Investigating the role of glutathione and glutathione biosynthetic genes in the adaptation of Anopheles gambiae to insecticides

Malaria remains a serious public health challenge in the tropical world, with 584,000 deaths globally in 2013, of which 90% occurred in Africa, and mostly in pregnant women and children under the age of five. Anopheles gambiae (An. gambiae) is the principal malaria vector in Africa, where vector control measures involve the use of insecticides in the forms of long-lasting insecticide-treated nets (LLINs) and indoor residual spraying (IRS). The development of insecticides resistance mitigates these approaches. Glutathione (GSH) is widely distributed among all living organisms, and is associated with detoxification pathways, especially the Glutathione S-transferases (GSTs). Its direct involvement and relevance in insecticide resistance in An. gambiae has not been determined. Thus, this work examines the contribution of GSH, its biosynthetic genes (GCLM, GCLC) and their possible transcriptional regulator Nrf2 in insecticide resistance in An. gambiae sampled from agricultural setting (areas of intensive agriculture) and residential setting (domestic area). Bioinformatics analysis, W.H.O. adult susceptibility bioassays and molecular techniques were employed to investigate. Total RNA was first isolated from the adults An. gambiae mosquitoes raised from agricultural and residential field-caught larvae which had been either challenged or unchallenged with insecticides. Semi-quantitative RT-PCR using gel image densitometry was used to determine the expression levels of GCLM, GCLC genes and Nrf2. Bioinformatics’ results established the presence of putative AGAP010259 (AhR) and AGAP005300 (Nf2e1) transcription factor binding sites in An. gambiae GCLC and GCLM promoters in silico. An. gambiae s.l. studied here were highly resistant to DDT and permethrin but less resistant to bendiocarb. Both knockdown resistance (kdr) mutation variants L1014S and L1014F that confers resistance to pyrethroid insecticides were identified in both An. coluzzii and An. arabiensis sampled from northern Nigeria. The L1014F was much associated with An. coluzzii. A significant positive correlation (P=0.04) between the frequency of the L1014F point mutation and resistance to DDT and permethrin was observed. However, a weak or non-significant correlation (P=0.772) between the frequency of the L1014S point mutation and resistance was also found. L1014S and L1014F mutations co-occurred in both agricultural and residential settings with high frequencies. However, the frequencies of the two mutations were greater in the agricultural settings than in the residential settings. The levels of total, reduced and oxidized GSH were significantly higher in mosquitoes from agricultural sites than those from residential sites. Increased oxidized GSH levels appears to correlate with higher DDT resistance. The expression levels of GCLM, GCLC and Nrf2 were also significantly up-regulated in adults An. gambiae raised from agricultural and residential field-caught larvae when challenged with insecticide. However, there was higher constitutive expression of GCLM, GCLC and Nrf2 in mosquitoes from agricultural setting. The increased expression levels of these genes and also GSH levels in this population suggest their roles in the response and adaptation of An. gambiae to insecticide challenges. There exists the feasibility of using GSH status in An. gambiae to monitor adaptation and resistance to insecticides.

Kinetic modelling of in vitro data of PI3K, mTOR1, PTEN enzymes and on-target inhibitors Rapamycin, BEZ235, and LY294002

The phosphatidylinositide 3-kinases (PI3K) and mammalian target of rapamycin-1 (mTOR1) are two key targets for anti-cancer therapy. Predicting the response of the PI3K/AKT/mTOR1 signalling pathway to targeted therapy is made difficult because of network complexities. Systems biology models can help explore those complexities but the value of such models is dependent on accurate parameterisation. Motivated by a need to increase accuracy in kinetic parameter estimation, and therefore the predictive power of the model, we present a framework to integrate kinetic data from enzyme assays into a unified enzyme kinetic model. We present exemplar kinetic models of PI3K and mTOR1, calibrated on in vitro enzyme data and founded on Michaelis-Menten (MM) approximation. We describe the effects of an allosteric mTOR1 inhibitor (Rapamycin) and ATP-competitive inhibitors (BEZ2235 and LY294002) that show dual inhibition of mTOR1 and PI3K. We also model the kinetics of phosphatase and tensin homolog (PTEN), which modulates sensitivity of the PI3K/AKT/mTOR1 pathway to these drugs. Model validation with independent data sets allows investigation of enzyme function and drug dose dependencies in a wide range of experimental conditions. Modelling of the mTOR1 kinetics showed that Rapamycin has an IC50 independent of ATP concentration and that it is a selective inhibitor of mTOR1 substrates S6K1 and 4EBP1: it retains 40% of mTOR1 activity relative to 4EBP1 phosphorylation and inhibits completely S6K1 activity. For the dual ATP-competitive inhibitors of mTOR1 and PI3K, LY294002 and BEZ235, we derived the dependence of the IC50 on ATP concentration that allows prediction of the IC50 at different ATP concentrations in enzyme and cellular assays. Comparison of the drug effectiveness in enzyme and cellular assays showed that some features of these drugs arise from signalling modulation beyond the on-target action and MM approximation and require a systems-level consideration of the whole PI3K/PTEN/AKT/mTOR1 network in order to understand mechanisms of drug sensitivity and resistance in different cancer cell lines. We suggest that using these models in systems biology investigation of the PI3K/AKT/mTOR1 signalling in cancer cells can bridge the gap between direct drug target action and the therapeutic response to these drugs and their combinations.