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 in | Journal of general virology Vol. 102; no. 1 |
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Main Authors | , |
Format | Journal Article |
Language | English |
Published |
England
Microbiology Society
2021
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Subjects | |
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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. |
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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 |
Author_xml | – sequence: 1 givenname: Ruben Michael orcidid: 0000-0002-8869-2800 surname: Ceballos fullname: Ceballos, Ruben Michael organization: Department of Biological Sciences, The University of Arkansas, Fayetteville, AR, USA, Arkansas Center for Space and Planetary Sciences, Fayetteville, AR, USA, Cell and Molecular Biology Program, The University of Arkansas, Fayetteville, AR, USA – sequence: 2 givenname: Carson Len orcidid: 0000-0002-8817-574X surname: Stacy fullname: Stacy, Carson Len organization: Cell and Molecular Biology Program, The University of Arkansas, Fayetteville, AR, USA, Department of Biological Sciences, The University of Arkansas, Fayetteville, AR, USA |
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Cites_doi | 10.1016/j.jim.2017.03.013 10.1371/journal.pone.0216292 10.1101/gr.210286.116 10.4049/jimmunol.88.3.339 10.1128/JB.180.12.3237-3240.1998 10.1038/bjc.1965.32 10.1016/S0923-2508(03)00074-3 10.1128/jvi.78.4.1954-1961.2004 10.3390/v10040189 10.1016/s0166-0934(03)00129-0 10.1038/ncomms1146 10.1128/AEM.56.6.1875-1881.1990 10.1016/j.jviromet.2009.03.007 10.3389/fmicb.2020.01218 10.1093/molbev/mst187 10.1016/0042-6822(91)90771-3 10.1371/journal.pbio.1001540 10.3389/fmicb.2012.00295 10.1016/j.virusres.2019.03.003 10.1146/annurev.mi.03.100149.002103 10.1016/j.jim.2012.06.005 10.1080/10408398.2011.570463 10.1371/journal.pone.0034846 10.1016/j.febslet.2005.02.025 |
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Keywords | Gompertz model relative virulence non-lytic viruses virus–host dynamicsx Sulfolobus spindle-shaped virus growth curve analysis |
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References | Monod (R13) 1949; 3 Ceballos (R11) 2020; 11 Galasso (R1) 1962; 88 R21 R20 R23 R22 R25 R27 R26 Stacy (R19) Storms (R18) 2019; 1 R2 R3 R4 R5 R6 R7 XXIV (R8) 1825; 115 R9 R10 R12 R14 R16 Wang (R24) 2010; 1 R15 R17 |
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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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