GII.4 NoV Variation over Time.

<p><b>2A: GII.4 blockade epitopes.</b> Three blockade epitopes have been identified in GII.4 NoVs. Epitope A (residues 294, 296–298, 368, and 372; green), Epitope D (residues 393–395; orange), and Epitope E (residues 407, 412–413; yellow) all map to the P2 subdomain on the surface of the virion. The HBGA interaction sites are shown in black. <b>2B: GII.4 P2 subdomain variation over time.</b> Colored residues indicate change over time since 1974; changes present in 1987 = yellow, 1997 = red, 2002 = teal, 2004 = green, 2005 = orange, 2006 = purple, 2009 = blue, HBGA interaction sites = black, carbohydrates = white sticks. <b>2C: GII.4 NoV variation over time in blockade-epitope regions.</b> GII.4 NoV blockade epitopes undergo change over time, likely in response to human herd immunity. Colors indicate in which outbreak strain a particular residue change originated. <b>2D: Mapping of GII.4 variation over time in blockade-epitope regions.</b> Each VLP shows areas within blockade epitopes that change over time. Yellow indicates differences from 1974 present in 1987, 1997 = red, 2002 = teal, 2004 = green, 2005 = orange, 2006 = purple, and 2009 = blue. These blockade epitopes have continued to evolve in new outbreak strains since 2009.</p

New Metrics for Evaluating Viral Respiratory Pathogenesis

<div><p>Viral pathogenesis studies in mice have relied on markers of severe systemic disease, rather than clinically relevant measures, to evaluate respiratory virus infection; thus confounding connections to human disease. Here, whole-body plethysmography was used to directly measure changes in pulmonary function during two respiratory viral infections. This methodology closely tracked with traditional pathogenesis metrics, distinguished both virus- and dose-specific responses, and identified long-term respiratory changes following both SARS-CoV and Influenza A Virus infection. Together, the work highlights the utility of examining respiratory function following infection in order to fully understand viral pathogenesis.</p></div

Dose-dependent respiratory stress following SARS-CoV infection.

<p>Four C57BL/6J animals per group were either mock-infected (black) or infected with increasing doses of SARS-CoV (10^3, Blue; 10^4, Green; 10^5, Red). Weight loss (A), Mortality (B), and Respiratory parameters (Sup. Data) were measured through 7 days post infection. Whether there was a significant effect of treatment on weight loss (A) was determined via partial F-test. Following significance assessment, those treatment groups different from each-other were assessed by Tukey’s HSD post-hoc analysis. All such differences are denoted at a p<0.05 level, and are marked as follows: * = mock different from all infected, # = mock different from all infected; 10^3 different from 10^4 and 10^5, % = mock different from 10^4 and 10^5 doses. C) UPGMA (<b>U</b>nweighted <b>P</b>air <b>G</b>roup <b>M</b>ethod with <b>A</b>rithmetic Mean)-Clustered correlation matrix describing the relationship between various plethysmographic outputs. For each pair of transformed phenotypes, the correlation between these phenotypes was calculated. The color of each cell relates to the strength of correlation (ranging from -1 at light blue, no correlation being black, and a +1 correlation being bright yellow). In this way strong positive and negative relationships, as well as clusters of tightly related phenotypes could be identified across the range of SARS-CoV dose responses.</p

The shape of the exhalatory flow curve (Rpef) indicated changes following infection with SARS-CoV.

<p>(A) Rpef measures the ratio of time to peak expiratory follow (PEF) relative to the total expiratory time. For both hypoxia (gray) and SARS-CoV infection (red), the time to PEF decreases relative to normal (black). However, the length of breath expands following SARS-CoV infection, causing significant drop in Rpef values relative to baseline. (B) Following SARS-CoV infection of C57BL/6J animals, we identified significant differences in Rpef across a range of doses relative to mock animals (black = mock, blue = 10^3 SARS, green = 10^4, red = 10^5; four animals per group). Significant effects of treatment on Rpef was determined via partial F-test. Following significance assessment, those treatment groups different from each-other were assessed by Tukey’s HSD post-hoc analysis. All such differences are denoted at a p<0.05 level, and are marked as follows: * = mock different from all infected, # = 10^5 dose different from all others.</p

Penh shows increased sensitivity in dose-dependent responses following SARS-CoV infection.

<p>Penh is a classically used, and derived measure of respiratory distress. (A) Penh is derived by assessing several measures of the respiratory response curve (peak expiratory flow of breath (PEF), peak inspiratory flow of breath (PIF), time of expiratory portion of breath (Te) and time required to exhale 65% of breath volume (Tr) (B) Following SARS-CoV infection of C57BL/6J animals, we identified significant differences in Penh across a range of doses relative to mock animals (black = mock, blue = 10^3 SARS, green = 10^4, red = 10^5; four animals per group). Within a time point, letters indicate groups that are NOT significantly different from each other. Significant effects of treatment on Penh was determined via partial F-test. Following significance assessment, those treatment groups different from each-other were assessed by Tukey’s HSD post-hoc analysis. All such differences are denoted at a p<0.05 level, and are marked as follows: * = mock different from all infected, # = 10^5 dose different from all others, % = mock different from all doses, 10^3 different from 10^4 and 10^5 doses.</p

Mid-tidal expiratory flow (EF50) demonstrated dose-dependent increase following SARS-CoV infection.

<p>(A) Measuring the flow rate at which 50% of the tidal volume has been expelled, EF50 provides information about the early portion of the respiratory curve and has demonstrated notable differences between normal (black), asthmatic/allergic (Gray), and viral infection (red). (B) Following SARS-CoV infection of C57BL/6J animals, we identified significant differences in EF50 across a range of doses relative to mock animals (black = mock, blue = 10^3 SARS, green = 10^4, red = 10^5; four animals per group). Significant effects of treatment on EF50 was determined via partial F-test. Following significance assessment, those treatment groups different from each-other were assessed by Tukey’s HSD post-hoc analysis. All such differences are denoted at a p<0.05 level, and are marked as follows: * = mock different from all infected, # = mock different from all infected; 10^3 different from 10^4 and 10^5, % = mock different from 10^4 and 10^5 doses.</p

Differential responses to two respiratory pathogens.

<p>C57BL/6J mice were mock-infected (Black, n = 3) or infected with 10^4 of SARS-CoV (Green, n = 4) or 10^4 IAV-H1N1-09 (Orange, n = 4), and Airflow resistance, penH (A) or the shape of the expiratory force curve, Rpef (B) were measured through 28 days post infection. Significant effects of treatment on respiratory responses were determined via partial F-test. Following significance assessment, those treatment groups different from each-other were assessed by Tukey’s HSD post-hoc analysis. All such differences are denoted at a p<0.05 level, and are marked as follows: * = mock different from all infected, # = SARS different from mock and flu; %Flu different from SARS and mock, $ = Flu different from mock.</p

Human dengue virus serotype 2 neutralizing antibodies target two distinct quaternary epitopes

<div><p>Dengue virus (DENV) infection causes dengue fever, dengue hemorrhagic fever and dengue shock syndrome. It is estimated that a third of the world’s population is at risk for infection, with an estimated 390 million infections annually. Dengue virus serotype 2 (DENV2) causes severe epidemics, and the leading tetravalent dengue vaccine has lower efficacy against DENV2 compared to the other 3 serotypes. In natural DENV2 infections, strongly neutralizing type-specific antibodies provide protection against subsequent DENV2 infection. While the epitopes of some human DENV2 type-specific antibodies have been mapped, it is not known if these are representative of the polyclonal antibody response. Using structure-guided immunogen design and reverse genetics, we generated a panel of recombinant viruses containing amino acid alterations and epitope transplants between different serotypes. Using this panel of recombinant viruses in binding, competition, and neutralization assays, we have finely mapped the epitopes of three human DENV2 type-specific monoclonal antibodies, finding shared and distinct epitope regions. Additionally, we used these recombinant viruses and polyclonal sera to dissect the epitope-specific responses following primary DENV2 natural infection and monovalent vaccination. Our results demonstrate that antibodies raised following DENV2 infection or vaccination circulate as separate populations that neutralize by occupying domain III and domain I quaternary epitopes. The fraction of neutralizing antibodies directed to different epitopes differs between individuals. The identification of these epitopes could potentially be harnessed to evaluate epitope-specific antibody responses as correlates of protective immunity, potentially improving vaccine design.</p></div

HMAbs 2D22 and 1L12 use different critical residues in their epitopes.

<p>(A) rDENV4/2-EDIII 5aa is a DENV4 virus with five EDIII residues from DENV2. 2D22 and 1L12 were assessed for their ability to bind (B and D) and neutralize (C and E) recombinant DENV in ELISA binding assays and Vero-81 Focus Reduction Neutralization Tests (FRNT). Dotted line in ELISA represents the background signal, determined as the OD value of wells containing all reagents except for viral antigen.</p

rMA15 induction of proinflammatory genes is reduced in MyD88^−/− mice.

<p>WT (black bars) and MyD88^−/− mice (white bars) were inoculated intranasally with PBS (grey bars) or 10⁵ pfu rMA15. At 2, 4, and 6 dpi, mice were euthanized and total lung RNA was analyzed for mRNA expression by qRT-PCR. Levels of gene transcription for Type I and Type III interferons (A), proinflammatory chemokines (B) and proinflammatory cytokines (C) were assessed. Data are normalized to 18S rRNA and are expressed as the relative fold increase over PBS inoculated mice. The data presented are the means from 3–4 mice per timepoint ± the standard error of the means. *, P<0.05.</p