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To prevent new infections with human immunodeficiency virus type 1 (HIV-1) in sub-Saharan Africa, UNAIDS recommends targeting interventions to populations that are at high risk of acquiring and passing on the virus. Yet it is often unclear who and where these ‘source’ populations are. Here we demonstrate how viral deep-sequencing can be used to reconstruct HIV-1 transmission networks and to infer the direction of transmission in these networks. We are able to deep-sequence virus from a large population-based sample of infected individuals in Rakai District, Uganda, reconstruct partial transmission networks, and infer the direction of transmission within them at an estimated error rate of 16.3% [8.8–28.3%]. With this error rate, deep-sequence phylogenetics cannot be used against individuals in legal contexts, but is sufficiently low for population-level inferences into the sources of epidemic spread. The technique presents new opportunities for characterizing source populations and for targeting of HIV-1 prevention interventions in Africa.

Background International and global organisations advocate targeting interventions to areas of high HIV prevalence (ie, hotspots). To better understand the potential benefits of geo-targeted control, we assessed the extent to which HIV hotspots along Lake Victoria sustain transmission in neighbouring populations in south-central Uganda. Methods We did a population-based survey in Rakai, Uganda, using data from the Rakai Community Cohort Study. The study surveyed all individuals aged 15-49 years in four high-prevalence Lake Victoria fishing communities and 36 neighbouring inland communities. Viral RNA was deep sequenced from participants infected with HIV who were antiretroviral therapy-naive during the observation period. Phylogenetic analysis was used to infer partial HIV transmission networks, including direction of transmission. Reconstructed networks were interpreted through data for current residence and migration history. HIV transmission flows within and between high-prevalence and low-prevalence areas were quantified adjusting for incomplete sampling of the population. Findings Between Aug 10, 2011, and Jan 30, 2015, data were collected for the Rakai Community Cohort Study. 25 882 individuals participated, including an estimated 75•7% of the lakeside population and 16•2% of the inland population in the Rakai region of Uganda. 5142 participants were HIV-positive (2703 [13•7%] in inland and 2439 [40•1%] in fishing communities). 3878 (75•4%) people who were HIV-positive did not report antiretroviral therapy use, of whom 2652 (68•4%) had virus deep-sequenced at sufficient quality for phylogenetic analysis. 446 transmission networks were reconstructed, including 293 linked pairs with inferred direction of transmission. Adjusting for incomplete sampling, an estimated 5•7% (95% credibility interval 4•4-7•3) of transmissions occurred within lakeside areas, 89•2% (86•0-91•8) within inland areas, 1•3% (0•6-2•6) from lakeside to inland areas, and 3•7% (2•3-5•8) from inland to lakeside areas. Interpretation Cross-community HIV transmissions between Lake Victoria hotspots and surrounding inland populations are infrequent and when they occur, virus more commonly flows into rather than out of hotspots. This result suggests that targeted interventions to these hotspots will not alone control the epidemic in inland populations, where most transmissions occur. Thus, geographical targeting of high prevalence areas might not be effective for broader epidemic control depending on underlying epidemic dynamics.

Nuclear domain 10 (ND10s), or promyelocytic leukemia protein (PML) nuclear bodies, are spherical nuclear structures that require PML proteins for their formation. Many viruses target these structures during infection. The E4 Orf3 protein of adenovirus 5 (Ad5) rearranges ND10s, causing PML to colocalize with Orf3 in nuclear tracks or fibers. There are six different PML isoforms (I to VI) present at ND10s, all sharing a common N terminus but with structural differences at their C termini. In this study, PML II was the only one of these six isoforms that was found to interact directly and specifically with Ad5 E4 Orf3 in vitro and in vivo; these results define a new Orf3 activity. Three of a series of 18 mutant Orf3 proteins were unable to interact with PML II; these were also unable to cause ND10 rearrangement. Moreover, in PML-null cells that contained neoformed ND10s comprising a single PML isoform, only ND10s formed of PML II were rearranged by Orf3. These data show that the interaction between Orf3 and PML II is necessary for ND10 rearrangement to occur. Finally, Orf3 was shown to self-associate in vitro. This activity was absent in mutant Orf3 proteins that were unable to form tracks and to bind PML II. Thus, Orf3 oligomerization may mediate the formation of nuclear tracks in vivo and may also be important for PML II binding.