Alam, Fairooza; (2025) Petri net Modelling to Assess the Performance of the Protein Folding Machinery for Recombinantly Expressed Proteins in Escherichia coli. Doctoral thesis (Ph.D), UCL (University College London).

Preview

Text Fairooza Alam Thesis Final.pdf - Accepted Version Download (10MB) | Preview

Abstract

The production of complex recombinant proteins in E. coli is a foundation mark in bioprocessing. However, roadblocks such as post-translational modifications and inclusion body formation often impede protein expression despite E. coli's reputation for achieving rapid growth, cost-effectiveness, and well-characterised genetics. Addressing these hurdles is essential for advancing the efficiency and productivity of bioprocesses. Formal modelling methods have been adopted in biotechnology to offer alternative solutions to challenges associated with cellular biology. This thesis presents the first model to combine different mechanisms in protein folding machinery in E. coli using Petri net, offering a novel approach to overcoming folding-related obstacles. The innovative model sheds light on the critical role of molecular chaperones in protein synthesis, translocation, and disulphide bond formation, which are fundamental processes that correct protein misfolds at the cellular level. By integrating the tricarboxylic acid (TCA) cycle and oxidative phosphorylation, the model also highlights the essential requirements for energy and reducing agents driving protein production. The fully constructed model comprises 315 unique biological states represented as places and 329 biological reactions represented as transitions, resulting in 896 arcs connecting various biochemical responses to the following biological state. The construction of this Petri net model was a comprehensive process involving a thorough search and analysis of datasets from multiple databases and literature. The discrepancies were carefully evaluated to validate the assumptions made while constructing the model. Using the human growth hormone (HGH) as a model protein, this research revealed a direct correlation between energy availability and the quantity of correctly folded protein produced. Furthermore, the model illustrates the detrimental effects of glucose limitation on protein folding, causing inclusion body formation and generating misoxidised proteins. Test cases evaluated the model's robustness and applicability. One of these test cases was modelling the pathways of signal peptides through the Sec system, which showed fluctuating transition patterns dependent on the coupled or uncoupled pathway. This biological phenomenon was documented for the first time in this work and is useful when determining which signal peptide to use for the expression and correct translocation of a specific protein. In addition, the model can investigate the utility of the commercial CyDisCo strain in protein production that employs the Tat translocation pathway. Furthermore, the impact of overexpressing critical molecular chaperones such as DnaK/DnaJ and GroEL/ES was explored, and it was shown that even minor changes in the transition rates describing the processes in these pathways could impact the total amount of protein produced. Lastly, the elimination of DsbA, DsbB, DsbC, and DsbD proteins from the disulphide bond formation process was studied to understand their role and impact on the model. The simulations exposed crucial data gaps and the interdependence between folding and translocation pathways, underscoring its potential as a potent tool for honing strain design. The model simulation showed that when the energy generation rate is slower than the rate of folding, misfolded proteins accumulate, creating a delay in folding. This model presents complementary and alternative methods to minimise the formation of inclusion bodies and improve the amount of correctly folded protein by removing chaperones and overexpressing chaperones, depending on the protein's nature. The utilisation of this model in strain design to facilitate the successful expression of recombinant proteins in E. coli is expected to propel the field of bioprocessing into a more efficient and productive future.

Download activity - last month

Export as JSONCSVXML

Download activity - last 12 months

Export as XMLCSVJSON

Downloads by country - last 12 months

Export as XMLCSVJSON

Archive Staff Only

View Item