Enzymatic Hydrolysis Optimization for Preparation of Sea Cucumber (Holothuria scabra) Hydrolysate with an Antiproliferative Effect on the HepG2 Liver Cancer Cell Line and Antioxidant Properties
Abstract
:1. Introduction
2. Results and Discussion
2.1. Chemical Composition of Sea Cucumber
2.2. Optimization of Sea Cucumber Hydrolysis Conditions
Response Surface Model Generation
2.3. Response Surface Plots
2.4. Optimization of Multiple Responses and Model Validation
2.5. The Effect of the Sea Cucumber Hydrolysate Concentration on Anticancer Activity
3. Materials and Methods
3.1. Raw Materials and Preparations
3.2. Chemicals and Enzymes
3.3. Enzymatic Hydrolysis of Sea Cucumber
3.4. Analyses
3.4.1. Chemical Composition of Sea Cucumber
3.4.2. Yield
3.4.3. Degree of Hydrolysis (DH)
3.4.4. DPPH Radical Scavenging Activity
3.4.5. ABTS Radical Scavenging Activity
3.4.6. Hydrogen Peroxide (H2O2) Scavenging Activity
3.4.7. Hydroxyl Radical Scavenging Activity
3.4.8. Antiproliferative Activity in the HepG2 Liver Cancer Cell Line
3.5. The Effect of the Sea Cucumber Hydrolysate Concentration on the Antiproliferative Activity of the HepG2 Liver Cancer Cell Line
3.6. Experimental Design and Statistical Analysis
4. Conclusions
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Samples | Moisture (%) | Protein (%) | Fat (%) | Ash (%) |
---|---|---|---|---|
Dried sea cucumber | 17.22 ± 0.47 | 65.75 ± 0.78 | 1.41 ± 0.08 | 13.98 ± 0.03 |
Sea cucumber Slurry | 82.69 ± 0.10 | 12.40 ± 1.3 | 1.24 ± 0.10 | 2.03 ± 0.09 |
Experimental Units | Factors | Responses | |||||||
---|---|---|---|---|---|---|---|---|---|
X1 | X2 | Yield (%) | DH (%) | DPPH (%) | ABTS (%) | H2O2 (%) | OH· (%) | Cell Viability (%) | |
(min) | (%) | ||||||||
1 | 60 | 1 | 6.69 a ± 1.06 | 79.6 a ± 0.44 | 89.5 bcd ± 0.84 | 66.6 bcde ± 3.14 | 21.3 ab ± 1.53 | 78.1 bc ± 3.77 | 5.14 d ± 0.55 |
2 | 360 | 1 | 10.9 bc ± 1.98 | 81.1 ab ± 1.74 | 82.5 abc ± 1.12 | 59.9 a ± 0.74 | 38.8 d ± 0.71 | 82.5 c ± 1.66 | 3.06 b ± 0.42 |
3 | 60 | 5 | 11.7 cd ± 0.23 | 79.8 a ± 0.34 | 79.8 a ± 1.97 | 63.9 abc ± 1.20 | 27.0 c ± 2.68 | 82.5 c ± 2.33 | 4.93 d ± 0.46 |
4 | 360 | 5 | 12.8 e ± 0.04 | 85.2 bc ± 0.95 | 91.7 cd ± 1.68 | 69.2 e ± 2.54 | 41.7 d ± 2.96 | 84.6 bc ± 4.01 | 3.77 bc ± 0.49 |
5 | 60 | 3 | 9.96 b ± 0.31 | 80.6 bc ± 1.99 | 85.3 ab ± 1.12 | 66.1 abcd ± 1.94 | 25.6 c ± 0.73 | 80.1 bc ± 1.39 | 4.81 cd ± 0.45 |
6 | 360 | 3 | 12.7 e ± 0.03 | 84.7 c ± 2.17 | 88.1 bcd ± 3.25 | 64.3 cde ± 0.85 | 38.9 d ± 0.85 | 83.0 bc ± 1.90 | 2.61 a ± 0.42 |
7 | 210 | 1 | 9.59 b ± 0.35 | 83.1 bc ± 0.97 | 87.2 bcd ± 3.08 | 61.6 ab ± 2.55 | 18.7 a ± 14.84 | 76.2 b ± 3.15 | 3.98 cd ± 0.62 |
8 | 210 | 5 | 12.4 de ± 0.23 | 84.5 bc ± 2.16 | 88.4 bcd ± 1.68 | 69.3 de ± 0.92 | 28.8 c ± 1.06 | 83.4 bc ± 0.92 | 4.01 bc ± 0.85 |
9 | 210 | 3 | 12.3 de ± 0.13 | 83.3 bc ± 3.81 | 91.7 d ± 0.56 | 67.6 de ± 0.10 | 25.8 c ± 1.40 | 73.0 a ± 7.59 | 4.77 cd ± 0.16 |
10 | 210 | 3 | 11.1 bc ± 0.78 | 85.1 bc ± 0.93 | 87.5 bcd ± 1.40 | 66.7 bcde ± 1.57 | 25.6 bc ± 1.92 | 76.7 bc ± 4.55 | 3.98 bc ± 0.53 |
11 | 210 | 3 | 12.3 de ± 2.29 | 82.8 ab ± 1.80 | 88.9 bcd ± 0.69 | 66.7 bcde ± 2.12 | 27.0 c ± 1.92 | 76.0 b ± 3.98 | 4.20 bc ± 0.24 |
Responses | Quadratic Polynomial Model | R2 | p-Value for Models | p-Value for Lack of Fit |
---|---|---|---|---|
Yield (%) | Y1 = 11.9 + 1.35X1 + 1.59X2 − −0.79X1X2 − 0.52X12 − 0.86X22 | 0.9643 | 0.0013 | 0.9654 |
DH (%) | Y2 = 84.0 + 1.84X1 + 0.96X2 + 0.97X1X2 − 1.76X12 − 0.61X22 | 0.9023 | 0.0146 | 0.8619 |
DPPH (%) | Y3 = 89.2 + 1.29X1 − 0.10X2 + 4.72X1X2 − 2.26X12 − 1.20X22 | 0.9225 | 0.0083 | 0.9633 |
ABTS (%) | Y4 = 66.8 − 0.54X1 + 2.38X2 + 2.99X1X2 − 1.17X12 − 0.88X22 | 0.9023 | 0.0145 | 0.1068 |
H2O2 (%) | Y5 = 25.6 − 7.58X1 + 3.13X2 − 0.70X1X2 + 7.33X12 − 1.14X22 | 0.9661 | 0.0011 | 0.0925 |
OH· (%) | Y6 = 76.2 + 1.56X1X + 0.28X2 − 0.59X1X2 + 4.10X12 + 2.34X22 | 0.8354 | 0.0495 | 0.5691 |
Cell viability (%) | Y7 = 4.14 − 0.91X1 − 0.09X2 + 0.23X1X2 − 0.17X12 + 0.12X22 | 0.8525 | 0.0384 | 0.4981 |
Responses | Code | Intercept | X1 | p-Value | X2 | p-Value | X1X2 | p-Value |
---|---|---|---|---|---|---|---|---|
Yield (%) | Y1 | 11.872 | 1.346 | 0.001 | 1.594 | 0.001 | −0.789 | 0.023 |
DH (%) | Y2 | 83.997 | 1.841 | 0.005 | 0.957 | 0.055 | 0.971 | 0.093 |
DPPH scavenging activity (%) | Y3 | 89.188 | 1.291 | 0.077 | 0.099 | 0.871 | 4.715 | 0.001 |
ABTS scavenging activity (%) | Y4 | 66.728 | −0.539 | 0.359 | 2.384 | 0.007 | 2.994 | 0.006 |
H2O2 scavenging activity (%) | Y5 | 25.636 | 7.584 | 0.0001 | 3.125 | 0.011 | −0.697 | 0.507 |
OH· scavenging activity (%) | Y6 | 76.137 | 1.557 | 0.043 | 2.278 | 0.050 | −0.593 | 0.612 |
Cell viability (%) | Y7 | 4.142 | −0.906 | 0.004 | 0.091 | 0.625 | 0.228 | 0.335 |
Response | Parameters | Predicated Value | Real Value | Composite Desirability | ||||
---|---|---|---|---|---|---|---|---|
Goal | Lower | Upper | Weight | Importance | ||||
X1 | is in range | 60 | 360 | 1 | 3 | 360 | 360 | 0.92 |
X2 | is in range | 1 | 5 | 1 | 3 | 4.3 | 4.3 | |
Yield (%) | maximize | 6.69 | 12.75 | 1 | 3 | 12.87 | 12.10 ± 0.54 | |
DH (%) | maximize | 79.58 | 85.22 | 1 | 3 | 85.07 | 74.52 ± 1.06 | |
DPPH (%) | maximize | 79.75 | 91.66 | 1 | 3 | 90.83 | 89.74 ± 1.51 | |
ABTS (%) | maximize | 59.88 | 69.33 | 1 | 3 | 68.12 | 74.92 ± 0.81 | |
H2O2 (%) | maximize | 18.66 | 41.7 | 1 | 3 | 41.64 | 39.42 ± 1.74 | |
OH· (%) | maximize | 73.03 | 84.56 | 1 | 3 | 84.3 | 88.71 ± 1.49 | |
Cell viability (%) | minimize | 2.61 | 5.14 | 1 | 3 | 3.32 | 9.89 ± 1.37 |
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Saiwong, S.; Autsavapromporn, N.; Siriwoharn, T.; Techapun, C.; Wangtueai, S. Enzymatic Hydrolysis Optimization for Preparation of Sea Cucumber (Holothuria scabra) Hydrolysate with an Antiproliferative Effect on the HepG2 Liver Cancer Cell Line and Antioxidant Properties. Int. J. Mol. Sci. 2023, 24, 9491. https://doi.org/10.3390/ijms24119491
Saiwong S, Autsavapromporn N, Siriwoharn T, Techapun C, Wangtueai S. Enzymatic Hydrolysis Optimization for Preparation of Sea Cucumber (Holothuria scabra) Hydrolysate with an Antiproliferative Effect on the HepG2 Liver Cancer Cell Line and Antioxidant Properties. International Journal of Molecular Sciences. 2023; 24(11):9491. https://doi.org/10.3390/ijms24119491
Chicago/Turabian StyleSaiwong, Supansa, Narongchai Autsavapromporn, Thanyaporn Siriwoharn, Charin Techapun, and Sutee Wangtueai. 2023. "Enzymatic Hydrolysis Optimization for Preparation of Sea Cucumber (Holothuria scabra) Hydrolysate with an Antiproliferative Effect on the HepG2 Liver Cancer Cell Line and Antioxidant Properties" International Journal of Molecular Sciences 24, no. 11: 9491. https://doi.org/10.3390/ijms24119491
APA StyleSaiwong, S., Autsavapromporn, N., Siriwoharn, T., Techapun, C., & Wangtueai, S. (2023). Enzymatic Hydrolysis Optimization for Preparation of Sea Cucumber (Holothuria scabra) Hydrolysate with an Antiproliferative Effect on the HepG2 Liver Cancer Cell Line and Antioxidant Properties. International Journal of Molecular Sciences, 24(11), 9491. https://doi.org/10.3390/ijms24119491