Deconvolving mutational patterns of poliovirus outbreaks reveals its intrinsic fitness landscape.

Vaccination has essentially eradicated poliovirus. Yet, its mutation rate is higher than that of viruses like HIV, for which no effective vaccine exists. To investigate this, we infer a fitness model for the poliovirus viral protein 1 (vp1), which successfully predicts in vitro fitness measurements. This is achieved by first developing a probabilistic model for the prevalence of vp1 sequences that enables us to isolate and remove data that are subject to strong vaccine-derived biases. The intrinsic fitness constraints derived for vp1, a capsid protein subject to antibody responses, are compared with those of analogous HIV proteins. We find that vp1 evolution is subject to tighter constraints, limiting its ability to evade vaccine-induced immune responses. Our analysis also indicates that circulating poliovirus strains in unimmunized populations serve as a reservoir that can seed outbreaks in spatio-temporally localized sub-optimally immunized populations

An Effective Membrane Model of the Immunological Synapse

The immunological synapse is a patterned collection of different types of receptors and ligands that forms in the intercellular junction between T Cells and antigen presenting cells (APCs) during recognition. The synapse is implicated in information transfer between cells, and is characterized by different spatial patterns of receptors at different stages in the life cycle of T cells. We obtain a minimalist model that captures this experimentally observed phenomenology. A functional RG analysis provides further insights.Comment: 6 pages, 3 figures, submitted for publicatio

Computational Prediction of Broadly Neutralizing HIV-1 Antibody Epitopes from Neutralization Activity Data

Broadly neutralizing monoclonal antibodies effective against the majority of circulating isolates of HIV-1 have been isolated from a small number of infected individuals. Definition of the conformational epitopes on the HIV spike to which these antibodies bind is of great value in defining targets for vaccine and drug design. Drawing on techniques from compressed sensing and information theory, we developed a computational methodology to predict key residues constituting the conformational epitopes on the viral spike from cross-clade neutralization activity data. Our approach does not require the availability of structural information for either the antibody or antigen. Predictions of the conformational epitopes of ten broadly neutralizing HIV-1 antibodies are shown to be in good agreement with new and existing experimental data. Our findings suggest that our approach offers a means to accelerate epitope identification for diverse pathogenic antigens

Selective elimination of pluripotent stem cells by PIKfyve specific inhibitors.

Inhibition of PIKfyve phosphoinositide kinase selectively kills autophagy-dependent cancer cells by disrupting lysosome homeostasis. Here, we show that PIKfyve inhibitors can also selectively eliminate pluripotent embryonal carcinoma cells (ECCs), embryonic stem cells, and induced pluripotent stem cells under conditions where differentiated cells remain viable. PIKfyve inhibitors prevented lysosome fission, induced autophagosome accumulation, and reduced cell proliferation in both pluripotent and differentiated cells, but they induced death only in pluripotent cells. The ability of PIKfyve inhibitors to distinguish between pluripotent and differentiated cells was confirmed with xenografts derived from ECCs. Pretreatment of ECCs with the PIKfyve specific inhibitor WX8 suppressed their ability to form teratocarcinomas in mice, and intraperitoneal injections of WX8 into mice harboring teratocarcinoma xenografts selectively eliminated pluripotent cells. Differentiated cells continued to proliferate, but at a reduced rate. These results provide a proof of principle that PIKfyve specific inhibitors can selectively eliminate pluripotent stem cells in vivo as well as in vitro

Coreceptor affinity for MHC defines peptide specificity requirements for TCR interaction with coagonist peptide-MHC

Recent work has demonstrated that nonstimulatory endogenous peptides can enhance T cell recognition of antigen, but MHCI- and MHCII-restricted systems have generated very different results. MHCII-restricted TCRs need to interact with the nonstimulatory peptide–MHC (pMHC), showing peptide specificity for activation enhancers or coagonists. In contrast, the MHCI-restricted cells studied to date show no such peptide specificity for coagonists, suggesting that CD8 binding to noncognate MHCI is more important. Here we show how this dichotomy can be resolved by varying CD8 and TCR binding to agonist and coagonists coupled with computer simulations, and we identify two distinct mechanisms by which CD8 influences the peptide specificity of coagonism. Mechanism 1 identifies the requirement of CD8 binding to noncognate ligand and suggests a direct relationship between the magnitude of coagonism and CD8 affinity for coagonist pMHCI. Mechanism 2 describes how the affinity of CD8 for agonist pMHCI changes the requirement for specific coagonist peptides. MHCs that bind CD8 strongly were tolerant of all or most peptides as coagonists, but weaker CD8-binding MHCs required stronger TCR binding to coagonist, limiting the potential coagonist peptides. These findings in MHCI systems also explain peptide-specific coagonism in MHCII-restricted cells, as CD4–MHCII interaction is generally weaker than CD8–MHCI.National Institutes of Health (U.S.). Pioneer Awar

Signaling Cascades Modulate the Speed of Signal Propagation through Space

Cells are not mixed bags of signaling molecules. As a consequence, signals must travel from their origin to distal locations. Much is understood about the purely diffusive propagation of signals through space. Many signals, however, propagate via signaling cascades. Here, we show that, depending on their kinetics, cascades speed up or slow down the propagation of signals through space, relative to pure diffusion.We modeled simple cascades operating under different limits of Michaelis-Menten kinetics using deterministic reaction-diffusion equations. Cascades operating far from enzyme saturation speed up signal propagation; the second mobile species moves more quickly than the first through space, on average. The enhanced speed is due to more efficient serial activation of a downstream signaling module (by the signaling molecule immediately upstream in the cascade) at points distal from the signaling origin, compared to locations closer to the source. Conversely, cascades operating under saturated kinetics, which exhibit zero-order ultrasensitivity, can slow down signals, ultimately localizing them to regions around the origin.Signal speed modulation may be a fundamental function of cascades, affecting the ability of signals to penetrate within a cell, to cross-react with other signals, and to activate distant targets. In particular, enhanced speeds provide a way to increase signal penetration into a cell without needing to flood the cell with large numbers of active signaling molecules; conversely, diminished speeds in zero-order ultrasensitive cascades facilitate strong, but localized, signaling

Optimality of mutation and selection in germinal centers

The population dynamics theory of B cells in a typical germinal center could play an important role in revealing how affinity maturation is achieved. However, the existing models encountered some conflicts with experiments. To resolve these conflicts, we present a coarse-grained model to calculate the B cell population development in affinity maturation, which allows a comprehensive analysis of its parameter space to look for optimal values of mutation rate, selection strength, and initial antibody-antigen binding level that maximize the affinity improvement. With these optimized parameters, the model is compatible with the experimental observations such as the ~100-fold affinity improvements, the number of mutations, the hypermutation rate, and the "all or none" phenomenon. Moreover, we study the reasons behind the optimal parameters. The optimal mutation rate, in agreement with the hypermutation rate in vivo, results from a tradeoff between accumulating enough beneficial mutations and avoiding too many deleterious or lethal mutations. The optimal selection strength evolves as a balance between the need for affinity improvement and the requirement to pass the population bottleneck. These findings point to the conclusion that germinal centers have been optimized by evolution to generate strong affinity antibodies effectively and rapidly. In addition, we study the enhancement of affinity improvement due to B cell migration between germinal centers. These results could enhance our understandings to the functions of germinal centers.Comment: 5 figures in main text, and 4 figures in Supplementary Informatio

Coactivator condensation at super-enhancers links phase separation and gene control

Super-enhancers (SEs) are clusters of enhancers that cooperatively assemble a high density of the transcriptional apparatus to drive robust expression of genes with prominent roles in cell identity. Here we demonstrate that the SE-enriched transcriptional coactivators BRD4 and MED1 form nuclear puncta at SEs that exhibit properties of liquid-like condensates and are disrupted by chemicals that perturb condensates. The intrinsically disordered regions (IDRs) of BRD4 and MED1 can form phase-separated droplets, and MED1-IDR droplets can compartmentalize and concentrate the transcription apparatus from nuclear extracts. These results support the idea that coactivators form phase-separated condensates at SEs that compartmentalize and concentrate the transcription apparatus, suggest a role for coactivator IDRs in this process, and offer insights into mechanisms involved in the control of key cell-identity genes.National Institutes of Health (U.S.) (Grant GM123511)National Institutes of Health (U.S.) (Grant P01-CA042063)National Science Foundation (U.S.) (Grant PHY-1743900)National Cancer Institute (U.S.) (Grant P30-CA14051