Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall

The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.

Saved in:
Bibliographic Details
Main Authors: Fukutani,Eduardo, Rodrigues,Moreno, Kasprzykowski,José Irahe, Araujo,Cintia Figueiredo de, Paschoal,Alexandre Rossi, Ramos,Pablo Ivan Pereira, Fukutani,Kiyoshi Ferreira, Queiroz,Artur Trancoso Lopo de
Format: Digital revista
Language:English
Published: Instituto Oswaldo Cruz, Ministério da Saúde 2018
Online Access:http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762018000600402
Tags: Add Tag
No Tags, Be the first to tag this record!
id oai:scielo:S0074-02762018000600402
record_format ojs
spelling oai:scielo:S0074-027620180006004022018-05-23Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wallFukutani,EduardoRodrigues,MorenoKasprzykowski,José IraheAraujo,Cintia Figueiredo dePaschoal,Alexandre RossiRamos,Pablo Ivan PereiraFukutani,Kiyoshi FerreiraQueiroz,Artur Trancoso Lopo de RNA-seq signature transcriptome Zika virus The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.info:eu-repo/semantics/openAccessInstituto Oswaldo Cruz, Ministério da SaúdeMemórias do Instituto Oswaldo Cruz v.113 n.6 20182018-01-01info:eu-repo/semantics/othertext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762018000600402en10.1590/0074-02760180053
institution SCIELO
collection OJS
country Brasil
countrycode BR
component Revista
access En linea
databasecode rev-scielo-br
tag revista
region America del Sur
libraryname SciELO
language English
format Digital
author Fukutani,Eduardo
Rodrigues,Moreno
Kasprzykowski,José Irahe
Araujo,Cintia Figueiredo de
Paschoal,Alexandre Rossi
Ramos,Pablo Ivan Pereira
Fukutani,Kiyoshi Ferreira
Queiroz,Artur Trancoso Lopo de
spellingShingle Fukutani,Eduardo
Rodrigues,Moreno
Kasprzykowski,José Irahe
Araujo,Cintia Figueiredo de
Paschoal,Alexandre Rossi
Ramos,Pablo Ivan Pereira
Fukutani,Kiyoshi Ferreira
Queiroz,Artur Trancoso Lopo de
Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
author_facet Fukutani,Eduardo
Rodrigues,Moreno
Kasprzykowski,José Irahe
Araujo,Cintia Figueiredo de
Paschoal,Alexandre Rossi
Ramos,Pablo Ivan Pereira
Fukutani,Kiyoshi Ferreira
Queiroz,Artur Trancoso Lopo de
author_sort Fukutani,Eduardo
title Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
title_short Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
title_full Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
title_fullStr Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
title_full_unstemmed Follow up of a robust meta-signature to identify Zika virus infection in Aedes aegypti: another brick in the wall
title_sort follow up of a robust meta-signature to identify zika virus infection in aedes aegypti: another brick in the wall
description The mosquito Aedes aegypti is the main vector of several arthropod-borne diseases that have global impacts. In a previous meta-analysis, our group identified a vector gene set containing 110 genes strongly associated with infections of dengue, West Nile and yellow fever viruses. Of these 110 genes, four genes allowed a highly accurate classification of infected status. More recently, a new study of Ae. aegypti infected with Zika virus (ZIKV) was published, providing new data to investigate whether this “infection” gene set is also altered during a ZIKV infection. Our hypothesis is that the infection-associated signature may also serve as a proxy to classify the ZIKV infection in the vector. Raw data associated with the NCBI/BioProject were downloaded and re-analysed. A total of 18 paired-end replicates corresponding to three ZIKV-infected samples and three controls were included in this study. The nMDS technique with a logistic regression was used to obtain the probabilities of belonging to a given class. Thus, to compare both gene sets, we used the area under the curve and performed a comparison using the bootstrap method. Our meta-signature was able to separate the infected mosquitoes from the controls with good predictive power to classify the Zika-infected mosquitoes.
publisher Instituto Oswaldo Cruz, Ministério da Saúde
publishDate 2018
url http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0074-02762018000600402
work_keys_str_mv AT fukutanieduardo followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT rodriguesmoreno followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT kasprzykowskijoseirahe followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT araujocintiafigueiredode followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT paschoalalexandrerossi followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT ramospabloivanpereira followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT fukutanikiyoshiferreira followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
AT queirozarturtrancosolopode followupofarobustmetasignaturetoidentifyzikavirusinfectioninaedesaegyptianotherbrickinthewall
_version_ 1756383888267018240