Andrew Currin
University of Manchester
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Publication
Featured researches published by Andrew Currin.
Chemical Society Reviews | 2015
Andrew Currin; Neil Swainston; Philip J. R. Day; Douglas B. Kell
Improving enzymes by directed evolution requires the navigation of very large search spaces; we survey how to do this intelligently.
Protein Engineering Design & Selection | 2014
Andrew Currin; Neil Swainston; Philip J. R. Day; Douglas B. Kell
The de novo synthesis of genes is becoming increasingly common in synthetic biology studies. However, the inherent error rate (introduced by errors incurred during oligonucleotide synthesis) limits its use in synthesising protein libraries to only short genes. Here we introduce SpeedyGenes, a PCR-based method for the synthesis of diverse protein libraries that includes an error-correction procedure, enabling the efficient synthesis of large genes for use directly in functional screening. First, we demonstrate an accurate gene synthesis method by synthesising and directly screening (without pre-selection) a 747 bp gene for green fluorescent protein (yielding 85% fluorescent colonies) and a larger 1518 bp gene (a monoamine oxidase, producing 76% colonies with full catalytic activity, a 4-fold improvement over previous methods). Secondly, we show that SpeedyGenes can accommodate multiple and combinatorial variant sequences while maintaining efficient enzymatic error correction, which is particularly crucial for larger genes. In its first application for directed evolution, we demonstrate the use of SpeedyGenes in the synthesis and screening of large libraries of MAO-N variants. Using this method, libraries are synthesised, transformed and screened within 3 days. Importantly, as each mutation we introduce is controlled by the oligonucleotide sequence, SpeedyGenes enables the synthesis of large, diverse, yet controlled variant sequences for the purposes of directed evolution.
Nucleic Acids Research | 2014
Neil Swainston; Andrew Currin; Philip J. R. Day; Douglas B. Kell
GeneGenie, a new online tool available at http://www.gene-genie.org, is introduced to support the design and self-assembly of synthetic genes and constructs. GeneGenie allows for the design of oligonucleotide cohorts encoding the gene sequence optimized for expression in any suitable host through an intuitive, easy-to-use web interface. The tool ensures consistent oligomer overlapping melting temperatures, minimizes the likelihood of misannealing, optimizes codon usage for expression in a selected host, allows for specification of forward and reverse cloning sequences (for downstream ligation) and also provides support for mutagenesis or directed evolution studies. Directed evolution studies are enabled through the construction of variant libraries via the optional specification of ‘variant codons’, containing mixtures of bases, at any position. For example, specifying the variant codon TNT (where N is any nucleotide) will generate an equimolar mixture of the codons TAT, TCT, TGT and TTT at that position, encoding a mixture of the amino acids Tyr, Ser, Cys and Phe. This facility is demonstrated through the use of GeneGenie to develop and synthesize a library of enhanced green fluorescent protein variants.
Journal of the Royal Society Interface | 2017
Andrew Currin; Konstantin Korovin; Maria Ababi; Katherine Roper; Douglas B. Kell; Philip J. R. Day; Ross D. King
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 DNAs 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 ‘theres 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 worlds current fastest supercomputer, while consuming a tiny fraction of its energy.
Biochemical Society Transactions | 2016
Pablo Carbonell; Andrew Currin; Mark S. Dunstan; Donal Fellows; Adrian J. Jervis; Nicholas J. W. Rattray; Christopher J. Robinson; Neil Swainston; Maria Vinaixa; Alan R. Williams; Cunyu Yan; Perdita E. Barran; Rainer Breitling; George Guo-Qiang Chen; Jean-Loup Faulon; Carole A. Goble; Royston Goodacre; Douglas B. Kell; Rosalind A. Le Feuvre; Jason Micklefield; Nigel S. Scrutton; Philip Shapira; Eriko Takano; Nicholas J. Turner
The Manchester Synthetic Biology Research Centre (SYNBIOCHEM) is a foundry for the biosynthesis and sustainable production of fine and speciality chemicals. The Centres integrated technology platforms provide a unique capability to facilitate predictable engineering of microbial bio-factories for chemicals production. An overview of these capabilities is described.
ACS Catalysis | 2018
Andrew Currin; Mark S. Dunstan; Linus O. Johannissen; Katherine A. Hollywood; Maria Vinaixa; Adrian J. Jervis; Neil Swainston; Nicholas J. W. Rattray; John M. Gardiner; Douglas B. Kell; Eriko Takano; Helen S. Toogood; Nigel S. Scrutton
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.
Synthetic and Systems Biotechnology | 2016
Le Feuvre Ra; Pablo Carbonell; Andrew Currin; Mark S. Dunstan; Donal Fellows; Adrian J. Jervis; Rattray Njw; Christopher J. Robinson; Neil Swainston; Maria Vinaixa; Antony J. Williams; Cunyu Yan; Perdita E. Barran; Rainer Breitling; George Guo-Qiang Chen; Jean-Loup Faulon; Carole A. Goble; Royston Goodacre; Douglas B. Kell; Jason Micklefield; Nigel S. Scrutton; Philip Shapira; Eriko Takano; Nicholas J. Turner
The UK Synthetic Biology Research Centre, SYNBIOCHEM, hosted by the Manchester Institute of Biotechnology at the University of Manchester is delivering innovative technology platforms to facilitate the predictable engineering of microbial bio-factories for fine and speciality chemicals production. We provide an overview of our foundry activities that are being applied to grand challenge projects to deliver innovation in bio-based chemicals production for industrial biotechnology.
Methods of Molecular Biology | 2017
Andrew Currin; Neil Swainston; Philip J. R. Day; Douglas B. Kell
Gene synthesis is a fundamental technology underpinning much research in the life sciences. In particular, synthetic biology and biotechnology utilize gene synthesis to assemble any desired DNA sequence, which can then be incorporated into novel parts and pathways. Here, we describe SpeedyGenes, a gene synthesis method that can assemble DNA sequences with greater fidelity (fewer errors) than existing methods, but that can also be used to encode extensive, statistically designed sequence variation at any position in the sequence to create diverse (but accurate) variant libraries. We summarize the integrated use of GeneGenie to design DNA and oligonucleotide sequences, followed by the procedure for assembling these accurately and efficiently using SpeedyGenes.
Communications Biology | 2018
Pablo Carbonell; Adrian J. Jervis; Christopher J. Robinson; Cunyu Yan; Mark S. Dunstan; Neil Swainston; Maria Vinaixa; Katherine A. Hollywood; Andrew Currin; Nicholas J. W. Rattray; Sandra Taylor; Reynard Spiess; Rehana Sung; Alan R. Williams; Donal Fellows; Natalie Stanford; Paul Mulherin; Rosalind A. Le Feuvre; Perdita E. Barran; Royston Goodacre; Nicholas J. Turner; Carole A. Goble; George Guo-Qiang Chen; Douglas B. Kell; Jason Micklefield; Rainer Breitling; Eriko Takano; Jean-Loup Faulon; Nigel S. Scrutton
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.Pablo Carbonell et al. present an automated pipeline for the discovery and optimization of biosynthetic pathways for microbial production of fine chemicals. They apply their pipeline to the production of the flavonoid (2S)-pinocembrin in Escherichia coli and show improvement of the pathway by 500-fold.
Natural Product Reports | 2016
Pablo Carbonell; Andrew Currin; Adrian J. Jervis; Nicholas J. W. Rattray; Neil Swainston; Cunyu Yan; Eriko Takano; Rainer Breitling