Literature DB >> 21995923

Matrix-assisted laser desorption/ionization-mass spectrometry of cuticular lipid profiles can differentiate sex, age, and mating status of Anopheles gambiae mosquitoes.

Estrella Suarez1, Hien P Nguyen, Israel P Ortiz, Kyu Jong Lee, Seoung Bum Kim, Jaroslaw Krzywinski, Kevin A Schug.   

Abstract

Malaria is a devastating mosquito-borne disease, which affects hundreds of millions of people each year. It is transmitted predominantly by Anopheles gambiae, whose females must be >10 days old to become infective. In this study, cuticular lipids from a laboratory strain of this mosquito species were analyzed using a mass spectrometry method to evaluate their utility for age, sex and mating status differentiation. Matrix-assisted laser desorption/ionization-mass spectrometry (MALDI-MS), in conjunction with an acenaphthene/silver nitrate matrix preparation, was shown to be 100% effective in classifying A. gambiae females into 1, 7-10, and 14 days of age. MALDI-MS analysis, supported by multivariate statistical methods, was also effective in detecting cuticular lipid differences between the sexes and between virgin and mated females. The technique requires further testing, but the obtained results suggest that MALDI-MS cuticular lipid spectra could be used for age grading of A. gambiae females with precision greater than with other available methods.
Copyright © 2011 Elsevier B.V. All rights reserved.

Entities:  

Mesh:

Substances:

Year:  2011        PMID: 21995923     DOI: 10.1016/j.aca.2011.08.033

Source DB:  PubMed          Journal:  Anal Chim Acta        ISSN: 0003-2670            Impact factor:   6.558


  8 in total

1.  Needs for monitoring mosquito transmission of malaria in a pre-elimination world.

Authors:  Stephanie James; Willem Takken; Frank H Collins; Michael Gottlieb
Journal:  Am J Trop Med Hyg       Date:  2013-11-25       Impact factor: 2.345

2.  Transcriptome analysis of the Chinese white wax scale Ericerus pela with focus on genes involved in wax biosynthesis.

Authors:  Pu Yang; Jia-Ying Zhu; Zhong-Jun Gong; Dong-Li Xu; Xiao-Ming Chen; Wei-Wei Liu; Xin-Da Lin; Yan-Fei Li
Journal:  PLoS One       Date:  2012-04-20       Impact factor: 3.240

3.  A Mass Spectrometric Analysis Method Based on PPCA and SVM for Early Detection of Ovarian Cancer.

Authors:  Jiang Wu; Yanju Ji; Ling Zhao; Mengying Ji; Zhuang Ye; Suyi Li
Journal:  Comput Math Methods Med       Date:  2016-08-23       Impact factor: 2.238

4.  Detection of Plasmodium falciparum infected Anopheles gambiae using near-infrared spectroscopy.

Authors:  Marta F Maia; Melissa Kapulu; Michelle Muthui; Martin G Wagah; Heather M Ferguson; Floyd E Dowell; Francesco Baldini; Lisa Ranford-Cartwright
Journal:  Malar J       Date:  2019-03-19       Impact factor: 2.979

5.  Dietary and Plasmodium challenge effects on the cuticular hydrocarbon profile of Anopheles albimanus.

Authors:  Fabiola Claudio-Piedras; Benito Recio-Tótoro; Jorge Cime-Castillo; Renaud Condé; Massimo Maffei; Humberto Lanz-Mendoza
Journal:  Sci Rep       Date:  2021-05-27       Impact factor: 4.379

6.  Matrix-assisted laser desorption ionization--time of flight mass spectrometry: an emerging tool for the rapid identification of mosquito vectors.

Authors:  Amina Yssouf; Cristina Socolovschi; Christophe Flaudrops; Mamadou Ousmane Ndiath; Seynabou Sougoufara; Jean-Sebastien Dehecq; Guillaume Lacour; Jean-Michel Berenger; Cheikh Sadibou Sokhna; Didier Raoult; Philippe Parola
Journal:  PLoS One       Date:  2013-08-15       Impact factor: 3.240

7.  Proteomic fingerprinting of Neotropical hard tick species (Acari: Ixodidae) using a self-curated mass spectra reference library.

Authors:  Rolando A Gittens; Alejandro Almanza; Kelly L Bennett; Luis C Mejía; Javier E Sanchez-Galan; Fernando Merchan; Jonathan Kern; Matthew J Miller; Helen J Esser; Robert Hwang; May Dong; Luis F De León; Eric Álvarez; Jose R Loaiza
Journal:  PLoS Negl Trop Dis       Date:  2020-10-27

8.  Prediction of mosquito species and population age structure using mid-infrared spectroscopy and supervised machine learning.

Authors:  Mario González Jiménez; Simon A Babayan; Pegah Khazaeli; Margaret Doyle; Finlay Walton; Elliott Reedy; Thomas Glew; Mafalda Viana; Lisa Ranford-Cartwright; Abdoulaye Niang; Doreen J Siria; Fredros O Okumu; Abdoulaye Diabaté; Heather M Ferguson; Francesco Baldini; Klaas Wynne
Journal:  Wellcome Open Res       Date:  2019-09-16
  8 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.