Michaelis–Menten Kinetics of Thermostable α-Amylase-Catalysed Starch Hydrolysis from Chlorella vulgaris Biomass for Bioethanol Production

Author

A.M. Danjuma., Umar J.I., A. Abubakar , Wakkala A.


Abstract

 Microalgal biomass is a highly promising non-food feedstock for third generation bioethanol production thanks to its higher carbohydrate content and lack of lignin. This research aimed to study the substrate utilization kinetics of pretreated Chlorella vulgaris starch during thermostable α-amylase depolymerization process and its subsequent ethanol fermentation process by Saccharomyces cerevisiae. Batch kinetic assays were performed over the range of 10-1000 mg/L of the substrates and the initial volumetric hydrolysis rates (ν) were calculated from the early linear release of reducing sugars (t ≤ 15 min) and related to the biocatalyst loading (X = 0.5 g/L) to get biomass-specific hydrolysis rates (qₛ). The theoretical maximum initial rate (Vₘₐₓ) and apparent Michaelis constant (Kₘ) were obtained using non-linear least-squares (NLLS) regression based on classical Michaelis–Menten kinetics, and were 86.56 ± 1.03 mg/L/h and 130.54 ± 4.89 mg/L, respectively, with a catalytic efficiency index (Vₘₐₓ/Kₘ) of 0.663 h⁻¹. At low substrate concentration (10-40 mg/L), the system exhibited an approximately first-order behaviour, with volumetric rates (ν) of 6.0-21.6 mg/L/h and specific utilization rates (qₛ) of 12.0-36.0 mg/g/h. The reaction gradually became saturated after 120 mg/L and the specific utilization rate reached 58.4 mg/g/h and the volumetric rate reached 40.9 mg/L/h. The reaction at high substrate concentration levels (600–1000 mg/L) was fairly close to zero-order reaction saturation kinetics with a maximum observed volumetric rate of 76.0 mg/L/h, which is 87.8% of the calculated Vₘₐₓ and an asymptotic maximum specific utilization rate (qₘₐₓ) of 80.0 mg/g/h. The model diagnostic results showed good agreement with the experimental data (R² = 0.999; RMSE = 0.845 mg/L/h), with residuals between −1.27 and +1.30 mg/L/h. The results indicate a high apparent amylolytic affinity for C. vulgaris glucans and no evidence of substrate inhibition in the range of glucans concentrations tested. 


Keywords

Chlorella vulgaris; bioethanol production; Michaelis–Menten kinetics; substrate utilization; specific utilization rate (qₛ).



Full Text:

Download Paper PDF


References


  1. Agu, K. C., & Oduola, M. K. (2021). Kinetic modeling of ethanol production by batch fermentation of sugarcane juice using immobilized yeast. Global Journal of Engineering and Technology Advances, 7(1), 124–136. https://doi.org/10.30574/gjeta.2021.7.1.0060
  2. Chen, H., Wang, J., & Zhou, Y. (2023). Diffusional limitations and first-order kinetic regimes in low-concentration starch depolymerization using amylolytic biocatalysts. International Journal of Biological Macromolecules, 242, Article 124892.
  3. CCAP (Culture Collection of Algae and Protozoa). (2020). BG11 (Blue-Green Medium), freshwater algae and protozoa (Media Preparation Recipe MR BG11, QF 09, Revision 001) [Protocol]. Scottish Marine Institute. https://www.ccap.ac.uk/wp-content/uploads/MR_BG11.pdf
  4. Choi, S. P., Nguyen, M. T., & Sim, S. J. (2010). Enzymatic pretreatment of Chlamydomonas reinhardtii biomass for ethanol production. Bioresource Technology, 101(14), 5330–5336. https://doi.org/10.1016/j.biortech.2010.02.026
  5. de Carvalho Silvello, M. A., Gasparotto, G. A., & Goldbeck, R. (2023). Enzymatic hydrolysis of carbohydrate-rich Chlorella vulgaris for third-generation bioethanol production by cellulase-recombinant yeast. Cleaner Chemical Engineering, 6, Article 100111. https://doi.org/10.1016/j.clce.2023.100111
  6. Chong, J. W. R., Khoo, K. S., Chew, K. W., Vo, D. V. N., & Show, P. L. (2022). Microalgae-based biorefinery for green biofuel production: A review on downstream processing and economic viability. Fuel, 330, Article 125633.
  7. Coronado-Reyes, J. A., Acosta-Ramírez, E., Martínez-Olguín, M. V., & González-Hernández, J. C. (2022). Antioxidant activity and kinetic characterization of Chlorella vulgaris growth under flask-level photoheterotrophic growth conditions. Molecules, 27(19), Article 6346. https://doi.org/10.3390/molecules27196346
  8. de Souza, P. M., & de Oliveira e Silva, P. P. (2010). Application of microbial α-amylase in industry—A review. Brazilian Journal of Microbiology, 41(4), 850–861. https://doi.org/10.1590/S1517-83822010000400004
  9. Dowd, J. E., & Riggs, D. S. (1965). A comparison of estimates of Michaelis-Menten kinetic constants from various linear transformations. Journal of Biological Chemistry, 240(2), 863–869. https://doi.org/10.1016/S0021-9258(17)45254-9
  10. de Carvalho Silvello, M. A., Gonçalves, I. S., Azambuja, S. P. H., Costa, S. S., Silva, P. G. P., Santos, L. O., & Goldbeck, R. (2022). Microalgae-based carbohydrates: A green innovative source of bioenergy. Bioresource Technology, 344, Article 126304. https://doi.org/10.1016/j.biortech.2021.126304
  11. Ho, S. H., Huang, S. W., Chen, C. Y., & Chang, J. S. (2021). Perspectives on microalgal carbohydrate production and conversion to biofuels. Current Opinion in Biotechnology, 67, 102–110.
  12. Kasap, I., Kut Yılmaz, A., Dönmez, G., & Karatay, S. E. (2026). Improvement of third generation bioethanol production from photoheterotrophically cultivated Chlorella vulgaris in the presence of carrot pomace and onion peel waste. Preparative Biochemistry & Biotechnology, 56(3), 442–451. https://doi.org/10.1080/10826068.2025.2543285
  13. Ho, S. H., Huang, S. W., Chen, C. Y., Hasunuma, T., Kondo, A., & Chang, J. S. (2013). Characterization and optimization of carbohydrate production from an indigenous microalga Chlorella vulgaris FSP-E. Bioresource Technology, 135, 157–165. https://doi.org/10.1016/j.biortech.2012.10.100
  14. Kumar, S., Shelly, M., & Mohan, S. V. (2020). Microalgae-mediated bioethanol production: Mechanistic insights, biorefinery concepts, and scalable engineering strategies. Bioresource Technology, 312, Article 123618.
  15. Khan, M. I., Shin, J. H., & Kim, J. D. (2023). Advances in microalgal biomass pretreatment and enzymatic hydrolysis for enhanced biofuel yield. Energy Conversion and Management, 277, Article 116642.
  16. Li, X., Zhang, R., & Liu, Y. (2021). Substrate utilization profiling and saturation kinetics during enzymatic saccharification of third-generation biomass. Bioresource Technology, 337, Article 125430.
  17. Melendez, J. R., Lowy, D. A., Hena, S., & Gutierrez, L. (2026). Advances in third-generation bioethanol production, industrial infrastructure and efficient technologies in sustainable processes with algae biomass: Systematic review. Fermentation, 12(1), Article 2. https://doi.org/10.3390/fermentation12010002
  18. Krishna Samal, D. P., & Sukla, L. B. (2025). Unveiling the dual potential of microalgae and seaweed biomass for sustainable biofuel production: A review. RSC Advances, 15(41), 34160–34175. https://doi.org/10.1039/D5RA04845A
  19. McCleary, B. V., Gibson, T. S., & Mugford, D. C. (1997). Measurement of total starch in cereal products by amyloglucosidase-alpha-amylase method: Collaborative study. Journal of AOAC International, 80(3), 571–579. https://doi.org/10.1093/jaoac/80.3.571
  20. Miller, G. L. (1959). Use of dinitrosalicylic acid reagent for determination of reducing sugar. Analytical Chemistry, 31(3), 426–428. https://doi.org/10.1021/ac60147a030
  21. Michaelis, L., & Menten, M. L. (1913). Die Kinetik der Invertinwirkung. Biochemische Zeitschrift, 49, 333–369.
  22. Motulsky, H., & Christopoulos, A. (2004). Fitting models to biological data using linear and nonlinear regression: A practical guide to curve fitting. Oxford University Press.
  23. Ojo, A. E., Okon, P. E., & Ibrahim, M. (2022). Kinetic transitions in multi-phase enzymatic hydrolysis: Transition from diffusion-controlled to enzyme-limiting regimes. Biochemical Engineering Journal, 187, Article 108620.
  24. Saratale, R. G., Shin, H. S., Kumar, G., & Saratale, G. D. (2022). Exploiting microalgal carbohydrates for biofuel and value-added biochemical production within circular bioeconomy framework. Renewable and Sustainable Energy Reviews, 168, Article 112836.
  25. Sharma, S., Garg, R., & Patel, V. (2023). Comparative kinetic modeling of amylase-catalyzed hydrolysis of conventional versus alternative starches for renewable ethanol. Biochemical Engineering Journal, 194, Article 108879.
  26. Wang, Z., Sun, L., & Zhao, M. (2024). Eliminating substrate inhibition thresholds during concentrated starch liquefaction using thermostable α-amylase formulations. Carbohydrate Polymers, 324, Article 121510.
  27. Zabed, H. M., Akor, C. A., Suely, A., Qi, X., & Xiang, W. (2020). A comprehensive review on bioethanol production from microalgal biomass: From culture systems to advanced fermentation strategies. Biomass and Bioenergy, 142, Article 105781.

 

Share your valuable work from Social Media Buttons