spread of hiv-1 infection
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Spread of HIV-1 Infection
Formation of CladesRec0mbinant Strains
Differential rates of evolutionNovel strategies for development of
vaccines and therapies
HIV env in 8 men infected in the USA
Pt.7
Pt.9
HIV1U36148
HIV1U36015
HIV1U35980
HIV1U36073
HIV1U35926
HIVU95460
Pt.2
Patient #6 fromWolinsky et al.
Pt.5
Pt.3Pt.1Pt.8
Pt.6
10%
Subtype B (US)Subtype B (US)
1996
1992
10%
88
87
90
92
100
95
95
97
100
Diversity 1.5% higher in 1996 vs.
1992 (p< 0.001)
/A D
Central China
outbreak: B/C
Kaliningrad: B/A E
M Group
B
D
J
CHA
G
F
I
U
SIVcpz
SIVcpz
10%
O Group
N Group
Clades within the HIV-1 phylogenetic tree are becoming more obscure. Virus chimeras (recombinants) are becoming more evident and are significant in emerging epidemics
HIV-1 env Genes
Evolution from genomic chimerization (recombination)
One person is infected from two sources
Two virions from different sources infect the same cell
Chimera formation
The hybrid virion infects a new cell, reverse transcription occurs and RT switches between templates, creating a chimeric proviral genome
Each virion goes through reverse transcription, integration and produces viral RNA
One of each RNA is packaged in a single virion
HIVSC
HIVBa1aHIVSFAAA
HIVYU10XpNL43
0.01
635Days
PI
HIVSCHIVBa1a
HIVSFAAAHIVYU10X
pNL430.01
PATIENT BUNIQUE
PATIENT B
PATIENT A152/164Days PI
COMMON
887 Days
PI
HIVSCHIVBa1a
HIVSFAAAHIVYU10X
pNL43
0.01
Dual Infection and Virus Chimeras in UW PIC Pt. 14
Chimera
Evidence for Recombination
• Topological Incongruence along the Genome
• Bootscan Analysis
• Pairwise Distance Analysis
Topological incongruence of 3’genome sequences in MACS Pt. 6(3.0 yrs PI)
quartergenome
104109
18267855
3493
2830
4351
3260
62582
4954
57
0.00198%
100%
79%
72%
10443
10928
783026
1855
8260
325
9334
5462
5149
57
74%
0.01
gp41
10449
5109
6260
309343
51342818
2678
3255
8254
57
0.01
100%
78%
vif
1045754
18109
3043
2832
606255
3493
4951
5822678 0.01
94%71%
76%
nefU3
10454
5710918
822678
325
9334
5560
51622849
3043
0.01
97%
94%
5582
1045430
18109
2893
5734
492656078
3243
51
62
0.01vpu
What is bootscan analysis? A sliding window phylogenetic analysis that moves along
the genome and looks to see when (or if) the sequence being tested changes its clade association on the tree
e.g., The unknown grouping with clade 1 in the gag region and the unknown grouping with clade 2 in the env region
HIV-1-E
10
20
30
40
50
60
70
80
90
100
Boots
trap V
alu
e (
%)
P2
P1
90Rec
P2
P1
95
Rec
Boots
trap V
alu
e (
%) 100
50
0
Region of the Genome
Bootscan Example
500 bp500 bp
500 bp
Tree 1
Tree 3Tree 2
500 bp500 bp
500 bp
Tree 11
Tree 13Tree 12
Cautions for the interpretation of Bootscan Analysis The Bootscan analysis has several potential problems:
It normally uses neighbor joining to produce the tree topologies and often uses the evolutionary substitution models of F84 or Jukes and Cantor.
Neighbor joining has the potential to producing incorrect topologies and this potential can be enhanced by using substitution models that do not accurately describe the pattern of substitution in HIV
Bootscanning procedures look at a sliding window of sequences and produce a number describing the percent of time that the unknown groups with different clades.
The ability to decide if a recombination event has occurred is an arbitrary one. You have to decide if the line dips low enough and long enough to call it a recombination event. Using this technique is in no way a statistical measure of recombination events. There can be several random dips in the bootscan plot that are just random events.
Bootscann procedures have used sliding windows of varied size. Small windows can add to the problem of identifying the incorrect topology
using neighbor joining
HIV-1-E
0
10
20
30
40
50
60
70
80
90
100
vprenvpol
vif nefgag
Boots
trap V
alu
e (
%)
Bootscan: HIV-1-E & Simulations
HIV-1-E
0
10
20
30
40
50
60
70
80
90
100
vprenvpol
vif nefgag
Boots
trap V
alu
e (
%)
Bootscan: HIV-1-E & Simulations
What the Kashino-Hasegawa (KH) does It asks: “Are these two trees significantly different from
one another The comparison is done on the likelihood scores of the two
topologies It tests the null hypothesis that there is no statistical difference in
the likelihoods of the two trees.)
Overall, we suggest that the bootscann analysis should be used in conjunction with the KH test to try and statistically prove that a recombination event has taken place.
Bootscanning analysis can locate potential recombination events and the KH test can test the hypothesis of a recombination event taking place.
Intrasubtype
0
Intersubtype
5
10
15
20
25
30
35
40
gag
vprenvpol
vif nefSequen
ce D
ista
nce
(%
Div
erg
ence
)Pairwise Distance Analysis
A/E
B/D
Simulated DataSimulated DataReal DataReal Data
0
5
10
15
20
25
30
35
40
gag
vprenvpol
vif nef
Sequen
ce D
ista
nce
(%
Div
erg
ence
)Simulated Pairwise Distance Analysis
Comparing Subtypes A and E
Statistical tests of reported recombinant HIV strains (1)
Assigned Reported Virus Gene region subtype Test Score Best p value Significance
ZAM184 pol 3173-3973 C C 6690.35 (best) A 6747.78 57.43 0.0032 YES
env-nef 6511-9463 A A 32524.71 (best) C 32619.66 94.940.0001 YES
92RW009 pol-vpr 2573-6071 C C 28378.06 (best) A 28806.18 428.12 <0.0001 YES
env 6109-8195 A A 22831.00 (best) C 22967.94 136.94 <0.0001 YES
MAL gag 789-1883 A A 9571.50 (best) D 9713.38 141.87 <0.0001 YES
vpr-env 5559-8751 D D 33543.66 (best) A 33725.95 182.29 <0.0001 YES
IBNG gag 789-2292 A A 13962.19 (best) G 14049.00 86.80 <0.0001 YES
pol 2293-3173 G G 6442.77 (best) A 6468.69 25.92 0.0096 YES
93BR029 pol 2085-5096 B B 23128.62 (best) F 23276.56 147.94 <0.0001 YES
env 6220-8795 F F 27885.77 (best) B 28273.97 388.19 <0.0001 YES
Assigned Reported Virus Gene region subtype Test Score Best p value Significance
BFP90 gag 789-1583 A A 7309.43 (best) J 7346.98 37.54 0.0261 YES G 7338.20 28.77 0.0133 YES env 6261-7312 G G 12646.18 (best) J 12675.35 29.17 0.0225 YES A 12749.43 103.24 <0.0001 YES nef 8424-9463 J J 12280.21 (best) A 12335.76 55.55 0.0003 YES G 12327.69 47.47 0.005 YES
94CY032 gag 789-1883 A A 9611.10 (best) G 9682.93 71.82 <0.0001 YES I 9635.65 24.55 0.012 YES pol 2189-4673 I I 20009.92 (best) A 20140.33 130.41 <0.0001 YES G 20036.07 26.14 0.0423 YES env 6311-6773 G G 4386.51 (best) A 4404.26 17.75 0.0605 NOI 4387.39 0.88 0.9251 NO
Statistical tests of reported recombinant HIV strains (2)
The weight of the evidence indicates that E and A are separate phylogenetic groups and not recombinants
Nearly all other reported recombinants reported to date satisfy our criteria
Variations in the rate of evolution along the HIV-1 genome can resemble a recombination event
Conclusions
Lineages observed through time
Time or Sequence Divergence
Semi logarithmic Transformationof the number of lineages
time ( )present
Lo
g N
1
10
100
00.020.040.060.080.10.12
Time ()
Lin
eages (N
)
US B 1992
US Lineages through time
US B 1996
0
1
2
3
4
5
6
7
8
Year
Epidemic transform:
US’96
US ‘92
Thai EThai B
1976 1980 1984 1988 1992 1996
Time estimates are predicted from values assuming a substitution rate of 0.55%/year
m (T
ransformed N
umber of Lineages)
mt= ln n0-ntn0nt
US and Thai lineages through time
Epidemics in the US and Thailand are growing exponentially, with the Thai HIV-1B epidemic growing more rapidly
Coalescent dates for subtype B epidemics in the USA and Thailand are in accordance with epidemiologic data
Coalescent date for subtype E epidemic in Thailand is earlier than predicted from epidemiologic data. Potential reasons to account for this discrepancy:
Multiple introductions of HIV-1 (no evidence from phylogenetics) HIV-1 was undetected in Thailand for about 7 years Mutation rates for subtype E in the C2-C3 region are higher than
for subtype B
Conclusions
Novel approaches to HIV Prophylaxis
Ancestral Virus Reconstructions To minimize differences between vaccine
strain and infecting virus Epidemic-, subtype- and M group-specific Recovers antigenic recognition sites???
Antiretroviral Chemoprophylaxis Once-a-day pill provides protection??? Eventual induction of protective
immunity???
HIV-1-B env C2-V5 in the USA
HIV-1-B env C2-V5 in the USA
10%
88
87
90
92
100
95
95
97
100
~1992 (n=40)
~1996 (n=57)
The accumulation in the number of substitutions along lineages terminating in late timepoint sequences was 1.5% higher in 1996 vs. 1992 (p< 0.001)
Thus, temporally accurate strains are more divergent than an ancestor would be from any currently circulating strain
10 % Divergence
SIVCPZUS
SIVCPZGAB
Group O
Group NGroup M
A
B
C
D
E
F
AGAGI
J
G
H
Phylogenetic Classification of HIV-1
C- Clade Ancestor(s).
10%
ZF Z
RR FKKEZ
FZF
ZC
Z
FZ
ZFKZJ
F
F
H
E
G
J
F
H
K
N
H
A
Z
B
1
ZGG
b
Z
H
b
b
H G
b
H
G
b
bb
Ab
b
b
bbb
bb
bbb
b
bbb
bbb
bb
b
bb bb
bbb
bZ
G9Z Z
ZZZ ZZZ
Z
G
GR
9
Z
Z
Z
ZZ
ZG
b
H
Z Z
Z
Z
Z
b
Z
GG
G
GG
G
Z Z
M
G
GG
G
G
S
G
G
G
G
Z
M
GG
G
G
G
GG
Z
GG
GGG G
H
Z
M ZGGG
G
G H
Z
A
E
GZ Z
N GG G G
GG MZ F
ZGG
G Z H G
KK
GGS
A
b
C'
G
No C' aa340E350A429E
340E/350A350E/429E340E/429E340E/350A/429E
B BelgiumH BotswanaR BrazilF BurundiC Democratic Republic of the CongoJ DjiboutiE EthiopiaF France1 Gabonb IndiaA IsraelK KenyaM MalawiN New ZealandS SenegalS SomaliaE SwedenG RussiaG South AfricaZ TanzaniaH Uganda9 ZambiaZ Zimbabwe
Accuracy ofancestor predictions
MRCA estimate of 1000 bp region of gp120 97.4% identical to BK28 inoculum 98.2% when 5 convergent glycosylation sites are removed
5 changes
H915
H591
L35597U18033
MM316ZJMM132ZC
PHTBE5SIVT5
MNE170
186 H915M2191 H915M2190 H915M2
188 H915M2108 H915W6
111 H915W6114 H915W6
115 H915W6112 H915W6
118 H915W6109 H915W6
110 H915W6
43 H59155 H591
47 H591
56 H591
45 H59146 H591
48 H591
51 H59157 H59154 H59149 H591
50 H591
117 H915W6
(two macaques infected with the same clone-derived SIV inoculum)
19 H824 2
110 H915W6 2
118 H915W6 2
112 H915W6 2
115 H915W6 2
114 H915W
6 2
111 H915W6 2108
H91
5W6
2
186
H915M
29 2
190
H91
5M29
2
191
H91
5M29
2
188
H915M
29 2
109
H91
5W6
2
11 H
824
2
10 H
824
2
14 H
824
2
18 H
824
2
16 H824 2
21 H824 215 H824 220 H824 212 H824 2
9 H824 213 H824 2
41 H500 2
123
H615M
4 239 H
500 2
63 I580 2
134 H042M4 240 H500 237 H500 2
180 H615LN 269 I580 2
135 H042M4 2
129 H615M4 235 H500 265 I580 2
50 H
591
2
45 H
591
257
H59
1 2
51 H
591
2
56 H591 2
48 H591 249 H591 2
54 H591 2
46 H591 255 H591 2
140 H042M4 2
117 H915W6 2
58 I580 247 H
591 2
33 H500 2
138 H042M
4 2
136 H042M
4 2
133 H042M
4 2
137 H042M
4 2143 H
042M4 2
60 I580 2139 H
042M4 2
67 I580 259 I580 2
68 I580 2
61 I5
80 2
32 H500 2
43 H
500
212
1 H
615M
4 2
120
H61
5M4
2
119 H615M
4 2
128
H61
5M4
2
176
H61
5LN
217
7 H
615L
N 2
179
H61
5LN
218
3 H
615L
N 2
182
H61
5LN
217
2 H
042L
N 2
173
H04
2LN
2
174
H04
2LN
2
171
H042L
N 2
170
H042L
N 2
MNE170
SIV
T5
U18033
MM132ZC
MM
316ZJ
PH
TB
E5L35597
84 H914 2
88 H914 2
83 H914 293 H914 292 H914 2
85 H914 2
86 H914 2
91 H914 2
89 H914 2
87 H914 2
126 H615M4 2
125 H615M4 2
127 H615M4 2
124 H615M4 2
43 H591 2
34 H500 2
70 I580 262 I580 2
64 I580 2
66 I580 2
130 H615M4 2
42 H500 238 H500 236 H500 2
0.001 changes
MRCA estimate is 98.5% identical
to 1- F965M4
Accuracy of ancestor predictions(macaques infected with in vivo passaged SIV-BK28 inoculum [F965 strain])
% of consensus epitopes missingwithinHIV-1-B gp160 proteins
HIVELICGHIVNDKHIVZ2Z6
B_ancestor
HIVLAICG87USSG3X88USWR27
89SP061AUC18
AUC18MBCAUMBC200AUMBC925
AUMBCC18BAUMBCC54AUMBCC98AUMBCD36CNRL42CG
D31HIVBH102HIVCAM1
HIVF12CGHIVHAN2HIVJC16
HIVJRCSFHIVJRFL
HIVMCK1HIVMN
HIVNL43HIVNY5CG
HIVOYIHIVPV22
HIVRFHIVSF2CG
HIVWEAU160HIVYU10X
HIVYU2XMANC
NLACH32OANLACH320B
US89.6USDH123
USAD8
0 5 10 15 20
COS-7 mixed with GHOST-R5
COS-7 mixed with GHOST-X4
COS-7
COS-7 mixed with GHOST-R5
COS-7 mixed withGHOST-X4
Expression of HIV-89.6 Env:
Expression of ANC1 Env:
Antiretroviral ChemoProphylaxis
1000
2000
3000
0.1
1
10
100
1000
0 10 20 30 40
vag SIV
PMPA
vag HIV-2
Controls
PMPACD4
IUPM
Novel Therapeutic Approaches
Inhibitor plus Mutagen
P24 (ng/ml)750
500
250
0
Con
trol
AZT 3.2nm5-FdU25nM
5-FdU 25nmAZT 3.2nM 5-FdU
50nM
5-FdU 50nMAZT 3.2nM
HIV alone
-6 -5 -4 0 36 60 84 108
5-FdU AZT HIV1 WASH 5-FdU 5-FdU 5-FdU Harvest 5-FdU+AZT AZT AZT AZT
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