In April 2024, following the annual International Committee on Taxonomy of Viruses (ICTV) ratification vote on newly proposed taxa, the phylum Negarnaviricota was expanded by 1 new order, 1 new family, 6 new subfamilies, 34 new genera and 270 new species. One class, two orders and six species were renamed. Seven families and 12 genera were moved; ten species were renamed and moved; and nine species were abolished. This article presents the updated taxonomy of Negarnaviricota as currently accepted by the ICTV, providing an essential annual update on the classification of members of this phylum that deepen understandings of their evolution, and supports critical public health measures for virus identification and tracking.
Inducing broadly neutralizing antibodies (bnAbs) against HIV remains a key challenge in vaccine development. Germline-targeting immunogens have effectively primed bnAb B cell lineages to individual HIV envelope epitopes in humans and nonhuman primates. However, eliciting consistent bnAb breadth requires the induction of multiple bnAb classes. We investigated whether immunization with a combination of germline-targeting immunogens could concurrently prime multiple bnAb lineages in nonhuman primates. Animals were immunized with three immunogens, targeting distinct epitopes: the V3-glycan/N332 supersite, the V2 Apex region, and the membrane-proximal external region (MPER), either individually or in combinations of two or all three. Triple combination immunization transiently reduced V2 Apex and V3-glycan responses, but by 8 weeks postboost, bnAb precursor lineages were observed to all three epitopes. Similar somatic hypermutation was observed across groups, indicative of permissive germinal center responses. These findings support combination germline-targeting immunization as a viable strategy to prime multiple bnAb lineages simultaneously.
The ability of proteins to adopt multiple conformations is fundamental to their biological function. With the advent of AlphaFold, machine learning (ML)-based methods have extended their capabilities to more broadly sample this intrinsic conformational diversity. However, the extent to which ML approaches can independently generate ensembles of diverse and biologically relevant conformations remains an open question. We sought to tackle this challenge by developing AlphaFold-RandomWalk (AF-RW) and AlphaFold-Ensemble (AF-Ensemble), novel ML-based methods to generate diverse protein conformations. As opposed to traditional approaches which rely on modifying the input multiple sequence alignment, AF-RW systematically adds noise to the weights of the model on a per-target basis, significantly increasing the conformational diversity of predicted models compared to conventional methods. AF-Ensemble takes the complementary approach fine-tuning an ensemble of models to produce diversity from a set of two-state systems. Additionally, both methods were incorporated into an automated, multistage computational pipeline that seeds unbiased molecular dynamics simulations from ML-generated conformations to efficiently sample alternative conformations. When evaluated on a diverse set of ten proteins, our pipeline provided useful, MD-guided hypotheses for determining biologically meaningful alternative conformations. Moreover, simulations seeded from diverse ML-generated conformations provided a reasonable approximation to the free energy landscape of two challenging protein targets, K-Ras and ribose-binding protein. Overall, our work highlights the potential of combining diverse conformations generated by perturbing the weights of AF with molecular dynamics simulations to efficiently probe protein conformational heterogeneity.
The NF-κB family of transcription factor complexes are central regulators of inflammation, and their dysregulation contributes to the pathology of multiple inflammatory disease conditions. Accordingly, identifying pharmacological mechanisms that restrain NF-κB overactivation remains an area of key importance. Here, we demonstrate that inhibition of the glycolytic enzyme phosphoglycerate kinase 1 (PGK1) with the small molecule inhibitor CBR-470-2 results in attenuated NF-κB signaling, decreasing transcriptional output in response to several canonical NF-κB activating stimuli. Mechanistically, PGK1 inhibition promotes the accumulation of the glycolytic metabolite methylglyoxal, which crosslinks and inactivates NF-κB proteins, limiting the phosphorylation and nuclear translocation of these transcription factor complexes. This work establishes a key connection between central carbon metabolism and immune signaling and further supports the notion that PGK1 inhibition may be a viable strategy to increase cellular survival and dampen inflammation in disease.
