Decoding metabolic burden: Experimental insights and mathematical modelling of heterologous protein production in Pseudomonas putida (COMET)

• Applicants: Professor Dr.-Ing. Andreas Kremling; Dr. Katharina Pflüger-Grau
• Subject Area: Biological Process Engineering ; Microbial Ecology and Applied Microbiology ; Metabolism, Biochemistry and Genetics of Microorganisms
• Term: since 2025
• Project identifier: Deutsche Forschungsgemeinschaft (DFG) - Project number 555300101

In biotechnological applications, heterologous genes are introduced to reprogram host cell metabolism towards desired products. However, this often imposes a metabolic burden on the host, consuming energy and resources and potentially slowing growth. Pseudomonas putida, a versatile Gram-negative bacterium, is a promising candidate for industrial biotechnology due to its metabolic flexibility, stress resistance, and established genetic tools. Its unique metabolic pathways, particularly in glucose metabolism, make it an attractive host for heterologous protein production. This research project aims to understand protein allocation in P. putida, both in general and specifically during heterologous protein production, through experimental and theoretical approaches. The key questions addressed are: (i) How is the proteome rearranged in response to heterologous protein production? (ii) What is the influence of modulating resource availability on metabolic burden? (iii) Is there a way to alleviate metabolic burden? The first objective investigates protein allocation in non-burdened versus burdened cells. Therefore, different growth rates will be set by different methods: using various carbon sources, titrating the carbon source uptake, or employing continuous culture techniques. The type of burden will be modulated by expressing various heterologous proteins in P. putida to assess their impact. Specific combinations of growth rate and burden type will be further analysed by determining the total protein/total RNA fraction, sugar uptake, heterologous protein production, and quantitative proteomics. These data will serve as the basis for theoretical considerations on protein allocation. A modular model will be developed to simulate the central metabolism, proteome sectors, and heterologous protein production. This proteome allocation model will predict optimal resource allocation and identify trade-offs between objectives like growth rate and yield. Once this is accomplished, efforts will be undertaken to optimize heterologous protein production. The impact of genome reduction on resource liberation during heterologous protein production will be investigated and the proteome allocation model will be used to identify further putative targets for enhancing resource availability. These targets may involve genetic modifications or process parameter adjustments. The impact of rearranging periplasmic fluxes and enhancing glucose uptake on heterologous protein production will be explored. The research will systematically investigate protein allocation in both non-burdened and burdened cells, create a comprehensive model of resource allocation, and optimize genetic and process conditions to improve overall efficiency. This integrated approach is expected to contribute to advancements in using P. putida as an industrial production host, enhancing its productivity and stability in various biotechnological applications.

• DFG Programme: Research Grants