Comparison of the RE-529 sequence and B1 gene for Toxoplasma gondii detection in blood samples of the at-risk seropositive cases using uracil DNA glycosylase supplemented loop-mediated isothermal amplification (UDG-LAMP) assay.


Journal

Microbial pathogenesis
ISSN: 1096-1208
Titre abrégé: Microb Pathog
Pays: England
ID NLM: 8606191

Informations de publication

Date de publication:
Mar 2020
Historique:
received: 26 08 2019
revised: 15 12 2019
accepted: 16 12 2019
pubmed: 22 12 2019
medline: 11 11 2020
entrez: 22 12 2019
Statut: ppublish

Résumé

Diagnosis of toxoplasmosis is an important issue, especially in at-risk patients. The molecular methods showed a promising future for such diagnosis; however, the method itself and the target sequence to be detected is an important part of accurate detection of the infection. The aim of the present study was to evaluate the RE-529 sequence and B1 gene for Toxoplasma gondii detection in blood samples of the at-risk seropositive cases using uracil DNA glycosylase supplemented loop-mediated isothermal amplification (UDG-LAMP) assay. In this study, 110 T. gondii seropositive at-risk individuals (pregnant women and immunocompromised patients) and 110 seronegative controls were enrolled. The two most studied sequences (RE-529 and B1) were used and compared for accurate and reliable detection of T. gondii in blood samples using UDG-LAMP assay and compared with real-time PCR method. The detection limit, accuracy, and reliability of UDG-LAMP for the parasite's DNA were also studied. Among 110 studied cases, 39 (35.45%) and 36 (32.7%) were positive for T. gondii DNA with the RE-LAMP and B1-LAMP, respectively. The seronegative cases remained negative for T. gondii DNA with the studied genes, however, there were few false negatives compared with real-time PCR method. The detection limit of the UDG-LAMP for both DNA targets was 0.16 tachyzoite's DNA per reaction tube. Based on the results of this study, the RE-529 sequence has a better detection rate compared to the B1 gene for toxoplasmosis among at-risk people. UDG-LAMP is a highly sensitive, accurate, and reliable method with no false-positive results for the diagnosis of T. gondii infection in blood specimens, however few cases may be missed.

Identifiants

pubmed: 31862390
pii: S0882-4010(19)31512-8
doi: 10.1016/j.micpath.2019.103938
pii:
doi:

Substances chimiques

DNA, Protozoan 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

103938

Informations de copyright

Copyright © 2019. Published by Elsevier Ltd.

Déclaration de conflit d'intérêts

Declaration of competing interest The authors declare that have no conflict of interests.

Auteurs

Hossein Keshavarz Valian (HK)

Department of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Hossein Mirhendi (H)

Department of Medical Parasitology and Mycology, School of Medicine, Isfahan University of Medical Sciences, Isfahan, Iran.

Mehdi Mohebali (M)

Department of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran; Center for Research of Endemic Parasites of Iran, Tehran University of Medical Sciences, Tehran, Iran.

Saeedeh Shojaee (S)

Department of Medical Parasitology and Mycology, School of Public Health, Tehran University of Medical Sciences, Tehran, Iran.

Shirzad Fallahi (S)

Hepatitis Research Center, Lorestan University of Medical Sciences, Khorramabad, Iran; Department of Medical Parasitology and Mycology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran.

Rasool Jafari (R)

Department of Medical Parasitology and Mycology, Faculty of Medicine, Urmia University of Medical Sciences, Urmia, Iran.

Farnaz Kheirandish (F)

Department of Medical Parasitology and Mycology, Faculty of Medicine, Lorestan University of Medical Sciences, Khorramabad, Iran.

Parisa Mousavi (P)

Skin Diseases and Leishmaniasis Research Center, Isfahan University of Medical Sciences, Isfahan, Iran. Electronic address: pra.mousavi@gmail.com.

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Classifications MeSH