Toward fine-tuned metabolic networks in industrial microorganisms

Automated characterization and analysis of expression compatibility between regulatory sequences and metabolic genes in Escherichia coli

Utilizing standardized artificial regulatory sequences to fine-tuning the expression of multiple metabolic pathways/genes is a key strategy in the creation of efficient microbial cell factories. However, when regulatory sequence expression strengths are characterized using only a few reporter genes, they may not be applicable across diverse genes. This introduces great uncertainty into the precise regulation of multiple genes at multiple expression levels. To address this, our study adopted a fluorescent protein fusion strategy for a more accurate assessment of target protein expression levels. We combined 41 commonly-used metabolic genes with 15 regulatory sequences, yielding an expression dataset encompassing 520 unique combinations. This dataset highlighted substantial variation in protein expression level under identical regulatory sequences, with relative expression levels ranging from 2.8 to 176-fold. It also demonstrated that improving the strength of regulatory sequences does not necessarily lead to significant improvements in the expression levels of target proteins. Utilizing this dataset, we have developed various machine learning models and discovered that the integration of promoter regions, ribosome binding sites, and coding sequences significantly improves the accuracy of predicting protein expression levels, with a Spearman correlation coefficient of 0.72, where the promoter sequence exerts a predominant influence. Our study aims not only to provide a detailed guide for fine-tuning gene expression in the metabolic engineering of Escherichia coli but also to deepen our understanding of the compatibility issues between regulatory sequences and target genes.

Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms

Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.

Manipulating gene expression levels in mammalian cell factories: An outline of synthetic molecular toolboxes to achieve multiplexed control

Mammalian cells have developed dedicated molecular mechanisms to tightly control expression levels of their genes where the specific transcriptomic signature across all genes eventually determines the cell's phenotype. Modulating cellular phenotypes is of major interest to study their role in disease or to reprogram cells for the manufacturing of recombinant products, such as biopharmaceuticals. Cells of mammalian origin, for example Chinese hamster ovary (CHO) and Human embryonic kidney 293 (HEK293) cells, are most commonly employed to produce therapeutic proteins. Early genetic engineering approaches to alter their phenotype have often been attempted by "uncontrolled" overexpression or knock-down/-out of specific genetic factors. Many studies in the past years, however, highlight that rationally regulating and fine-tuning the strength of overexpression or knock-down to an optimum level, can adjust phenotypic traits with much more precision than such "uncontrolled" approaches. To this end, synthetic biology tools have been generated that enable (fine-)tunable and/or inducible control of gene expression. In this review, we discuss various molecular tools used in mammalian cell lines and group them by their mode of action: transcriptional, post-transcriptional, translational and post-translational regulation. We discuss the advantages and disadvantages of using these tools for each cell regulatory layer and with respect to cell line engineering approaches. This review highlights the plethora of synthetic toolboxes that could be employed, alone or in combination, to optimize cellular systems and eventually gain enhanced control over the cellular phenotype to equip mammalian cell factories with the tools required for efficient production of emerging, more difficult-to-express biologics formats.

Protein engineering and iterative multimodule optimization for vitamin B6 production in Escherichia coli

Vitamin B6 is an essential nutrient with extensive applications in the medicine, food, animal feed, and cosmetics industries. Pyridoxine (PN), the most common commercial form of vitamin B6, is currently chemically synthesized using expensive and toxic chemicals. However, the low catalytic efficiencies of natural enzymes and the tight regulation of the metabolic pathway have hindered PN production by the microbial fermentation process. Here, we report an engineered Escherichia coli strain for PN production. Parallel pathway engineering is performed to decouple PN production and cell growth. Further, protein engineering is rationally designed including the inefficient enzymes PdxA, PdxJ, and the initial enzymes Epd and Dxs. By the iterative multimodule optimization strategy, the final strain produces 1.4 g/L of PN with productivity of 29.16 mg/L/h by fed-batch fermentation. The strategies reported here will be useful for developing microbial strains for the production of vitamins and other bioproducts having inherently low metabolic fluxes.

Overexpression and RNAi-mediated Knockdown of Two 3β-hydroxy-Δ5-steroid dehydrogenase Genes in Digitalis lanata Shoot Cultures Reveal Their Role in Cardenolide Biosynthesis

3β-hydroxy-Δ5-steroid dehydrogenases (3βHSDs) are supposed to be involved in 5β-cardenolide biosynthesis. Here, a novel 3βHSD (Dl3βHSD2) was isolated from Digitalis lanata shoot cultures and expressed in E. coli. Recombinant Dl3βHSD1 and Dl3βHSD2 shared 70% amino acid identity, reduced various 3-oxopregnanes and oxidised 3-hydroxypregnanes, but only rDl3βHSD2 converted small ketones and secondary alcohols efficiently. To explain these differences in substrate specificity, we established homology models using borneol dehydrogenase of Salvia rosmarinus (6zyz) as the template. Hydrophobicity and amino acid residues in the binding pocket may explain the difference in enzyme activities and substrate preferences. Compared to Dl3βHSD1, Dl3βHSD2 is weakly expressed in D. lanata shoots. High constitutive expression of Dl3βHSDs was realised by Agrobacterium-mediated transfer of Dl3βHSD genes fused to the CaMV-35S promotor into the genome of D. lanata wild type shoot cultures. Transformed shoots (35S:Dl3βHSD1 and 35S:Dl3βHSD2) accumulated less cardenolides than controls. The levels of reduced glutathione (GSH), which is known to inhibit cardenolide formation, were higher in the 35S:Dl3βHSD1 lines than in the controls. In the 35S:Dl3βHSD1 lines cardenolide levels were restored after adding of the substrate pregnane-3,20-dione in combination with buthionine-sulfoximine (BSO), an inhibitor of GSH formation. RNAi-mediated knockdown of the Dl3βHSD1 yielded several shoot culture lines with strongly reduced cardenolide levels. In these lines, cardenolide biosynthesis was fully restored after addition of the downstream precursor pregnan-3β-ol-20-one, whereas upstream precursors such as progesterone had no effect, indicating that no shunt pathway could overcome the Dl3βHSD1 knockdown. These results can be taken as the first direct proof that Dl3βHSD1 is indeed involved in 5β-cardenolide biosynthesis.

Identification of key genes through the constructed CRISPR-dcas9 to facilitate the efficient production of O-acetylhomoserine in Corynebacterium glutamicum

O-Acetylhomoserine (OAH) is an important platform chemical for the synthesis of L-methamidophos and l-methionine. It has been produced efficiently in Corynebacterium glutamicum. However, a wider range of key factors had not been identified, limiting further increases in OAH production. This study successfully identified some limiting factors and regulated them to improve OAH titer. Firstly, an efficient clustered regularly interspaced short palindromic repeats/dead CRISPR associated protein 9 (CRISPR-dCas9) system was constructed and used to identify the key genes in central metabolism and branch pathways associated with OAH biosynthesis. Then, the gltA gene involved in TCA cycle was identified as the most critical gene. A sequential promoter P_NCgl2698, which showed different transcriptional intensity in different strain growth periods, was used to control the expression of gltA gene, resulting in OAH production of 7.0 g/L at 48 h. Finally, the OAH titer of the engineered strain reached 25.9 g/L at 72 h in a 5-L bioreactor. These results show that the identification and regulation of key genes are critical for OAH biosynthesis, which would provide a better research basis for the industrial production of OAH in C. glutamicum.

A repackaged CRISPR platform increases homology-directed repair for yeast engineering

Inefficient homology-directed repair (HDR) constrains CRISPR-Cas9 genome editing in organisms that preferentially employ nonhomologous end joining (NHEJ) to fix DNA double-strand breaks (DSBs). Current strategies used to alleviate NHEJ proficiency involve NHEJ disruption. To confer precision editing without NHEJ disruption, we identified the shortcomings of the conventional CRISPR platforms and developed a CRISPR platform-lowered indel nuclease system enabling accurate repair (LINEAR)-which enhanced HDR rates (to 67-100%) compared to those in previous reports using conventional platforms in four NHEJ-proficient yeasts. With NHEJ preserved, we demonstrate its ability to survey genomic landscapes, identifying loci whose spatiotemporal genomic architectures yield favorable expression dynamics for heterologous pathways. We present a case study that deploys LINEAR precision editing and NHEJ-mediated random integration to rapidly engineer and optimize a microbial factory to produce (S)-norcoclaurine. Taken together, this work demonstrates how to leverage an antagonizing pair of DNA DSB repair pathways to expand the current collection of microbial factories.