Articles producció científica> Bioquímica i Biotecnologia

An Unsupervised Algorithm for Host Identification in Flaviviruses

  • Datos identificativos

    Identificador: imarina:9216859
    Autores:
    Phuoc Truong NguyenGarcia-Valle, SantiagoPuigbo, Pere
    Resumen:
    Early characterization of emerging viruses is essential to control their spread, such as the Zika Virus outbreak in 2014. Among other non-viral factors, host information is essential for the surveillance and control of virus spread. Flaviviruses (genus Flavivirus), akin to other viruses, are modulated by high mutation rates and selective forces to adapt their codon usage to that of their hosts. However, a major challenge is the identification of potential hosts for novel viruses. Usually, potential hosts of emerging zoonotic viruses are identified after several confirmed cases. This is inefficient for deterring future outbreaks. In this paper, we introduce an algorithm to identify the host range of a virus from its raw genome sequences. The proposed strategy relies on comparing codon usage frequencies across viruses and hosts, by means of a normalized Codon Adaptation Index (CAI). We have tested our algorithm on 94 flaviviruses and 16 potential hosts. This novel method is able to distinguish between arthropod and vertebrate hosts for several flaviviruses with high values of accuracy (virus group 91.9% and host type 86.1%) and specificity (virus group 94.9% and host type 79.6%), in comparison to empirical observations. Overall, this algorithm may be useful as a complementary tool to current phylogenetic methods in monitoring current and future viral outbreaks by understanding host-virus relationships.
  • Otros:

    Autor según el artículo: Phuoc Truong Nguyen; Garcia-Valle, Santiago; Puigbo, Pere;
    Departamento: Bioquímica i Biotecnologia
    Autor/es de la URV: Garcia Vallve, Santiago / PUIGBÒ AVALOS, PEDRO
    Palabras clave: Virus Host identification Genus Flavivirus Codon usage bias Codon adaptation index Algorithm Adaptation
    Resumen: Early characterization of emerging viruses is essential to control their spread, such as the Zika Virus outbreak in 2014. Among other non-viral factors, host information is essential for the surveillance and control of virus spread. Flaviviruses (genus Flavivirus), akin to other viruses, are modulated by high mutation rates and selective forces to adapt their codon usage to that of their hosts. However, a major challenge is the identification of potential hosts for novel viruses. Usually, potential hosts of emerging zoonotic viruses are identified after several confirmed cases. This is inefficient for deterring future outbreaks. In this paper, we introduce an algorithm to identify the host range of a virus from its raw genome sequences. The proposed strategy relies on comparing codon usage frequencies across viruses and hosts, by means of a normalized Codon Adaptation Index (CAI). We have tested our algorithm on 94 flaviviruses and 16 potential hosts. This novel method is able to distinguish between arthropod and vertebrate hosts for several flaviviruses with high values of accuracy (virus group 91.9% and host type 86.1%) and specificity (virus group 94.9% and host type 79.6%), in comparison to empirical observations. Overall, this algorithm may be useful as a complementary tool to current phylogenetic methods in monitoring current and future viral outbreaks by understanding host-virus relationships.
    Áreas temáticas: Space and planetary science Paleontology General biochemistry,genetics and molecular biology Ecology, evolution, behavior and systematics Biology Biochemistry, genetics and molecular biology (miscellaneous) Biochemistry, genetics and molecular biology (all)
    Acceso a la licencia de uso: https://creativecommons.org/licenses/by/3.0/es/
    Direcció de correo del autor: santi.garcia-vallve@urv.cat
    Identificador del autor: 0000-0002-0348-7497
    Fecha de alta del registro: 2024-10-26
    Versión del articulo depositado: info:eu-repo/semantics/publishedVersion
    Enlace a la fuente original: https://www.mdpi.com/2075-1729/11/5/442
    URL Documento de licencia: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referencia al articulo segun fuente origial: Life. 11 (5):
    Referencia de l'ítem segons les normes APA: Phuoc Truong Nguyen; Garcia-Valle, Santiago; Puigbo, Pere; (2021). An Unsupervised Algorithm for Host Identification in Flaviviruses. Life, 11(5), -. DOI: 10.3390/life11050442
    DOI del artículo: 10.3390/life11050442
    Entidad: Universitat Rovira i Virgili
    Año de publicación de la revista: 2021
    Tipo de publicación: Journal Publications
  • Palabras clave:

    Biochemistry, Genetics and Molecular Biology (Miscellaneous),Biology,Ecology, Evolution, Behavior and Systematics,Paleontology,Space and Planetary Science
    Virus
    Host identification
    Genus
    Flavivirus
    Codon usage bias
    Codon adaptation index
    Algorithm
    Adaptation
    Space and planetary science
    Paleontology
    General biochemistry,genetics and molecular biology
    Ecology, evolution, behavior and systematics
    Biology
    Biochemistry, genetics and molecular biology (miscellaneous)
    Biochemistry, genetics and molecular biology (all)
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