Optimisation of induction conditions for a bacterial strain producing proinsulin aspart

Diabetes poses a serious threat to the health of people around the world. Therefore, in 2021, the World Health Organisation launched the Global Diabetes Compact, an initiative aimed at improving the management and prevention of diabetes. The rapid growth in the number of diabetic patients has increased the need for insulin. Rapid-acting human insulin analogues, including insulin aspart, improve the efficacy of insulin therapy. Methods for insulin aspart production include its biosynthesis in the proinsulin form in Escherichia coli. However, the yield of the recombinant protein largely depends on the optimisation of the production process.

The aim of the study was to optimise the induction conditions for an E. coli strain expressing recombinant proinsulin aspart through applying the Design of Experiment (DoE) approach to enhance bacterial cell productivity.

Materials and methods. The study focused on a strain of E. coli producing proinsulin aspart. The authors planned the experiment using MODDE software and the reduced face-centred central composite design (CCF) enabling the assessment of factor interactions and the creation of design spaces. The authors carried out fermentations of the producing strain in a 5 L Biostat® B bioreactor and measured proinsulin aspart concentrations by capillary gel electrophoresis. The results were analysed using GraphPad Prism 6.

Results. Using the DoE approach, the authors optimised the conditions for the growth of the producer strain and the biosynthesis of proinsulin aspart. Based on data from response surface plots for wet biomass concentration, specific productivity, and volumetric productivity, as well as plotted models, the authors established design spaces for the induction of proinsulin aspart expression in E. coli. The plotted models demonstrated high predictive power and high reproducibility of the results. The authors successfully validated the induction process for the synthesis of proinsulin aspart in a bioreactor under optimised conditions. The volumetric productivity of the strain producing proinsulin aspart increased from 3.06±0.16 g/L (conventional conditions) to 4.93±0.80 g/L (optimised conditions).

Conclusions. The authors achieved a 60% increase in the volumetric yield of proinsulin aspart. The study results may be used to intensify the industrial production of insulin aspart.

1. Chapman TM, Noble S, Goa KL. Insulin aspart: a review of its use in the management of type 1 and 2 diabetes mellitus. Drugs. 2002;62(13):1945–81. https://doi.org/10.2165/00003495-200262130-00014

2. Valerio LG, Jr. Tenth anniversary of Expert Opinion on Drug Metabolism & Toxicology. Expert Opin Drug Metab Toxicol. 2014;10(6):767–8. https://doi.org/10.1517/17425255.2014.920007

3. Siew YY, Zhang W. Downstream processing of recombinant human insulin and its analogues production from E. coli inclusion bodies. Bioresour Bioprocess. 2021;8(1):65. https://doi.org/10.1186/s40643-021-00419-w

4. Baeshen NA, Baeshen MN, Sheikh A, Bora RS, Ahmed MM, Ramadan HA, et al. Cell factories for insulin production. Microb Cell Fact. 2014;13:141. https://doi.org/10.1186/s12934-014-0141-0

5. Mikiewicz D, Bierczyńska-Krzysik A, Sobolewska A, Stadnik D, Bogiel M, Pawłowska M, et al. Soluble insulin analogs combining rapid- and long-acting hypoglycemic properties — from an efficient E. coli expression system to a pharmaceutical formulation. PLoS One. 2017;12(3):e0172600. https://doi.org/10.1371/journal.pone.0172600

6. Uhoraningoga A, Kinsella GK, Henehan GT, Ryan BJ. The Goldilocks approach: a review of employing design of experiments in prokaryotic recombinant protein production. Bioengineering (Basel). 2018;5(4):89. https://doi.org/10.3390/bioengineering5040089

7. Haider MA, Pakshirajan K. Screening and optimization of media constituents for enhancing lipolytic activity by a soil microorganism using statistically designed experiments. Appl Biochem Biotechnol. 2007;141(2–3):377–90. https://doi.org/10.1007/BF02729074

8. Gutiérrez-González M, Farías C, Tello S, Pérez-Etcheverry D, Romero A, Zúñiga R, et al. Optimization of culture conditions for the expression of three different insoluble proteins in Escherichia coli. Sci Rep. 2019;9(1):16850. https://doi.org/10.1038/s41598-019-53200-7

9. Ashayeri-Panah M, Eftekhar F, Kazemi B, Joseph J. Cloning, optimization of induction conditions and purification of Mycobacterium tuberculosis Rv1733c protein expressed in Escherichia coli. Iran J Microbiol. 2017;9(2):64–73.

10. 10. Azaman SN, Ramakrishnan NR, Tan JS, Rahim RA, Abdullah MP, Ariff AB. Optimization of an induction strategy for improving interferon-alpha2b production in the periplasm of Escherichia coli using response surface methodology. Biotechnol Appl Biochem. 2010;56(4):141–50. https://doi.org/10.1042/BA20100104

11. Huang Y, Lu X, Wang J, Jin X, Zhu J. Optimization of expression conditions of an induction strategy for improving liver targeted interferon (IFN-CSP) production in E. coli. Sheng Wu Yi Xue Gong Cheng Xue Za Zhi. 2014;31(2):432–8.

12. Larentis AL, Corrêa Argondizzo AP, dos Santos Esteves G, Jessouron E, Galler R, Medeiros MA. Cloning and optimization of induction conditions for mature PsaA (pneumococcal surface adhesin A) expression in Escherichia coli and recombinant protein stability during long-term storage. Protein Expr Purif. 2011;78(1):38–47. https://doi.org/10.1016/j.pep.2011.02.013

13. Mandenius CF, Brundin A. Bioprocess optimization using design-of-experiments methodology. Biotechnol Prog. 2008;24(6):1191–203. https://doi.org/10.1002/btpr.67

14. Dolnik V. Capillary electrophoresis of proteins 2005–2007. Electrophoresis. 2008;29(1):143–56. https://doi.org/10.1002/elps.200700584

15. Castellanos-Mendoza A, Castro-Acosta RM, Olvera A, Zavala G, Mendoza-Vera M, García-Hernández E, et al. Influence of pH control in the formation of inclusion bodies during production of recombinant sphingomyelinase-D in Escherichia coli. Microb Cell Fact. 2014;13:137. https://doi.org/10.1186/s12934-014-0137-9

16. Slouka C, Kopp J, Hutwimmer S, Strahammer M, Strohmer D, Eitenberger E, et al. Custom made inclusion bodies: impact of classical process parameters and physiological parameters on inclusion body quality attributes. Microb Cell Fact. 2018;17(1):148. https://doi.org/10.1186/s12934-018-0997-5

17. Chen H, Jiang P, Li F, Wu H. Improving production of thermostable and fluorescent holo-β-allophycocyanin by metabolically engineered Escherichia coli using response surface methodology. Prep Biochem Biotechnol. 2015;45(7):730–41. https://doi.org/10.1080/10826068.2014.943374

18. Einsfeldt K, Severo Júnior JB, Corrêa Argondizzo AP, Medeiros MA, Alves TL, Almeida RV, Larentis AL. Cloning and expression of protease ClpP from Streptococcus pneumoniae in Escherichia coli: study of the infl uence of kanamycin and IPTG concentration on cell growth, recombinant protein production and plasmid stability. Vaccine. 2011;29(41):7136–43. https://doi.org/10.1016/j.vaccine.2011.05.073

19. Marini G, Luchese MD, Corrêa Argondizzo AP, Magalhães Andrade de Góes AC, Galler R, Moitinho Alves TL, et al. Experimental design approach in recombinant protein expression: determining medium composition and induction conditions for expression of pneumolysin from Streptococcus pneumoniae in Escherichia coli and preliminary purification process. BMC Biotechnol. 2014;14:1. https://doi.org/10.1186/1472-6750-14-1

20. Mühlmann M, Forsten E, Noack S, Büchs J. Optimizing recombinant protein expression via automated induction profiling in microtiter plates at different temperatures. Microb Cell Fact. 2017;16(1):220. https://doi.org/10.1186/s12934-017-0832-4