scholarly journals Molecular analysis of multiple cytochrome P450 genes from the malaria vector, Anopheles gambiae

2002 ◽  
Vol 11 (5) ◽  
pp. 409-418 ◽  
Author(s):  
H. Ranson ◽  
D. Nikou ◽  
M. Hutchinson ◽  
X. Wang ◽  
C. W. Roth ◽  
...  
2011 ◽  
Vol 41 (7) ◽  
pp. 492-502 ◽  
Author(s):  
Bradley J. Stevenson ◽  
Jaclyn Bibby ◽  
Patricia Pignatelli ◽  
Sant Muangnoicharoen ◽  
Paul M. O’Neill ◽  
...  

2013 ◽  
Vol 12 (1) ◽  
pp. 97 ◽  
Author(s):  
Fauzia K Musasia ◽  
Alfred O Isaac ◽  
Daniel K Masiga ◽  
Irene A Omedo ◽  
Ramadhan Mwakubambanya ◽  
...  

2019 ◽  
Vol 220 (3) ◽  
pp. 467-475 ◽  
Author(s):  
Jacob M Riveron ◽  
Silvie Huijben ◽  
Williams Tchapga ◽  
Magellan Tchouakui ◽  
Murielle J Wondji ◽  
...  

Abstract Background Insecticide resistance poses a serious threat to insecticide-based interventions in Africa. There is a fear that resistance escalation could jeopardize malaria control efforts. Monitoring of cases of aggravation of resistance intensity and its impact on the efficacy of control tools is crucial to predict consequences of resistance. Methods The resistance levels of an Anopheles funestus population from Palmeira, southern Mozambique, were characterized and their impact on the efficacy of various insecticide-treated nets established. Results A dramatic loss of efficacy of all long-lasting insecticidal nets (LLINs), including piperonyl butoxide (PBO)–based nets (Olyset Plus), was observed. This An. funestus population consistently (2016, 2017, and 2018) exhibited a high degree of pyrethroid resistance. Molecular analyses revealed that this resistance escalation was associated with a massive overexpression of the duplicated cytochrome P450 genes CYP6P9a and CYP6P9b, and also the fixation of the resistance CYP6P9a_R allele in this population in 2016 (100%) in contrast to 2002 (5%). However, the low recovery of susceptibility after PBO synergist assay suggests that other resistance mechanisms could be involved. Conclusions The loss of efficacy of pyrethroid-based LLINs with and without PBO is a concern for the effectiveness of insecticide-based interventions, and action should be taken to prevent the spread of such super-resistance.


BMC Genomics ◽  
2021 ◽  
Vol 22 (1) ◽  
Author(s):  
Melina Campos ◽  
Luisa D. P. Rona ◽  
Katie Willis ◽  
George K. Christophides ◽  
Robert M. MacCallum

Abstract Background Whole genome re-sequencing provides powerful data for population genomic studies, allowing robust inferences of population structure, gene flow and evolutionary history. For the major malaria vector in Africa, Anopheles gambiae, other genetic aspects such as selection and adaptation are also important. In the present study, we explore population genetic variation from genome-wide sequencing of 765 An. gambiae and An. coluzzii specimens collected from across Africa. We used t-SNE, a recently popularized dimensionality reduction method, to create a 2D-map of An. gambiae and An. coluzzii genes that reflect their population structure similarities. Results The map allows intuitive navigation among genes distributed throughout the so-called “mainland” and numerous surrounding “island-like” gene clusters. These gene clusters of various sizes correspond predominantly to low recombination genomic regions such as inversions and centromeres, and also to recent selective sweeps. Because this mosquito species complex has been studied extensively, we were able to support our interpretations with previously published findings. Several novel observations and hypotheses are also made, including selective sweeps and a multi-locus selection event in Guinea-Bissau, a known intense hybridization zone between An. gambiae and An. coluzzii. Conclusions Our results present a rich dataset that could be utilized in functional investigations aiming to shed light onto An. gambiae s.l genome evolution and eventual speciation. In addition, the methodology presented here can be used to further characterize other species not so well studied as An. gambiae, shortening the time required to progress from field sampling to the identification of genes and genomic regions under unique evolutionary processes.


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