Articles producció científica> Bioquímica i Biotecnologia

An Unsupervised Algorithm for Host Identification in Flaviviruses

  • Dades identificatives

    Identificador: imarina:9216859
    Autors:
    Phuoc Truong NguyenGarcia-Valle, SantiagoPuigbo, Pere
    Resum:
    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.
  • Altres:

    Autor segons l'article: Phuoc Truong Nguyen; Garcia-Valle, Santiago; Puigbo, Pere;
    Departament: Bioquímica i Biotecnologia
    Autor/s de la URV: Garcia Vallve, Santiago / PUIGBÒ AVALOS, PEDRO
    Paraules clau: Virus Host identification Genus Flavivirus Codon usage bias Codon adaptation index Algorithm Adaptation
    Resum: 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.
    Àrees temàtiques: 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)
    Accès a la llicència d'ús: https://creativecommons.org/licenses/by/3.0/es/
    Adreça de correu electrònic de l'autor: santi.garcia-vallve@urv.cat
    Identificador de l'autor: 0000-0002-0348-7497
    Data d'alta del registre: 2024-10-26
    Versió de l'article dipositat: info:eu-repo/semantics/publishedVersion
    Enllaç font original: https://www.mdpi.com/2075-1729/11/5/442
    URL Document de llicència: https://repositori.urv.cat/ca/proteccio-de-dades/
    Referència a l'article segons font original: Life. 11 (5):
    Referència 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 de l'article: 10.3390/life11050442
    Entitat: Universitat Rovira i Virgili
    Any de publicació de la revista: 2021
    Tipus de publicació: Journal Publications
  • Paraules clau:

    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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