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dc.contributor.author | Moreno-Mesonero, L. | es_ES |
dc.contributor.author | Amoros, Inmaculada | es_ES |
dc.contributor.author | Moreno Trigos, Mª Yolanda | es_ES |
dc.contributor.author | Alonso Molina, José Luís | es_ES |
dc.date.accessioned | 2023-05-26T18:01:34Z | |
dc.date.available | 2023-05-26T18:01:34Z | |
dc.date.issued | 2022-07-15 | es_ES |
dc.identifier.issn | 0301-4797 | es_ES |
dc.identifier.uri | http://hdl.handle.net/10251/193622 | |
dc.description.abstract | [EN] Waterborne parasitic protozoa (WPP) infections have a worldwide distribution and are a source for epidemic and endemic human diseases. Although a variety of protozoa are commonly detected in wastewater and cited as causative agents of outbreaks, effluents from wastewater treatment plants (WWTPs) used for irrigation can contain other pathogenic protozoa that are not currently being controlled. The lack of control on a routine basis using rapid and sensitive methods to detect these parasites in water may keep them under-recognized. This study focused on using molecular tools, 18 S rRNA amplicon-based sequencing and qPCR, to characterize WPP distribution in wastewater samples from urban WWTPs used for irrigation. A total of eight wastewater samples (from secondary and tertiary disinfection treatment effluents) were collected. Potentially pathogenic protozoa identified by 18 S rRNA sequencing and/or qPCR in the analyzed samples included Acanthamoeba spp., Blastocystis sp., Entamoeba coli, Entamoeba dispar, Entamoeba hartmanni, Giardia intestinalis assemblage A and Toxoplasma gondii Positive results by qPCR were in non-quantifiable levels. Blastocystis sp. was the most represented protozoa among the sequences retrieved from the amplicon sequencing. Blastocystis ST1 and ST2 were the most abundant subtypes among the obtained OTUs. Moreover, Blastocystis sp. ST3, ST4, ST6 and ST8 were also detected, although in lower abundances. Results of this study showed that WWTP effluents used for irrigation can provide a source of WPP. | es_ES |
dc.description.sponsorship | This work has been financed through the project funded by the Spanish Ministry of Economy and Competitiveness (MINECO), in the frame of the collaborative international consortium JPIW2013-095-C0302 -METAWATER of the Water Challenges for a Changing World Joint Programming Initiative (Water JPI) Pilot Call. | es_ES |
dc.language | Inglés | es_ES |
dc.publisher | Elsevier | es_ES |
dc.relation.ispartof | Journal of Environmental Management | es_ES |
dc.rights | Reconocimiento - No comercial - Sin obra derivada (by-nc-nd) | es_ES |
dc.subject | Irrigation water | es_ES |
dc.subject | Wastewater | es_ES |
dc.subject | Waterborne parasitic protozoa | es_ES |
dc.subject | Blastocystis subtypesq | es_ES |
dc.subject | PCRAmplicon sequencing | es_ES |
dc.title | Simultaneous detection of less frequent waterborne parasitic protozoa in reused wastewater using amplicon sequencing and qPCR techniques | es_ES |
dc.type | Artículo | es_ES |
dc.identifier.doi | 10.1016/j.jenvman.2022.115029 | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//JPIW2013-095-C03-02/ES/NUEVOS INSTRUMENTOS MOLECULARES Y DE METAGENOMICA PARA LA IDENTIFICACION Y CONTROL A ESCALA EUROPEA DE CONTAMINANTES MICROBIANOS EMERGENTES EN AGUA DE RIEGO/ | es_ES |
dc.relation.projectID | info:eu-repo/grantAgreement/MINECO//JPIW2013-095-C03-02//NUEVOS INSTRUMENTOS MOLECULARES Y DE METAGENOMICA PARA LA IDENTIFICACION Y CONTROL A ESCALA EUROPEA DE CONTAMINANTES MICROBIANOS EMERGENTES EN AGUA DE RIEGO/ | es_ES |
dc.rights.accessRights | Abierto | es_ES |
dc.contributor.affiliation | Universitat Politècnica de València. Instituto Universitario de Ingeniería del Agua y del Medio Ambiente - Institut Universitari d'Enginyeria de l'Aigua i Medi Ambient | es_ES |
dc.description.bibliographicCitation | Moreno-Mesonero, L.; Amoros, I.; Moreno Trigos, MY.; Alonso Molina, JL. (2022). Simultaneous detection of less frequent waterborne parasitic protozoa in reused wastewater using amplicon sequencing and qPCR techniques. Journal of Environmental Management. 314:1-9. https://doi.org/10.1016/j.jenvman.2022.115029 | es_ES |
dc.description.accrualMethod | S | es_ES |
dc.relation.publisherversion | https://doi.org/10.1016/j.jenvman.2022.115029 | es_ES |
dc.description.upvformatpinicio | 1 | es_ES |
dc.description.upvformatpfin | 9 | es_ES |
dc.type.version | info:eu-repo/semantics/publishedVersion | es_ES |
dc.description.volume | 314 | es_ES |
dc.identifier.pmid | 35430514 | es_ES |
dc.relation.pasarela | S\468672 | es_ES |
dc.contributor.funder | Ministerio de Economía y Competitividad | es_ES |