tetano
Editor, Senior Moderator
Philos Trans R Soc Lond B Biol Sci. 2019 Sep 30;374(1782):20180346. doi: 10.1098/rstb.2018.0346. Epub 2019 Aug 12.
[h=1]Improving risk assessment of the emergence of novel influenza A viruses by incorporating environmental surveillance.[/h] Pepin KM[SUP]1[/SUP], Hopken MW[SUP]1,[/SUP][SUP]2[/SUP], Shriner SA[SUP]1[/SUP], Spackman E[SUP]3[/SUP], Abdo Z[SUP]2[/SUP], Parrish C[SUP]4[/SUP], Riley S[SUP]5[/SUP], Lloyd-Smith JO[SUP]6,[/SUP][SUP]7[/SUP], Piaggio AJ[SUP]1[/SUP].
[h=3]Author information[/h] 1 National Wildlife Research Center, USDA-APHIS, Fort Collins, CO 80521, USA. 2 Colorado State University, Fort Collins, CO 80523, USA. 3 Exotic and Emerging Avian Viral Diseases Research, USDA-ARS, Athens, GA 30605, USA. 4 Baker Institute for Animal Health, Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14853, USA. 5 MRC Centre for Global Infectious Disease Analysis, Imperial College, London, SW7 2AZ, UK. 6 UCLA, Los Angeles, CA 90095, USA. 7 Department of Ecology and Evolutionary Biology, Fogarty International Center, National Institutes of Health, Bethesda MD 20892, USA.
[h=3]Abstract[/h] Reassortment is an evolutionary mechanism by which influenza A viruses (IAV) generate genetic novelty. Reassortment is an important driver of host jumps and is widespread according to retrospective surveillance studies. However, predicting the epidemiological risk of reassortant emergence in novel hosts from surveillance data remains challenging. IAV strains persist and co-occur in the environment, promoting co-infection during environmental transmission. These conditions offer opportunity to understand reassortant emergence in reservoir and spillover hosts. Specifically, environmental RNA could provide rich information for understanding the evolutionary ecology of segmented viruses, and transform our ability to quantify epidemiological risk to spillover hosts. However, significant challenges with recovering and interpreting genomic RNA from the environment have impeded progress towards predicting reassortant emergence from environmental surveillance data. We discuss how the fields of genomics, experimental ecology and epidemiological modelling are well positioned to address these challenges. Coupling quantitative disease models and natural transmission studies with new molecular technologies, such as deep-mutational scanning and single-virus sequencing of environmental samples, should dramatically improve our understanding of viral co-occurrence and reassortment. We define observable risk metrics for emerging molecular technologies and propose a conceptual research framework for improving accuracy and efficiency of risk prediction. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
[h=4]KEYWORDS:[/h] co-infection; environmental transmission; influenza A; reassortment; single-virus sequencing; surveillance
PMID: 31401963 DOI: 10.1098/rstb.2018.0346
[h=1]Improving risk assessment of the emergence of novel influenza A viruses by incorporating environmental surveillance.[/h] Pepin KM[SUP]1[/SUP], Hopken MW[SUP]1,[/SUP][SUP]2[/SUP], Shriner SA[SUP]1[/SUP], Spackman E[SUP]3[/SUP], Abdo Z[SUP]2[/SUP], Parrish C[SUP]4[/SUP], Riley S[SUP]5[/SUP], Lloyd-Smith JO[SUP]6,[/SUP][SUP]7[/SUP], Piaggio AJ[SUP]1[/SUP].
[h=3]Author information[/h] 1 National Wildlife Research Center, USDA-APHIS, Fort Collins, CO 80521, USA. 2 Colorado State University, Fort Collins, CO 80523, USA. 3 Exotic and Emerging Avian Viral Diseases Research, USDA-ARS, Athens, GA 30605, USA. 4 Baker Institute for Animal Health, Department of Microbiology and Immunology, Cornell University, Ithaca, NY 14853, USA. 5 MRC Centre for Global Infectious Disease Analysis, Imperial College, London, SW7 2AZ, UK. 6 UCLA, Los Angeles, CA 90095, USA. 7 Department of Ecology and Evolutionary Biology, Fogarty International Center, National Institutes of Health, Bethesda MD 20892, USA.
[h=3]Abstract[/h] Reassortment is an evolutionary mechanism by which influenza A viruses (IAV) generate genetic novelty. Reassortment is an important driver of host jumps and is widespread according to retrospective surveillance studies. However, predicting the epidemiological risk of reassortant emergence in novel hosts from surveillance data remains challenging. IAV strains persist and co-occur in the environment, promoting co-infection during environmental transmission. These conditions offer opportunity to understand reassortant emergence in reservoir and spillover hosts. Specifically, environmental RNA could provide rich information for understanding the evolutionary ecology of segmented viruses, and transform our ability to quantify epidemiological risk to spillover hosts. However, significant challenges with recovering and interpreting genomic RNA from the environment have impeded progress towards predicting reassortant emergence from environmental surveillance data. We discuss how the fields of genomics, experimental ecology and epidemiological modelling are well positioned to address these challenges. Coupling quantitative disease models and natural transmission studies with new molecular technologies, such as deep-mutational scanning and single-virus sequencing of environmental samples, should dramatically improve our understanding of viral co-occurrence and reassortment. We define observable risk metrics for emerging molecular technologies and propose a conceptual research framework for improving accuracy and efficiency of risk prediction. This article is part of the theme issue 'Dynamic and integrative approaches to understanding pathogen spillover'.
[h=4]KEYWORDS:[/h] co-infection; environmental transmission; influenza A; reassortment; single-virus sequencing; surveillance
PMID: 31401963 DOI: 10.1098/rstb.2018.0346