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HIV-1 group M was transmitted to humans nearly one century ago. The virus has since evolved to form distinct clades, which spread to different regions of the world. The envelope glycoproteins (Envs) of HIV-1 have rapidly diversified in all infected populations. We examined whether key antigenic sites of Env and signatures of vaccine efficacy are evolving toward similar or distinct structural forms in different populations worldwide. Patterns of amino acid variants that emerged at each position of Env were compared between diverse HIV-1 clades and isolates from different geographic regions. Interestingly, at each Env position, the amino acid in the clade ancestral or regional-founder virus was replaced by a unique frequency distribution (FD) of amino acids. FDs are highly conserved in populations from different regions worldwide and in paraphyletic and monophyletic subclade groups. Remarkably, founder effects of Env mutations at the clade and regional levels have gradually decreased during the pandemic by evolution of each site toward the unique combination of variants. Therefore, HIV-1 Env is evolving at a population level toward well-defined “target” states; these states are not specific amino acids but rather specific distributions of amino acid frequencies. Our findings reveal the powerful nature of the forces that guide evolution of Env and their conservation across different populations. Such forces have caused a gradual decrease in the interpopulation diversity of Env despite an increasing intrapopulation diversity. IMPORTANCE The Env protein of HIV-1 is the primary target in AIDS vaccine design. Frequent mutations in the virus increase the number of Env forms in each population, limiting the efficacy of AIDS vaccines. Comparison of newly emerging forms in different populations showed that each position of Env is evolving toward a specific combination of amino acids. Similar changes are occurring in different HIV-1 subtypes and geographic regions toward the same position-specific combinations of amino acids, often from distinct ancestral sequences. The predictable nature of HIV-1 Env evolution, as shown here, provides a new framework for designing vaccines that are tailored to the unique combination of variants expected to emerge in each virus subtype and geographic region.

Background & Purpose: Exogenous administration of uric acid, a naturally occurring antioxidant that scavenges reactive oxygen species in vasculature, has shown protective efficacy in both rodent models of stroke and in human stroke patients in Spain as an adjuvant treatment to mechanical thrombectomy. In accordance with STAIR-RIGOR criteria, confirmation of efficacy in alternative preclinical models is required before clinical trials can be initiated in the United States. To date, preclinical efficacy has only been established in the acute setting in male rodents. Methods: Seven to nine week old ovariectomized female mice were subjected to filament-induced right middle cerebral artery ischemia and reperfusion, an established preclinical model of mechanical thrombectomy. Fidelity of the procedure was monitored by laser Doppler flowmetry in all animals. A separate lab randomly assigned animals to vehicle vs uric acid infusion, which was initiated immediately after 45 minutes of reperfusion. Post-stroke analysis of infarction size and neurological function were conducted by investigators blind to treatment group, with a 7 day primary endpoint and intermediary analysis at 1and 3 days. Results: Infarct size and neurological function at 7 days post-stroke was significantly improved in uric acid-treated animals, relative to vehicle. Conclusions: Efficacy of uric acid in preclinical models of stroke is now expanded to include female mice analyzed at a more chronic time point than has been investigated previously. These results supports STAIR-RIGOR driven determination of the suitability of acute administration of uric acid as an adjuvant to mechanical thrombectomy in clinical trials for patients with stroke.

Therapeutics that target the envelope glycoproteins (Envs) of human immunodeficiency virus type 1 (HIV-1) effectively reduce virus levels in patients. However, due to mutations, new Env variants are frequently generated, which may be resistant to the treatments. The appearance of such sequence variance at any Env position is seemingly random. A better understanding of the spatiotemporal patterns of variance across Env may lead to the development of new therapeutic strategies. We hypothesized that, at any time point in a patient, positions with sequence variance are clustered on the three-dimensional structure of Env. To test this hypothesis, we examined whether variance at any Env position can be predicted by the variance measured at adjacent positions. Sequences from 300 HIV-infected patients were applied to a new algorithm we developed. The k-best classifiers (KBC) method is a dynamic ensemble selection technique that identifies the best classifier(s) within the neighborhood of a new observation. It applies bootstrap resampling to generate out-of-bag samples that are used with the resampled set to evaluate each classifier. For many positions of Env, primarily in the CD4-binding site, KBC accurately predicted variance based on the variance at their adjacent positions. KBC improved performance compared to the initial learners, static ensemble, and other baseline models. KBC also outperformed other algorithms for predicting variance at multi-position footprints of therapeutics on Env. These understandings can be applied to refine models that predict future changes in HIV-1 Env. More generally, we propose KBC as a new high-performance dynamic ensemble selection technique.

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