High quality de novo genome assembly of the non-conventional yeast Kazachstania bulderi describes a potential low pH production host for biorefineries.

Kazachstania bulderi is a non-conventional yeast species able to grow efficiently on glucose and δ-gluconolactone at low pH. These unique traits make K. bulderi an ideal candidate for use in sustainable biotechnology processes including low pH fermentations and the production of green chemicals including organic acids. To accelerate strain development with this species, detailed information of its genetics is needed. Here, by employing long read sequencing we report a high-quality phased genome assembly for three strains of K. bulderi species, including the type strain. The sequences were assembled into 12 chromosomes with a total length of 14 Mb, and the genome was fully annotated at structural and functional levels, including allelic and structural variants, ribosomal array and mating type locus. This high-quality reference genome provides a resource to advance our fundamental knowledge of biotechnologically relevant non-conventional yeasts and to support the development of genetic tools for manipulating such strains towards their use as production hosts in biotechnological processes.

Telomere-to-telomere genome sequence of the model mould pathogen Aspergillus fumigatus.

The pathogenic fungus Aspergillus fumigatus is a major etiological agent of fungal invasive and chronic diseases affecting tens of millions of individuals worldwide. Draft genome sequences of two clinical isolates (Af293 and A1163) are commonly used as reference genomes for analyses of clinical and environmental strains. However, the reference sequences lack coverage of centromeres, an accurate sequence for ribosomal repeats, and a comprehensive annotation of chromosomal rearrangements such as translocations and inversions. Here, we used PacBio Single Molecule Real-Time (SMRT), Oxford Nanopore and Illumina HiSeq sequencing for de novo genome assembly and polishing of two laboratory reference strains of A. fumigatus, CEA10 (parental isolate of A1163) and its descendant A1160. We generated full length chromosome assemblies and a comprehensive telomere-to-telomere coverage for CEA10 and near complete assembly of A1160 including ribosomal repeats and the sequences of centromeres, which we discovered to be composed of long transposon elements. We envision these high-quality reference genomes will become fundamental resources to study A. fumigatus biology, pathogenicity and virulence, and to discover more effective treatments against diseases caused by this fungus.

Baseline proteomics characterisation of the emerging host biomanufacturing organism Halomonas bluephagenesis.

Despite its greener credentials, biomanufacturing remains financially uncompetitive compared with the higher carbon emitting, hydrocarbon-based chemical industry. Replacing traditional chassis such as E. coli with novel robust organisms, are a route to cost reduction for biomanufacturing. Extremophile bacteria such as the halophilic Halomonas bluephagenesis TD01 exemplify this potential by thriving in environments inherently inimical to other organisms, so reducing sterilisation costs. Novel chassis are inevitably less well annotated than established organisms. Rapid characterisation along with community data sharing will facilitate adoption of such organisms for biomanufacturing. The data record comprises a newly sequenced genome for the organism and evidence via LC-MS based proteomics for expression of 1160 proteins (30% of the proteome) including baseline quantification of 1063 proteins (27% of the proteome), and a spectral library enabling re-use for targeted LC-MS proteomics assays. Protein data are annotated with KEGG Orthology, enabling rapid matching of quantitative data to pathways of interest to biomanufacturing.

SpeedyGenesXL: an Automated, High-Throughput Platform for the Preparation of Bespoke Ultralarge Variant Libraries for Directed Evolution.

Directed evolution of proteins is a highly effective strategy for tailoring biocatalysts to a particular application, and is capable of engineering improvements such as kcat, thermostability and organic solvent tolerance. It is recognized that large and systematic libraries are required to navigate a protein's vast and rugged sequence landscape effectively, yet their preparation is nontrivial and commercial libraries are extremely costly. To address this, we have developed SpeedyGenesXL, an automated, high-throughput platform for the production of wild-type genes, Boolean OR, combinatorial, or combinatorial-OR-type libraries based on the SpeedyGenes methodology. Together this offers a flexible platform for library synthesis, capable of generating many different bespoke, diverse libraries simultaneously.

GeneORator: An Efficient Method for the Systematic Mutagenesis of Entire Genes.

Directed evolution is a powerful tool for the rapid improvement of a target protein toward a desired fitness criteria, such as activity, specificity, or stability. In order to achieve these desired improvements, it is often beneficial to subject the entirety of the protein to mutagenesis. However, the creation of such libraries by targeted methods (i.e. site-directed mutagenesis) can be a laborious and costly task. Here we outline the GeneORator method, which uses Boolean "OR" logic to introduce specific codon mutations at multiple loci in a single reaction, thereby greatly reducing the experimental workload. The method describes library synthesis using asymmetric PCR, in which mutagenic primers are designed to create OR-type mutations at multiple sites of variation in a two-step protocol. As an example, we show how this can be utilized for controlled and economical mutagenesis of every amino acid codon in a gene.

Prototyping of microbial chassis for the biomanufacturing of high-value chemical targets.

Metabolic engineering technologies have been employed with increasing success over the last three decades for the engineering and optimization of industrial host strains to competitively produce high-value chemical targets. To this end, continued reductions in the time taken from concept, to development, to scale-up are essential. Design-Build-Test-Learn pipelines that are able to rapidly deliver diverse chemical targets through iterative optimization of microbial production strains have been established. Biofoundries are employing in silico tools for the design of genetic parts, alongside combinatorial design of experiments approaches to optimize selection from within the potential design space of biological circuits based on multi-criteria objectives. These genetic constructs can then be built and tested through automated laboratory workflows, with performance data analysed in the learn phase to inform further design. Successful examples of rapid prototyping processes for microbially produced compounds reveal the potential role of biofoundries in leading the sustainable production of next-generation bio-based chemicals.

The evolving art of creating genetic diversity: From directed evolution to synthetic biology.

The ability to engineer biological systems, whether to introduce novel functionality or improved performance, is a cornerstone of biotechnology and synthetic biology. Typically, this requires the generation of genetic diversity to explore variations in phenotype, a process that can be performed at many levels, from single molecule targets (i.e., in directed evolution of enzymes) to whole organisms (e.g., in chassis engineering). Recent advances in DNA synthesis technology and automation have enhanced our ability to create variant libraries with greater control and throughput. This review highlights the latest developments in approaches to create such a hierarchy of diversity from the enzyme level to entire pathways in vitro, with a focus on the creation of combinatorial libraries that are required to navigate a target's vast design space successfully to uncover significant improvements in function.

Engineering Escherichia coli towards de novo production of gatekeeper (2S)-flavanones: naringenin, pinocembrin, eriodictyol and homoeriodictyol.

Natural plant-based flavonoids have drawn significant attention as dietary supplements due to their potential health benefits, including anti-cancer, anti-oxidant and anti-asthmatic activities. Naringenin, pinocembrin, eriodictyol and homoeriodictyol are classified as (2S)-flavanones, an important sub-group of naturally occurring flavonoids, with wide-reaching applications in human health and nutrition. These four compounds occupy a central position as branch point intermediates towards a broad spectrum of naturally occurring flavonoids. Here, we report the development of Escherichia coli production chassis for each of these key gatekeeper flavonoids. Selection of key enzymes, genetic construct design and the optimization of process conditions resulted in the highest reported titers for naringenin (484 mg/l), improved production of pinocembrin (198 mg/l) and eriodictyol (55 mg/l from caffeic acid), and provided the first example of in vivo production of homoeriodictyol directly from glycerol (17 mg/l). This work provides a springboard for future production of diverse downstream natural and non-natural flavonoid targets.

Rapid prototyping of microbial production strains for the biomanufacture of potential materials monomers.

Bio-based production of industrial chemicals using synthetic biology can provide alternative green routes from renewable resources, allowing for cleaner production processes. To efficiently produce chemicals on-demand through microbial strain engineering, biomanufacturing foundries have developed automated pipelines that are largely compound agnostic in their time to delivery. Here we benchmark the capabilities of a biomanufacturing pipeline to enable rapid prototyping of microbial cell factories for the production of chemically diverse industrially relevant material building blocks. Over 85 days the pipeline was able to produce 17 potential material monomers and key intermediates by combining 160 genetic parts into 115 unique biosynthetic pathways. To explore the scale-up potential of our prototype production strains, we optimized the enantioselective production of mandelic acid and hydroxymandelic acid, achieving gram-scale production in fed-batch fermenters. The high success rate in the rapid design and prototyping of microbially-produced material building blocks reveals the potential role of biofoundries in leading the transition to sustainable materials production.

Directed evolution of the PcaV allosteric transcription factor to generate a biosensor for aromatic aldehydes.

BACKGROUND: Transcription factor-based biosensors are useful tools for the detection of metabolites and industrially valuable molecules, and present many potential applications in biotechnology and biomedicine. However, the most common approach to develop biosensors relies on employing a limited set of naturally occurring allosteric transcription factors (aTFs). Therefore, altering the ligand specificity of aTFs towards the detection of new effectors is an important goal. RESULTS: Here, the PcaV repressor, a member of the MarR aTF family, was used to develop a biosensor for the detection of hydroxyl-substituted benzoic acids, including protocatechuic acid (PCA). The PCA biosensor was further subjected to directed evolution to alter its ligand specificity towards vanillin and other closely related aromatic aldehydes, to generate the Van2 biosensor. Ligand recognition of Van2 was explored in vitro using a range of biochemical and biophysical analyses, and extensive in vivo genetic-phenotypic analysis was performed to determine the role of each amino acid change upon biosensor performance. CONCLUSIONS: This is the first study to report directed evolution of a member of the MarR aTF family, and demonstrates the plasticity of the PCA biosensor by altering its ligand specificity to generate a biosensor for aromatic aldehydes.

An automated pipeline for the screening of diverse monoterpene synthase libraries.

Monoterpenoids are a structurally diverse group of natural products with applications as pharmaceuticals, flavourings, fragrances, pesticides, and biofuels. Recent advances in synthetic biology offer new routes to this chemical diversity through the introduction of heterologous isoprenoid production pathways into engineered microorganisms. Due to the nature of the branched reaction mechanism, monoterpene synthases often produce multiple products when expressed in monoterpenoid production platforms. Rational engineering of terpene synthases is challenging due to a lack of correlation between protein sequence and cyclisation reaction catalysed. Directed evolution offers an attractive alternative protein engineering strategy as limited prior sequence-function knowledge is required. However, directed evolution of terpene synthases is hampered by the lack of a convenient high-throughput screening assay for the detection of multiple volatile terpene products. Here we applied an automated pipeline for the screening of diverse monoterpene synthase libraries, employing robotic liquid handling platforms coupled to GC-MS, and automated data extraction. We used the pipeline to screen pinene synthase variant libraries, with mutations in three areas of plasticity, capable of producing multiple monoterpene products. We successfully identified variants with altered product profiles and demonstrated good agreement between the results of the automated screen and traditional shake-flask cultures. In addition, useful insights into the cyclisation reaction catalysed by pinene synthase were obtained, including the identification of positions with the highest level of plasticity, and the significance of region 2 in carbocation cyclisation. The results obtained will aid the prediction and design of novel terpene synthase activities towards clean monoterpenoid products.

Experiment and Simulation Reveal How Mutations in Functional Plasticity Regions Guide Plant Monoterpene Synthase Product Outcome.

Monoterpenes (C10 isoprenoids) are a structurally diverse group of natural compounds that are attractive to industry as flavours and fragrances. Monoterpenes are produced from a single linear substrate, geranyl diphosphate, by a group of enzymes called the monoterpene cyclases/synthases (mTC/Ss) that catalyse high-energy cyclisation reactions involving unstable carbocation intermediates. Efforts towards producing monoterpenes via biocatalysis or metabolic engineering often result in the formation of multiple products due to the nature of the highly branched reaction mechanism of mTC/Ss. Rational engineering of mTC/Ss is hampered by the lack of correlation between the active site sequence and cyclisation type. We used available mutagenesis data to show that amino acids involved in product outcome are clustered and spatially conserved within the mTC/S family. Consensus sequences for three such plasticity regions were introduced in different mTC/S with increasingly complex cyclisation cascades, including the model enzyme limonene synthase (LimS). In all three mTC/S studied, mutations in the first two regions mostly give rise to products that result from premature quenching of the linalyl or α-terpinyl cations, suggesting that both plasticity regions are involved in the formation and stabilisation of cations early in the reaction cascade. A LimS variant with mutations in the second region (S454G, C457V, M458I), produced mainly more complex bicyclic products. QM/MM MD simulations reveal that the second cyclisation is not due to compression of the C2-C7 distance in the α-terpinyl cation, but is the result of an increased distance between C8 of the α-terpinyl cation and two putative bases (W324, H579) located on the other side of the active site, preventing early termination by deprotonation. Such insights into the impact of mutations can only be obtained using integrated experimental and computational approaches, and will aid the design of altered mTC/S activities towards clean monoterpenoid products.

GeneORator: An Effective Strategy for Navigating Protein Sequence Space More Efficiently through Boolean OR-Type DNA Libraries.

Directed evolution requires the creation of genetic diversity and subsequent screening or selection for improved variants. For DNA mutagenesis, conventional site-directed methods implicitly utilize the Boolean AND operator (creating all mutations simultaneously), producing a combinatorial explosion in the number of genetic variants as the number of mutations increases. We introduce GeneORator, a novel strategy for creating DNA libraries based on the Boolean logical OR operator. Here, a single library is divided into many subsets, each containing different combinations of the desired mutations. Consequently, the effect of adding more mutations on the number of genetic combinations is additive (Boolean OR logic) and not exponential (AND logic). We demonstrate this strategy with large-scale mutagenesis studies, using monoamine oxidase-N ( Aspergillus niger) as the exemplar target. First, we mutated every residue in the secondary structure-containing regions (276 out of a total 495 amino acids) to screen for improvements in kcat. Second, combinatorial OR-type libraries permitted screening of diverse mutation combinations in the enzyme active site to detect activity toward novel substrates. In both examples, OR-type libraries effectively reduced the number of variants searched up to 1010-fold, dramatically reducing the screening effort required to discover variants with improved and/or novel activity. Importantly, this approach enables the screening of a greater diversity of mutation combinations, accessing a larger area of a protein's sequence space. OR-type libraries can be applied to any biological engineering objective requiring DNA mutagenesis, and the approach has wide ranging applications in, for example, enzyme engineering, antibody engineering, and synthetic biology.

Highly multiplexed, fast and accurate nanopore sequencing for verification of synthetic DNA constructs and sequence libraries.

Synthetic biology utilizes the Design-Build-Test-Learn pipeline for the engineering of biological systems. Typically, this requires the construction of specifically designed, large and complex DNA assemblies. The availability of cheap DNA synthesis and automation enables high-throughput assembly approaches, which generates a heavy demand for DNA sequencing to verify correctly assembled constructs. Next-generation sequencing is ideally positioned to perform this task, however with expensive hardware costs and bespoke data analysis requirements few laboratories utilize this technology in-house. Here a workflow for highly multiplexed sequencing is presented, capable of fast and accurate sequence verification of DNA assemblies using nanopore technology. A novel sample barcoding system using polymerase chain reaction is introduced, and sequencing data are analyzed through a bespoke analysis algorithm. Crucially, this algorithm overcomes the problem of high-error rate nanopore data (which typically prevents identification of single nucleotide variants) through statistical analysis of strand bias, permitting accurate sequence analysis with single-base resolution. As an example, 576 constructs (6 × 96 well plates) were processed in a single workflow in 72 h (from Escherichia coli colonies to analyzed data). Given our procedure's low hardware costs and highly multiplexed capability, this provides cost-effective access to powerful DNA sequencing for any laboratory, with applications beyond synthetic biology including directed evolution, single nucleotide polymorphism analysis and gene synthesis.

Machine Learning of Designed Translational Control Allows Predictive Pathway Optimization in Escherichia coli.

The field of synthetic biology aims to make the design of biological systems predictable, shrinking the huge design space to practical numbers for testing. When designing microbial cell factories, most optimization efforts have focused on enzyme and strain selection/engineering, pathway regulation, and process development. In silico tools for the predictive design of bacterial ribosome binding sites (RBSs) and RBS libraries now allow translational tuning of biochemical pathways; however, methods for predicting optimal RBS combinations in multigene pathways are desirable. Here we present the implementation of machine learning algorithms to model the RBS sequence-phenotype relationship from representative subsets of large combinatorial RBS libraries allowing the accurate prediction of optimal high-producers. Applied to a recombinant monoterpenoid production pathway in Escherichia coli, our approach was able to boost production titers by over 60% when screening under 3% of a library. To facilitate library screening, a multiwell plate fermentation procedure was developed, allowing increased screening throughput with sufficient resolution to discriminate between high and low producers. High producers from one library did not translate during scale-up, but the reduced screening requirements allowed rapid rescreening at the larger scale. This methodology is potentially compatible with any biochemical pathway and provides a powerful tool toward predictive design of bacterial production chassis.

An automated Design-Build-Test-Learn pipeline for enhanced microbial production of fine chemicals.

The microbial production of fine chemicals provides a promising biosustainable manufacturing solution that has led to the successful production of a growing catalog of natural products and high-value chemicals. However, development at industrial levels has been hindered by the large resource investments required. Here we present an integrated Design-Build-Test-Learn (DBTL) pipeline for the discovery and optimization of biosynthetic pathways, which is designed to be compound agnostic and automated throughout. We initially applied the pipeline for the production of the flavonoid (2S)-pinocembrin in Escherichia coli, to demonstrate rapid iterative DBTL cycling with automation at every stage. In this case, application of two DBTL cycles successfully established a production pathway improved by 500-fold, with competitive titers up to 88 mg L-1. The further application of the pipeline to optimize an alkaloids pathway demonstrates how it could facilitate the rapid optimization of microbial strains for production of any chemical compound of interest.

Ultra-high throughput functional enrichment of large monoamine oxidase (MAO-N) libraries by fluorescence activated cell sorting.

Directed evolution enables the improvement and optimisation of enzymes for particular applications and is a valuable tool for biotechnology and synthetic biology. However, studies are often limited in their scope by the inability to screen very large numbers of variants to identify improved enzymes. One class of enzyme for which a universal, operationally simple ultra-high throughput (>106 variants per day) assay is not available is flavin adenine dinucleotide (FAD) dependent oxidases. The current high throughput assay involves a visual, colourimetric, colony-based screen, however this is not suitable for very large libraries and does not enable quantification of the relative fitness of variants. To address this, we describe an optimised method for the sensitive detection of oxidase activity within single Escherichia coli (E. coli) cells, using the monoamine oxidase from Aspergillus niger, MAO-N, as a model system. In contrast to other methods for the screening of oxidase activity in vivo, this method does not require cell surface expression, emulsion formation or the addition of an extracellular peroxidase. Furthermore, we show that fluorescence activated cell sorting (FACS) of large libraries derived from MAO-N under the assay conditions can enrich the library in functional variants at much higher rates than via the colony-based method. We demonstrate its use for directed evolution by identifying a new mutant of MAO-N with improved activity towards a novel secondary amine substrate. This work demonstrates, for the first time, an ultra-high throughput screening methodology widely applicable for the directed evolution of FAD dependent oxidases in E. coli.

Fast and Flexible Synthesis of Combinatorial Libraries for Directed Evolution.

Directed evolution (DE) is a powerful tool for optimizing an enzyme's properties toward a particular objective, such as broader substrate scope, greater thermostability, or increased kcat. A successful DE project requires the generation of genetic diversity and subsequent screening or selection to identify variants with improved fitness. In contrast to random methods (error-prone PCR or DNA shuffling), site-directed mutagenesis enables the rational design of variant libraries and provides control over the nature and frequency of the encoded mutations. Knowledge of protein structure, dynamics, enzyme mechanisms, and natural evolution demonstrates that multiple (combinatorial) mutations are required to discover the most improved variants. To this end, we describe an experimentally straightforward and low-cost method for the preparation of combinatorial variant libraries. Our approach employs a two-step PCR protocol, first producing mutagenic megaprimers, which can then be combined in a "mix-and-match" fashion to generate diverse sets of combinatorial variant libraries both quickly and accurately.

Engineering the "Missing Link" in Biosynthetic (-)-Menthol Production: Bacterial Isopulegone Isomerase.

The realization of a synthetic biology approach to microbial (1R,2S,5R)-(-)-menthol (1) production relies on the identification of a gene encoding an isopulegone isomerase (IPGI), the only enzyme in the Mentha piperita biosynthetic pathway as yet unidentified. We demonstrate that Δ5-3-ketosteroid isomerase (KSI) from Pseudomonas putida can act as an IPGI, producing (R)-(+)-pulegone ((R)-2) from (+)-cis-isopulegone (3). Using a robotics-driven semirational design strategy, we identified a key KSI variant encoding four active site mutations, which confer a 4.3-fold increase in activity over the wild-type enzyme. This was assisted by the generation of crystal structures of four KSI variants, combined with molecular modeling of 3 binding to identify key active site residue targets. The KSI variant was demonstrated to function efficiently within cascade biocatalytic reactions with downstream Mentha enzymes pulegone reductase and (-)-menthone:(-)-menthol reductase to generate 1 from 3. This study introduces the use of a recombinant IPGI, engineered to function efficiently within a biosynthetic pathway for the production of 1 in microorganisms.

Computing exponentially faster: implementing a non-deterministic universal Turing machine using DNA.

The theory of computer science is based around universal Turing machines (UTMs): abstract machines able to execute all possible algorithms. Modern digital computers are physical embodiments of classical UTMs. For the most important class of problem in computer science, non-deterministic polynomial complete problems, non-deterministic UTMs (NUTMs) are theoretically exponentially faster than both classical UTMs and quantum mechanical UTMs (QUTMs). However, no attempt has previously been made to build an NUTM, and their construction has been regarded as impossible. Here, we demonstrate the first physical design of an NUTM. This design is based on Thue string rewriting systems, and thereby avoids the limitations of most previous DNA computing schemes: all the computation is local (simple edits to strings) so there is no need for communication, and there is no need to order operations. The design exploits DNA's ability to replicate to execute an exponential number of computational paths in P time. Each Thue rewriting step is embodied in a DNA edit implemented using a novel combination of polymerase chain reactions and site-directed mutagenesis. We demonstrate that the design works using both computational modelling and in vitro molecular biology experimentation: the design is thermodynamically favourable, microprogramming can be used to encode arbitrary Thue rules, all classes of Thue rule can be implemented, and non-deterministic rule implementation. In an NUTM, the resource limitation is space, which contrasts with classical UTMs and QUTMs where it is time. This fundamental difference enables an NUTM to trade space for time, which is significant for both theoretical computer science and physics. It is also of practical importance, for to quote Richard Feynman 'there's plenty of room at the bottom'. This means that a desktop DNA NUTM could potentially utilize more processors than all the electronic computers in the world combined, and thereby outperform the world's current fastest supercomputer, while consuming a tiny fraction of its energy.