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Title: Comparison of Recombinant Proteins of Kinesin 39, Heat Shock Protein 70, Heat Shock Protein 83, and Glycoprotein 63 for Antibody Detection of Leishmania martiniquensis Infection
Authors: Suradej Siripattanapipong
Hirotomo Kato
Peerapan Tan-ariya
Mathirut Mungthin
Saovanee Leelayoova
Mahidol University
Jichi Medical University
Phramongkutklao College of Medicine
Keywords: Immunology and Microbiology
Issue Date: 1-Nov-2017
Citation: Journal of Eukaryotic Microbiology. Vol.64, No.6 (2017), 820-828
Abstract: © 2017 The Author(s) Journal of Eukaryotic Microbiology © 2017 International Society of Protistologists Leishmania martiniquensis, a zoonotic hemoflagellate, is a causative agent of cutaneous (CL) and visceral leishmaniasis (VL) among humans and animals. This organism, first reported in Martinique Island, now has become an emerging infectious agent in Thailand. Symptomatic cases of L. martiniquensis infection among humans have continuously increased. In the meantime, asymptomatic infection of this novel species has seriously created national public health awareness and concern to prevent and control disease transmission. The unsuccessful serological test using the commercial rK39 dipstick based on antigen from Leishmania donovani to detect the antibodies against VL among infected Thai patients has encouraged us to further explore a new sensitive and specific antigenic epitope. In this study, we determined the sequences and expressed recombinant proteins of kinesin 39 (k39), heat shock protein 70 (hsp70), heat shock protein 83 (hsp83), and glycoprotein 63 (gp63) of L. martiniquensis to evaluate the diagnostic efficiency to detect antibodies against L. martiniquensis in patient sera. The preliminary results from western blot analysis have suggested that K39 is the most sensitive recombinant protein to detect L. martiniquensis. Moreover, this recombinant protein reacts with antibodies against L. donovani and Leishmania infantum, making it a promising antigen for further development of a universal rapid diagnostic tool for VL.
ISSN: 15507408
Appears in Collections:Scopus 2016-2017

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