PCR wells for each test (D). Cell 166, 1004–1015, August 11, 2016 S3 D A J G M 0.02 0.02 0.02 0.02 0.02 B E H K N 0.02 0.05 0.02 0.05 C F I L 0.02 Legend 0.02 0.02 0.05 0.02 Plasma TCM TTM TEM Figure S3. Phylogenetic Trees Representing Single-Copy HIV Sequence Results Obtained by FCA from Plasma Virions and from CellAssociated DNA of CD4 TCM, TTM, and TEM in HIV Controllers, Related to Figure 2 Each tree represents results from a single study participant, rooted on the HXB2 sequence. Sequences from each participant showing G-to-A hypermutation are indicated as detached branches in the box associated with that participant’s tree. Sequences in which relative insertions were excised or deletions filled in alignment production are shown with gray arrows. (A–N) Participant identifiers are as follows: (A) S1492, (B) S1270, (C) S1788, (D) S1548, (E) LIR04, (F) V907, (G) S1475, (H) S1349, (I) S1495, (J) S1541, (K) LIR02, (L) LIR01, (M) V912, and (N) LIR03. S4 Cell 166, 1004–1015, August 11, 2016 A C E 0.05 0.02 0.05 B D F 0.02 0.02 0.05 Legend Plasma TCM TTM TEM Figure S4. Phylogenetic Trees Representing Single-Copy HIV Sequence Results Obtained by FCA from Plasma Virions and from CellAssociated DNA of CD4 TCM, TTM, and TEM in Non-controllers, Related to Figure 2 Each tree represents results from a single study participant, rooted on the HXB2 sequence. Sequences from each participant showing G-to-A hypermutation are indicated as detached branches in the box associated with that participant’s tree. Sequences in which relative insertions were excised or deletions filled in alignment production are shown with gray arrows. (A–F) Participant identifiers are as follows: (A) V016, (B) V257, (C) V621, (D) V667, (E) V965, and (F) V723. Cell 166, 1004–1015, August 11, 2016 S5 00 10 60 0 0 20 40 30 20 10 0 Recurrent HIV DNA sequence S1495_14 S1495_30 S1495_32 S1495_34 S1495_43 S1495_55 S1495_58 V912_14 V912_16 V912_25 V912_26 V912_29 V912_30 V912_41 V912_47 V912_8 V912_9 S1788_29 S1788_3 S1349_10 S1349_17 S1349_6 S1349_7 S1349_9 S1270_1 S1270_2 S1270_5 S1270_6 S1270_7 S1270_8 S1270_9 Cells in stimulation culture Figure S5. Calculated Numbers of Cells from Presumptive Expanded CD4 T Cell Clones Included in Virion Induction Cultures of CD4 TCM, TTM, and TEM Cells from HIV Controllers, Related to Figure 5 Each presumptive expanded clone is defined by a distinct HIV DNA sequence (y axis labels). Blue bars indicate TCM cultures, green bars indicate TTM cultures, and red bars indicate TEM cultures. Filled bars indicate sequences also detected in virions induced from the given CD4 T cell subset. S6 Cell 166, 1004–1015, August 11, 2016 E I 10-2 10-3 10-4 CD8 29.8 G 37.8 57.1 0.59 4.08 EM T T FH FSC-A C 0.08 Avg. pairwise dist. plas. CD4 FSC-H J CM 10-5 TM 83.2 10-1 T F Blood 100 T CM N on CD -G 57 C T G FH C T 90.9 Myeloid dump Lymph Node 101 T CD4 SSC-A FSC-A B HIV DNA copies/100 cells 99.6 75.8 EM A 0.06 0.04 0.02 Viability dump D C N C 1.50 0.37 96.8 1.31 CD57 99.6 CD4 K CD45RO H Avg. plas. dist. to MRCA CD3 CD27 0.00 0.15 0.10 0.05 C N PD1 C 0.00 CD20 Figure S6. Study Participant LIR01, Related to Figures 6 and 7 (A–H) Gating for fluorescence-activated cell sorting (FACS) of CD4 T cell subsets from lymph node. Leukocytes (A) not part of multi-cell conjugates (B) that were viable and stained with the T cell marker CD3 (C) but not B cell marker CD20 (D), myeloid cell markers CD14 and CD11c (E), or the cytotoxic T cell marker CD8 (F) were divided by CD27 and CD45RO staining and collected as TN (G, top-left quadrant) or TEM (G, bottom quadrants) subsets. Cells that were double-positive for CD27 and CD45RO (G, top-right quadrant) were further divided by CD57 and PD1 staining (H) into CD57+ TCM (top-left quadrant), GC TFH (top-right quadrant) and non-GC TFH (bottom-right quadrant) subsets. Both CD4high and CD4low cells (F) were included in sorted subsets to ensure collection of any cells with CD4 downregulation due to active HIV infection and Nef activity. Numbers on plots represent percentages of plotted cells falling within the gates or quadrants shown. (I) Ex vivo quantification of HIV DNA in memory CD4 T cell subsets from lymph node and blood. Undetectable values are plotted at the assay LOD with open bars. (J) Average pairwise genetic distances among plasma virus sequences from all study donors, with the value for participant LIR01 shown in dark blue. (K) Average genetic distances to MRCA of plasma virus sequences from all study donors, with the value for participant LIR01 shown in dark blue. C, HIV controllers; NC, non-controllers. (I) includes results from blood CD4 TCM, TTM, and TEM subsets that are also shown in Figure 1. (K) shows results that are also shown in Figure 3. Cell 166, 1004–1015, August 11, 2016 S7 Plasma HIV RNA (copies/mL) 1500 r = 0.5453 P = 0.0469 1000 500 0 0.5 1.0 1.5 2.0 TCM relative proximity to plasma Figure S7. Correlation between the Relative Genetic Proximity of Blood TCM Cell-Associated HIV DNA Sequences to the Plasma Virus and Plasma HIV RNA Levels in HIV Controllers, Related to Figures 6 and 7 Genetic proximity to the plasma virus was defined as the reciprocal of the average genetic distance between HIV DNA sequences in a given subset and plasma virus RNA sequences. The genetic proximity to the plasma virus of HIV DNA sequences from the TCM subset was normalized to the corresponding value for HIV DNA sequences from the TEM subset in the same individual to determine the relative genetic proximity of TCM cell-associated HIV DNA sequences to the plasma virus for that individual. For participant S1270, who had no detectable HIV DNA in blood TCM cells, the relative genetic proximity of blood TCM cell-associated HIV DNA sequences to the plasma virus was set equal to the lowest value among the remaining participants. This was done to reflect the absence of HIV DNA sequences closely related to the plasma virus within the blood TCM cell subset in this individual. Spearman r and p values are shown. S8 Cell 166, 1004–1015, August 11, 2016 Cell, Volume 166 Supplemental Information Multiple Origins of Virus Persistence during Natural Control of HIV Infection Eli A. Boritz, Samuel Darko, Luke Swaszek, Gideon Wolf, David Wells, Xiaolin Wu, Amy R. Henry, Farida Laboune, Jianfei Hu, David Ambrozak, Marybeth S. Hughes, Rebecca Hoh, Joseph P. Casazza, Alexander Vostal, Daniel Bunis, Krystelle Nganou-Makamdop, James S. Lee, Stephen A. Migueles, Richard A. Koup, Mark Connors, Susan Moir, Timothy Schacker, Frank Maldarelli, Stephen H. Hughes, Steven G. Deeks, and Daniel C. Douek SUPPLEMENTAL EXPERIMENTAL PROCEDURES Extraction and quality analysis of cell-associated RNA and DNA. CD4 T cell subsets were sorted by FACS into heatinactivated fetal calf serum and kept on ice until further processing. Cells were then sedimented by centrifugation to 420 x g for 7 minutes at 4°C, lysed in RNAzol RT at <5 x 106 cells/mL, homogenized by pipetting, and stored at -80°C until extraction. For dual RNA and DNA extraction, 0.4 volume of sterile H2O was added to each lysate to allow aqueous and organic phase separation. Total RNA was extracted from the aqueous phase according to the manufacturer’s instructions. The organic phase of each lysate was solubilized in DNAzol (Molecular Research Centers) to allow DNA extraction according to the manufacturer’s instructions. RNA yield and integrity were verified by microelectrophoresis using the RNA 6000 Pico Bioanalyzer Kit (Agilent). DNA yield was determined on a Nanodrop spectrophotometer (Thermo Scientific). For DNA samples from memory CD4 T cell subsets yielding no amplifiable HIV DNA by fluorescence-assisted clonal amplification (FCA), PCR inhibition was ruled out by quantitative PCR for the albumin gene in serial sample dilutions. Cell staining for FACS. Cells were labeled with LIVE/DEAD Aqua stain (Molecular Probes) and the following antibodies: CXCR5-Alexa Fluor 488 (Pharmingen); CD27-Cy5PE (Coulter); CD45RO-PE-Texas Red (Coulter); CD14-PE (BD); CD11c-PE (BD); CD3-H7APC (BD); CCR7-Alexa Fluor 700 (Pharmingen); CD20-APC (BD); CD56-APC (BD); T cell receptor gamma delta (TCR-γδ)-APC (Pharmingen); CD57-QDot 800 (Invitrogen); PD1-Brilliant Violet 711 (BioLegend); CD4-Briliant Violet 785 (BioLegend); CD8-QDot 655 (Invitrogen); and CCR6-Brilliant Violet 421. LN cells were stained with the same antibodies, except for the inclusion of CD20-Brilliant Violet 570 (BioLegend) in place of CD20-APC and the exclusion of CD56-APC and TCR-γδ-APC. Due to sample availability constraints, cells were only sorted according to the markers CXCR5, CCR6, and CD57 for participants V912, V907, S1475, S1492, S1495, and S1548. Reverse transcription of HIV virion RNA. Virion RNA samples for FCA and sequencing were denatured at 65°C for 10 minutes, annealed to env reverse transcription primer (either LSr1 or envB3out) at a primer concentration of 100 nM, and reverse transcribed using SuperScript III (Life Technologies) at 50°C for 50 minutes followed by incubation at 85°C for 10 minutes to inactivate the reverse transcriptase. Fluorescence-assisted clonal amplification (FCA). FCA for single-copy quantification and sequencing of CD4 T cellassociated HIV DNA molecules or single-copy sequencing of HIV virion cDNA molecules was performed in replicate PCR wells at an estimated 0.3 HIV copies/well using primer mixes ESf2 and LSr1, which were prepared as equimolar combinations of related oligonucleotides accounting for degenerate sequences at several base positions (see Table S4). These primer mixes were added to a final concentration 150 nM for each oligonucleotide. Amplification was performed with Platinum Taq DNA Polymerase High Fidelity (Life Technologies) in the presence of a 1:250,000-fold dilution of SYBR Green I Gel Stain (Molecular Probes) as a double-stranded DNA marker. To inhibit primer amplification artifacts, yeast transfer RNA was included in each reaction at a concentration inversely related to the quantity of CD4 T cell DNA template in the reaction. Up to 5,000 cell-equivalents of template DNA were loaded per reaction well. Reactions were run in 384-well standard PCR plates (ThermoFisher catalog # AB1384) under the following cycling conditions: 94°C for 2 minutes; then 50 cycles of 94°C for 15 seconds, 63°C for 15 seconds, and 68°C for 45 seconds; and then melt curve analysis. Positive wells were defined as those showing exponential amplification of SYBR green I fluorescence and a discrete melt curve peak between 76.0°C and 82.0°C. For each sample analyzed by FCA, a small sample aliquot was initially run in enough replicate wells to allow rough quantification of HIV DNA copy number, calculated as follows: HIV DNA copy number = (number of replicate wells) x (-ln(fraction of negative replicate wells)). The quantity of each sample used in this quantification FCA was chosen based on plasma virus load (for plasma virion cDNA samples) or the proportion of CD4 T cells in the sample predicted to contain HIV DNA (generally 10-4-10-3), with the goal of achieving 50% positive wells. Quantification FCAs yielding non-quantifiable results (i.e., 0% or 100% positive wells) were repeated after adjustment of sample input quantity. Based on quantification FCA results, a volume of sample predicted to contain approximately 30 HIV DNA copies (where available) was loaded into enough replicate wells to ensure limiting dilution. Preliminary quantifications of HIV DNA copy number were determined from these larger-scale FCA runs. Positive wells from FCA runs where <35% of wells were positive (i.e., samples run at limiting dilution) were reamplified with primers FCAf3 and FCArB using Platinum Taq DNA Polymerase High Fidelity under the following cycling conditions: 94°C for 2 minutes; then 35 cycles of 94°C for 15 seconds, 60°C for 15 seconds, and 68°C for 45 seconds. Reamplified products were then Sanger sequenced. Products not yielding the expected HIV env sequence were considered to reflect poor amplification due to possible mismatch between nested primer sequences and the original FCA reaction products, and were thus “rescued” by reamplification of original FCA reaction products with the outer primers ESf2 and LSrB instead of the nested primers. FCA wells that were originally called positive but that did not yield the expected HIV env sequence upon rescue reamplification were considered to be false positives. Final quantifications of HIV DNA copy number were determined after excluding these false positive wells. To determine the percentage of cells from each sorted CD4 T cell subset containing HIV DNA, each HIV DNA copy number value was normalized to the sorted cell number. Quantitative reverse transcription PCR (qRTPCR) for HIV RNAs. Total RNA samples from CD4 T cell subsets extracted as described above were treated with DNAse I for 20 minutes at 37°C and then 15 minutes at 70°C to inactivate the DNAse. Unspliced and spliced HIV transcripts were quantified using the RNA UltraSense One-Step Quantitative RT-PCR System (ThermoFisher). For unspliced (gag) RNA detection, the forward primer was gag F, the reverse primer was gag R, and the probe was gag P (see Table S4). For spliced RNA detection, the forward primer was rev F, the reverse primer was rev R, and the probe was rev P. Cycling conditions were 45°C for 30 minutes, 95°C for 2 minutes, and then 45 cycles of 95°C for 15 seconds and 60°C for 60 seconds. Template RNA was loaded at between 4,000 and 5,500 cell-equivalents per reaction. Sanger sequence editing. Base calls for Sanger sequence reads were initially made in Sequencher after ends trimming with default settings. Each sequence read with a high-quality base call at every position within the range defined by HIV HXB2 coordinates 7011-7502 was included in later analysis without further editing. Each sequence read with a single ambiguous base call (defined by the presence of a secondary, in-phase chromatogram peak with a magnitude at least 25% of that of the primary peak) over this same env region was considered a possible PCR error and included in later analysis with the ambiguity included in the final sequence. Each sequence read with ≥2 ambiguous base calls separated by unambiguous base calls was considered to be non-clonal and was thus excluded from later analysis. Reads with widespread ambiguities occurring after long poly(dA) runs were attributed to polymerase slipping during PCR and were manually overwritten assuming this mechanism. Downstream analysis of these sequences universally showed G-to-A hypermutation. In rare examples of this pattern, base call ambiguities were too severe to be overwritten manually. Such sequence reads were trimmed and used for virus DNA quantification and diversity analyses, but not for any phylogenetic tree-based analysis. HIV sequence analysis. Edited sequences from all study participants were aligned using GeneCutter at www.hiv.lanl.gov. The alignment was improved manually and used for maximum-likelihood phylogenetic tree construction in MEGA, allowing identification and removal of rare contaminants. The remaining sequences from each participant were compared to one another in pairwise fashion without alignment. Each group of matching sequences thus identified was collapsed to generate a uniquely identified cluster tagged with the number of corresponding reads from each virion or cell subset. Normalized Shannon diversity was determined by using the R package, Vegan, to calculate the absolute Shannon diversity within the collapsed, counted data from each virion or cell subset and then dividing this by the maximum Shannon diversity for that subset determined by the number of sequence reads analyzed. Sequences were then realigned by participant and used to create maximum-likelihood trees in DIVEIN (https://indra.mullins.microbiol.washington.edu/DIVEIN/) (Deng et al. 2010). Sequences showing G-to-A hypermutation were tentatively identified within each participant’s alignment using Hypermut at www.hiv.lanl.gov and confirmed by their genetic distance from the group of non-hypermutated sequences in that participant’s tree. Hypermutated sequences were removed from each participant’s alignment before realignment and construction of a final phylogenetic tree in DIVEIN, rooted on the HXB2 sequence. Genetic characteristics of individual HIV sequences or sequence clusters were determined using pairwise distances calculated in this analysis. Copy numbers of repeated CD4 T cell-associated HIV DNA sequences per volume of blood were calculated for each CD4 T cell subset as follows: copy number from subset/mL = (participant’s CD4 count in cells/mL) x (proportion of CD4 T cells from subset in participant) x (copies HIV DNA per cell in subset in participant) x (proportion of HIV DNA copies corresponding to repeated sequence in subset in participant). The total copy number of each repeated sequence per volume of blood was then determined by summing the results for that sequence from all subsets. Relative abundance values of repeated CD4 T cellassociated HIV DNA sequences from LN were calculated in similar fashion, but without adjustment for absolute CD4 T cell numbers across different participants. Repeated sequences in LN cells were classified as occurring at low, medium, or high relative abundance after stratifying all such sequences by their relative abundance levels into three groups of equal size. Genetic compartmentalization of HIV sequences was assessed by Slatkin-Maddison testing using HyPhy (Pond, Frost, and Muse 2005). Analysis of G-to-A hypermutation. The Original Hypermut algorithm on the LANL HIV sequence database website was used to identify sequences with G-to-A hypermutation. Because the use of the HXB2 sequence as a reference in this algorithm caused an apparent decrease in sensitivity in our initial trials, we chose a reference sequence for each participant from the set of cell- and virion-associated sequences determined for that participant. This was accomplished by determining a “least hypermutated” sequence from each participant’s alignment after scoring all possible pairwise comparisons between sequences for evidence of APOBEC3G-induced hypermutation using Hyperpack (Kijak et al. 2007). Sequences with significant evidence of hypermutation (P < 0.05) using the least hypermutated sequence as a reference in the Hypermut algorithm were considered to be hypermutated if they did not cluster with non-hypermutated sequences in the phylogenetic tree for the participant. TCRB gene deep sequencing. Total RNA from sorted CD4 T cell subsets was reverse transcribed using a modified version of the SMARTer cDNA Synthesis kit (Clontech). TCRB sequences were then amplified using the SMARTer 5’ primer and TCRB constant region-specific primer Hu/Rh MBC2. The amplicons were amplified further to incorporate the Illumina flow cell binding sequences, Illumina read 1 priming sequences, and unique identifiers. Libraries were sequenced in 2 x 150 bp paired-end runs to obtain V region, J region, and CDR3 sequences. TCRB annotation was performed by combining a custom Java program written for these analyses and the National Center for Biotechnology Information’s BLAST program. Germline V and J genes of a TCRB read were identified first, and the CDR3 was determined by finding the conserved cysteine at the 5’ end of the CDR and the conserved phenylalanine at the 3’ end of the CDR. Unique TCRB combinations (V-CDR3-J) were collapsed to determine counts. HIV integration site library preparation and confirmatory PCR. Genomic DNA was fragmented by random shearing into 300- to 500-bp fragments. Linker-mediated nested PCR was performed to amplify the human genomic regions and the linked virus sequences from both the 5’ and 3’ long terminal repeats (LTRs). Paired-end sequencing was carried out using the MiSeq 2 x 150-bp paired end kit (Illumina). The sequences of the host-virus junctions and the host DNA breakpoints were determined. The host DNA sequences were then mapped to human genome (hg19) with BLAT. A stringent filter was used to check quality of recovered integration sites. Sequences with exactly the same integration site but different host DNA breakpoints came from different cells; this test thus identifies proviruses in clonally amplified cells. Integration sites in clonally expanded cells identified by this method were confirmed by PCR using a modified version of the FCA forward primer (ESf2Short, see Table S4) and a reverse primer targeting the integration site. In two cases, 45 PCR cycles generated ~3.2Kb products that were purified after excision from agarose gels and Sanger sequenced to determine the associated env region sequences. In a third case, 35 cycles of nested PCR using the first-round PCR product were necessary before gel purification and Sanger sequencing of the confirmatory ~3.2Kb product. These PCR reactions were performed using Platinum Taq Polymerase (Life Technologies) and additional reagents supplied by the manufacturer. Virion induction in vitro. Sorted CD4 TCM, TTM, and TEM cell subsets in RPMI 1640 + 10% fetal calf serum + penicillin/streptomycin/L-glutamine supplemented with Abacavir (5 nM) and Efavirenz (40 nM) were stimulated using T cell activation/expansion beads (Miltenyi) according to the manufacturer’s instructions. T cell activation was confirmed by flow cytometric analysis for CD25 and CD69 expression after 24-48 hours. After 4 days of culture, 75% of volume of medium from each culture was withdrawn for virion isolation and replaced with fresh medium. Each culture was then incubated for an additional 4-5 days, and culture medium was again withdrawn for virion isolation. Virions were isolated by high-speed centrifugation as described (Yukl et al. 2011) after an initial pre-clarification spin at 2,000 x g for 10 minutes and after spiking with known quantities of RCAS virions as a recovery control (Palmer et al. 2003). Virion RNA extracted from resulting pellets was reverse transcribed for FCA or subjected to FCA without reverse transcription to exclude HIV DNA contamination. Two sequences detected from induced virions were determined potentially to have come from contaminating DNA and were therefore excluded from further analysis. SUPPLEMENTAL TABLES Table S1. Related to Figure 1. Characteristics of study participants. C, HIV controller; NC, HIV-infected non-controller. ID Sex V912 V907 S1270 S1349 S1475 S1492 S1495 S1541 S1548 S1788 LIR01 LIR02 LIR03 LIR04 V016 V257 V621 V667 V723 V965 M M M M M M M M F M M F M M M M M M M M Clinical Group C C C C C C C C C C C C C C NC NC NC NC NC NC HIV Diagnosis Year 1989 2007 1986 2005 1992 2004 1992 1996 1991 2000 1984 2005 1994 2003 2003 2003 1993 1980 2008 2008 Sample Date 4/2011 4/2011 4/2014 2/2014 6/2010 6/2010 4/2014 1/2014 5/2010 3/2014 4/2014 6/2014 7/2014 11/2014 7/2010 4/2008 10/2010 10/2009 7/2010 3/2011 HLA-B Alleles B44/53 B07/45 B*0705/*5701 B*2705/*3501 B*3501/*5101 B*3501/*5703 B*2705/*4402 B*0702/*1402 B*4901/*5201 B*2705/*5701 B*1401/*5701 B14/15 B57/8101 B15/40:12 B*5701 B*5701/*0801 B*0801/*4801 B*4403/*5301 B35/39 Not performed CD4 count (cells/µL) 604 772 578 620 1216 746 293 933 846 503 934 551 494 530 230 373 412 564 501 467 Plasma HIV RNA (copies/mL) 442 854 <40 <40 66 486 525 988 118 41 <40 267 159 132 22240 25300 21381 13500 17728 23492 Table S2. Related to Figures 3 and 4. Characteristics of HIV DNA sequences in presumptive expanded CD4 T cell clones from HIV controllers. Participant ID Sequence IDa Defectb Copies/mL Average Distance to Plasma HIVc % Blood CD4 T Cell HIV DNA V912 V912 V912 V912 V912 V912 V912 V912 V912 V912 V907 V907 V907 V907 V907 S1270 S1270 S1270 S1270 S1270 S1270 S1270 S1349 S1349 S1349 S1349 S1349 S1475 S1475 S1475 S1475 S1475 S1475 S1475 S1475 S1492 S1492 S1492 S1492 S1495 S1495 S1495 S1495 S1495 S1495 S1495 S1541 S1541 S1541 S1541 S1541 V912_26 V912_47 V912_30 V912_41 V912_29 V912_14 V912_16 V912_25 V912_9 V912_8 V907_16 V907_25 V907_15 V907_19 V907_13 S12702014_1 S12702014_2 S12702014_6 S12702014_9 S12702014_8 S12702014_7 S12702014_5 S1349_7 S1349_9 S1349_17 S1349_6 S1349_10 S1475_18 S1475_17 S1475_19 S1475_12 S1475_8 S1475_35 S1475_24 S1475_20 S1492_23 S1492_42 S1492_27 S1492_22 S1495_14 S1495_43 S1495_55 S1495_32 S1495_58 S1495_30 S1495_34 S15412014_1 S15412014_4 S15412014_9 S15412014_13 S15412014_3 HM HM Del HM HM HM HM HM HM HM HM HM HM 39.03 10.88 2.84 1.89 1.89 1.89 1.21 0.80 0.53 0.53 1368.61 39.64 4.95 2.70 2.70 64.66 9.04 1.87 1.25 1.25 1.25 1.25 180.35 0.92 0.71 0.37 0.37 15.62 2.87 2.85 2.40 1.60 1.60 1.19 0.95 97.84 7.58 2.33 2.33 30.55 4.97 1.29 1.29 0.65 0.65 0.32 172.32 10.99 4.01 4.01 2.67 10.37% 12.11% 6.49% 3.68% 9.72% 4.01% 4.03% 4.71% 3.51% 3.51% na na 4.78% 4.78% 5.33% 5.26% 1.08% 4.86% na 4.40% na na 1.46% na 1.68% 1.68% 1.90% 7.97% 8.57% 8.25% 2.91% 2.45% na 4.46% 7.27% 4.04% na 1.72% 1.53% 5.62% 5.90% 2.06% 5.65% na 3.71% 2.58% 5.19% na 2.28% na na 41.7% 11.6% 3.0% 2.0% 2.0% 2.0% 1.3% 0.9% 0.6% 0.6% 88.8% 2.6% 0.3% 0.2% 0.2% 76.8% 10.7% 2.2% 1.5% 1.5% 1.5% 1.5% 95.5% 0.5% 0.4% 0.2% 0.2% 35.1% 6.4% 6.4% 5.4% 3.6% 3.6% 2.7% 2.1% 77.4% 6.0% 1.8% 1.8% 57.2% 9.3% 2.4% 2.4% 1.2% 1.2% 0.6% 80.4% 5.1% 1.9% 1.9% 1.2% Gened NSD1 MED26 POLM S1541 S1541 S1541 S1548 S1548 S1548 S1548 S1548 S1548 S1548 S1548 S1548 S1548 S1788 S1788 S1788 S1788 S1788 S1788 LIR01 LIR01 LIR01 LIR01 LIR01 LIR02 LIR02 LIR02 LIR02 LIR02 LIR02 LIR02 LIR03 LIR03 LIR03 LIR03 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 LIR04 a S15412014_10 S15412014_6 S15412014_27 S1548_24 S1548_31 S1548_22 S1548_43 S1548_34 S1548_44 S1548_48 S1548_28 S1548_33 S1548_38 S1788_3 S1788_29 S1788_1 S1788_2 S1788_6 S1788_16 LIR01_3 LIR01_4 LIR01_6 LIR01_2 LIR01_5 LIR02_8 LIR02_31 LIR02_1 LIR02_23 LIR02_19 LIR02_4 LIR02_18 LIR03_6 LIR03_7 LIR03_8 LIR03_18 LIR04_19 LIR04_26 LIR04_31 LIR04_96 LIR04_92 LIR04_66 LIR04_6 LIR04_32 LIR04_60 LIR04_24 LIR04_16 LIR04_13 LIR04_100 HM HM HM HM HM HM HM HM HM HM - 2.67 1.46 1.46 147.24 126.61 75.90 51.83 43.20 34.67 27.68 27.13 21.10 7.06 1.38 1.16 0.55 0.54 0.38 0.38 4.20 1.97 0.84 0.52 0.39 3.72 2.26 2.05 1.22 1.12 1.02 1.02 9.82 6.26 4.43 1.26 1.67 1.64 1.55 1.04 1.04 1.04 1.01 0.60 0.50 0.50 0.50 0.50 0.40 4.30% na na 4.89% 8.33% 9.73% na 9.65% 2.79% na 9.48% 3.60% 8.51% 1.37% 1.52% 1.16% na na na 13.50% 9.50% 2.72% 10.66% 4.81% 3.66% 5.62% na 3.86% 2.16% 3.47% 1.76% 4.96% 5.64% 5.75% 3.95% 6.37% 4.04% 4.34% na na 2.44% 1.80% 6.92% na 1.92% 3.19% 3.01% 6.63% 1.2% 0.7% 0.7% 18.8% 16.1% 9.7% 6.6% 5.5% 4.4% 3.5% 3.5% 2.7% 0.9% 15.9% 13.3% 6.3% 6.2% 4.4% 4.4% 35.39% 16.59% 7.06% 4.36% 3.26% 9.8% 6.0% 5.4% 3.2% 3.0% 2.7% 2.7% 23.5% 15.0% 10.6% 3.0% 6.3% 6.2% 5.9% 3.9% 3.9% 3.9% 3.9% 2.3% 1.9% 1.9% 1.9% 1.9% 1.5% Each unique HIV env sequence was given a unique identifier, indicated as “Participant ID_sequence number.” HM, G-to-A hypermutation pattern; Del, internal deletion and frameshift; -, no defect detected over the region sequenced. c Calculated as the average pairwise genetic distance between the indicated sequence and all plasma virus sequences. na, calculation not attempted for sequences showing G-to-A hypermutation. d Integration site as demonstrated by long-range PCR from the env forward primer to an integration site-specific reverse primer, confirmed by sequencing of the env portion of the PCR product. b Table S3. Related to Figures 6 and 7. HIV controllers who underwent LN biopsy. LIR01 CD4 count (cells/µL) 934 Plasma HIV RNA (copies/mL) <40 HLA-B Alleles B*1401/*5701 Biopsy Site Inguinal Cell Yield 3.74 x 107 CD4 T Cell HIV DNA Copies [47]a LIR02 551 267 B14/15 Inguinal 1.37 x 108 27859 LIR03 494 159 B57/8101 Axillary 5.50 x 108 90152 Inguinal 7 26189 ID LIR04 530 132 B15/40:12 9.50 x 10 a Bracketed value represents total HIV DNA copy number calculated based on detection of a single HIV DNA copy in all sorted material. This single detected copy showed G-to-A hypermutation. SUPPLEMENTAL REFERENCES Deng, W., B. S. Maust, D. C. Nickle, G. H. Learn, Y. Liu, L. Heath, S. L. Kosakovsky Pond, and J. I. Mullins. 2010. 'DIVEIN: a web server to analyze phylogenies, sequence divergence, diversity, and informative sites', Biotechniques, 48: 405-8. Kijak, G. H., M. Janini, S. Tovanabutra, E. E. Sanders-Buell, D. L. Birx, M. L. Robb, N. L. Michael, and F. E. McCutchan. 2007. 'HyperPack: a software package for the study of levels, contexts, and patterns of APOBEC-mediated hypermutation in HIV', AIDS Res Hum Retroviruses, 23: 554-7. Palmer, S., A. P. Wiegand, F. Maldarelli, H. Bazmi, J. M. Mican, M. Polis, R. L. Dewar, A. Planta, S. Liu, J. A. Metcalf, J. W. Mellors, and J. M. Coffin. 2003. 'New real-time reverse transcriptase-initiated PCR assay with single-copy sensitivity for human immunodeficiency virus type 1 RNA in plasma', J Clin Microbiol, 41: 4531-6. Pond, S. L., S. D. Frost, and S. V. Muse. 2005. 'HyPhy: hypothesis testing using phylogenies', Bioinformatics, 21: 676-9. Yukl, S. A., P. Li, K. Fujimoto, H. Lampiris, C. M. Lu, C. B. Hare, S. G. Deeks, T. Liegler, M. Pandori, D. V. Havlir, and J. K. Wong. 2011. 'Modification of the Abbott RealTime assay for detection of HIV-1 plasma RNA viral loads less than one copy per milliliter', J Virol Methods, 175: 261-5.
