Combination antiretroviral therapy controls but does not cure

HIV-1 infection due to a small fraction of cells harboring latent

viruses that can produce rebound viremia upon therapy

interruption. The circulating intact latent reservoir has been

documented by either VOAs, or by amplifying NFL proviral

sequences from DNA. Analysis of samples obtained in clinical

studies whereby individuals underwent ATI, showed little

overlap between latent viruses from VOAs pre-ATI, and

viruses isolated from plasma during viral rebound. To

determine whether intact proviruses from DNA are more

closely related to rebound viruses than those obtained from

VOAs, we assayed 12 individuals who underwent ATI after

infusion of broadly neutralizing anti-HIV-1 antibodies (bNAbs).

Analysis of samples obtained in clinical studies in which individuals underwent analytical treatment interruption (ATI) showed little if any overlap between circulating latent viruses obtained from outgrowth cultures and plasma rebound viruses. To determine whether intact proviruses amplified from DNA are more closely related to plasma rebound viruses than those obtained from qualitative and quantitative viral outgrowth assays (Q2VOAs), we assayed 12 individuals who underwent ATI after infusion of a combination of two monoclonal anti-HIV-1 antibodies. A total of 435 intact proviruses obtained from near full length (NFL) sequencing were compared with 650 latent viruses from Q2VOAs and 246 plasma rebound viruses. Although 39% of the intact NFL sequences overlap with sequences from Q2VOAs, the size of the reservoir estimated from NFL sequencing did not correlate with Q2VOAs. Intact proviruses documented by NFL sequencing showed no sequence overlap with rebound viruses, however, they appear to contribute to recombinant viruses found in plasma during rebound.

Relationship between intact HIV-1 proviruses and plasma rebound viruses

Ching-Lan Lu1,, Joy Pai1, Lilian Nogueira1, Pilar Mendoza1, Thiago Y. Oliveira1, John Barton2, Marina Caskey1, Mila Jankovic1, Michel C. Nussenzweig,1,3,*

1 Laboratory of Molecular Immunology, The Rockefeller University. 2 Department of Physics and Astronomy, University of California, Riverside. 3 Howard Hughes Medical Institute.

ABSTRACT:

INTRODUCTION:

RESULTS:

Figure 3. Comparison of reservoir measurements. Graph shows frequency per million CD4+ T cells at the preinfusion (wk-2) and week-12 (wk12) time points: gag+ proviruses (gag), env+ proviruses (env), near full-size proviruses (near full size) (left), intact proviruses (intact) (middle), and inducible proviruses (Q2VOA) (right). Each dot represents a different participant. Horizontal bars indicate median values. Statistical significance was determined using two-tailed Mann–Whitney U test.

CONCLUSIONS: 1.  The number of latent cells in the reservoir enumerated by

Q2VOA and NFL differ significantly. 2.  The overlap was most significant in individuals with a more

clonal and less diverse reservoir. 3.  Many of the rebound viruses appeared to be recombinants

from the circulating latent reservoir.

Figure 11. Recombination events between env sequences derived from Q2VOA, intact NFL, and rebound viruses. Circos plots depicting recombination events between env sequences derived from Q2VOA at wk-2 (blue), intact NFL at wk-2 (green), and rebound plasma SGA (red). Gray lines show the contribution of parent sequences to recombinant sequences. The thickness of the black outer bars represents the number of sequences obtained from that particular clone. Asterisks indicate the same env sequences between intact NFL and Q2VOA sequences.

Weeks -2 0 3 6 12 30

NFL PCR (intact proviruses)

ART ART interruption

3BNC117 10-1074

D2 ATI

Leukapheresis: assess the latent reservoir

PBMC CD4+ T cells Q2VOA (inducible proviruses)

DNA extraction

Rebound viremia

Figure 1. Study design. The combination of the two monoclonal anti-HIV-1 antibodies (3BNC117+10-1074) was administrated to 15 individuals undergoing ATI, 2 days before, and 3 and 6 weeks after ATI. Leukapheresis was performed 2 weeks before and 12 weeks after ATI, and plasma was obtained for single genome analysis at the time of rebound. NFL sequencing and Q2VOA were performed using CD4+ T cells obtained from the two leukapheresis samples.

Figure 2. NFL HIV-1 genomes sequencing strategy. NFL genomes were amplified from DNA aliquots containing a single HIV-1 genome. Only samples containing full-length env fragment were further processed and subjected to sequences analysis.

Figure 4. Correlation between frequency of intact proviruses and other reservoir measurements. Pearson correlation between frequency of intact proviruses and other reservoir measurements at wk-2 (circles) and wk12 (triangles) time points. Participant 9254 was excluded from the quantitative analysis because of inadequate sample availability.

Figure 6. Sequence analysis of near full-size proviruses. (A) Pie charts summarize sequence analysis at wk-2 and wk12. The number in the middle of the pie represents the number of near full-size proviruses sequenced. Pie slices depict the proportion of sequences for each participant that were intact or had different lethal defects. (B) Scatter plot showing the frequency and location of stop codons mediated by hypermutation (red circles) or by other mechanisms (green circles). The location of stop codons and indels was determined using HXB2 genome as reference.

Figure 5. Correlation between frequency of intact proviruses and weeks to rebound. Pearson correlation between weeks to rebound and frequency of intact proviruses (left), and between weeks to rebound and fold change in the frequency of intact proviruses before and after antibodies infusion (right).

0 2 4 6 8 100

10

20

30

40

number of intact proviruses

wee

ks to

reb

ound

0 1 2 310

20

30

40

fold change in the number of intact proviruses

wee

ks to

reb

ound

0 2 4 6 8 100

10

20

30

40

number of intact proviruses

wee

ks to

reb

ound

0 1 2 310

20

30

40

fold change in the number of intact proviruses

wee

ks to

reb

ound

P=0.69 P=0.07

Figure 7. Qualitative analysis of the circulating latent reservoir. Pie charts show the clonal distribution of env sequences derived from Q2VOA or NFL sequencing for each participant at wk-2 and wk12. The number in the middle indicates the total number of env sequences analyzed. White slices represent unique sequences isolated only once across both time points from both Q2VOA and NFL sequencing (singles), and colored slices represent identical sequences that appear more than once (clones). Blue arrows indicate clones that show significant differences between the time points.

Figure 8. Comparisons of the circulating latent reservoir and rebound viruses. Diagrams show the overlap between env sequences obtained from Q2VOA (blue), NFL sequencing (yellow), and rebound plasma SGA or PBMC outgrowth culture (red). The intersection of the NFL and Q2VOA circles represents the number of identical env sequences belonging to clones obtained by both methods.

Figure 9. Phylogenetic trees of env sequences. Phylogenetic trees of env sequences obtained from Q2VOA at wk-2 (green) and wk12 (blue), NFL at wk-2 (purple) and wk12 (orange), and rebound viruses from SGA or outgrowth cultures (red) from two representative participants.

Figure 10. Relationship between latent and rebound sequences. Histograms show the proportion of env sequences (y-axis) and number of mutations (x-axis). The blue bars represent the Hamming distance between rebound and NFL/Q2VOA sequences. The grey bars represent the predicted distance between rebound and NFL/Q2VOA sequences based on a simulation of mutation accumulation during the ATI period for each participant. Yellow bars represent the predicted distance between the rebound and NFL/Q2VOA sequences when the possibility of recombination is included.

Frequency of intact proviruses Fold change in the frequency of intact proviruses

FUNDING: Grant #UL1 TR001866 (NIH), Clinical and Translational Science Award program, The Rockefeller University Center for Clinical and Translational Science, Shapiro-Silverberg Fund for the advancement of translational research