Using a vector pool containing variable-strength promoters to optimize protein production in Yarrowia lipolytica. Issue 1 (December 2017)

• Record Type: Journal Article
• Authors: Dulermo, Rémi; Brunel, François; Dulermo, Thierry; Ledesma-Amaro, Rodrigo; Vion, Jérémy; Trassaert, Marion; Thomas, Stéphane; Nicaud, Jean-Marc; Leplat, Christophe
• Is Part Of: Microbial cell factories. Volume 16:Issue 1(2017)
• Page Start: 1
• Page End: 11
• Publication Date: 2017-12
• Subjects: Yarrowia lipolytica -- Protein production -- RedStar2 -- Glucoamylase -- Xylanase -- Hybrid promoters; Microbial biotechnology -- Periodicals; Recombinant proteins -- Synthesis -- Periodicals; 660.62
• DOI: 10.1186/s12934-017-0647-3
• Languages: English
• ISSNs: 1475-2859

Abstract

Abstract Background The yeastYarrowia lipolytica is an increasingly common biofactory. To enhance protein expression, several promoters have been developed, including the constitutiveTEF promoter, the induciblePOX2 promotor, and the hybrid hp4d promoter. Recently, new hp4d-inspired promoters have been created that couple various numbers of UAS1 tandem elements with the minimalLEU2 promoter or theTEF promoter. Three different protein-secretion signaling sequences can be used: preLip2, preXpr2, and preSuc2. Results To our knowledge, our study is the first to use a set of vectors with promoters of variable strength to produce proteins of industrial interest. We used the more conventionalTEF and hp4d promoters along with five new hybrid promoters: 2UAS1-pTEF, 3UAS1-pTEF, 4UAS1-pTEF, 8UAS1-pTEF, and hp8d. We compared the production of RedStar2, glucoamylase, and xylanase C when strains were grown on three media. As expected, levels of RedStar2 and glucoamylase were greatest in the strain with the 8UAS1-pTEF promoter, which was stronger. However, surprisingly, the 2UAS1-pTEF promoter was associated with the greatest xylanase C production and activity. This finding underscored that stronger promoters are not always better when it comes to protein production. We therefore developed a method for easily identifying the best promoter for a given protein of interest. In this gateway method, genes for YFP and α-amylase were transferred into a pool of vectors containing different promoters and gene expression was then analyzed. We observed that, in most cases, protein production and activity were correlated with promoter strength, although this pattern was protein dependent. Conclusions Protein expression depends on more than just promoter strength. Indeed, promoter suitability appears to be protein dependent; in some cases, optimal expression and activity was obtained using a weaker promoter. We showed that using a vector pool containing promoters of variable strength can be a powerful tool for rapidly identifying the best producer for a given protein of interest.