Abstract:
:Pre-clinical responses to fast-moving infectious disease outbreaks heavily depend on choosing the best isolates for animal models that inform diagnostics, vaccines and treatments. Current approaches are driven by practical considerations (e.g. first available virus isolate) rather than a detailed analysis of the characteristics of the virus strain chosen, which can lead to animal models that are not representative of the circulating or emerging clusters. Here, we suggest a combination of epidemiological, experimental and bioinformatic considerations when choosing virus strains for animal model generation. We discuss the currently chosen SARS-CoV-2 strains for international coronavirus disease (COVID-19) models in the context of their phylogeny as well as in a novel alignment-free bioinformatic approach. Unlike phylogenetic trees, which focus on individual shared mutations, this new approach assesses genome-wide co-developing functionalities and hence offers a more fluid view of the 'cloud of variances' that RNA viruses are prone to accumulate. This joint approach concludes that while the current animal models cover the existing viral strains adequately, there is substantial evolutionary activity that is likely not considered by the current models. Based on insights from the non-discrete alignment-free approach and experimental observations, we suggest isolates for future animal models.
journal_name
Transbound Emerg Disjournal_title
Transboundary and emerging diseasesauthors
Bauer DC,Tay AP,Wilson LOW,Reti D,Hosking C,McAuley AJ,Pharo E,Todd S,Stevens V,Neave MJ,Tachedjian M,Drew TW,Vasan SSdoi
10.1111/tbed.13588subject
Has Abstractpub_date
2020-07-01 00:00:00pages
1453-1462issue
4eissn
1865-1674issn
1865-1682journal_volume
67pub_type
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journal_title:Transboundary and emerging diseases
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pub_type: 杂志文章
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journal_title:Transboundary and emerging diseases
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