Laboratoire de Synthèse et Physicochimie des Molécules d'Intérêt Biologique, UMR 5068, Université Paul Sabatier, 31062 Toulouse, France
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Abstract |
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Keywords: acetylcholinesterase/biosensor/insecticide/pesticide
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Introduction |
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Organophosphate and carbamate compounds can be chemically detected by coupling gas chromatography and mass spectrometry. However, as this technique is expensive and time consuming, it is not suitable for field or home use. An alternative method is to use biosensors using AChE as biological element. Such a method has been described to detect low levels of contaminants in crops, soil, water or food samples using several biosensors based on various transducers (Marty et al., 1992). In addition to their rapidity and low cost, biosensor-based methods have two other advantages: they allow the detection of insecticides inhibiting AChE, even in a mixture of different compounds at low concentrations in the same sample, and also they permit the identification of the insecticide by using several electrodes bearing different enzymes and an artificial neural network (Bachmann and Schmid, 1999
).
In a previous study, we looked for the best enzyme by comparing AChE from different sources for organophosphorus and carbamate irreversible inhibition. We found that the enzyme from Drosophila is the most sensitive, i.e. the rate of phosphorylation or carbamoylation was higher with the Drosophila enzyme than with enzymes from other species. This was to be expected if we consider that insecticides were developed to kill insects. Furthermore, we were able to increase its sensitivity by performing a single point mutation (Villatte et al., 1998). This strongly suggests that in vitro mutagenesis could be used to increase the enzyme sensitivity further. Taking into account that there are more than 600 amino acid residues in the Drosophila AChE, we used different strategies to determine the choice of the mutant. We mutated positions known to control insecticide toxicity in insects, in addition to positions determined by docking into the AChE active site. Since the enzyme did not become sufficiently sensitive, we performed an alanine scan on the amino acids lining the active site gorge. This method allowed us to identify crucial positions that we substituted with various amino acid residues. Finally, we combined the best mutations in the same enzyme.
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Materials and methods |
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The mechanism of inhibition of AChE by organophosphate or carbamate compounds has been described by Aldridge (1950):
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To follow the inhibition, the enzyme (550 nmol/l) was incubated for various times (15 s to 30 min) with inhibitor at 25°C in 25 mM phosphate buffer, pH 7. The change in the remaining free enzyme concentration [E]/[E0] with time was estimated by sampling aliquots at various times and recording the remaining activity with 1 mM acetylthiocholine. Disappearance of free enzyme ([E]) follows second-order kinetics:
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Results |
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Several AChE mutations have been reported in insecticide-resistant insects (Fournier et al., 1992; Mutero et al., 1994
; Zhu et al., 1996
; Williamson et al., 1998
), suggesting that certain positions are important in the phosphorylation or carbamoylation of the enzyme by insecticides. We assumed that the characteristics of the side chains responsible for resistance could be reversed by another substitution and hence result in sensitivity. We chose two positions, F330 and I161, located at two parts of the active site. F330 is a component of the acyl pocket which recognizes the acyl moiety of the substrate and I161 is located behind the anionic site which recognizes the trimethylammonium moiety of acetylcholine (Figure 1
). In resistant AChE, these are mutated to Tyr and to Val, respectively (Fournier et al., 1992
; Mutero et al., 1994
). Both mutations confer resistance for most of the 10 insecticides tested, indicating the importance of these positions for the enzymatic function of AChE. We have shown previously that among three mutations at position 330 (to His, Trp and Leu) there is some increased sensivity to some insecticides (Bachmann et al., 2000
), e.g. F330L increases the sensitivity to paraoxon. By performing other mutations at the two positions (161 and 330), we found new mutants with higher sensitivity for the four insecticides tested, three organophosphates (malaoxon, paraoxon and omethoate) and one carbamate (carbaryl). For example, mutant F330H displayed a high sensitivity to carbaryl (Figure 2
). However, we did not find any correlation between the properties of the side chain and the insecticide sensitivity. As the increase in sensitivity was weak and as no mutations conferred sensitivity to the four insecticides, we performed mutagenesis at other positions.
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The three-dimensional structure of Drosophila AChE has recently been published (Harel et al., 2000). We used this structure to perform experiments on insecticide docking at the bottom of the site. They revealed potential interactions between some side chain residues and the insecticide. Mutations corresponding to these residues are presented in Figure 3
. It appeared that all the residues were actually involved in enzyme sensitivity. Some mutations provided specific sensitivity, e.g. mutation L328F provided sensitivity only to paraoxon and omethoate whereas other mutations such as Y370F resulted in an increased sensitivity to the four insecticides tested.
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The entrance of the gorge was modified by addition of N-glycosylation sites at positions 69, 71, 321 and 375 by mutation in asparagine. In each case, a mutation to serine was done at two positions downstream, at positions 71, 73, 323 and 378. The effects of these mutations on insecticide sensitivity were not significant (not shown).
Alanine-scanning mutagenesis
Before reaching the bottom of the gorge, the insecticide comes into contact with a lot of side chains lining the gorge. To test if these residues have any effect on enzyme sensitivity, we performed 19 site-directed alanine replacements. We chose alanine because replacement by this amino acid eliminates the side chain beyond the ß-carbon and does not alter the backbone conformation or impose extreme electrostatic or steric effects (Cunningham and Wells, 1989). The sensitivity of the different mutants is reported in Figure 4
. The results indicate that several positions can be critical for enzyme sensitivity. Furthermore, some mutations located at the rim (e.g. Y324A) or in the middle (Y370A) of the gorge are also effective. The importance of residues located at the rim of the gorge is in accordance with the report of Radic and Taylor (1999), who found that some ligands which bind at the rim of the gorge increase the rate of enzyme phosphorylation. This implies that predicting the effect of a mutation on sensitivity by docking the insecticide inside the active site, at the bottom of the gorge, is not sufficient since it does not take into account the whole trajectory of the insecticide from the rim to the active serine.
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In order to increase sensitivity further, we focused on three positions, 69, 370 and 371. Amino acid 69 is located at the rim of the gorge; it is the main component of a regulatory site where substrate binds and controls the entrance of other substrate molecules (Marcel et al., 2000). Amino acid 370 is located in the middle of the gorge and was chosen because mutation to alanine resulted in the strongest sensitivity: a 10-fold increase for carbaryl. Amino acid 371, also located in the middle of the gorge, was chosen because mutation to alanine resulted either in sensitivity or in resistance, depending on the insecticide. The results revealed that sensitivity may be increased by this strategy by up to 30-fold for one insecticide with the mutant E69W (Figure 5
). Note that several mutations at position 370 increased the sensitivity to malaoxon, paraoxon and carbaryl and decreased that to omethoate. This illustrates that mutations may provide enzymes with new specificities for insecticides, allowing the determination of the compound in a sample using multielectrode biosensors and an artificial neural network.
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The last attempt to increase the AChE sensitivity involved combining mutations. In nature, resistant AChE is obtained through the combination of several mutations each providing low resistance (Mutero et al., 1994). By analogy, we assumed that the combination of several mutations which increase sensitivity to an insecticide could provide a high degree of sensitivity. Therefore, we combined several sensitive mutants (Figure 6
). Some combinations gave more sensitive AChE, e.g. the combination of E69Y and Y330L provided the best enzyme to detect paraoxon (Table I
). However, the results were not predictable and sensitivity appeared to be independent of the number of mutations.
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Discussion |
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Improvement of enzymes for catalysis of substrates by in vitro directed mutagenesis has been described previously (Arnold, 1993) and several strategies have been developed. The first is random mutagenesis with screening or selection of the desired property. The principal drawback of this method is that it requires a convenient screening method to select the mutant and is applicable, for example, when the protein confers a new property to the cell. Random mutagenesis cannot be applied to improving the sensitivity of AChE to organophosphates since AChE is secreted into the culture medium. Hence in vivo screening of mutants is not possible and each mutated protein has to be produced, purified and tested individually.
When the 3-D structure of the enzyme is available, substrate modelling in the catalytic site shows the amino acids involved in the catalytic process and reduces the field of investigation (Spiller et al., 1999). 3-D modelling has been used with success to direct mutagenesis in cholinesterases, e.g. to find residues responsible for the hydrolysis specificity of acetyl- and butyrylcholine esters (Harel et al., 1992
; Vellom et al., 1993
) or to transform butyrylcholinesterase into organophosphate hydrolase (Millard et al., 1998
). However, although modelling helped to choose the position to be mutated, it did not predict the effect of the mutation. Several explanations can be put forward. First, the difficulty in prediction originates from the structure of the active site, which is a deep gorge with an active serine, buried 20 Å inside the protein. Before reaching the active serine, the insecticide has to pass through a gorge. The trajectory is not known and is dependent on the amino acid residues lining the walls of the gorge. Hence sensitivity results not only from the positioning of the insecticide molecule at the bottom of the gorge, i.e. it does not depend only on the weak bond responsible for the Michaelian complex, but also from the recognition of the insecticide at the rim of the gorge and its displacement along the gorge. Another explanation is the allostery of the active site gorge. This allostery of the active site was first evidenced by the effect of inhibitors (Changeux, 1966
; Berman et al., 1981
) and was recently confirmed by mutagenesis. For example, mutations at the rim of the gorge affect the dephosphorylation of the phosphoryl-enzyme at the bottom and affect the positioning of a tryptophan at the bottom of the gorge which is the main component of the recognition of trimethylammonium (Barak et al., 1994
; Masson et al., 1997
). Identically, mutations at the bottom of the gorge affect the binding of ligands to the rim. Hence almost all mutations of amino acids located in the active site gorge change the conformation of the gorge, indirectly affecting substrate entrance and positioning. Indeed, a mutation which affects the Michaelian complex also affects the entrance of the insecticide through the gorge.
Combining mutations, also called directed evolution, has been used with success and the effect of combination is usually additive (Wells, 1990; Arnold and Moore, 1997
; Ford, 1999
). However, the effect of a combination of mutations was also found to be unpredictable. This contrasts with the enhanced resistance that originates from the combination of several mutations each providing weak resistance in a natural population (Mutero et al., 1994
). This poses the question as to why synergism occurs for combinations of mutations providing resistance whereas we did not observe the same synergism for mutations which provide sensitivity. Most probably, the difference results from natural selection, where only mutations which show a synergistic effect have been selected by insecticide treatments. The non-additivity of the effect of combining mutations also contrasts with experiments with other proteins where additivity is generally observed (Arnold, 1993
) and may originate from the allostery between the different parts of the site.
Nevertheless, this study clearly demonstrates the possibility of generating AChE mutants sensitive for specific organophosphate or carbamate insecticides by random site-directed mutagenesis and random combinations of mutations. Taking into account both the large number of positions which can be mutated with an effect on sensitivity (>19) and all the possible combinations between the mutations (>1919), we can assume that enzymes with even higher sensitivity can be generated.
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Notes |
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Acknowledgments |
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References |
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Received January 18, 2001; revised September 27, 2001; accepted October 12, 2001.