Final Report Summary - PSEUDOMODEL (Integrative Modeling and Engineering of Pseudomonas putida for Green Chemistry) The widespread use of petrol-based fuels and plastic is a major cause of environmental pollution, and their current production depends on limited and non-renewable oil resources. A promising approach for the renewable production of environmentally friendly chemicals is the genetic engineering of microorganisms. To this end, the activities of the genes encoded in a microorganism can be modified, or new genes inserted from different organisms. In both cases, the goal is to develop microorganisms capable of efficiently producing the desired chemicals, such as bioplastics or biofuels, by modifying or extending their genetic repertoire. Compared to the commonly used production processes based on petrochemicals, these biological processes are renewable and less polluting, which is why they are referred to as green chemistry. However, the combinatorial possibilities for integrating genes from different organisms into a microbial host are too complex in order to be explored systematically by classical approaches, which rely on the manual review of known genetic functions and their experimental validation. Therefore, the development of computational methods for predicting genetic engineering strategies for the design of efficient microbial production strains and their integration with experiments is at the forefront of modern approaches in biotechnology.Within the PSEUDOMODEL project, computational methods were developed to facilitate the prediction of genetic engineering strategies, aiming at the efficient production of biofuels and bioplastics. First, a dataset of the enzymatic repertoires of 23 organisms was assembled. A new computational framework was developed, which predicts minimal interventions for controlling the activity of a specific pathway of interest. The method was validated by demonstrating that the predicted genes are under strong cellular regulation, and are thus used by the organism for efficient control of cellular pathways. The results led to the identification of several promising targets for genetic engineering. Pseudomonas putida KT2440 has been used for the production of polyhydroxyalkanoates (PHA), important precursors for bioplastics. The existing models of Pseudomonas putida KT2440 were compared and validated. The developed computational method was employed to predict genetic engineering strategies for the efficient production of Acetyl-Coenzyme A, an important precursor of PHA, using three different scenarios: (1) optimization of microbial growth, (2) optimization of Acetyl-Coenzyme A yield, and (3) combined optimization of growth and Acetyl-Coenzyme A yield. The results suggest that several alternative engineering strategies may increase growth by up to 147%, and PHA production by up to 136%. Further, the results of scenario (2) indicate that Acetyl-Coenzyme A production is limited by the uptake rate of succinate, pointing at the possibility of further increasing its production by optimizing the growth medium for succinate uptake. These results can be exploited by biotechnology companies for the economic production of bioplastic using the proposed engineering strategies.Since most biofuels are toxic, current efforts for their production are limited by the tolerance of microorganisms to these biofuels. Pseudomonas putida DOT-T1E represents a promising microorganism due to its superior tolerance of toxic compounds. Within the project, the biofuel tolerance of P. putida DOT-T1E was evaluated, and the strain was genetically engineered in order to further improve its tolerance. The resulting engineered strains represent promising host systems for the efficient production of biofuels. Their capabilities may be exploited in the future for the renewable production of biofuels by bioenergy companies.
