ArticleData in brief2015
Combining two-dimensional gel electrophoresis and metabolomic data in support of dry-season survival in the two main species of the malarial mosquito Anopheles gambiae.
Article in Data in brief, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- Review
- Insects With Survival Kits for Desiccation Tolerance Under Extreme Water Deficits.Frontiers in physiology · 2018Review
- The contribution of dietary restriction to extended longevity in the malaria vector Anopheles coluzzii.Parasites & vectors · 2017Article
- Comparative physiological plasticity to desiccation in distinct populations of the malarial mosquito Anopheles coluzzii.Parasites & vectors · 2016Article
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Authors and funding
8 authors.
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No grant is acknowledged in the PubMed record.
Abstract
In dry savannahs of West-Africa, the malarial mosquitoes of the Anopheles gambiae sensu stricto complex annually survive the harsh desiccating conditions of the dry season. However, the physiological and biochemical mechanisms underlying how these mosquitoes survive such desiccating conditions are still undefined, and controversial. In this context, we provide the first work examining both proteomic and metabolomic changes in the two molecular forms of A. gambiae s.s (M and S forms) experimentally exposed to the rainy and dry season conditions as they experience in the field. Protein abundances of the mosquitoes were measured using a two-dimensional fluorescence difference gel electrophoresis (2D DIGE) coupled with a matrix-assisted laser desorption/ionisation-time of flight (MALDI-TOF) and tandem mass spectrometry (MS) for protein identification. These assays were conducted by Applied Biomics (http://www.appliedbiomics.com, Applied Biomics, Inc. Hayward, CA, USA), and the mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium (http://proteomecentral.proteomexchange.org) via the PRIDE partner repository with the dataset identifier PXD000294. The metabolomic analysis was conducted using both Acquity UPLC(®) system (for amino acid identification), and a gas-chromatography-mass spectrometry platform (for sugars identification). Metabolomic fingerprintings were assessed in the University of Rennes 1, UMR CNRS 6553 EcoBio (France). A detailed interpretation of the obtained data can be found in Hidalgo et al. (2014) [1] (Journal of Insect Physiology (2014)).
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