Literature DB >> 21585828

Gut content identification of larvae of the Anopheles gambiae complex in western Kenya using a barcoding approach.

C Garros1, N Ngugi, A E Githeko, N Tuno, G Yan.   

Abstract

Although larvae feeding and food source are vital to the development, survival and population regulation of African malaria vectors, the prey organisms of Anopheles gambiae larvae in the natural environment have not been well studied. This study used a molecular barcoding approach to investigate the natural diets of Anopheles gambiae s.l. larvae in western Kenya. Gut contents from third- and fourth-instar larvae from natural habitats were dissected and DNA was extracted. The 18S ribosomal DNA gene was amplified, the resulting clones were screened using a restriction fragment length polymorphism method and nonmosquito clones were sequenced. Homology search and phylogenetic analyses were then conducted using the sequences of non-mosquito clones to identify the putative microorganisms ingested. The phylogenetic analyses clustered ingested microorganisms in four clades, including two clades of green algae (Chlorophyta, Chlorophyceae Class, Chlamydomonadales and Chlorococcales families), one fungal clade, and one unknown eukaryote clade. In parallel, using the same approach, an analysis of the biodiversity present in the larval habitats was carried out. This present study demonstrated the feasibility of the barcoding approach to infer the natural diets of Anopheles gambiae larvae. Our analysis suggests that despite the wide range of microorganisms available in natural habitats, mosquito larvae fed on specific groups of algae. The novel tools developed from this study can be used to improve our understanding of the larval ecology of African malaria vectors and to facilitate the development of new mosquito control tools.
© 2007 The Authors.

Entities:  

Year:  2008        PMID: 21585828      PMCID: PMC3736344          DOI: 10.1111/j.1471-8286.2007.02013.x

Source DB:  PubMed          Journal:  Mol Ecol Resour        ISSN: 1755-098X            Impact factor:   7.090


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