Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
There is being presented simulation of increasing membrane permeability cellular baker’s yeast for the set values concentrations of alcohol solutions. It allows for easy activity forecasting intracellular catalase. Due to the costs associated with disposal large volumes of waste and the purchase of permeabilizing agents the tolerance of the permeabilization process to changes in alcohols concentration was checked. For this purpose, appropriate mathematical models were used. The obtained results confirm the high sensitivity of the process to changes in concentration permeabilizing factor. Of the three permeabilizations studied, this is the process using ethanol turned out to be the least tolerant to change concentration of the permeabilizing factor. The concentration of the solution of this alcohol, which will be used in permeabilization to obtain cells yeast with catalase activity half of the optimal activity, is only 20% lower than the optimal concentration. Processes permeabilization using the other two alcohols considered less sensitive to changes in their concentration. The concentrations of 1-propanol and 2-propanol solutions for AS=½ Aopt are 2.5 times and 3.5 times lower than the optimal concentrations, respectively.
Czasopismo
Rocznik
Tom
Strony
187--192
Opis fizyczny
Bibliogr. 22 poz., tab.
Twórcy
autor
- Department of Chemical and Bioprocess Engineering, Faculty of Chemical Technology and Engineering, University of Science and Technology in Bydgoszcz, ul. Seminaryjna 3, 85-326 Bydgoszcz, Poland
Bibliografia
- 1. Chan L.W., Hern K.E., Ngambenjawong C., Lee K., Kwon E.J., Hung D.T., Bhatia S.N. 2021. Selective permeabilization of gram-negative bacterial membranes using multivalent peptide constructs for antibiotic sensitization. ACS Infectious Diseases, 7(4), 721–732. https://doi.org/10.1021/acsinfecdis.0c00805
- 2. Gravel J., Paradis-Bleau C., Schmitzer A.R. 2017. Adaptation of a bacterial membrane permeabilization assay for quantitative evaluation of benzalkonium chloride as a membrane-disrupting agent. MedChemComm, 8(7), 1408–1413. https://doi.org/10.1039/c7md00113d
- 3. Hamid S., Skinder B.M., Bhat M.A. 2020. Zero waste: a sustainable approach for waste management. Innovative Waste Management Technologies for Sustainable Development. IGI Global, Hershey.
- 4. Kaushal J., Mehandia S., Singh G., Raina A., Arya S.K. 2018. Catalase enzyme: application in bioremediation and food industry. Biocatalysis and Agricultural Biotechnology, 16, 192–199. https://doi.org/10.1016/j.bcab.2018.07.035
- 5. Lane S., Dong J., Jin Y.S. 2018. Value-Added biotransformation of cellulosic sugars by engineered Saccharomyces cerevisiae. Bioresource Technology, 260, 380−394. https://doi.org/10.1016/j.biortech.2018.04.013
- 6. Liu X., Kokare C. 2023. Microbial enzymes of use in industry. Biotechnology of microbial enzymes. Academic Press, Cambridge.
- 7. Luo Y., Kurian V., Ogunnaike B.A. 2021. Bioprocess systems analysis, modeling, estimation, and control. Current Opinion in Chemical Engineering, 33, 100705. https://doi.org/10.1016/j.coche.2021.100705.
- 8. Mityushev V., Nawalaniec W., Rylko N. 2018. Introduction to mathematical modeling and computer simulations, 1st ed.; Chapman and Hall/CRC, London.
- 9. Mukherjee S. 2019. Isolation and purification of industrial enzymes: advances in enzyme technology. Elsevier, Amsterdam.
- 10. Nishimoto T., Watanabe T., Furuta M., Kataoka M., Kishida M. 2016. Roles of catalase and trehalose in the protection from hydrogen peroxide toxicity in Saccharomyces cerevisiae. Biocontrol Science, 2016(21), 179–82. https://doi.org/10.4265/bio.21.179
- 11. Ogra Y., Shimizu M., Takahashi K., Anan Y. 2018. Biotransformation of organic selenium compounds in budding yeast, Saccharomyces cerevisiae. Metall, 10(9), 1257–1263. https://doi.org/10.1039/C8MT00176F
- 12. Panesar P.S., Panesar R., Singh R.S., Bera M.B. 2007. Permeabilization of yeast cells with organic solvents for β-galactosidase activity. Research Journal of Microbiology, 2(1), 34–41. https://doi.org/10.3923/jm.2007.34.41
- 13. Rasmussen R.E., Erstad S.M., Ramos-Martinez E.M., Fimognari L., Porcellinis A.J., Sakuragi Y. 2016. An easy and efficient permeabilization protocol for in vivo enzyme activity assays in cyanobacteria. Microbial Cell Factories, 15, 186. https://doi.org/10.1186/s12934-016-0587-3
- 14. Santos V.C.S., Pedrinho D.R., Ito Morioka L.R., Suguimoto H.H. 2018. Determination of Cell Permeabilization and Beta-Galactosidase Extraction from Aspergillus oryzae CCT 0977 Grown in Cheese Whey. International Journal of Chemical Engineering, 1367434. https://doi.org/10.1155/2018/1367434
- 15. Skliar V., Krusir G., Shunko H., Zakharchuk V., Malovanyy M. 2020. A promising way to dispose of fatty waste by hydrolysis and study of the conditions for immobilization of Rhizopus japonicus lipase on carriers. Journal of Ecological Engineering, 21(2), 201–208. https://doi.org/10.12911/22998993/116343
- 16. Trawczynska I. 2020. Use of the chemical permeabilization process in yeast cells: production of highactivity whole cell biocatalysts. BioTechnologia. Journal of Biotechnology Computational Biology and Bionanotechnology, 101(3), 239–252. https://doi.org/10.5114/bta.2020.97882
- 17. Trawczyńska I., Miłek J., Kwiatkowska-Marks S. 2018. Effect of temperature, concentration of alcohols and time on baker’s yeast permeabilization process. Technical Sciences, 21(3), 195–206. https://doi.org/10.31648/ts.2886
- 18. Ugya A.Y., Meguellati K. 2022. Microalgae biomass modelling and optimization for sustainable biotechnology – a concise review. Journal of Ecological Engineering, 23(9), 309–318. https://doi.org/10.12911/22998993/150627
- 19. Willaert R.G. 2017. Yeast Biotechnology. Mdpi AG, Basel.
- 20. Winsberg E. 2015. Computer simulations in science. The Stanford Encyclopedia of Philosophy. Stanford.
- 21. Zhao W., Hu S., Huang J., Mei H. 2014. Improve microorganism cell permeability for whole-cell bioprocess: methods and strategies. China Biotechnology, 34(3), 125–131. https://doi.org/10.13523/j.cb.20140318
- 22. Zhou H. 2013. Computer Modeling for Injection Molding, John Wiley & Sons, Hoboken.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-8723a940-d099-4925-815b-a1b2104a0455