New human norovirus strains emerge every 2 to 3 years, partly due to mutations in the viral capsid that allow escape from antibody neutralization and herd immunity. To understand how noroviruses evolve antibody resistance, we investigated the structural basis for the escape of murine norovirus (MNV) from antibody neutralization. To identify specific residues in the MNV-1 protruding (P) domain of the capsid that play a role in escape from the neutralizing monoclonal antibody (MAb) A6.2, 22 recombinant MNVs were generated with amino acid substitutions in the A=B= and E=F= loops. Six mutations in the E=F= loop (V378F, A382K, A382P, A382R, D385G, and L386F) mediated escape from MAb A6.2 neutralization. To elucidate underlying structural mechanisms for these results, the atomic structure of the A6.2 Fab was determined and fitted into the previously generated pseudoatomic model of the A6.2 Fab/MNV-1 virion complex. Previously, two distinct conformations, A and B, of the atomic structures of the MNV-1 P domain were identified due to flexibility in the two P domain loops. A superior stereochemical fit of the A6.2 Fab to the A conformation of the MNV P domain was observed. Structural analysis of our observed escape mutants indicates changes toward the less-preferred B conformation of the P domain. The shift in the structural equilibrium of the P domain toward the conformation with poor structural complementarity to the antibody strongly supports a unique mechanism for antibody escape that occurs via antigen flexibility instead of direct antibody-antigen binding. IMPORTANCEHuman noroviruses cause the majority of all nonbacterial gastroenteritis worldwide. New epidemic strains arise in part by mutations in the viral capsid leading to escape from antibody neutralization. Herein, we identify a series of point mutations in a norovirus capsid that mediate escape from antibody neutralization and determine the structure of a neutralizing antibody. Fitting of the antibody structure into the virion/antibody complex identifies two conformations of the antibody binding domain of the viral capsid: one with a superior fit and the other with an inferior fit to the antibody. These data suggest a unique mode of antibody neutralization. In contrast to other viruses that largely escape antibody neutralization through direct disruption of the antibody-virus interface, we identify mutations that acted indirectly by limiting the conformation of the antibody binding loop in the viral capsid and drive the antibody binding domain into the conformation unable to be bound by the antibody.

Viral evolutionary pathways are determined by the fitness landscape, which maps viral genotype to fitness. However, a quantitative description of the landscape and the evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based on capsid folding stability and antibody binding affinity to predict the evolutionary pathway of norovirus escaping a neutralizing antibody. The model is validated by experimental evolution in bulk culture and in a drop-based microfluidics that propagates millions of independent small viral subpopulations. We demonstrate that along the axis of binding affinity, selection for escape variants and drift due to random mutations have the same direction, an atypical case in evolution. However, along folding stability, selection and drift are opposing forces whose balance is tuned by viral population size. Our results demonstrate that predictable epistatic tradeoffs between molecular traits of viral proteins shape viral evolution.

No abstract

Background Skin, the largest organ of the human body by weight, hosts a diversity of microorganisms that can influence health. The microbial residents of the skin are now appreciated for their roles in host immune interactions, wound healing, colonization resistance, and various skin disorders. Still, much remains to be discovered in terms of the host pathways influenced by skin microorganisms, as well as the higher-level skin properties impacted through these microbe-host interactions. Towards this direction, recent efforts using mouse models point to pronounced changes in the transcriptional profiles of the skin in response to the presence of a microbial community. However, there is a need to quantify the roles of microorganisms at both the individual and community-level in healthy human skin. In this study, we utilize human skin equivalents to study the effects of individual taxa and a microbial community in a precisely controlled context. Through transcriptomics analysis, we identify key genes and pathways influenced by skin microbes, and we also characterize higher-level impacts on skin processes and properties through histological analyses. Results The presence of a microbiome on a 3D skin tissue model led to significantly altered patterns of gene expression, influencing genes involved in the regulation of apoptosis, proliferation, and the extracellular matrix (among others). Moreover, microbiome treatment influenced the thickness of the epidermal layer, reduced the number of actively proliferating cells, and increased filaggrin expression. Many of these findings were evident upon treatment with the mixed community, but either not detected or less pronounced in treatments by single microorganisms, underscoring the impact that a diverse skin microbiome has on the host. Conclusions This work contributes to the understanding of how microbiome constituents individually and collectively influence human skin processes and properties. The results show that, while it is important to understand the effect of individual microbes on the host, a full community of microbes has unique and pronounced effects on the skin. Thus, in its impacts on the host, the skin microbiome is more than the sum of its parts.

1Predicting viral evolution remains a major challenge with profound implications for public 2 health. Viral evolutionary pathways are determined by the fitness landscape, which maps 3 viral genotype to fitness. However, a quantitative description of the landscape and the 4 evolutionary forces on it remain elusive. Here, we apply a biophysical fitness model based 5 on capsid folding stability and antibody binding affinity to predict the evolutionary 6 pathway of norovirus escaping a neutralizing antibody. The model is validated by 7 experimental evolution in bulk culture and in a drop-based microfluidics device, the 8 "Evolution Chip", which propagates millions of independent viral sub-populations. We 9 demonstrate that along the axis of binding affinity, selection for escape variants and drift 10 due to random mutations have the same direction. However, along folding stability, 11 selection and drift are opposing forces whose balance is tuned by viral population size. Our 12 results demonstrate that predictable epistatic tradeoffs shape viral evolution. 13 14

Background Skin, the largest organ of the human body by weight, hosts a diversity of microorganisms that can influence health. The microbial residents of the skin are now appreciated for their roles in host immune interactions, wound healing, colonization resistance, and various skin disorders. Still, much remains to be discovered in terms of the host pathways influenced by skin microorganisms, as well as the higher-level skin properties impacted through these microbe-host interactions. Towards this direction, recent efforts using mouse models pointed to pronounced changes in the transcriptional profiles of the skin in response to the presence of a microbial community. However, there is a need to quantify the roles of microorganisms at both the individual and community-level in healthy human skin. In this study, we utilize human skin equivalents to study the effects of individual taxa and a microbial community in a precisely controlled context. Through transcriptomics analysis, we identify key genes and pathways influenced by skin microbes, and we also characterize higher-level impacts on skin processes and properties through histological analyses. Results The presence of a microbiome on a 3D skin tissue model led to significantly altered patterns of gene expression, influencing genes involved in the regulation of apoptosis, proliferation, and the extracellular matrix (among others). Moreover, microbiome treatment influenced the thickness of the epidermal layer, reduced the number of actively proliferating cells, and increased filaggrin expression. Many of these findings were evident upon treatment with the mixed community, but either not detected or less pronounced in treatments by single microorganisms, underscoring the impact that a diverse skin microbiome has on the host. Conclusions This work contributes to the understanding of how microbiome constituents individually and collectively influence human skin processes and properties. The results show that, while it is important to understand the effect of individual microbes on the host, a full community of microbes has unique and pronounced effects on the skin. Thus, in its impacts on the host, the skin microbiome is more than the sum of its parts.

No abstract

Automated plant analysis methods can inform basic and applied plant research. Computed tomography (CT) has been used to image plants in canopies and individual plants; however this method is underutilized for dynamic analysis of plant growth. In this work we present a workflow and associated algorithm to nondestructively extract leaf area from 120 individual CT scans for plants with flat [soybean, Glycine max (L.) Merr.], textured (tomato, Solanum lycopersicum L.), and grassy (wheat, Triticum aestivum L.) leaves. Under low water conditions, we see significant changes in leaf area depending on leaf type. This work enables future automated phenotyping using CT scanning of whole plants.