Sugar-Improved Enzymatic Synthesis of Biodiesel with Yarrowia

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Sugar-Improved Enzymatic Synthesis of Biodiesel with Yarrowia lipolytica Lipase 2 Hao Cao, Meng Wang, Li Deng, Luo Liu, Ulrich Schwaneberg, Tianwei Tan, Fang Wang, and Kaili Nie Energy Fuels, Just Accepted Manuscript • Publication Date (Web): 02 May 2017 Downloaded from http://pubs.acs.org on May 8, 2017

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Sugar-Improved Enzymatic Synthesis of Biodiesel with Yarrowia lipolytica Lipase 2 Hao Cao,1,2 Meng Wang, *,1 Li Deng,1 Luo Liu,1 Ulrich Schwaneberg, 2,3

Tianwei Tan,1 Fang Wang,1 Kaili Nie*,1

1 Beijing Bioprocess Key Laboratory, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China

2 Lehrstuhl für Biotechnologie, RWTH Aachen University, Worringerweg 3, 52074 Aachen, Germany

3 DWI-Leibniz Institut für Interaktive Materialien, Forckenbeckstraße 50, 52056 Aachen, Germany

1

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KEYWORDS Yarrowia lipolytica Lipase 2; Biodiesel; Glucose; Sugars; Methanol resistance; Molecular dynamics.

ABSTRACT In this research, it was found that in Yarrowia lipolytica Lipase 2 (YLLIP2) catalyzed biodiesel production, the content of fatty acid methyl esters (FAMEs) was increased by about 10% with the addition of

D(+)-glucose.

The result indicated that the

D(+)-glucose

could be used as an

effective additive in YLLIP2 catalyzed biodiesel production. According to the results above, the single factor experiments of key parameters in the process were first carried out. Based on the single factor experiment results, a five-factor, three-level response surface method was adopted to obtain the optimal reaction conditions: lipase dosage 40 IU/g oil, D(+)-glucose to lipase 1:1.05 (w/w), water content 1.95%, and reaction temperature 39.4 °C. A stoichiometric amount of methanol (11.5%, methanol/waste oil) was added in 6 times (every 4 hours for each addition). A subsequent pilot scale production in a 5-ton reactor was carried out to check the performance of this method, and a good biodiesel content of 91.4% was obtained. Finally, molecular dynamics (MD) simulation was adopted to help to explain the possible functions of D(+)-glucose acting on the lipase in the process. The simulation results indicated that one of the functions maybe attributed to

D(+)-glucose

preventing methanol to diffuse into YLLIP2, thus resulting in the

prevention of the methanol disruption to protein.


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Introduction Lipase (glycerol ester hydrolase EC 3.1.1.3) has a broad range of applications in industry through hydrolysis, esterification and transesterification reactions1. In the last decade, chemical methods were frequently used for biodiesel production, but these methods have drawbacks, such as the need for removal of catalysts, high energy consumption and negative environmental issues. For those reasons, lipase has been widely investigated in biodiesel production to avoid the drawbacks of chemical methods2. However, the sensitivity of lipase to polar solvents, such as methanol, limits the widely utilization of lipases in the industrial applications. Methanol is a commonly used alcohol in biodiesel synthesis due to its low cost3 and availability4. Moreover, the use of methanol is advantageous as methanol could be more reactive than other short chain alcohols for biodiesel production5 and be easily and simultaneously separated with glycerol in the process4. In principle, the theoretically optimal methanol: triacylglycerols molar ratio is 3:1 in biodiesel production. An increase in methanol concentration was suggested for to a higher content of biodiesel. However, when the concentration of methanol is excess to a certain amount or even at the stoichiometric condition, methanol still exhibits the inactivation, inhibition, or denaturation effect on lipase. The explanations of methanol caused lipase catalytic activity decrease were previously reported in the view of disruption of enzyme-water interaction6, contribution of substrate-solvent interaction7, disruption of intra-protein interactions8 and competitive inhibition9. Consequently, several strategies were employed to overcome the deleterious effect of the presence of methanol on lipase (Table 1). Host screening strategy indicated that lipases could be


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classified as sensitivity or robustness to methanol. Lipase from Burkholderia and Stenotrophomonas genus appeared to be highly tolerant to methanol, while Candida genus lipase and several others were methanol sensitive ones. In the case of protein engineering, modifications of surface amino acid residues of lipases could change the surface hydrophobicity in order to influence the contact between lipase and solvent, resulting in improving the lipase stability in methanol solvent. Towards process engineering, a stepwise addition strategy requires a critical selection of the most suitable bioreactors when applied to the industrial scale; both cosolvent and additive strategies have the problem of raw materials’ cost and the requirement for separation from the products. Table 1. Improved strategies for to overcome the negative effect of the presence of methanol on lipase Strategy

Microorganism engineering

Protein engineering

Process engineering

Strain

Method

Result

Ref.

Burkholderia glumae

Host screening

Highest activity in the presence of 50–70 % methanol

10

Stenotrophomonas maltophilia

Host screening

11

Proteus mirabilis

Directed evolution

Geobacillus stearothermophilus

Semi-directed evolution

Candida antarctica

Rational design

Thermomyces lanuginosus Pseudomonas fluorescens Yarrowia lipolytica

Stepwise addition Cosolvent

82.2 % residual activity in 20% methanol solvent for 24 h 50 fold longer halfinactivation time in 50% methanol 23 fold longer halfinactivation time in 70% methanol 75 % residual activity in 80% methanol solvent for 24 h Optimal yield reached 97 % from 85% Optimal yield reached 87.6 % from 61.6% Optimal yield reached 89 % from 68 %

Additive

12

13

14

15

16

17


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Candida antarctica

Replacement of Acyl acceptor

Optimal yield reached 92 % with stoichiometric methyl acetate

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In our previous work, β-cyclodextrin (β-CD) was used as additive to improve the biodiesel synthesis with Yarrowia lipolytica Lipase 2 (YLLIP2)

17

. The results of molecular dynamics

(MD) simulation indicated that the mechanism of the action of this circular saccharide on the protein was the interaction between the hydroxyl groups of β-CD and the polar residues on the surface of lipase, thus enhancing the methanol resistance19. β-CD is constructed by 7 glucose units. It has been known that sugars may increase the thermal stability of proteins, and can be used as protective agent in protein lyophilization 20, 21. However, literature scarcely reported that sugar could protect lipase against being denatured by polar solvents through direct addition into the reaction system. The aim of this research was to investigate whether the glucose could be an additive to improve the efficiency of the biodiesel synthesis process catalyzed by YLLIP2, and to find out the optimal reaction conditions. Furthermore, MD simulations were utilized to understand and explain the positive effect of glucose on the YLLIP2 in a methanol solvent in order to develop a rational strategy to improve the lipase-catalyzed reaction using additives. Materials and methods Experimental Materials Waste cooking oil (WCOs) was obtained from Lvming Co. Ltd (Shanghai, China). It contains 83.9% of free fatty acids (FFAs), 0.5% of monoacylglycerols (MAGs), 6.9% of diacylglycerols (DAGs), and 8.7% of triacylglycerols (TAGs). Since Shanghai is a coastal city in South China, the temperature and air humidity are relatively high year-round. For this reason, the waste cooking oil generally had a serious rancidification during collection, storage, and transportation processes. Most of the WCOs used by Lvming had a free fatty acid content around


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70%-80% by weight. The average fatty acid molecular mass was 275.9 g/mol according to the fatty acid compositions (Table 2). According to the composition of WCOs and average fatty acid molecular mass, the stoichiometric amount of methanol was 1.15g with 10 g waste cooking oil by calculation. The WCOs with high free fatty acid content were difficult to transform using traditional chemical method. Table 2. Fatty acid compositions of the waste cooking oil Fatty acid

wt%

Molecular formula

Name of fatty acid

C14:0

Myristic acid

0.8±0.1

C16:0

Palmitic acid

21.2±1.1

C16:1

Palmitoleic acid

1.2±0.1

C18:0

Stearic acid

6.6±0.6

C18:1

Oleic acid

34.6±1.2

C18:2

Linoleic acid

30.6±0.8

C18:3

Linolenic acid

3.4±0.2

C20:0

Erucic acid

1.0±0.2

C22:1

Arachidic acid

0.6±0.1

Lipase from Candida sp. 99-125 belonging to Yarrowia lipolytica with enzyme activity about 20,000 IU/g was used as catalyst (Kaitai Biochemical Technology Company, Beijing, China).

D(+)-glucose

(using glucose as abbreviation in the following descriptions) and other

chemicals were of analytical grade and purchased from Beijing Chemical Factory (Beijing, China). Lipase activity assay


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In this research, the hydrolytic activity of lipase was quantified as the initial and residual enzyme activity. The hydrolytic activity of lipase was measured by titrimetric assay according to a modified olive oil emulsion method19, 20. Olive oil [5%, (v/v)] was emulsified in distilled water containing 2% (w/v) of polyvinyl alcohol (PVA) in a homogenizer for 6 min at maximum speed. The assay mixture consisted of emulsion (5 mL), phosphate buffer (4 mL, 100 mmol·L-1, pH 8.0) and lipase (1 mL, concentrated or diluted, depending on the quantity of lipase). The oil hydrolysis was incubated at 40 oC for 10 min with agitation. The reaction was stopped by adding 20 mL ethanol. The enzyme activity was determined by titration of the fatty acids using 50 mmol·L-1 NaOH. One activity unit of lipase was defined as the amount of enzyme that released 1 mmol of fatty acids per minute under the assay conditions. General process for methanolysis of waste oil The enzymatic synthesis was carried out in a 100 mL conical flask at a 200 rpm in an air bath rotating bed. In single factor experiment, 10 g waste cooking oil was used, and stoichiometric amounts of methanol were added six times. The reaction time and temperature were set at 24 h and under 40oC following the previous research22. The amount of lipase, glucose and water content were individually optimized, meaning that when the effect of a given parameter was investigated, the other parameters were kept constant. In response surface optimization process, 10 g waste cooking oil and stoichiometric amounts of methanol were used as substrate. Other parameters, such as lipase dosage, water content, glucose/lipase, reaction temperature and methanol adding frequency were optimized with response surface methodology. A five-factor, three-level response surface was designed by Design Expert 7.0.0 software using Box-Behnken design methodology and shown in SI Table 1 and SI Table 2. The reaction results were also analyzed by Design Expert 7.0.0 software. During the reaction process, 10µL of


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reaction mixture was taken every 2 h and dissolved in 1 mL n-hexane. After centrifugation at 4800 ×g, the n-hexane solution was used for gas chromatography analysis. The data are shown as averages with their standard deviation (n = 3). Methanol tolerance assay Parallel reactions were performed under the following conditions. 10 g oil, 2.5 g methanol, and 2.5 g water were added into a 200 mL conical flask. 0.5 g lipase with 0.5 g glucose or other sugars were mixed, and then added into the system. The flasks were incubated in an air bath rotating bed with a 200 rpm stirring at 40 °C, 45 °C and 50 °C, respectively. Samples were taken every 2 h. The lipase was collected after centrifugation (4800×g). The residual activity of lipase was detected. The control experiments without glucose were performed and the lipase activity was also assayed. The data are shown as averages with their standard deviation (n = 3). Gas chromatography analysis The free fatty acid and esters, such as free acid methyl ester (FAMEs), contents in the mixture were quantified by a GC-2010 gas chromatography (GC, Shimadzu 2010 Japan). The GC analytical method was the same as reported23, 24. Heptadecanoic acid and its methyl ester purchased from Sigma were used as an internal standard. The specific compound content was defined as the weight ratio of a specific compound divided by the total weight of FFAs, FAMEs, MAGs, DAGs and TAGs, as shown in Equation (1) Specific compound content/% =

Weight of a specific compound × 100% Total weight of FFAs, FAMEs, MAGs, DAGs and TAGs …………………………………Equation (1)


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Circular dichroism measurement The protein secondary structure of YLLIP2 was measured by circular dichroism spectrum (CD) between 180 nm and 250 nm at 25°C. The system without enzyme was used as a blank control. The secondary structure element content was estimated using the DICHROWEB application package based on the SELCON3 algorithm described by Sreerama et al.25, 26. Computational procedures Protein structure used The initial opened conformation of YLLIP2, based on the X-ray structure of YLLIP2 (PDB ID: 4JEI), was obtained in our previous study

27

.It was a semi-open conformation and was

similar with the report of Bordes et al.28. Crystal waters around the surface were preserved in the molecular dynamics simulations. Molecular Dynamics Simulations All molecular simulations were performed with the YASARA software package (version 16.3.8) using the AMBER03 force ﬁeld29. The lipase was embedded in a cubic box with a 1.0 nm space left around the lipase for adding 50 % (v/v) methanol-water mixture solvent system, in which the TIP3P model was used for water molecules and methanol, α-D-glucopyranose and β-Dglucopyranose molecules were optimized by semi-empirical quantum mechanics. The rough ratio (α:β=1:1,mol/mol) of D-glucopyranose was employed due to the variable conformation of glucose in the solvent (SI Table 4). 108 α-D-glucopyranose molecules and 108 β-Dglucopyranose molecules were added into the solvent system (glucose:lipase = 1:1, w/w). The production simulations of the protein-solvent systems were performed at 313 K and at atmospheric

pressure

for

10

ns

using

the

standard

md_run

macro

(http://www.yasara.org/macros.htm) on YASARA.


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In order to reduce the bias of the initial atom velocities and position of glucose molecules, three independent MD simulations were carried out. Control experiments without glucose were also performed according to the same methods. Simulation procedure The root-mean-square displacement (RMSD) of backbone atoms (the carboxylic carbon atom, the α carbon atom and the amino nitrogen atom of each amino acid residue) and the root mean square distance of all atoms of each residue from the mass center of protein (radius of gyration) were calculated to evaluate the overall motion of YLLIP2. The radial distribution function (RDF), g(r) in a system of particles, describes how the density varies as a function of distance from a reference particle. In the present work, RDF was calculated to detect the distribution of solvent molecules around YLLIP230. The dynamic cross-correlation matrix (DCCM) was calculated to analyze the movements of residues31. The values in the DCCM range from -1 (perfectly anti-correlated) to +1 (perfectly correlated). The values along the diagonal are always +1 (because the motion of an atom is perfectly correlated to itself). The 10 ns trajectory was used to calculate the above values. YASARA's definition of a hydrogen bond is that the hydrogen bond energy is better than 6.25 kJ/mol. The structural snapshot of YLLIP2 at 10 ns was obtained to view and analyze by Pymol package 32. Results and discussion Effects of glucose on biodiesel production Previously, β-CD was successfully used as additive in enzymatic synthesis of biodiesel

17

.

Recently, glucose, as an additive, was used to improve the biodiesel production. The comparative experiments for YLLIP2 lipase were undertaken both with and without glucose. The


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content of fatty acid methyl esters (FAMEs) was monitored to evaluate the effect of glucose in the biodiesel production. As shown in Figure 1, the content of FAMEs was 77.4 % with a lipase dosage of 1000 IU/g WCOs without glucose. However, the content reached 85.6 % under the same condition with glucose present. The results indicated that glucose could improve the methanolysis reaction with YLLIP2 for biodiesel production.

Figure 1. YLLIP2 catalyzed methanolysis both with and without glucose. (Conditions: waste oil (10 g), water content (5 wt %), lipase dosage (1000 IU/g WCOs), glucose:lipase = 1:1(w/w), 40°C, intermittent methanol addition of 6 times, during 40 h reaction.) To investigate the positive function of glucose, the methanol tolerance assay was designed. The effect of methanol and temperature on the lipase with or without glucose was checked. More methanol amount (25%wt, methanol/oil) than the methanol resistance of YLLIP233 was added to make the comparative results more obvious. As shown in Figure 2, the residual activity of


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YLLIP2 without glucose was only 40 % of initial activity at 40 °C in 10 h. Whereas, YLLIP2 with glucose present could maintain 65 % of its initial activity. With increasing of incubation temperature, the residual activity of YLLIP2 when using glucose was 2.9 times and 4.6 times than that of YLLIP2 without using glucose at 45 °C and 50 °C in 10 h, respectively. Several researches indicated that methanol, especially methanol-water mixtures, inhibited the activity of lipases. The denaturation of lipase by methanol was explained that methanol molecule can penetrate into the enzyme molecules (or strip the critical water from the enzyme surface), then resulted in solvent-swollen or unfolding of the tertiary structure34, 35. On the other hand, lyophilized enzymes with sugars exhibited the desired performance in organic solvents in which the anhydrous environment presumably locks the enzyme molecule kinetically in its prior conformation. However, the lyophilization also could significantly cause protein denature because of the dehydration, and this detrimental effect can be greatly minimized or even prevented by lyophilizing enzymes in the presence of sugars36. Interestingly, in the present work, the simple addition of glucose to the reaction system could do well to the enzymatic synthesis of biodiesel with YLLIP2, indicating that glucose could help to improve the properties of YLLIP2. The results of CD analysis further proved that glucose slightly impacts the secondary structure of YLLIP2. At all tested temperatures, the α-helix of lipase with glucose was always higher than that without glucose, which indicated that the structure of protein might be more stable in the presence of glucose (SI Figure 1). In the following parts, MD simulation was employed to further investigate the effect of glucose on the methanol resistance of YLLIP2.


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Figure 2. Residual activity of YLLIP2 with glucose and without glucose after incubation in oleic triacylglycerol with 50% (v/v) methanol-water solvent at 40 °C, 45 °C and 50 °C for 10 h. Optimization of sugar-assisted lipase catalyzed biodiesel production To make this sugar-assisted lipase-catalyzed reaction more economically feasible for further industrial operation, the reaction conditions were optimized using single factor experiments and response surface method. Lipase amount, additive dosage, and water content had been investigated as the important parameters for biodiesel synthesis in our previous work 17. Normally, the feasibility of an enzymatic process depends on the dosage of biocatalyst. Therefore, the lipase dosage was first optimized in this research. The results indicated that the ester content increased significantly when lipase dosage increased from 10 IU/g WCOs to 40 IU/g WCOs. The content leveled off when the lipase dosage was excess to 40 IU/g oil (Figure 3 A). Based on the minimization of the cost of the process, an enzyme dosage of 40 IU/g WCOs was chosen as optimal condition.


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The effect of lipase and additive weight ratio was shown in Figure 3 B. The content of FAMEs increased with lipase: glucose ratio (w/w) from 1:0 to 1:1, and then decreased when the glucose was excess to lipase. The results were in accordance with our work with β-CD as additive for biodiesel production17. Lower amounts of glucose than lipase were insufficient to the lipase, whereas overload of glucose might block the mass transfer between the substrate and lipase. As a result, the optimal amount of glucose dosage was chosen as lipase: glucose ratio (w/w) of 1:1. The optimal water content for enzymatic methanolysis is different for various lipases. For example, the synthesis of alkylesters by Candida antarctica lipase B decreases with increasing water content, whereas water improves the yields of reactions catalysed by Rhizopus oryzae, Candida sp. 99-125, and Pseudomonas cepacia37. In our previous work, the optimal water content for Yarrowia lipolytica Lipase 2 without any additives was 5-10 wt% (water/oil, w/w) in the methanolysis reaction22. In this work, the optimal water content was reduced to 2 wt% (water/oil, w/w) in the presence of glucose (Figure 3 C). A specific amount of water is clearly essential for maintaining the active three-dimensional structure of lipase in the reaction system38. It is assumed that glucose may replace the essential water to stabilize the lipase structure, which leads to a significant reduction of the optimal water content.


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Figure 3. Effects of enzyme dosage (A), glucose dosage (B) and water content (C) on methanolysis with (■) and without glucose (●). Conditions: 10 g of waste oil, 40 ° C, intermittent methanol addition of 6 times, during 24 h reaction. Based on these optimal parameters from single factor experiments, further investigations were made by response surface methodology to figure out the interaction that may exist among the individual variables. A five-factor (lipase dosage, water content, glucose/lipase weight ratio, temperature, and methanol adding frequency), three-level response surface was designed. Design Expert 7.0.0 program was used to evaluate the effect of each factor and their interactions on FAMEs content.


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The experimental data obtained from Box-Behnken design were analyzed by response surface methodology. A mathematical model, following a second-order polynomial Eq. (2) which includes all interaction terms was used to calculate the predicted response: 1

#$%&'(&' = )* + , )- .- + -34

1

, )-- .-/ -34

1

+ , )-0 .- .0 -20

…………………………………Equation (2) The experimental results were illustrated in SI Table 1 and SI Table 2. The content of FAMEs varied from 50.75% to 91.69% (shown in SI Table 2), and the experiments of 2 and 3 gave the minimum and maximum contents, respectively. According to the results in SI Table 2, the model expressed can be by Eq. (3). The statistical significance of Eq. (3) was controlled by F-test and the analysis of variance (ANOVA) for response surface quadratic model and is given in SI Table 3. Values of probability (P)>F less than 0.005 indicate that model terms are significant. The relationship between predicted and experimental FAMEs content was shown in SI Figure 2.

Content/% = 85.64 + 1.57A − 0.72B − 0.72C − 1.86D + 11.87E − 4.60AB + 0.06AC + 4.03AD − 3.18AE − 0.42BC + 4.07BD − 0.46BE + 0.57CD − 0.32CE − 2.4DE − 0.90A/ − 2.32B/ + 0.42C/ − 2.31D/ − 8.75E / …………………………………Equation (3) With A (Lipase dosage), B (Water content), C (Glucose/lipase (w/w)), D (Temperature) and E (Methanol adding frequency), the optimum waste cooking oil methyl ester content was


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Energy & Fuels

determined from the model (Eq. (3)). The optimum conditions of lipase catalyzed biodiesel synthesis from WCOs were: lipase dosage 40 IU/g oil, water content 1.95%, glucose/lipase (w/w) 1.05:1, temperature 39.4 oC and methanol adding frequency 6 times. The predicted WCOs methyl ester content was 92.3% from the model. To confirm the accuracy of the model, lipase catalyzed biodiesel synthesis from WCOs was carried out under the optimal conditions. The experimental WCOs methyl ester content was 92.1%. According to the results, verification experiments confirmed the validity of the predicted model. The reusability of the lipase in the glucose system was also tested. After each batch, the reaction mixture stood for half an hour to allow the lipase and glucose to settle down to the bottom of the reactor. Then the upper oils layer (biodiesel and oil) could be separated. Fresh WCOs was added to the reactor for the next batch reaction. The results were shown in Table 3. Following the procedures, lipase could be reused for 4 batches with the content of FAMEs over 80%. Table 3. The reuse of lipase under optimal conditions Content (%) Batches FAMEs

FFAs

MAGs

DAGs

TAGs

1

90.2±0.9

4.79±0.36

2.97±0.15

1.14±0.12

0.11±0.05

2

88.1±1.2

5.82±0.27

3.20±0.23

1.31±0.09

0.62±0.11

3

86.2±1.5

7.39±0.52

3.22±0.12

1.37±0.11

0.72±0.18

4

83.0±1.4

9.87±0.29

3.05±0.18

1.77±0.08

0.95±0.07

5

74.1±1.1

14.37±0.48

3.51±0.21

2.98±0.15

2.96±0.13


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Furthermore, the process has been scaled up to a 5-ton reactor (Figure 4). Due to the insufficient mass transfer in the pilot scale reactor, the reaction time was prolonged to 40 hours to obtain a better FAMEs content and the result was shown in Figure 5. The reuse of lipase was also tested in this scaled-up production. The content of FAMEs in five batches were 91.4%, 89.5%, 83.4%, 82.5%, and 76.2% respectively. The content of FAMEs when using glucose was similar with that by using β-CD in the previous work. The cost of additive was significantly reduced since the price of glucose is much cheaper than that of β-CD, which would make the process more feasible for industrial application. After the separation process, the biodiesel properties in scaled-up experiments meet the EU biodiesel standard (EN14214), and the data were shown in SI Table 5.

Figure 4. The structure and photographic illustration of the 5 ton reactor used in the research.


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Figure 5. Biodiesel production with glucose as additive under optimal conditions in a 5 ton reactor. Conditions: 3.5 ton waste oil, water content 2 wt%, lipase dosage (40000 IU/kg waste oil, 0.2 wt% to the weight of oil), glucose:lipase = 1:1(w/w), 40 °C, intermittent methanol addition of 6 times, during the 40 hr reaction. Components of fatty acid methyl esters (FAMEs), free

fatty

acids

(FFAs),

monoacylglycerols

(MAGs),

diacylglycerols

(DAGs)

and

triacylglycerols (TAGs) were illustrated. In order to compare the difference of sugars on this process, a series of sugars were tested (Table 4). The results indicated that all kinds of common sugars could be used as additives in the YLLIP2 catalyzed biodiesel production. Glucose and lactose gave the highest FAMEs content improvement, following by fructose, galactose, maltose, and sucrose. Furthermore, this result validated the MD simulation results, which indicated that the protein-sugar interaction could help to improve the stability of YLLIP2. Table 4. Effect of different sugars on FAMEs content catalyzed by YLLIP2


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Additives

FAMEs Content (%)

Blank Control (without additives)

( ( /% 74.3±1.4

D(+)-Glucose

90.2±0.8

D(-)-Fructose

89.9±1.1

D(+)-Galactose

89.7±1.5

α-D-Glucosido-(1→2)β-D-fructofuranoside

85.4±0.9

α-D-Glucopyranosido-(1→4)α-glucopyranose

88.2±1.2

β-D-galactopyranosyl-(1→4)α-glucopyranose

90.5±0.7

Reaction Conditions: 10g waste cooking oil was used as substrate, lipase dosage 40 IU/g oil, sugars:lipase=1:1 (w/w), water content 2%, temperature 40 oC, stoichiometric amount of methanol was added 6 times in 40 h.

Mechanism investigation by MD simulation for the glucose case RMSD is the most widely used measurement for comparing protein structures39. For each simulation system with and without glucose, three independent trajectories were presented in the supplementary information (SI Figure 3 and SI Figure 4). These trajectories (RMSD of backbone atoms vs. simulation time) reached the similar plateau before 10000 ps, indicating the convergence of the simulation calculation. Moreover, The RMSD of backbone atoms, Rg of YLLIP2, RDF of solvent system and DCCM of per-residues were calculated from the average of the three trajectories in the system with and without glucose, respectively, which could provide more reliable information for protein motion in solution than single trajectory does. In


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comparison to the relatively larger fluctuation of the RMSD value in the control group, the change of RMSD value in the presence of glucose was less pronounced, indicating that glucose stabilized the structure of YLLIP2. Especially, regarding the system in absence of glucose, the trajectory of RMSD exhibited the obvious upward fluctuation at 4000 ps, which was consistent with the increment of Rg at 4000 ps (Figure 6). In contrast, the Rg values remain fairly stable, comparing to the initial conformation in the system with glucose (Figure 6). The above results meant that glucose improved the overall structure stability of YLLIP2 in methanol.

Figure 6. RMSD of backbone atoms (A) Rg (B)of YLLIP2 in 50 % (v/v) methanol-water mixture solvent system with and without glucose, starting from the initial structure vs. simulation time. To understand the molecular mechanism underlying glucose stabilizing the protein structure, the distribution of the solvent on the protein surface was calculated using RDF between the solvent molecules and the protein. As shown in Figure 7 A, the high density of water molecules is distributed around the protein from about 0.1 nm to 0.5 nm, while the distribution of methanol and glucose molecules is 0.1 nm distance away from water molecules. In contrast, Figure 7 B showed the distribution of methanol in absence of glucose. The peak of methanol from about 0.1 to 0.2 nm was higher than that of water. This indicated that many


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methanol molecules diffused into the water shell of protein, and some water molecules were expelled from the protein surface. These results were in agreement with other methanol-induced protein denaturation mechanisms, in which methanol molecules penetrated into the enzyme molecules or stripped the critical water from enzyme surface, thus resulting in solvent-swollen or unfolding of the tertiary structure34, 35. In the system with glucose, glucose molecules could form hydrogen bonds with methanol and then overcome the tendency of methanol molecule to accumulate in the critical water layer and diffuse to the protein chains. The number of hydrogen bonds of methanol-residue and residue-residue were calculated (Figure 8). The fewer number of hydrogen bonds between methanol-residue and more hydrogen presence between residue-residue with glucose demonstrated that glucose could prevent methanol molecules denaturing YLLIP2.

Figiure 7. RDF for solvent molecules around the surface of YLLIP2 in 50 % (v/v) methanolwater mixture solvent system, with (A) and without glucose (B).


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Figure 8. Average hydrogen bond number between residue-residue of YLLIP2 (A) and methanol molecule-residue of YLLIP2 (B) in 50 % (v/v) methanol-water mixture solvent system with and without glucose. In order to characterize the protection of the structure stability of YLLIP2 from glucose, four regions with obvious difference between the system both with and without glucose were pointed in the DCCM of pre-residues. The region Ⅲ and Ⅳ including the residues of the catalytic triad, and the independent stabilization of catalytic triad is important for lipase to keep its catalytic activity. As shown in Figure 9, the movement of buried residues (Glu54-Gly141, Lys20-Pro152 and Ile156-Gly240) in the regionsⅠ, Ⅲ and Ⅳ exhibited the anti-correlated to the surface regions (Lys39-Phe50, Asn261-Leu290 and Asp145-Pro152) in the presence of glucose. The result indicated that the protein internal was not disturbed by the solvent environment. However, without the protection of glucose, the movement of the core is more correlated with the movement of surface residues caused by the diffusion of the methanol (Figure 9).


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Figure 9. DCCM of per-residues of YLLIP2 in 50 % (v/v) methanol-water mixture solvent system with (A) and without glucose (B). The values in the DCCM ranged from -1 (perfectly anti-correlated) to +1 (perfectly correlated). The values along the diagonal are always +1 (because the motion of an atom is perfectly correlated to itself). The critical regions in DCCM are pointed and presented in the structural model of YLLIP2.


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With respect to the abnormal regionⅡ, both two correlated regions (Arg 99-Thr 106 and Asn 107-Gln 150) are located on the surface of the protein. Hence, the interaction between glucose and regionⅡ was analyzed, and a snapshot at 10 ns was show in Figure 10. As shown in Figure 10, the glucose molecules bound the secondary structures of the protein together through hydrogen and Van der Waals bonds, and could lead to the coupled movement between the Arg 99-Thr 106 region and the Asn 107-Gln 150 region. Emil Fischer indicated the specific interaction between enzyme and glucoside in 198440. Later, Researchers have further investigated the protein-sugar interaction. Quiocho et.al presented a review of the biochemical characteristics of carbohydrate-binding sites and identified the polar residues (Asn, Asp, Gln, Glu, Arg) as the most frequently involved residues in hydrogen bonding41.

Figure 10. Graphical representation of interaction among surface residues (Asn134 and Ala111) of YLLIP2, glucose, methanol and water molecules. Speculative hydrogen bond was pointed by black dashed. Conclusion


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The process using glucose as an additive in lipase catalyzed biodiesel synthesis was developed. This efficient and economic method provides a feasible enzymatic catalysis at an industrial scale. Moreover, the using of glucose provided a way to improve the methanol tolerance of YLLIP2. The MD simulation results showed that the glucose molecules not only self-assemble at the surface of the protein through hydrogen bond and Van der Waals attraction, but could also become a "member" of surface residues to defense the impaction of the environment on the structure of proteins. The present work is a successful example of combining experiments and MD simulations in order to explain and understand the protection mechanism of additives in the enzymatic process. In future work, an integrated semi-rational strategy with MD simulation could be developed to predict and guide the application of additives to improve the enzymatic reactions. ASSOCIATED CONTENT Supporting Information. Experimental setup of response surface (SI Table 1), Experimental data of response surface (SI Table 2), Analysis of variance (ANOVA) (SI Table 3), Optical rotation of

D-glucose

in

methanol-water solution(SI Table 4), Fuel properties of the biodiesel product Secondary (SI Table 5), structure measurement (SI Figure 1.), Predicted fatty acid methyl ester content versus experimental fatty acid methyl ester content (SI Figure 2.), RMSD values (SI Figure 3.) and Rg values (SI Figure 4.) (.docx)

AUTHOR INFORMATION Corresponding Author


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* Corresponding author: Kaili Nie Tel: +86 18611510432 Email: [email protected] Beijing Bioprocess Key Laboratory, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China Meng Wang Tel: +86 159011005745 Email: [email protected] Beijing Bioprocess Key Laboratory, College of Life Science and Technology, Beijing University of Chemical Technology, Beijing, 100029, PR China

Notes The authors declare no competing financial interest. Acknowledgements This work was supported by the National 973 Basic Research Program of China (2014CB745100), National Natural Science Foundation of China (21406011, 21676016).


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Table of Contents


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Sugar-Improved Enzymatic Synthesis of Biodiesel with Yarrowia

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