Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection

Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration an...

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Vydáno v:	PLoS computational biology Ročník 19; číslo 5; s. e1011173
Hlavní autoři:	Sunagawa, Junya, Komorizono, Ryo, Park, Hyeongki, Hart, William S., Thompson, Robin N., Makino, Akiko, Tomonaga, Keizo, Iwami, Shingo, Yamaguchi, Ryo
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	United States Public Library of Science 30.05.2023 Public Library of Science (PLoS)
Témata:	Accuracy Analysis Animals Binomial distribution Biology and Life Sciences Borna disease COVID-19 Disease Disease transmission Equilibrium Evolution Genetic algorithms Genetic aspects Health aspects Human populations Humans Infection Infections Medicine and Health Sciences Modelling Natural history Peak load Persistent infection Population biology Population dynamics Populations RNA RNA polymerase RNA viruses SARS-CoV-2 - genetics Severe acute respiratory syndrome coronavirus 2 Viral diseases Viral infections Virus Diseases Viruses Viruses - genetics Japan
ISSN:	1553-7358, 1553-734X, 1553-7358
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Abstract	Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.
AbstractList	Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society. Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society.Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society. Viruses evolve in infected host populations, and host population dynamics affect viral evolution. RNA viruses with a short duration of infection and a high peak viral load, such as SARS-CoV-2, are maintained in human populations. By contrast, RNA viruses characterized by a long infection duration and a low peak viral load (e.g., borna disease virus) can be maintained in nonhuman populations, and the process of the evolution of persistent viruses has rarely been explored. Here, using a multi-level modeling approach including both individual-level virus infection dynamics and population-scale transmission, we consider virus evolution based on the host environment, specifically, the effect of the contact history of infected hosts. We found that, with a highly dense contact history, viruses with a high virus production rate but low accuracy are likely to be optimal, resulting in a short infectious period with a high peak viral load. In contrast, with a low-density contact history, viral evolution is toward low virus production but high accuracy, resulting in long infection durations with low peak viral load. Our study sheds light on the origin of persistent viruses and why acute viral infections but not persistent virus infection tends to prevail in human society. As exemplified by the SARS-CoV-2 variants of concern and influenza A virus variants, we need to predict the future evolution of viral properties to counter an oncoming pandemic. While some RNA viruses such as influenza A viruses adopt an acute infection strategy, others, such as Borna disease virus, adopt a persistent infection strategy. In what kind of environment did these viruses evolve? This study presents a modeling framework to investigate the evolution of proliferative ability and accuracy throughout the viral life cycle. Specifically, we calculated eco-evolutionary dynamics from virus infection in the host to transmission between hosts and capture the transmission potential of the virus. The acute infection phenotype evolves under a contact history involving frequent contacts between hosts. By contrast, the persistent infection phenotype evolves under an environment with a small mean and a large variance in the host contact history. These findings have direct implications for the fight against the continuous evolution of various viruses, which have easily prevailed in the setting of dense human contacts. We believe it is essential to readdress the evolution of viruses from an evolutionary and ecological perspective.
Audience	Academic
Author	Hart, William S. Makino, Akiko Iwami, Shingo Sunagawa, Junya Park, Hyeongki Tomonaga, Keizo Komorizono, Ryo Yamaguchi, Ryo Thompson, Robin N.
AuthorAffiliation	13 Science Groove Inc., Fukuoka, Japan 3 interdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan 8 Department of Molecular Virology, Graduate School of Medicine, Kyoto University, Kyoto, Japan 1 Department of Advanced Transdisciplinary Science, Hokkaido University, Sapporo, Hokkaido, Japan 2 Laboratory of RNA Viruses, Department of Virus Research, Institute for Life and Medical Sciences (LiMe), Kyoto University, Kyoto, Japan 9 Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan 5 Mathematics Institute, University of Warwick, Coventry, United Kingdom 12 NEXT-Ganken Program, Japanese Foundation for Cancer Research (JFCR), Tokyo, Japan 14 Department of Zoology & Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada 4 Mathematical Institute, University of Oxford, Oxford, United Kingdom 6 Zeeman Institute for Systems Biology and Infectious Disease Epidemiolo
AuthorAffiliation_xml	– name: 9 Institute of Mathematics for Industry, Kyushu University, Fukuoka, Japan – name: 13 Science Groove Inc., Fukuoka, Japan – name: University of California San Diego, UNITED STATES – name: 6 Zeeman Institute for Systems Biology and Infectious Disease Epidemiology Research, University of Warwick, Coventry, United Kingdom – name: 1 Department of Advanced Transdisciplinary Science, Hokkaido University, Sapporo, Hokkaido, Japan – name: 2 Laboratory of RNA Viruses, Department of Virus Research, Institute for Life and Medical Sciences (LiMe), Kyoto University, Kyoto, Japan – name: 4 Mathematical Institute, University of Oxford, Oxford, United Kingdom – name: 12 NEXT-Ganken Program, Japanese Foundation for Cancer Research (JFCR), Tokyo, Japan – name: 8 Department of Molecular Virology, Graduate School of Medicine, Kyoto University, Kyoto, Japan – name: 3 interdisciplinary Biology Laboratory (iBLab), Division of Natural Science, Graduate School of Science, Nagoya University, Nagoya, Japan – name: 10 Institute for the Advanced Study of Human Biology (ASHBi), Kyoto University, Kyoto, Japan – name: 7 Laboratory of RNA Viruses, Graduate School of Biostudies, Kyoto University, Kyoto, Japan – name: 5 Mathematics Institute, University of Warwick, Coventry, United Kingdom – name: 14 Department of Zoology & Biodiversity Research Centre, University of British Columbia, Vancouver, British Columbia, Canada – name: 11 Interdisciplinary Theoretical and Mathematical Sciences Program (iTHEMS), RIKEN, Saitama, Japan
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Copyright	Copyright: © 2023 Sunagawa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. COPYRIGHT 2023 Public Library of Science 2023 Sunagawa et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. 2023 Sunagawa et al 2023 Sunagawa et al
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SubjectTerms	Accuracy Analysis Animals Binomial distribution Biology and Life Sciences Borna disease COVID-19 Disease Disease transmission Equilibrium Evolution Genetic algorithms Genetic aspects Health aspects Human populations Humans Infection Infections Medicine and Health Sciences Modelling Natural history Peak load Persistent infection Population biology Population dynamics Populations RNA RNA polymerase RNA viruses SARS-CoV-2 - genetics Severe acute respiratory syndrome coronavirus 2 Viral diseases Viral infections Virus Diseases Viruses Viruses - genetics
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Title	Contact-number-driven virus evolution: A multi-level modeling framework for the evolution of acute or persistent RNA virus infection
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Volume	19
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