Supporting pandemic response using genomics and bioinformatics: A case study on the emergent SARS-CoV-2 outbreak.
Transbound Emerg Dis
; 67(4): 1453-1462, 2020 Jul.
Article
in English
| MEDLINE | ID: covidwho-71844
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.
Keywords
Full text:
Available
Collection:
International databases
Database:
MEDLINE
Main subject:
Pneumonia, Viral
/
Disease Outbreaks
/
Coronavirus Infections
/
Computational Biology
/
Genomics
/
Pandemics
Type of study:
Case report
/
Observational study
/
Prognostic study
/
Randomized controlled trials
Topics:
Vaccines
Limits:
Animals
/
Humans
Language:
English
Journal:
Transbound Emerg Dis
Journal subject:
Veterinary Medicine
Year:
2020
Document Type:
Article
Affiliation country:
Tbed.13588
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