Abstract

The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. The development of economically viable producer cells is, however, lagging behind, as it requires substantial engineering of the host metabolism. A chassis strain suitable for production of a range of molecules is therefore highly sought after but remains elusive. Here, we propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae – a widely used microbial cell factory. For a group of 29 products covering a broad range of biochemistry and applications, we identified modular metabolic engineering strategies for re-routing carbon flux towards the desired product. We find distinct product families with shared targets forming the basis for the corresponding chassis cells. The design strategies include overexpression targets that group products by similarity in precursor and cofactor requirements, as well as gene deletion strategies for growth-product coupling that lead to non-intuitive product groups. Our results reveal the extent and the nature of flux re-routing necessary for producing a diverse range of products in a widely used cell factory and provide blueprints for constructing pre-optimized chassis strains.

Highlights

  • The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing

  • We address the design of a set of pre-optimized S. cerevisiae chassis cells

  • All 29 products considered here originate from only a handful of precursors in the endogenous metabolism of S. cerevisiae (Fig. 1A)

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Summary

Introduction

The diversity of industrially important molecules for which microbial production routes have been experimentally demonstrated is rapidly increasing. We propose a genome-scale metabolic modeling approach to design chassis strains of Saccharomyces cerevisiae – a widely used microbial cell factory. Diverting the input carbon flux away from ethanol, biomass and CO2 production, and to the desired product, requires considerable expertise and several trial-and-error cycles of identifying and implementing genetic engineering targets. These hurdles hamper innovation and delay realization of final bioprocesses. The strain engineering strategies towards increasing precursor and cofactor availability can be rationalized using genome-scale metabolic models[19,20] Such models are available for a number of industrially relevant microbial hosts including S. cerevisiae.

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