Process Evaluation and Kinetics of Recombinant Chitin Deacetylase Expression in E. coli Rosetta pLysS Cells Using a Statistical Technique

Summary

In the current protocol, a statistical technique, central composite design (CCD), was applied to optimize the process conditions for the expression of recombinant bacterial chitin deacetylase (BaCDA) in E. coli Rosetta pLysS cells. The employment of CCD resulted in a ~2.39-fold increase in the expression and activity of BaCDA.

Abstract

In recent years, the greener route of the deacetylation of chitin to chitosan using the enzyme chitin deacetylase has gained importance. Enzymatically converted chitosan with emulating characteristics has a broad range of applications, particularly in the biomedical field. Several recombinant chitin deacetylases from various environmental sources have been reported, but there are no studies on process optimization for the production of these recombinant chitin deacetylases. The present study used the central composite design of response surface methodology to maximize the recombinant bacterial chitin deacetylase (BaCDA) production in E. coli Rosetta pLysS. The optimized process conditions were 0.061% glucose concentration, 1% lactose concentration, an incubation temperature of 22 °C, an agitation speed at 128 rpm, and 30 h of fermentation. At optimized conditions, the expression due to lactose induction was initiated after 16 h of fermentation. The maximum expression, biomass, and BaCDA activity were recorded 14 h post-induction. At the optimized condition, the BaCDA activity of expressed BaCDA was increased ~2.39-fold. The process optimization reduced the total fermentation cycle by 22 h and expression time by 10 h post-induction. This is the first study to report the process optimization of recombinant chitin deacetylase expression using a central composite design and its kinetic profiling. Adapting these optimal growth conditions could result in cost-effective, large-scale production of the lesser-explored moneran deacetylase, embarking on a greener route for biomedical-grade chitosan production.

Introduction

Chitin, a structural β, 1-4 glycosidic linked natural polymer, is the second-most abundant polysaccharide in nature after cellulose. Despite this fact, chitin has limited industrial applications due to its insolubility¹. This bottleneck is addressed by subjecting chitin to N-deacetylation, which imparts a positive charge and increases the solubility of the resulting polymer, chitosan¹. Chitin can be modified to chitosan through two different routes: chemical and enzymatic. The biomedical application of chitosan requires controlled and defined deacetylation, which is restricted in chemical routes^2,3. This limitation can be addressed using chitin deacetylases (CDAs), a green enzymatic approach for the deacetylation process^4,5.

Chitin deacetylase belongs to the carbohydrate esterase 4 (CE-4) family, defined in the carbohydrate-active enzymes (CAZY) database. The enzymes of the CE-4 family share the NodB homology or polysaccharide deacetylase domain as the conserved region. The central composite design (CCD), a statistical tool, is used for the optimization of several wild-type chitin-modifying enzymes^6,7,8,9. However, the downstream steps in the usage of wild-type organisms becomes tedious, hence the shift toward recombinant enzymes^{10,11,12,13,14,15,16,17}. In recent years, halophilic recombinant CDA from marine sources have gained importance due to their ease in the industrial application and production of biomedical-grade chitosan^18,19.

Recombinant enzyme production in E. coli has a limitation on the process, and media optimization is needed as its expression in E. coli varies depending on the gene and plasmid used²⁰. Thus, screening of a suitable process and nutrient parameters becomes important. One factor at a time (OFAT), the commonly employed optimization method, requires tremendous resources and time to perform step-by-step experiments. This method suffers from a lack of statistical information regarding the interaction among the parameters^20,21,22,23. Therefore, the CCD of response surface methodology (RSM) was adopted to study the halophilic bacterial chitin deacetylase (BaCDA) expression yield and BaCDA activity in E. coli Rosetta pLysS. The parameters considered for expression optimization in the E. coli host were lactose concentration, glucose concentration, incubation temperature, agitation rate, and incubation time. In most E. coli expression studies, Luria Bertani (LB) media with Isopropyl β-d-1-thiogalactopyranoside (IPTG) was used as an inducer. This addition of IPTG required regular growth monitoring²⁴. These recurrent mediations during the fermentative process also open avenues for contamination. Hence, research groups have shifted to terrific broth (TB) with lactose as the inducer. The inclusion of lactose in the media instead of IPTG addresses this concern; E. coli consumes this lactose and produces allo-lactose as a by-product, resulting in an auto-induction condition. This auto-inducer media includes glycerol, which has exhibited improved yields of recombinant protein²⁵.  This overexpression of recombinant proteins in TB media was further improved by optimizing the process parameters. In the present study, a central composite design was applied to optimize the heterologous expression of halophilic BaCDA in E. coli Rosetta pLysS cells. The process parameters chosen were incubation temperature, agitation rate, and incubation time, and the nutrient parameters evaluated were glucose and lactose concentration. The halophilic BaCDA expression was evaluated with the predicted optimized condition and cross-validated using SDS-PAGE.

Protocol

1. Expression media and culture condition

1. Transform the pET-22b vector containing the BaCDA gene into E. coli Rosetta pLysS competent cells using the heat-shock method, as described in¹⁵.
   NOTE: Care has to be taken while working with microorganisms. All microbiological work has to be performed inside a biosafety cabinet hood to avoid contamination.
2. Perform the preliminary expression study in TB media containing 0.05% (w/v) glucose and 0.2% (w/v) lactose at 16 °C and 180 rpm. Grow 6.792 x 10⁷ E. coli Rosetta pLysS cells in 100 mL of media containing BaCDA cloned plasmid till it reaches the stationary phase. At the mentioned growth conditions, the E. coli Rosetta pLysS cells reach an optical density 600 (OD₆₀₀) of 10.85 ± 0.21.
   NOTE: Composition of the TB media (% w/v): tryptone, 1.2; yeast extract, 2.4; glycerol, 0.6; and 1x TB salt (17 mM KH₂PO₄ and 74 mM K₂HPO₄)¹⁷.

2. Optimization and experimental design

1. Design the experiments and fit the second-order polynomial model in central composite design using the statistical tool software. The statistical software used in the present study was MINITAB 17.0 (trial version).
   1. To do this, open the software and click on the following buttons: Stat > DoE > Response surface > Create response surface > Response design > Central composite. The output appears as a dialogue box.
2. Feed the five parameters, incubation temperature, agitation rate, incubation time, glucose concentration, and lactose concentration, at five levels (-2, -1, 0, +1, +2) in the dialogue box.
   1. To do this, enter the parameters with the levels in the dialogue box, enter the details of all the parameters, and press OK. This generates the experimental design matrix with six replicates at the center point, requiring 32 experimental runs. The software generates a table containing the parameters and their levels in coded and uncoded terms, used in the process optimization using CCD (Table 1).
3. Perform the 32 experiments with the software-generated conditions. Feed the experimental results into the experimental design matrix (generated by the software) containing levels and parameters in terms of coded and uncoded units (Table 2).
4. Analyze the experimental design matrix (Table 2) using the software. To do this, open the software and feed the response into the datasheet. Select Response column > Stat > DoE > Response surface > Analyze response surface design > OK. The output is analyzed for statistical significance, and a model is predicted by the software.

Table 1: The parameters and their levels in coded and uncoded terms used in the experimental design to estimate the expression of recombinant chitin deacetylase in E. coli Rosetta pLysS cells. Please click here to download this Table.

Table 2: Experimental design matrix with experimental and predicted BaCDA activity (expression) of recombinant chitin deacetylase in E. coli Rosetta pLysS cells. Please click here to download this Table.

3. Validation of model

1. Validate the designed model using the response optimizer tool available in the software.
2. Repeat the fermentation at software-predicted optimum conditions and compare the experimental value with the software-predicted value.
   1. To do this, open the software and select Response column > Stat > DoE > Response surface > Response optimizer > Maximize > OK. The output is optimum process conditions and values predicted by the software. Repeat the fermentation at predicted optimum conditions and compare the values.

4. Analytical methods

1. Expression, biomass, and protein quantification
   1. Perform the fermentation in 32 conditions given by the software in the experimental design matrix (Table 2). Obtain the pellet after each run by centrifuging the culture at 5,405 x g for 10 min at 4 °C. Weigh the cell pellet to determine the biomass yield.
      NOTE: All microbial handling should be done in aseptic conditions (i.e., inside biosafety cabinets).
   2. Lyse the cell pellet to obtain periplasmic protein by sonication. Add 5 mL of lysis buffer (50 mM Tris-HCl, 300 mM NaCl, 10 mM Imidazole) to each gram of cell pellet and disrupt by sonicating for 10 cycles with a pulse of 10 s on and 10 s off at 60% amplitude. Collect the lysate by centrifuging at 5,405 x g for 10 min at 4 °C. Quantify the protein concentration by Bradford's assay²⁶.
      NOTE: To avoid protein denaturation, sonication has to be done under cold conditions. Place the samples on ice while performing sonication.
   3. Analyze the BaCDA expression using SDS-PAGE followed by ImageJ software. Load 10 µL of soluble cell lysate (periplasmic protein) on 12% bis-acrylamide gel and run under 1x tris-glycine-SDS (TGS) buffer at a 100 V current for 2 h. After the run is completed, stain the gel with Coomassie blue and destain to remove the background²⁷.
   4. Capture an image using a gel documentation unit. Determine the BaCDA expression by comparing the band intensity in the form of the pixel values using ImageJ software. Consider the experimental run with the lowest BaCDA activity and biomass as the reference pixel ²⁸.
      1. To do this, open the software and open the image file, then select each lane using the rectangular box. Go to Analyze and set each lane as 100%, then select the overexpressed band in each lane using the rectangular box. Go to Analyze and determine the intensity of the band, repeat the process in each lane, and export the result as .xls file. Consider the band intensity of the experimental run with the lowest BaCDA activity as the reference intensity and analyze the expression of each lane.
2. Enzyme activity assay
   1. Determine the BaCDA activity using an acetate assay kit¹⁵, using ethylene glycol chitin (1 mg/mL; EGC) as the substrate²⁹.
   2. Allow 20 µL of BaCDA to react with 40 µL of the substrate in the presence of 40 µL of 50 mM Tris-HCl (pH 7) buffer for 1 h at 30 °C by agitating at 800 rpm.
   3. After 1 h, centrifuge the 100 µL reactant through a 3 kDa column at 2,111 x g for 15 min at 4 °C. Discard the retentate comprising of BaCDA and collect the filtrate containing acetate released during the reaction. Use the filtrate for the acetate assay to determine the BaCDA activity.
      ​NOTE: One unit of the enzyme is defined as the activity which releases 1 µM of acetate from the substrate per microliter of enzyme per minute. The enzyme activity assay was carried out in triplicates, and the respective enzyme activity was calculated accordingly.
3. Fermentation kinetics of lactose induction
   1. Investigate the activity profile to determine the point of lactose induction and expression start point. The activity profiling is made by estimating biomass and BaCDA activity with the optimized fermentation conditions.
   2. Determine the glucose concentration in the media using a glucose estimation kit. Plot the activity profile using biomass, glucose concentration, and BaCDA activity against the fermentation time.

Results

Process optimization of expression of periplasmic recombinant enzyme chitin deacetylase in E. coli using central composite design (CCD)
The pET22b-BaCDA construct, when grown in unoptimized conditions, gave a maximum biomass yield and BaCDA activity of 22.26 ± 0.98 g/L and 84.67 ± 0.56 U/L, respectively¹⁵. In the current study, a statistical approach CCD was adopted to find the optimal process conditions for expressing periplasmic recombinant enzyme ...

Discussion

Deacetylated chitin, chitosan, has many applications, especially in the biomedical field³⁰. However, the reproducibility of chitosan concerning its degree of acetylation (DA) and pattern of acetylation (PA) is a major concern in addition to other environmental apprehensions. The greener route, using enzymes, has thus been exploited. The array of CDAs can be employed to create chitosan with a unique pattern of deacetylation, which would increase their biomedical applications⁴

Materials

List of materials used in this article

Name	Company	Catalog Number	Comments
Kits
Acetate assay kit	Megazyme, Ireland	K-ACETAK	The protocol has been slightly modified and optimized to perform the assay in 96 well plate
Glucose estimation kit	Agappe diagnosis Ltd., India	12018013	The protocol has been slightly modified and optimized to perform the assay in 96 well plate
Chemicals
Acetic acid	Hi-media, India	AS001	Used for preparing SDS-PAGE staining and destaing solution
Acrylamide	Hi-media, India	MB068	Used for preparing SDS-PAGE gel
Ammonium pursulphate	Hi-media, India	MB003	Used for preparing SDS-PAGE gel
Bis-acrylamide	Hi-media, India	MB005	Used for preparing SDS-PAGE gel
Coomassie briliiant blue G-250	Hi-media, India	MB092	Used for preparing SDS-PAGE staining and destaing solution
Coomassie briliiant blue R-250	Hi-media, India	MB153	Used for preparing Bardford's assay
Ethylene glycol chitosan	Sigma-aldrich, USA	E1502	Used to prepare Ethylene glycol chitin and Ethylene glycol chitin was used as substrate for enzymatic reaction
D-glucose	Hi-media, India	MB037	Used as an media component.
Imidazole	Hi-media, India	GRM1864	Used in lysis buffer
Lactose	Hi-media, India	GRM017	Used as an media component.
Methanol	Finar, India	30930LC250	Used for preparing SDS-PAGE staining and destaing solution
Sodium chloride (NaCl)	Hi-media, India	MB023	Used in lysis buffer
Phosphoric acid	Hi-media, India	MB157	Used for preparing Bardford's assay
sodium dodecyl sulfate (SDS)	Hi-media, India	GRM6218	Used for preparing SDS-PAGE gel
Sodium phosphate dibasic anhydrous	Hi-media, India	MB024	Used to prepare TB sald for media and buffer for enzymatic reaction.
Sodium phosphate monobasic anhydrous	Hi-media, India	GRM3964	Used to prepare TB sald for media and buffer for enzymatic reaction.
Tetramethylethylenediamine (TEMED)	Hi-media, India	MB026	Used for preparing SDS-PAGE gel
Tris base	Hi-media, India	MB029	Used for preparing SDS-PAGE gel
Tryptone	Hi-media, India	RM7707	Used as an media component.
Yeast extract	Hi-media, India	RM027	Used as an media component.
Equipment
AlphaImager HP gel documentation unit	ProteinSimple, USA	92-13823-00	Used to capture SDS-PAGE photographs
Benchtop mixer	Eppendorf, Germany	9.776 660	Used to keep for enzymatic reaction with 2 mL adaptor
Bioincubator shaker	Trishul instruments, India	13410622	Used to incubate bacterial culture at different temparature and RPM
Biospectrophotometer	Eppendorf, Germany	6135000009	Used to take all spectroscopic readings
Cooling centrifuge	Eppendorf, Germany	5805000017	Used to centrifuge culture, lysate and all other centrifuging protocols
Dry bath	Labnet International, USA	S81522039	Used to denature protein sample for SDS-PAGE
Micropipettes	Eppendorf, Germany	3123000900	Used throghout the protocol for volume measurements
Rocker shaker	Trishul instruments, India	11770719	Used to shake SDS-PAGE gel for staining and destaining
SDS-PAGE unit	Bio-Rad, USA	1658001FC	Used to cast and run SDS-PAGE gel
Ultra sonicator	Sonics & Materials, Inc., USA	VCX 130	Used to lyse the bacterial cell by ultra sonication
Weighing balance	Sartorius, Germany	BSA124 S	Used to measure weight throughout the protocol
Devices
Nanosep Centrifugal Devices with Omega Membrane (3 kDa)	PALL life sciences, USA	OD003C33	Used to separate enzyme after substrate treatment
Softwares	Version	Developed at
MINITAB	17.0  (Trial version)	The Pennsylvania State University	Used to design the experimental model and analyse the data
ImageJ	1.53o	National Institutes of Health (NIH)	Used to analyse the expression level using SDS-PAGE image
Plasmid
pET22b (+) DNA—Novagen	Merck- Millipore, USA	69744	Stored at − 20 °C
Cells
E. coli Rosetta pLysS—Novagen	Merck- Millipore, USA	70956	Maintained in Luria–Bertani (LB) broth containing 25% glycerol at − 80 °C