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Due to theoretical and practical applications in biomedical, environmental, and industrial microbiology, robust metrics for quantifying the virulence of pathogens is vital. For many virus–host systems, multiple virus strains propagate through host populations. Each strain may exhibit a different virulence level. Likewise, different hosts may manifest different levels of host resilience to infection by a given virus. Recent publications have assessed metrics for quantifying virulence (VR) from growth curve data. Regardless of the metric used, a feature that most methods have in common is focus on the exponential growth phase of virus–host interactions. Often ignored is mortality phase. Following a report introducing the Stacy–Ceballos Inhibition Index (ISC), a robust metric to quantify relative virulence (VR) between viruses, we have turned attention to quantifying relative resilience (RR) between hosts in single-virus/single-host (SVSH) experimental infections. Although resilience during viral infection impacts the entire host growth curve, RR has particular biological significance during the mortality phase. In this report, we argue that calculating RR using a modified ISC provides a robust metric for comparisons between SVSH infections. Wet lab data from fusellovirus infections in Sulfolobales, bacteriophage infections in Mycobacteriales, and simulated infected-host growth profiles form the basis for developing this metric, RR, for quantifying resilience.
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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 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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- Award ID(s):
- 1818346
- PAR ID:
- 10223792
- Date Published:
- Journal Name:
- Journal of General Virology
- Volume:
- 102
- Issue:
- 1
- ISSN:
- 0022-1317
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.1099/jgv.0.001515
