Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America

Autores
Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; Marti, Gerardo Anibal
Año de publicación
2015
Idioma
inglés
Tipo de recurso
artículo
Estado
versión publicada
Descripción
Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.
Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; Argentina
Fil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Materia
Triatoma virus
TriatominaE
Ecological Niche Modelling
MaxEnt
WorldClim
AVHRR imagery
Nivel de accesibilidad
acceso abierto
Condiciones de uso
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
Repositorio
CONICET Digital (CONICET)
Institución
Consejo Nacional de Investigaciones Científicas y Técnicas
OAI Identificador
oai:ri.conicet.gov.ar:11336/10684
Acceder
id CONICETDig_83763d773edf079665f93e4615891c95
oai_identifier_str oai:ri.conicet.gov.ar:11336/10684
network_acronym_str CONICETDig
repository_id_str 3498
network_name_str CONICET Digital (CONICET)
spelling Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South AmericaCeccarelli, SoledadBalsalobre, AgustinSusevich, Maria LauraEcheverria, Maria GabrielaGorla, David EladioMarti, Gerardo AnibalTriatoma virusTriatominaEEcological Niche ModellingMaxEntWorldClimAVHRR imageryhttps://purl.org/becyt/ford/1.6https://purl.org/becyt/ford/1Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaFil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; ArgentinaFil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; ArgentinaFil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; ArgentinaBiomed Central2015-03info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionhttp://purl.org/coar/resource_type/c_6501info:ar-repo/semantics/articuloapplication/pdfapplication/pdfapplication/pdfapplication/pdfapplication/pdfhttp://hdl.handle.net/11336/10684Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-20151756-3305enginfo:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pubmed/25881183info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25881183/info:eu-repo/semantics/openAccesshttps://creativecommons.org/licenses/by-nc-sa/2.5/ar/reponame:CONICET Digital (CONICET)instname:Consejo Nacional de Investigaciones Científicas y Técnicas2025-10-22T12:08:00Zoai:ri.conicet.gov.ar:11336/10684instacron:CONICETInstitucionalhttp://ri.conicet.gov.ar/Organismo científico-tecnológicoNo correspondehttp://ri.conicet.gov.ar/oai/requestdasensio@conicet.gov.ar; lcarlino@conicet.gov.arArgentinaNo correspondeNo correspondeNo correspondeopendoar:34982025-10-22 12:08:01.216CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicasfalse
dc.title.none.fl_str_mv Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
title Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
spellingShingle Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
Ceccarelli, Soledad
Triatoma virus
TriatominaE
Ecological Niche Modelling
MaxEnt
WorldClim
AVHRR imagery
title_short Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
title_full Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
title_fullStr Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
title_full_unstemmed Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
title_sort Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America
dc.creator.none.fl_str_mv Ceccarelli, Soledad
Balsalobre, Agustin
Susevich, Maria Laura
Echeverria, Maria Gabriela
Gorla, David Eladio
Marti, Gerardo Anibal
author Ceccarelli, Soledad
author_facet Ceccarelli, Soledad
Balsalobre, Agustin
Susevich, Maria Laura
Echeverria, Maria Gabriela
Gorla, David Eladio
Marti, Gerardo Anibal
author_role author
author2 Balsalobre, Agustin
Susevich, Maria Laura
Echeverria, Maria Gabriela
Gorla, David Eladio
Marti, Gerardo Anibal
author2_role author
author
author
author
author
dc.subject.none.fl_str_mv Triatoma virus
TriatominaE
Ecological Niche Modelling
MaxEnt
WorldClim
AVHRR imagery
topic Triatoma virus
TriatominaE
Ecological Niche Modelling
MaxEnt
WorldClim
AVHRR imagery
purl_subject.fl_str_mv https://purl.org/becyt/ford/1.6
https://purl.org/becyt/ford/1
dc.description.none.fl_txt_mv Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.
Fil: Ceccarelli, Soledad. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Balsalobre, Agustin. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Susevich, Maria Laura. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
Fil: Echeverria, Maria Gabriela. Universidad Nacional de la Plata. Facultad de Ciencias Veterinarias. Departamento de Microbiología. Cátedra de Virología; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina
Fil: Gorla, David Eladio. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Regional de Investigaciones Cientificas y Transferencia Tecnológica de Anillaco; Argentina
Fil: Marti, Gerardo Anibal. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico la Plata. Centro de Estudios Parasitológicos y de Vectores (i); Argentina. Universidad Nacional de La Plata. Facultad de Ciencias Naturales y Museo; Argentina
description Background: Triatoma virus (TrV) is the only entomopathogenous virus identified in triatomines. We estimated the potential geographic distribution of triatomine species naturally infected by TrV, using remotely sensed and meteorological environmental variables, to predict new potential areas where triatomines infected with TrV may be found. Methods: Detection of TrV infection in samples was performed with RT-PCR. Ecological niche models (ENM) were constructed using the MaxEnt software. We used 42 environmental variables derived from remotely sensed imagery (AVHRR) and 19 bioclimatic variables (Bioclim). The MaxEnt Jackknife procedure was used to minimize the number of environmental variables that showed an influence on final models. The goodness of fit of the model predictions was evaluated by the mean area under the curve (AUC). Results: We obtained 37 samples of 7 species of triatomines naturally infected with TrV. Of the TrV positive samples, 32% were from sylvatic habitat, 46% came from peridomicile habitats and 22% from domicile habitats. Five of the seven infected species were found only in the sylvatic habitat, one species only in the domicile and only Triatoma infestans was found in the three habitats. The MaxEnt model estimated with the Bioclim dataset identified five environmental variables as best predictors: temperature annual range, mean diurnal range, mean temperature of coldest quarter, temperature seasonality and annual mean temperature. The model using the AVHRR dataset identified six environmental variables: minimum Land Surface Temperature (LST), minimum Middle Infrared Radiation (MIR), LST annual amplitude, MIR annual amplitude annual, LST variance and MIR variance. The potential geographic distribution of triatomine species infected by TrV coincides with the Chaco and the Monte ecoregions either modelled by AVHRR or Bioclim environmental datasets. Conclusions: Our results show that the conditions of the Dry Chaco ecoregion in Argentina are favourable for the infection of triatomine species with TrV, and open the possibility of its use as a potential agent for the biological control of peridomestic and/or sylvatic triatomine species. Results identify areas of potential occurrence that should be verified in the field.
publishDate 2015
dc.date.none.fl_str_mv 2015-03
dc.type.none.fl_str_mv info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
http://purl.org/coar/resource_type/c_6501
info:ar-repo/semantics/articulo
format article
status_str publishedVersion
dc.identifier.none.fl_str_mv http://hdl.handle.net/11336/10684
Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-2015
1756-3305
url http://hdl.handle.net/11336/10684
identifier_str_mv Ceccarelli, Soledad; Balsalobre, Agustin; Susevich, Maria Laura; Echeverria, Maria Gabriela; Gorla, David Eladio; et al.; Modelling the potential geographic distribution of triatomines infected by Triatoma virus in the southern cone of South America; Biomed Central; Parasites And Vectors; 8; 153; 3-2015
1756-3305
dc.language.none.fl_str_mv eng
language eng
dc.relation.none.fl_str_mv info:eu-repo/semantics/altIdentifier/doi/10.1186/s13071-015-0761-1
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pubmed/25881183
info:eu-repo/semantics/altIdentifier/url/https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/25881183/
dc.rights.none.fl_str_mv info:eu-repo/semantics/openAccess
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
eu_rights_str_mv openAccess
rights_invalid_str_mv https://creativecommons.org/licenses/by-nc-sa/2.5/ar/
dc.format.none.fl_str_mv application/pdf
application/pdf
application/pdf
application/pdf
application/pdf
dc.publisher.none.fl_str_mv Biomed Central
publisher.none.fl_str_mv Biomed Central
dc.source.none.fl_str_mv reponame:CONICET Digital (CONICET)
instname:Consejo Nacional de Investigaciones Científicas y Técnicas
reponame_str CONICET Digital (CONICET)
collection CONICET Digital (CONICET)
instname_str Consejo Nacional de Investigaciones Científicas y Técnicas
repository.name.fl_str_mv CONICET Digital (CONICET) - Consejo Nacional de Investigaciones Científicas y Técnicas
repository.mail.fl_str_mv dasensio@conicet.gov.ar; lcarlino@conicet.gov.ar
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