Carboxylic acid reductase-dependent biosynthesis of eugenol and related allylphenols.

BACKGROUND: (Hydroxy)cinnamyl alcohols and allylphenols, including coniferyl alcohol and eugenol, are naturally occurring aromatic compounds widely utilised in pharmaceuticals, flavours, and fragrances. Traditionally, the heterologous biosynthesis of (hydroxy)cinnamyl alcohols from (hydroxy)cinnamic acids involved CoA-dependent activation of the substrate. However, a recently explored alternative pathway involving carboxylic acid reductase (CAR) has proven efficient in generating the (hydroxy)cinnamyl aldehyde intermediate without the need for CoA activation. In this study, we investigated the application of the CAR pathway for whole-cell bioconversion of a range of (hydroxy)cinnamic acids into their corresponding (hydroxy)cinnamyl alcohols. Furthermore, we sought to extend the pathway to enable the production of a variety of allylphenols and allylbenzene. RESULTS: By screening the activity of several heterologously expressed enzymes in crude cell lysates, we identified the combination of Segniliparus rugosus CAR (SrCAR) and Medicago sativa cinnamyl alcohol dehydrogenase (MsCAD2) as the most efficient enzymatic cascade for the two-step reduction of ferulic acid to coniferyl alcohol. To optimise the whole-cell bioconversion in Escherichia coli, we implemented a combinatorial approach to balance the gene expression levels of SrCAR and MsCAD2. This optimisation resulted in a coniferyl alcohol yield of almost 100%. Furthermore, we extended the pathway by incorporating coniferyl alcohol acyltransferase and eugenol synthase, which allowed for the production of eugenol with a titre of up to 1.61 mM (264 mg/L) from 3 mM ferulic acid. This improvement in titre surpasses previous achievements in the field employing a CoA-dependent coniferyl alcohol biosynthesis pathway. Our study not only demonstrated the successful utilisation of the CAR pathway for the biosynthesis of diverse (hydroxy)cinnamyl alcohols, such as p-coumaryl alcohol, caffeyl alcohol, cinnamyl alcohol, and sinapyl alcohol, from their corresponding (hydroxy)cinnamic acid precursors but also extended the pathway to produce allylphenols, including chavicol, hydroxychavicol, and methoxyeugenol. Notably, the microbial production of methoxyeugenol from sinapic acid represents a novel achievement. CONCLUSION: The combination of SrCAR and MsCAD2 enzymes offers an efficient enzymatic cascade for the production of a wide array of (hydroxy)cinnamyl alcohols and, ultimately, allylphenols from their respective (hydroxy)cinnamic acids. This expands the range of value-added molecules that can be generated using microbial cell factories and creates new possibilities for applications in industries such as pharmaceuticals, flavours, and fragrances. These findings underscore the versatility of the CAR pathway, emphasising its potential in various biotechnological applications.

Design of Four Small-Molecule-Inducible Systems in the Yeast Chromosome, Applied to Optimize Terpene Biosynthesis.

The optimization of cellular functions often requires the balancing of gene expression, but the physical construction and screening of alternative designs are costly and time-consuming. Here, we construct a strain of Saccharomyces cerevisiae that contains a "sensor array" containing bacterial regulators that respond to four small-molecule inducers (vanillic acid, xylose, aTc, IPTG). Four promoters can be independently controlled with low background and a 40- to 5000-fold dynamic range. These systems can be used to study the impact of changing the level and timing of gene expression without requiring the construction of multiple strains. We apply this approach to the optimization of a four-gene heterologous pathway to the terpene linalool, which is a flavor and precursor to energetic materials. Using this approach, we identify bottlenecks in the metabolic pathway. This work can aid the rapid automated strain development of yeasts for the bio-manufacturing of diverse products, including chemicals, materials, fuels, and food ingredients.

Efficient multiplexed gene regulation in Saccharomyces cerevisiae using dCas12a.

CRISPR Cas12a is an RNA-programmable endonuclease particularly suitable for gene regulation. This is due to its preference for T-rich PAMs that allows it to more easily target AT-rich promoter sequences, and built-in RNase activity which can process a single CRISPR RNA array encoding multiple spacers into individual guide RNAs (gRNAs), thereby simplifying multiplexed gene regulation. Here, we develop a flexible dCas12a-based CRISPRi system for Saccharomyces cerevisiae and systematically evaluate its design features. This includes the role of the NLS position, use of repression domains, and the position of the gRNA target. Our optimal system is comprised of dCas12a E925A with a single C-terminal NLS and a Mxi1 or a MIG1 repression domain, which enables up to 97% downregulation of a reporter gene. We also extend this system to allow for inducible regulation via an RNAP II-controlled promoter, demonstrate position-dependent effects in crRNA arrays, and use multiplexed regulation to stringently control a heterologous ß-carotene pathway. Together these findings offer valuable insights into the design constraints of dCas12a-based CRISPRi and enable new avenues for flexible and efficient gene regulation in S. cerevisiae.

Metabolic enzyme clustering by coiled coils improves the biosynthesis of resveratrol and mevalonate.

The clustering of biosynthetic enzymes is used in nature to channel reaction products and increase the yield of compounds produced by multiple reaction steps. The coupling of multiple enzymes has been shown to increase the biosynthetic product yield. Different clustering strategies have particular advantages as the spatial organization of multiple enzymes creates biocatalytic cascades with a higher efficiency of biochemical reaction. However, there are also some drawbacks, such as misfolding and the variable stability of interaction domains, which may differ between particular biosynthetic reactions and the host organism. Here, we compared different protein-based clustering strategies, including direct fusion, fusion mediated by intein, and noncovalent interactions mediated through small coiled-coil dimer-forming domains. The clustering of enzymes through orthogonally designed coiled-coil interaction domains increased the production of resveratrol in Escherichia coli more than the intein-mediated fusion of biosynthetic enzymes. The improvement of resveratrol production correlated with the stability of the coiled-coil dimers. The coiled-coil fusion-based approach also increased mevalonate production in Saccharomyces cerevisiae, thus demonstrating the wider applicability of this strategy.

CRISPR/Cas12a Multiplex Genome Editing of Saccharomyces cerevisiae and the Creation of Yeast Pixel Art.

High efficiency, ease of use and versatility of the clustered regularly interspaced short palindromic repeats/CRISPR-associated protein 9 (CRISPR/Cas9) system has facilitated advanced genetic modification of Saccharomyces cerevisiae, a model organism and workhorse in industrial biotechnology. CRISPR-associated protein 12a (Cas12a), an RNA-guided endonuclease with features distinguishable from Cas9 is applied in this work, further extending the molecular toolbox for genome editing purposes. A benefit of the CRISPR/Cas12a system is that it can be used in multiplex genome editing with multiple guide RNAs expressed from a single transcriptional unit (single CRISPR RNA (crRNA) array). We present a protocol for multiplex integration of multiple heterologous genes into independent loci of the S. cerevisiae genome using the CRISPR/Cas12a system with multiple crRNAs expressed from a single crRNA array construct. The proposed method exploits the ability of S. cerevisiae to perform in vivo recombination of DNA fragments to assemble the single crRNA array into a plasmid that can be used for transformant selection, as well as the assembly of donor DNA sequences that integrate into the genome at intended positions. Cas12a is pre-expressed constitutively, facilitating cleavage of the S. cerevisiae genome at the intended positions upon expression of the single crRNA array. The protocol includes the design and construction of a single crRNA array and donor DNA expression cassettes, and exploits an integration approach making use of unique 50-bp DNA connectors sequences and separate integration flank DNA sequences, which simplifies experimental design through standardization and modularization and extends the range of applications. Finally, we demonstrate a straightforward technique for creating yeast pixel art with an acoustic liquid handler using differently colored carotenoid producing yeast strains that were constructed.

Multiplex genome editing of microorganisms using CRISPR-Cas.

Microbial production of chemical compounds often requires highly engineered microbial cell factories. During the last years, CRISPR-Cas nucleases have been repurposed as powerful tools for genome editing. Here, we briefly review the most frequently used CRISPR-Cas tools and describe some of their applications. We describe the progress made with respect to CRISPR-based multiplex genome editing of industrial bacteria and eukaryotic microorganisms. We also review the state of the art in terms of gene expression regulation using CRISPRi and CRISPRa. Finally, we summarize the pillars for efficient multiplexed genome editing and present our view on future developments and applications of CRISPR-Cas tools for multiplex genome editing.

Novel sequencing technologies to support industrial biotechnology.

Industrial biotechnology develops and applies microorganisms for the production of bioproducts and enzymes with applications ranging from food and feed ingredients and processing to bio-based chemicals, biofuels and pharmaceutical products. Next generation DNA sequencing technologies play an increasingly important role in improving and accelerating microbial strain development for existing and novel bio-products via screening, gene and pathway discovery, metabolic engineering and additional optimization and understanding of large-scale manufacturing. In this mini-review, we describe novel DNA sequencing and analysis technologies with a focus on applications to industrial strain development, enzyme discovery and microbial community analysis.

Iterative algorithm-guided design of massive strain libraries, applied to itaconic acid production in yeast.

Metabolic engineering requires multiple rounds of strain construction to evaluate alternative pathways and enzyme concentrations. Optimizing multigene pathways stepwise or by randomly selecting enzymes and expression levels is inefficient. Here, we apply methods from design of experiments (DOE) to guide the construction of strain libraries from which the maximum information can be extracted without sampling every possible combination. We use Saccharomyces cerevisiae as a host for a novel six-gene pathway to itaconic acid, selected by comparing alternative shunt pathways that bypass the mitochondrial TCA cycle. The pathway is distinctive for the use of acetylating acetaldehyde dehydrogenase to increase cytosolic acetyl-CoA pools, a bacterial enzyme to synthesize citrate in the cytosol, and an itaconic acid exporter. Precise control over the expression of each gene is enabled by a set of promoter-terminator pairs that span a 174-fold range. Two large combinatorial libraries (160 variants, 2.4 Mb and 32 variants, 0.6 Mb) are designed where the expression levels are selected by statistical methods (I-optimal response surface methodology, full factorial, or Plackett-Burman) with the intent of extracting different types of guiding information after the screen. This is applied to the design of a third library (24 variants, 0.5 Mb) intended to alleviate a bottleneck in cis-aconitate decarboxylase (CAD) expression. The top strain produces 815 mg/l itaconic acid, a 4-fold improvement over the initial strain achieved by iteratively balancing pathway expression. Including a methylated product in the total, the strain produces 1.3 g/l combined itaconic acids. Further, a regression analysis of the libraries reveals the optimal expression level of CAD as well as pairwise interdependencies between genes that result in increased titer and purity of itaconic acid. This work demonstrates adapting algorithmic design strategies to guide automated yeast strain construction and learn information after each iteration.

CRISPR/Cpf1 enables fast and simple genome editing of Saccharomyces cerevisiae.

Cpf1 represents a novel single RNA-guided CRISPR/Cas endonuclease system suitable for genome editing with distinct features compared with Cas9. We demonstrate the functionality of three Cpf1 orthologues - Acidaminococcus spp. BV3L6 (AsCpf1), Lachnospiraceae bacterium ND2006 (LbCpf1) and Francisella novicida U112 (FnCpf1) - for genome editing of Saccharomyces cerevisiae. These Cpf1-based systems enable fast and reliable introduction of donor DNA on the genome using a two-plasmid-based editing approach together with linear donor DNA. LbCpf1 and FnCpf1 displayed editing efficiencies comparable with the CRISPR/Cas9 system, whereas AsCpf1 editing efficiency was lower. Further characterization showed that AsCpf1 and LbCpf1 displayed a preference for their cognate crRNA, while FnCpf1-mediated editing with similar efficiencies was observed using non-cognate crRNAs of AsCpf1 and LbCpf1. In addition, multiplex genome editing using a single LbCpf1 crRNA array is shown to be functional in yeast. This work demonstrates that Cpf1 broadens the genome editing toolbox available for Saccharomyces cerevisiae. © 2017 The Authors. Yeast published by John Wiley & Sons, Ltd.

A Minimal Model of Ribosome Allocation Dynamics Captures Trade-offs in Expression between Endogenous and Synthetic Genes.

Cells contain a finite set of resources that must be distributed across many processes to ensure survival. Among them, the largest proportion of cellular resources is dedicated to protein translation. Synthetic biology often exploits these resources in executing orthogonal genetic circuits, yet the burden this places on the cell is rarely considered. Here, we develop a minimal model of ribosome allocation dynamics capturing the demands on translation when expressing a synthetic construct together with endogenous genes required for the maintenance of cell physiology. Critically, it contains three key variables related to design parameters of the synthetic construct covering transcript abundance, translation initiation rate, and elongation time. We show that model-predicted changes in ribosome allocation closely match experimental shifts in synthetic protein expression rate and cellular growth. Intriguingly, the model is also able to accurately infer transcript levels and translation times after further exposure to additional ambient stress. Our results demonstrate that a simple model of resource allocation faithfully captures the redistribution of protein synthesis resources when faced with the burden of synthetic gene expression and environmental stress. The tractable nature of the model makes it a versatile tool for exploring the guiding principles of efficient heterologous expression and the indirect interactions that can arise between synthetic circuits and their host chassis because of competition for shared translational resources.

Algorithmic co-optimization of genetic constructs and growth conditions: application to 6-ACA, a potential nylon-6 precursor.

Optimizing bio-production involves strain and process improvements performed as discrete steps. However, environment impacts genotype and a strain that is optimal under one set of conditions may not be under different conditions. We present a methodology to simultaneously vary genetic and process factors, so that both can be guided by design of experiments (DOE). Advances in DNA assembly and gene insulation facilitate this approach by accelerating multi-gene pathway construction and the statistical interpretation of screening data. This is applied to a 6-aminocaproic acid (6-ACA) pathway in Escherichia coli consisting of six heterologous enzymes. A 32-member fraction factorial library is designed that simultaneously perturbs expression and media composition. This is compared to a 64-member full factorial library just varying expression (0.64 Mb of DNA assembly). Statistical analysis of the screening data from these libraries leads to different predictions as to whether the expression of enzymes needs to increase or decrease. Therefore, if genotype and media were varied separately this would lead to a suboptimal combination. This is applied to the design of a strain and media composition that increases 6-ACA from 9 to 48 mg/l in a single optimization step. This work introduces a generalizable platform to co-optimize genetic and non-genetic factors.

Trade-offs between tRNA abundance and mRNA secondary structure support smoothing of translation elongation rate.

Translation of protein from mRNA is a complex multi-step process that occurs at a non-uniform rate. Variability in ribosome speed along an mRNA enables refinement of the proteome and plays a critical role in protein biogenesis. Detailed single protein studies have found both tRNA abundance and mRNA secondary structure as key modulators of translation elongation rate, but recent genome-wide ribosome profiling experiments have not observed significant influence of either on translation efficiency. Here we provide evidence that this results from an inherent trade-off between these factors. We find codons pairing to high-abundance tRNAs are preferentially used in regions of high secondary structure content, while codons read by significantly less abundant tRNAs are located in lowly structured regions. By considering long stretches of high and low mRNA secondary structure in Saccharomyces cerevisiae and Escherichia coli and comparing them to randomized-gene models and experimental expression data, we were able to distinguish clear selective pressures and increased protein expression for specific codon choices. The trade-off between secondary structure and tRNA-concentration based codon choice allows for compensation of their independent effects on translation, helping to smooth overall translational speed and reducing the chance of potentially detrimental points of excessively slow or fast ribosome movement.

Protein redesign by learning from data.

Protein redesign methods aim to improve a desired property by carefully selecting mutations in relevant regions guided by protein structure. However, often protein structural requirements underlying biological characteristics are not well understood. Here, we introduce a methodology that learns relevant mutations from a set of proteins that have the desired property and demonstrate it by successfully improving production levels of two enzymes by Aspergillus niger, a relevant host organism for industrial enzyme production. We validated our method on two enzymes, an esterase and an inulinase, creating four redesigns with 5-45 mutations. Up to 10-fold increase in production was obtained with preserved enzyme activity for small numbers of mutations, whereas production levels and activities dropped for too aggressive redesigns. Our results demonstrate the feasibility of protein redesign by learning. Such an approach has great potential for improving production levels of many industrial enzymes and could potentially be employed for other design goals.

SPiCE: a web-based tool for sequence-based protein classification and exploration.

BACKGROUND: Amino acid sequences and features extracted from such sequences have been used to predict many protein properties, such as subcellular localization or solubility, using classifier algorithms. Although software tools are available for both feature extraction and classifier construction, their application is not straightforward, requiring users to install various packages and to convert data into different formats. This lack of easily accessible software hampers quick, explorative use of sequence-based classification techniques by biologists. RESULTS: We have developed the web-based software tool SPiCE for exploring sequence-based features of proteins in predefined classes. It offers data upload/download, sequence-based feature calculation, data visualization and protein classifier construction and testing in a single integrated, interactive environment. To illustrate its use, two example datasets are included showing the identification of differences in amino acid composition between proteins yielding low and high production levels in fungi and low and high expression levels in yeast, respectively. CONCLUSIONS: SPiCE is an easy-to-use online tool for extracting and exploring sequence-based features of sets of proteins, allowing non-experts to apply advanced classification techniques. The tool is available at http://helix.ewi.tudelft.nl/spice.

Using synthetic biological parts and microbioreactors to explore the protein expression characteristics of Escherichia coli.

Synthetic biology has developed numerous parts for the precise control of protein expression. However, relatively little is known about the burden these place on a host, or their reliability under varying environmental conditions. To address this, we made use of synthetic transcriptional and translational elements to create a combinatorial library of constructs that modulated expression strength of a green fluorescent protein. Combining this library with a microbioreactor platform, we were able to perform a detailed large-scale assessment of transient expression and growth characteristics of two Escherichia coli strains across several temperatures. This revealed significant differences in the robustness of both strains to differing types of protein expression, and a complex response of transcriptional and translational elements to differing temperatures. This study supports the development of reliable synthetic biological systems capable of working across different hosts and environmental contexts. Plasmids developed during this work have been made publicly available to act as a reference set for future research.

Translational sensitivity of the Escherichia coli genome to fluctuating tRNA availability.

The synthesis of protein from messenger RNA during translation is a highly dynamic process that plays a key role in controlling the efficiency and fidelity of genome-wide protein expression. The availability of aminoacylated transfer RNA (tRNA) is a major factor influencing the speed of ribosomal movement, which depending on codon choices, varies considerably along a transcript. Furthermore, it has been shown experimentally that tRNA availability can vary significantly under different growth and stress conditions, offering the cell a way to adapt translational dynamics across the genome. Existing models of translation have neglected fluctuations of tRNA pools, instead assuming fixed tRNA availabilities over time. This has lead to an incomplete understanding of this process. Here, we show for the entire Escherichia coli genome how and to what extent translational speed profiles, which capture local aspects of translational elongation, respond to measured shifts in tRNA availability. We find that translational profiles across the genome are affected to differing degrees, with genes that are essential or related to fundamental processes such as translation, being more robust than those linked to regulation. Furthermore, we reveal how fluctuating tRNA availability influences profiles of specific sequences known to play a significant role in translational control of gene expression.

Exploring sequence characteristics related to high-level production of secreted proteins in Aspergillus niger.

Protein sequence features are explored in relation to the production of over-expressed extracellular proteins by fungi. Knowledge on features influencing protein production and secretion could be employed to improve enzyme production levels in industrial bioprocesses via protein engineering. A large set, over 600 homologous and nearly 2,000 heterologous fungal genes, were overexpressed in Aspergillus niger using a standardized expression cassette and scored for high versus no production. Subsequently, sequence-based machine learning techniques were applied for identifying relevant DNA and protein sequence features. The amino-acid composition of the protein sequence was found to be most predictive and interpretation revealed that, for both homologous and heterologous gene expression, the same features are important: tyrosine and asparagine composition was found to have a positive correlation with high-level production, whereas for unsuccessful production, contributions were found for methionine and lysine composition. The predictor is available online at http://bioinformatics.tudelft.nl/hipsec. Subsequent work aims at validating these findings by protein engineering as a method for increasing expression levels per gene copy.

Genetic circuit performance under conditions relevant for industrial bioreactors.

Synthetic genetic programs promise to enable novel applications in industrial processes. For such applications, the genetic circuits that compose programs will require fidelity in varying and complex environments. In this work, we report the performance of two synthetic circuits in Escherichia coli under industrially relevant conditions, including the selection of media, strain, and growth rate. We test and compare two transcriptional circuits: an AND and a NOR gate. In E. coli DH10B, the AND gate is inactive in minimal media; activity can be rescued by supplementing the media and transferring the gate into the industrial strain E. coli DS68637 where normal function is observed in minimal media. In contrast, the NOR gate is robust to media composition and functions similarly in both strains. The AND gate is evaluated at three stages of early scale-up: 100 mL shake flask experiments, a 1 mL MTP microreactor, and a 10 L bioreactor. A reference plasmid that constitutively produces a GFP reporter is used to make comparisons of circuit performance across conditions. The AND gate function is quantitatively different at each scale. The output deteriorates late in fermentation after the shift from exponential to constant feed rates, which induces rapid resource depletion and changes in growth rate. In addition, one of the output states of the AND gate failed in the bioreactor, effectively making it only responsive to a single input. Finally, cells carrying the AND gate show considerably less accumulation of biomass. Overall, these results highlight challenges and suggest modified strategies for developing and characterizing genetic circuits that function reliably during fermentation.

Comparative genomics of citric-acid-producing Aspergillus niger ATCC 1015 versus enzyme-producing CBS 513.88.

The filamentous fungus Aspergillus niger exhibits great diversity in its phenotype. It is found globally, both as marine and terrestrial strains, produces both organic acids and hydrolytic enzymes in high amounts, and some isolates exhibit pathogenicity. Although the genome of an industrial enzyme-producing A. niger strain (CBS 513.88) has already been sequenced, the versatility and diversity of this species compel additional exploration. We therefore undertook whole-genome sequencing of the acidogenic A. niger wild-type strain (ATCC 1015) and produced a genome sequence of very high quality. Only 15 gaps are present in the sequence, and half the telomeric regions have been elucidated. Moreover, sequence information from ATCC 1015 was used to improve the genome sequence of CBS 513.88. Chromosome-level comparisons uncovered several genome rearrangements, deletions, a clear case of strain-specific horizontal gene transfer, and identification of 0.8 Mb of novel sequence. Single nucleotide polymorphisms per kilobase (SNPs/kb) between the two strains were found to be exceptionally high (average: 7.8, maximum: 160 SNPs/kb). High variation within the species was confirmed with exo-metabolite profiling and phylogenetics. Detailed lists of alleles were generated, and genotypic differences were observed to accumulate in metabolic pathways essential to acid production and protein synthesis. A transcriptome analysis supported up-regulation of genes associated with biosynthesis of amino acids that are abundant in glucoamylase A, tRNA-synthases, and protein transporters in the protein producing CBS 513.88 strain. Our results and data sets from this integrative systems biology analysis resulted in a snapshot of fungal evolution and will support further optimization of cell factories based on filamentous fungi.

The decarboxylation of the weak-acid preservative, sorbic acid, is encoded by linked genes in Aspergillus spp.

The ability to resist anti-microbial compounds is of key evolutionary benefit to microorganisms. Aspergillus niger has previously been shown to require the activity of a phenylacrylic acid decarboxylase (encoded by padA1) for the decarboxylation of the weak-acid preservative sorbic acid (2,4-hexadienoic acid) to 1,3-pentadiene. It is now shown that this decarboxylation process also requires the activity of a putative 4-hydroxybenzoic acid (3-octaprenyl-4-hydroxybenzoic acid) decarboxylase, encoded by a gene termed ohbA1, and a putative transcription factor, sorbic acid decarboxylase regulator, encoded by sdrA. The padA1,ohbA1 and sdrA genes are in close proximity to each other on chromosome 6 in the A. niger genome and further bioinformatic analysis revealed conserved synteny at this locus in several Aspergillus species and other ascomycete fungi indicating clustering of metabolic function. This cluster is absent from the genomes of A. fumigatus and A. clavatus and, as a consequence, neither species is capable of decarboxylating sorbic acid.