Cargando…

Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading

Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mos...

Descripción completa

Detalles Bibliográficos
Autores principales: Wang, Mei-Hui, Marinotti, Osvaldo, Zhong, Daibin, James, Anthony A., Walker, Edward, Guda, Tom, Kweka, Eliningaya J., Githure, John, Yan, Guiyun
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720620/
https://www.ncbi.nlm.nih.gov/pubmed/23936017
http://dx.doi.org/10.1371/journal.pone.0069439
_version_ 1782277976751079424
author Wang, Mei-Hui
Marinotti, Osvaldo
Zhong, Daibin
James, Anthony A.
Walker, Edward
Guda, Tom
Kweka, Eliningaya J.
Githure, John
Yan, Guiyun
author_facet Wang, Mei-Hui
Marinotti, Osvaldo
Zhong, Daibin
James, Anthony A.
Walker, Edward
Guda, Tom
Kweka, Eliningaya J.
Githure, John
Yan, Guiyun
author_sort Wang, Mei-Hui
collection PubMed
description Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mosquito age for Aedes and Anopheles mosquitoes, however, whether this new method is adequate for natural conditions is unknown. This study tests the applicability of transcriptional profiling for age-grading of Anopheles gambiae, the most important malaria vector in Africa. The transcript abundance of two An. gambiae genes, AGAP009551 and AGAP011615, was measured during aging under laboratory and field conditions in three mosquito strains. Age-dependent monotonic changes in transcript levels were observed in all strains evaluated. These genes were validated as age-grading biomarkers using the mark, release and recapture (MRR) method. The MRR method determined a good correspondence between actual and predicted age, and thus demonstrated the value of age classifications derived from the transcriptional profiling of these two genes. The technique was used to establish the age structure of mosquito populations from two malaria-endemic areas in western Kenya. The population age structure determined by the transcriptional profiling method was consistent with that based on mosquito parity. This study demonstrates that the transcription profiling method based on two genes is valuable for age determination of natural mosquitoes, providing a new approach for determining a key life history trait of malaria vectors.
format Online
Article
Text
id pubmed-3720620
institution National Center for Biotechnology Information
language English
publishDate 2013
publisher Public Library of Science
record_format MEDLINE/PubMed
spelling pubmed-37206202013-08-09 Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading Wang, Mei-Hui Marinotti, Osvaldo Zhong, Daibin James, Anthony A. Walker, Edward Guda, Tom Kweka, Eliningaya J. Githure, John Yan, Guiyun PLoS One Research Article Information on population age structure of mosquitoes under natural conditions is fundamental to the understanding of vectorial capacity and crucial for assessing the impact of vector control measures on malaria transmission. Transcriptional profiling has been proposed as a method for predicting mosquito age for Aedes and Anopheles mosquitoes, however, whether this new method is adequate for natural conditions is unknown. This study tests the applicability of transcriptional profiling for age-grading of Anopheles gambiae, the most important malaria vector in Africa. The transcript abundance of two An. gambiae genes, AGAP009551 and AGAP011615, was measured during aging under laboratory and field conditions in three mosquito strains. Age-dependent monotonic changes in transcript levels were observed in all strains evaluated. These genes were validated as age-grading biomarkers using the mark, release and recapture (MRR) method. The MRR method determined a good correspondence between actual and predicted age, and thus demonstrated the value of age classifications derived from the transcriptional profiling of these two genes. The technique was used to establish the age structure of mosquito populations from two malaria-endemic areas in western Kenya. The population age structure determined by the transcriptional profiling method was consistent with that based on mosquito parity. This study demonstrates that the transcription profiling method based on two genes is valuable for age determination of natural mosquitoes, providing a new approach for determining a key life history trait of malaria vectors. Public Library of Science 2013-07-23 /pmc/articles/PMC3720620/ /pubmed/23936017 http://dx.doi.org/10.1371/journal.pone.0069439 Text en © 2013 Wang et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Wang, Mei-Hui
Marinotti, Osvaldo
Zhong, Daibin
James, Anthony A.
Walker, Edward
Guda, Tom
Kweka, Eliningaya J.
Githure, John
Yan, Guiyun
Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title_full Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title_fullStr Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title_full_unstemmed Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title_short Gene Expression-Based Biomarkers for Anopheles gambiae Age Grading
title_sort gene expression-based biomarkers for anopheles gambiae age grading
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3720620/
https://www.ncbi.nlm.nih.gov/pubmed/23936017
http://dx.doi.org/10.1371/journal.pone.0069439
work_keys_str_mv AT wangmeihui geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT marinottiosvaldo geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT zhongdaibin geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT jamesanthonya geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT walkeredward geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT gudatom geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT kwekaeliningayaj geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT githurejohn geneexpressionbasedbiomarkersforanophelesgambiaeagegrading
AT yanguiyun geneexpressionbasedbiomarkersforanophelesgambiaeagegrading