Frontiers of yeast metabolic engineering: diversifying beyond ethanol and Saccharomyces

Engineering Promoter Architecture in Oleaginous Yeast Yarrowia lipolytica

Eukaryotic promoters have a complex architecture to control both the strength and timing of gene transcription spanning up to thousands of bases from the initiation site. This complexity makes rational fine-tuning of promoters in fungi difficult to predict; however, this very same complexity enables multiple possible strategies for engineering promoter strength. Here, we studied promoter architecture in the oleaginous yeast, Yarrowia lipolytica. While recent studies have focused on upstream activating sequences, we systematically examined various components common in fungal promoters. Here, we examine several promoter components including upstream activating sequences, proximal promoter sequences, core promoters, and the TATA box in autonomously replicating expression plasmids and integrated into the genome. Our findings show that promoter strength can be fine-tuned through the engineering of the TATA box sequence, core promoter, and upstream activating sequences. Additionally, we identified a previously unreported oleic acid responsive transcription enhancement in the XPR2 upstream activating sequences, which illustrates the complexity of fungal promoters. The promoters engineered here provide new genetic tools for metabolic engineering in Y. lipolytica and provide promoter engineering strategies that may be useful in engineering other non-model fungal systems.

A Toolbox of Diverse Promoters Related to Methanol Utilization: Functionally Verified Parts for Heterologous Pathway Expression in Pichia pastoris

The heterologous expression of biosynthetic pathways for pharmaceutical or fine chemical production requires suitable expression hosts and vectors. In eukaryotes, the pathway flux is typically balanced by stoichiometric fine-tuning of reaction steps by varying the transcript levels of the genes involved. Regulated (inducible) promoters are desirable to allow a separation of pathway expression from cell growth. Ideally, the promoter sequences used should not be identical to avoid loss by recombination. The methylotrophic yeast Pichia pastoris is a commonly used protein production host, and single genes have been expressed at high levels using the methanol-inducible, strong, and tightly regulated promoter of the alcohol oxidase 1 gene (PAOX1). Here, we have studied the regulation of the P. pastoris methanol utilization (MUT) pathway to identify a useful set of promoters that (i) allow high coexpression and (ii) differ in DNA sequence to increase genetic stability. We noticed a pronounced involvement of the pentose phosphate pathway (PPP) and genes involved in the defense of reactive oxygen species (ROS), providing strong promoters that, in part, even outperform PAOX1 and offer novel regulatory profiles. We have applied these tightly regulated promoters together with novel terminators as useful tools for the expression of a heterologous biosynthetic pathway. With the synthetic biology toolbox presented here, P. pastoris is now equipped with one of the largest sets of strong and co-regulated promoters of any microbe, moving it from a protein production host to a general industrial biotechnology host.

Microfluidics and microbial engineering

The combination of microbial engineering and microfluidics is synergistic in nature. For example, microfluidics is benefiting from the outcome of microbial engineering and many reported point-of-care microfluidic devices employ engineered microbes as functional parts for the microsystems. In addition, microbial engineering is facilitated by various microfluidic techniques, due to their inherent strength in high-throughput screening and miniaturization. In this review article, we firstly examine the applications of engineered microbes for toxicity detection, biosensing, and motion generation in microfluidic platforms. Secondly, we look into how microfluidic technologies facilitate the upstream and downstream processes of microbial engineering, including DNA recombination, transformation, target microbe selection, mutant characterization, and microbial function analysis. Thirdly, we highlight an emerging concept in microbial engineering, namely, microbial consortium engineering, where the behavior of a multicultural microbial community rather than that of a single cell/species is delineated. Integrating the disciplines of microfluidics and microbial engineering opens up many new opportunities, for example in diagnostics, engineering of microbial motors, development of portable devices for genetics, high throughput characterization of genetic mutants, isolation and identification of rare/unculturable microbial species, single-cell analysis with high spatio-temporal resolution, and exploration of natural microbial communities.

Engineering cell factories for producing building block chemicals for bio-polymer synthesis

Synthetic polymers are widely used in daily life. Due to increasing environmental concerns related to global warming and the depletion of oil reserves, the development of microbial-based fermentation processes for the production of polymer building block chemicals from renewable resources is desirable to replace current petroleum-based methods. To this end, strains that efficiently produce the target chemicals at high yields and productivity are needed. Recent advances in metabolic engineering have enabled the biosynthesis of polymer compounds at high yield and productivities by governing the carbon flux towards the target chemicals. Using these methods, microbial strains have been engineered to produce monomer chemicals for replacing traditional petroleum-derived aliphatic polymers. These developments also raise the possibility of microbial production of aromatic chemicals for synthesizing high-performance polymers with desirable properties, such as ultraviolet absorbance, high thermal resistance, and mechanical strength. In the present review, we summarize recent progress in metabolic engineering approaches to optimize microbial strains for producing building blocks to synthesize aliphatic and high-performance aromatic polymers.

Improvement of lactic acid production in Saccharomyces cerevisiae by a deletion of ssb1

Polylactic acid (PLA) is an important renewable polymer, but current processes for producing its precursor, lactic acid, suffer from process inefficiencies related to the use of bacterial hosts. Therefore, improving the capacity of Saccharomyces cerevisiae to produce lactic acid is a promising approach to improve industrial production of lactic acid. As one such improvement required, the lactic acid tolerance of yeast must be significantly increased. To enable improved tolerance, we employed an RNAi-mediated genome-wide expression knockdown approach as a means to rapidly identify potential genetic targets. In this approach, several gene knockdown targets were identified which confer increased acid tolerance to S. cerevisiae BY4741, of which knockdown of the ribosome-associated chaperone SSB1 conferred the highest increase (52%). This target was then transferred into a lactic acid-overproducing strain of S. cerevisiae CEN.PK in the form of a knockout and the resulting strain demonstrated up to 33% increased cell growth, 58% increased glucose consumption, and 60% increased L-lactic acid production. As SSB1 contains a close functional homolog SSB2 in yeast, this result was counterintuitive and may point to as-yet-undefined functional differences between SSB1 and SSB2 related to lactic acid production. The final strain produced over 50 g/L of lactic acid in under 60 h of fermentation.

Designing overall stoichiometric conversions and intervening metabolic reactions

Existing computational tools for de novo metabolic pathway assembly, either based on mixed integer linear programming techniques or graph-search applications, generally only find linear pathways connecting the source to the target metabolite. The overall stoichiometry of conversion along with alternate co-reactant (or co-product) combinations is not part of the pathway design. Therefore, global carbon and energy efficiency is in essence fixed with no opportunities to identify more efficient routes for recycling carbon flux closer to the thermodynamic limit. Here, we introduce a two-stage computational procedure that both identifies the optimum overall stoichiometry (i.e., optStoic) and selects for (non-)native reactions (i.e., minRxn/minFlux) that maximize carbon, energy or price efficiency while satisfying thermodynamic feasibility requirements. Implementation for recent pathway design studies identified non-intuitive designs with improved efficiencies. Specifically, multiple alternatives for non-oxidative glycolysis are generated and non-intuitive ways of co-utilizing carbon dioxide with methanol are revealed for the production of C₂₊ metabolites with higher carbon efficiency.

Reconstitution of a 10-gene pathway for synthesis of the plant alkaloid dihydrosanguinarine in Saccharomyces cerevisiae

Benzylisoquinoline alkaloids (BIAs) represent a large class of plant secondary metabolites, including pharmaceuticals such as morphine, codeine and their derivatives. Large-scale production of BIA-based pharmaceuticals is limited to extraction and derivatization of alkaloids that accumulate in planta. Synthesis of BIAs in microbial hosts could bypass such limitations and transform both industrial production of BIAs with recognized value and research into uncharacterized BIAs. Here we reconstitute a 10-gene plant pathway in Saccharomyces cerevisiae that allows for the production of dihydrosanguinarine and its oxidized derivative sanguinarine from (R,S)-norlaudanosoline. Synthesis of dihydrosanguinarine also yields the side-products N-methylscoulerine and N-methylcheilanthifoline, the latter of which has not been detected in plants. This work represents the longest reconstituted alkaloid pathway ever assembled in yeast and demonstrates the feasibility of the production of high-value alkaloids in microbial systems.

MESSI: metabolic engineering target selection and best strain identification tool

Metabolic engineering and synthetic biology are synergistically related fields for manipulating target pathways and designing microorganisms that can act as chemical factories. Saccharomyces cerevisiae’s ideal bioprocessing traits make yeast a very attractive chemical factory for production of fuels, pharmaceuticals, nutraceuticals as well as a wide range of chemicals. However, future attempts of engineering S. cerevisiae’s metabolism using synthetic biology need to move towards more integrative models that incorporate the high connectivity of metabolic pathways and regulatory processes and the interactions in genetic elements across those pathways and processes. To contribute in this direction, we have developed Metabolic Engineering target Selection and best Strain Identification tool (MESSI), a web server for predicting efficient chassis and regulatory components for yeast bio-based production. The server provides an integrative platform for users to analyse ready-to-use public high-throughput metabolomic data, which are transformed to metabolic pathway activities for identifying the most efficient S. cerevisiae strain for the production of a compound of interest. As input MESSI accepts metabolite KEGG IDs or pathway names. MESSI outputs a ranked list of S. cerevisiae strains based on aggregation algorithms. Furthermore, through a genome-wide association study of the metabolic pathway activities with the strains’ natural variation, MESSI prioritizes genes and small variants as potential regulatory points and promising metabolic engineering targets. Users can choose various parameters in the whole process such as (i) weight and expectation of each metabolic pathway activity in the final ranking of the strains, (ii) Weighted AddScore Fuse or Weighted Borda Fuse aggregation algorithm, (iii) type of variants to be included, (iv) variant sets in different biological levels.

Database URL:http://sbb.hku.hk/MESSI/

Cell-surface display of enzymes by the yeast Saccharomyces cerevisiae for synthetic biology

In yeast cell-surface displays, functional proteins, such as cellulases, are genetically fused to an anchor protein and expressed on the cell surface. Saccharomyces cerevisiae, which is often utilized as a cell factory for the production of fuels, chemicals, and proteins, is the most commonly used yeast for cell-surface display. To construct yeast cells with a desired function, such as the ability to utilize cellulose as a substrate for bioethanol production, cell-surface display techniques for the efficient expression of enzymes on the cell membrane need to be combined with metabolic engineering approaches for manipulating target pathways within cells. In this Minireview, we summarize the recent progress of biorefinery fields in the development and application of yeast cell-surface displays from a synthetic biology perspective and discuss approaches for further enhancing cell-surface display efficiency.

Genome-scale modeling for metabolic engineering

We focus on the application of constraint-based methodologies and, more specifically, flux balance analysis in the field of metabolic engineering, and enumerate recent developments and successes of the field. We also review computational frameworks that have been developed with the express purpose of automatically selecting optimal gene deletions for achieving improved production of a chemical of interest. The application of flux balance analysis methods in rational metabolic engineering requires a metabolic network reconstruction and a corresponding in silico metabolic model for the microorganism in question. For this reason, we additionally present a brief overview of automated reconstruction techniques. Finally, we emphasize the importance of integrating metabolic networks with regulatory information-an area which we expect will become increasingly important for metabolic engineering-and present recent developments in the field of metabolic and regulatory integration.

Recent advances in engineering yeast for pharmaceutical protein production

Currently available systems and synthetic biology tools can be applied to yeast engineering for improved biopharmaceutical protein production.

Improving industrial yeast strains: exploiting natural and artificial diversity

Yeasts have been used for thousands of years to make fermented foods and beverages, such as beer, wine, sake, and bread. However, the choice for a particular yeast strain or species for a specific industrial application is often based on historical, rather than scientific grounds. Moreover, new biotechnological yeast applications, such as the production of second-generation biofuels, confront yeast with environments and challenges that differ from those encountered in traditional food fermentations. Together, this implies that there are interesting opportunities to isolate or generate yeast variants that perform better than the currently used strains. Here, we discuss the different strategies of strain selection and improvement available for both conventional and nonconventional yeasts. Exploiting the existing natural diversity and using techniques such as mutagenesis, protoplast fusion, breeding, genome shuffling and directed evolution to generate artificial diversity, or the use of genetic modification strategies to alter traits in a more targeted way, have led to the selection of superior industrial yeasts. Furthermore, recent technological advances allowed the development of high-throughput techniques, such as 'global transcription machinery engineering' (gTME), to induce genetic variation, providing a new source of yeast genetic diversity.

Draft Genome Sequence of the Oleaginous Yeast Yarrowia lipolytica PO1f, a Commonly Used Metabolic Engineering Host

The draft genome sequence of the oleaginous yeast Yarrowia lipolytica stain PO1f, a commonly used metabolic engineering host, is presented here. The approximately 20.3-Mb genome sequence of PO1f will greatly facilitate research efforts in metabolic engineering of Yarrowia lipolytica for value-added chemical production.

Optimization of a yeast RNA interference system for controlling gene expression and enabling rapid metabolic engineering

Reduction of endogenous gene expression is a fundamental operation of metabolic engineering, yet current methods for gene knockdown (i.e., genome editing) remain laborious and slow, especially in yeast. In contrast, RNA interference allows facile and tunable gene knockdown via a simple plasmid transformation step, enabling metabolic engineers to rapidly prototype knockdown strategies in multiple strains before expending significant cost to undertake genome editing. Although RNAi is naturally present in a myriad of eukaryotes, it has only been recently implemented in Saccharomyces cerevisiae as a heterologous pathway and so has not yet been optimized as a metabolic engineering tool. In this study, we elucidate a set of design principles for the construction of hairpin RNA expression cassettes in yeast and implement RNA interference to quickly identify routes for improvement of itaconic acid production in this organism. The approach developed here enables rapid prototyping of knockdown strategies and thus accelerates and reduces the cost of the design-build-test cycle in yeast.

Harnessing Yarrowia lipolytica lipogenesis to create a platform for lipid and biofuel production

Economic feasibility of biosynthetic fuel and chemical production hinges upon harnessing metabolism to achieve high titre and yield. Here we report a thorough genotypic and phenotypic optimization of an oleaginous organism to create a strain with significant lipogenesis capability. Specifically, we rewire Yarrowia lipolytica's native metabolism for superior de novo lipogenesis by coupling combinatorial multiplexing of lipogenesis targets with phenotypic induction. We further complete direct conversion of lipid content into biodiesel. Tri-level metabolic control results in saturated cells containing upwards of 90% lipid content and titres exceeding 25 g l(-1) lipids, which represents a 60-fold improvement over parental strain and conditions. Through this rewiring effort, we advance fundamental understanding of lipogenesis, demonstrate non-canonical environmental and intracellular stimuli and uncouple lipogenesis from nitrogen starvation. The high titres and carbon-source independent nature of this lipogenesis in Y. lipolytica highlight the potential of this organism as a platform for efficient oleochemical production.

Rewiring yeast sugar transporter preference through modifying a conserved protein motif

Utilization of exogenous sugars found in lignocellulosic biomass hydrolysates, such as xylose, must be improved before yeast can serve as an efficient biofuel and biochemical production platform. In particular, the first step in this process, the molecular transport of xylose into the cell, can serve as a significant flux bottleneck and is highly inhibited by other sugars. Here we demonstrate that sugar transport preference and kinetics can be rewired through the programming of a sequence motif of the general form G-G/F-XXX-G found in the first transmembrane span. By evaluating 46 different heterologously expressed transporters, we find that this motif is conserved among functional transporters and highly enriched in transporters that confer growth on xylose. Through saturation mutagenesis and subsequent rational mutagenesis, four transporter mutants unable to confer growth on glucose but able to sustain growth on xylose were engineered. Specifically, Candida intermedia gxs1 Phe(38)Ile(39)Met(40), Scheffersomyces stipitis rgt2 Phe(38) and Met(40), and Saccharomyces cerevisiae hxt7 Ile(39)Met(40)Met(340) all exhibit this phenotype. In these cases, primary hexose transporters were rewired into xylose transporters. These xylose transporters nevertheless remained inhibited by glucose. Furthermore, in the course of identifying this motif, novel wild-type transporters with superior monosaccharide growth profiles were discovered, namely S. stipitis RGT2 and Debaryomyces hansenii 2D01474. These findings build toward the engineering of efficient pentose utilization in yeast and provide a blueprint for reprogramming transporter properties.

Use of expression-enhancing terminators in Saccharomyces cerevisiae to increase mRNA half-life and improve gene expression control for metabolic engineering applications

Control of gene and protein expression of both endogenous and heterologous genes is a key component of metabolic engineering. While a large amount of work has been published characterizing promoters for this purpose, less effort has been exerted to elucidate the role of terminators in yeast. In this study, we characterize over 30 terminators for use in metabolic engineering applications in Saccharomyces cerevisiae and determine mRNA half-life changes to be the major cause of the varied protein and transcript expression level. We demonstrate that the difference in transcript level can be over 6.5-fold even for high strength promoters. The influence of terminator selection is magnified when coupled with a low-expression promoter, with a maximum difference in protein expression of 11-fold between an expression-enhancing terminator and the parent plasmid terminator and over 35-fold difference when compared with a no-terminator baseline. This is the first time that terminators have been investigated in the context of multiple promoters spanning orders of magnitude in activity. Finally, we demonstrate the utility of terminator selection for metabolic engineering by using a mutant xylose isomerase gene as a proof-of-concept. Through pairing an expression-enhancing terminator with a low-expression promoter, we were able to achieve the same phenotypic result as with a promoter considerably higher in strength. Moreover, we can further boost the phenotype of the high-strength promoter by pairing it with an expression-enhancing terminator. This work highlights how terminator elements can be used to control metabolic pathways in the same way that promoters are traditionally used in yeast. Together, this work demonstrates that terminators will be an important part of heterologous gene expression and metabolic engineering for yeast in the future.