Effects of metabolic pathway gene copy numbers on the biosynthesis of (2S)-naringenin in Saccharomyces cerevisiae
Introduction
Flavonoids are secondary plant metabolites with many critical physiological functions and applications. Currently, approximately 10,000 unique structures of flavonoids have been recorded (Dixon and Pasinetti, 2010; Lv et al., 2019). Plants produce flavonoids to protect themselves from fungal parasites, pathogens, and ultraviolet radiation (Dixon and Steele, 1999; Fowler and Koffas, 2009; Wang et al., 2011). Flavonoids also confer plant color and facilitate communication with other species, such as by encouraging animals to scatter their seeds (Havsteen, 2002). Furthermore, flavonoids exhibit diverse biological and pharmacological effects such as antioxidant, antiallergic, antibacterial, anticancer, and hepatoprotective properties (Khan et al., 2019; Najmanova et al., 2019; Thaiss et al., 2016; Ulusoy and Sanlier, 2019; Zhang et al., 2019). (2S)-Naringenin, a crucial intermediate for producing various flavonoids, has an important role in the microbial synthesis of flavonoids.
Plant extraction remains the primary route for the industrial production of flavonoids, but this method is problematic in terms of environmental pollution and sustainability. In recent years, studies have provided increasing evidence that microbial synthesis of flavonoids is a promising alternative to plant extraction (Gao et al., 2020a; Lyu et al., 2017). Saccharomyces cerevisiae is a generally regarded as safe (GRAS) organism that has been widely used in the pharmaceutical and biotechnology industries. As a model eukaryotic system, it has been intensely studied in the fields of molecular biology and cell biology (Lian et al., 2018). Genomic integration of foreign DNA through homologous recombination in yeast occurs with high efficiency (Shao et al., 2009). Homologous recombination of 50-bp is feasible for genetic integration in yeast, but longer lengths (such as >500-bp) are more efficient (Li et al., 2019a; Shao et al., 2009).
Integration methods based on single-copy sites have been used to express heterologous synthetic pathway genes (Lyu et al., 2017). However, microbial heterologous synthesis of target products may be affected by copy number restrictions. Multi-copy genomic integration (such as ribosomal DNA, rDNA) is more suitable than using single-copy sites for metabolic engineering (Lian et al., 2018). In yeast, rDNA is assembled with the same repeat sequence in a tandem arrangement, and each rDNA unit consists of two transcribed regions (5S- and 35S-rDNA) and two non-transcribed spacers (NTS1 and NTS2) (Kobayashi et al., 2004). Genomic integration based on rDNA sites has been applied in the production of secondary metabolic products by engineered yeast, including ginsenosides (Dai et al., 2013), β-amyrin (Zhang et al., 2015), glycyrrhetinic acid (Zhu et al., 2018), lycopene (Li et al., 2019b), and isobutanol (Park and Hahn, 2019). Therefore, the integration of heterologous pathway genes into S. cerevisiae high copy sites has excellent potential for high titer production of secondary metabolic products. However, the number of copies of heterologous pathway genes integrated into multiple copy sites is random. The copy number of the strain produced is uncertain. Therefore, the actual integration number of metabolic pathway genes must be determined. Moreover, the influence of the expression levels of heterologous metabolic pathway genes on the yield of target products must also be quantified. The regulatory relationships among heterologous pathway integration copy number, gene expression level, and the titer of the product of interest require further exploration.
In this study, we designed and constructed a one-step multi-copy integration of the (2S)-naringenin metabolic pathway through an in vivo homologous recombination mechanism in S. cerevisiae. High efficiency was obtained with the use of long homologous sequences for the integration of naringenin metabolic pathway genes. In addition, the donor DNA concentration was optimized to ensure the highest probability of obtaining engineered strains. The number of metabolic pathway gene copies and the expression levels of key genes were positively associated with (2S)-naringenin production. Our results indicated that the higher (2S)-naringenin in the engineered strain could be ascribed to increased precursor supply and multi-copy integration of metabolic pathway genes.
Section snippets
Strains, media, and chemicals
The S. cerevisiae strain CEN.PK2-1D (MATα; 98 ura3-52; trp1-289; leu2-3,112; his3Δ1; MAL2-8C; SUC2) (Entian and Kotter, 2007) was used as the host for pathway engineering. Escherichia coli JM109 was used for routine transformation and plasmid construction. For transformation, E. coli was cultured at 37 °C at 220 rpm in Luria broth prepared with 10 g/L tryptone, 5 g/L yeast extract, and 10 g/L NaCl. Ampicillin (100 μg/mL) was added when required. For the selection of transformants, yeast
Construction of the (2S)-naringenin biosynthesis pathway in S. cerevisiae
To multiplex the (2S)-naringenin metabolic pathway genes into the C800 genome, we used rDNA clusters as integration sites. Complete NTS1 (1001 bp) and NTS2 (1240 bp) sequences were selected as homologous recombination regions for the (2S)-naringenin metabolic pathway genes to ensure efficient integration (Fig. 1B). As a proof of concept, a single-step integration of multiple genes in the (2S)-naringenin biosynthetic pathway was designed and constructed (Fig. 1A, B). The colony PCR results
Discussion
Compared with natural source extraction and chemical synthesis, the use of S. cerevisiae for flavonoid production is a promising platform to provide shorter cultivation periods and markedly higher yields (Cao et al., 2020). Previous studies have reported successful examples of synthesis of flavonoids in S. cerevisiae, such as kaempferol (Rodriguez et al., 2017), quercetin (Rodriguez et al., 2017), and apigenin (Vanegas et al., 2018). In this work, the relationships between the titer of (2S
CRediT authorship contribution statement
Hongbiao Li: Data curation, Writing - original draft, Writing - review & editing. Song Gao: Visualization, Investigation. Siqi Zhang: Software, Validation. Weizhu Zeng: Supervision. Jingwen Zhou: Conceptualization, Methodology, Software.
Declaration of Competing Interest
The authors report no declarations of interest.
Acknowledgements
This work was supported by the National Key Research and Development Program of China (2019YFA0904800), the National Outstanding Youth Foundation (21822806), the Fundamental Research Funds for the Central Universities (JUSRP52018A), and the National First-class Discipline Program of Light Industry Technology and Engineering (LITE2018-08).
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