Predicting proteome allocation, overflow metabolism, and metal requirements in a model acetogen

The unique capability of acetogens to ferment a broad range of substrates renders them ideal candidates for the biotechnological production of commodity chemicals. In particular the ability to grow with H2:CO2 or syngas (a mixture of H2/CO/CO2) makes these microorganisms ideal chassis for sustainable bioproduction. However, advanced design strategies for acetogens are currently hampered by incomplete knowledge about their physiology and our inability to accurately predict phenotypes. Here we describe the reconstruction of a novel genome-scale model of metabolism and macromolecular synthesis (ME-model) to gain new insights into the biology of the model acetogen Clostridium ljungdahlii. The model represents the first ME-model of a Gram-positive bacterium and captures all major central metabolic, amino acid, nucleotide, lipid, major cofactors, and vitamin synthesis pathways as well as pathways to synthesis RNA and protein molecules necessary to catalyze these reactions, thus significantly broadens the scope and predictability. Use of the model revealed how protein allocation and media composition influence metabolic pathways and energy conservation in acetogens and accurately predicted secretion of multiple fermentation products. Predicting overflow metabolism is of particular interest since it enables new design strategies, e.g. the formation of glycerol, a novel product for C. ljungdahlii, thus broadening the metabolic capability for this model microbe. Furthermore, prediction and experimental validation of changing secretion rates based on different metal availability opens the window into fermentation optimization and provides new knowledge about the proteome utilization and carbon flux in acetogens.
Author summary Acetogens are renowned for their potential biotechnological applications. The model acetogen Clostridium ljungdahlii has been studied intensively for its ability to produce biofuels from sustainable resources, like syngas. We describe a novel genome-scale model of metabolism and gene expression (ME-model) to gain insights into this model acetogen. This first ME-model for a Gram-positive bacterium contains all major metabolic and biosynthetic pathways and calculates accurate proteome allocations under diverse growth conditions, thereby significantly broadening the scope of predictability of metabolic models. Furthermore, the ME-model enables rational medium design for improved production. Our experimental validation implies wide applicability to others strains for rapid improvement of yield and titer in biotechnology-relevant applications.