1
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Gilliot PA, Gorochowski TE. Transfer learning for cross-context prediction of protein expression from 5'UTR sequence. Nucleic Acids Res 2024:gkae491. [PMID: 38864396 DOI: 10.1093/nar/gkae491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/10/2023] [Revised: 04/28/2024] [Accepted: 05/28/2024] [Indexed: 06/13/2024] Open
Abstract
Model-guided DNA sequence design can accelerate the reprogramming of living cells. It allows us to engineer more complex biological systems by removing the need to physically assemble and test each potential design. While mechanistic models of gene expression have seen some success in supporting this goal, data-centric, deep learning-based approaches often provide more accurate predictions. This accuracy, however, comes at a cost - a lack of generalization across genetic and experimental contexts that has limited their wider use outside the context in which they were trained. Here, we address this issue by demonstrating how a simple transfer learning procedure can effectively tune a pre-trained deep learning model to predict protein translation rate from 5' untranslated region (5'UTR) sequence for diverse contexts in Escherichia coli using a small number of new measurements. This allows for important model features learnt from expensive massively parallel reporter assays to be easily transferred to new settings. By releasing our trained deep learning model and complementary calibration procedure, this study acts as a starting point for continually refined model-based sequence design that builds on previous knowledge and future experimental efforts.
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Affiliation(s)
- Pierre-Aurélien Gilliot
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK
| | - Thomas E Gorochowski
- School of Biological Sciences, University of Bristol, 24 Tyndall Avenue, Bristol BS8 1TQ, UK
- BrisEngBio, School of Chemistry, University of Bristol, Cantock's Close, Bristol BS8 1TS, UK
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2
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Turecka K, Firczuk M, Werel W. Alteration of the -35 and -10 sequences and deletion the upstream sequence of the -35 region of the promoter A1 of the phage T7 in dsDNA confirm the contribution of non-specific interactions with E. coli RNA polymerase to the transcription initiation process. Front Mol Biosci 2024; 10:1335409. [PMID: 38259683 PMCID: PMC10800924 DOI: 10.3389/fmolb.2023.1335409] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2023] [Accepted: 12/18/2023] [Indexed: 01/24/2024] Open
Abstract
Transcription initiation is a multi-step process, in which the RNA polymerase holoenzyme binds to the specific promoter sequences to form a closed complex, which, through intermediate stages, isomerizes into an open complex capable of initiating the productive phase of transcription. The aim of this work was to determine the contribution of the -10 and -35 regions of the promoter, as well as the role of non-specific interactions, in the binding of RNA polymerase and the formation of an active initiation complex capable of transcription. Therefore, fragments of promoter DNA, derived from the strong promoter A1 of the phage T7, containing completely and partially altered elements -35 and -10, and devoid of an upstream region, were constructed using genetic engineering methods. Functional analyses of modified promoter fragments were carried out, checking their ability to form binary complexes with Escherichia coli RNA polymerase (RNAP) and the efficiency of converting binary complexes into triple complexes characteristic of the productive phase of transcription. The obtained results suggest that, in relation to the A1 promoter of the T7 phage, the most important role of the -35 region is carrying the open complex through the next phases of transcription initiation. The weakening of specific impacts within the region -35 is a reason for the defect associated with the transformation of the open complex, formed by a DNA fragment containing the completely altered -35 region, into elongation and the impairment of RNA synthesis. This leads to breaking contacts with the RNA polymerase holoenzyme, and destabilization and disintegration of the complex in the initial phase of productive transcription. This confirms the hypothesis of the so-called stressed intermediate state associated with the stage of transition from the open complex to the elongation complex. The experiments carried out in this work confirm also that the process of promoter localization and recognition, as well as the formation of binary complexes, is sequential in nature, and that the region located upstream of the -35 hexamer, and the hexamer itself, plays here an additive role.
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Affiliation(s)
- Katarzyna Turecka
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Medical University of Gdańsk, Gdańsk, Poland
| | | | - Władysław Werel
- Department of Pharmaceutical Microbiology, Faculty of Pharmacy, Medical University of Gdańsk, Gdańsk, Poland
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3
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Aldulijan I, Beal J, Billerbeck S, Bouffard J, Chambonnier G, Ntelkis N, Guerreiro I, Holub M, Ross P, Selvarajah V, Sprent N, Vidal G, Vignoni A. Functional Synthetic Biology. Synth Biol (Oxf) 2023; 8:ysad006. [PMID: 37073284 PMCID: PMC10105873 DOI: 10.1093/synbio/ysad006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2022] [Revised: 02/17/2023] [Accepted: 04/04/2023] [Indexed: 04/20/2023] Open
Abstract
Synthetic biologists have made great progress over the past decade in developing methods for modular assembly of genetic sequences and in engineering biological systems with a wide variety of functions in various contexts and organisms. However, current paradigms in the field entangle sequence and functionality in a manner that makes abstraction difficult, reduces engineering flexibility and impairs predictability and design reuse. Functional Synthetic Biology aims to overcome these impediments by focusing the design of biological systems on function, rather than on sequence. This reorientation will decouple the engineering of biological devices from the specifics of how those devices are put to use, requiring both conceptual and organizational change, as well as supporting software tooling. Realizing this vision of Functional Synthetic Biology will allow more flexibility in how devices are used, more opportunity for reuse of devices and data, improvements in predictability and reductions in technical risk and cost.
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Affiliation(s)
- Ibrahim Aldulijan
- Systems Engineering, Stevens Institute of Technology, 1 Castle Point Terrace, Hoboken, 07030, NJ, USA
| | | | - Sonja Billerbeck
- Molecular Microbiology, Groningen Biomolecular Sciences and Biotechnology Institute, University of Groningen, Nijenborgh 7, 9747 AG, Groningen, The Netherlands
| | - Jeff Bouffard
- Centre for Applied Synthetic Biology, and Department of Biology, Concordia University, 7141 Sherbrooke Street West, Montréal, H4B 1R6, Québec, Canada
| | - Gaël Chambonnier
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, 02139, MA, USA
| | - Nikolaos Ntelkis
- Specialized Metabolism research group, Center for Plant Systems Biology, VIB-Ghent University, Technologiepark 71, Zwijnaarde, 9052, Belgium
| | - Isaac Guerreiro
- iGEM Foundation, 45 Prospect Street, Cambridge, 02139, MA, USA
| | - Martin Holub
- Delft University of Technology, Van der Maasweg 9, 2629 HZ, The Netherlands
| | - Paul Ross
- BioStrat Marketing, 9965 Harbour Lake Circle, Boynton Beach, FL, 33437, USA
| | | | - Noah Sprent
- Department of Chemical Engineering, Imperial College London, South Kensington Campus, Exhibition Road, SW7 2AZ, UK
| | - Gonzalo Vidal
- Interdisciplinary Computing and Complex BioSystems (ICOS) research group, School of Computing, Newcastle University, Devonshire Building, Devonshire Terrace, NE1 7RU, Newcastle Upon Tyne, UK
| | - Alejandro Vignoni
- Synthetic Biology and Biosystems Control Lab, Instituto de Automatica e Informatica Industrial, Universitat Politecnica de Valencia, Camino de Vera s/n, 46022, Valencia, Spain
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4
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Vidal G, Vitalis C, Muñoz Silva M, Castillo-Passi C, Yáñez Feliú G, Federici F, Rudge TJ. Accurate characterization of dynamic microbial gene expression and growth rate profiles. Synth Biol (Oxf) 2022; 7:ysac020. [PMID: 36267953 PMCID: PMC9569155 DOI: 10.1093/synbio/ysac020] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2021] [Revised: 07/16/2022] [Accepted: 09/29/2022] [Indexed: 11/16/2022] Open
Abstract
Genetic circuits are subject to variability due to cellular and compositional contexts. Cells face changing internal states and environments, the cellular context, to which they sense and respond by changing their gene expression and growth rates. Furthermore, each gene in a genetic circuit operates in a compositional context of genes which may interact with each other and the host cell in complex ways. The context of genetic circuits can, therefore, change gene expression and growth rates, and measuring their dynamics is essential to understanding natural and synthetic regulatory networks that give rise to functional phenotypes. However, reconstruction of microbial gene expression and growth rate profiles from typical noisy measurements of cell populations is difficult due to the effects of noise at low cell densities among other factors. We present here a method for the estimation of dynamic microbial gene expression rates and growth rates from noisy measurement data. Compared to the current state-of-the-art, our method significantly reduced the mean squared error of reconstructions from simulated data of growth and gene expression rates, improving the estimation of timing and magnitude of relevant shapes of profiles. We applied our method to characterize a triple-reporter plasmid library combining multiple transcription units in different compositional and cellular contexts in Escherichia coli. Our analysis reveals cellular and compositional context effects on microbial growth and gene expression rate dynamics and suggests a method for the dynamic ratiometric characterization of constitutive promoters relative to an in vivo reference.
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Affiliation(s)
- Gonzalo Vidal
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
| | - Carolus Vitalis
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Macarena Muñoz Silva
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Carlos Castillo-Passi
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- School of Biomedical Engineering and Imaging Sciences, King’s College London, St Thomas’ Hospital, London, UK
- Millennium Institute for Intelligent Healthcare Engineering (iHEALTH), Santiago, Chile
| | - Guillermo Yáñez Feliú
- Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Fernán Federici
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
- ANID – Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio) & FONDAP Center for Genome Regulation, Santiago, Chile
| | - Timothy J Rudge
- Interdisciplinary Computing and Complex BioSystems (ICOS) Research Group, School of Computing, Newcastle University, Newcastle Upon Tyne, UK
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5
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Pfotenhauer AC, Occhialini A, Nguyen MA, Scott H, Dice LT, Harbison SA, Li L, Reuter DN, Schimel TM, Stewart CN, Beal J, Lenaghan SC. Building the Plant SynBio Toolbox through Combinatorial Analysis of DNA Regulatory Elements. ACS Synth Biol 2022; 11:2741-2755. [PMID: 35901078 PMCID: PMC9396662 DOI: 10.1021/acssynbio.2c00147] [Citation(s) in RCA: 5] [Impact Index Per Article: 2.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
![]()
While the installation of complex genetic circuits in
microorganisms
is relatively routine, the synthetic biology toolbox is severely limited
in plants. Of particular concern is the absence of combinatorial analysis
of regulatory elements, the long design-build-test cycles associated
with transgenic plant analysis, and a lack of naming standardization
for cloning parts. Here, we use previously described plant regulatory
elements to design, build, and test 91 transgene cassettes for relative
expression strength. Constructs were transiently transfected into Nicotiana benthamiana leaves and expression of a
fluorescent reporter was measured from plant canopies, leaves, and
protoplasts isolated from transfected plants. As anticipated, a dynamic
level of expression was achieved from the library, ranging from near
undetectable for the weakest cassette to a ∼200-fold increase
for the strongest. Analysis of expression levels in plant canopies,
individual leaves, and protoplasts were correlated, indicating that
any of the methods could be used to evaluate regulatory elements in
plants. Through this effort, a well-curated 37-member part library
of plant regulatory elements was characterized, providing the necessary
data to standardize construct design for precision metabolic engineering
in plants.
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Affiliation(s)
- Alexander C Pfotenhauer
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Alessandro Occhialini
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Mary-Anne Nguyen
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Helen Scott
- Intelligent Software and Systems, Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Lezlee T Dice
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Stacee A Harbison
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Li Li
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - D Nikki Reuter
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - Tayler M Schimel
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
| | - C Neal Stewart
- Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States.,Department of Plant Sciences, University of Tennessee Knoxville, 2431 Joe Johnson Dr., Knoxville, Tennessee 37996, United States
| | - Jacob Beal
- Intelligent Software and Systems, Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Scott C Lenaghan
- Department of Food Science, University of Tennessee Knoxville, 102 Food Safety and Processing Building 2600 River Dr., Knoxville, Tennessee 37996, United States.,Center for Agricultural Synthetic Biology, University of Tennessee Institute of Agriculture, Knoxville, Tennessee 37996, United States
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6
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Vidal G, Vidal-Céspedes C, Rudge TJ. LOICA: Integrating Models with Data for Genetic Network Design Automation. ACS Synth Biol 2022; 11:1984-1990. [PMID: 35507566 PMCID: PMC9127962 DOI: 10.1021/acssynbio.1c00603] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/01/2021] [Indexed: 11/30/2022]
Abstract
Genetic design automation tools are necessary to expand the scale and complexity of possible synthetic genetic networks. These tools are enabled by abstraction of a hierarchy of standardized components and devices. Abstracted elements must be parametrized from data derived from relevant experiments, and these experiments must be related to the part composition of the abstract components. Here we present Logical Operators for Integrated Cell Algorithms (LOICA), a Python package for designing, modeling, and characterizing genetic networks based on a simple object-oriented design abstraction. LOICA uses classes to represent different biological and experimental components, which generate models through their interactions. These models can be parametrized by direct connection to data contained in Flapjack so that abstracted components of designs can characterize themselves. Models can be simulated using continuous or stochastic methods and the data published and managed using Flapjack. LOICA also outputs SBOL3 descriptions and generates graph representations of genetic network designs.
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Affiliation(s)
- Gonzalo Vidal
- Institute
for Biological and Medical Engineering, Schools of Engineering, Biology,
and Medicine, Pontificia Universidad Católica
de Chile, Santiago 7820244, Chile
- Interdisciplinary
Computing and Complex BioSystems (ICOS) Research Group, School of
Computing, Newcastle University, Newcastle upon Tyne NE1
7RU, U.K.
| | - Carlos Vidal-Céspedes
- Institute
for Biological and Medical Engineering, Schools of Engineering, Biology,
and Medicine, Pontificia Universidad Católica
de Chile, Santiago 7820244, Chile
| | - Timothy J. Rudge
- Interdisciplinary
Computing and Complex BioSystems (ICOS) Research Group, School of
Computing, Newcastle University, Newcastle upon Tyne NE1
7RU, U.K.
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7
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Lawrence JM, Yin Y, Bombelli P, Scarampi A, Storch M, Wey LT, Climent-Catala A, Baldwin GS, O’Hare D, Howe CJ, Zhang JZ, Ouldridge TE, Ledesma-Amaro R. Synthetic biology and bioelectrochemical tools for electrogenetic system engineering. SCIENCE ADVANCES 2022; 8:eabm5091. [PMID: 35507663 PMCID: PMC9067924 DOI: 10.1126/sciadv.abm5091] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/15/2023]
Abstract
Synthetic biology research and its industrial applications rely on deterministic spatiotemporal control of gene expression. Recently, electrochemical control of gene expression has been demonstrated in electrogenetic systems (redox-responsive promoters used alongside redox inducers and electrodes), allowing for the direct integration of electronics with biological processes. However, the use of electrogenetic systems is limited by poor activity, tunability, and standardization. In this work, we developed a strong, unidirectional, redox-responsive promoter before deriving a mutant promoter library with a spectrum of strengths. We constructed genetic circuits with these parts and demonstrated their activation by multiple classes of redox molecules. Last, we demonstrated electrochemical activation of gene expression under aerobic conditions using a novel, modular bioelectrochemical device. These genetic and electrochemical tools facilitate the design and improve the performance of electrogenetic systems. Furthermore, the genetic design strategies used can be applied to other redox-responsive promoters to further expand the available tools for electrogenetics.
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Affiliation(s)
- Joshua M. Lawrence
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | - Yutong Yin
- Department of Bioengineering, Imperial College London, London, UK
| | - Paolo Bombelli
- Department of Biochemistry, University of Cambridge, Cambridge, UK
- Department of Bioengineering, Imperial College London, London, UK
- Department of Environmental Science and Policy, Università degli Studi di Milano, Milano, Italy
| | - Alberto Scarampi
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | - Marko Storch
- London DNA Foundry, Imperial College Translation and Innovation Hub, London, UK
| | - Laura T. Wey
- Department of Biochemistry, University of Cambridge, Cambridge, UK
| | | | | | - Geoff S. Baldwin
- Department of Life Sciences, Imperial College London, London, UK
| | - Danny O’Hare
- Department of Bioengineering, Imperial College London, London, UK
| | | | - Jenny Z. Zhang
- Yusuf Hamied Department of Chemistry, University of Cambridge, Cambridge, UK
| | | | - Rodrigo Ledesma-Amaro
- Department of Bioengineering, Imperial College London, London, UK
- Corresponding author.
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8
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Beal J, Teague B, Sexton JT, Castillo-Hair S, DeLateur NA, Samineni M, Tabor JJ, Weiss R. Meeting Measurement Precision Requirements for Effective Engineering of Genetic Regulatory Networks. ACS Synth Biol 2022; 11:1196-1207. [PMID: 35156365 DOI: 10.1021/acssynbio.1c00488] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Reliable, predictable engineering of cellular behavior is one of the key goals of synthetic biology. As the field matures, biological engineers will become increasingly reliant on computer models that allow for the rapid exploration of design space prior to the more costly construction and characterization of candidate designs. The efficacy of such models, however, depends on the accuracy of their predictions, the precision of the measurements used to parametrize the models, and the tolerance of biological devices for imperfections in modeling and measurement. To better understand this relationship, we have derived an Engineering Error Inequality that provides a quantitative mathematical bound on the relationship between predictability of results, model accuracy, measurement precision, and device characteristics. We apply this relation to estimate measurement precision requirements for engineering genetic regulatory networks given current model and device characteristics, recommending a target standard deviation of 1.5-fold. We then compare these requirements with the results of an interlaboratory study to validate that these requirements can be met via flow cytometry with matched instrument channels and an independent calibrant. On the basis of these results, we recommend a set of best practices for quality control of flow cytometry data and discuss how these might be extended to other measurement modalities and applied to support further development of genetic regulatory network engineering.
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Affiliation(s)
- Jacob Beal
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Brian Teague
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - John T. Sexton
- Department of Bioengineering, Rice University, Houston, Texas 77005, United States
| | | | - Nicholas A. DeLateur
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
| | - Meher Samineni
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Jeffrey J. Tabor
- Department of Bioengineering, Rice University, Houston, Texas 77005, United States
| | - Ron Weiss
- Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts 02139, United States
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9
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Tarnowski MJ, Gorochowski TE. Massively parallel characterization of engineered transcript isoforms using direct RNA sequencing. Nat Commun 2022; 13:434. [PMID: 35064117 PMCID: PMC8783025 DOI: 10.1038/s41467-022-28074-5] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/22/2021] [Accepted: 01/07/2022] [Indexed: 12/23/2022] Open
Abstract
Transcriptional terminators signal where transcribing RNA polymerases (RNAPs) should halt and disassociate from DNA. However, because termination is stochastic, two different forms of transcript could be produced: one ending at the terminator and the other reading through. An ability to control the abundance of these transcript isoforms would offer bioengineers a mechanism to regulate multi-gene constructs at the level of transcription. Here, we explore this possibility by repurposing terminators as 'transcriptional valves' that can tune the proportion of RNAP read-through. Using one-pot combinatorial DNA assembly, we iteratively construct 1780 transcriptional valves for T7 RNAP and show how nanopore-based direct RNA sequencing (dRNA-seq) can be used to characterize entire libraries of valves simultaneously at a nucleotide resolution in vitro and unravel genetic design principles to tune and insulate termination. Finally, we engineer valves for multiplexed regulation of CRISPR guide RNAs. This work provides new avenues for controlling transcription and demonstrates the benefits of long-read sequencing for exploring complex sequence-function landscapes.
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Affiliation(s)
- Matthew J Tarnowski
- School of Biological Sciences, University of Bristol, Tyndall Avenue, Bristol, BS8 1TQ, UK
| | - Thomas E Gorochowski
- School of Biological Sciences, University of Bristol, Tyndall Avenue, Bristol, BS8 1TQ, UK.
- BrisSynBio, University of Bristol, Tyndall Avenue, Bristol, BS8 1TQ, UK.
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10
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Tietze L, Lale R. Importance of the 5' regulatory region to bacterial synthetic biology applications. Microb Biotechnol 2021; 14:2291-2315. [PMID: 34171170 PMCID: PMC8601185 DOI: 10.1111/1751-7915.13868] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/03/2021] [Revised: 06/03/2021] [Accepted: 06/04/2021] [Indexed: 01/02/2023] Open
Abstract
The field of synthetic biology is evolving at a fast pace. It is advancing beyond single-gene alterations in single hosts to the logical design of complex circuits and the development of integrated synthetic genomes. Recent breakthroughs in deep learning, which is increasingly used in de novo assembly of DNA components with predictable effects, are also aiding the discipline. Despite advances in computing, the field is still reliant on the availability of pre-characterized DNA parts, whether natural or synthetic, to regulate gene expression in bacteria and make valuable compounds. In this review, we discuss the different bacterial synthetic biology methodologies employed in the creation of 5' regulatory regions - promoters, untranslated regions and 5'-end of coding sequences. We summarize methodologies and discuss their significance for each of the functional DNA components, and highlight the key advances made in bacterial engineering by concentrating on their flaws and strengths. We end the review by outlining the issues that the discipline may face in the near future.
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Affiliation(s)
- Lisa Tietze
- PhotoSynLabDepartment of BiotechnologyFaculty of Natural SciencesNorwegian University of Science and TechnologyTrondheimN‐7491Norway
| | - Rahmi Lale
- PhotoSynLabDepartment of BiotechnologyFaculty of Natural SciencesNorwegian University of Science and TechnologyTrondheimN‐7491Norway
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11
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Young R, Haines M, Storch M, Freemont PS. Combinatorial metabolic pathway assembly approaches and toolkits for modular assembly. Metab Eng 2020; 63:81-101. [PMID: 33301873 DOI: 10.1016/j.ymben.2020.12.001] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/29/2020] [Revised: 11/16/2020] [Accepted: 12/03/2020] [Indexed: 12/18/2022]
Abstract
Synthetic Biology is a rapidly growing interdisciplinary field that is primarily built upon foundational advances in molecular biology combined with engineering design principles such as modularity and interoperability. The field considers living systems as programmable at the genetic level and has been defined by the development of new platform technologies and methodological advances. A key concept driving the field is the Design-Build-Test-Learn cycle which provides a systematic framework for building new biological systems. One major application area for synthetic biology is biosynthetic pathway engineering that requires the modular assembly of different genetic regulatory elements and biosynthetic enzymes. In this review we provide an overview of modular DNA assembly and describe and compare the plethora of in vitro and in vivo assembly methods for combinatorial pathway engineering. Considerations for part design and methods for enzyme balancing are also presented, and we briefly discuss alternatives to intracellular pathway assembly including microbial consortia and cell-free systems for biosynthesis. Finally, we describe computational tools and automation for pathway design and assembly and argue that a deeper understanding of the many different variables of genetic design, pathway regulation and cellular metabolism will allow more predictive pathway design and engineering.
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Affiliation(s)
- Rosanna Young
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK
| | - Matthew Haines
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK
| | - Marko Storch
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK; London Biofoundry, Imperial College Translation & Innovation Hub, London, W12 0BZ, UK
| | - Paul S Freemont
- Department of Infectious Disease, Sir Alexander Fleming Building, South Kensington Campus, Imperial College London, SW7 2AZ, UK; London Biofoundry, Imperial College Translation & Innovation Hub, London, W12 0BZ, UK; UK DRI Care Research and Technology Centre, Imperial College London, Hammersmith Campus, Du Cane Road, London, W12 0NN, UK.
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12
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Genetic circuit design automation for yeast. Nat Microbiol 2020; 5:1349-1360. [DOI: 10.1038/s41564-020-0757-2] [Citation(s) in RCA: 58] [Impact Index Per Article: 14.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2020] [Accepted: 06/17/2020] [Indexed: 11/08/2022]
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13
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Beal J, Goñi-Moreno A, Myers C, Hecht A, de Vicente MDC, Parco M, Schmidt M, Timmis K, Baldwin G, Friedrichs S, Freemont P, Kiga D, Ordozgoiti E, Rennig M, Rios L, Tanner K, de Lorenzo V, Porcar M. The long journey towards standards for engineering biosystems: Are the Molecular Biology and the Biotech communities ready to standardise? EMBO Rep 2020; 21:e50521. [PMID: 32337821 PMCID: PMC7202200 DOI: 10.15252/embr.202050521] [Citation(s) in RCA: 34] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022] Open
Affiliation(s)
- Jacob Beal
- Raytheon BBN Technologies, Cambridge, MA, USA
| | - Angel Goñi-Moreno
- School of Computing, Newcastle University, Newcastle upon Tyne, UK.,Centro de Biotecnología y Genómica de Plantas, (CBGP, UPM-INIA), Universidad Politécnica de Madrid, Pozuelo de Alarcón, Spain
| | | | | | | | | | | | - Kenneth Timmis
- Institute of Microbiology, Technical University Braunschweig, Braunschweig, Germany
| | | | | | | | | | | | - Maja Rennig
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Lyngby, Denmark
| | - Leonardo Rios
- Institute for Bioengineering and Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, UK
| | | | | | - Manuel Porcar
- Institute for Integrative Systems Biology, University of Valencia, Paterna, Spain
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14
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Shin J, Zhang S, Der BS, Nielsen AAK, Voigt CA. Programming Escherichia coli to function as a digital display. Mol Syst Biol 2020; 16:e9401. [PMID: 32141239 PMCID: PMC7058928 DOI: 10.15252/msb.20199401] [Citation(s) in RCA: 37] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/09/2019] [Revised: 02/04/2020] [Accepted: 02/07/2020] [Indexed: 01/18/2023] Open
Abstract
Synthetic genetic circuits offer the potential to wield computational control over biology, but their complexity is limited by the accuracy of mathematical models. Here, we present advances that enable the complete encoding of an electronic chip in the DNA carried by Escherichia coli (E. coli). The chip is a binary-coded digit (BCD) to 7-segment decoder, associated with clocks and calculators, to turn on segments to visualize 0-9. Design automation is used to build seven strains, each of which contains a circuit with up to 12 repressors and two activators (totaling 63 regulators and 76,000 bp DNA). The inputs to each circuit represent the digit to be displayed (encoded in binary by four molecules), and output is the segment state, reported as fluorescence. Implementation requires an advanced gate model that captures dynamics, promoter interference, and a measure of total power usage (RNAP flux). This project is an exemplar of design automation pushing engineering beyond that achievable "by hand", essential for realizing the potential of biology.
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Affiliation(s)
- Jonghyeon Shin
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Shuyi Zhang
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Bryan S Der
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Alec AK Nielsen
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
| | - Christopher A Voigt
- Department of Biological EngineeringMassachusetts Institute of TechnologyCambridgeMAUSA
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15
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Jin L, Nawab S, Xia M, Ma X, Huo Y. Context-dependency of synthetic minimal promoters in driving gene expression: a case study. Microb Biotechnol 2019; 12:1476-1486. [PMID: 31578818 PMCID: PMC6801132 DOI: 10.1111/1751-7915.13489] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/09/2019] [Accepted: 09/09/2019] [Indexed: 12/13/2022] Open
Abstract
Synthetic promoters are considered ideal candidates in driving robust gene expression. Most of the available synthetic promoters are minimal promoters, for which the upstream sequence of the 5' end of the core region is usually excluded. Although the upstream sequence has been shown to mediate transcription of natural promoters, its impact on synthetic promoters has not been widely studied. Here, a library of chromosomal DNA fragments is randomly fused with the 5' end of the J23119 synthetic promoter, and the transcriptional performance of the promoter is evaluated through β-galactosidase assay, fluorescence intensity and chemical biosynthesis. Results show that changes in the upstream sequence can induce significant variation in the promoter strength of up to 5.8-fold. The effect is independent of the length of the insertions and the number of potential transcription factor binding sites. Several DNA fragments that are able to enhance the transcription of both the natural and the synthetic promoters are identified. This study indicates that the synthetic minimal promoters are susceptible to the surrounding sequence context. Therefore, the upstream sequence should be treated as an indispensable component in the design and application of synthetic promoters, or as an independent genetic part for the fine-tuning of gene expression.
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Affiliation(s)
- Liyuan Jin
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Said Nawab
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Mengli Xia
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Xiaoyan Ma
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
| | - Yi‐Xin Huo
- Key Laboratory of Molecular Medicine and BiotherapySchool of Life ScienceBeijing Institute of Technology5 South Zhongguancun Street, Haidian DistrictBeijing100081China
- UCLA Institute for Technology Advancement (Suzhou)10 Yueliangwan Road, Suzhou Industrial ParkSuzhou215123China
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16
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Beal J, Overney C, Adler A, Yaman F, Tiberio L, Samineni M. TASBE Flow Analytics: A Package for Calibrated Flow Cytometry Analysis. ACS Synth Biol 2019; 8:1524-1529. [PMID: 31053031 DOI: 10.1021/acssynbio.8b00533] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/04/2023]
Abstract
Flow cytometry is a powerful method for high-throughput precision measurement of cell fluorescence and size. Effective use of this tool for quantification of synthetic biology devices and circuits, however, generally requires careful application of complex multistage workflows for calibration, filtering, and analysis with appropriate statistics. The TASBE Flow Analytics package provides a free, open, and accessible implementation of such workflows in a form designed for high-throughput analysis of large synthetic biology data sets. Given a set of experimental samples and controls, this package can process them to output calibrated data, quantitative analyses and comparisons, automatically generated figures, and detailed debugging and diagnostic reports in both human-readable and machine-readable forms. TASBE Flow Analytics can be used through a simple user-friendly interactive Excel interface, as a library supporting Matlab, Octave, or Python interactive sessions, or as a component integrated into automated workflows.
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Affiliation(s)
- Jacob Beal
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Cassandra Overney
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
- Olin College, Needham, Massachusetts 02492, United States
| | - Aaron Adler
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Fusun Yaman
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Lisa Tiberio
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
| | - Meher Samineni
- Raytheon BBN Technologies, Cambridge, Massachusetts 02138, United States
- University of Utah, Salt Lake City, Utah 84112, United States
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17
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Kent R, Dixon N. Systematic Evaluation of Genetic and Environmental Factors Affecting Performance of Translational Riboswitches. ACS Synth Biol 2019; 8:884-901. [PMID: 30897329 PMCID: PMC6492952 DOI: 10.1021/acssynbio.9b00017] [Citation(s) in RCA: 10] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/11/2022]
Abstract
Since their discovery, riboswitches have been attractive tools for the user-controlled regulation of gene expression in bacterial systems. Riboswitches facilitate small molecule mediated fine-tuning of protein expression, making these tools of great use to the synthetic biology community. However, the use of riboswitches is often restricted due to context dependent performance and limited dynamic range. Here, we report the drastic improvement of a previously developed orthogonal riboswitch achieved through in vivo functional selection and optimization of flanking coding and noncoding sequences. The behavior of the derived riboswitches was mapped under a wide array of growth and induction conditions, using a structured Design of Experiments approach. This approach successfully improved the maximal protein expression levels 8.2-fold relative to the original riboswitches, and the dynamic range was improved to afford riboswitch dependent control of 80-fold. The optimized orthogonal riboswitch was then integrated downstream of four endogenous stress promoters, responsive to phosphate starvation, hyperosmotic stress, redox stress, and carbon starvation. These responsive stress promoter-riboswitch devices were demonstrated to allow for tuning of protein expression up to ∼650-fold in response to both environmental and cellular stress responses and riboswitch dependent attenuation. We envisage that these riboswitch stress responsive devices will be useful tools for the construction of advanced genetic circuits, bioprocessing, and protein expression.
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Affiliation(s)
- R. Kent
- Manchester Institute of Biotechnology, School of Chemistry, University of Manchester, Manchester M13 9PL, United Kingdom
| | - N. Dixon
- Manchester Institute of Biotechnology, School of Chemistry, University of Manchester, Manchester M13 9PL, United Kingdom
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18
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Mechanistic Models of Inducible Synthetic Circuits for Joint Description of DNA Copy Number, Regulatory Protein Level, and Cell Load. Processes (Basel) 2019. [DOI: 10.3390/pr7030119] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/06/2023] Open
Abstract
Accurate predictive mathematical models are urgently needed in synthetic biology to support the bottom-up design of complex biological systems, minimizing trial-and-error approaches. The majority of models used so far adopt empirical Hill functions to describe activation and repression in exogenously-controlled inducible promoter systems. However, such equations may be poorly predictive in practical situations that are typical in bottom-up design, including changes in promoter copy number, regulatory protein level, and cell load. In this work, we derived novel mechanistic steady-state models of the lux inducible system, used as case study, relying on different assumptions on regulatory protein (LuxR) and cognate promoter (Plux) concentrations, inducer-protein complex formation, and resource usage limitation. We demonstrated that a change in the considered model assumptions can significantly affect circuit output, and preliminary experimental data are in accordance with the simulated activation curves. We finally showed that the models are identifiable a priori (in the analytically tractable cases) and a posteriori, and we determined the specific experiments needed to parametrize them. Although a larger-scale experimental validation is required, in the future the reported models may support synthetic circuits output prediction in practical situations with unprecedented details.
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19
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Exley K, Reynolds CR, Suckling L, Chee SM, Tsipa A, Freemont PS, McClymont D, Kitney RI. Utilising datasheets for the informed automated design and build of a synthetic metabolic pathway. J Biol Eng 2019; 13:8. [PMID: 30675181 PMCID: PMC6339355 DOI: 10.1186/s13036-019-0141-z] [Citation(s) in RCA: 18] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2018] [Accepted: 01/07/2019] [Indexed: 02/08/2023] Open
Abstract
BACKGROUND The 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. RESULT An 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. CONCLUSION The 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.
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Affiliation(s)
- Kealan Exley
- Department of Bioengineering, Imperial College London, London, UK
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
| | - Christopher Robert Reynolds
- Department of Bioengineering, Imperial College London, London, UK
- Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
| | - Lorna Suckling
- Department of Bioengineering, Imperial College London, London, UK
- The London DNA Foundry, Imperial College London, London, UK
| | - Soo Mei Chee
- Department of Bioengineering, Imperial College London, London, UK
- SynbiCITE, Imperial College London, London, UK
| | - Argyro Tsipa
- Department of Bioengineering, Imperial College London, London, UK
- SynbiCITE, Imperial College London, London, UK
| | - Paul S. Freemont
- SynbiCITE, Imperial College London, London, UK
- Section of Structural Biology, Department of Medicine, Imperial College London, London, UK
| | | | - Richard Ian Kitney
- Department of Bioengineering, Imperial College London, London, UK
- SynbiCITE, Imperial College London, London, UK
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20
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Urtecho G, Tripp AD, Insigne KD, Kim H, Kosuri S. Systematic Dissection of Sequence Elements Controlling σ70 Promoters Using a Genomically Encoded Multiplexed Reporter Assay in Escherichia coli. Biochemistry 2018; 58:1539-1551. [PMID: 29388765 DOI: 10.1021/acs.biochem.7b01069] [Citation(s) in RCA: 46] [Impact Index Per Article: 7.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Promoters are the key drivers of gene expression and are largely responsible for the regulation of cellular responses to time and environment. In Escherichia coli, decades of studies have revealed most, if not all, of the sequence elements necessary to encode promoter function. Despite our knowledge of these motifs, it is still not possible to predict the strength and regulation of a promoter from primary sequence alone. Here we develop a novel multiplexed assay to study promoter function in E. coli by building a site-specific genomic recombination-mediated cassette exchange system that allows for the facile construction and testing of large libraries of genetic designs integrated into precise genomic locations. We build and test a library of 10898 σ70 promoter variants consisting of all combinations of a set of eight -35 elements, eight -10 elements, three UP elements, eight spacers, and eight backgrounds. We find that the -35 and -10 sequence elements can explain approximately 74% of the variance in promoter strength within our data set using a simple log-linear statistical model. Simple neural network models explain >95% of the variance in our data set by capturing nonlinear interactions with the spacer, background, and UP elements.
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Affiliation(s)
- Guillaume Urtecho
- Molecular Biology Interdepartmental Doctoral Program , University of California , Los Angeles , California 90095 , United States
| | - Arielle D Tripp
- Department of Molecular, Cell, and Developmental Biology , University of California , Los Angeles , California 90095 , United States
| | - Kimberly D Insigne
- Bioinformatics Interdepartmental Graduate Program , University of California , Los Angeles , California 90095 , United States
| | - Hwangbeom Kim
- Department of Chemistry and Biochemistry , University of California , Los Angeles , California 90095 , United States
| | - Sriram Kosuri
- Department of Chemistry and Biochemistry , University of California , Los Angeles , California 90095 , United States.,UCLA-DOE Institute for Genomics and Proteomics, Molecular Biology Institute, Quantitative and Computational Biology Institute, Eli and Edythe Broad Center of Regenerative Medicine and Stem Cell Research, Jonsson Comprehensive Cancer Center , University of California , Los Angeles , California 90095 , United States
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21
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Bojar D, Fuhrer T, Fussenegger M. Purity by design: Reducing impurities in bioproduction by stimulus-controlled global translational downregulation of non-product proteins. Metab Eng 2018; 52:110-123. [PMID: 30468874 DOI: 10.1016/j.ymben.2018.11.007] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/30/2018] [Revised: 11/01/2018] [Accepted: 11/17/2018] [Indexed: 01/22/2023]
Abstract
Capitalizing on the ability of mammalian cells to conduct complex post-translational modifications, most protein therapeutics are currently produced in cell culture systems. Addition of a signal peptide to the product protein enables its accumulation in the cell culture supernatant, but separation of the product from endogenously secreted proteins remains costly and labor-intensive. We considered that global downregulation of translation of non-product proteins would be an efficient strategy to minimize downstream processing requirements. Therefore, taking advantage of the ability of mammalian protein kinase R (PKR) to switch off most cellular translation processes in response to infection by viruses, we fused a caffeine-inducible dimerization domain to the catalytic domain of PKR. Addition of caffeine to this construct results in homodimerization and activation of PKR, effectively rewiring rapid global translational downregulation to the addition of the stimulus in a dose-dependent manner. Then, to protect translation of the target therapeutic, we screened viral and cellular internal ribosomal entry sites (IRESes) known or suspected to be resistant to PKR-induced translational stress. After choosing the best-in-class Seneca valley virus (SVV) IRES, we additionally screened for IRES transactivation factors (ITAFs) as well as for supplementary small molecules to further boost the production titer of the product protein under conditions of global translational downregulation. Importantly, the residual global translation activity of roughly 10% under maximal downregulation is sufficient to maintain cellular viability during a production timeframe of at least five days. Standard industrially used adherent as well as suspension-adapted cell lines transfected with this synthetic biology-inspired Protein Kinase R-Enhanced Protein Production (PREPP) system could produce several medicinally relevant protein therapeutics, such as the blockbuster drug rituximab, in substantial quantities and with significantly higher purity than previous culture technologies. We believe incorporation of such purity-by-design technology in the production process will alleviate downstream processing bottlenecks in future biopharmaceutical manufacturing.
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Affiliation(s)
- Daniel Bojar
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058 Basel, Switzerland
| | - Tobias Fuhrer
- ETH Zurich, Institute of Molecular Systems Biology, Auguste-Piccard-Hof 1, 8093 Zurich, Switzerland
| | - Martin Fussenegger
- ETH Zurich, Department of Biosystems Science and Engineering, Mattenstrasse 26, 4058 Basel, Switzerland; Faculty of Life Science, University of Basel, Mattenstrasse 26, CH-4058 Basel, Switzerland.
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22
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Xiang Y, Dalchau N, Wang B. Scaling up genetic circuit design for cellular computing: advances and prospects. NATURAL COMPUTING 2018; 17:833-853. [PMID: 30524216 PMCID: PMC6244767 DOI: 10.1007/s11047-018-9715-9] [Citation(s) in RCA: 29] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 06/09/2023]
Abstract
Synthetic biology aims to engineer and redesign biological systems for useful real-world applications in biomanufacturing, biosensing and biotherapy following a typical design-build-test cycle. Inspired from computer science and electronics, synthetic gene circuits have been designed to exhibit control over the flow of information in biological systems. Two types are Boolean logic inspired TRUE or FALSE digital logic and graded analog computation. Key principles for gene circuit engineering include modularity, orthogonality, predictability and reliability. Initial circuits in the field were small and hampered by a lack of modular and orthogonal components, however in recent years the library of available parts has increased vastly. New tools for high throughput DNA assembly and characterization have been developed enabling rapid prototyping, systematic in situ characterization, as well as automated design and assembly of circuits. Recently implemented computing paradigms in circuit memory and distributed computing using cell consortia will also be discussed. Finally, we will examine existing challenges in building predictable large-scale circuits including modularity, context dependency and metabolic burden as well as tools and methods used to resolve them. These new trends and techniques have the potential to accelerate design of larger gene circuits and result in an increase in our basic understanding of circuit and host behaviour.
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Affiliation(s)
- Yiyu Xiang
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF UK
- Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, EH9 3JR UK
| | | | - Baojun Wang
- School of Biological Sciences, University of Edinburgh, Edinburgh, EH9 3FF UK
- Centre for Synthetic and Systems Biology, University of Edinburgh, Edinburgh, EH9 3JR UK
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23
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Beal J, Haddock-Angelli T, Farny N, Rettberg R. Time to Get Serious about Measurement in Synthetic Biology. Trends Biotechnol 2018; 36:869-871. [DOI: 10.1016/j.tibtech.2018.05.003] [Citation(s) in RCA: 13] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/22/2018] [Revised: 05/11/2018] [Accepted: 05/14/2018] [Indexed: 10/14/2022]
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24
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Designing with living systems in the synthetic yeast project. Nat Commun 2018; 9:2950. [PMID: 30054478 PMCID: PMC6063962 DOI: 10.1038/s41467-018-05332-z] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2018] [Accepted: 06/28/2018] [Indexed: 11/08/2022] Open
Abstract
Synthetic biology is challenged by the complexity and the unpredictability of living systems. While one response to this complexity involves simplifying cells to create more fully specified systems, another approach utilizes directed evolution, releasing some control and using unpredictable change to achieve design goals. Here we discuss SCRaMbLE, employed in the synthetic yeast project, as an example of synthetic biology design through working with living systems. SCRaMbLE is a designed tool without being a design tool, harnessing the activities of the yeast rather than relying entirely on scientists’ deliberate choices. We suggest that directed evolution at the level of the whole organism allows scientists and microorganisms to “collaborate” to achieve design goals, suggesting new directions for synthetic biology. Synthetic biology often views the organism as a chassis into which a circuit can be inserted. Here the authors explore the idea of the organism as a core aspect of design, aiding researchers in navigating the genetic space opened up by SCRaMbLE.
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25
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Wu F, Zhang Q, Wang X. Design of Adjacent Transcriptional Regions to Tune Gene Expression and Facilitate Circuit Construction. Cell Syst 2018; 6:206-215.e6. [PMID: 29428414 PMCID: PMC5832616 DOI: 10.1016/j.cels.2018.01.010] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2017] [Revised: 11/05/2017] [Accepted: 01/08/2018] [Indexed: 01/23/2023]
Abstract
Polycistronic architecture is common for synthetic gene circuits, however, it remains unknown how expression of one gene is affected by the presence of other genes/noncoding regions in the operon, termed adjacent transcriptional regions (ATR). Here, we constructed synthetic operons with a reporter gene flanked by different ATRs, and we found that ATRs with high GC content, small size, and low folding energy lead to high gene expression. Based on these results, we built a model of gene expression and generated a metric that takes into account ATRs. We used the metric to design and construct logic gates with low basal expression and high sensitivity and nonlinearity. Furthermore, we rationally designed synthetic 5'ATRs with different GC content and sizes to tune protein expression levels over a 300-fold range and used these to build synthetic toggle switches with varying basal expression and degrees of bistability. Our comprehensive model and gene expression metric could facilitate the future engineering of more complex synthetic gene circuits.
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Affiliation(s)
- Fuqing Wu
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Qi Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Xiao Wang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA.
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26
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Pasotti L, Bellato M, Casanova M, Zucca S, Cusella De Angelis MG, Magni P. Re-using biological devices: a model-aided analysis of interconnected transcriptional cascades designed from the bottom-up. J Biol Eng 2017; 11:50. [PMID: 29255481 PMCID: PMC5729246 DOI: 10.1186/s13036-017-0090-3] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2017] [Accepted: 11/21/2017] [Indexed: 01/09/2023] Open
Abstract
Background The study of simplified, ad-hoc constructed model systems can help to elucidate if quantitatively characterized biological parts can be effectively re-used in composite circuits to yield predictable functions. Synthetic systems designed from the bottom-up can enable the building of complex interconnected devices via rational approach, supported by mathematical modelling. However, such process is affected by different, usually non-modelled, unpredictability sources, like cell burden. Methods Here, we analyzed a set of synthetic transcriptional cascades in Escherichia coli. We aimed to test the predictive power of a simple Hill function activation/repression model (no-burden model, NBM) and of a recently proposed model, including Hill functions and the modulation of proteins expression by cell load (burden model, BM). To test the bottom-up approach, the circuit collection was divided into training and test sets, used to learn individual component functions and test the predicted output of interconnected circuits, respectively. Results Among the constructed configurations, two test set circuits showed unexpected logic behaviour. Both NBM and BM were able to predict the quantitative output of interconnected devices with expected behaviour, but only the BM was also able to predict the output of one circuit with unexpected behaviour. Moreover, considering training and test set data together, the BM captures circuits output with higher accuracy than the NBM, which is unable to capture the experimental output exhibited by some of the circuits even qualitatively. Finally, resource usage parameters, estimated via BM, guided the successful construction of new corrected variants of the two circuits showing unexpected behaviour. Conclusions Superior descriptive and predictive capabilities were achieved considering resource limitation modelling, but further efforts are needed to improve the accuracy of models for biological engineering. Electronic supplementary material The online version of this article (10.1186/s13036-017-0090-3) contains supplementary material, which is available to authorized users.
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Affiliation(s)
- Lorenzo Pasotti
- Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.,Centre for Health Technologies, University of Pavia, 27100 Pavia, Italy
| | - Massimo Bellato
- Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.,Centre for Health Technologies, University of Pavia, 27100 Pavia, Italy
| | - Michela Casanova
- Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.,Centre for Health Technologies, University of Pavia, 27100 Pavia, Italy
| | - Susanna Zucca
- Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.,Centre for Health Technologies, University of Pavia, 27100 Pavia, Italy
| | | | - Paolo Magni
- Laboratory of Bioinformatics, Mathematical Modelling and Synthetic Biology, Department of Electrical, Computer and Biomedical Engineering, University of Pavia, 27100 Pavia, Italy.,Centre for Health Technologies, University of Pavia, 27100 Pavia, Italy
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27
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Ortiz L, Pavan M, McCarthy L, Timmons J, Densmore DM. Automated Robotic Liquid Handling Assembly of Modular DNA Devices. J Vis Exp 2017. [PMID: 29286379 PMCID: PMC5755516 DOI: 10.3791/54703] [Citation(s) in RCA: 11] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/31/2022] Open
Abstract
Recent advances in modular DNA assembly techniques have enabled synthetic biologists to test significantly more of the available "design space" represented by "devices" created as combinations of individual genetic components. However, manual assembly of such large numbers of devices is time-intensive, error-prone, and costly. The increasing sophistication and scale of synthetic biology research necessitates an efficient, reproducible way to accommodate large-scale, complex, and high throughput device construction. Here, a DNA assembly protocol using the Type-IIS restriction endonuclease based Modular Cloning (MoClo) technique is automated on two liquid-handling robotic platforms. Automated liquid-handling robots require careful, often times tedious optimization of pipetting parameters for liquids of different viscosities (e.g. enzymes, DNA, water, buffers), as well as explicit programming to ensure correct aspiration and dispensing of DNA parts and reagents. This makes manual script writing for complex assemblies just as problematic as manual DNA assembly, and necessitates a software tool that can automate script generation. To this end, we have developed a web-based software tool, http://mocloassembly.com, for generating combinatorial DNA device libraries from basic DNA parts uploaded as Genbank files. We provide access to the tool, and an export file from our liquid handler software which includes optimized liquid classes, labware parameters, and deck layout. All DNA parts used are available through Addgene, and their digital maps can be accessed via the Boston University BDC ICE Registry. Together, these elements provide a foundation for other organizations to automate modular cloning experiments and similar protocols. The automated DNA assembly workflow presented here enables the repeatable, automated, high-throughput production of DNA devices, and reduces the risk of human error arising from repetitive manual pipetting. Sequencing data show the automated DNA assembly reactions generated from this workflow are ~95% correct and require as little as 4% as much hands-on time, compared to manual reaction preparation.
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Affiliation(s)
- Luis Ortiz
- Graduate Program in Molecular Biology, Cell Biology, and Biochemistry, Boston University; Biological Design Center, Boston University
| | | | | | | | - Douglas M Densmore
- Department of Electrical and Computer Engineering, Biological Design Center, Boston University;
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Decoene T, De Paepe B, Maertens J, Coussement P, Peters G, De Maeseneire SL, De Mey M. Standardization in synthetic biology: an engineering discipline coming of age. Crit Rev Biotechnol 2017; 38:647-656. [PMID: 28954542 DOI: 10.1080/07388551.2017.1380600] [Citation(s) in RCA: 36] [Impact Index Per Article: 5.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/18/2022]
Abstract
BACKGROUND Leaping DNA read-and-write technologies, and extensive automation and miniaturization are radically transforming the field of biological experimentation by providing the tools that enable the cost-effective high-throughput required to address the enormous complexity of biological systems. However, standardization of the synthetic biology workflow has not kept abreast with dwindling technical and resource constraints, leading, for example, to the collection of multi-level and multi-omics large data sets that end up disconnected or remain under- or even unexploited. PURPOSE In this contribution, we critically evaluate the various efforts, and the (limited) success thereof, in order to introduce standards for defining, designing, assembling, characterizing, and sharing synthetic biology parts. The causes for this success or the lack thereof, as well as possible solutions to overcome these, are discussed. CONCLUSION Akin to other engineering disciplines, extensive standardization will undoubtedly speed-up and reduce the cost of bioprocess development. In this respect, further implementation of synthetic biology standards will be crucial for the field in order to redeem its promise, i.e. to enable predictable forward engineering.
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Affiliation(s)
- Thomas Decoene
- a Centre for Synthetic Biology, Ghent University , Ghent , Belgium
| | - Brecht De Paepe
- a Centre for Synthetic Biology, Ghent University , Ghent , Belgium
| | - Jo Maertens
- a Centre for Synthetic Biology, Ghent University , Ghent , Belgium
| | | | - Gert Peters
- a Centre for Synthetic Biology, Ghent University , Ghent , Belgium
| | - Sofie L De Maeseneire
- b InBio.be, Centre for Industrial Biotechnology and Biocatalysis, Ghent University , Ghent , Belgium
| | - Marjan De Mey
- a Centre for Synthetic Biology, Ghent University , Ghent , Belgium
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Beal J. Biochemical complexity drives log‐normal variation in genetic expression. ENGINEERING BIOLOGY 2017. [DOI: 10.1049/enb.2017.0004] [Citation(s) in RCA: 51] [Impact Index Per Article: 7.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Affiliation(s)
- Jacob Beal
- Raytheon BBN Technologies Cambridge MA 02138 USA
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