Literature DB >> 30269696

Accurate identification of Australian mosquitoes using protein profiling.

Andrea L Lawrence1, Jana Batovska2, Cameron E Webb1, Stacey E Lynch2, Mark J Blacket2, Jan Šlapeta3, Philippe Parola4, Maureen Laroche4.   

Abstract

Australian mosquito species significantly impact human health through nuisance biting and the transmission of endemic and exotic pathogens. Surveillance programmes designed to provide an early warning of mosquito-borne disease risk require reliable identification of mosquitoes. This study aimed to investigate the viability of Matrix-Assisted Laser Desorption/Ionization-Time-of-Flight Mass Spectrometry (MALDI-TOF MS) as a rapid and inexpensive approach to the identification of Australian mosquitoes and was validated using a three-step taxonomic approach. A total of 300 mosquitoes representing 21 species were collected from south-eastern New South Wales and morphologically identified. The legs from the mosquitoes were removed and subjected to MALDI-TOF MS analysis. Fifty-eight mosquitoes were sequenced at the cytochrome c oxidase subunit I (cox1) gene region and genetic relationships were analysed. We create the first MALDI-TOF MS spectra database of Australian mosquito species including 19 species. We clearly demonstrate the accuracy of MALDI-TOF MS for identification of Australian mosquitoes. It is especially useful for assessing gaps in the effectiveness of DNA barcoding by differentiating closely related taxa. Indeed, cox1 DNA barcoding was not able to differentiate members of the Culex pipiens group, Cx. quinquefasciatus and Cx. pipiens molestus, but these specimens were correctly identified using MALDI-TOF MS.

Entities:  

Keywords:  DNA barcoding; MALDI-TOF MS; identification; mosquitoes; protein profiling; surveillance

Mesh:

Substances:

Year:  2018        PMID: 30269696     DOI: 10.1017/S0031182018001658

Source DB:  PubMed          Journal:  Parasitology        ISSN: 0031-1820            Impact factor:   3.234


  6 in total

1.  Enhanced procedures for mosquito identification by MALDI-TOF MS.

Authors:  Roland Bamou; Monique Melo Costa; Adama Zan Diarra; Ademir Jesus Martins; Philippe Parola; Lionel Almeras
Journal:  Parasit Vectors       Date:  2022-06-30       Impact factor: 4.047

2.  MALDI-TOF MS: An effective tool for a global surveillance of dengue vector species.

Authors:  Antsa Rakotonirina; Morgane Pol; Fara Nantenaina Raharimalala; Valentine Ballan; Malia Kainiu; Sébastien Boyer; Sosiasi Kilama; Sébastien Marcombe; Sylvie Russet; Emilie Barsac; Rama Vineshwaran; Malia Kaleméli Selemago; Vincent Jessop; Geneviève Robic; Romain Girod; Paul T Brey; Julien Colot; Myrielle Dupont-Rouzeyrol; Vincent Richard; Nicolas Pocquet
Journal:  PLoS One       Date:  2022-10-20       Impact factor: 3.752

3.  Breeding Site Characteristics and Associated Factors of Culex pipiens Complex in Lhasa, Tibet, P. R. China.

Authors:  Xiaobo Liu; Haixia Wu; Yuhong Guo; Dongsheng Ren; Jun Yang; Jing Li; Ning Zhao; Jimin Sun; Jing Li; Jun Wang; Qiyong Liu
Journal:  Int J Environ Res Public Health       Date:  2019-04-18       Impact factor: 3.390

4.  Development of MALDI-TOF mass spectrometry for the identification of lice isolated from farm animals.

Authors:  Basma Ouarti; Maureen Laroche; Souad Righi; Mohamed Nadir Meguini; Ahmed Benakhla; Didier Raoult; Philippe Parola
Journal:  Parasite       Date:  2020-04-30       Impact factor: 3.000

5.  MALDI-TOF mass spectrometry identification of mosquitoes collected in Vietnam.

Authors:  Ly Na Huynh; Adama Zan Diarra; Hong Sang Nguyen; Long Bien Tran; Van Nguyen Do; Tran Duc Anh Ly; Van Hoang Ho; Xuan Quang Nguyen; Philippe Parola
Journal:  Parasit Vectors       Date:  2022-01-28       Impact factor: 3.876

6.  Using MALDI-TOF mass spectrometry to identify ticks collected on domestic and wild animals from the Democratic Republic of the Congo.

Authors:  Steve Ngoy; Adama Zan Diarra; Anne Laudisoit; Guy-Crispin Gembu; Erik Verheyen; Onésime Mubenga; Sylvestre Gambalemoke Mbalitini; Pascal Baelo; Maureen Laroche; Philippe Parola
Journal:  Exp Appl Acarol       Date:  2021-06-19       Impact factor: 2.132

  6 in total

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