Is HIV-1 Losing Fitness Due to Genetic Entropy?

Is HIV-1 Losing Fitness Due to Genetic Entropy?

The views expressed in this paper are those of the writer(s) and are not necessarily those of the ARJ Editor or Answers in Genesis.


Evasion of cytotoxic T lymphocytes is a major driving force of HIV-1 evolution within a host. In a genetically homogenous population where some MHC class I types are dominant, repeated selection of escape mutants can cause HIV-1 to lose fitness. However, in a heterogenous population, reversions are more frequent and attenuation of HIV is slower. HIV-1 may have experienced adaptation to the human host after crossing species from primates, but immune selection and random drift are causing the viral genome to degenerate. Antiviral therapy further cuts into viral fitness, even when the drugs are resisted. HIV-1 is an important example which shows that genetic entropy is operating throughout the biological realm, even while meaningful genetic adaptations are occurring.


Human immunodeficiency virus type 1 (HIV-1), causative agent of the AIDS pandemic, is notorious for rapidly accumulating mutations due to its error-prone RNA polymerase and the absence of RNA repair enzymes. However, long-term maintenance of proviral DNA in resting host cells prevents the viral genome from rapid degeneration (Salgado et al. 2010). The diploid nature of the viral genome and frequent recombination also helps to preserve lentiviral lineages. The situation is analogous to the stability of diploid germline genomes in higher organisms because reproductive cells experience fewer cycles of cell division and undergo regular genetic recombination during meiosis. Nevertheless, we know that even higher genomes are degenerating (Sanford 2014).

Since its introduction into mankind in the beginning of the twentieth century (Sharp and Hahn 2011; Wertheim and Worobey 2009), HIV-1 has replicated in humans through a great many generations—which is comparable with deep evolutionary time in higher organisms (Behe 2007). Therefore, analyzing the evolution of HIV-1 through the past few decades offers a glimpse into the evolution of diploid cellular genomes through evolutionary time. The major forces that shape the HIV-1 genome are immune evasion, random drift, and antiretroviral therapy.

Racing to Stay Ahead of Host Antibodies

The impressive reproduction rate of HIV-1 (up to 1010 viral particles daily, Goering et al. 2013) affords strong selection. The most important selective force in untreated patients is host immunity. The infected host produces antibodies, especially antibodies against the surface glycoprotein, Env, which can neutralize extracellular viral particles (Wei et al. 2003). However, mutations in the env gene of HIV-1 quickly render the antibodies powerless. The host can produce new antibodies against the changing virus, but viral evolution is always faster than antibody development. Even though natural selection generally results in directional evolution, the random nature of antibody development and the recurrent nature of HIV mutation results in cyclic selection (Shriner et al. 2004). In the long run, antibodies do not drive the virus anywhere specific. Conceivably, some mutants have compromised replication capacity (fitness), but when the virus is transmitted into another host, antibody-driven mutations will likely revert as higher replication capacity is favored.

War of Attrition Against T lymphocytes

Fig. 1

Fig. 1. Presentation of viral peptides by an infected cell to a cytotoxic T lymphocyte, using the MHC-I complex. (Illustration by Kaiser 2008).

In HIV infection, antibodies are not nearly as protective as cytotoxic T lymphocytes (CTLs), which attack and kill HIV-infected cells. In contrast to the almost unlimited number of antibodies that a body can produce, the CTL response is limited by selective presentation of viral peptides (epitopes) on the surface of the infected cell, using MHC class I molecules as carriers (see fig. 1 after Kaiser 2008). Each person has a unique set of six types of MHC-I molecules. The uniqueness is due to diverse forms of MHC genes in the population. The MHC-I molecules of an infected individual presents a unique repertoire of HIV peptides to his/her CTL cells. However, the overall number of HIV peptides presentable by human MHC-I molecules is limited (a few hundred, see the official list in table 1, reviewed by Llano et al. 2013).

Epitope Protein HXB2 Location Subprotein HXB2 DNA Contig Subtype Species HLA
GELDRWEKI Gag 11-19 s>p17(11-19) 820..846   human B*4002
KIRLRPGGK Gag 18-26 s>p17(18-26) 841..867   human A*0301
IRLRPGGKK Gag 19-27 s>p17(19-27) 844..870 B human B*2705
RLRPGGKKK Gag 20-28 p17(20-28) 847..873   human A*0301
RLRPGGKKKY Gag 20-29 s>p17(20-29) 847..876 B human A*0301
RPGGKKKYKL Gag 22-31 s>p17(22-31) 853..882 B human B*5101
GGKKKYKLK Gag 24-32 s>p17(24-32) 859..885 B human B*0801
KYKLKHIVW Gag 28-36 s>p17(28-36) 871..897 B human A*2402
HLVWASREL Gag 33-41 s>p17(33-41) 886..912   human Cw*0804
LVWASRELERF Gag 34-44 s>p17(34-44) 889..921 B human A30
WASRELERF Gag 36-44 s>p17(36-44) 895..921 B human B*3501
ELRSLYNTV Gag 74-82 s>P17(74-82) 1009..1035   human B*0801
RSLYNTVATLY Gag 76-86 s>p17(76-86) 1015..1047 B human A*3002, B58, B63
SLYNTVATL Gag 77-85 s>p17(77-85) 1018..1044 B human A*0201, A*0202, A*0205
SLYNTVATLY Gag 77-86 s>p17(77-86) 1018..1047 B human A*0201
LYNTVATL Gag 78-85 s>p17(78-85) 1021..1044   human Cw14
LYNTVATLY Gag 78-86 s>p17(78-86) 1021..1047   human A*2092, B*4403
TLYCVHOK Gag 84-91 s>p17(84-91) 1039..1062   human A*1101
IEIKDTKEAL Gag 92-101 s>p17(92-101) 1063..1092   human B*4001
NSSKVSONY Gag 124-132 s>p17(124-132) 1159..1185 B human B*3501
VONLOGOMV Gag 135-143 s>p24(3-11) 1192..1218   human B13
HOAISPRTL Gag 144-152 s>p24(12-20) 1219..1245   human B*1510
OAISPRTLNAW Gag 145-155 s>p24(13-23) 1222..1254 B human A*2501
ISPRTLNAW Gag 147-155 s>p24(15-23) 1228..1254   human B*5701, B63
SPRTLNAWV Gag 148-156 s>p24(16-24) 1231..1257   human B*0702
VKVIEEKAF Gag 156-164 s>p24(24-32) 1255..1281   human B*1503
EEKAFSPEV Gag 160-168 s>p24(28-36) 1267..1293   human B*4415
KAFSPEVI Gag 162-169 s>p24(30-37) 1273..1296 B human B*5703
KAFSPEVIPMF Gag 162-172 s>p24(30-40) 1273..1305 B human B*5701, B*5703, B63
FSPEVIPMF Gag 164-172 s>p24(32-40) 1279..1305   human B57
EVIPMFSAL Gag 167-175 s>p24(35-43) 1288..1314 B human A*2601, A*2602, A*2603
VIPMFSAL Gag 168-175 s>p24(36-43) 1291..1314 B human Cw*0102
SEGATPODL Gag 176-184 s>p24(44-52) 1315..1341   human B*4001
TPODLNTML Gag 180-188 s>p24(48-56) 1327..1353 B human B*0702, B*3910, B*4201, B*8101, Cw*0802
TPODLNMML Gag 180-188 s>p24(48-56) 1327..1353 A human B53
TPYDINOML Gag 180-188 s>p24(48-56) 1327..1353 HIV-2 human B*5301
GHOAAMOML Gag 193-201 s>p24(61-69) 1366..1392 B human B*1510, B*3901
KETINEEAA Gag 202-210 p24(70-78) 1393..1419   human B*4002
ETINEEAAEW Gag 203-212 p24(71-80) 1396..1425   human A*2501
AEWDRVHPV Gag 210-218 p24(78-86) 1417..1443   human B*4002
HPVHAGPIA Gag 216-224 p24(84-92) 1435..1461   human B*3501, B7
GOMREPRGSDI Gag 226-236 p24(94-104) 1465..1497   human B13
TSTLOEOIGW Gag 240-249 p24(108-117) 1507..1536 B human B*5701,
NPPIPVGDIY Gag 253-262 p24(121-130) 1546..1575   human B*3501
PPIPVGDIY Gag 254-262 p24(122-130) 1549..1575 B human B*3051
EIYKRWII Gag 260-267 p24(128-135) 1567..1590 B human B*0801
RRWIOLGLOK Gag 263-272 p24(131-140) 1576..1605   human B*2703
KRWIILGLNK Gag 263-272 p24(131-140) 1576..1605 B human B*2705
GLNKIVRMY Gag 269-277 p24(137-145) 1594..1620 B human B*1501,
VRMYSPVSI Gag 274-282 p24(142-150) 1609..1635   human Cw18
RMYSPTSI Gag 275-282 p24(143-150) 1612..1635   human B*5201
YSPVSILDI Gag 277-285 p24(145-153) 1618..1644 CRF01_AE human Cw*0102
FRDYVDRFF Gag 293-301 p24(161-169) 1666..1692   human Cw18
FRDYVDRFYK Gag 293-302 p24(161-170) 1666..1695 B, D human B*1801
RDYVDRFFKTL Gag 294-304 p24(162-172) 1669..1701 A human A*2402
RDYVDRFYKTL Gag 294-304 p24(162-172) 1669..1701 B human B*4402
YVDRFYKTL Gag 296-304 p24(164-172) 1675..1701   human A*0207
YVDRFFKTL Gag 296-304 p24(164-172) 1675..1701   human B*1503,
DRFYKTLRA Gag 298-306 p24(166-174) 1681..1707 B human B*1402
AEOASODVKNW Gag 306-316 p24(174-184) 1705..1737 B human B*4402
AEOASOEVKNWM Gag 306-317 p24(174-185) 1705..1740   human Cw5
OASOEVKNW Gag 308-316 p24(176-184) 1711..1737 B human B*5301,
VKNWMTETL Gag 313-321 p24(181-189) 1726..1752 B human B*4801
DCKTILKAL Gag 329-337 p24(197-205) 1774..1800 B human B*0801
ACOGVGGPGHK Gag 349-359 p24(217-227) 1834..1866   human A*1101
GPGHKARVL Gag 355-363 p24(223-231) 1852..1878 B human B*0702
AEAMSOVTNS Gag 364-373 p2p7p1p6(1-10) 1879..1908   human B*4501
CRAPRKKGC Gag 405-413 p2p7p1p6(42-50) 2002..2028   human B14
TEROANFL Gag 427-434 p2p7p1p6(64-71) 2068..2091   human B*4002
ROANFLGKI Gag 429-437 p2p7p1p6(66-74) 2074..2100 B human B*4801, B13
FLGKIWPSYK Gag 433-442 p2p7p1p6(70-79) 2086..2115   human A*0201
KELYPLTSL Gag 481-489 p2p7p1p6(118-126) 2230..2256   human B*4001
NSPTRREL Pol 24-31 Gag/Pol-TF(24-31) 2154..2177   human Cw*0102
ITLWORPLV Pol 59-67 Protease(3-11) 2259..2285 A, B, D human A*6802,
DTVLEEWNL Pol 86-94 Protease(30-38) 2340..2366 C human A*6802
EEMNLPGRW Pol 90-98 Protease(34-42) 2352..2378   human B44
ROYDOILIEI Pol 113-122 Protease(57-66) 2421..2450   human B13
GKKAIGTVL Pol 124-132 Protease(68-76) 2454..2480   human B*1503
KAIGTVLV Pol 126-133 Protease(70-77) 2460..2483   human B57
LVGPTPVNI Pol 132-140 Protease(76-84) 2478..2504   human A*0201
TPVNIIGRNML Pol 136-146 Protease(80-90) 2490..2522   human B81
FPISPIETV Pol 155-163 Protease(99)-RT(8) 2547..2573 B human B*5401
IETVPVKL Pol 160-167 RT(5-12) 2562..2585   human B*4001
GPKVKOWPL Pol 173-181 RT(18-26) 2601..2627 B human B*0801
ALVEICTEM Pol 188-196 RT(33-41) 2646..2672 B human A*0201
ALVEICTEMEK Pol 188-198 RT(33-43) 2646..2678   human A*0301
KLVDFRELNK Pol 228-237 RT(73-82) 2766..2795   human A*0301
GIPHPAGLK Pol 248-256 RT(93-101) 2826..2852 B human A*0301
TVLDVGDAY Pol 262-270 RT(107-115) 2868..2894   human B*3501
VPLDEDFRKY Pol 273-282 RT(118-127) 2901..2930   human B*3501
YTAFTIPSV Pol 282-290 RT(127-135) 2928..2954   human A2
TAFTIPSI Pol 283-290 RT(129-135) 2931..2954   human B*5101
NETPGIRYOY Pol 292-301 RT(137-146) 2958..2987   human B18
TRYOYNVL Pol 297-304 RT(142-149) 2973..2996   human B*1401
LPOGWKGSPA Pol 304-313 RT(149-158) 2994..3023 B human B*5401
SPAIFOSSM Pol 311-319 RT(156-164) 3015..3041   human B7
AIFOSSMTK Pol 313-321 RT(158-166) 3021..3047 B human A*0301,
KONPDIVIY Pol 328-336 RT(173-181) 3066..3092 B human A*3002,
NPEIVIYOY Pol 330-338 RT(175-183) 3072..3098   human B18
HPDIVIYOY Pol 330-338 RT(175-183) 3072..3098 B human B*3501
VIYOYMDDL Pol 334-342 RT(179-187) 3084..3110 B human A*0201
IEELROHLL Pol 357-365 RT(202-210) 3153..3179 B human B*4001
IVLPEKDSW Pol 399-407 RT(244-252) 3279..3305   human B*5701
LVGKLNWASOIY Pol 415-426 RT(260-271) 3327..3362   human B*1501
KLNWASOIY Pol 418-426 RT(263-271) 3336..3362 B human A*3002
OIYPGIKVR Pol 424-432 RT(269-277) 3354..3380 B human A*0301
YPGIKVROL Pol 426-434 RT(271-279) 3360..3386 B human B*4201
IPLTEEAEL Pol 448-456 RT(293-301) 3426..3452   human B*3501,
ILKEPVHGV Pol 464-472 RT(309-317) 3474..3500 B human A*0201
ILKEPVHGVY Pol 464-473 RT(309-318) 3474..3503 B human B*1501,
GOGOWTYOI Pol 488-496 RT(333-341) 3546..3572   human B13
IYOEPFKNLK Pol 496-505 RT(341-350) 3570..3599 B human A*1101
RMRGAHTNDV Pol 511-520 RT(356-365) 3615..3644   human A*3002
RMRGAHTNDVK Pol 511-521 RT(356-366) 3615..3647   human A*0301
IAMESIVIW Pol 530-538 RT(375-383) 3672..3698   human B*5801
PIOKETWETW Pol 547-556 RT(392-401) 3723..3752 B human A*3201
GAETFYVDGA Pol 591-600 RT(436-445) 3855..3884   human A*6802
ETFYVDGAANR Pol 593-603 RT(438-448) 3861..3893   human A66
ETKLGKAGY Pol 604-612 RT(449-457) 3894..3920   human A*2601
IVTDSOYAL Pol 650-658 RT(495-503) 4032..4058   human Cw*0802
VTDSOYALGI Pol 651-660 RT(496-505) 4035..4064   human B*1503
OIIEOLIKK Pol 675-683 RT(520-528) 4107..4133 B human A*1101
LFLDGIDKA Pol 715-723 RT(560)-Integrase(8) 4227..4253   human B81
LPPIVAKEI Pol 743-751 Integrase(28-36) 4311..4337   human B*4201
THLEGKIIL Pol 781-789 Integrase(66-74) 4425..4451   human B*1510
HVASGYIEA Pol 793-801 Integrase(78-86) 4461..4487 B human B*5401
IEAEVIPAET Pol 799-808 Integrase(84-93) 4479..4508 B human B*4002
HTDNGSNF Pol 829-836 Integraser(114-121) 4569..4592   human Cw5
STTVKAACWW Pol 838-847 Integrase(123-132) 4596..4625   human B57
IOOEFGIPY Pol 850-858 Integrase(135-143) 4632..4658   human B*1503
VRDOAEHL Pol 880-887 Integrase(165-172) 4722..4745   human Cw18
KTAVOMAVF Pol 888-896 Integrase(173-181) 4746..4772   human B*5701
AVFIHNFKRK Pol 894-903 Integrase(179-188) 4764..4793 B human A*0301,
FKRKGGIGGY Pol 900-909 Integrase(185-194) 4782..4811   human B*1503
KRKGGIGGY Pol 901-909 Integrase(186-194) 4785..4811   human B*2705
GERIVDII Pol 912-919 Integrase(197-204) 4818..4841 B human B*4002
IIATDIOTK Pol 918-926 Integrase(203-211) 4836..4862 B human A11
KIONFRVYY Pol 934-942 Integrase(219-277) 4884..4910   human A*3002
VPRRKAKII Pol 975-983 Integrase(260-268) 5007..5033   human B42
RKAKIIRDY Pol 978-986 Integrase(263-271) 5016..5042   human B*1503
RIRTWKSLVK Vif 17-26   5089..5118 B human A*0301
HMYISKKAK Vif 28-36   5122..5148   human A*0301
ISKKAKGWE Vif 31-39   5131..5157   human B*5701
HPRVSSEVHI Vif 48-57   5182..5211   human B*0702
IPLGDAKLII Vif 57-66   5209..5238   human B51
WHLGHGVSI Vif 79-87   5275..5301   human B*1510
WHLGOGVSI Vif 79-87   5275..5301   human B*3801
LGHGVSIEW Vif 81-89   5281..5307   human B*5703
LADOLIHLHY Vif 102-111   5344..5373   human B*1801
KTKPPLPSVKK Vif 158-168   5512..5544   human A*0301
EAVRHFPRI Vpr 29-37   5643..5669   human B51
AVRHFPRIW Vpr 30-38   5646..5672   human B*5701
VRHFPRIWL Vpr 31-39   5649..5675   human B27
FPRIWLHGL Vpr 34-42   5658..5684   human B*0702,
ETYGDTWTGV Vpr 48-57   5700..5729   human A*6802
DTWAGVEAIIR Vpr 52-62   5712..5744   human A*6801
AIIRILOOL Vpr 59-67   5733..5759 B human A*0201
CCFHCOVC Tat 30-37   5918..5941   human Cw12
FOTKGLGISY Tat 38-47   5942..5971   human B*1503
ITKGLGISYGR Tat 39-49   5945..5977   human A*6801
KAVRLIKFLY Rev 14-23   6009..6038 B human B*5701,
OAVRIIKILY Rev 14-23   6009..6038 C human B*5703
ERILSTYLGR Rev 57-66   8471..8500   human A*0301
RPAEPVPLOL Rev 66-75   8498..8527   human B7
SAEPVPLOL Rev 67-75   8501..8527 B human Cw*0501
YRLGVGALI Vpu 5-13   6074..6100 C human Cw18
EYRKILROR Vpu 29-37   6146..6172   human A*3303
RVKEKYOHL gp160 2-10 gp120(2-10)        
AENLWVTVY gp160 31-39 gp120(31-39) 6315..6341   human B*1801,
AENLWVTVYY gp160 31-40 gp120(31-40) 6315..6344   human B*4402
TVYYGVPVWK gp160 37-46 gp120(37-46) 6333..6362 B human A*0301
VPVWKEATTT gp160 42-51 gp120(42-51) 6348..6377   human B*5501
VPVWKEATTTL gp160 42-52 gp120(42-52) 6328..6380   human B*3501
LFCASDAKAY gp160 52-61 gp120(52-61) 6378..6407 B human A*2402
KAYETEVHNVW gp160 59-69 gp120(59-69) 5399..6431   human B58
YETEVHNVW gp160 78-86 gp120(78-86) 6456..6482   human B*3501
MHEDIISLW gp160 104-112 gp120(104-112) 6534..6560   human B*3801
SVITOACPK gp160 199-207 gp120(199-207) 6819..6845   human A*1101
SFEPIPIHY gp160 209-217 gp120(209-217) 6849..6875 B human A*2902
CAPAGFAIL gp160 218-226 gp120(218-226) 6876..6902   human Cw1
RPNNNTRKSI gp160 298-307 gp120(298-307) 7116..7145 B human B*0702
HIGPGRAFY gp160 310-318 gp120(310-318) 7152..7178   human A*3002
RGPGRAFVTI gp160 311-320 gp120(311-320) 7155..7184   human A*0201
EIIGDIROAY gp160 321-330 gp120(321-330) 7185..7214   human A*2501
SFNCGGEFF gp160 375-383 gp120(375-383) 7374..7373 B human B*1516,
LPCRIKOII gp160 416-424 gp120(416-424) 7470..7496 B human B*5101
RIKOIINMW gp160 419-427 gp120(419-427) 7479..7505 B human A*3201
RAIEAOOHL gp160 557-565 gp41(46-54) 7893..7919   human Cw*0304,
RAIEAOOHM gp160 557-565 gp41(46-54) 7893..7919   human Cw8
OTRVLAIERYL gp160 577-587 gp41(66-76) 7953..7985 C human B*5802
ERYLKDOOL gp160 584-592 gp41(73-81) 7974..8000   human B*1402
RYLKDOOLL gp160 585-593 gp41(74-82) 7977..8003 B human A*2402,
YLKDOOLL gp160 586-593 gp41(75-82) 7980..8003   human B*0801
TAVPWNASW gp160 606-614 gp41(95-103) 8040..8066 B human B*3501
VFAVLSIVNR gp160 698-707 gp41(187-196) 8316..8345   human A*3303
IVNRNROGY gp160 704-712 gp41(193-201) 8334..8360 B human A*3002
RLRDLLLIVTR gp160 770-780 gp41(259-269) 8532..8564 B human A*0301,
IVTRIVELL gp160 777-785 gp41(266-274) 8553..8579 B human A*6802
GRRGWEALKY gp160 786-795 gp41(275-284) 8580..8609 B human B*2705
RRGWEVLKY gp160 787-795 gp41(276-284) 8583..8609   human A*0101
KYCWNLLOY gp160 794-802 gp41(283-291) 8604..8630 B human A*3002
OELKNSAVSL gp160 805-814 gp41(294-303) 8637..8666 B human B*4001
SLLNATDIAV gp160 813-822 gp41(302-311) 8661..8690 B human A*0201
LLNATDIAV gp160 814-22 gp41(303-311) 8664..8690 B human A*0201
EVAORAYR gp160 831-838 gp41(320-327) 8715..8738   human A*3303
IPRRIROGL gp160 843-851 gp41(332-340) 8751..8777 B human B*0702
RIROGLERA gp160 846-854 gp41(335-343) 8760..8786   human A*0205
ROGLERALL gp160 848-856 gp41(337-345)        
WPTVRERM Nef 13-20   8833..8856 B human B*0801
RMRRAEPAA Nef 19-27   8851..8877   human B62
LEKHGAITS Nef 37-45   8905..8931   human B*4001,
FPVTPOVPL Nef 68-76   8998..9024   human B*0702
FPVTPOVPLR Nef 68-77   8998..9027 B human B+0702
TPOVPLRPM Nef 71-79   9007..9033 B human B*0702
RPOVPLRPM Nef 71-79   9007..9033   human B*4201,
RPOVPLRPMTY Nef 71-81   9007..9039 B human B35
OVPLRPMTYK Nef 73-82   9013..9042 B human A*0301,
VPLRPMTY Nef 74-81   9016..9039 B human B*3501
PLRPMTYK Nef 75-82   9019..9042 B human A*1101
LRPMTYKAA Nef 76-84   9022..9048 B human B*2703
RPMTYKAAL Nef 77-85   9025..9051 B human B*0702
KAAFDLSFF Nef 82-90   9040..9066   human B*5703,
KAAVDLSHFL Nef 82-91   9040..9069   human Cw8
GAFDLSFFL Nef 83-91   9043..9069   human A*0205
AAFDLSFFL Nef 83-91   9043..9069   human B*5703
AAVDLSHFL Nef 83-91   9043..9069 B human Cw*0802
AALDLSHFL Nef 83-91   9043..9069   human Cw3
AVDLSHFLK Nef 84-92   9046..9072 B human A*0301,
FLKEKGGL Nef 90-97   9064..9087 B human B*0801
KEKGGLEGL Nef 92-100   9070..9096 B human B*4001,
RRODILDLWI Nef 105-114   9109..9138 B human B*2705
RRODILDLWVY Nef 105-115   9109..9141   human B18
KROEILDLWVY Nef 105-115   9109..9141   human Cw7
RODILDLWI Nef 106-114   9112..9138   human B13
RODILDLWV Nef 106-114   9112..9138   human B*1302
HTOGYFPDW Nef 116-124   9142..9168   human B*5703,
TOGYFPDWONY Nef 117-127   9145..9177 B human B*1501
YFPDWONYT Nef 120-128   9154..9180 B human A29,
FPDWONYTP Nef 121-129   9157..9183 B human B*5401
YTPGPGIRY Nef 127-135   9175..9201   human B57, B63
TPGPGVRYPL Nef 128-137   9178..9207 B human B*0702,
TRYPLTFGW Nef 133-141   9193..9219   human A33
RYPLTFGW Nef 134-141   9196..9219 B human A*2402
YPLTFGWCY Nef 135-143   9199..9225 B human B*1801,
YPLTFGWCF Nef 135-143   9199..9225   human B53
PLTFGWCYKL Nef 136-145   9202..9231 B human A*0201
LTFGWCFKL Nef 137-145   9205..9231   human B57, B63
VLEWRFDSRL Nef 180-189   9334..9363 B human A*0201
WRFDSRLAF Nef 183-191   9343..9369   human B*1503

During the early stages of infection, the CTL response successfully brings HIV replication under control, but some viruses always escape by mutating CTL targets. If the HIV peptides presented by the MHC-I molecules happen to be located on viral protein domains critical for replication, escape mutants will suffer lowered replication capacity (fitness loss). In such patients, there will be a long war of attrition between the immune system and the virus (Boutwell, Rowley, and Essex 2009). On the other hand, if the HIV peptides presented by the MHC-I molecules are few in number and/or located on less critical regions of HIV proteins, the virus will escape the CTLs easily without significant fitness cost. The virus will destroy infected T lymphocytes, overpower the CTLs, and cause AIDS after a short latency period (Yue et al. 2015).

Most patients are infected by a single viral particle or a single infected cell (Keele et al. 2008). The virus rapidly diversifies within the host. Subsequent immune selection curbs the rate of viral diversification (see fig. 2, after Maldarelli et al. 2013). Contrary to Darwinian thinking, the replication capacity of the early viral population is high, and quickly declines along an exponential curve (see fig. 3, after Arnott et al. 2010), presumably due to accumulation of escape mutants with compromised fitness. However, as recognizable CTL targets dwindle, and as CD4+ T cells are killed by the virus, the virus gradually diversifies again, with concurrent increase in replication capacity and plasma viral load (Arnott et al. 2010; Maldarelli et al. 2013; Troyer et al. 2005). The relationship between viral fitness, diversity, and plasma viral load is schematically illustrated in Fig. 4.

Fig. 2

Fig. 2. Nonlinear accumulation of HIV diversity over time. Overall diversity was determined from alignments of pro-pol sequences. Multiple samples from the same patient are shown with the same color. Patients for whom only a single sample was available for analysis are shown in black. After Fig. 2A of Maldarelli et al. 2013 at http://www.

Fig. 3

Fig. 3. Viral fitness of baseline isolates obtained from acute HIV-1 infection subjects (PULSE) and from early chronic HIV-1 infection subjects (PHAEDRA) relative to the stage of seroconversion, after Fig. 10 of Arnott et al. 2010 at

Fig. 4

Fig. 4. Viral diversity, fitness, and plasma viral load during HIV-1 infection. The diversity curve is based on Fig. 2A of Maldarelli et al. 2013. The fitness curve is based on Fig. 10 of Arnott et al. 2010. The viral load curve is based on Fig. 4 of an article on the website of the National Institute of Allergy and Infectious Diseases entitled “The Relationship Between the Human Immunodeficiency Virus and the Acquired Immunodeficiency Syndrome”.

Long-Term Evolution

If a population is genetically homogenous, individuals will have similar MHC phenotypes and their CTLs would target similar HIV peptides. Passage of the virus through the population will consistently select for the same immune escape mutations. Although the resulting mutants are adapted to protective CTLs, their replication capacity will be compromised. This is indeed found in Japan and in Africa (Nomura et al. 2013; Payne et al. 2014). In Japan, a reduction of replication capacity was observed in subtype B of HIV-1 between 1995 and 2009. Meanwhile, MHC A*24, a common protective MHC type, lost its protective effect in the population. The fitness loss of HIV-1 was associated with mutations in the gag and pol genes. Similarly, viral replication capacity in Botswana was lower than in South Africa because the epidemic in Botswana had been ongoing for a longer period of time, resulting in a more attenuated virus. Interestingly, the average CD4 cell count in treatment-naïve Botswanan patients was lower than in South African patients, i.e., decreased fitness is associated with increased virulence, in agreement with previous analysis of the Nef protein (Liu 2015). The African study also revealed adaptation of HIV-1 to certain MHC types, particularly to the well-known protective types, B*57 and B*58.01.

On the other hand, the North American population is more varied in MHC types. Therefore, when HIV-1 is transmitted into a new host, it is less likely to encounter the same selective pressure as in the previous host. Thus immune escape mutations are more likely to revert in favor of maximum replication capacity. After several decades of interhost evolution in North America, the viral genes have become more diverse, as a result of mutations driven by diverse CTL responses (Cotton et al. 2014, see star-like phylogeny in fig. 5). There are small yet significant increases in the frequency of escape mutations against protective MHC types. However, the study did not find a significant change in replication capacity, although the fitness of modern viruses is distributed over a broader range of values. The ability of the Nef protein to down-regulate CD4 and MHC molecules was gradually optimized to the level of the inferred ancestral virus. It is interesting that the improvement of Nef activities since 1979 is reaching the maximum (notice asymmetrical distribution of dots in Fig. 6 after Cotton et al. 2014, with more dots below the average values than above). Optimization of Nef functions may also account for the increase in viral load levels and decreased CD4 counts in HIV-1 infected patients in the Netherlands (Gras et al. 2009).

Fig. 5

Fig. 5. Diversity of North American Gag and Nef sequences from historic (1979–1989) and modern (2000+) eras, after Fig. 1 of Cotton et al. 2014.

Fig. 6 A

Fig. 6 A. CD4 downregulation activities of the inferred ancestral Nef sequence (mean±S.E.M. of eight replicate measurements) and patient-derived Nef clones from various eras (one per patient, representing the mean of triplicate measurements). CD4 downregulation values are normalized to that of HIV subtype B control Nef strain SF2, such that a value of 1 indicates CD4 downregulation activity equal to that of SF2 while values>1 and <1 indicate activities higher or lower than SF2 respectively. Modern Nefs exhibited significantly higher CD4 downregulation activity compared to historic Nefs (Kruskal-Wallis p<0.0001).

Fig. 6 B

Fig. 6 B. SF2-normalized HLA class I downregulation activities of inferred ancestral (mean±S.E.M. of 8 replicate measurements) and patient-derived Nef sequences (one per patient, mean of triplicate measurements). Modern Nefs exhibited significantly higher HLA downregulation activity compared to historic Nefs (Kruskal-Wallis p<0.0001). After Figs. 8B and 8C of Cotton et al. 2010 at

Random Drift

During the early stages of infection, one founder virus expands exponentially to establish a quasispecies. The process is largely random and subject to genetic drift (Keele et al. 2008). The resulting population provides the basis on which immune selection subsequently acts. Even with strong CTL selection during the first three months of infection, a study by Abrahams et al. (2013) failed to reveal significant differences in the rates of HIV diversification between rapid and slow progressors, indicating much diversification is not attributable to immune selection. Maldarelli et al. (2013) discovered that even non-synonymous mutations may be nearly-neutral and immune to selection.

Pandit and Sinha (2011) analyzed the evolution of codon usage by HIV-1 and compared the codon preferences of the virus and that of the human host. They found the differences in codon preferences between the virus and the host narrowed significantly between the early 1980s and the late 1990s, indicating a period of adaptation between the two species over 15 years. However, the trend changed since then. Codon usage evolution of HIV-1 became stagnant since the 1990s and in fact is drifting away from preferred codon usage of the human species (see fig. 7, after Pandit and Sinha 2011).

Fig. 7

Fig. 7. Temporal variation in the codon usage pattern of HIV-1 genes with respect to human host, after Fig. 5 of Pandit and Sinha, 2011 at

The Effect of Antiretroviral Therapy

The above discussion did not consider antiviral treatment. However, in developed countries, antiretroviral therapy has become the primary engine in HIV evolution, driving the virus toward extinction.

Antiretroviral drugs are designed to suppress viral replication, but are frequently resisted by HIV-1 through target mutations. However, drug-resistant mutations are associated with reduced replication capacity, compromised transmissibility, and lower plasma viral load (Machouf et al. 2006; Pingen et al. 2014). For this reason, many clinicians see a value in maintaining sup-optimal therapy when alternative drugs are not available.

There is an estimate that the in vivo mutation rate of HIV-1 is close to its error threshold (Tripathi et al. 2012). Therefore it is feasible to use drugs that increase the mutation rate in reverse transcription of RNA to drive the virus toward error-catastrophe.

How Far Has HIV-1 Degenerated?

Since the AIDS pandemic started three decades ago, the evolution of HIV-1 has been carefully observed and systematically documented. This is especially true for subtype B, the dominant subtype in developed countries. A quick comparison of historical and modern sequences revealed continuous divergence within subtype B. Nucleotide identity decreased from 94.8 ± 0.94% among genomic sequences collected between 1982 and 1985, to 90.0 ± 1.35% among sequences collected between 2011 and 2013. The consensus sequences also differed by about 4%.1 Nucleotide identity between subtypes is 70–90% (See review by Ariën, Vanham, and Arts 2007). If all subtypes of group M indeed descended from a common ancestor transmitted to mankind in the early 1900s, the degeneration rate of HIV-1 would be comparable to that of the H1N1 strain of the influenza virus, which mutated more than 15% of its genome in about a century (see Carter and Sanford 2012. The genome sizes of the two viruses are comparable). While the original H1N1 influenza virus has gone extinct, HIV-1 sill thrives in various forms. This may have to do with the persistent nature of HIV infection. However, in highly prevalent areas of Africa, as well as globally, subtype C, which has a lower replication capacity, is replacing other subtypes due to its relatively higher transmissibility and longer survival of the host (Ariën, Vanham, and Arts 2007).

Nonetheless, HIV-1-associated mortality is still higher in subtype C-dominant areas than in subtype B-dominant areas, presumably because the latter are wealthier countries where antiviral therapies are more accessible (Ortblad, Lozano, and Murray 2013). This indicates that viral attenuation is not the primary cause of the currently observed decline in AIDS mortality.


HIV-1 adapts to host codon preferences, immune pressure, and antiretroviral drugs through mutation. However, most such adaptive mutations carry a fitness cost. Even with diploidy, genome recombination, and persistence in the DNA form, HIV-1 appears to be losing fitness. By coreceptor switch and optimization of viral genes for maximum replication efficiency, the virus may gain virulence, but high virulence compromises its preservation in the human population. While the less virulent subtype C seems to be taking over the epidemic, antiretroviral therapies are driving down the fitness of all subtypes of HIV-1.


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  1. Complete or nearly complete proviral genomes of subtype B were retrieved from the HIV Sequence Database of the Los Alamos National Laboratory and aligned with Clustal Omega. Where there were multiple sequences from the same patient, only one sequence per patient was chosen. There were altogether 24 sequences from different patients, 17 of which from the United States, available to represent the period between 1982 and 1985. Thirty-three sequences between 2011 and 2013 (23 from the U.S.) were used to represent modern genomes. Using only U.S. sequences yielded similar results (Nucleotide identity of 94.9±0.90% among historical sequences, and 90.5±1.48% among modern sequences).

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