Quantifying relative virulence: when μ max fails and AUC alone just is not enough

A challenge in virology is quantifying relative virulence ( V R ) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host growth curve analysis is often used to mathematically characterize virus–host interactions and to quantify the magnitude of de...

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Published inJournal of general virology Vol. 102; no. 1
Main Authors Ceballos, Ruben Michael, Stacy, Carson Len
Format Journal Article
LanguageEnglish
Published England Microbiology Society 2021
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Abstract A challenge in virology is quantifying relative virulence ( V R ) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host growth curve analysis is often used to mathematically characterize virus–host interactions and to quantify the magnitude of detriment to host due to viral infection. Quantifying V R using canonical parameters, like maximum specific growth rate ( μ max ), can fail to provide reliable information regarding virulence. Although area-under-the-curve (AUC) calculations are more robust, they are sensitive to limit selection. Using empirical data from Sulfolobus Spindle-shaped Virus (SSV) infections, we introduce a novel, simple metric that has proven to be more robust than existing methods for assessing V R . This metric ( I SC ) accurately aligns biological phenomena with quantified metrics to determine V R . It also addresses a gap in virology by permitting comparisons between different non-lytic virus infections or non-lytic versus lytic virus infections on a given host in single-virus/single-host infections.
AbstractList A challenge in virology is quantifying relative virulence (VR) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host growth curve analysis is often used to mathematically characterize virus-host interactions and to quantify the magnitude of detriment to host due to viral infection. Quantifying VR using canonical parameters, like maximum specific growth rate (μmax), can fail to provide reliable information regarding virulence. Although area-under-the-curve (AUC) calculations are more robust, they are sensitive to limit selection. Using empirical data from Sulfolobus Spindle-shaped Virus (SSV) infections, we introduce a novel, simple metric that has proven to be more robust than existing methods for assessing VR. This metric (ISC) accurately aligns biological phenomena with quantified metrics to determine VR. It also addresses a gap in virology by permitting comparisons between different non-lytic virus infections or non-lytic versus lytic virus infections on a given host in single-virus/single-host infections.A challenge in virology is quantifying relative virulence (VR) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host growth curve analysis is often used to mathematically characterize virus-host interactions and to quantify the magnitude of detriment to host due to viral infection. Quantifying VR using canonical parameters, like maximum specific growth rate (μmax), can fail to provide reliable information regarding virulence. Although area-under-the-curve (AUC) calculations are more robust, they are sensitive to limit selection. Using empirical data from Sulfolobus Spindle-shaped Virus (SSV) infections, we introduce a novel, simple metric that has proven to be more robust than existing methods for assessing VR. This metric (ISC) accurately aligns biological phenomena with quantified metrics to determine VR. It also addresses a gap in virology by permitting comparisons between different non-lytic virus infections or non-lytic versus lytic virus infections on a given host in single-virus/single-host infections.
A challenge in virology is quantifying relative virulence ( ) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host is often used to mathematically characterize virus-host interactions and to quantify the magnitude of detriment to host due to viral infection. Quantifying using canonical parameters, like maximum specific growth rate ( ), can fail to provide reliable information regarding virulence. Although area-under-the-curve (AUC) calculations are more robust, they are sensitive to limit selection. Using empirical data from Sulfolobus Spindle-shaped Virus (SSV) infections, we introduce a novel, simple metric that has proven to be more robust than existing methods for assessing . This metric ( ) accurately aligns biological phenomena with quantified metrics to determine . It also addresses a gap in virology by permitting comparisons between different non-lytic virus infections or non-lytic versus lytic virus infections on a given host in single-virus/single-host infections.
A challenge in virology is quantifying relative virulence ( V R ) between two (or more) viruses that exhibit different replication dynamics in a given susceptible host. Host growth curve analysis is often used to mathematically characterize virus–host interactions and to quantify the magnitude of detriment to host due to viral infection. Quantifying V R using canonical parameters, like maximum specific growth rate ( μ max ), can fail to provide reliable information regarding virulence. Although area-under-the-curve (AUC) calculations are more robust, they are sensitive to limit selection. Using empirical data from Sulfolobus Spindle-shaped Virus (SSV) infections, we introduce a novel, simple metric that has proven to be more robust than existing methods for assessing V R . This metric ( I SC ) accurately aligns biological phenomena with quantified metrics to determine V R . It also addresses a gap in virology by permitting comparisons between different non-lytic virus infections or non-lytic versus lytic virus infections on a given host in single-virus/single-host infections.
Author Stacy, Carson Len
Ceballos, Ruben Michael
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Issue 1
Keywords Gompertz model
relative virulence
non-lytic viruses
virus–host dynamicsx
Sulfolobus spindle-shaped virus
growth curve analysis
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Snippet A challenge in virology is quantifying relative virulence ( V R ) between two (or more) viruses that exhibit different replication dynamics in a given...
A challenge in virology is quantifying relative virulence ( ) between two (or more) viruses that exhibit different replication dynamics in a given susceptible...
A challenge in virology is quantifying relative virulence (VR) between two (or more) viruses that exhibit different replication dynamics in a given susceptible...
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SubjectTerms Archaea - growth & development
Archaea - virology
Area Under Curve
Fuselloviridae - growth & development
Fuselloviridae - pathogenicity
Host-Pathogen Interactions
Models, Biological
Short Communication
Virology - methods
Virulence
Virus Replication
Viruses - growth & development
Viruses - pathogenicity
Title Quantifying relative virulence: when μ max fails and AUC alone just is not enough
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