HIV-1 superinfection can occur in the presence of broadly neutralizing antibodies

A Systematic Molecular Epidemiology Screen Reveals Numerous Human Immunodeficiency Virus (HIV) Type 1 Superinfections in the Swiss HIV Cohort Study

BACKGROUND

Studying human immunodeficiency virus type 1 (HIV-1) superinfection is important to understand virus transmission, disease progression, and vaccine design. But detection remains challenging, with low sampling frequencies and insufficient longitudinal samples.

METHODS

Using the Swiss HIV Cohort Study (SHCS), we developed a molecular epidemiology screening for superinfections. A phylogeny built from 22 243 HIV-1 partial polymerase sequences was used to identify potential superinfections among 4575 SHCS participants with longitudinal sequences. A subset of potential superinfections was tested by near-full-length viral genome sequencing (NFVGS) of biobanked plasma samples.

RESULTS

Based on phylogenetic and distance criteria, 325 potential HIV-1 superinfections were identified and categorized by their likelihood of being detected as superinfections due to sample misidentification. NFVGS was performed for 128 potential superinfections; of these, 52 were confirmed by NFVGS, 15 were not confirmed, and for 61 sampling did not allow confirming or rejecting superinfection because the sequenced samples did not include the relevant time points causing the superinfection signal in the original screen. Thus, NFVGS could support 52 of 67 adequately sampled potential superinfections.

CONCLUSIONS

This cohort-based molecular approach identified, to our knowledge, the largest population of confirmed superinfections, showing that, while rare with a prevalence of 1%-7%, superinfections are not negligible events.

HIV-1 antibodies in prevention of transmission

PURPOSE OF REVIEW

To present the data that suggest that antibodies to HIV may prevent HIV-1 infection.

RECENT FINDINGS

Many human monoclonal broadly neutralizing antibodies (bnAbs) have been isolated over the last decade. Numerous experiments of passive immunization in nonhuman primate models have allowed to accumulate strong evidences that bnAbs, opposed to nonneutralizing antibodies, are the best candidates to prevent HIV-1 infection. bnAbs counteract HIV-1 by both blocking the virus at the portal of entry and clearing rapidly viral foci established at distance after dissemination of the virus following infection. Cocktails of bnAbs or modified bi/trispecific antibodies will be necessary to counter the large and evolving antigenic diversity of the HIV-1 species. Two large multicenter phase IIb clinical trials have been initiated. Even if they are not conducted with the most recent and most potent bnAb, the results which are expected in 2022 will inform us on the real potency of bnAbs at preventing HIV-1 acquisition in the real life.

SUMMARY

If these trials demonstrate the efficacy of bnAbs, they will open the trail toward new strategies for preexposure prophylaxis, eventually postexposure prophylaxis and prevention of mother-to-child transmission.

Reduced frequency of HIV superinfection in a high-risk cohort in Zambia

Rates of HIV-1 superinfection, re-infection with a genetically distinct virus despite HIV-1 specific immune responses, vary in different risk populations. We previously found the rates of superinfection were similar to primary HIV infection (PHI) in a Zambian heterosexual transmission cohort. Here, we conduct a similar analysis of 47 HIV-positive Zambians from an acute infection cohort with more frequent follow-up, all infected by non-spousal partners. We identified only one case of superinfection in the first two years, significantly fewer than in our previous study, which was likely due to increased counseling during acute infection and an overall population-wide decline in factors associated with HIV transmission. The predominant virus detected after superinfection was a recombinant of the transmitted founder (TF) and the superinfecting strain. The superinfected individual mounted a neutralizing antibody response to the primary TF virus, which remained TF-specific over time and even after superinfection, did not neutralize the superinfecting variant.

Model-based estimation of superinfection prevalence from limited datasets

Humans can be infected sequentially by different strains of the same virus. Estimating the prevalence of so-called 'superinfection' for a particular pathogen is vital because superinfection implies a failure of immunologic memory against a given virus despite past exposure, which may signal challenges for future vaccine development. Increasingly, viral deep sequencing and phylogenetic inference can discriminate distinct strains within a host. Yet, a population-level study may misrepresent the true prevalence of superinfection for several reasons. First, certain infections such as herpes simplex virus (HSV-2) only reactivate single strains, making multiple samples necessary to detect superinfection. Second, the number of samples collected in a study may be fewer than the actual number of independently acquired strains within a single person. Third, detecting strains that are relatively less abundant can be difficult, even for other infections such as HIV-1 where deep sequencing may identify multiple strains simultaneously. Here we develop a model of superinfection inspired by ecology. We define an infected individual's richness as the number of infecting strains and use ecological evenness to quantify the relative strain abundances. The model uses an EM methodology to infer the true prevalence of superinfection from limited clinical datasets. Simulation studies with known true prevalence are used to contrast our EM method to a standard (naive) calculation. While varying richness, evenness and sampling we quantify the accuracy and precision of our method. The EM method outperforms in all cases, particularly when sampling is low, and richness or unevenness is high. Here, sensitivity to our assumptions about clinical data is considered. The simulation studies also provide insight into optimal study designs; estimates of prevalence improve equally by enrolling more participants or gathering more samples per person. Finally, we apply our method to data from published studies of HSV-2 and HIV-1 superinfection.