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Fine-tuning biosynthetic pathways is crucial for the development of economic feasible microbial cell factories. Therefore, the use of computational models able to predictably design regulatory sequences for pathway engineering proves to be a valuable tool, especially for modifying genes at the translational level. In this study we developed a computational approach for the de novo design of 5'-untranslated regions (5'UTRs) in Saccharomyces cerevisiae with a predictive outcome on translation initiation rate. On the basis of existing data, a partial least-squares (PLS) regression model was trained and showed good performance on predicting protein abundances of an independent test set. This model was further used for the construction of a "yUTR calculator" that can design 5'UTR sequences with a diverse range of desired translation efficiencies. The predictive power of our yUTR calculator was confirmed in vivo by different representative case studies. As such, these results show the great potential of data driven approaches for reliable pathway engineering in S. cerevisiae.

Combinatorial engineering approaches are becoming increasingly popular, yet they are hindered by the lack of specialized techniques for both efficient introduction of sequence variability and assembly of numerous DNA parts, required for the construction of lengthy multigene pathways. In this contribution, we introduce a new combinatorial multigene pathway assembly scheme based on Single Strand Assembly (SSA) methods and Golden Gate Assembly, exploiting the strengths of both assembly techniques. With a minimum of intermediary steps and an accompanying set of well-characterized and ready-to-use genetic parts, the developed workflow allows effective introduction of various libraries and efficient assembly of multigene pathways. It was put to the test by optimizing the lycopene pathway as proof-of-principle. The here constructed libraries yield ample variation in lycopene production. In addition, good-performing transformants with a significantly higher lycopene production were obtained as compared to previously published reference strains. The best selected producer yielded 3-fold improvement in lycopene titers up to 448 mg lycopene/g CDW. The proposed workflow in combination with the accompanying sets of ready-to-use expression and carrier plasmids, will allow the combinatorial assembly of increasingly lengthy product pathways with minimal effort.

1,3-Propanediol (PDO) is the starting point of a new-generation polymer with superior properties which is used in the textile and carpet industry. This product is mainly produced chemically, but high pressure, high temperature and expensive catalysts are required and toxic intermediates are released. Therefore, the biological production route has been studied intensively. DuPont and Genencor International, Inc. have modified Escherichia coli genetically so that this organism could produce PDO from glucose. However, due to the tremendous growth of the biofuel industry, a glycerol surplus has been created, so more and more researchers started to investigate the natural producing strains for the production of PDO from glycerol. Several metabolic engineering techniques have been used to enhance the production of PDO. This contribution gives an overview of the different strategies to increase the final titer, yield, and productivity of 1,3-propanediol in non-natural and natural producing strains.