413 results found
Kitney RI, Bell J, Philp J, 2021, Build a Sustainable Vaccines Industry with Synthetic Biology., Trends Biotechnol
The vaccines industry has not changed appreciably in decades regarding technology, and has struggled to remain viable, with large companies withdrawing from production. Meanwhile, there has been no let-up in outbreaks of viral disease, at a time when the biopharmaceuticals industry is discussing downsizing. The distributed manufacturing model aligns well with this, and the advent of synthetic biology promises much in terms of vaccine design. Biofoundries separate design from manufacturing, a hallmark of modern engineering. Once designed in a biofoundry, digital code can be transferred to a small-scale manufacturing facility close to the point of care, rather than physically transferring cold-chain-dependent vaccine. Thus, biofoundries and distributed manufacturing have the potential to open up a new era of biomanufacturing, one based on digital biology and information systems. This seems a better model for tackling future outbreaks and pandemics.
Clarke L, Kitney R, 2020, Developing synthetic biology for industrial biotechnology applications, BIOCHEMICAL SOCIETY TRANSACTIONS, Vol: 48, Pages: 113-122, ISSN: 0300-5127
Kitney R, Adeogun M, Fujishima Y, et al., 2019, Enabling the Advanced Bioeconomy through Public Policy Supporting Biofoundries and Engineering Biology, TRENDS IN BIOTECHNOLOGY, Vol: 37, Pages: 917-920, ISSN: 0167-7799
Hillson N, Caddick M, Cai Y, et al., 2019, Building a global alliance of biofoundries (vol 10, 2040, 2019), Nature Communications, Vol: 10, Pages: 1-2, ISSN: 2041-1723
Rajakumar PD, Gower G, Suckling L, et al., 2019, Rapid prototyping platform for Saccharomyces cerevisiae using computer-aided genetic design enabled by parallel software and workcell platform development, Slas Technology, Vol: 24, Pages: 291-297, ISSN: 2472-6303
Biofoundries have enabled the ability to automate the construction of genetic constructs using computer-aided design. In this study, we have developed the methodology required to abstract and automate the construction of yeast-compatible designs. We demonstrate the use of our in-house software tool, AMOS, to coordinate with design software, JMP, and robotic liquid handling platforms to successfully manage the construction of a library of 88 yeast expression plasmids. In this proof-of-principle study, we used three fluorescent genes as proxy for three enzyme coding sequences. Our platform has been designed to quickly iterate around a design cycle of four protein coding sequences per plasmid, with larger numbers possible with multiplexed genome integrations in Saccharomyces cerevisiae. This work highlights how developing scalable new biotechnology applications requires a close integration between software development, liquid handling robotics, and protocol development.
Suckling L, McFarlane C, Sawyer C, et al., 2019, Miniaturisation of high-throughput plasmid DNA library preparation for next-generation sequencing using multifactorial optimisation, Synthetic and Systems Biotechnology, Vol: 4, Pages: 57-66, ISSN: 2405-805X
High-throughput preparation of plasmid DNA libraries for next-generation sequencing (NGS) is an important capability for molecular biology laboratories. In particular, it is an essential quality control (QC) check when large numbers of plasmid variants are being generated. Here, we describe the use of the Design of Experiments (DOE) methodology to optimise the miniaturised preparation of plasmid DNA libraries for NGS, using the Illumina® Nextera XT technology and the Labcyte Echo® acoustic liquid dispensing system. Furthermore, we describe methods which can be implemented as a QC check for identifying the presence of genomic DNA (gDNA) in plasmid DNA samples and the subsequent shearing of the gDNA, which otherwise prevents the acoustic transfer of plasmid DNA. This workflow enables the preparation of plasmid DNA libraries which yield high-quality sequencing data.
Exley K, Reynolds C, Suckling L, et al., 2019, Utilising datasheets for the informed automated design and build of a synthetic metabolic pathway, Journal of Biological Engineering, Vol: 13, ISSN: 1754-1611
BackgroundThe automation of modular cloning methodologies permits the assembly of many genetic designs. Utilising characterised biological parts aids in the design and redesign of genetic pathways. The characterisation information held on datasheets can be used to determine whether a biological part meets the design requirements. To manage the design of genetic pathways, researchers have turned to modelling-based computer aided design software tools.ResultAn automated workflow has been developed for the design and build of heterologous metabolic pathways. In addition, to demonstrate the powers of electronic datasheets we have developed software which can transfer part information from a datasheet to the Design of Experiment software JMP. To this end we were able to use Design of Experiment software to rationally design and test randomised samples from the design space of a lycopene pathway in E. coli. This pathway was optimised by individually modulating the promoter strength, RBS strength, and gene order targets.ConclusionThe use of standardised and characterised biological parts will empower a design-oriented synthetic biology for the forward engineering of heterologous expression systems. A Design of Experiment approach streamlines the design-build-test cycle to achieve optimised solutions in biodesign. Developed automated workflows provide effective transfer of information between characterised information (in the form of datasheets) and DoE software.
Sainz de Murieta I, Bultelle M, Kitney R, 2018, A Data Model for Biopart Datasheets, Engineering Biology, Vol: 2, Pages: 7-18
This study introduces a new data model, based on the DICOM-SB (see glossary of terms for definition of acronyms) standard for synthetic biology, that is capable of describing/incorporating the data, metadata and ancillary information from detailed characterisation experiments - to present DNA components (bioparts) in datasheets. The data model offers a standardised mechanism to associate bioparts with data and information about component performance - in a particular biological context (or a range of contexts, e.g. chassis). The data model includes the raw, experimental data for each characterisation run, and the protocol details needed to reliably reproduce the experiment. In addition, it provides metrics (e.g. relative promoter units, synthesis/growth rates etc.) that constitute the main content of a biopart datasheet. The data model has been developed to directly link to DICOM-SB, but also to be compatible with existing data standards, e.g. SBOL and SBML. It has been implemented within the latest version of the API that enables access to the SynBIS information system. The work should contribute significantly to the current standardisation effort in synthetic biology. The standard data model for datasheets is seen as a necessary step towards effective interoperability between part repositories, and between repositories and BioCAD applications.
Claesen S, Stone A, van Rossum M, et al., 2017, Comprehensive web-based broker for bio-technology design and manufacturing, Engineering Biology, Vol: 1, Pages: 100-102, ISSN: 2398-6182
Synthetic biology, particularly in relation to characterisation experiments relating to the description of bio-parts frequently involves the use of a wide range of equipment, including, for example, plate reader's, flow cytometers, and mass spectrometers. This equipment is often from multiple manufacturers. The study describes broker technology that has been developed which has the ability to connect multiple types of equipment into a common information environment; the connectivity from the databases and equipment is achieved using Visbion's ‘cube’ technology that involves military specification encryption for data security. The broker technology uses a new, developing standard, Digital Imaging and Communication in Medicine (DICOM)-SB, that is based on the highly successful international standard for biomedicine, DICOM. The broker uses a version of the DICOM data model that has been specifically designed for synthetic biology and, in particular, characterisation data.
Kitney RI, Freemont PS, 2017, Engineering biology: a key driver of the bio-economy, Engineering Biology, Vol: 1, Pages: 3-6, ISSN: 2398-6182
This study provides a relatively brief overview of the field of synthetic biology/engineering biology for thenon-specialist reader. This is in line with one of the basic aims of the new journalEngineering Biology–which is toopen up the field to a much wider audience than those currently engaged and, particularly, to people working incompanies and disciplines whose technology may be relevant to the field. Consequently, the study contains somedidactic material.
Reynolds CR, Exley K, Bultelle MA, et al., 2017, Debugging experiment machinery through time-course event sequence analysis, Engineering Biology, Vol: 1, Pages: 51-54, ISSN: 2398-6182
This application note describes an open-source web application software package for viewing and analysing time-course event sequences in the form of log files containing timestamps. Web pages allow the visualisation of time-course event sequences as time curves and the comparison of sequences against each other to visualise deviations between the timings of the sequences. A feature allows the analysis of the sequences by parsing selected sections with a support vector machine model that heuristically calculates a value for the likelihood of an error occurring based on the textual output in the log files. This allows quick analysis for errors in files with large numbers of log events. The software is written in ASP.NET with Visual Basic code-behind to allow it to be hosted on servers and integrated into web application frameworks.
Misirli G, Madsen C, Sainz de Murieta I, et al., 2017, Constructing synthetic biology workflows in the cloud, Engineering Biology, Vol: 1, Pages: 61-65, ISSN: 2398-6182
The synthetic biology design process has traditionally been heavily dependent upon manual searching, acquisition and integration of existing biological data. A large amount of such data is already available from Internet-based resources, but data exchange between these resources is often undertaken manually. Automating the communication between different resources can be done by the generation of computational workflows to achieve complex tasks that cannot be carried out easily or efficiently by a single resource. Computational workflows involve the passage of data from one resource, or process, to another in a distributed computing environment. In a typical bioinformatics workflow, the predefined order in which processes are invoked in a synchronous fashion and are described in a workflow definition document. However, in synthetic biology the diversity of resources and manufacturing tasks required favour a more flexible model for process execution. Here, the authors present the Protocol for Linking External Nodes (POLEN), a Cloud-based system that facilitates synthetic biology design workflows that operate asynchronously. Messages are used to notify POLEN resources of events in real time, and to log historical events such as the availability of new data, enabling networks of cooperation. POLEN can be used to coordinate the integration of different synthetic biology resources, to ensure consistency of information across distributed repositories through added support for data standards, and ultimately to facilitate the synthetic biology life cycle for designing and implementing biological systems.
Clarke LJ, Kitney RI, 2016, Synthetic biology in the UK – An outline of plans and progress, Synthetic and Systems Biotechnology, Vol: 1, Pages: 243-257, ISSN: 2405-805X
Synthetic biology is capable of delivering new solutions to key challenges spanning the bioeconomy, both nationally and internationally. Recognising this significant potential and the associated need to facilitate its translation and commercialisation the UK government commissioned the production of a national Synthetic Biology Roadmap in 2011, and subsequently provided crucial support to assist its implementation.Critical infrastructural investments have been made, and important strides made towards the development of an effectively connected community of practitioners and interest groups. A number of Synthetic Biology Research Centres, DNA Synthesis Foundries, a Centre for Doctoral Training, and an Innovation Knowledge Centre have been established, creating a nationally distributed and integrated network of complementary facilities and expertise.The UK Synthetic Biology Leadership Council published a UK Synthetic Biology Strategic Plan in 2016, increasing focus on the processes of translation and commercialisation. Over 50 start-ups, SMEs and larger companies are actively engaged in synthetic biology in the UK, and inward investments are starting to flow.Together these initiatives provide an important foundation for stimulating innovation, actively contributing to international research and development partnerships, and helping deliver useful benefits from synthetic biology in response to local and global needs and challenges.
Sainz de Murieta I, Bultelle M, Kitney RI, 2016, Toward the first data acquisition standard in synthetic biology, ACS Synthetic Biology, Vol: 5, Pages: 817-826, ISSN: 2161-5063
This paper describes the development of a new data acquisition standard for synthetic biology. This comprises the creation of a methodology that is designed to capture all the data, metadata, and protocol information associated with biopart characterization experiments. The new standard, called DICOM-SB, is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. A data model is described which has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data. DICOM-SB also includes services orientated toward the automatic exchange of data and information between modalities and repositories. DICOM-SB has been developed in the context of systematic design in synthetic biology, which is based on the engineering principles of modularity, standardization, and characterization. The systematic design approach utilizes the design, build, test, and learn design cycle paradigm. DICOM-SB has been designed to be compatible with and complementary to other standards in synthetic biology, including SBOL. In this regard, the software provides effective interoperability. The new standard has been tested by experiments and data exchange between Nanyang Technological University in Singapore and Imperial College London.
Chambers S, Kitney R, Freemont P, 2016, The Foundry: the DNA synthesis and construction Foundry at Imperial College., Biochemical Society Transactions, Vol: 44, Pages: 687-688, ISSN: 1470-8752
The establishment of a DNA synthesis and construction foundry at Imperial College in London heralds a new chapter in the development of synthetic biology to meet new global challenges. The Foundry employs the latest technology to make the process of engineering biology easier, faster and scalable. The integration of advanced software, automation and analytics allows the rapid design, build and testing of engineered organisms.
Florea M, Hagemann H, Santosa G, et al., 2016, Engineering control of bacterial cellulose production using a genetic toolkit and a new cellulose-producing strain, Proceedings of the National Academy of Sciences of the United States of America, Vol: 113, Pages: E3431-E3440, ISSN: 1091-6490
Bacterial cellulose is a strong and ultrapure form of cellulose produced naturally by several species of the Acetobacteraceae. Its high strength, purity and biocompatibility make it of great interest to materials science, however precise control of its biosynthesis has remained a challenge for biotechnology. Here we isolate a new strain of Komagataeibacter rhaeticus (Komagataeibacter rhaeticus iGEM) that can produce cellulose at high yields, grow in low nitrogen conditions, and is highly resistant to toxic chemicals. We achieve external control over its bacterial cellulose production through development of a modular genetic toolkit that enables rational reprogramming of the cell. To further its use as an organism for biotechnology, we sequenced its genome and demonstrate genetic circuits that enable functionalization and patterning of heterologous gene expression within the cellulose matrix. This work lays the foundations for using genetic engineering to produce cellulose-based materials, with numerous applications in basic science, materials engineering and biotechnology.
Coghlan A, Kitney R, 2016, Tiny but mighty, New Scientist, Vol: 230, Pages: 7-7, ISSN: 1364-8500
Kitney RI, 2016, DICOM-SB at Imperial
This website hosts supporting information for the paper 'Towards the First Data Acquisition Standard in Synthetic Biology' (Sainz de Murieta, Bultelle, Kitney, 2016) .The paper describes the development of a new data acquisition standard for synthetic biology, called DICOM-SB, which is based on the highly successful Digital Imaging and Communications in Medicine (DICOM) standard in medicine. It also introduces a data model that has been specifically developed for synthetic biology. The model is a modular, extensible data model for the experimental process, which can optimize data storage for large amounts of data.
Reynolds CR, Exley K, Bultelle MA, et al., 2016, Business process management of synthetic biology workflows
Rutten PJ, Kitney RI, 2016, Design and characterisation of new to nature inducible promoters
De Murieta IS, Bultelle M, Kitney RI, 2016, Information standards supporting the characterisation of bioparts in synthetic biology
De Murieta IS, Bultelle M, Kitney RI, 2016, A data model for biopart datasheets
Wong A, Wang H, Poh CL, et al., 2015, Layering genetic circuits to build a single cell, bacterial half adder, BMC Biology, Vol: 13, ISSN: 1741-7007
Background: Gene regulation in biological systems is impacted by the cellular and genetic context-dependenteffects of the biological parts which comprise the circuit. Here, we have sought to elucidate the limitations ofengineering biology from an architectural point of view, with the aim of compiling a set of engineering solutionsfor overcoming failure modes during the development of complex, synthetic genetic circuits.Results: Using a synthetic biology approach that is supported by computational modelling and rigorouscharacterisation, AND, OR and NOT biological logic gates were layered in both parallel and serial arrangements togenerate a repertoire of Boolean operations that include NIMPLY, XOR, half adder and half subtractor logics in asingle cell. Subsequent evaluation of these near-digital biological systems revealed critical design pitfalls thattriggered genetic context-dependent effects, including 5′ UTR interferences and uncontrolled switch-on behaviourof the supercoiled σ54 promoter. In particular, the presence of seven consecutive hairpins immediately downstreamof the promoter transcription start site severely impeded gene expression.Conclusions: As synthetic biology moves forward with greater focus on scaling the complexity of engineeredgenetic circuits, studies which thoroughly evaluate failure modes and engineering solutions will serve as importantreferences for future design and development of synthetic biological systems. This work describes a representativecase study for the debugging of genetic context-dependent effects through principles elucidated herein, therebyproviding a rational design framework to integrate multiple genetic circuits in a single prokaryotic cell.
Tay D, Poh CL, Van Reeth E, et al., 2015, The Effect of Sample Age and Prediction Resolution on Myocardial Infarction Risk Prediction, IEEE JOURNAL OF BIOMEDICAL AND HEALTH INFORMATICS, Vol: 19, Pages: 1178-1185, ISSN: 2168-2194
bultelle, Sainz de Murieta Fuentes I, kitney RI, 2015, Introducing Synbis – the Synthetic Biology Information System, Synthetic Biology: Engineering, Evolution & Design (SEED)
Tay D, Poh CL, Kitney RI, 2015, A novel neural-inspired learning algorithm with application to clinical risk prediction, JOURNAL OF BIOMEDICAL INFORMATICS, Vol: 54, Pages: 305-314, ISSN: 1532-0464
Sainz de Murieta Fuentes I, bultelle M, kitney, 2015, A DICOM Extension Supporting Data Acquisition in Synthetic Biology, Synthetic Biology: Engineering, Evolution & Design (SEED)
This data is extracted from the Web of Science and reproduced under a licence from Thomson Reuters. You may not copy or re-distribute this data in whole or in part without the written consent of the Science business of Thomson Reuters.