Evaluation and comparison of colorimetric outputs for yeast-based biosensors in laboratory and point-of-use settings

Recent research has shown the potential of yeast-based biosensors (YBBs) for point-of-use detection of pathogens and target molecules in saliva, blood, and urine samples. The choice of output can greatly affect the sensitivity, dynamic range, detection time, and ease-of-use of a sensor. For visual detection without the need for additional reagents or machinery, colorimetric outputs have shown great potential. Here, we evaluated the inducible generation of prodeoxyviolacein and proviolacein as colorimetric YBB outputs and benchmarked these against lycopene. The outputs were induced via the yeast mating pathway and were compared on agar plates, in liquid culture, and on paper slips. We found that all three outputs produced comparable pigment intensity on agar plates, making them applicable for bioengineering settings. In liquid media and on paper slips, lycopene resulted in a higher intensity pigment and a decreased time-of-detection.

Saccharomyces cerevisiae strains performing similarly during fermentation of lignocellulosic hydrolysates show pronounced differences in transcriptional stress responses

Improving our understanding of the transcriptional changes of Saccharomyces cerevisiae during fermentation of lignocellulosic hydrolysates is crucial for the creation of more efficient strains to be used in biorefineries. We performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. Many of the differently expressed genes identified among the strains have previously been reported to be important for tolerance to lignocellulosic hydrolysates or inhibitors therein. Our study demonstrates that stress responses typically identified during aerobic conditions such as glutathione metabolism, osmotolerance, and detoxification processes also are important for anaerobic processes. Overall, the transcriptomic responses were largely strain dependent, and we focused our study on similarities and differences in the transcriptomes of the LBCM strains. The expression of sugar transporter-encoding genes was higher in LBCM31 compared with LBCM109 that showed high expression of genes involved in iron metabolism and genes promoting the accumulation of sphingolipids, phospholipids, and ergosterol. These results highlight different evolutionary adaptations enabling S. cerevisiae to strive in lignocellulosic hydrolysates and suggest novel gene targets for improving fermentation performance and robustness.

IMPORTANCE

The need for sustainable alternatives to oil-based production of biochemicals and biofuels is undisputable. Saccharomyces cerevisiae is the most commonly used industrial fermentation workhorse. The fermentation of lignocellulosic hydrolysates, second-generation biomass unsuited for food and feed, is still hampered by lowered productivities as the raw material is inhibitory for the cells. In order to map the genetic responses of different S. cerevisiae strains, we performed RNA sequencing of a CEN.PK laboratory strain, two industrial strains (KE6-12 and Ethanol Red), and two wild-type isolates of the LBCM collection when cultivated anaerobically in wheat straw hydrolysate. While the response to inhibitors of S. cerevisiae has been studied earlier, this has in previous studies been done in aerobic conditions. The transcriptomic analysis highlights different evolutionary adaptations among the different S. cerevisiae strains and suggests novel gene targets for improving fermentation performance and robustness.

Fine-tuning of p-coumaric acid synthesis to increase (2S)-naringenin production in yeast

(2S)-Naringenin is a key precursor for biosynthesis of various high-value flavonoids and possesses a variety of nutritional and pharmaceutical properties on human health. Systematic optimization approaches have been employed to improve (2S)-naringenin production in different microbial hosts. However, very few studies have focused on the spatiotemporal distribution of (2S)-naringenin and the related pathway intermediate p-coumaric acid, which is an important factor for efficient production. Here, we first optimized the (2S)-naringenin biosynthetic pathway by alleviating the bottleneck downstream of p-coumaric acid and increasing malonyl-CoA supply, which improved (2S)-naringenin production but significant accumulation of p-coumaric acid still existed extracellularly. We thus established a dual dynamic control system through combining a malonyl-CoA biosensor regulator and an RNAi strategy, to autonomously control the synthesis of p-coumaric acid with the supply of malonyl-CoA. Furthermore, screening potential transporters led to identification of Pdr12 for improved (2S)-naringenin production and reduced accumulation of p-coumaric acid. Finally, a titer of 2.05 g/L (2S)-naringenin with negligible accumulation of p-coumaric acid was achieved in a fed batch fermentation. Our work highlights the importance of systematic control of pathway intermediates for efficient microbial production of plant natural products.

Expanding the genetic toolbox of Rhodotorula toruloides by identification and validation of six novel promoters induced or repressed under nitrogen starvation

BACKGROUND

The non-conventional yeast Rhodotorula toruloides is an emerging host organism in biotechnology by merit of its natural capacity to accumulate high levels of carotenoids and intracellular storage lipids from a variety of carbon sources. While the number of genetic engineering strategies that employ R. toruloides is increasing, the lack of genetic tools available for modification of this yeast is still limiting strain development. For instance, several strong, constitutive R. toruloides promoters have been characterized, but to date, only five inducible promoters have been identified. Although nitrogen-limited cultivation conditions are commonly used to induce lipid accumulation in this yeast, no promoters regulated by nitrogen starvation have been described for R. toruloides.

RESULTS

In this study, we used a combination of genomics and transcriptomics methods to identify novel R. toruloides promoter sequences that are either inducible or repressible by nitrogen starvation. RNA sequencing was used to assess gene expression in the recently isolated strain R. toruloides BOT-A2 during exponential growth and during nitrogen starvation, when cultivated with either glucose or xylose as the carbon source. The genome of BOT-A2 was sequenced using a combination of long- and short-read sequencing and annotated with support of the RNAseq data. Differential expression analysis was used to identify genes with a |log2 fold change|≥ 2 when comparing their expression during nitrogen depletion to that during exponential growth. The promoter regions from 16 of these genes were evaluated for their ability to drive the expression of a fluorescent reporter gene. Three promoters that were clearly upregulated under nitrogen starvation and three that were downregulated were selected and further characterized. One promoter, derived from gene RTBOTA2_003877, was found to function like an on-off switch, as it was only upregulated under full nitrogen depletion and downregulated in the presence of the nitrogen source.

CONCLUSIONS

Six new R. toruloides promoters that were either upregulated or downregulated under nitrogen-starvation were identified. These substantially contribute to the available promoters when engineering this organism and are foreseen to be particularly useful for future engineering strategies requiring specific regulation of target genes in accordance with nitrogen availability.

Multiplexed Guide RNA Expression Leads to Increased Mutation Frequency in Targeted Window Using a CRISPR-Guided Error-Prone DNA Polymerase in Saccharomyces cerevisiae

Clustered regularly interspaced short palindromic repeats (CRISPR)-Cas9 technology, with its ability to target a specific DNA locus using guide RNAs (gRNAs), is particularly suited for targeted mutagenesis. The targeted diversification of nucleotides in Saccharomyces cerevisiae using a CRISPR-guided error-prone DNA polymerase─called yEvolvR─was recently reported. Here, we investigate the effect of multiplexed expression of gRNAs flanking a short stretch of DNA on reversion and mutation frequencies using yEvolvR. Phenotypic assays demonstrate that higher reversion frequencies are observed when expressing multiple gRNAs simultaneously. Next generation sequencing reveals a synergistic effect of multiple gRNAs on mutation frequencies, which is more pronounced in a mutant with a partially defective DNA mismatch repair system. Additionally, we characterize a galactose-inducible yEvolvR, which enables temporal control of mutagenesis. This study demonstrates that multiplex expression of gRNAs and induction of mutagenesis greatly improves the capabilities of yEvolvR for generation of genetic libraries in vivo.

Targeted In Vivo Mutagenesis in Yeast Using CRISPR/Cas9 and Hyperactive Cytidine and Adenine Deaminases

Directed evolution is a preferred strategy to improve the function of proteins such as enzymes that act as bottlenecks in metabolic pathways. Common directed evolution approaches rely on error-prone PCR-based libraries where the number of possible variants is usually limited by cellular transformation efficiencies. Targeted in vivo mutagenesis can advance directed evolution approaches and help to overcome limitations in library generation. In the current study, we aimed to develop a high-efficiency time-controllable targeted mutagenesis toolkit in the yeast Saccharomyces cerevisiae by employing the CRISPR/Cas9 technology. To that end, we fused the dCas9 protein with hyperactive variants of adenine and cytidine deaminases aiming to create an inducible CRISPR-based mutagenesis tool targeting a specific DNA sequence in vivo with extended editing windows and high mutagenesis efficiency. We also investigated the effect of guide RNA multiplexing on the mutagenesis efficiency both phenotypically and on the DNA level.

Directed evolution of a wax ester synthase for production of fatty acid ethyl esters in Saccharomyces cerevisiae

Wax ester synthases (WSs) utilize a fatty alcohol and a fatty acyl-coenzyme A (activated fatty acid) to synthesize the corresponding wax ester. There is much interest in developing novel cell factories that can produce shorter esters, e.g., fatty acid ethyl esters (FAEEs), with properties similar to biodiesel in order to use these as transportation fuels. However, ethanol is a poor substrate for WSs, and this may limit the biosynthesis of FAEEs. Here, we implemented a random mutagenesis approach to enhance the catalytic efficiency of a WS from Marinobacter hydrocarbonoclasticus (MhWS2, encoded by the ws2 gene). Our selection system was based on FAEE formation serving as a detoxification mechanism for excessive oleate, where high WS activity was essential for a storage-lipid free yeast to survive. A random mutagenesis library of ws2 was used to transform the storage-lipid free yeast, and mutants could be selected by plating the transformants on oleate containing plates. The variants encoding WS with improved activity were sequenced, and an identified point mutation translated into the residue substitution at position A344 was discovered to substantially increase the selectivity of MhWS2 toward ethanol and other shorter alcohols. Structural modeling indicated that an A344T substitution might affect the alcohol selectivity due to change of both steric effects and polarity changes near the active site. This work not only provides a new WS variant with altered selectivity to shorter alcohols but also presents a new high-throughput selection system to isolate WSs with a desired selectivity. KEY POINTS: • The work provides WS variants with altered substrate preference for shorter alcohols • A novel method was developed for directed evolution of WS of desired selectivity.

Functional genome annotation and transcriptome analysis of Pseudozyma hubeiensis BOT-O, an oleaginous yeast that utilizes glucose and xylose at equal rates

Pseudozyma hubeiensis is a basidiomycete yeast that has the highly desirable traits for lignocellulose valorisation of being equally efficient at utilization of glucose and xylose, and capable of their co-utilization. The species has previously mainly been studied for its capacity to produce secreted biosurfactants in the form of mannosylerythritol lipids, but it is also an oleaginous species capable of accumulating high levels of triacylglycerol storage lipids during nutrient starvation. In this study, we aimed to further characterize the oleaginous nature of P. hubeiensis by evaluating metabolism and gene expression responses during storage lipid formation conditions with glucose or xylose as a carbon source. The genome of the recently isolated P. hubeiensis BOT-O strain was sequenced using MinION long-read sequencing and resulted in the most contiguous P. hubeiensis assembly to date with 18.95 Mb in 31 contigs. Using transcriptome data as experimental support, we generated the first mRNA-supported P. hubeiensis genome annotation and identified 6540 genes. 80% of the predicted genes were assigned functional annotations based on protein homology to other yeasts. Based on the annotation, key metabolic pathways in BOT-O were reconstructed, including pathways for storage lipids, mannosylerythritol lipids and xylose assimilation. BOT-O was confirmed to consume glucose and xylose at equal rates, but during mixed glucose-xylose cultivation glucose was found to be taken up faster. Differential expression analysis revealed that only a total of 122 genes were significantly differentially expressed at a cut-off of |log₂ fold change| ≥ 2 when comparing cultivation on xylose with glucose, during exponential growth and during nitrogen-starvation. Of these 122 genes, a core-set of 24 genes was identified that were differentially expressed at all time points. Nitrogen-starvation resulted in a larger transcriptional effect, with a total of 1179 genes with significant expression changes at the designated fold change cut-off compared with exponential growth on either glucose or xylose.

A p-Coumaroyl-CoA Biosensor for Dynamic Regulation of Naringenin Biosynthesis in Saccharomyces cerevisiae

In vivo biosensors that can convert metabolite concentrations into measurable output signals are valuable tools for high-throughput screening and dynamic pathway control in the field of metabolic engineering. Here, we present a novel biosensor in Saccharomyces cerevisiae that is responsive to p-coumaroyl-CoA, a central precursor of many flavonoids. The sensor is based on the transcriptional repressor CouR from Rhodopseudomonas palustris and was applied in combination with a previously developed malonyl-CoA biosensor for dual regulation of p-coumaroyl-CoA synthesis within the naringenin production pathway. Using this approach, we obtained a naringenin titer of 47.3 mg/L upon external precursor feeding, representing a 15-fold increase over the nonregulated system.

Genetically Encoded Whole Cell Biosensor for Drug Discovery of HIF-1 Interaction Inhibitors

The heterodimeric transcription factor, hypoxia inducible factor-1 (HIF-1), is an important anticancer target as it supports the adaptation and response of tumors to hypoxia. Here, we optimized the repressed transactivator yeast two-hybrid system to further develop it as part of a versatile yeast-based drug discovery platform and validated it using HIF-1. We demonstrate both fluorescence-based and auxotrophy-based selections that could detect HIF-1α/HIF-1β dimerization inhibition. The engineered genetic selection is tunable and able to differentiate between strong and weak interactions, shows a large dynamic range, and is stable over different growth phases. Furthermore, we engineered mechanisms to control for cellular activity and off-target drug effects. We thoroughly characterized all parts of the biosensor system and argue this tool will be generally applicable to a wide array of protein-protein interaction targets. We anticipate this biosensor will be useful as part of a drug discovery platform, particularly when screening DNA-encoded new modality drugs.

Identification of acetic acid sensitive strains through biosensor-based screening of a Saccharomyces cerevisiae CRISPRi library

Background

Acetic acid tolerance is crucial for the development of robust cell factories for conversion of lignocellulosic hydrolysates that typically contain high levels of acetic acid. Screening mutants for growth in medium with acetic acid is an attractive way to identify sensitive variants and can provide novel insights into the complex mechanisms regulating the acetic acid stress response.

Results

An acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1, was used to screen a CRISPRi yeast strain library where dCas9-Mxi was set to individually repress each essential or respiratory growth essential gene. Fluorescence-activated cell sorting led to the enrichment of a population of cells with higher acetic acid retention. These cells with higher biosensor signal were demonstrated to be more sensitive to acetic acid. Biosensor-based screening of the CRISPRi library strains enabled identification of strains with increased acetic acid sensitivity: strains with gRNAs targeting TIF34, MSN5, PAP1, COX10 or TRA1.

Conclusions

This study demonstrated that biosensors are valuable tools for screening and monitoring acetic acid tolerance in yeast. Fine-tuning the expression of essential genes can lead to altered acetic acid tolerance.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01938-7.

CRISPR/Cas9-mediated point mutations improve α-amylase secretion in Saccharomyces cerevisiae

The rapid expansion of the application of pharmaceutical proteins and industrial enzymes requires robust microbial workhorses for high protein production. The budding yeast Saccharomyces cerevisiae is an attractive cell factory due to its ability to perform eukaryotic post-translational modifications and to secrete proteins. Many strategies have been used to engineer yeast platform strains for higher protein secretion capacity. Herein, we investigated a line of strains that have previously been selected after UV random mutagenesis for improved α-amylase secretion. A total of 42 amino acid altering point mutations identified in this strain line were reintroduced into the parental strain AAC to study their individual effects on protein secretion. These point mutations included missense mutations (amino acid substitution), nonsense mutations (stop codon generation), and frameshift mutations. For comparison, single gene deletions for the corresponding target genes were also performed in this study. A total of 11 point mutations and seven gene deletions were found to effectively improve α-amylase secretion. These targets were involved in several bioprocesses, including cellular stresses, protein degradation, transportation, mRNA processing and export, DNA replication, and repair, which indicates that the improved protein secretion capacity in the evolved strains is the result of the interaction of multiple intracellular processes. Our findings will contribute to the construction of novel cell factories for recombinant protein secretion.

Reconstruction of a catalogue of genome-scale metabolic models with enzymatic constraints using GECKO 2.0

Genome-scale metabolic models (GEMs) have been widely used for quantitative exploration of the relation between genotype and phenotype. Streamlined integration of enzyme constraints and proteomics data into such models was first enabled by the GECKO toolbox, allowing the study of phenotypes constrained by protein limitations. Here, we upgrade the toolbox in order to enhance models with enzyme and proteomics constraints for any organism with a compatible GEM reconstruction. With this, enzyme-constrained models for the budding yeasts Saccharomyces cerevisiae, Yarrowia lipolytica and Kluyveromyces marxianus are generated to study their long-term adaptation to several stress factors by incorporation of proteomics data. Predictions reveal that upregulation and high saturation of enzymes in amino acid metabolism are common across organisms and conditions, suggesting the relevance of metabolic robustness in contrast to optimal protein utilization as a cellular objective for microbial growth under stress and nutrient-limited conditions. The functionality of GECKO is expanded with an automated framework for continuous and version-controlled update of enzyme-constrained GEMs, also producing such models for Escherichia coli and Homo sapiens. In this work, we facilitate the utilization of enzyme-constrained GEMs in basic science, metabolic engineering and synthetic biology purposes.

Dataset for suppressors of amyloid-β toxicity and their functions in recombinant protein production in yeast

The production of recombinant proteins at high levels often induces stress-related phenotypes by protein misfolding or aggregation. These are similar to those of the yeast Alzheimer's disease (AD) model in which amyloid-β peptides (Aβ42) were accumulated [1], [2]. We have previously identified suppressors of Aβ42 cytotoxicity via the genome-wide synthetic genetic array (SGA) [3] and here we use them as metabolic engineering targets to evaluate their potentiality on recombinant protein production in yeast Saccharomyces cerevisiae. In order to investigate the mechanisms linking the genetic modifications to the improved recombinant protein production, we perform systems biology approaches (transcriptomics and proteomics) on the resulting strain and intermediate strains. The RNAseq data are preprocessed by the nf-core/RNAseq pipeline and analyzed using the Platform for Integrative Analysis of Omics (PIANO) package [4]. The quantitative proteome is analyzed on an Orbitrap Fusion Lumos mass spectrometer interfaced with an Easy-nLC1200 liquid chromatography (LC) system. LC-MS data files are processed by Proteome Discoverer version 2.4 with Mascot 2.5.1 as a database search engine. The original data presented in this work can be found in the research paper titled “Suppressors of Amyloid-β Toxicity Improve Recombinant Protein Production in yeast by Reducing Oxidative Stress and Tuning Cellular Metabolism”, by Chen et al. [5].

Identification of a novel gene required for competitive growth at high temperature in the thermotolerant yeast Kluyveromyces marxianus

It is important to understand the basis of thermotolerance in yeasts to broaden their application in industrial biotechnology. The capacity to run bioprocesses at temperatures above 40 °C is of great interest but this is beyond the growth range of most of the commonly used yeast species. In contrast, some industrial yeasts such as Kluyveromyces marxianus can grow at temperatures of 45 °C or higher. Such species are valuable for direct use in industrial biotechnology and as a vehicle to study the genetic and physiological basis of yeast thermotolerance. In previous work, we reported that evolutionarily young genes disproportionately changed expression when yeast were growing under stressful conditions and postulated that such genes could be important for long-term adaptation to stress. Here, we tested this hypothesis in K. marxianus by identifying and studying species-specific genes that showed increased expression during high-temperature growth. Twelve such genes were identified and 11 were successfully inactivated using CRISPR-mediated mutagenesis. One gene, KLMX_70384, is required for competitive growth at high temperature, supporting the hypothesis that evolutionary young genes could play roles in adaptation to harsh environments. KLMX_70384 is predicted to encode an 83 aa peptide, and RNA sequencing and ribo-sequencing were used to confirm transcription and translation of the gene. The precise function of KLMX_70384 remains unknown but some features are suggestive of RNA-binding activity. The gene is located in what was previously considered an intergenic region of the genome, which lacks homologues in other yeasts or in databases. Overall, the data support the hypothesis that genes that arose de novo in K. marxianus after the speciation event that separated K. marxianus and K. lactis contribute to some of its unique traits.

Engineering Saccharomyces cerevisiae for the production and secretion of Affibody molecules

Background

Affibody molecules are synthetic peptides with a variety of therapeutic and diagnostic applications. To date, Affibody molecules have mainly been produced by the bacterial production host Escherichia coli. There is an interest in exploring alternative production hosts to identify potential improvements in terms of yield, ease of production and purification advantages. In this study, we evaluated the feasibility of Saccharomyces cerevisiae as a production chassis for this group of proteins.

Results

We examined the production of three different Affibody molecules in S. cerevisiae and found that these Affibody molecules were partially degraded. An albumin-binding domain, which may be attached to the Affibody molecules to increase their half-life, was identified to be a substrate for several S. cerevisiae proteases. We tested the removal of three vacuolar proteases, proteinase A, proteinase B and carboxypeptidase Y. Removal of one of these, proteinase A, resulted in intact secretion of one of the targeted Affibody molecules. Removal of either or both of the two additional proteases, carboxypeptidase Y and proteinase B, resulted in intact secretion of the two remaining Affibody molecules. The produced Affibody molecules were verified to bind their target, human HER3, as potently as the corresponding molecules produced in E. coli in an in vitro surface-plasmon resonance binding assay. Finally, we performed a fed-batch fermentation with one of the engineered protease-deficient S. cerevisiae strains and achieved a protein titer of 530 mg Affibody molecule/L.

Conclusion

This study shows that engineered S. cerevisiae has a great potential as a production host for recombinant Affibody molecules, reaching a high titer, and for proteins where endotoxin removal could be challenging, the use of S. cerevisiae obviates the need for endotoxin removal from protein produced in E. coli.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12934-022-01761-0.

Saccharomyces cerevisiae as a Heterologous Host for Natural Products

Cell factories can provide a sustainable supply of natural products with applications as pharmaceuticals, food-additives or biofuels. Besides being an important model organism for eukaryotic systems, Saccharomyces cerevisiae is used as a chassis for the heterologous production of natural products. Its success as a cell factory can be attributed to the vast knowledge accumulated over decades of research, its overall ease of engineering and its robustness. Many methods and toolkits have been developed by the yeast metabolic engineering community with the aim of simplifying and accelerating the engineering process.In this chapter, a range of methodologies are highlighted, which can be used to develop novel natural product cell factories or to improve titer, rate and yields of an existing cell factory with the goal of developing an industrially relevant strain. The addressed topics are applicable for different stages of a cell factory engineering project and include the choice of a natural product platform strain, expression cassette design for heterologous or native genes, basic and advanced genetic engineering strategies, and library screening methods using biosensors. The many engineering methods available and the examples of yeast cell factories underline the importance and future potential of this host for industrial production of natural products.

An Overview on Selection Marker Genes for Transformation of Saccharomyces cerevisiae

For genetic manipulation of yeast, numerous selection marker genes have been employed. These include prototrophic markers, markers conferring drug resistance, autoselection markers, and counterselectable markers. This chapter describes the different classes of selection markers and provides a number of examples for different applications.

Expansion of the Yeast Modular Cloning Toolkit for CRISPR-Based Applications, Genomic Integrations and Combinatorial Libraries

Standardisation of genetic parts has become a topic of increasing interest over the last decades. The promise of simplifying molecular cloning procedures, while at the same time making them more predictable and reproducible has led to the design of several biological standards, one of which is modular cloning (MoClo). The Yeast MoClo toolkit provides a large library of characterised genetic parts combined with a comprehensive and flexible assembly strategy. Here we aimed to (1) simplify the adoption of the standard by providing a simple design tool for including new parts in the MoClo library, (2) characterise the toolkit further by demonstrating the impact of a BglII site in promoter parts on protein expression, and (3) expand the toolkit to enable efficient construction of gRNA arrays, marker-less integration cassettes and combinatorial libraries. These additions make the toolkit more applicable for common engineering tasks and will further promote its adoption in the yeast biological engineering community.

Rational gRNA design based on transcription factor binding data

The clustered regularly interspaced short palindromic repeats (CRISPR)/Cas9 system has become a standard tool in many genome engineering endeavors. The endonuclease-deficient version of Cas9 (dCas9) is also a powerful programmable tool for gene regulation. In this study, we made use of Saccharomyces cerevisiae transcription factor (TF) binding data to obtain a better understanding of the interplay between TF binding and binding of dCas9 fused to an activator domain, VPR. More specifically, we targeted dCas9–VPR toward binding sites of Gcr1–Gcr2 and Tye7 present in several promoters of genes encoding enzymes engaged in the central carbon metabolism. From our data, we observed an upregulation of gene expression when dCas9–VPR was targeted next to a TF binding motif, whereas a downregulation or no change was observed when dCas9 was bound on a TF motif. This suggests a steric competition between dCas9 and the specific TF. Integrating TF binding data, therefore, proved to be useful for designing guide RNAs for CRISPR interference or CRISPR activation applications.

A single chromosome strain of S. cerevisiae exhibits diminished ethanol metabolism and tolerance

BACKGROUND

Eukaryotic organisms, like the model yeast S. cerevisiae, have linear chromosomes that facilitate organization and protection of nuclear DNA. A recent work described a stepwise break/repair method that enabled fusion of the 16 chromosomes of S. cerevisiae into a single large chromosome. Construction of this strain resulted in the removal of 30 of 32 telomeres, over 300 kb of subtelomeric DNA, and 107 subtelomeric ORFs. Despite these changes, characterization of the single chromosome strain uncovered modest phenotypes compared to a reference strain.

RESULTS

This study further characterized the single chromosome strain and found that it exhibited a longer lag phase, increased doubling time, and lower final biomass concentration compared with a reference strain when grown on YPD. These phenotypes were amplified when ethanol was added to the medium or used as the sole carbon source. RNAseq analysis showed poor induction of genes involved in diauxic shift, ethanol metabolism, and fatty-acid ß-oxidation during growth on ethanol compared to the reference strain. Enzyme-constrained metabolic modeling identified decreased flux through the enzymes that are encoded by these poorly induced genes as a likely cause of diminished biomass accumulation. The diminished growth on ethanol for the single chromosome strain was rescued by nicotinamide, an inhibitor of sirtuin family deacetylases, which have been shown to silence gene expression in heterochromatic regions.

CONCLUSIONS

Our results indicate that sirtuin-mediated silencing in the single chromosome strain interferes with growth on non-fermentable carbon sources. We propose that the removal of subtelomeric DNA that would otherwise be bound by sirtuins leads to silencing at other loci in the single chromosome strain. Further, we hypothesize that the poorly induced genes in the single chromosome strain during ethanol growth could be silenced by sirtuins in wildtype S. cerevisiae during growth on glucose.

Development of an Haa1-based biosensor for acetic acid sensing in Saccharomyces cerevisiae

Acetic acid is one of the main inhibitors of lignocellulosic hydrolysates and acetic acid tolerance is crucial for the development of robust cell factories for conversion of biomass. As a precursor of acetyl-coenzyme A, it also plays an important role in central carbon metabolism. Thus, monitoring acetic acid levels is a crucial aspect when cultivating yeast. Transcription factor-based biosensors represent useful tools to follow metabolite concentrations. Here, we present the development of an acetic acid biosensor based on the Saccharomyces cerevisiae transcription factor Haa1 that upon binding to acetic acid relocates to the nucleus. In the biosensor, a synthetic transcription factor consisting of Haa1 and BM3R1 from Bacillus megaterium was used to control expression of a reporter gene under a promoter containing BM3R1 binding sites. The biosensor did not drive expression under a promoter containing Haa1 binding sites and responded to acetic acid over a linear range spanning from 10 to 60 mM. To validate its applicability, the biosensor was integrated into acetic acid-producing strains. A direct correlation between biosensor output and acetic acid production was detected. The developed biosensor enables high-throughput screening of strains producing acetic acid and could also be used to investigate acetic acid-tolerant strain libraries.

Expression of antibody fragments in Saccharomyces cerevisiae strains evolved for enhanced protein secretion

Monoclonal antibodies, antibody fragments and fusion proteins derived thereof have revolutionized the practice of medicine. Major challenges faced by the biopharmaceutical industry are however high production costs, long processing times and low productivities associated with their production in mammalian cell lines. The yeast Saccharomyces cerevisiae, a well-characterized eukaryotic cell factory possessing the capacity of post-translational modifications, has been industrially exploited as a secretion host for production of a range of products, including pharmaceuticals. However, due to the incompatible surface glycosylation, few antibody molecules have been functionally expressed in S. cerevisiae. Here, three non-glycosylated antibody fragments from human and the Camelidae family were chosen for expression in a S. cerevisiae strain (HA) previously evolved for high α-amylase secretion. These included the Fab fragment Ranibizumab (Ran), the scFv peptide Pexelizumab (Pex), and a nanobody consisting of a single V-type domain (Nan). Both secretion and biological activities of the antibody fragments were confirmed. In addition, the secretion level of each protein was compared in the wild type (LA) and two evolved strains (HA and MA) with different secretory capacities. We found that the secretion of Ran and Nan was positively correlated with the strains' secretory capacity, while Pex was most efficiently secreted in the parental strain. To investigate the mechanisms for different secretion abilities in these selected yeast strains for the different antibody fragments, RNA-seq analysis was performed. The results showed that several bioprocesses were significantly enriched for differentially expressed genes when comparing the enriched terms between HA.Nan vs. LA.Nan and HA.Pex vs. LA.Pex, including amino acid metabolism, protein synthesis, cell cycle and others, which indicates that there are unique physiological needs for each antibody fragment secretion.

GTR 2.0: gRNA-tRNA Array and Cas9-NG Based Genome Disruption and Single-Nucleotide Conversion in Saccharomyces cerevisiae

Targeted genome disruptions and single-nucleotide conversions with the CRISPR/Cas system have greatly facilitated the development of gene therapy, basic biological research, and synthetic biology. With vast progress in this field, there are still aspects to be optimized, including the target range, the ability to multiplex, the mutation efficiency and specificity, as well as the requirement of adjusting protospacer adjacent motifs (PAMs). Here, we report the development of a highly efficient genome disruption and single-nucleotide conversion tool with a gRNA-tRNA array and SpCas9-NG (GTR 2.0). We performed gene disruptions in yeast cells covering all 16 possible NGN PAMs and all 12 possible single-nucleotide conversions (N to N) with near 100% efficiencies. Moreover, we applied GTR 2.0 for multiplexed single-nucleotide conversions, resulting in 66.67% mutation efficiency in simultaneous generation of 4 single-nucleotide conversions in one gene, as well as 100% mutation efficiency for simultaneously generating 2 single-nucleotide conversions in two different genes. GTR 2.0 will substantially expand the scope, efficiency, and capabilities of yeast genome editing, and will be a versatile and invaluable addition to the toolbox of synthetic biology and metabolic engineering.

Evaluating accessibility, usability and interoperability of genome-scale metabolic models for diverse yeasts species

Metabolic network reconstructions have become an important tool for probing cellular metabolism in the field of systems biology. They are used as tools for quantitative prediction but also as scaffolds for further knowledge contextualization. The yeast Saccharomyces cerevisiae was one of the first organisms for which a genome-scale metabolic model (GEM) was reconstructed, in 2003, and since then 45 metabolic models have been developed for a wide variety of relevant yeasts species. A systematic evaluation of these models revealed that-despite this long modeling history-the sequential process of tracing model files, setting them up for basic simulation purposes and comparing them across species and even different versions, is still not a generalizable task. These findings call the yeast modeling community to comply to standard practices on model development and sharing in order to make GEMs accessible and useful for a wider public.

Transcriptomic response of Saccharomyces cerevisiae to octanoic acid production

The medium-chain fatty acid octanoic acid is an important platform compound widely used in industry. The microbial production from sugars in Saccharomyces cerevisiae is a promising alternative to current non-sustainable production methods, however, titers need to be further increased. To achieve this, it is essential to have in-depth knowledge about the cell physiology during octanoic acid production. To this end, we collected the first RNA-Seq data of an octanoic acid producer strain at three time points during fermentation. The strain produced higher levels of octanoic acid and increased levels of fatty acids of other chain lengths (C6-C18) but showed decreased growth compared to the reference. Furthermore, we show that the here analyzed transcriptomic response to internally produced octanoic acid is notably distinct from a wild type's response to externally supplied octanoic acid as reported in previous publications. By comparing the transcriptomic response of different sampling times, we identified several genes that we subsequently overexpressed and knocked out, respectively. Hereby we identified RPL40B, to date unknown to play a role in fatty acid biosynthesis or medium-chain fatty acid tolerance. Overexpression of RPL40B led to an increase in octanoic acid titers by 40%.

Production of 10-methyl branched fatty acids in yeast

BACKGROUND

Despite the environmental value of biobased lubricants, they account for less than 2% of global lubricant use due to poor thermo-oxidative stability arising from the presence of unsaturated double bonds. Methyl branched fatty acids (BFAs), particularly those with branching near the acyl-chain mid-point, are a high-performance alternative to existing vegetable oils because of their low melting temperature and full saturation.

RESULTS

We cloned and characterized two pathways to produce 10-methyl BFAs isolated from actinomycetes and γ-proteobacteria. In the two-step bfa pathway of actinomycetes, BfaB methylates Δ9 unsaturated fatty acids to form 10-methylene BFAs, and subsequently, BfaA reduces the double bond to produce a fully saturated 10-methyl branched fatty acid. A BfaA-B fusion enzyme increased the conversion efficiency of 10-methyl BFAs. The ten-methyl palmitate production (tmp) pathway of γ-proteobacteria produces a 10-methylene intermediate, but the TmpA putative reductase was not active in E. coli or yeast. Comparison of BfaB and TmpB activities revealed a range of substrate specificities from C14-C20 fatty acids unsaturated at the Δ9, Δ10 or Δ11 position. We demonstrated efficient production of 10-methylene and 10-methyl BFAs in S. cerevisiae by secretion of free fatty acids and in Y. lipolytica as triacylglycerides, which accumulated to levels more than 35% of total cellular fatty acids.

CONCLUSIONS

We report here the characterization of a set of enzymes that can produce position-specific methylene and methyl branched fatty acids. Yeast expression of bfa enzymes can provide a platform for the large-scale production of branched fatty acids suitable for industrial and consumer applications.

Does co-expression of Yarrowia lipolytica genes encoding Yas1p, Yas2p and Yas3p make a potential alkane-responsive biosensor in Saccharomyces cerevisiae?

Alkane-based biofuels are desirable to produce at a commercial scale as these have properties similar to current petroleum-derived transportation fuels. Rationally engineering microorganisms to produce a desirable compound, such as alkanes, is, however, challenging. Metabolic engineers are therefore increasingly implementing evolutionary engineering approaches combined with high-throughput screening tools, including metabolite biosensors, to identify productive cells. Engineering Saccharomyces cerevisiae to produce alkanes could be facilitated by using an alkane-responsive biosensor, which can potentially be developed from the native alkane-sensing system in Yarrowia lipolytica, a well-known alkane-assimilating yeast. This putative alkane-sensing system is, at least, based on three different transcription factors (TFs) named Yas1p, Yas2p and Yas3p. Although this system is not fully elucidated in Y. lipolytica, we were interested in evaluating the possibility of translating this system into an alkane-responsive biosensor in S. cerevisiae. We evaluated the alkane-sensing system in S. cerevisiae by developing one sensor based on the native Y. lipolytica ALK1 promoter and one sensor based on the native S. cerevisiae CYC1 promoter. In both systems, we found that the TFs Yas1p, Yas2p and Yas3p do not seem to act in the same way as these have been reported to do in their native host. Additional analysis of the TFs suggests that more knowledge regarding their mechanism is needed before a potential alkane-responsive sensor based on the Y. lipolytica system can be established in S. cerevisiae.

Deep learning suggests that gene expression is encoded in all parts of a co-evolving interacting gene regulatory structure

Understanding the genetic regulatory code governing gene expression is an important challenge in molecular biology. However, how individual coding and non-coding regions of the gene regulatory structure interact and contribute to mRNA expression levels remains unclear. Here we apply deep learning on over 20,000 mRNA datasets to examine the genetic regulatory code controlling mRNA abundance in 7 model organisms ranging from bacteria to Human. In all organisms, we can predict mRNA abundance directly from DNA sequence, with up to 82% of the variation of transcript levels encoded in the gene regulatory structure. By searching for DNA regulatory motifs across the gene regulatory structure, we discover that motif interactions could explain the whole dynamic range of mRNA levels. Co-evolution across coding and non-coding regions suggests that it is not single motifs or regions, but the entire gene regulatory structure and specific combination of regulatory elements that define gene expression levels.

The transcription factor Leu3 shows differential binding behavior in response to changing leucine availability

The main transcriptional regulator of leucine biosynthesis in the yeast Saccharomyces cerevisiae is the transcription factor Leu3. It has previously been reported that Leu3 always binds to its target genes, but requires activation to induce their expression. In a recent large-scale study of high-resolution transcription factor binding site identification, we showed that Leu3 has divergent binding sites in different cultivation conditions, thereby questioning the results of earlier studies. Here, we present a follow-up study using chromatin immunoprecipitation followed by sequencing (ChIP-seq) to investigate the influence of leucine supplementation on Leu3 binding activity and strength. With this new data set we are able to show that Leu3 exhibits changes in binding activity in response to changing levels of leucine availability.

Stress-induced expression is enriched for evolutionarily young genes in diverse budding yeasts

The Saccharomycotina subphylum (budding yeasts) spans 400 million years of evolution and includes species that thrive in diverse environments. To study niche-adaptation, we identify changes in gene expression in three divergent yeasts grown in the presence of various stressors. Duplicated and non-conserved genes are significantly more likely to respond to stress than genes that are conserved as single-copy orthologs. Next, we develop a sorting method that considers evolutionary origin and duplication timing to assign an evolutionary age to each gene. Subsequent analysis reveals that genes that emerged in recent evolutionary time are enriched amongst stress-responsive genes for each species. This gene expression pattern suggests that budding yeasts share a stress adaptation mechanism, whereby selective pressure leads to functionalization of young genes to improve growth in adverse conditions. Further characterization of young genes from species that thrive in harsh environments can inform the design of more robust strains for biotechnology.

Fermentation parameters of industrial processes are often not the ideal growth conditions for industrial microbes. Here, the authors reveal that young genes are more responsive to environmental stress than ancient genes using a new gene age assignment method and provide targeted genes for metabolic engineering.

Engineering Saccharomyces cerevisiae cells for production of fatty acid-derived biofuels and chemicals

The yeast Saccharomyces cerevisiae is a widely used cell factory for the production of fuels and chemicals, in particular ethanol, a biofuel produced in large quantities. With a need for high-energy-density fuels for jets and heavy trucks, there is, however, much interest in the biobased production of hydrocarbons that can be derived from fatty acids. Fatty acids also serve as precursors to a number of oleochemicals and hence provide interesting platform chemicals. Here, we review the recent strategies applied to metabolic engineering of S. cerevisiae for the production of fatty acid-derived biofuels and for improvement of the titre, rate and yield (TRY). This includes, for instance, redirection of the flux towards fatty acids through engineering of the central carbon metabolism, balancing the redox power and varying the chain length of fatty acids by enzyme engineering. We also discuss the challenges that currently hinder further TRY improvements and the potential solutions in order to meet the requirements for commercial application.

Adaptive Laboratory Evolution of Ale and Lager Yeasts for Improved Brewing Efficiency and Beer Quality

Yeasts directly impact the efficiency of brewery fermentations as well as the character of the beers produced. In recent years, there has been renewed interest in yeast selection and development inspired by the demand to utilize resources more efficiently and the need to differentiate beers in a competitive market. Reviewed here are the different, non-genetically modified (GM) approaches that have been considered, including bioprospecting, hybridization, and adaptive laboratory evolution (ALE). Particular emphasis is placed on the latter, which represents an extension of the processes that have led to the domestication of strains already used in commercial breweries. ALE can be used to accentuate the positive traits of brewing yeast as well as temper some of the traits that are less desirable from a modern brewer's perspective. This method has the added advantage of being non-GM and therefore suitable for food and beverage production.

Effects of overexpression of STB5 in Saccharomyces cerevisiae on fatty acid biosynthesis, physiology and transcriptome

Microbial conversion of biomass to fatty acids (FA) and products derived thereof is an attractive alternative to the traditional oleochemical production route from animal and plant lipids. This study examined if NADPH-costly FA biosynthesis could be enhanced by overexpressing the transcription factor Stb5 in Saccharomyces cerevisiae. Stb5 activates expression of multiple genes encoding enzymes within the pentose phosphate pathway (PPP) and other NADPH-producing reactions. Overexpression of STB5 led to a decreased growth rate and an increased free fatty acid (FFA) production during growth on glucose. The improved FFA synthetic ability in the glucose phase was shown to be independent of flux through the oxidative PPP. RNAseq analysis revealed that STB5 overexpression had wide-ranging effects on the transcriptome in the batch phase, and appeared to cause a counterintuitive phenotype with reduced flux through the oxidative PPP. During glucose limitation, when an increased NADPH supply is likely less harmful, an overall induction of the proposed target genes of Stb5 (eg. GND1/2, TAL1, ALD6, YEF1) was observed. Taken together, the strategy of utilizing STB5 overexpression to increase NADPH supply for reductive biosynthesis is suggested to have potential in strains engineered to have strong ability to consume excess NADPH, alleviating a potential redox imbalance.

Integration of a multi-step heterologous pathway in Saccharomyces cerevisiae for the production of abscisic acid

BACKGROUND

The sesquiterpenoid abscisic acid (ABA) is mostly known for regulating developmental processes and abiotic stress responses in higher plants. Recent studies show that ABA also exhibits a variety of pharmacological activities. Affordable and sustainable production will be required to utilize the compound in agriculture and as a potential pharmaceutical. Saccharomyces cerevisiae is an established workhorse for the biotechnological production of chemicals. In this study, we constructed and characterised an ABA-producing S. cerevisiae strain using the ABA biosynthetic pathway from Botrytis cinerea.

RESULTS

Expression of the B. cinerea genes bcaba1, bcaba2, bcaba3 and bcaba4 was sufficient to establish ABA production in the heterologous host. We characterised the ABA-producing strain further by monitoring ABA production over time and, since the pathway contains two cytochrome P450 enzymes, by investigating the effects of overexpressing the native S. cerevisiae or the B. cinerea cytochrome P450 reductase. Both, overexpression of the native or heterologous cytochrome P450 reductase, led to increased ABA titres. We were able to show that ABA production was not affected by precursor or NADPH supply, which suggested that the heterologous enzymes were limiting the flux towards the product. The B. cinerea cytochrome P450 monooxygenases BcABA1 and BcABA2 were identified as pathway bottlenecks and balancing the expression levels of the pathway enzymes resulted in 4.1-fold increased ABA titres while reducing by-product formation.

CONCLUSION

This work represents the first step towards a heterologous ABA cell factory for the commercially relevant sesquiterpenoid.

Model-Assisted Fine-Tuning of Central Carbon Metabolism in Yeast through dCas9-Based Regulation

Engineering Saccharomyces cerevisiae for industrial-scale production of valuable chemicals involves extensive modulation of its metabolism. Here, we identified novel gene expression fine-tuning set-ups to enhance endogenous metabolic fluxes toward increasing levels of acetyl-CoA and malonyl-CoA. dCas9-based transcriptional regulation was combined together with a malonyl-CoA responsive intracellular biosensor to select for beneficial set-ups. The candidate genes for screening were predicted using a genome-scale metabolic model, and a gRNA library targeting a total of 168 selected genes was designed. After multiple rounds of fluorescence-activated cell sorting and library sequencing, the gRNAs that were functional and increased flux toward malonyl-CoA were assessed for their efficiency to enhance 3-hydroxypropionic acid (3-HP) production. 3-HP production was significantly improved upon fine-tuning genes involved in providing malonyl-CoA precursors, cofactor supply, as well as chromatin remodeling.

Expanding the Dynamic Range of a Transcription Factor-Based Biosensor in Saccharomyces cerevisiae

Metabolite biosensors are useful tools for high-throughput screening approaches and pathway regulation approaches. An important feature of biosensors is the dynamic range. To expand the maximum dynamic range of a transcription factor-based biosensor in Saccharomyces cerevisiae, using the fapO/FapR system from Bacillus subtilis as an example case, five native promoters, including constitutive and glucose-regulated ones, were modified. By evaluating different binding site (BS) positions in the core promoters, we identified locations that resulted in a high maximum dynamic range with low expression under repressed conditions. We further identified BS positions in the upstream element region of the TEF1 promoter that did not influence the native promoter strength but resulted in repression in the presence of a chimeric repressor consisting of FapR and the yeast repressor Mig1. These modified promoters with broad dynamic ranges will provide useful information for the engineering of future biosensors and their use in complex genetic circuits.

Saccharomyces cerevisiae displays a stable transcription start site landscape in multiple conditions

One of the fundamental processes that determine cellular fate is regulation of gene transcription. Understanding these regulatory processes is therefore essential for understanding cellular responses to changes in environmental conditions. At the core promoter, the regulatory region containing the transcription start site (TSS), all inputs regulating transcription are integrated. Here, we used Cap Analysis of Gene Expression (CAGE) to analyze the pattern of TSSs at four different environmental conditions (limited in ethanol, limited in nitrogen, limited in glucose and limited in glucose under anaerobic conditions) using the Saccharomyces cerevisiae strain CEN.PK113-7D. With this experimental setup, we were able to show that the TSS landscape in yeast is stable at different metabolic states of the cell. We also show that the spatial distribution of transcription initiation events, described by the shape index, has a surprisingly strong negative correlation with measured gene expression levels, meaning that genes with higher expression levels tend to have a broader distribution of TSSs. Our analysis supplies a set of high-quality TSS annotations useful for metabolic engineering and synthetic biology approaches in the industrially relevant laboratory strain CEN.PK113-7D, and provides novel insights into yeast TSS dynamics and gene regulation.

FadR-Based Biosensor-Assisted Screening for Genes Enhancing Fatty Acyl-CoA Pools in Saccharomyces cerevisiae

Fatty acid-derived compounds have a range of industrial applications, from chemical building blocks to biofuels. Due to the highly dynamic nature of fatty acid metabolism, it is difficult to identify genes modulating fatty acyl-CoA levels using a rational approach. Metabolite biosensors can be used to screen genes from large-scale libraries in vivo in a high throughput manner. Here, a fatty acyl-CoA sensor based on the transcription factor FadR from Escherichia coli was established in Saccharomyces cerevisiae and combined with a gene overexpression library to screen for genes increasing the fatty acyl-CoA pool. Fluorescence-activated cell sorting, followed by data analysis, identified genes enhancing acyl-CoA levels. From these, overexpression of RTC3, GGA2, and LPP1 resulted in about 80% increased fatty alcohol levels. Changes in fatty acid saturation and chain length distribution could also be observed. These results indicate that the use of this acyl-CoA biosensor combined with a gene overexpression library allows for identification of gene targets improving production of fatty acids and derived products.

Identification of genes involved in shea butter biosynthesis from Vitellaria paradoxa fruits through transcriptomics and functional heterologous expression

Shea tree (Vitellaria paradoxa) is one economically important plant species that mainly distributes in West Africa. Shea butter extracted from shea fruit kernels can be used as valuable products in the food and cosmetic industries. The most valuable composition in shea butter was one kind of triacylglycerol (TAG), 1,3-distearoyl-2-oleoyl-glycerol (SOS, C18:0–C18:1–C18:0). However, shea butter production is limited and little is known about the genetic information of shea tree. In this study, we tried to reveal genetic information of shea tree and identified shea TAG biosynthetic genes for future shea butter production in yeast cell factories. First, we measured lipid content, lipid composition, and TAG composition of seven shea fruits at different ripe stages. Then, we performed transcriptome analysis on two shea fruits containing obviously different levels of SOS and revealed a list of TAG biosynthetic genes potentially involved in TAG biosynthesis. In total, 4 glycerol-3-phosphate acyltransferase (GPAT) genes, 8 lysophospholipid acyltransferase (LPAT) genes, and 11 diacylglycerol acyltransferase (DGAT) genes in TAG biosynthetic pathway were predicted from the assembled transcriptome and 14 of them were cloned from shea fruit cDNA. Furthermore, the heterologous expression of these 14 potential GPAT, LPAT, and DGAT genes in Saccharomyces cerevisiae changed yeast fatty acid and lipid profiles, suggesting that they functioned in S. cerevisiae. Moreover, two shea DGAT genes, VpDGAT1 and VpDGAT7, were identified as functional DGATs in shea tree, showing they might be useful for shea butter (SOS) production in yeast cell factories.

Increasing jojoba-like wax ester production in Saccharomyces cerevisiae by enhancing very long-chain, monounsaturated fatty acid synthesis

BACKGROUND

Fatty acids (FAs) with a chain length of more than 18 carbon atoms (> C18) are interesting for the production of specialty compounds derived from these FAs. These compounds include free FAs, like erucic acid (C22:1-Δ13), primary fatty alcohols (FOHs), like docosanol (C22:0-FOH), as well as jojoba-like wax esters (WEs) (C38-WE to C44-WE), which are esters of (very) long-chain FAs and (very) long-chain FOHs. In particular, FAs, FOHs and WEs are used in the production of chemicals, pharmaceuticals and cosmetic products. Jojoba seed oil is highly enriched in diunsaturated WEs with over 70 mol% being composed of C18:1-C24:1 monounsaturated FOH and monounsaturated FA moieties. In this study, we aim for the production of jojoba-like WEs in the yeast Saccharomyces cerevisiae by increasing the amount of very long-chain, monounsaturated FAs and simultaneously expressing enzymes required for WE synthesis.

RESULTS

We show that the combined expression of a plant-derived fatty acid elongase (FAE/KCS) from Crambe abyssinica (CaKCS) together with the yeast intrinsic fatty acid desaturase (FAD) Ole1p leads to an increase in C20:1 and C22:1 FAs in S. cerevisiae. We also demonstrate that the best enzyme candidate for C24:1 FA production in S. cerevisiae is a FAE derived from Lunaria annua (LaKCS). The combined overexpression of CaKCS and Ole1p together with a fatty acyl reductase (FAR/FAldhR) from Marinobacter aquaeolei VT8 (MaFAldhR) and a wax synthase (WS) from Simmondsia chinensis (SciWS) in a S. cerevisiae strain, overexpressing a range of other enzymes involved in FA synthesis and elongation, leads to a yeast strain capable of producing high amounts of monounsaturated FOHs (up to C22:1-FOH) as well as diunsaturated WEs (up to C46:2-WE).

CONCLUSIONS

Changing the FA profile of the yeast S. cerevisiae towards very long-chain monounsaturated FAs is possible by combined overexpression of endogenous and heterologous enzymes derived from various sources (e.g. a marine copepod or plants). This strategy was used to produce jojoba-like WEs in S. cerevisiae and can potentially be extended towards other commercially interesting products derived from very long-chain FAs.

Heterologous phosphoketolase expression redirects flux towards acetate, perturbs sugar phosphate pools and increases respiratory demand in Saccharomyces cerevisiae

Introduction

Phosphoketolases (Xfpk) are a non-native group of enzymes in yeast, which can be expressed in combination with other metabolic enzymes to positively influence the yield of acetyl-CoA derived products by reducing carbon losses in the form of CO₂. In this study, a yeast strain expressing Xfpk from Bifidobacterium breve, which was previously found to have a growth defect and to increase acetate production, was characterized.

Results

Xfpk-expression was found to increase respiration and reduce biomass yield during glucose consumption in batch and chemostat cultivations. By cultivating yeast with or without Xfpk in bioreactors at different pHs, we show that certain aspects of the negative growth effects coupled with Xfpk-expression are likely to be explained by proton decoupling. At low pH, this manifests as a reduction in biomass yield and growth rate in the ethanol phase. Secondly, we show that intracellular sugar phosphate pools are significantly altered in the Xfpk-expressing strain. In particular a decrease of the substrates xylulose-5-phosphate and fructose-6-phosphate was detected (26% and 74% of control levels) together with an increase of the products glyceraldehyde-3-phosphate and erythrose-4-phosphate (208% and 542% of control levels), clearly verifying in vivo Xfpk enzymatic activity. Lastly, RNAseq analysis shows that Xfpk expression increases transcription of genes related to the glyoxylate cycle, the TCA cycle and respiration, while expression of genes related to ethanol and acetate formation is reduced. The physiological and transcriptional changes clearly demonstrate that a heterologous phosphoketolase flux in combination with endogenous hydrolysis of acetyl-phosphate to acetate increases the cellular demand for acetate assimilation and respiratory ATP-generation, leading to carbon losses.

Conclusion

Our study shows that expression of Xfpk in yeast diverts a relatively small part of its glycolytic flux towards acetate formation, which has a significant impact on intracellular sugar phosphate levels and on cell energetics. The elevated acetate flux increases the ATP-requirement for ion homeostasis and need for respiratory assimilation, which leads to an increased production of CO₂. A majority of the negative growth effects coupled to Xfpk expression could likely be counteracted by preventing acetate accumulation via direct channeling of acetyl-phosphate towards acetyl-CoA.

Electronic supplementary material

The online version of this article (10.1186/s12934-019-1072-6) contains supplementary material, which is available to authorized users.