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New Metrics for Evaluating Viral Respiratory Pathogenesis.

Menachery VD, Gralinski LE, Baric RS, Ferris MT - PLoS ONE (2015)

Bottom Line: 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.Together, the work highlights the utility of examining respiratory function following infection in order to fully understand viral pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus

Dose-dependent respiratory stress following SARS-CoV infection.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 (Unweighted Pair Group Method with Arithmetic 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.
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pone.0131451.g001: Dose-dependent respiratory stress following SARS-CoV infection.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 (Unweighted Pair Group Method with Arithmetic 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.

Mentions: During the 5-minute measurement period within the plethysmograph, the plethysmograph continually measures respiratory responses, and outputs these data as 150 2-second summaries of 11 various respiratory measures (shown in Fig 1C and S1 Table), as well as several data quality controal metrics. Output data were examined and transformed to normality using the Box-Cox approach.


New Metrics for Evaluating Viral Respiratory Pathogenesis.

Menachery VD, Gralinski LE, Baric RS, Ferris MT - PLoS ONE (2015)

Dose-dependent respiratory stress following SARS-CoV infection.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 (Unweighted Pair Group Method with Arithmetic 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.
© Copyright Policy
Related In: Results  -  Collection

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getmorefigures.php?uid=PMC4482571&req=5

pone.0131451.g001: Dose-dependent respiratory stress following SARS-CoV infection.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 (Unweighted Pair Group Method with Arithmetic 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.
Mentions: During the 5-minute measurement period within the plethysmograph, the plethysmograph continually measures respiratory responses, and outputs these data as 150 2-second summaries of 11 various respiratory measures (shown in Fig 1C and S1 Table), as well as several data quality controal metrics. Output data were examined and transformed to normality using the Box-Cox approach.

Bottom Line: 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.Together, the work highlights the utility of examining respiratory function following infection in order to fully understand viral pathogenesis.

View Article: PubMed Central - PubMed

Affiliation: Department of Epidemiology, University of North Carolina at Chapel Hill, Chapel Hill, NC, United States of America.

ABSTRACT
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.

No MeSH data available.


Related in: MedlinePlus