The Bayesian reconstruction and the evolutionary history of Salivirus type 1 and type 2: the worldwide spreading

Silvia Angeletti; Domenico Benvenuto; Marta Fogolari; Cecilia De Flora; Giancarlo Ceccarelli; Ivana Maida; Riccardo Bazzardi; Silvia Spoto; Stefano Pascarella; Boban Mugosa; Massimo Ciccozzi

doi:10.3855/jidc.12141

The Bayesian reconstruction and the evolutionary history of Salivirus type 1 and type 2: the worldwide spreading

Authors

Silvia Angeletti Unit of Clinical Laboratory Science, University Campus Bio-Medico of Rome, Italy
Domenico Benvenuto Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Italy
Marta Fogolari Unit of Clinical Laboratory Science, University Campus Bio-Medico of Rome, Italy
Cecilia De Flora Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Italy
Giancarlo Ceccarelli Department of Public Health and Infectious Diseases, University of Rome, “Sapienza”, Policlinico “Umberto I”, Rome, Italy
Ivana Maida Department of Medical, Surgical and Experimental Sciences Infectious Diseases, University of Sassari, Italy
Riccardo Bazzardi Controllo Microbiologico e Ispezione degli Alimenti, Istituto Zooprofilattico Sperimentale della Sardegna “G. Pegreffi”, Sassari, Italy
Silvia Spoto 7Diagnostic and Therapeutic Medicine Department, University Campus Bio-Medico of Rome, Rome, Italy
Stefano Pascarella Department of Biochemical Science “A. Rossi Fanelli”, Sapienza University, Rome, Italy
Boban Mugosa Institute of Public Health, Podgorica, Montenegro
Massimo Ciccozzi Unit of Medical Statistics and Molecular Epidemiology, University Campus Bio-Medico of Rome, Italy

DOI:

https://doi.org/10.3855/jidc.12141

Keywords:

Salivirus, Bayesian analysis, evolutionary analysis, homology modelling

Abstract

Introduction: Salivirus (SalV) represents an emerging problem in public health especially during the recent years. In this study, the Bayesian evolutionary history and the spread of the virus through the different countries have been reported.

Methodology: a database of 81 sequences of SalV structural VP1 fragment were downloaded from GenBank, aligned and manually edited by Bioedit Software. ModelTest v. 3.7 software was used to estimate the simplest evolutionary model fitting the sequence dataset. A Maximum-Likelihood tree has been generated using MEGA-X to test the “clockliness” signal using TempEst 1.5.1. The Bayesian phylogenetic tree was built by BEAST. Homology modelling was performed by SWISS-Model and protein variability evaluated by ConSurf server.

Results: the phylogenetic tree showed a clade of SalV A2 and three main clades of SalV A1, revealing several infections in humans in South Korea, India, Tunisia, China, Nigeria, Ethiopia and USA. The Bayesian maximum clade credibility tree and the time of the most common recent ancestor dated back the root of the tree to the year 1788 with the probable origin in USA. Selective pressure analysis revealed two positive selection sites, His at 100^th and Leu at 116^th positions that at the homology modelling resulted important to guarantee protein stability and variability. This could contribute to the development of new mutations modifying the clinical features of this evolving virus.

Conclusions: Bayesian phylogenetic and phylodynamic represented a useful tool to follow the transmission dynamic of SalV and to prevent new epidemics worldwide.

Downloads

Published

2021-03-07

How to Cite

Angeletti S, Benvenuto D, Fogolari M, De Flora C, Ceccarelli G, Maida I, Bazzardi R, Spoto S, Pascarella S, Mugosa B, Ciccozzi M (2021) The Bayesian reconstruction and the evolutionary history of Salivirus type 1 and type 2: the worldwide spreading. J Infect Dev Ctries 15:280–288. doi: 10.3855/jidc.12141

Download Citation

Endnote/Zotero/Mendeley (RIS)

Issue

Vol. 15 No. 02: February 2021

Section

Original Articles

License

Authors who publish with this journal agree to the following terms:

Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution License that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book), with an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See The Effect of Open Access).