Next Article in Journal
Deep Eutectic Solvents as Catalysts for Upgrading Biomass
Next Article in Special Issue
Biocatalytic Transformation of 5-Hydroxymethylfurfural into 2,5-di(hydroxymethyl)furan by a Newly Isolated Fusarium striatum Strain
Previous Article in Journal
Nanowire-Based Materials as Coke-Resistant Catalyst Supports for Dry Methane Reforming
Previous Article in Special Issue
Enzymology of Alternative Carbohydrate Catabolic Pathways
 
 
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Optimizing the Production of Recombinant Hydroperoxide Lyase in Escherichia coli Using Statistical Design

Laboratoire de Biochimie et Biologie Moléculaire Végétales, Campus Grimaldi, Université de Corse, CNRS UMR6134 SPE, BP52, 20250 Corte, France
*
Authors to whom correspondence should be addressed.
Catalysts 2021, 11(2), 176; https://doi.org/10.3390/catal11020176
Submission received: 5 January 2021 / Revised: 23 January 2021 / Accepted: 25 January 2021 / Published: 28 January 2021
(This article belongs to the Special Issue Biocatalysis and Whole-Cell Biotransformation in Biomanufacturing)

Abstract

:
Hydroperoxide lyase (HPL) catalyzes the synthesis of volatiles C6 or C9 aldehydes from fatty acid hydroperoxides. These short carbon chain aldehydes, known as green leaf volatiles (GLV), are widely used in cosmetic industries and as food additives because of their “fresh green” aroma. To meet the growing demand for natural GLVs, the use of recombinant HPL as a biocatalyst in enzyme-catalyzed processes appears to be an interesting application. Previously, we cloned and expressed a 13-HPL from olive fruit in Escherichia coli and showed high conversion rates (up to 94%) during the synthesis of C6 aldehydes. To consider a scale-up of this process, optimization of the recombinant enzyme production is necessary. In this study, four host-vector combinations were tested. Experimental design and response surface methodology (RSM) were used to optimize the expression conditions. Three factors were considered, i.e., temperature, inducer concentration and induction duration. The Box–Behnken design consisted of 45 assays for each expression system performed in deep-well microplates. The regression models were built and fitted well to the experimental data (R2 coefficient > 97%). The best response (production level of the soluble enzyme) was obtained with E. coli BL21 DE3 cells. Using the optimal conditions, 2277 U L−1of culture of the soluble enzyme was produced in microliter plates and 21,920 U L−1of culture in an Erlenmeyer flask, which represents a 79-fold increase compared to the production levels previously reported.

1. Introduction

Hydroperoxide lyase (HPL) is a membrane-bound enzyme mainly distributed in higher plants, algae, and fungi [1,2,3]. HPL is involved in the lipoxygenase (LOX) pathway, which is a lipid oxidation pathway activated in response to biotic or abiotic stress, or during various plant stages development, to produce phyto-oxylipins acting as defense and signaling molecules [4,5,6,7,8,9,10,11,12]. In this pathway, LOX first catalyzes the oxygenation of polyunsaturated fatty acids (PUFAs), such as linoleic or α-linolenic acids, to produce corresponding hydroperoxides [4,13,14]. Subsequently, HPL acts on these PUFA hydroperoxides to form volatile short-chain aldehydes (C6 or C9-aldehydes) and ω-oxoacids [6,15,16,17,18,19]. HPLs are heme enzymes belonging to the cytochrome P450 family and are divided into two subfamilies by their substrate specificities, namely CYP74B for 13-HPLs and CYP74C for 9-HPLs and 9/13-HPLs. 13-HPLs preferentially act on 13-hydroperoxide of linolenic acid (13-HPOT) and 13-hydroperoxide of linoleic acid (13-HPOD) to form (3Z)-hexenal and hexanal, respectively [20,21,22,23,24,25], while 9-HPLs transform 9-hydroperoxide of linolenic acid (9-HPOT) and 9-hydroperoxide of linoleic acid (9-HPOD) into (3Z)-nonadienal and (3Z)-nonenal, respectively [16]. (3Z)-hexenal, (3Z)-nonadienal, and (3Z)-nonenal are enzymatically or spontaneously isomerized into more stable (2E)-hexenal, (2E)-nonadienal, and (2E)-nonenal. 9-/13-HPLs have both 9- and 13-HPL activities [26,27,28].
Volatile aldehydes produced by HPL are part of the green leaf volatiles (GLVs) compounds and are important constituents of the fresh smell of green leaves and cut grass called “green note” [29,30]. Because of their green, fresh and fruity aromas, GLVs are widely used in perfumes and fragrances. In food products, GLVs are added mainly to restore the natural fresh green aroma of fruits and vegetables, which is lost during industrial processing or sterilization processes, but they can also improve the shelf life and safety of processed foods due to their antibacterial activities [31]. The industrial production of GLVs by chemical synthesis is environmentally unfriendly, and nowadays, consumers have a strong preference for naturally synthesized additives and flavors. Given the high demand for such natural flavors and the low yield of extracting the compounds directly from plants, efficient biocatalytic processes using the enzymes of the LOX pathway are developed [19,32]. In these processes, vegetal oils are hydrolyzed by lipase, and then the PUFAs released are converted by LOX and HPL into green note aldehydes [23,33,34,35,36]. Since lipases and LOXs are commercially available, genetic engineering approaches focus on the production of recombinant HPL [19,37,38,39,40,41].
In previous work, we isolated a complementary DNA (cDNA) encoding for a 13-HPL from black olive fruit (Olea europaea L., Leccino variety) [42]. Olive recombinant 13-HPL was expressed in Escherichia coli (E. coli) M15, purified by affinity chromatography and biochemically characterized [42]. In another work, we improved the stability and increased activity of the enzyme using selected chemical additives [43]. The use of olive recombinant 13-HPL for C6-aldehydes synthesis from 13-HPOD and 13-HPOT showed that it is an efficient and promising biocatalyst for the bioconversion process (conversion rates up to 94%) [42,43]. Its use for C6-aldehyde production in a high-scale bioreactor requires an optimization of the heterologous expression of recombinant HPL in order to recover larger amounts of the soluble and active enzymes.
E. coli is the most commonly used host for the expression of heterologous genes, notably due to its rapid growth, relatively low culture cost, significant knowledge of genetic and metabolism and many molecular tools (such as plasmids) available to induce a strong expression of the genes coding for heterologous proteins [44,45]. Protein overproduction in E. coli is today very widespread [46,47,48] and used in large-scale industry for the production of drugs, vaccines, enzymes or modified proteins. However, the formation of insoluble protein aggregates as inclusion bodies is often a phenomenon limiting heterologous expression [49,50]. Various E. coli strains and/or expression vectors were specifically designed to improve protein overexpression and solubility, sometimes leading to significant success, although the improvements are highly protein-dependent [45]. Otherwise, one of the simplest means generally used to try to lower protein aggregation and to promote better folding of proteins is decreasing the culture temperature of E. coli.
In the present study, we proposed to test different suitable systems of E. coli strains/expression vectors and to perform for each a screening of the culture conditions (by varying factors including temperature, inducer concentration and induction duration) in order to optimize the expression of the soluble and active olive recombinant 13-HPL. Since many factor combinations were to be tested to find the best conditions for enzyme expression, a statistical design of the experiments was carried out. The response surface methodology (RSM) was used to evaluate the effect of the factors on the soluble enzyme production, identify the optimum factor levels and provide reliable predictions of production yields. Improved yields of the soluble active enzyme were reached, which will greatly facilitate future studies and will allow the higher-scale use of the olive recombinant HPL in the bioproduction processes of flavoring aldehydes.

2. Results

2.1. Optimizing the Culture Conditions Using RSM

2.1.1. Model Fitting and Statistical Analysis

For each of the four E. coli strain/expression vector systems (M30, I30, B19 and A19), the optimization of the production of the soluble and active olive recombinant HPL was carried out using RSM. A Box–Behnken design was used to investigate the effects of three factors, i.e., temperature (T), inducer concentration (I) and induction duration (D), on this enzyme production estimated by measuring soluble enzyme activity (expressed in U L−1of culture). The results obtained from 45 experimental runs carried out according to the Box–Behnken design are summarized in Supplementary Materials, Table S1.
Regression analysis was then performed on the experimental data. The measured values of the soluble activity were fitted to a second-order polynomial equation. For each expression system (M30, I30, B19 and A19), the predicted model can be described by the equation showed in Table 1.
Through regression-fitting, the second-order polynomial equations represent the relationship between the various factors and the HPL activity in the soluble fraction of bacterial lysate.
R2 coefficients of the model were calculated to be 0.97, 0.97, 0.98 and 0.97 for the expression systems M30, I30, B19 and A19, respectively. They revealed a satisfactory adjustment of the model to the experimental data and indicated that, respectively, 97, 97, 98 and 97% of the variability in the response could be explained by the model. Thus, these models could be used for the analysis and prediction of the soluble HPL activity produced.
The significance of the fit of the second-order polynomial for enzyme activity is assessed by carrying out an analysis of variance (ANOVA). The results of the second-order response surface model fitting in the form of ANOVA and p-values of each linear, quadratic or interaction terms are reported in Supplementary Materials, Table S2. A p-value < 0.05 was considered to be significant. The models were simplified by keeping terms showing p-values lower than 0.05 (except for the first-order terms, which were kept as long as an interaction or a quadratic term including this factor was statistically significant). The simplified models are shown in Table 2.
Analysis of RSM for the M30 expression system revealed that linear terms temperature (T), induction concentration (I), and induction duration (D) showed a p-value lower than 0.05, indicating that those three factors significantly influence the production of the soluble enzyme. The quadratic terms—T2, I2 and D2—were also statistically significant. Concerning interaction terms, only temperature × induction duration (T × D) exhibited a significant influence on the soluble enzyme production.
Regarding the I30 expression system, linear terms temperature T, I and D had a significant impact on the production of the soluble enzymes. The quadratic terms T2 and D2 were statistically significant. Likewise, only the interaction term T × D had a significant influence.
For the B19 expression system, the linear terms T, I and D as well as the associated quadratic terms T2, I2 and D2 were statistically significant. T × D and T × I were the two cross-product terms influencing the production of the soluble enzyme.
Concerning the A19 expression system, the linear terms T and D were statistically significant, as well as their quadratic terms T2 and D2. Neither the linear term I nor the quadratic term I2 was significant. Interaction term T × D had a significant influence on the soluble enzyme production.
Henry’s half-lines displaying a comparison of the effects of each significant linear, square and interaction term were made for each of the expression systems (Figure 1). The adjustment line indicates where the points should be if there was no effect. All significant terms are labeled, are located on the right side of the graph, and their distance from the line highlights their relative importance.
For the M30, I30 and B19 expression systems, the temperature (T and T2) was the variable that had the largest effect on the soluble enzyme production. The value for the normalized effect for expression systems M30, I30 and B19 was, respectively, 22, 23 and 27 for the quadratic term T2 and 17.5 19 and 22 for the linear term T. The order of the variables influencing the soluble enzyme production was as follows: temperature > induction duration > inducer concentration.
For the A19 expression system, the interaction term T × D had the most significant effect on the soluble activity (normalized effect with a value of 16.5) showing the importance of jointly adjusting the value of these two variables to influence enzyme production. Concordantly, T and D showed fairly close normalized effect values (respectively 14.5 and 15.7).

2.1.2. 3D Response Surface Plots and Experimental Validation

Effects of cross term product factors on the soluble activity level were further examined using three-dimensional (3D) response surface plots (Figure 2) or contour plots (Supplementary Materials, Figure S1). Only significant interactions were kept.
The M30 and I30 expression systems, for which only the T × D interaction term was significant, displayed similar plots (Figure 2). Response surface plots as a function of the temperature and induction duration confirmed that these variables are critical factors influencing soluble enzyme production and must be tightly adjusted to reach a maximum production at 23 °C and 51.5 h for M30 and 23.5 °C and 48.5 h for I30 (Figure 2).
Regarding the B19 expression system, the T × D and T × I interaction terms were significant. Response surface plot as a function of the temperature and induction duration confirmed that these variables were closely linked, both strongly influencing soluble enzyme production, as observed for M30 and I30. A maximum of the soluble activity could be reached for 23 °C and 49 h.
For B19 as well as for M30 and I30, on the 3D response surface plot (Figure 2), for the highest temperatures like 30 °C, we observed little influence of the induction duration. For example, for I30, the soluble enzymatic activity remained between about 1600 and 1700 U L−1of culture at 30 °C whatever the induction duration. This is in agreement with Henry’s half-lines results (Figure 1), indicating that temperature had a higher impact on the soluble enzymatic activity than the duration of the induction. For example, for I30, the normalized effect value of T (18.9) was 2.2-fold higher than that of D (8.7) (Figure 1).
For B19, the response surface plot as a function of the temperature and inducer concentration confirmed the value of 23 °C as the optimal temperature and showed that a maximum production could be reached with 1 mM inducer concentration. Even if the T × I interaction term exhibited a significant p-value, only a small impact of the inducer concentration was observed on the 3D response surface plot at the various temperatures (Figure 2).
Concerning the A19 expression system, the temperature and the induction duration are factors strongly affecting enzyme expression. In Figure 2, we observed that for temperatures below 15 °C, the induction duration strongly influences the soluble enzymatic activity, which increased with the duration of the induction. On the other hand, for durations of the induction less than 40 h, the temperature had an important influence, and soluble enzymatic activity increased with the increase of the temperature. Thus, temperature and induction duration must be adjusted together in order to obtain maximum soluble enzymatic activity. Henry’s half-line showed that the interaction term T × D had the most important effect on the soluble activity (Figure 1). When the temperature and induction duration were tightly adjusted, a maximum production could be reached at 16 °C and 50.5 h.
The RSM approach determines relationships between the input factors and the response to provide a prediction of the optimal factor values to maximize response. Thus, this approach allowed us to predict the maximum value of the soluble HPL activity (expressed in U L−1of culture) for each expression system and the optimal expression conditions (temperature, induction duration, inducer concentration) to achieve this predicted value of the enzymatic activity. The model was then subject to experimental validation by measuring the soluble HPL activity obtained in the optimal expression conditions (Table 3).
According to the model, a predicted soluble HPL activity of 2197 U L−1of culture for the M30 expression system could be obtained with the optimal conditions set at a temperature of 23 °C, an inducer concentration (IPTG) of 1 mM and an induction duration of 51.5 h. Experimentally, a soluble HPL activity of 2254 ± 19 U L−1of culture was recovered, which is in accordance with the predicted value, considering a standard deviation of 2.5%.
In a previous work [42], we expressed the olive recombinant HPL using the M30 expression system (pQE30/E. coli M15 bacteria). The bacterial culture was incubated at 37 °C until the cell density had increased to A600 0.6 to 0.8. Then, the expression of HPL was induced by the addition of 0.5 mM IPTG followed by stirring at 15 °C for 48 h. Applying this unoptimized protocol in a 2 mL expression experience in microplates, we recovered a soluble HPL activity of 399 ± 25 U L−1of culture. Optimizing HPL expression in the M30 system, therefore, allows a 5.6-fold increase of the soluble enzymatic activity compared to the previous unoptimized protocol.
For the I30 expression system, the model predicted the highest value of 2250 U L−1of culture for the soluble enzymatic activity with the optimal conditions set at 23.5 °C, 1 mM ITPG and induction duration of 48.5 h. The measured experimental HPL activity was 2177 ± 20 U L−1of culture and is closed to the predicted value (standard deviation of 3.2%). Otherwise, compared to the previous unoptimized studies, it represents a 5.5-fold improvement.
Concerning B19, the optimal production of 2277 U L−1of culture was predicted with the optimal conditions set at 23 °C, 1 mM ITPG and an induction duration of 49 h. This prediction was experimentally validated with a measured enzymatic activity of 2285 ± 12 U L−1of culture, corresponding to a standard deviation value of only 0.4%. A 5.7-fold increase of the soluble enzymatic activity production was thus obtained compared to the previous assays without optimization.
Finally, regarding A19, the results of RSM showed that a maximum activity production of 2143 U L−1of culture could be reached with the optimal conditions set at 16 °C, 1 mM IPTG and an induction duration of 50.5 h. A soluble enzymatic activity of 2209 ± 16 U L−1of culture was experimentally recovered. This result is in accordance with the predicted value, considering a 3% standard deviation. This represents a 5.5-fold increase compared to the soluble enzymatic activity production obtained with the previous unoptimized protocol.
For each expression system, the experimental results validated the model and, therefore, the optimal conditions for the production of the soluble and active HPL.

2.2. Large-Scale Production

A large-scale production (400 mL) of olive recombinant HPL was performed in a 1 L Erlenmeyer flask, using the optimized conditions determined from the model prediction. Soluble enzymatic activity reached 20,740 ± 537, 20,634 ± 486, 21,920 ± 356 and 20,687 ± 980 U L−1of culture with M30, I30, B19 and A19 expression systems, respectively.
In a previous unoptimized work [42] using the M30 expression system, we expressed the olive recombinant HPL in 400 mL culture medium in 1 L Erlenmeyer flask, and we recovered 277 ± 9 U L−1of culture. Optimization of HPL expression in M30, I30, B19 and A19 system represents, respectively, a 75, 74, 79, and 75-fold increase of the soluble enzymatic activity recovered compared to the value obtained in the previous work.

2.3. Protein Expression Analysis by SDS–PAGE and Western Blot

Identical amounts of proteins from the soluble fractions of the bacterial lysate, obtained with M30, I30, B19 and A19 expression systems, were separated by electrophoresis on 12% polyacrylamide gel in the presence of SDS and stained with Coomassie blue or transferred to membrane for Western blot analyses (Figure 3).
The Western blot allowed to specifically reveal the recombinant HPL by using a specific anti-His antibody. A band estimated around 50 kDa, corresponding to the size of an HPL subunit, can be observed on all lanes, thus confirming HPL expression (Figure 3b, lanes 1 to 4). For A19, on the gel stained with Coomassie blue, a high-intensity band around 55 kDa corresponding to chaperones (Cpn60 and Cpn10), overexpressed in Arctic Express DE3 host strain (Figure 3a, line 4) can be observed.

3. Discussion

In order to increase the amount of heterologous protein produced, the first approach is to test several bacterial host strains to maximize chances to produce recombinant protein in a soluble fraction. The expression vector is also a key parameter. In this study, we proposed to test four E. coli expression strains, M15 and IqExpress strains, based on the T5 system with pQE30 expression vector and BL21 DE3 and Arctic Express DE3 based on the T7 system with pET19b expression vector.
Besides the fact that the improvements depend on the genetic context of the recombinant cell and are protein-dependent, culture parameters that influence protein expression and folding must be systematically considered. The high concentration of nascent polypeptide chains in a recombinant cell promotes aggregation reactions at the expense of the productive reaction to the native state. The production of large amounts of the incorrectly folded protein, generating aggregates of proteins in a mostly biologically inactive state known as inclusion bodies, is the main trouble to the production of heterologous proteins [44,45,46,47,49,50,51]. While the aggregated protein may be easy to purify [52,53,54], obtaining active protein from inclusion bodies typically requires protein-specific and labor-intensive in vitro re-folding steps, with no guarantee of obtaining biologically active product [55]. The composition of the culture medium, the cell growth temperature, the level of transcription or translation of the recombinant gene, the overexpression of the chaperones and the inactivation of the genes coding for the proteases are all examples of parameters that can influence the amount of the soluble recombinant proteins recovered.
The option of optimizing recombinant olive HPL production by means of experimental design and response surface methodology (RSM) was attractive. The three-factor Box–Behnken design developed here in microplates was fast and efficient to optimize the soluble enzyme production. The model was well-fitted to the data, as evidenced by the high R2 coefficients (0.97–0.98) and the small standard deviation (at most 3.2%) between the predicted activities and the measured activities.
Among the three studied factors (temperature, inducer concentration and induction duration), the temperature and induction duration were the two most important ones, as they showed the strongest effects on the soluble enzyme activity (linear, quadratic and cross term interactions, Figure 1 and Table 2). Decreasing culture temperature slows down the cell machinery, probably diminishing protein aggregation and formation of inclusion bodies [56,57,58,59]. This method has been effective for many proteins such as luciferase, β-lactamase, rabbit glycogen phosphorylase, interferon α-2, or α-(1→2) branching sucrase [60,61].
In this study, the temperature of choice for maximal production of active olive recombinant HPL was 23 °C for M30 and B19 expression systems and 23.5 °C for the I30 expression system (Figure 2 and Table 3). The results showed that temperatures above this optimal temperature and especially temperatures above 25 °C resulted in a huge decrease of the soluble and active enzyme production (Figure 2). As a general rule, the rise in the temperature increases the exposure of the hydrophobic regions of the proteins, thus increasing the rate of aggregation, which participates in the formation of the inclusion bodies [62]. By reducing the culture temperature, the correct folding of the protein should be favored [62]. Indeed, the drop in the temperature has the effect of slowing down cellular metabolism with the consequence of lower protein production, which can be an advantage for better folding of the proteins produced. Noordermeer et al. [37] reported that the optimal temperature for expression of active alfalfa HPL in M15 E. coli cells appeared to be 25 °C. They showed that at higher temperatures, most of the expressed HPL was inactive and probably located in inclusion bodies. Delcarte et al. [38] reported that the temperature required for the expression of HPL from immature bell peppers in M15 E. coli cells is 20 °C and observed a 500 times lower expression at 37 °C. Vuillemin et al. [61] using RSM to optimize the production of an α-(1→2) branching sucrase in E. coli showed that the optimal temperature for the production of the enzyme in Arctic Express and BL21 strains was 23 °C. They reported that a drastic decrease of the culture temperature (down to 18 °C) resulted in a decrease in the soluble enzyme production [61].
Moreover, the temperature is tightly linked to the induction duration (Figure 1 and Figure 2). For all considered expression systems, at the lowest temperatures (20 °C for M30, I30 and B19 or 10 °C for A19), the highest soluble activities were observed for the highest induction duration (66 h) (Figure 2). This highlights the importance of using experimental design and RSM that consider cross term interactions to establish the best compromise. For all expression systems tested, among the cross term interactions, the interaction between temperature and induction duration has the highest normalized effect (Figure 1), and is the only cross term interaction that is significant for M30, I30 and A19 expression systems (Table 2). The tight link between temperature and induction duration is most marked for the A19 system.
A less intense effect of the inducer concentration was observed for all expression systems (Figure 1), and the interaction between temperature and inducer concentration was only significant for the B19 expression system (Table 2). Even so, for all considered expression systems, 1 mM IPTG was the concentration of choice for maximal HPL production. According to Noordermeer et al. [37], for the optimal expression of alfalfa HPL in the M15 E. coli strain, 1 mM IPTG had to be added at A600 less than 0.8. Delcarte et al., 2003 reported that the best expression of HPL from immature bell peppers in M15 E. coli was obtained with 0.5 mM IPTG.
Globally, this study shows that fairly high HPL activity (up to 2285 U L−1of culture in microplates with a B19 expression system) can be recovered in the soluble fraction of the bacterial lysate produced when key parameters are tightly controlled. Optimization of HPL expression in the B19 system represents a 5.7-fold increase of the soluble enzyme production compared to the value obtained with the protocol published previously. To this end, the RSM approach is quite efficient. In the previous expression protocol, the cell growth phase was carried out at 37 °C, and the induction of protein expression with IPTG was carried out at 15 °C. This was likely to result in the production of large quantities of incorrectly folded proteins that aggregated in an inactive state. By lowering the growth temperature and keeping it identical for the induction, the correct folding of the protein would therefore be favored. Moreover, at the temperature of 15 °C used in the previous protocol, E. coli chaperonins, which facilitate proper protein folding by binding to and stabilizing unfolded or partially folded proteins, could lose activity at this reduced temperature. Specifically, it has been shown that the activity of the E. coli chaperonin complex GroEL/ES retains only about 30% refolding activity at 12 °C [63].
During the scale-up in Erlenmeyer, the highest soluble HPL activities were obtained (up to 21,920 ± 356 U L−1of culture using B19 expression system, which represents a 79-fold increase of the soluble enzymatic activity recovered compared to the value obtained in the previous unoptimized work). As it was previously described, notably by Kimata et al. [64] and Vuillemin et al. [61], levels of protein expression are often reduced in small-scale cultivation format compared to production in Erlenmeyer flasks probably due to aeration and agitation parameters that are more difficult to control. Therefore, the production of the soluble and active HPL would appear to be fairly equivalent in T5 as well as in T7 expression systems. Arctic Express cells (A19 expression system) have been specially engineered for improved protein processing at low temperatures. These cells co-express the Cpn10 and Cpn60 chaperonins, which show high protein refolding activities at temperatures of 4–12 °C. When expressed in Arctic Express cells, these cold-adapted chaperonins can provide improved protein processing at low temperatures. Analysis by SDS-PAGE of protein expression with A19 expression system showed very high amounts of produced Cpn60 and Cpn10 chaperones whose molecular weights are around 55 kDa. This value is close to the molecular weight of the olive recombinant HPL, which is 54.57 kDa. On the gel stained with Coomassie blue, chaperones and HPL appeared as a single very thick band, and it is likely that the amount of produced chaperones was higher than that of the protein of interest. Moreover, according to Vuillemin et al. [61], purification assays rapidly showed that highly overexpressed chaperones in Arctic Express DE3 E. coli extract troubled the automated purification (FPLC) process. The A19 expression system results in the production of a high level of the soluble and active HPL but also has drawbacks that limit its use and make it undesirable if purification of the enzyme of interest is envisaged subsequently. The B19 expression system expressing a high amount of the soluble and active enzyme (21,920 ± 356 U L−1of culture) seems suitable for the production of recombinant olive HPL. The cell growth phase to reach an A600 of 0.6 is shortened with this system compared to the A19 system (because it is done at 23 °C instead of 16 °C), making it easier and faster to use in the laboratory. The soluble HPL activity recovered in this study is much higher than that obtained by Delcarte et al. [38] who found 7900 U L−1of culture of HPL activity from extracts of E. coli cells culture, and that obtained by Noordermeer et al. [37] who found up to 800 U L−1of culture for expression of recombinant HPL alfalfa in a 10 L of E. coli M15 culture under optimal conditions. Bourel et al. [39] and Santiago-Gomez et al. [40] obtained 1200 to 1800 units of HPL of green pepper per liter of culture medium during expression in the yeast Yarrowia lipolytica. In these protocols, the biomass is obtained in batch culture, and therefore the bacterial growth will influence the conditions of the environment. The concentration of nutrients, the accumulation of inhibitor products, the concentration of dissolved oxygen, or even the change in pH are all factors that are not controlled and vary in batches. Culture in a fermenter makes it possible to control all these parameters and to eliminate those which may contribute to the appearance of inclusion bodies.
Otherwise, for each system, HPL stability during long-term storage was checked. For each system, the HPL activity was measured in the soluble fraction after a period of one month of storage at 4 °C and then compared to the values mentioned in paragraph 2.2. The results showed that 98, 96, 99 and 99% of HPL activity was recovered respectively for M30, I30, B19 and A19 expression systems. These results were in accordance with those of Noordermeer et al. [37] that showed that alfalfa HPL preparation could be stored at 4 °C for at least 1 month without significant loss of activity.

4. Material and Methods

4.1. Bacterial Strains and Expression Vectors

Four strains of E. coli were selected for testing. Two of these strains, M15 (QIAGEN, Hilden, Germany) and IqExpress (New England BioLabs, Ipswich, MA, USA), were used with the pQE30 (QIAGEN, Hilden, Germany) expression vector and are based on the T5 expression system. The other two strains, BL21 (DE3) (New England BioLabs, Ipswich, MA, USA) and Arctic Express (DE3) (Agilent Technologies, Santa Clara, CA, USA), were used with the pET19b (Novagen, Merck, Darmstadt, Germany) expression vector and are based on the T7 system. Genotypes of these different strains are presented in Supplementary Materials, Table S3. For all hosts/vector systems, the expression of recombinant proteins can be rapidly induced by the addition of isopropyl-β-D-thiogalactoside (IPTG).
M15 strain contains the plasmid pREP4, which confers kanamycin resistance and constitutively expresses the lac repressor protein encoded by the lac I gene. Unfortunately, the M15 strain is no longer commercially available. IqExpress strain is deficient in lon and ompT proteases and contains the lac I gene on miniF, therefore, requiring no antibiotic selection pressure to propagate. The pQE30 vector allows the cloning of the desired gene in fusion with an N-terminal 6xHis tag coding sequence and under control of the T5 promoter. Expression of the recombinant protein is induced by the addition of IPTG, which binds to the lac repressor protein and inactivates it. Once the lac repressor is inactivated, the host cell’s RNA polymerase can transcribe the gene of interest cloned downstream from the T5 promoter.
BL21 DE3 and Arctic Express DE3 strains express the lac repressor protein encoded by the lac I gene and contain the λDE3 prophage present within the chromosome. Both of these DE3 strains express T7 RNA polymerase from the lacUV5 promoter. They are used with the expression vector pET19b allowing the cloning of the desired gene under the control of the T7 promoter. The addition of IPTG induces the expression of T7 RNA polymerase, which can then transcribe the gene of interest cloned downstream of the T7 promoter. BL21 DE3 and Arctic Express DE3 strains are deficient in lon and ompT proteases. Arctic Express DE3 cells are derived from BL21 cells and are specially designed to overcome the obstacle of protein insolubility during heterologous expression. They are particularly suitable for the heterologous expression of proteins at low temperatures, which represents one interesting strategy for increasing the recovery of the soluble protein. Indeed, in Arctic Express DE3, the chaperonins Cpn10 and Cpn60 from the psychrophilic bacterium Oleispira antarctica are constitutively expressed from a pACYC-based plasmid that contains a gentamycin resistance gene. These chaperonins show high protein refolding activities at temperatures of 4–12 °C, which results in improved protein processing at lower temperatures, potentially increasing the yield of active and soluble recombinant protein.

4.2. Molecular Cloning and Construction of Expression Clones

In a previous work [42], the cloned olive HPL cDNA was introduced in the pQE30 expression vector at the SphI and XmaI restriction sites. The recombinant construct (pQE30-HPL) was used to transform M15 E. coli cells, which then allowed the expression of the olive recombinant HPL.
In this study, in order to test another strain for the T5 expression system, the recombinant construct pQE30-HPL was used to transform IqExpress E. coli cells. Expression clones were selected on Luria–Bertani (LB) agar plates with 50 µg·mL−1 ampicillin. Plasmids were extracted with Promega Wizard® Plus SV Minipreps DNA purification system kit and verified by restriction analyses and sequencing (GATC Biotech, Ebersberg, Germany).
Furthermore, in order to test the T7 system for the expression of the olive recombinant HPL, olive HPL cDNA was inserted into the pET19b vector using a PCR strategy with pQE30-HPL as a template. The specific primers NcoI6xHisHPLfor: 5′-atcatgccatgggccatcatcatcatcatcatacgggttcgccctccgtgact-3′ and XhoIHPLrev: 5′-gtgccgctcgagtcacttggacttctcaactgcagtgattga-3′, were used to introduce, respectively a NcoI restriction site at the 5′ end upstream of the ATG start codon itself upstream the 6xHis tag coding sequence, and an XhoI restriction site at the 3′ end downstream of the stop codon. The PCR products were cloned in the NcoI-XhoI-oriented direction into the pET19b vector. The recombinant construct (pET19b-HPL) was then used to transform BL21 DE3 and Arctic Express DE3 E. coli cells. Expression clones were selected on LB agar plates with 50 µg·mL−1 ampicillin (supplemented with 20 µg·mL−1 gentamycin for Arctic Express). Plasmids were extracted with Promega Wizard® Plus SV Minipreps DNA purification system kit and verified by restriction analyses and sequencing (GATC Biotech, Ebersberg, Germany).

4.3. Statistical Analyses for Optimization of Culture Conditions Using Response Surface Methodology (RSM)

For each of the four E. coli strain/recombinant vector couples, a three-factor Box–Behnken design was used to study the combined effect of the temperature, inducer concentration and induction duration on the production of the soluble and active olive recombinant HPL. Table 4 provides details on the factor levels coded −1, 0 and 1 for low, middle and high values, respectively.
The response surface methodology (RSM) was applied to correlate the relationship between factors and to identify optimum levels of the three factors to obtain the combination of values that optimize the response. For each E. coli strain/recombinant vector couple, the response surface design was generated using Minitab Software (Release 18) and consisted of 45 experiments, including three repetitions. The experimental design with response values are shown in Supplementary Materials, Table S1. All experiments were conducted in randomized order.
The analyses were performed using the response surface analysis module of the Minitab software. Regression analyses were carried out to fit the mathematical model to the experimental data obtained. The following generalized second-order polynomial equation describes the contribution of the various factors on the response and was used for predicting the optimal values:
Ŷ = β 0 +   i = 1 I β i X i +   i = 1 I β i i X i 2 +   i j β i j X i X j
where Ŷ is the predicted response, I is the number of factors (three in this study), β0 is the model constant, βi is the linear coefficient associated with factor Xi, βii is the quadratic coefficient associated with factor Xi, and βij is the interaction coefficient between factors Xi and Xj. To achieve clarity, factors Xi will be coded as follows: temperature (T), inducer (IPTG) concentration (I) and induction duration (D).
An analysis of variance (ANOVA) was carried out, and the estimates of each coefficient as well as their significance level were determined. The adequacy of models is checked by determination coefficient (R2) analysis. p-value is checked to find out the significance of all the fitted equation terms at a 5% level of significance. The response surface plots of the predicted model were obtained by depicting two significant factors within the experimental range and keeping the other factors at their central level. Finally, the model allowed determining each factor value leading to the optimal production of the soluble active olive recombinant HPL.

4.4. Culture in Microplates

Five milliliters of LB Broth with 50 µg·mL−1 of ampicillin were inoculated with a single bacterial colony of freshly transformed E. coli BL21 DE3, Arctic Express DE3 (supplemented with gentamycin 20 µg·mL−1), M15 (supplemented with 25 µg·mL−1 kanamycin) or IqExpress. The cultures were incubated overnight (18 h) at 37 °C with shaking (250 rpm).
Six hundred microliters of each overnight culture was used to inoculate 10 mL of culture TB medium (24 g·L−1 yeast extract; 12 g·L−1 tryptone, 0.4% (v/v) glycerol; 0.17 M KH2PO4; 0.72 M K2HPO4) supplemented with appropriated antibiotics. Each culture was then incubated at different temperatures defined by the experimental design (10–30 °C) until the OD (600 nm) reached 0.6. The expression of the recombinant enzyme is then induced by adding isopropyl β-D-1-thiogalactopyranoside (IPTG) at different concentrations defined by the experimental design (0.1–1 mM). δ-aminolevulinic acid (2.5 mM), which serves as the precursor for heme synthesis, is also added. The experimental design assays were performed in 24-well format plates using 2 mL of induced culture volume. The plates were incubated at desired temperatures under horizontal agitation (200 rpm) and centrifuged (30 min, 2000× g, 4 °C) after different induction duration defined by the experimental design (18–66 h). The cell pellets were washed with 1 mL of phosphate-buffered saline (PBS). After centrifugation (30 min, 2000× g, 4 °C), the cells pellets were resuspended in 500 μL of lysis buffer (50 mM sodium phosphate buffer pH 7 containing 0.25 mg·mL−1 lysozyme, 500 mM NaCl and 0.1% (v/v) Triton X-100), followed by freezing overnight at −80 °C. After thawing, 0.05 mg·mL−1 of DNase I, 50 mM MgSO4 and 1 mM of PMSF are added to each well, and then the plates were incubated for 1 h at 4 °C. The HPL activity recovered in the soluble fraction (supernatant) after centrifugation (30 min, 2000× g, 4 °C) of the crude cell extract was determined by spectrophotometry and expressed in units per liter of culture (U L−1of culture).

4.5. Culture in 1 L Erlenmeyer Flask

Twenty-five milliliters of LB Broth with ampicillin 50 µg·mL−1 were inoculated with a single bacterial colony of freshly transformed E. coli BL21 DE3, Arctic Express DE3 (supplemented with gentamycin 20 µg·mL−1), M15 (supplemented with kanamycin 25 µg·mL−1) or IqExpress. The cultures were incubated overnight (18 h) at 37 °C with shaking (250 rpm).
Twenty-four milliliters of each overnight culture was used to inoculate 400 mL of culture TB medium supplemented with appropriate antibiotics. Each culture was then incubated at a temperature defined by the experimental design analyses until the OD (600 nm) reached 0.6. After the addition of δ-aminolevulinic acid (2.5 mM) and IPTG at the predicted optimal concentration, each culture was incubated for an induction duration defined by the experimental design analyses. Cells were harvested by centrifugation (30 min, 7000× g, 4 °C) and resuspended in 50 mM sodium phosphate buffer pH 7 containing 0.25 mg·mL−1 lysozyme, 300 mM NaCl, 0.01 mg·mL−1 of DNase I and 1% emulfogene, in the proportions of 6 mL of buffer for 40 mL of culture. Then cells are disrupted by sonication before adding 1 mM of PMSF. After centrifugation (30 min, 2000× g, 4 °C), the supernatant was collected. The HPL activity was spectrophotometrically measured and expressed in U L−1of culture.

4.6. Enzymatic Assays

Hydroperoxides substrates of HPL were prepared as described by Vick [65] with adaptations. The reaction mixture (30 mL final volume) containing 70 mM sodium borate buffer pH 9 with 6.35 mM linoleic or linolenic acids, 11 mM NaOH, and 30 units of commercial soybean LOX (Sigma-Aldrich, St. Louis, MI, USA) was stirred for 30 min at 4 °C under oxygen bubbling. The reaction was stopped by acidification (pH 3) with 1 M HCl. Hydroperoxides were extracted with 3 × 30 mL of diethyl ether and washed with 2 × 30 mL of water. The synthesis of hydroperoxides was checked by TLC in solvent heptane/diethyl ether/acetic acid (55/45/1) and revealed by copper acetate/phosphoric acid (50/50). The identification of products was performed by 13C-NMR, and the concentration of hydroperoxide solutions was determined by measuring absorbance at 234 nm using the extinction coefficient of ε = 25,000 M−1·cm−1.
HPL activity was determined at 25 °C by continuously monitoring the decrease of absorbance at 234 nm corresponding to the cleavage of the conjugated diene system of hydroperoxide by the enzyme. The standard 1 mL reaction mixture consisted of 50 mM sodium phosphate buffer pH 7.5 and 10 μL of enzyme extract. The reaction was started by adding 43 μM hydroperoxide. One unit of HPL activity was defined as the amount of enzyme that converts 1 μmol of substrate per minute at 25 °C.

4.7. Protein Expression Analysis by SDS–PAGE and Western Blot

SDS–PAGE was performed using 12% polyacrylamide gels in the presence of 2% SDS. Proteins were stained with EZBlue gel staining reagent (Sigma-Aldrich, St. Louis, MI, USA) or transferred onto nitrocellulose (Bio-Rad, Hercules, CA, USA) and immune-revealed using the monoclonal peroxidase-conjugated anti-His antibody (Sigma-Aldrich, St. Louis, MI, USA) at 1:4000. Peroxidase activity was revealed using 1.3 mM 3,3′-diaminobenzidine tetrahydrochloride (DAB) (Merck, Darmstadt, Germany) in PBS containing 0.01% H2O2.

5. Conclusions

In this study, we were interested in optimizing the expression of olive recombinant 13-HPL, an enzyme responsible for the synthesis of flavoring compounds of industrial interest. We tested different suitable systems of E. coli strains/expression vectors and many expression conditions (by varying factors including temperature, inducer concentration and induction duration). Experimental design and RSM were used to find the expression conditions that result in higher soluble enzyme production.
Best levels of the soluble HPL activity were obtained with E. coli BL21 DE3 cells. Using the optimal expression conditions, 2277 U L−1of culture of the soluble enzyme was produced in microplates. Obtaining such activity during the expression of recombinant HPL in microplates allows the development of new enzymatic engineering strategies to extend applications. Moreover, scaling-up the culture conditions in a 1 L Erlenmeyer flask allowed to produce of higher soluble enzyme activities (up to 21,920 U L−1of culture) that were never reported before for any HPL, which are membrane-bound enzymes and having a tendency to form inclusion bodies in E. coli. This result represents a 79-fold increase compared to the production levels reported with the previous protocol [42,43]. To this end, the RSM approach is quite efficient and allows to show that high yields of recombinant protein can be reached when key parameters are tightly controlled. The optimized production achieved in this study can now allow using of the olive recombinant HPL as a biocatalyst in higher-scale reactions to produce natural flavoring aldehydes with high added value.

Supplementary Materials

The following are available online at https://www.mdpi.com/2073-4344/11/2/176/s1, Table S1: Experimental design (Box-Behnken design) for each expression system (E. coli strain/expression vector). Table S2: Response surface quadratic model analysis of soluble enzyme production with M15 E. coli strain/pQE30 expression vector (M30), with IqExpress E. coli strain/pQE30 expression vector (I30), BL21 DE3 E. coli strain/pET19b expression vector (B19) and ArcticExpress DE3 E. coli strain/pET19b expression vector (A19). Figure S1: Contour plots showing the effects of cross term product factors on the soluble HPL activity level. (Only significant interactions were kept). Table S3: E. coli strain genotypes used in this study for recombinant protein expression and for cloning experiments.

Author Contributions

Conceptualization: S.V., V.B.-B.d.C., L.B. and J.M.; methodology: S.V., J.C., E.F. and M.M.; validation: L.B. and J.M.; formal analysis: S.V., V.B.-B.d.C., L.B. and J.M.; investigation: S.V., J.C., E.F. and M.M.; resources: S.V., V.B.-B.d.C., L.B. and J.M.; writing—original draft preparation, S.V. and J.M.; writing—review and editing, S.V., V.B.-B.d.C., L.B. and J.M.; supervision: L.B. and J.M.; project administration: L.B. and J.M.; funding acquisition: L.B. and J.M. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

This work was supported by the Collectivité de Corse and the FEDER project 2014–2020, AGRIEX No. CO 0009204.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Gardner, H.W.; Weisleder, D.; Plattner, R.D. Hydroperoxide lyase and other hydroperoxide-metabolizing activity in tissues of soybean. Glycine Max. Plant Physiol. 1991, 97, 1059–1072. [Google Scholar] [CrossRef] [Green Version]
  2. Delcarte, J.; Fauconnier, M.-L.; Hoyaux, P.; Jacques, P.; Thonart, P.; Marlier, M. Revue bibliographique: L’hydroperoxyde lyase. Biotechnol. Agron. Soc. Environ. 2000, 4, 157–167. [Google Scholar]
  3. Noordermeer, M.A.; Veldink, G.A.; Vliegenthart, J.F. Fatty acid hydroperoxide lyase: A plant cytochrome p450 enzyme involved in wound healing and pest resistance. Chembiochem. 2001, 2, 494–504. [Google Scholar] [CrossRef]
  4. Feussner, I.; Wasternack, C. The lipoxygenase pathway. Annu. Rev. Plant Biol. 2002, 53, 275–297. [Google Scholar] [CrossRef] [PubMed]
  5. Howe, G.A.; Schilmiller, A.L. Oxylipin metabolism in response to stress. Curr. Opin. Plant Biol. 2002, 5, 230–236. [Google Scholar] [CrossRef]
  6. Matsui, K.; Minami, A.; Hornung, E.; Shibata, H.; Kishimoto, K.; Ahnert, V.; Kindl, H.; Kajiwara, T.; Feussner, I. Biosynthesis of fatty acid derived aldehydes is induced upon mechanical wounding and its products show fungicidal activities in cucumber. Phytochemistry 2006, 67, 649–657. [Google Scholar] [CrossRef] [PubMed]
  7. Hughes, R.K.; De Domenico, S.; Santino, A. Plant cytochrome CYP74 family: Biochemical features, endocellular localisation, activation mechanism in plant defence and improvements for industrial applications. ChemBioChem 2009, 10, 1122–1133. [Google Scholar] [CrossRef] [PubMed]
  8. Huang, F.C.; Schwab, W. Cloning and characterization of a 9-lipoxygenase gene induced by pathogen attack from Nicotiana benthamiana for biotechnological application. BMC Biotechnol. 2011, 11, 30–44. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  9. Savchenko, T.; Dehesh, K. Drought stress modulates oxylipin signature by eliciting 12-OPDA as a potent regulator of stomatal aperture. Plant Signal. Behav. 2014, 9, e28304. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  10. Savchenko, T.V.; Zastrijnaja, O.M.; Klimov, V.V. Oxylipins and plant abiotic stress resistance. Biochem. Mosc. 2014, 79, 362–375. [Google Scholar] [CrossRef]
  11. Hassan, M.N.; Zainal, Z.; Ismail, I. Green leaf volatiles: Biosynthesis, biological functions and their applications in biotechnology. Plant Biotechnol. J. 2015, 13, 727–739. [Google Scholar] [CrossRef] [PubMed]
  12. Rustgi, S.; Springer, A.; Kang, C.; von Wettstein, D.; Reinbothe, C.; Reinbothe, S.; Pollmann, S. ALLENE OXIDE SYNTHASE and HYDROPEROXIDE LYASE, Two Non-Canonical Cytochrome P450s in Arabidopsis thaliana and Their Different Roles in Plant Defense. Int. J. Mol. Sci. 2019, 20, 3064. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Liavonchanka, A.; Feussner, I. Lipoxygenases: Occurrence, functions and catalysis. J. Plant Physiol. 2006, 163, 348–357. [Google Scholar] [CrossRef] [PubMed]
  14. Schiller, D.; Contreras, C.; Vogt, J.; Dunemann, F.; Defilippi, B.G.; Beaudry, R.; Schwab, W. A dual positional specific lipoxygenase functions in the generation of flavor compounds during climacteric ripening of apple. Hortic. Res. 2015, 2, 15003. [Google Scholar] [CrossRef] [Green Version]
  15. Grechkin, A.N.; Hamberg, M. The “heterolytic hydroperoxide lyase” is an isomerase producing a short-lived fatty acid hemiacetal. Biochim. Biophys. Acta 2004, 1636, 47–58. [Google Scholar] [CrossRef]
  16. Mita, G.; Quarta, A.; Fasano, P.; De Paolis, A.; Di Sansebastiano, G.P.; Perrotta, C.; Iannacone, R.; Belfield, E.; Hughes, R.; Tsesmetzis, N.; et al. Molecular cloning and characterization of an almond 9-hydroperoxide lyase, a new CYP74 targeted to lipid bodies. J. Exp. Bot. 2005, 56, 2321–2333. [Google Scholar] [CrossRef] [Green Version]
  17. Grechkin, A.N.; Bruhlmann, F.; Mukhtarova, L.S.; Gogolev, Y.V.; Hamberg, M. Hydroperoxide lyases (CYP74C and CYP74B) catalyze the homolytic isomerization of fatty acid hydroperoxides into hemiacetals. Biochim. Biophys. Acta 2006, 1761, 1419–1428. [Google Scholar] [CrossRef]
  18. Lee, D.S.; Nioche, P.; Hamberg, M.; Raman, C.S. Structural insights into the evolutionary paths of oxylipin biosynthetic enzymes. Nature 2008, 455, 363–368. [Google Scholar] [CrossRef]
  19. Vincenti, S.; Mariani, M.; Alberti, J.-C.; Jacopini, S.; Brunini-Bronzini de Caraffa, V.; Berti, L.; Maury, J. Biocatalytic Synthesis of Natural Green Leaf Volatiles Using the Lipoxygenase Metabolic Pathway. Catalysts 2019, 9, 873. [Google Scholar] [CrossRef] [Green Version]
  20. Suurmeijer, C.N.; Perez-Gilabert, M.; van Unen, D.J.; van der Hijden, H.T.; Veldink, G.A.; Vliegenthart, J.F. Purification, stabilization and characterization of tomato fatty acid hydroperoxide lyase. Phytochemistry 2000, 53, 177–185. [Google Scholar] [CrossRef] [Green Version]
  21. Tijet, N.; Wäspi, U.; Gaskin, D.J.; Hunziker, P.; Muller, B.L.; Vulfson, E.N.; Slusarenko, A.; Brash, A.R.; Whitehead, I.M. Purification, molecular cloning, and expression of the gene encoding fatty acid 13-hydroperoxide lyase from guava fruit (Psidium guajava). Lipids 2000, 35, 709–720. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Fukushige, H.; Hildebrand, D.F. Watermelon (Citrullus lanatus) hydroperoxide lyase greatly increases C6 aldehyde formation in transgenic leaves. J. Agric. Food Chem. 2005, 53, 2046–2051. [Google Scholar] [CrossRef]
  23. Rabetafika, H.N.; Gigot, C.; Fauconnier, M.-L.; Ongena, M.; Destain, J.; Du Jardin, P.; Wathelet, J.-P.; Thonart, P. Sugar beet leaves as new source of hydroperoxide lyase in a bioprocess producing green-note aldehydes. Biotechnol. Lett. 2008, 30, 1115–1119. [Google Scholar] [CrossRef] [PubMed]
  24. Padilla, M.N.; Hernandez, M.L.; Perez, A.G.; Sanz, C.; Martinez-Rivas, J.M. Isolation, expression, and characterization of a 13-hydroperoxide lyase gene from olive fruit related to the biosynthesis of the main virgin olive oil aroma compounds. J. Agric. Food Chem. 2010, 58, 5649–5657. [Google Scholar] [CrossRef] [PubMed]
  25. Mu, W.; Xue, Q.; Jiang, B.; Hua, Y. Molecular cloning, expression, and enzymatic characterization of Solanum tuberosum hydroperoxide lyase. Eur. Food Res. Technol. 2012, 234, 723–731. [Google Scholar] [CrossRef]
  26. Matsui, K.; Ujita, C.; Fujimoto, S.; Wilkinson, J.; Hiatt, B.; Knauf, V.; Kajiwara, T.; Feussner, I. Fatty acid 9- and 13-hydroperoxide lyases from cucumber. FEBS Lett. 2000, 481, 183–188. [Google Scholar] [CrossRef] [Green Version]
  27. Tijet, N.; Schneider, C.; Muller, B.L.; Brash, A.R. Biogenesis of volatile aldehydes from fatty acid hydroperoxides: Molecular cloning of a hydroperoxide lyase (CYP74C) with specificity for both the 9- and 13-hydroperoxides of linoleic and linolenic acids. Arch. Biochem. Biophys. 2001, 386, 281–289. [Google Scholar] [CrossRef]
  28. Kuroda, H.; Oshima, T.; Kaneda, H.; Takashio, M. Identification and functional analyses of two cDNAs that encode fatty acid 9-/13-hydroperoxide lyase (CYP74C) in rice. Biosci. Biotechnol. Biochem. 2005, 69, 1545–1554. [Google Scholar] [CrossRef] [Green Version]
  29. Hatanaka, A.; Kajiwara, T.; Sekiya, J. Biosynthetic pathway for C6-aldehydes formation from linolenic acid in green leaves. Chem. Phys. Lipids 1987, 44, 341–361. [Google Scholar] [CrossRef]
  30. Hatanaka, A. The biogeneration of green odour by green leaves. Phytochemistry 1993, 34, 1201–1218. [Google Scholar] [CrossRef]
  31. Lanciotti, R.; Gianotti, A.; Patrignani, F.; Belletti, N.; Guerzoni, M.E.; Gardini, F. Use of natural aroma compounds to improve shelf-life and safety of minimally processed fruits. Trends Food Sci. Technol. 2004, 15, 201–208. [Google Scholar] [CrossRef]
  32. Gigot, C.; Ongena, M.; Fauconnier, M.-L.; Wathelet, J.-P.; Du Jardin, P.; Thonart, P. The lipoxygenase metabolic pathway in plants: Potential for industrial production of natural green leaf volatiles. Biotechnol. Agron. Soc. Environ. 2010, 14, 451–460. [Google Scholar]
  33. Muller, B.; Gautier, A.; Dean, C.; Kuhn, J.C. Process for the Enzymatic Preparation of Aliphatic Alcohols and Aldehydes from Linoleic Acid, Linoleic Acid, or a Natural Precursor. U.S. Patent 5,464,761 A, 7 November 1995. [Google Scholar]
  34. Márczy, J.S.; Németh, Á.S.; Samu, Z.; Háger-Veress, Á.; Szajáni, B. Production of hexanal from hydrolyzed sunflower oil by lipoxygenase and hydroperoxide lyase enzymes. Biotechnol. Lett. 2002, 24, 1673–1675. [Google Scholar] [CrossRef]
  35. Németh, Á.S.; Márczy, J.S.; Samu, Z.; Háger-Veress, Á.; Szajáni, B. Biocatalytic production of 2(E)-hexenal from hydrolysed linseed oil. Enzym. Microb. Technol. 2004, 34, 667–672. [Google Scholar] [CrossRef]
  36. Whitehead, I.M.; Slusarenko, A.J.; Waspi, U.; Gaskin, D.J.H.; Brash, A.R.; Tijet, N. Guava (Psidium Guajava) 13-Hydroperoxide Lyase and Uses Thereof. U.S. Patent 6,780,621 B2, 24 August 2004. [Google Scholar]
  37. Noordermeer, M.A.; Van Der Goot, W.; Van Kooij, A.J.; Veldsink, J.W.; Veldink, G.A.; Vliegenthart, J.F. Development of a biocatalytic process for the production of c6-aldehydes from vegetable oils by soybean lipoxygenase and recombinant hydroperoxide lyase. J. Agric. Food Chem. 2002, 50, 4270–4274. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  38. Delcarte, J.; Fauconnier, M.; Jacques, P.; Matsui, K.; Thonart, P.; Marlier, M. Optimisation of expression and immobilized metal ion affinity chromatographic purification of recombinant (His)6-tagged cytochrome P450 hydroperoxide lyase in Escherichia coli. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2003, 786, 229–236. [Google Scholar] [CrossRef]
  39. Bourel, G.; Nicaud, J.-M.; Nthangeni, B.; Santiago-Gomez, P.; Belin, J.-M.; Husson, F. Fatty acid hydroperoxide lyase of green bell pepper: Cloning in Yarrowia lipolytica and biogenesis of volatile aldehydes. Enzym. Microb. Technol. 2004, 35, 293–299. [Google Scholar] [CrossRef]
  40. Santiago-Gomez, M.P.; Thanh, H.T.; De Coninck, J.; Cachon, R.; Kermasha, S.; Belin, J.-M.; Gervais, P.; Husson, F. Modeling hexanal production in oxido-reducing conditions by the yeast Yarrowia lipolytica. Process Biochem. 2009, 44, 1013–1018. [Google Scholar] [CrossRef]
  41. Gigot, C.; Ongena, M.; Fauconnier, M.-L.; Muhovski, Y.; Wathelet, J.-P.; Du Jardin, P.; Thonart, P. Optimization and scaling up of a biotechnological synthesis of natural green leaf volatiles using Beta vulgaris hydroperoxide lyase. Process Biochem. 2012, 47, 2547–2551. [Google Scholar] [CrossRef]
  42. Jacopini, S.; Mariani, M.; Brunini-Bronzini de Caraffa, V.; Gambotti, C.; Vincenti, S.; Desjobert, J.-M.; Muselli, A.; Costa, J.; Berti, L.; Maury, J. Olive recombinant hydroperoxide lyase, an efficient biocatalyst for synthesis of green leaf volatiles. Appl. Biochem. Biotechnol. 2016, 179, 671–683. [Google Scholar] [CrossRef]
  43. Jacopini, S.; Vincenti, S.; Mariani, M.; Brunini-Bronzini de Caraffa, V.; Gambotti, C.; Desjobert, J.M.; Muselli, A.; Costa, J.; Tomi, F.; Berti, L.; et al. Activation and Stabilization of Olive Recombinant 13-Hydroperoxide Lyase Using Selected Additives. Appl. Biochem. Biotechnol. 2017, 182, 1000–1013. [Google Scholar] [CrossRef] [PubMed]
  44. Baneyx, F. Recombinant protein expression in Escherichia coli. Curr. Opin. Biotechnol. 1999, 10, 411–421. [Google Scholar] [CrossRef]
  45. Baneyx, F. Protein Expression Technologies: Current Status and Future Trends; Garland Science: New York, NY, USA, 2004; p. 546. [Google Scholar]
  46. Thomas, J.G.; Baneyx, F. Protein Misfolding and Inclusion Body Formation in Recombinant Escherichia coli Cells Overexpressing Heat-shock Proteins. J. Biol. Chem. 1996, 271, 11141–11147. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  47. Thomas, J.G.; Ayling, A.; Baneyx, F. Molecular chaperones, folding catalysts, and the recovery of active recombinant proteins from E. coli. Appl. Biochem. Biotechnol. 1997, 66, 197–238. [Google Scholar] [CrossRef]
  48. Mertens, J.A.; Skory, C.D. Isolation and characterization of two genes that encode active glucoamylase without a starch binding domain from Rhizopus oryzae. Curr. Microbiol. 2007, 54, 462–466. [Google Scholar] [CrossRef]
  49. Villaverde, A.; Mar Carrió, M. Protein aggregation in recombinant bacteria: Biological role of inclusion bodies. Biotechnol. Lett. 2003, 25, 1385–1395. [Google Scholar] [CrossRef]
  50. Schrödel, A.; de Marco, A. Characterization of the aggregates formed during recombinant protein expression in bacteria. BMC Biochem. 2005, 6, 10. [Google Scholar] [CrossRef] [Green Version]
  51. Machida, S.; Yu, Y.; Singh, S.P.; Kim, J.-D.; Hayashi, K.; Kawata, Y. Overproduction of β-glucosidase in active form by an Escherichia coli system coexpressing the chaperonin GroEL/ES. FEMS Microbiol. Lett. 1998, 159, 41–46. [Google Scholar] [CrossRef]
  52. De Bernardez Clark, E.; Schwarz, E.; Rudolph, R. Inhibition of aggregation side reactions during in vitro protein folding. Methods Enzymol. 1999, 309, 217–236. [Google Scholar]
  53. Palmer, I.; Wingfield, P.T. Preparation and Extraction of Insoluble (Inclusion-Body) Proteins from Escherichia coli. Curr. Protoc. Protein Sci. 2012, 70, 6.3.1–6.3.20. [Google Scholar] [CrossRef] [Green Version]
  54. Singh, S.M.; Panda, A.K. Solubilization and refolding of bacterial inclusion body proteins. J. Biosci. Bioeng. 2005, 99, 303–310. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  55. Ventura, S.; Villaverde, A. Protein quality in bacterial inclusion bodies. Trends Biotechnol. 2006, 24, 179–185. [Google Scholar] [CrossRef] [PubMed]
  56. Schein, C.H. Production of Soluble Recombinant Proteins in Bacteria. Bio Technol. 1989, 7, 1141–1149. [Google Scholar] [CrossRef]
  57. Feller, G.; Le Bussy, O.; Gerday, C. Expression of Psychrophilic Genes in Mesophilic Hosts: Assessment of the Folding State of a Recombinant α-Amylase. Appl. Environ. Microbiol. 1998, 64, 1163–1165. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  58. Mujacic, M.; Cooper, K.W.; Baneyx, F. Cold-inducible cloning vectors for low-temperature protein expression in Escherichia coli: Application to the production of a toxic and proteolytically sensitive fusion protein. Gene 1999, 238, 325–332. [Google Scholar] [CrossRef]
  59. Song, J.M.; An, Y.J.; Kang, M.H.; Lee, Y.-H.; Cha, S.-S. Cultivation at 6–10 °C is an effective strategy to overcome the insolubility of recombinant proteins in Escherichia coli. Protein Expr. Purif. 2012, 82, 297–301. [Google Scholar] [CrossRef]
  60. Vasina, J.A.; Baneyx, F. Expression of Aggregation-Prone Recombinant Proteins at Low Temperatures: A Comparative Study of the Escherichia coli cspA and tac Promoter Systems. Protein Expr. Purif. 1997, 9, 211–218. [Google Scholar] [CrossRef]
  61. Vuillemin, M.; Malbert, Y.; Laguerre, S.; Remaud-Siméon, M.; Moulis, C. Optimizing the production of an α-(1→2) branching sucrase in Escherichia coli using statistical design. Appl. Microbiol. Biotechnol. 2014, 98, 5173–5184. [Google Scholar] [CrossRef] [Green Version]
  62. Betton, J.-M.; Chaffotte, A. Repliement et production de protéines recombinantes. Méd. Sci. 2005, 21, 613–617. [Google Scholar] [CrossRef] [Green Version]
  63. Ferrer, M.; Chernikova, T.N.; Yakimov, M.M.; Golyshin, P.N.; Timmis, K.N. Chaperonins govern growth of Escherichia coli at low temperatures. Nat. Biotechnol. 2003, 21, 1266–1267. [Google Scholar] [CrossRef]
  64. Kimata, K.; Yamaguchi, M.; Saito, Y.; Hata, H.; Miyake, K.; Yamane, T.; Nakagawa, Y.; Yano, A.; Ito, K.; Kawarasaki, Y. High cell-density expression system: A novel method for extracellular production of difficult-to-express proteins. J. Biosci. Bioeng. 2012, 113, 154–159. [Google Scholar] [CrossRef] [PubMed]
  65. Vick, B.A. A spectrophotometric assay for hydroperoxide lyase. Lipids 1991, 26, 315–320. [Google Scholar] [CrossRef]
Figure 1. Henry’s half-line of the normalizing effects of the temperature, inducer concentration and induction duration, for M30, I30, B19 and A19; factors are coded as follows: temperature (A), inducer concentration (B), induction duration (C); answer = enzyme activity (U L-1of culture); α = 0.05; the adjustment line in red indicates where the points should be if there was no effect. Henry’s half-line displays the absolute value of all the normalized effects, positive and negative. All terms are on the right side of the graph, and their distance from the line highlights their relative importance; significant effects are represented by red squares (), while non-significant effects are represented by blue circles ().
Figure 1. Henry’s half-line of the normalizing effects of the temperature, inducer concentration and induction duration, for M30, I30, B19 and A19; factors are coded as follows: temperature (A), inducer concentration (B), induction duration (C); answer = enzyme activity (U L-1of culture); α = 0.05; the adjustment line in red indicates where the points should be if there was no effect. Henry’s half-line displays the absolute value of all the normalized effects, positive and negative. All terms are on the right side of the graph, and their distance from the line highlights their relative importance; significant effects are represented by red squares (), while non-significant effects are represented by blue circles ().
Catalysts 11 00176 g001
Figure 2. Three-dimensional (3D) response surface plots of the HPL activity recovered in the soluble fraction for M30 and I30 expression systems, as a function of the temperature and induction duration; for B19 expression system, as a function of (a) temperature and induction duration and (b) temperature and inducer concentration; and for A19 expression system.
Figure 2. Three-dimensional (3D) response surface plots of the HPL activity recovered in the soluble fraction for M30 and I30 expression systems, as a function of the temperature and induction duration; for B19 expression system, as a function of (a) temperature and induction duration and (b) temperature and inducer concentration; and for A19 expression system.
Catalysts 11 00176 g002
Figure 3. SDS–PAGE (12% acrylamide) analysis of proteins from the soluble fraction of cell lysate. The proteins (15 µg for (a) and 0.5 µg for (b)) were separated by electrophoresis then (a) stained by EZBlue gel staining reagent or (b) blotted and probed with the specific monoclonal peroxidase conjugated anti-His antibody; MS: molecular mass standard (Precision Plus protein dual-color standard, Bio-Rad, Hercules, CA, USA). Lanes 1 to 4 relate to expression, respectively, with M30, I30, B19 and A19 expression systems.
Figure 3. SDS–PAGE (12% acrylamide) analysis of proteins from the soluble fraction of cell lysate. The proteins (15 µg for (a) and 0.5 µg for (b)) were separated by electrophoresis then (a) stained by EZBlue gel staining reagent or (b) blotted and probed with the specific monoclonal peroxidase conjugated anti-His antibody; MS: molecular mass standard (Precision Plus protein dual-color standard, Bio-Rad, Hercules, CA, USA). Lanes 1 to 4 relate to expression, respectively, with M30, I30, B19 and A19 expression systems.
Catalysts 11 00176 g003
Table 1. Response surface quadratic model analysis of hydroperoxide lyase (HPL) activity level obtained with M30, I30, B19 and A19 expression system, after model simplification—second-order polynomial equations and determination coefficients.
Table 1. Response surface quadratic model analysis of hydroperoxide lyase (HPL) activity level obtained with M30, I30, B19 and A19 expression system, after model simplification—second-order polynomial equations and determination coefficients.
Expression SystemEquation aR2Adj R2
M30Soluble activity (U L−1of culture) = −5346 + 516.1 × T + 97 × I + 56.89 × D − 9.929 × T2 + 146.7 × I2 − 0.3363 × D2 − 8.99 × T × I − 1.0205 × T × D + 1.27 × I × D0.97240.9653
I30Soluble activity (U L−1of culture) = −4477 + 500.8 × T + 185 × I + 28.38 × D − 10.336 × T2 −32.2 × I2 − 0.2090 × D2 + 1.08 × T × I − 0.3006 × T × D − 1.090 × I × D0.97060.9630
B19Soluble activity (U L−1of culture) = −3809 + 430.8 × T + 176 × I + 34.64 × D − 8.573 × T2 + 207 × I2 − 0.2275 × D2 − 9.70 × T × I − 0.4994 × T × D − 0.724 × I × D0.98010.9750
A19Soluble activity (U L−1of culture) = −3571 + 442.1 × T − 152 × I + 86.35 × D − 9.566 × T2 + 132 × I2 − 0.4398 × D2 + 0.27 × T × I − 2.734 × T × D + 1.49 × I × D0.96650.9578
a Factors coded as follows: temperature (T), inducer concentration (I) and culture duration (D).
Table 2. Response surface quadratic model analysis of HPL activity level obtained with M30, I30, B19 and A19 expression system, after model simplification—analysis of variance (ANOVA).
Table 2. Response surface quadratic model analysis of HPL activity level obtained with M30, I30, B19 and A19 expression system, after model simplification—analysis of variance (ANOVA).
Source aSum of SquaresDegree of FreedomF Valuep-Value b
M30I30B19A19M30I30B19A19M30I30B19A19M30I30B19A19
Model1,963,0261,532,2371,284,8124,758,6539999136.81128.21191.51112.090.0000.0000.0000.000
T482,971473,401350,658979,8621111302.93356.50470.40207.730.0000.0000.0000.000
I36,46583,49783,35517,275111122.8762.88111.823.660.0000.0000.0000.064
D190,478101,02396,5201,175,4131111119.4776.08129.48249.190.0000.0000.0000.000
T2682,550739,644508,860633,5491111428.12557.00682.63134.310.0000.0000.0000.000
I29777-19,462-1-1-6.13-26.11-0.018-0.000-
D2415,704160,588190,188710,9701111260.74120.93255.13150.730.0000.0000.0000.000
T × I--5720---1---7.67---0.009-
T × D181,54815,61043,1041,291,3361111113.8711.7657.82273.770.0000.0020.0000.000
I × D----------------
Lack of fit49,27533,76118,529156,098333380.5428.3226.14185.120.0000.0000.0000.000
Pure error652612,7157561899432323232--------
Total2,018,8271,578,7141,310,9034,923,74544444444--------
a Factors coded as follows: temperature (T), inducer concentration (I) and culture duration (D); b p-value < 0.05 indicates a statistical significance of the factor.
Table 3. Predicted and measured HPL soluble activity level with the optimal conditions from response surface methodology (RSM) analyses for M30, I30, B19 and A19 expression systems.
Table 3. Predicted and measured HPL soluble activity level with the optimal conditions from response surface methodology (RSM) analyses for M30, I30, B19 and A19 expression systems.
Expression SystemOptimal Expression ConditionsPredicted HPL Activity a
(U L−1of culture)
Measured HPL Activity b
(U L−1of culture)
T (°C)I (mM)D (h)
M3023151.521972254 ± 19
I3023.5148.522502177 ± 20
B192314922772285 ± 12
A1916150.521432209 ± 16
Factors are coded as follows: temperature (T), inducer concentration (I), induction duration (D); a activity predicted by RSM analysis for 2 mL production in microplates; b two-milliliter production in microplates for experimental validation. Measured activity in the optimal conditions predicted by RSM analysis.
Table 4. Experimental level of factors affecting the olive recombinant HPL production for each host-vector combination.
Table 4. Experimental level of factors affecting the olive recombinant HPL production for each host-vector combination.
FactorE. coli Strain/Vector Construction
M30 I30 B19A19
Codded Factor LevelsCodded Factor Levels
−1 (Low)0 (Middle)+1 (High)−1 (Low)0 (Middle)+1 (High)
Temperature (T), °C202530101520
Inducer conc. (I), mM0.10.5510.10.551
Duration (D), h184266184266
M30 for M15 transformed with pQE30. I30 for IqExpress transformed with pQE30. B19 for BL21 DE3 transformed with pET19b. A19 for Arctic Express DE3 transformed with pET19b.
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Vincenti, S.; Mariani, M.; Croce, J.; Faillace, E.; de Caraffa, V.B.-B.; Berti, L.; Maury, J. Optimizing the Production of Recombinant Hydroperoxide Lyase in Escherichia coli Using Statistical Design. Catalysts 2021, 11, 176. https://doi.org/10.3390/catal11020176

AMA Style

Vincenti S, Mariani M, Croce J, Faillace E, de Caraffa VB-B, Berti L, Maury J. Optimizing the Production of Recombinant Hydroperoxide Lyase in Escherichia coli Using Statistical Design. Catalysts. 2021; 11(2):176. https://doi.org/10.3390/catal11020176

Chicago/Turabian Style

Vincenti, Sophie, Magali Mariani, Jessica Croce, Eva Faillace, Virginie Brunini-Bronzini de Caraffa, Liliane Berti, and Jacques Maury. 2021. "Optimizing the Production of Recombinant Hydroperoxide Lyase in Escherichia coli Using Statistical Design" Catalysts 11, no. 2: 176. https://doi.org/10.3390/catal11020176

APA Style

Vincenti, S., Mariani, M., Croce, J., Faillace, E., de Caraffa, V. B. -B., Berti, L., & Maury, J. (2021). Optimizing the Production of Recombinant Hydroperoxide Lyase in Escherichia coli Using Statistical Design. Catalysts, 11(2), 176. https://doi.org/10.3390/catal11020176

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop