1
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Chan DTC, Bernstein HC. Pangenomic landscapes shape performances of a synthetic genetic circuit across Stutzerimonas species. mSystems 2024:e0084924. [PMID: 39166875 DOI: 10.1128/msystems.00849-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/28/2024] [Accepted: 07/18/2024] [Indexed: 08/23/2024] Open
Abstract
Engineering identical genetic circuits into different species typically results in large differences in performance due to the unique cellular environmental context of each host, a phenomenon known as the "chassis-effect" or "context-dependency". A better understanding of how genomic and physiological contexts underpin the chassis-effect will improve biodesign strategies across diverse microorganisms. Here, we combined a pangenomic-based gene expression analysis with quantitative measurements of performance from an engineered genetic inverter device to uncover how genome structure and function relate to the observed chassis-effect across six closely related Stutzerimonas hosts. Our results reveal that genome architecture underpins divergent responses between our chosen non-model bacterial hosts to the engineered device. Specifically, differential expression of the core genome, gene clusters shared between all hosts, was found to be the main source of significant concordance to the observed differential genetic device performance, whereas specialty genes from respective accessory genomes were not significant. A data-driven investigation revealed that genes involved in denitrification and components of trans-membrane transporter proteins were among the most differentially expressed gene clusters between hosts in response to the genetic device. Our results show that the chassis-effect can be traced along differences among the most conserved genome-encoded functions and that these differences create a unique biodesign space among closely related species.IMPORTANCEContemporary synthetic biology endeavors often default to a handful of model organisms to host their engineered systems. Model organisms such as Escherichia coli serve as attractive hosts due to their tractability but do not necessarily provide the ideal environment to optimize performance. As more novel microbes are domesticated for use as biotechnology platforms, synthetic biologists are urged to explore the chassis-design space to optimize their systems and deliver on the promises of synthetic biology. The consequences of the chassis-effect will therefore only become more relevant as the field of biodesign grows. In our work, we demonstrate that the performance of a genetic device is highly dependent on the host environment it operates within, promoting the notion that the chassis can be considered a design variable to tune circuit function. Importantly, our results unveil that the chassis-effect can be traced along similarities in genome architecture, specifically the shared core genome. Our study advocates for the exploration of the chassis-design space and is a step forward to empowering synthetic biologists with knowledge for more efficient exploration of the chassis-design space to enable the next generation of broad-host-range synthetic biology.
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Affiliation(s)
- Dennis Tin Chat Chan
- Faculty of Biosciences, Fisheries and Economics, UiT - The Arctic University of Norway, Tromsø, Norway
| | - Hans C Bernstein
- Faculty of Biosciences, Fisheries and Economics, UiT - The Arctic University of Norway, Tromsø, Norway
- The Arctic Centre for Sustainable Energy, UiT - The Arctic University of Norway, Tromsø, Norway
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2
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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; 52:e58. [PMID: 38864396 PMCID: PMC11260469 DOI: 10.1093/nar/gkae491] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [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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3
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Stone A, Youssef A, Rijal S, Zhang R, Tian XJ. Context-dependent redesign of robust synthetic gene circuits. Trends Biotechnol 2024; 42:895-909. [PMID: 38320912 PMCID: PMC11223972 DOI: 10.1016/j.tibtech.2024.01.003] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2023] [Revised: 01/10/2024] [Accepted: 01/11/2024] [Indexed: 02/08/2024]
Abstract
Cells provide dynamic platforms for executing exogenous genetic programs in synthetic biology, resulting in highly context-dependent circuit performance. Recent years have seen an increasing interest in understanding the intricacies of circuit-host relationships, their influence on the synthetic bioengineering workflow, and in devising strategies to alleviate undesired effects. We provide an overview of how emerging circuit-host interactions, such as growth feedback and resource competition, impact both deterministic and stochastic circuit behaviors. We also emphasize control strategies for mitigating these unwanted effects. This review summarizes the latest advances and the current state of host-aware and resource-aware design of synthetic gene circuits.
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Affiliation(s)
- Austin Stone
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Abdelrahaman Youssef
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Sadikshya Rijal
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Rong Zhang
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Xiao-Jun Tian
- School of Biological and Health System Engineering, Arizona State University, Tempe, AZ 85281, USA.
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4
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Chakravarty S, Zhang R, Tian XJ. Noise Reduction in Resource-Coupled Multi-Module Gene Circuits through Antithetic Feedback Control. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.05.24.595570. [PMID: 38826454 PMCID: PMC11142251 DOI: 10.1101/2024.05.24.595570] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2024]
Abstract
Gene circuits within the same host cell often experience coupling, stemming from the competition for limited resources during transcriptional and translational processes. This resource competition introduces an additional layer of noise to gene expression. Here we present three multi-module antithetic control strategies: negatively competitive regulation (NCR) controller, alongside local and global controllers, aimed at reducing the gene expression noise within the context of resource competition. Through stochastic simulations and fluctuation-dissipation theorem (FDT) analysis, our findings highlight the superior performance of the NCR antithetic controller in reducing noise levels. Our research provides an effective control strategy for attenuating resource-driven noise and offers insight into the development of robust gene circuits.
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Affiliation(s)
- Suchana Chakravarty
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85287, USA
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5
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De Marchi D, Shaposhnikov R, Gobaa S, Pastorelli D, Batt G, Magni P, Pasotti L. Design and Model-Driven Analysis of Synthetic Circuits with the Staphylococcus aureus Dead-Cas9 (sadCas9) as a Programmable Transcriptional Regulator in Bacteria. ACS Synth Biol 2024; 13:763-780. [PMID: 38374729 DOI: 10.1021/acssynbio.3c00541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/21/2024]
Abstract
Synthetic circuit design is crucial for engineering microbes that process environmental cues and provide biologically relevant outputs. To reliably scale-up circuit complexity, the availability of parts toolkits is central. Streptococcus pyogenes (sp)-derived CRISPR interference/dead-Cas9 (CRISPRi/spdCas9) is widely adopted for implementing programmable regulations in synthetic circuits, and alternative CRISPRi systems will further expand our toolkits of orthogonal components. Here, we showcase the potential of CRISPRi using the engineered dCas9 from Staphylococcus aureus (sadCas9), not previously used in bacterial circuits, that is attractive for its low size and high specificity. We designed a collection of ∼20 increasingly complex circuits and variants in Escherichia coli, including circuits with static function like one-/two-input logic gates (NOT, NAND), circuits with dynamic behavior like incoherent feedforward loops (iFFLs), and applied sadCas9 to fix a T7 polymerase-based cascade. Data demonstrated specific and efficient target repression (100-fold) and qualitatively successful functioning for all circuits. Other advantageous features included low sadCas9-borne cell load and orthogonality with spdCas9. However, different circuit variants showed quantitatively unexpected and previously unreported steady-state responses: the dynamic range, switch point, and slope of NOT/NAND gates changed for different output promoters, and a multiphasic behavior was observed in iFFLs, differing from the expected bell-shaped or sigmoidal curves. Model analysis explained the observed curves by complex interplays among components, due to reporter gene-borne cell load and regulator competition. Overall, CRISPRi/sadCas9 successfully expanded the available toolkit for bacterial engineering. Analysis of our circuit collection depicted the impact of generally neglected effects modulating the shape of component dose-response curves, to avoid drawing wrong conclusions on circuit functioning.
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Affiliation(s)
- Davide De Marchi
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Centre for Health Technologies, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
| | - Roman Shaposhnikov
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Centre for Health Technologies, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
| | - Samy Gobaa
- Institut Pasteur, Université Paris Cité, Biomaterials and Microfluidics Core Facility, 28 Rue du Docteur Roux, 75015 Paris, France
| | - Daniele Pastorelli
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Centre for Health Technologies, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
| | - Gregory Batt
- Institut Pasteur, Inria, Université Paris Cité, 28 rue du Docteur Roux, 75015 Paris, France
| | - Paolo Magni
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Centre for Health Technologies, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
| | - Lorenzo Pasotti
- Department of Electrical, Computer and Biomedical Engineering, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Centre for Health Technologies, University of Pavia, via Ferrata 5, 27100 Pavia, Italy
- Institut Pasteur, Inria, Université Paris Cité, 28 rue du Docteur Roux, 75015 Paris, France
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6
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Love AM, Nair NU. Specific codons control cellular resources and fitness. SCIENCE ADVANCES 2024; 10:eadk3485. [PMID: 38381824 PMCID: PMC10881034 DOI: 10.1126/sciadv.adk3485] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/16/2023] [Accepted: 01/18/2024] [Indexed: 02/23/2024]
Abstract
As cellular engineering progresses from simply overexpressing proteins to imparting complex phenotypes through multigene expression, judicious appropriation of cellular resources is essential. Since codon use is degenerate and biased, codons may control cellular resources at a translational level. We investigate how partitioning transfer RNA (tRNA) resources by incorporating dissimilar codon usage can drastically alter interdependence of expression level and burden on the host. By isolating the effect of individual codons' use during translation elongation while eliminating confounding factors, we show that codon choice can trans-regulate fitness of the host and expression of other heterologous or native genes. We correlate specific codon usage patterns with host fitness and derive a coding scheme for multigene expression called the Codon Health Index (CHI, χ). This empirically derived coding scheme (χ) enables the design of multigene expression systems that avoid catastrophic cellular burden and is robust across several proteins and conditions.
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Affiliation(s)
- Aaron M. Love
- Manus Bio, Waltham, MA 02453, USA
- Department of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA
| | - Nikhil U. Nair
- Department of Chemical and Biological Engineering, Tufts University, Medford, MA 02155, USA
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7
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Sychla A, Stach CS, Roach SN, Hayward AN, Langlois RA, Smanski MJ. High-throughput investigation of genetic design constraints in domesticated Influenza A Virus for transient gene delivery. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.02.14.580300. [PMID: 38405907 PMCID: PMC10888799 DOI: 10.1101/2024.02.14.580300] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/27/2024]
Abstract
Replication-incompetent single cycle infectious Influenza A Virus (sciIAV) has demonstrated utility as a research and vaccination platform. Protein-based therapeutics are increasingly attractive due to their high selectivity and potent efficacy but still suffer from low bioavailability and high manufacturing cost. Transient RNA-mediated delivery is a safe alternative that allows for expression of protein-based therapeutics within the target cells or tissues but is limited by delivery efficiency. Here, we develop recombinant sciIAV as a platform for transient gene delivery in vivo and in vitro for therapeutic, research, and manufacturing applications (in vivo antimicrobial production, cell culture contamination clearance, and production of antiviral proteins in vitro). While adapting the system to deliver new protein cargo we discovered expression differences presumably resulting from genetic context effects. We applied a high-throughput screen to map these within the 3'-untranslated and coding regions of the hemagglutinin-encoding segment 4. This screen revealed permissible mutations in the 3'-UTR and depletion of RNA level motifs in the N-terminal coding region.
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Affiliation(s)
- Adam Sychla
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Biotechnology Institute, University of Minnesota, Saint Paul, MN 55108
| | - Christopher S Stach
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Biotechnology Institute, University of Minnesota, Saint Paul, MN 55108
| | - Shanley N Roach
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Department of Microbiology and Immunology, University of Minnesota, Saint Paul, MN 55108
| | - Amanda N Hayward
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Biotechnology Institute, University of Minnesota, Saint Paul, MN 55108
| | - Ryan A Langlois
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Department of Microbiology and Immunology, University of Minnesota, Saint Paul, MN 55108
| | - Michael J Smanski
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, Saint Paul, MN 55108
- Biotechnology Institute, University of Minnesota, Saint Paul, MN 55108
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8
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Stone A, Rijal S, Zhang R, Tian XJ. Enhancing circuit stability under growth feedback with supplementary repressive regulation. Nucleic Acids Res 2024; 52:1512-1521. [PMID: 38164993 PMCID: PMC10853785 DOI: 10.1093/nar/gkad1233] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/17/2023] [Revised: 11/20/2023] [Accepted: 12/13/2023] [Indexed: 01/03/2024] Open
Abstract
The field of synthetic biology and biosystems engineering increasingly acknowledges the need for a holistic design approach that incorporates circuit-host interactions into the design process. Engineered circuits are not isolated entities but inherently entwined with the dynamic host environment. One such circuit-host interaction, 'growth feedback', results when modifications in host growth patterns influence the operation of gene circuits. The growth-mediated effects can range from growth-dependent elevation in protein/mRNA dilution rate to changes in resource reallocation within the cell, which can lead to complete functional collapse in complex circuits. To achieve robust circuit performance, synthetic biologists employ a variety of control mechanisms to stabilize and insulate circuit behavior against growth changes. Here we propose a simple strategy by incorporating one repressive edge in a growth-sensitive bistable circuit. Through both simulation and in vitro experimentation, we demonstrate how this additional repressive node stabilizes protein levels and increases the robustness of a bistable circuit in response to growth feedback. We propose the incorporation of repressive links in gene circuits as a control strategy for desensitizing gene circuits against growth fluctuations.
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Affiliation(s)
- Austin Stone
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Sadikshya Rijal
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Rong Zhang
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, AZ 85281, USA
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9
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Stock M, Gorochowski TE. Open-endedness in synthetic biology: A route to continual innovation for biological design. SCIENCE ADVANCES 2024; 10:eadi3621. [PMID: 38241375 DOI: 10.1126/sciadv.adi3621] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Accepted: 12/20/2023] [Indexed: 01/21/2024]
Abstract
Design in synthetic biology is typically goal oriented, aiming to repurpose or optimize existing biological functions, augmenting biology with new-to-nature capabilities, or creating life-like systems from scratch. While the field has seen many advances, bottlenecks in the complexity of the systems built are emerging and designs that function in the lab often fail when used in real-world contexts. Here, we propose an open-ended approach to biological design, with the novelty of designed biology being at least as important as how well it fulfils its goal. Rather than solely focusing on optimization toward a single best design, designing with novelty in mind may allow us to move beyond the diminishing returns we see in performance for most engineered biology. Research from the artificial life community has demonstrated that embracing novelty can automatically generate innovative and unexpected solutions to challenging problems beyond local optima. Synthetic biology offers the ideal playground to explore more creative approaches to biological design.
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Affiliation(s)
- Michiel Stock
- KERMIT & Biobix, Department of Data Analysis and Mathematical Modelling, Ghent University, Ghent, Belgium
| | - Thomas E Gorochowski
- School of Biological Sciences, University of Bristol, Life Sciences Building, 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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10
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Moon S, Saboe A, Smanski MJ. Using design of experiments to guide genetic optimization of engineered metabolic pathways. J Ind Microbiol Biotechnol 2024; 51:kuae010. [PMID: 38490746 PMCID: PMC10981448 DOI: 10.1093/jimb/kuae010] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/12/2023] [Accepted: 03/14/2024] [Indexed: 03/17/2024]
Abstract
Design of experiments (DoE) is a term used to describe the application of statistical approaches to interrogate the impact of many variables on the performance of a multivariate system. It is commonly used for process optimization in fields such as chemical engineering and material science. Recent advances in the ability to quantitatively control the expression of genes in biological systems open up the possibility to apply DoE for genetic optimization. In this review targeted to genetic and metabolic engineers, we introduce several approaches in DoE at a high level and describe instances wherein these were applied to interrogate or optimize engineered genetic systems. We discuss the challenges of applying DoE and propose strategies to mitigate these challenges. ONE-SENTENCE SUMMARY This is a review of literature related to applying Design of Experiments for genetic optimization.
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Affiliation(s)
- Seonyun Moon
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, St Paul, MN 55108, USA
- Biotechnology Institute, University of Minnesota, St Paul, MN 55108, USA
| | - Anna Saboe
- Biotechnology Institute, University of Minnesota, St Paul, MN 55108, USA
| | - Michael J Smanski
- Department of Biochemistry, Molecular Biology, and Biophysics, University of Minnesota, St Paul, MN 55108, USA
- Biotechnology Institute, University of Minnesota, St Paul, MN 55108, USA
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11
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Huang Y, Wipat A, Bacardit J. Transcriptional biomarker discovery toward building a load stress reporting system for engineered Escherichia coli strains. Biotechnol Bioeng 2024; 121:355-365. [PMID: 37807718 PMCID: PMC10953381 DOI: 10.1002/bit.28567] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/09/2023] [Revised: 09/15/2023] [Accepted: 09/25/2023] [Indexed: 10/10/2023]
Abstract
Foreign proteins are produced by introducing synthetic constructs into host bacteria for biotechnology applications. This process can cause resource competition between synthetic circuits and host cells, placing a metabolic burden on the host cells which may result in load stress and detrimental physiological changes. Consequently, the host bacteria can experience slow growth, and the synthetic system may suffer from suboptimal function. To help in the detection of bacterial load stress, we developed machine-learning strategies to select a minimal number of genes that could serve as biomarkers for the design of load stress reporters. We identified pairs of biomarkers that showed discriminative capacity to detect the load stress states induced in 41 engineered Escherichia coli strains.
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Affiliation(s)
- Yiming Huang
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
| | - Anil Wipat
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
| | - Jaume Bacardit
- Interdisciplinary Computing and Complex BioSystems GroupNewcastle UniversityNewcastle upon TyneUK
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12
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Gyorgy A. Competition and evolutionary selection among core regulatory motifs in gene expression control. Nat Commun 2023; 14:8266. [PMID: 38092759 PMCID: PMC10719253 DOI: 10.1038/s41467-023-43327-7] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/04/2023] [Accepted: 11/07/2023] [Indexed: 12/17/2023] Open
Abstract
Gene products that are beneficial in one environment may become burdensome in another, prompting the emergence of diverse regulatory schemes that carry their own bioenergetic cost. By ensuring that regulators are only expressed when needed, we demonstrate that autoregulation generally offers an advantage in an environment combining mutation and time-varying selection. Whether positive or negative feedback emerges as dominant depends primarily on the demand for the target gene product, typically to ensure that the detrimental impact of inevitable mutations is minimized. While self-repression of the regulator curbs the spread of these loss-of-function mutations, self-activation instead facilitates their propagation. By analyzing the transcription network of multiple model organisms, we reveal that reduced bioenergetic cost may contribute to the preferential selection of autoregulation among transcription factors. Our results not only uncover how seemingly equivalent regulatory motifs have fundamentally different impact on population structure, growth dynamics, and evolutionary outcomes, but they can also be leveraged to promote the design of evolutionarily robust synthetic gene circuits.
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Affiliation(s)
- Andras Gyorgy
- Division of Engineering, New York University Abu Dhabi, Abu Dhabi, UAE.
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13
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Blázquez B, León DS, Torres-Bacete J, Gómez-Luengo Á, Kniewel R, Martínez I, Sordon S, Wilczak A, Salgado S, Huszcza E, Popłoński J, Prieto A, Nogales J. Golden Standard: a complete standard, portable, and interoperative MoClo tool for model and non-model proteobacteria. Nucleic Acids Res 2023; 51:e98. [PMID: 37718823 PMCID: PMC10602866 DOI: 10.1093/nar/gkad758] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/04/2022] [Accepted: 09/06/2023] [Indexed: 09/19/2023] Open
Abstract
Modular cloning has become a benchmark technology in synthetic biology. However, a notable disparity exists between its remarkable development and the need for standardization to facilitate seamless interoperability among systems. The field is thus impeded by an overwhelming proliferation of organism-specific systems that frequently lack compatibility. To overcome these issues, we present Golden Standard (GS), a Type IIS assembly method underpinned by the Standard European Vector Architecture. GS unlocks modular cloning applications for most bacteria, and delivers combinatorial multi-part assembly to create genetic circuits of up to twenty transcription units (TUs). Reliance on MoClo syntax renders GS fully compatible with many existing tools and it sets the path towards efficient reusability of available part libraries and assembled TUs. GS was validated in terms of DNA assembly, portability, interoperability and phenotype engineering in α-, β-, γ- and δ-proteobacteria. Furthermore, we provide a computational pipeline for parts characterization that was used to assess the performance of GS parts. To promote community-driven development of GS, we provide a dedicated web-portal including a repository of parts, vectors, and Wizard and Setup tools that guide users in designing constructs. Overall, GS establishes an open, standardized framework propelling the progress of synthetic biology as a whole.
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Affiliation(s)
- Blas Blázquez
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
| | - David San León
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
| | - Jesús Torres-Bacete
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
| | - Álvaro Gómez-Luengo
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
| | - Ryan Kniewel
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
| | - Igor Martínez
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
| | - Sandra Sordon
- Wrocław University of Environmental and Life Sciences, Department of Food Chemistry and Biocatalysis, Norwida 25, 50-375, Wrocław, Poland
| | - Aleksandra Wilczak
- Wrocław University of Environmental and Life Sciences, Department of Food Chemistry and Biocatalysis, Norwida 25, 50-375, Wrocław, Poland
| | - Sergio Salgado
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
| | - Ewa Huszcza
- Wrocław University of Environmental and Life Sciences, Department of Food Chemistry and Biocatalysis, Norwida 25, 50-375, Wrocław, Poland
| | - Jarosław Popłoński
- Wrocław University of Environmental and Life Sciences, Department of Food Chemistry and Biocatalysis, Norwida 25, 50-375, Wrocław, Poland
| | - Auxiliadora Prieto
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
- Microbial and Plant Biotechnology Department, Biological Research Center-Margarita Salas, CSIC, Madrid, Spain
| | - Juan Nogales
- Department of Systems Biology, Centro Nacional de Biotecnología, CSIC, Madrid, Spain
- Interdisciplinary Platform for Sustainable Plastics towards a Circular Economy-Spanish National Research Council (SusPlast-CSIC), Madrid, Spain
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14
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Kell B, Ripsman R, Hilfinger A. Noise properties of adaptation-conferring biochemical control modules. Proc Natl Acad Sci U S A 2023; 120:e2302016120. [PMID: 37695915 PMCID: PMC10515136 DOI: 10.1073/pnas.2302016120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/05/2023] [Accepted: 06/12/2023] [Indexed: 09/13/2023] Open
Abstract
A key goal of synthetic biology is to develop functional biochemical modules with network-independent properties. Antithetic integral feedback (AIF) is a recently developed control module in which two control species perfectly annihilate each other's biological activity. The AIF module confers robust perfect adaptation to the steady-state average level of a controlled intracellular component when subjected to sustained perturbations. Recent work has suggested that such robustness comes at the unavoidable price of increased stochastic fluctuations around average levels. We present theoretical results that support and quantify this trade-off for the commonly analyzed AIF variant in the idealized limit with perfect annihilation. However, we also show that this trade-off is a singular limit of the control module: Even minute deviations from perfect adaptation allow systems to achieve effective noise suppression as long as cells can pay the corresponding energetic cost. We further show that a variant of the AIF control module can achieve significant noise suppression even in the idealized limit with perfect adaptation. This atypical configuration may thus be preferable in synthetic biology applications.
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Affiliation(s)
- Brayden Kell
- Department of Physics, University of Toronto, Toronto, ONM5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto, Mississauga, ONL5L 1C6, Canada
- Department of Molecular Biosciences, Northwestern University, Evanston, IL60208
- National Science Foundation-Simons Center for Quantitative Biology, Northwestern University, Evanston, IL60208
| | - Ryan Ripsman
- Department of Physics, University of Toronto, Toronto, ONM5S 1A7, Canada
- Department of Laboratory Medicine and Pathobiology, University of Toronto, Toronto, ONM5S 1A8, Canada
| | - Andreas Hilfinger
- Department of Physics, University of Toronto, Toronto, ONM5S 1A7, Canada
- Department of Chemical and Physical Sciences, University of Toronto, Mississauga, ONL5L 1C6, Canada
- Department of Mathematics, University of Toronto, Toronto, ONM5S 2E4, Canada
- Department of Cell and Systems Biology, University of Toronto, Toronto, ONM5S 3G5, Canada
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15
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Chan DTC, Baldwin GS, Bernstein HC. Revealing the Host-Dependent Nature of an Engineered Genetic Inverter in Concordance with Physiology. BIODESIGN RESEARCH 2023; 5:0016. [PMID: 37849456 PMCID: PMC10432152 DOI: 10.34133/bdr.0016] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 07/17/2023] [Indexed: 10/19/2023] Open
Abstract
Broad-host-range synthetic biology is an emerging frontier that aims to expand our current engineerable domain of microbial hosts for biodesign applications. As more novel species are brought to "model status," synthetic biologists are discovering that identically engineered genetic circuits can exhibit different performances depending on the organism it operates within, an observation referred to as the "chassis effect." It remains a major challenge to uncover which genome-encoded and biological determinants will underpin chassis effects that govern the performance of engineered genetic devices. In this study, we compared model and novel bacterial hosts to ask whether phylogenomic relatedness or similarity in host physiology is a better predictor of genetic circuit performance. This was accomplished using a comparative framework based on multivariate statistical approaches to systematically demonstrate the chassis effect and characterize the performance dynamics of a genetic inverter circuit operating within 6 Gammaproteobacteria. Our results solidify the notion that genetic devices are strongly impacted by the host context. Furthermore, we formally determined that hosts exhibiting more similar metrics of growth and molecular physiology also exhibit more similar performance of the genetic inverter, indicating that specific bacterial physiology underpins measurable chassis effects. The result of this study contributes to the field of broad-host-range synthetic biology by lending increased predictive power to the implementation of genetic devices in less-established microbial hosts.
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Affiliation(s)
- Dennis Tin Chat Chan
- Faculty of Biosciences, Fisheries and Economics, UiT, The Arctic University of Norway, 9019 Tromsø, Norway
| | - Geoff S. Baldwin
- Department of Life Sciences, Imperial College London, South Kensington, London SW7 2AZ, UK
- Imperial College Centre for Synthetic Biology, Imperial College London, South Kensington, London SW7 2AZ, UK
| | - Hans C. Bernstein
- Faculty of Biosciences, Fisheries and Economics, UiT, The Arctic University of Norway, 9019 Tromsø, Norway
- The Arctic Centre for Sustainable Energy, UiT, The Arctic University of Norway, 9019 Tromsø, Norway
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16
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Alexis E, Schulte CCM, Cardelli L, Papachristodoulou A. Regulation strategies for two-output biomolecular networks. J R Soc Interface 2023; 20:20230174. [PMID: 37528680 PMCID: PMC10394417 DOI: 10.1098/rsif.2023.0174] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/26/2023] [Accepted: 07/06/2023] [Indexed: 08/03/2023] Open
Abstract
Feedback control theory facilitates the development of self-regulating systems with desired performance which are predictable and insensitive to disturbances. Feedback regulatory topologies are found in many natural systems and have been of key importance in the design of reliable synthetic bio-devices operating in complex biological environments. Here, we study control schemes for biomolecular processes with two outputs of interest, expanding previously described concepts based on single-output systems. Regulation of such processes may unlock new design possibilities but can be challenging due to coupling interactions; also potential disturbances applied on one of the outputs may affect both. We therefore propose architectures for robustly manipulating the ratio/product and linear combinations of the outputs as well as each of the outputs independently. To demonstrate their characteristics, we apply these architectures to a simple process of two mutually activated biomolecular species. We also highlight the potential for experimental implementation by exploring synthetic realizations both in vivo and in vitro. This work presents an important step forward in building bio-devices capable of sophisticated functions.
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Affiliation(s)
- Emmanouil Alexis
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
| | - Carolin C. M. Schulte
- Department of Engineering Science, University of Oxford, Oxford OX1 3PJ, UK
- Department of Biology, University of Oxford, Oxford OX1 3RB, UK
| | - Luca Cardelli
- Department of Computer Science, University of Oxford, Oxford OX1 3QD, UK
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17
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Maheshwari AJ, Calles J, Waterton SK, Endy D. Engineering tRNA abundances for synthetic cellular systems. Nat Commun 2023; 14:4594. [PMID: 37524714 PMCID: PMC10390467 DOI: 10.1038/s41467-023-40199-9] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/24/2022] [Accepted: 07/13/2023] [Indexed: 08/02/2023] Open
Abstract
Routinizing the engineering of synthetic cells requires specifying beforehand how many of each molecule are needed. Physics-based tools for estimating desired molecular abundances in whole-cell synthetic biology are missing. Here, we use a colloidal dynamics simulator to make predictions for how tRNA abundances impact protein synthesis rates. We use rational design and direct RNA synthesis to make 21 synthetic tRNA surrogates from scratch. We use evolutionary algorithms within a computer aided design framework to engineer translation systems predicted to work faster or slower depending on tRNA abundance differences. We build and test the so-specified synthetic systems and find qualitative agreement between expected and observed systems. First principles modeling combined with bottom-up experiments can help molecular-to-cellular scale synthetic biology realize design-build-work frameworks that transcend tinker-and-test.
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Affiliation(s)
| | - Jonathan Calles
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA
| | - Sean K Waterton
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
| | - Drew Endy
- Department of Bioengineering, Stanford University, Stanford, CA, 94305, USA.
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18
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Chlebek JL, Leonard SP, Kang-Yun C, Yung MC, Ricci DP, Jiao Y, Park DM. Prolonging genetic circuit stability through adaptive evolution of overlapping genes. Nucleic Acids Res 2023; 51:7094-7108. [PMID: 37260076 PMCID: PMC10359631 DOI: 10.1093/nar/gkad484] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2023] [Revised: 05/12/2023] [Accepted: 05/23/2023] [Indexed: 06/02/2023] Open
Abstract
The development of synthetic biological circuits that maintain functionality over application-relevant time scales remains a significant challenge. Here, we employed synthetic overlapping sequences in which one gene is encoded or 'entangled' entirely within an alternative reading frame of another gene. In this design, the toxin-encoding relE was entangled within ilvA, which encodes threonine deaminase, an enzyme essential for isoleucine biosynthesis. A functional entanglement construct was obtained upon modification of the ribosome-binding site of the internal relE gene. Using this optimized design, we found that the selection pressure to maintain functional IlvA stabilized the production of burdensome RelE for >130 generations, which compares favorably with the most stable kill-switch circuits developed to date. This stabilizing effect was achieved through a complete alteration of the allowable landscape of mutations such that mutations inactivating the entangled genes were disfavored. Instead, the majority of lineages accumulated mutations within the regulatory region of ilvA. By reducing baseline relE expression, these more 'benign' mutations lowered circuit burden, which suppressed the accumulation of relE-inactivating mutations, thereby prolonging kill-switch function. Overall, this work demonstrates the utility of sequence entanglement paired with an adaptive laboratory evolution campaign to increase the evolutionary stability of burdensome synthetic circuits.
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Affiliation(s)
- Jennifer L Chlebek
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Sean P Leonard
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Christina Kang-Yun
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Mimi C Yung
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Dante P Ricci
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Yongqin Jiao
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
| | - Dan M Park
- Biosciences and Biotechnology Division, Lawrence Livermore National Laboratory, Livermore, CA 94550, USA
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19
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Hueso-Gil A, Calles B, de Lorenzo V. In Vivo Sampling of Intracellular Heterogeneity of Pseudomonas putida Enables Multiobjective Optimization of Genetic Devices. ACS Synth Biol 2023; 12:1667-1676. [PMID: 37196337 PMCID: PMC10278179 DOI: 10.1021/acssynbio.3c00009] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/06/2023] [Indexed: 05/19/2023]
Abstract
The inner physicochemical heterogeneity of bacterial cells generates three-dimensional (3D)-dependent variations of resources for effective expression of given chromosomally located genes. This fact has been exploited for adjusting the most favorable parameters for implanting a complex device for optogenetic control of biofilm formation in the soil bacterium Pseudomonas putida. To this end, a DNA segment encoding a superactive variant of the Caulobacter crescendus diguanylate cyclase PleD expressed under the control of the cyanobacterial light-responsive CcaSR system was placed in a mini-Tn5 transposon vector and randomly inserted through the chromosome of wild-type and biofilm-deficient variants of P. putida lacking the wsp gene cluster. This operation delivered a collection of clones covering a whole range of biofilm-building capacities and dynamic ranges in response to green light. Since the phenotypic output of the device depends on a large number of parameters (multiple promoters, RNA stability, translational efficacy, metabolic precursors, protein folding, etc.), we argue that random chromosomal insertions enable sampling the intracellular milieu for an optimal set of resources that deliver a preset phenotypic specification. Results thus support the notion that the context dependency can be exploited as a tool for multiobjective optimization, rather than a foe to be suppressed in Synthetic Biology constructs.
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Affiliation(s)
| | - Belén Calles
- Systems Biology Department, Centro Nacional de Biotecnología-CSIC, Campus
de Cantoblanco, Madrid 28049, Spain
| | - Víctor de Lorenzo
- Systems Biology Department, Centro Nacional de Biotecnología-CSIC, Campus
de Cantoblanco, Madrid 28049, Spain
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20
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Gyorgy A, Menezes A, Arcak M. A blueprint for a synthetic genetic feedback optimizer. Nat Commun 2023; 14:2554. [PMID: 37137895 PMCID: PMC10156725 DOI: 10.1038/s41467-023-37903-0] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/18/2022] [Accepted: 04/05/2023] [Indexed: 05/05/2023] Open
Abstract
Biomolecular control enables leveraging cells as biomanufacturing factories. Despite recent advancements, we currently lack genetically encoded modules that can be deployed to dynamically fine-tune and optimize cellular performance. Here, we address this shortcoming by presenting the blueprint of a genetic feedback module to optimize a broadly defined performance metric by adjusting the production and decay rate of a (set of) regulator species. We demonstrate that the optimizer can be implemented by combining available synthetic biology parts and components, and that it can be readily integrated with existing pathways and genetically encoded biosensors to ensure its successful deployment in a variety of settings. We further illustrate that the optimizer successfully locates and tracks the optimum in diverse contexts when relying on mass action kinetics-based dynamics and parameter values typical in Escherichia coli.
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Affiliation(s)
- Andras Gyorgy
- Division of Engineering, New York University Abu Dhabi, Abu Dhabi, UAE.
| | - Amor Menezes
- Department of Mechanical and Aerospace Engineering, University of Florida, Gainesville, FL, USA
| | - Murat Arcak
- Department of Electrical Engineering and Computer Sciences, University of California, Berkeley, CA, USA
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21
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Scott M, Hwa T. Shaping bacterial gene expression by physiological and proteome allocation constraints. Nat Rev Microbiol 2023; 21:327-342. [PMID: 36376406 PMCID: PMC10121745 DOI: 10.1038/s41579-022-00818-6] [Citation(s) in RCA: 26] [Impact Index Per Article: 26.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Accepted: 10/12/2022] [Indexed: 11/16/2022]
Abstract
Networks of molecular regulators are often the primary objects of focus in the study of gene regulation, with the machinery of protein synthesis tacitly relegated to the background. Shifting focus to the constraints imposed by the allocation of protein synthesis flux reveals surprising ways in which the actions of molecular regulators are shaped by physiological demands. Using carbon catabolite repression as a case study, we describe how physiological constraints are sensed through metabolic fluxes and how flux-controlled regulation gives rise to simple empirical relations between protein levels and the rate of cell growth.
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Affiliation(s)
- Matthew Scott
- Department of Applied Mathematics, University of Waterloo, Waterloo, ON, Canada.
| | - Terence Hwa
- Department of Physics, University of California at San Diego, La Jolla, CA, USA.
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22
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Chen SAA, Kern AF, Ang RML, Xie Y, Fraser HB. Gene-by-environment interactions are pervasive among natural genetic variants. CELL GENOMICS 2023; 3:100273. [PMID: 37082145 PMCID: PMC10112290 DOI: 10.1016/j.xgen.2023.100273] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/05/2022] [Revised: 10/09/2022] [Accepted: 01/31/2023] [Indexed: 04/22/2023]
Abstract
Gene-by-environment (GxE) interactions, in which a genetic variant's phenotypic effect is condition specific, are fundamental for understanding fitness landscapes and evolution but have been difficult to identify at the single-nucleotide level. Although many condition-specific quantitative trait loci (QTLs) have been mapped, these typically contain numerous inconsequential variants in linkage, precluding understanding of the causal GxE variants. Here, we introduce BARcoded Cas9 retron precise parallel editing via homology (CRISPEY-BAR), a high-throughput precision genome editing strategy, and use it to map GxE interactions of naturally occurring genetic polymorphisms impacting yeast growth. We identified hundreds of GxE variants within condition-specific QTLs, revealing unexpected genetic complexity. Moreover, we found that 93.7% of non-neutral natural variants within ergosterol biosynthesis pathway genes showed GxE interactions, including many impacting antifungal drug resistance through diverse molecular mechanisms. In sum, our results suggest an extremely complex, context-dependent fitness landscape characterized by pervasive GxE interactions while also demonstrating massively parallel genome editing as an effective means for investigating this complexity.
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Affiliation(s)
- Shi-An A. Chen
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Alexander F. Kern
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Roy Moh Lik Ang
- Department of Genetics, Stanford University School of Medicine, Stanford, CA 94305, USA
| | - Yihua Xie
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Hunter B. Fraser
- Department of Biology, Stanford University, Stanford, CA 94305, USA
- Corresponding author
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23
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Ghataora JS, Gebhard S, Reeksting BJ. Chimeric MerR-Family Regulators and Logic Elements for the Design of Metal Sensitive Genetic Circuits in Bacillus subtilis. ACS Synth Biol 2023; 12:735-749. [PMID: 36629785 PMCID: PMC10028694 DOI: 10.1021/acssynbio.2c00545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2023]
Abstract
Whole-cell biosensors are emerging as promising tools for monitoring environmental pollutants such as heavy metals. These sensors constitute a genetic circuit comprising a sensing module and an output module, such that a detectable signal is produced in the presence of the desired analyte. The MerR family of metal-responsive regulators offers great potential for the construction of metal sensing circuits, due to their high sensitivity, tight transcription control, and large diversity in metal-specificity. However, the sensing diversity is broadest in Gram-negative systems, while chassis organisms are often selected from Gram-positive species, particularly sporulating bacilli. This can be problematic, because Gram-negative biological parts, such as promoters, are frequently observed to be nonfunctional in Gram-positive hosts. Herein, we combined construction of synthetic genetic circuits and chimeric MerR regulators, supported by structure-guided design, to generate metal-sensitive biosensor modules that are functional in the biotechnological work-horse species Bacillus subtilis. These chimeras consist of a constant Gram-positive derived DNA-binding domain fused to variable metal binding domains of Gram-negative origins. To improve the specificity of the whole-cell biosensor, we developed a modular "AND gate" logic system based on the B. subtilis two-subunit σ-factor, SigO-RsoA, designed to maximize future use for synthetic biology applications in B. subtilis. This work provides insights into the use of modular regulators, such as the MerR family, in the design of synthetic circuits for the detection of heavy metals, with potentially wider applicability of the approach to other systems and genetic backgrounds.
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Affiliation(s)
- Jasdeep S Ghataora
- Life Sciences Department, Milner Centre for Evolution, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
| | - Susanne Gebhard
- Life Sciences Department, Milner Centre for Evolution, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
| | - Bianca J Reeksting
- Life Sciences Department, Milner Centre for Evolution, University of Bath, Claverton Down, Bath BA2 7AY, United Kingdom
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24
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Hsu SY, Lee J, Sychla A, Smanski MJ. Rational search of genetic design space for a heterologous terpene metabolic pathway in Streptomyces. Metab Eng 2023; 77:1-11. [PMID: 36863605 DOI: 10.1016/j.ymben.2023.02.011] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/18/2022] [Revised: 01/05/2023] [Accepted: 02/22/2023] [Indexed: 03/04/2023]
Abstract
Modern tools in DNA synthesis and assembly give genetic engineers control over the nucleotide-level design of complex, multi-gene systems. Systematic approaches to explore genetic design space and optimize the performance of genetic constructs are lacking. Here we explore the application of a five-level Plackett-Burman fractional factorial design to improve the titer of a heterologous terpene biosynthetic pathway in Streptomyces. A library of 125 engineered gene clusters encoding the production of diterpenoid ent-atiserenoic acid (eAA) via the methylerythritol phosphate pathway was constructed and introduced into Streptomyces albidoflavus J1047 for heterologous expression. The eAA production titer varied within the library by over two orders of magnitude and host strains showed unexpected and reproducible colony morphology phenotypes. Analysis of Plackett-Burman design identified expression of dxs, the gene encoding the first and the flux-controlling enzyme, having the strongest impact on eAA titer, but with a counter-intuitive negative correlation between dxs expression and eAA production. Finally, simulation modeling was performed to determine how several plausible sources of experimental error/noise and non-linearity impact the utility of Plackett-Burman analyses.
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Affiliation(s)
- Szu-Yi Hsu
- Department of Biochemistry, Molecular Biology, and Biophysics, USA; Biotechnology Institute, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Jihaeng Lee
- Department of Biochemistry, Molecular Biology, and Biophysics, USA; Biotechnology Institute, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Adam Sychla
- Department of Biochemistry, Molecular Biology, and Biophysics, USA; Biotechnology Institute, University of Minnesota, Saint Paul, MN, 55108, USA
| | - Michael J Smanski
- Department of Biochemistry, Molecular Biology, and Biophysics, USA; Biotechnology Institute, University of Minnesota, Saint Paul, MN, 55108, USA.
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25
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Casas-Mollano JA, Zinselmeier M, Sychla A, Smanski MJ. Efficient gene activation in plants by the MoonTag programmable transcriptional activator. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.02.15.528671. [PMID: 36824723 PMCID: PMC9948947 DOI: 10.1101/2023.02.15.528671] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 02/18/2023]
Abstract
CRISPR/Cas-based transcriptional activators have been developed to induce gene expression in eukaryotic and prokaryotic organisms. The main advantages of CRISPR-Cas based systems is that they can achieve high levels of transcriptional activation and are very easy to program via pairing between the guide RNA and the DNA target strand. SunTag is a second-generation system that activates transcription by recruiting multiple copies of an activation domain (AD) to its target promoters. SunTag is a strong activator; however, in some species it is difficult to stably express. To overcome this problem, we designed MoonTag, a new activator that worked on the same basic principle as SunTag, but whose components are better tolerated when stably expressed in transgenic plants. We demonstrate that MoonTag is capable of inducing high levels of transcription in all plants tested. In Setaria, MoonTag is capable of inducing high levels of transcription of reporter genes as well as of endogenous genes. More important, MoonTag components are expressed in transgenic plants to high levels without any deleterious effects. MoonTag is also able to efficiently activate genes in eudicotyledonous species such as Arabidopsis and tomato. Finally, we show that MoonTag activation is functional across a range of temperatures, which is promising for potential field applications.
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26
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Engelmann N, Schwarz T, Kubaczka E, Hochberger C, Koeppl H. Context-Aware Technology Mapping in Genetic Design Automation. ACS Synth Biol 2023; 12:446-459. [PMID: 36693176 PMCID: PMC9942193 DOI: 10.1021/acssynbio.2c00361] [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] [Indexed: 01/25/2023]
Abstract
Genetic design automation (GDA) tools hold promise to speed-up circuit design in synthetic biology. Their widespread adoption is hampered by their limited predictive power, resulting in frequent deviations between the in silico and in vivo performance of a genetic circuit. Context effects, i.e., the change in overall circuit functioning, due to the intracellular environment of the host and due to cross-talk among circuits components are believed to be a major source for the aforementioned deviations. Incorporating these effects in computational models of GDA tools is challenging but is expected to boost their predictive power and hence their deployment. Using fine-grained thermodynamic models of promoter activity, we show in this work how to account for two major components of cellular context effects: (i) crosstalk due to limited specificity of used regulators and (ii) titration of circuit regulators to off-target binding sites on the host genome. We show how we can compensate the incurred increase in computational complexity through dedicated branch-and-bound techniques during the technology mapping process. Using the synthesis of several combinational logic circuits based on Cello's device library as a case study, we analyze the effect of different intensities and distributions of crosstalk on circuit performance and on the usability of a given device library.
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Affiliation(s)
- Nicolai Engelmann
- Department
of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany
| | - Tobias Schwarz
- Department
of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany
| | - Erik Kubaczka
- Department
of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany
| | - Christian Hochberger
- Department
of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany,Centre
for Synthetic Biology, TU Darmstadt, Darmstadt64283, Germany
| | - Heinz Koeppl
- Department
of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt64283, Germany,Centre
for Synthetic Biology, TU Darmstadt, Darmstadt64283, Germany,
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27
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Lohrey A, Boreham B. The two principles that shape scientific research. Commun Integr Biol 2023; 16:2203625. [PMID: 37091831 PMCID: PMC10114983 DOI: 10.1080/19420889.2023.2203625] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/25/2023] Open
Abstract
This paper argues that all scientific research is framed by one of two organizing principles that underpin and shape almost every aspect of scientific research as well as nonscientific inquiry. The most commonly employed principle within mainstream science is content determines content. This is a closed, circular principle that is usually unstated within hypotheses but plays a major role in developing methodologies and arriving at conclusions. The second more open principle is context determines content. This principle represents the implied background embedded within hypotheses. The difference between these two principles revolves around the issue of context, with the first principle closing off contexts by ignoring, erasing, or devaluing them, while the second more holistic principle explicitly takes them into account. Each of these research principles has a focus on the explicit detailed nature of 'content' while differing in relation to the source and cause of such content. We argue that the more open and holistic principle of context determines that content is superior in producing reliable evidence, results and conclusions.
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Affiliation(s)
- Andrew Lohrey
- CONTACT Andrew Lohrey P O Box 249 St Marys, TAS7215, Australia
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28
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Stone A, Ryan J, Tang X, Tian XJ. Negatively Competitive Incoherent Feedforward Loops Mitigate Winner-Take-All Resource Competition. ACS Synth Biol 2022; 11:3986-3995. [PMID: 36355441 DOI: 10.1021/acssynbio.2c00318] [Citation(s) in RCA: 4] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/12/2022]
Abstract
The effects of host resource limitations on the function of synthetic gene circuits have gained significant attention over the past years. Hosts, having evolved resource capacities optimal for their own genome, have been repeatedly demonstrated to suffer from the added burden of synthetic genetic programs, which may in return pose deleterious effects on the circuit's function. Three resource controller archetypes have been proposed previously to mitigate resource distribution problems in dynamic circuits: the local controller, the global controller, and a "negatively competitive" regulatory (NCR) controller that utilizes synthetic competition to combat resource competition. The dynamics of negative feedback forms of these controllers have been previously investigated, and here we extend the analysis of these resource allocation strategies to the incoherent feedforward loop (iFFL) topology. We demonstrate that the three iFFL controllers can attenuate Winner-Take-All resource competition between two bistable switches. We uncover that the parameters associated with the synthetic competition in the NCR iFFL controller are paramount to its increased efficacy over the local controller type, while the global controllers demonstrate to be relatively ineffectual. Interestingly, unlike the negative feedback counterpart topologies, iFFL controllers exhibit a unique coupling of switch activation thresholds which we term the "coactivation threshold shift" effect. Finally, we demonstrate that a nearly fully orthogonal set of bistable switches could be achieved by pairing an NCR controller with an appropriate level of controller resource consumption.
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Affiliation(s)
- Austin Stone
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona85281, United States
| | - Jordan Ryan
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana70803, United States
| | - Xun Tang
- Cain Department of Chemical Engineering, Louisiana State University, Baton Rouge, Louisiana70803, United States
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona85281, United States
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29
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Gupta A, Khammash M. Universal structural requirements for maximal robust perfect adaptation in biomolecular networks. Proc Natl Acad Sci U S A 2022; 119:e2207802119. [PMID: 36256812 PMCID: PMC9618122 DOI: 10.1073/pnas.2207802119] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Accepted: 09/21/2022] [Indexed: 12/31/2022] Open
Abstract
Adaptation is a running theme in biology. It allows a living system to survive and thrive in the face of unpredictable environments by maintaining key physiological variables at their desired levels through tight regulation. When one such variable is maintained at a certain value at the steady state despite perturbations to a single input, this property is called robust perfect adaptation (RPA). Here we address and solve the fundamental problem of maximal RPA (maxRPA), whereby, for a designated output variable, RPA is achieved with respect to perturbations in virtually all network parameters. In particular, we show that the maxRPA property imposes certain structural constraints on the network. We then prove that these constraints are fully characterized by simple linear algebraic stoichiometric conditions which differ between deterministic and stochastic descriptions of the dynamics. We use our results to derive a new internal model principle (IMP) for biomolecular maxRPA networks, akin to the celebrated IMP in control theory. We exemplify our results through several known biological examples of robustly adapting networks and construct examples of such networks with the aid of our linear algebraic characterization. Our results reveal the universal requirements for maxRPA in all biological systems, and establish a foundation for studying adaptation in general biomolecular networks, with important implications for both systems and synthetic biology.
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Affiliation(s)
- Ankit Gupta
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zurich, 4058 Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering, Eidgenössische Technische Hochschule Zurich, 4058 Basel, Switzerland
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30
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Abstract
AbstractComputational properties of neuronal networks have been applied to computing systems using simplified models comprising repeated connected nodes, e.g., perceptrons, with decision-making capabilities and flexible weighted links. Analogously to their revolutionary impact on computing, neuro-inspired models can transform synthetic gene circuit design in a manner that is reliable, efficient in resource utilization, and readily reconfigurable for different tasks. To this end, we introduce the perceptgene, a perceptron that computes in the logarithmic domain, which enables efficient implementation of artificial neural networks in Escherichia coli cells. We successfully modify perceptgene parameters to create devices that encode a minimum, maximum, and average of analog inputs. With these devices, we create multi-layer perceptgene circuits that compute a soft majority function, perform an analog-to-digital conversion, and implement a ternary switch. We also create a programmable perceptgene circuit whose computation can be modified from OR to AND logic using small molecule induction. Finally, we show that our approach enables circuit optimization via artificial intelligence algorithms.
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31
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Sridhar S, Ajo-Franklin CM, Masiello CA. A Framework for the Systematic Selection of Biosensor Chassis for Environmental Synthetic Biology. ACS Synth Biol 2022; 11:2909-2916. [PMID: 35961652 PMCID: PMC9486965 DOI: 10.1021/acssynbio.2c00079] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2022] [Indexed: 01/24/2023]
Abstract
Microbial biosensors sense and report exposures to stimuli, thereby facilitating our understanding of environmental processes. Successful design and deployment of biosensors hinge on the persistence of the microbial host of the genetic circuit, termed the chassis. However, model chassis organisms may persist poorly in environmental conditions. In contrast, non-model organisms persist better in environmental conditions but are limited by other challenges, such as genetic intractability and part unavailability. Here we identify ecological, metabolic, and genetic constraints for chassis development and propose a conceptual framework for the systematic selection of environmental biosensor chassis. We identify key challenges with using current model chassis and delineate major points of conflict in choosing the most suitable organisms as chassis for environmental biosensing. This framework provides a way forward in the selection of biosensor chassis for environmental synthetic biology.
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Affiliation(s)
- Swetha Sridhar
- Systems,
Synthetic, and Physical Biology Graduate Program, Rice University, 6100 Main Street, MS-180, Houston, Texas 77005, United
States
| | - Caroline M. Ajo-Franklin
- Department
of BioSciences, Rice University, 6100 Main Street, MS-140, Houston, Texas 77005, United States
| | - Caroline A. Masiello
- Department
of BioSciences, Rice University, 6100 Main Street, MS-140, Houston, Texas 77005, United States
- Department
of Earth, Environmental, and Planetary Sciences, Rice University, 6100 Main St, MS-126, Houston, Texas 77005, United
States
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32
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Melendez-Alvarez JR, Tian XJ. Emergence of qualitative states in synthetic circuits driven by ultrasensitive growth feedback. PLoS Comput Biol 2022; 18:e1010518. [PMID: 36112667 PMCID: PMC9518899 DOI: 10.1371/journal.pcbi.1010518] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2022] [Revised: 09/28/2022] [Accepted: 08/26/2022] [Indexed: 11/24/2022] Open
Abstract
The mutual interactions between the synthetic gene circuits and the host growth could cause unexpected outcomes in the dynamical behaviors of the circuits. However, how the steady states and the stabilities of the gene circuits are affected by host cell growth is not fully understood. Here, we developed a mathematical model for nonlinear growth feedback based on published experimental data. The model analysis predicts that growth feedback could significantly change the qualitative states of the system. Bistability could emerge in a circuit without positive feedback, and high-order multistability (three or more steady states) arises in the self-activation and toggle switch circuits. Our results provide insight into the potential effects of ultrasensitive growth feedback on the emergence of qualitative states in synthetic circuits and the corresponding underlying mechanism. The mutual inhibitory effect between synthetic gene circuits and cell growth produces growth feedback in the host-circuit system. Previous studies have demonstrated that the growth feedback could significantly impact the dynamics of the host-circuit system. However, the complexity of the growth feedback impact is not fully understood. Here, our data analysis displays ultrasensitive growth feedback between the cells and synthetic gene circuits under different growth conditions. To study the effect of ultrasensitive growth feedback on the host-circuit system, we develop a mathematical modeling framework. Our results reveal the emergence of qualitative states on the host-circuit system induced by ultrasensitive growth feedback. We found an emergence of bistability in a simple synthetic gene circuit with a constitutive promoter. Also, tristability could be seen in self-activation and toggle switch circuits. Our research uncovered the effect of ultrasensitive growth feedback in synthetic gene circuits and host interactions. Understanding the effects of ultrasensitive growth feedback could help scientists and engineers identify unexpected outcomes in gene circuits and formulate control strategies.
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Affiliation(s)
- Juan Ramon Melendez-Alvarez
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
| | - Xiao-Jun Tian
- School of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona, United States of America
- * E-mail:
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33
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Dundas CM, Dinneny JR. Genetic Circuit Design in Rhizobacteria. BIODESIGN RESEARCH 2022; 2022:9858049. [PMID: 37850138 PMCID: PMC10521742 DOI: 10.34133/2022/9858049] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/29/2022] [Accepted: 07/31/2022] [Indexed: 10/19/2023] Open
Abstract
Genetically engineered plants hold enormous promise for tackling global food security and agricultural sustainability challenges. However, construction of plant-based genetic circuitry is constrained by a lack of well-characterized genetic parts and circuit design rules. In contrast, advances in bacterial synthetic biology have yielded a wealth of sensors, actuators, and other tools that can be used to build bacterial circuitry. As root-colonizing bacteria (rhizobacteria) exert substantial influence over plant health and growth, genetic circuit design in these microorganisms can be used to indirectly engineer plants and accelerate the design-build-test-learn cycle. Here, we outline genetic parts and best practices for designing rhizobacterial circuits, with an emphasis on sensors, actuators, and chassis species that can be used to monitor/control rhizosphere and plant processes.
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Affiliation(s)
| | - José R. Dinneny
- Department of Biology, Stanford University, Stanford, CA 94305, USA
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34
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Moschner C, Wedd C, Bakshi S. The context matrix: Navigating biological complexity for advanced biodesign. Front Bioeng Biotechnol 2022; 10:954707. [PMID: 36082163 PMCID: PMC9445834 DOI: 10.3389/fbioe.2022.954707] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2022] [Accepted: 06/29/2022] [Indexed: 12/05/2022] Open
Abstract
Synthetic biology offers many solutions in healthcare, production, sensing and agriculture. However, the ability to rationally engineer synthetic biosystems with predictable and robust functionality remains a challenge. A major reason is the complex interplay between the synthetic genetic construct, its host, and the environment. Each of these contexts contains a number of input factors which together can create unpredictable behaviours in the engineered biosystem. It has become apparent that for the accurate assessment of these contextual effects a more holistic approach to design and characterisation is required. In this perspective article, we present the context matrix, a conceptual framework to categorise and explore these contexts and their net effect on the designed synthetic biosystem. We propose the use and community-development of the context matrix as an aid for experimental design that simplifies navigation through the complex design space in synthetic biology.
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35
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Hartline CJ, Zhang F. The Growth Dependent Design Constraints of Transcription-Factor-Based Metabolite Biosensors. ACS Synth Biol 2022; 11:2247-2258. [PMID: 35700119 PMCID: PMC9994378 DOI: 10.1021/acssynbio.2c00143] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Metabolite biosensors based on metabolite-responsive transcription factors are key synthetic biology components for sensing and precisely controlling cellular metabolism. Biosensors are often designed under laboratory conditions but are deployed in applications where cellular growth rate differs drastically from its initial characterization. Here we asked how growth rate impacts the minimum and maximum biosensor outputs and the dynamic range, which are key metrics of biosensor performance. Using LacI, TetR, and FadR-based biosensors in Escherichia coli as models, we find that the dynamic range of different biosensors have different growth rate dependencies. We developed a kinetic model to explore how tuning biosensor parameters impact the dynamic range growth rate dependence. Our modeling and experimental results revealed that the effects to dynamic range and its growth rate dependence are often coupled, and the metabolite transport mechanisms shape the dynamic range-growth rate response. This work provides a systematic understanding of biosensor performance under different growth rates, which will be useful for predicting biosensor behavior in broad synthetic biology and metabolic engineering applications.
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Affiliation(s)
- Christopher J Hartline
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, Saint Louis, Missouri 63130, United States
| | - Fuzhong Zhang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, Saint Louis, Missouri 63130, United States.,Division of Biology & Biomedical Sciences, Washington University in St. Louis, Saint Louis, Missouri 63130, United States.,Institute of Materials Science & Engineering, Washington University in St. Louis, Saint Louis, Missouri 63130, United States
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36
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Song H, Yang Y, Li H, Du J, Hu Z, Chen Y, Yang N, Mei M, Xiong Z, Tang K, Yi L, Zhang Y, Yang S. Determination of Nucleotide Sequences within Promoter Regions Affecting Promoter Compatibility between Zymomonas mobilis and Escherichia coli. ACS Synth Biol 2022; 11:2811-2819. [PMID: 35771099 DOI: 10.1021/acssynbio.2c00187] [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: 11/29/2022]
Abstract
A promoter plays a crucial role in controlling the expression of the target gene in cells, thus being one of the key biological parts for synthetic biology practices. Although significant efforts have been made to identify and characterize promoters with different strengths in various microorganisms, the compatibility of promoters within different hosts still lacks investigation. In this study, we chose the native Pgap promoter of Zymomonas mobilis to investigate nucleotide sequences within promoter regions affecting promoter compatibility between Escherichia coli and Z. mobilis. Pgap is one of the strongest promotors in Z. mobilis that has many excellent characteristics to be developed as microbial cell factories. Using EGFP as a reporter, a Z. mobilis-derived Pgap mutant library was constructed and sorted in E. coli, with candidate promoters exhibiting high fluorescence intensity collected. A total of 53 variants were finally selected and sequenced by Sanger sequencing. The sequencing results grouped these variants into 12 different Pgap variant types, among which seven types presented higher promoter strength than native Pgap in E. coli. The next-generation sequencing technique was then employed to identify key mutations within the Pgap promoter region that affect the promoter compatibility. Finally, six important sites were identified and confirmed to help increase Pgap strength in E. coli while keeping similar strength of native Pgap in Z. mobilis. Compared to native Pgap, synthetic promoters combining these sites had enhanced strength; especially, Pgap-6M combining all six sites exhibited 20-fold greater strength than native Pgap in E. coli. This study thus not only determined six important sites affecting promoter compatibility but also confirmed a series of Pgap promoter variants with strong promoter activity in both E. coli and Z. mobilis. In addition, a strategy was established in this study to investigate and determine nucleotide sequences in promoter regions affecting promoter compatibility, which can be applied in other microorganisms to help reveal universal factors affecting promoter compatibility and design promoters with desired strengths among different microbial cell factories.
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Affiliation(s)
- Haoyue Song
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Yongfu Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Han Li
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Jun Du
- Beijing Tsingke Biotechnology Co., Ltd., Beijing 101111, China
| | - Zhousheng Hu
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Yunhao Chen
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Ning Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Meng Mei
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Zhiqiang Xiong
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Ke Tang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Li Yi
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
| | - Yu Zhang
- Key Laboratory of Synthetic Biology, CAS Center for Excellence in Molecular Plant Sciences, Shanghai Institute of Plant Physiology and Ecology, Chinese Academy of Sciences, Shanghai 200032, China
| | - Shihui Yang
- State Key Laboratory of Biocatalysis and Enzyme Engineering, and School of Life Sciences, Hubei University, Wuhan 430062, China
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37
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Guan Y, Chen X, Shao B, Ji X, Xiang Y, Jiang G, Xu L, Lin Z, Ouyang Q, Lou C. Mitigating Host Burden of Genetic Circuits by Engineering Autonegatively Regulated Parts and Improving Functional Prediction. ACS Synth Biol 2022; 11:2361-2371. [PMID: 35772024 DOI: 10.1021/acssynbio.2c00073] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/02/2023]
Abstract
Mitigating unintended interferences between circuits and host cells is key to realize applications of synthetic regulatory systems both for bacteria and mammalian cells. Here, we demonstrated that growth burden and circuit dysregulation occurred in a concentration-dependent manner for specific transcription factors (CymR*/CymR) in E.coli, and direct negative feedback modules were able to control the concentration of CymR*/CymR, mitigate growth burden, and restore circuit functions. A quantitative design scheme was developed for circuits embedded with autorepression modules. Four key parameters were theoretically identified to determine the performance of autoregulated switches and were experimentally modified by fine-tuning promoter architectures and cooperativity. Using this strategy, we synthesized a number of switches and demonstrated its improvement of product titers and host growth controlling the complex deoxyviolacein biosynthesis pathway. Furthermore, we restored functions of a dysregulated multilayer NOR gate by integrating autorepression modules. Our work provides a blueprint for engineering host-adaptable synthetic systems.
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Affiliation(s)
- Ying Guan
- Department of Chemical Engineering, Tsinghua University, Beijing 100871, China.,Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xinmao Chen
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Bin Shao
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Xiangyu Ji
- CAS Key Laboratory of Microbial Physiological and Metabolic Engineering, State Key Laboratory of Microbial Resources, Institute of Microbiology, Chinese Academy of Sciences, Beijing 100101, China.,College of Life Science, University of Chinese Academy of Science, Beijing 100149, China
| | - Yanhui Xiang
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Guoqiang Jiang
- Department of Chemical Engineering, Tsinghua University, Beijing 100871, China
| | - Lina Xu
- National Protein Science Facility, Tsinghua University, Beijing 100871, China
| | - Zhanglin Lin
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China
| | - Qi Ouyang
- Center for Quantitative Biology, Peking-Tsinghua Joint Center for Life Sciences, School of Physics, Peking University, Beijing 100871, China
| | - Chunbo Lou
- Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.,College of Life Science, University of Chinese Academy of Science, Beijing 100149, China
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38
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Wang LJ, Jiang XR, Hou J, Wang CH, Chen GQ. Engineering Halomonas bluephagenesis via small regulatory RNAs. Metab Eng 2022; 73:58-69. [PMID: 35738548 DOI: 10.1016/j.ymben.2022.06.005] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/15/2022] [Revised: 05/05/2022] [Accepted: 06/17/2022] [Indexed: 12/25/2022]
Abstract
Halomonas bluephagenesis, a robust and contamination-resistant microorganism has been developed as a chassis for "Next Generation Industrial Biotechnology". The non-model H. bluephagenesis requires efficient tools to fine-tune its metabolic fluxes for enhanced production phenotypes. Here we report a highly efficient gene expression regulation system (PrrF1-2-HfqPa) in H. bluephagenesis, small regulatory RNA (sRNA) PrrF1 scaffold from Pseudomonas aeruginosa and a target-binding sequence that downregulate gene expression, and its cognate P. aeruginosa Hfq (HfqPa), recruited by the scaffold to facilitate the hybridization of sRNA and the target mRNA. The PrrF1-2-HfqPa system targeting prpC in H. bluephagenesis helps increase 3-hydroxyvalerate fraction in poly(3-hydroxybutyrate-co-3-hydroxyvalerate) to 21 mol% compared to 3.1 mol% of the control. This sRNA system repressed phaP1 and minD simultaneously, resulting in large polyhydroxybutyrate granules. Further, an sRNA library targeting 30 genes was employed for large-scale target identification to increase mevalonate production. This work expands the study on using an sRNA system not based on Escherichia coli MicC/SgrS-Hfq to repress gene expression, providing a framework to exploit new powerful genome engineering tools based on other sRNAs.
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Affiliation(s)
- Li-Juan Wang
- College of Biotechnology and Bioengineering, Zhejiang University of Technology, Hangzhou, 310014, China; Shandong Provincial Research Center for Bioinformatic Engineering and Technology, School of Life Sciences, Shandong University of Technology, Zibo, 255049, China
| | - Xiao-Ran Jiang
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China
| | - Jie Hou
- Shandong Provincial Research Center for Bioinformatic Engineering and Technology, School of Life Sciences, Shandong University of Technology, Zibo, 255049, China
| | - Cong-Han Wang
- Shandong Provincial Research Center for Bioinformatic Engineering and Technology, School of Life Sciences, Shandong University of Technology, Zibo, 255049, China
| | - Guo-Qiang Chen
- MOE Key Lab of Bioinformatics, School of Life Sciences, Tsinghua-Peking Center for Life Sciences, Tsinghua University, Beijing, 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China; MOE Key Laboratory for Industrial Biocatalysis, Dept Chemical Engineering, Tsinghua University, Beijing, 100084, China.
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39
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Atkinson E, Tuza Z, Perrino G, Stan GB, Ledesma-Amaro R. Resource-aware whole-cell model of division of labour in a microbial consortium for complex-substrate degradation. Microb Cell Fact 2022; 21:115. [PMID: 35698129 PMCID: PMC9195437 DOI: 10.1186/s12934-022-01842-0] [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: 01/28/2022] [Accepted: 05/30/2022] [Indexed: 11/10/2022] Open
Abstract
BACKGROUND Low-cost sustainable feedstocks are essential for commercially viable biotechnologies. These feedstocks, often derived from plant or food waste, contain a multitude of different complex biomolecules which require multiple enzymes to hydrolyse and metabolise. Current standard biotechnology uses monocultures in which a single host expresses all the proteins required for the consolidated bioprocess. However, these hosts have limited capacity for expressing proteins before growth is impacted. This limitation may be overcome by utilising division of labour (DOL) in a consortium, where each member expresses a single protein of a longer degradation pathway. RESULTS Here, we model a two-strain consortium, with one strain expressing an endohydrolase and a second strain expressing an exohydrolase, for cooperative degradation of a complex substrate. Our results suggest that there is a balance between increasing expression to enhance degradation versus the burden that higher expression causes. Once a threshold of burden is reached, the consortium will consistently perform better than an equivalent single-cell monoculture. CONCLUSIONS We demonstrate that resource-aware whole-cell models can be used to predict the benefits and limitations of using consortia systems to overcome burden. Our model predicts the region of expression where DOL would be beneficial for growth on starch, which will assist in making informed design choices for this, and other, complex-substrate degradation pathways.
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Affiliation(s)
- Eliza Atkinson
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Zoltan Tuza
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Giansimone Perrino
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK
| | - Guy-Bart Stan
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK.
| | - Rodrigo Ledesma-Amaro
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, SW72AZ, UK.
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40
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Lu J, Şimşek E, Silver A, You L. Advances and challenges in programming pattern formation using living cells. Curr Opin Chem Biol 2022; 68:102147. [PMID: 35472832 PMCID: PMC9158282 DOI: 10.1016/j.cbpa.2022.102147] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2022] [Revised: 03/15/2022] [Accepted: 03/18/2022] [Indexed: 11/29/2022]
Abstract
Spatial patterning of cell populations is a ubiquitous phenomenon in nature. Patterns occur at various length and time scales and exhibit immense diversity. In addition to offering a deeper understanding of the emergence of patterns in nature, the ability to program synthetic patterns using living cells has the potential for broad applications. To date, however, progress in engineering pattern formation has been hampered by technical challenges. In this Review, we discuss recent advances in programming pattern formation in terms of biological insights, experimental and computational tool development, and potential applications.
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Affiliation(s)
- Jia Lu
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Emrah Şimşek
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Anita Silver
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC 27708, USA; Center for Genomic and Computational Biology, Duke University, Durham, NC, 27708, USA; Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, NC, 27708, USA.
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41
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Talenton V, Baby V, Gourgues G, Mouden C, Claverol S, Vashee S, Blanchard A, Labroussaa F, Jores J, Arfi Y, Sirand-Pugnet P, Lartigue C. Genome Engineering of the Fast-Growing Mycoplasma feriruminatoris toward a Live Vaccine Chassis. ACS Synth Biol 2022; 11:1919-1930. [PMID: 35511588 PMCID: PMC9128628 DOI: 10.1021/acssynbio.2c00062] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
Abstract
Development of a new generation of vaccines is a key challenge for the control of infectious diseases affecting both humans and animals. Synthetic biology methods offer new ways to engineer bacterial chassis that can be used as vectors to present heterologous antigens and train the immune system against pathogens. Here, we describe the construction of a bacterial chassis based on the fast-growing Mycoplasma feriruminatoris, and the first steps toward its application as a live vaccine against contagious caprine pleuropneumonia (CCPP). To do so, the M. feriruminatoris genome was cloned in yeast, modified by iterative cycles of Cas9-mediated deletion of loci encoding virulence factors, and transplanted back in Mycoplasma capricolum subsp. capricolum recipient cells to produce the designed M. feriruminatoris chassis. Deleted genes encoded the glycerol transport and metabolism systems GtsABCD and GlpOKF and the Mycoplasma Ig binding protein-Mycoplasma Ig protease (MIB-MIP) immunoglobulin cleavage system. Phenotypic assays of the M. feriruminatoris chassis confirmed the corresponding loss of H2O2 production and IgG cleavage activities, while growth remained unaltered. The resulting mycoplasma chassis was further evaluated as a platform for the expression of heterologous surface proteins. A genome locus encoding an inactivated MIB-MIP system from the CCPP-causative agent Mycoplasma capricolum subsp. capripneumoniae was grafted in replacement of its homolog at the original locus in the chassis genome. Both heterologous proteins were detected in the resulting strain using proteomics, confirming their expression. This study demonstrates that advanced genome engineering methods are henceforth available for the fast-growing M. feriruminatoris, facilitating the development of novel vaccines, in particular against major mycoplasma diseases.
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Affiliation(s)
- Vincent Talenton
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
| | - Vincent Baby
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
- Département de Biologie, Université de Sherbrooke, J1K 2R1 Sherbrooke, Québec, Canada
| | - Geraldine Gourgues
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
| | | | - Stephane Claverol
- Plateforme Proteome, University of Bordeaux, F-33076 Bordeaux, France
| | - Sanjay Vashee
- J. Craig Venter Institute, Rockville, Maryland 20850, United States
| | - Alain Blanchard
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
| | - Fabien Labroussaa
- Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern CH-3001, Switzerland
| | - Joerg Jores
- Institute of Veterinary Bacteriology, Vetsuisse Faculty, University of Bern, Bern CH-3001, Switzerland
| | - Yonathan Arfi
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
| | | | - Carole Lartigue
- University of Bordeaux, INRAE, UMR BFP, F-33882 Villenave d’Ornon, France
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42
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Chakraborty D, Rengaswamy R, Raman K. Designing Biological Circuits: From Principles to Applications. ACS Synth Biol 2022; 11:1377-1388. [PMID: 35320676 DOI: 10.1021/acssynbio.1c00557] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
Abstract
Genetic circuit design is a well-studied problem in synthetic biology. Ever since the first genetic circuits─the repressilator and the toggle switch─were designed and implemented, many advances have been made in this area of research. The current review systematically organizes a number of key works in this domain by employing the versatile framework of generalized morphological analysis. Literature in the area has been mapped on the basis of (a) the design methodologies used, ranging from brute-force searches to control-theoretic approaches, (b) the modeling techniques employed, (c) various circuit functionalities implemented, (d) key design characteristics, and (e) the strategies used for the robust design of genetic circuits. We conclude our review with an outlook on multiple exciting areas for future research, based on the systematic assessment of key research gaps that have been readily unravelled by our analysis framework.
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Affiliation(s)
- Debomita Chakraborty
- Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
| | - Raghunathan Rengaswamy
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Department of Chemical Engineering, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
| | - Karthik Raman
- Bhupat and Jyoti Mehta School of Biosciences, Department of Biotechnology, Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Centre for Integrative Biology and Systems medicinE (IBSE), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
- Robert Bosch Centre for Data Science and Articial Intelligence (RBCDSAI), Indian Institute of Technology (IIT) Madras, Chennai 600 036, India
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43
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Kar S, Bordiya Y, Rodriguez N, Kim J, Gardner EC, Gollihar JD, Sung S, Ellington AD. Orthogonal control of gene expression in plants using synthetic promoters and CRISPR-based transcription factors. PLANT METHODS 2022; 18:42. [PMID: 35351174 PMCID: PMC8966344 DOI: 10.1186/s13007-022-00867-1] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/22/2021] [Accepted: 03/01/2022] [Indexed: 06/01/2023]
Abstract
BACKGROUND The construction and application of synthetic genetic circuits is frequently improved if gene expression can be orthogonally controlled, relative to the host. In plants, orthogonality can be achieved via the use of CRISPR-based transcription factors that are programmed to act on natural or synthetic promoters. The construction of complex gene circuits can require multiple, orthogonal regulatory interactions, and this in turn requires that the full programmability of CRISPR elements be adapted to non-natural and non-standard promoters that have few constraints on their design. Therefore, we have developed synthetic promoter elements in which regions upstream of the minimal 35S CaMV promoter are designed from scratch to interact via programmed gRNAs with dCas9 fusions that allow activation of gene expression. RESULTS A panel of three, mutually orthogonal promoters that can be acted on by artificial gRNAs bound by CRISPR regulators were designed. Guide RNA expression targeting these promoters was in turn controlled by either Pol III (U6) or ethylene-inducible Pol II promoters, implementing for the first time a fully artificial Orthogonal Control System (OCS). Following demonstration of the complete orthogonality of the designs, the OCS was tied to cellular metabolism by putting gRNA expression under the control of an endogenous plant signaling molecule, ethylene. The ability to form complex circuitry was demonstrated via the ethylene-driven, ratiometric expression of fluorescent proteins in single plants. CONCLUSIONS The design of synthetic promoters is highly generalizable to large tracts of sequence space, allowing Orthogonal Control Systems of increasing complexity to potentially be generated at will. The ability to tie in several different basal features of plant molecular biology (Pol II and Pol III promoters, ethylene regulation) to the OCS demonstrates multiple opportunities for engineering at the system level. Moreover, given the fungibility of the core 35S CaMV promoter elements, the derived synthetic promoters can potentially be utilized across a variety of plant species.
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Affiliation(s)
- Shaunak Kar
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.
- Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, TX, USA.
| | - Yogendra Bordiya
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA
- Life Sciences Solutions Group, Thermo Fisher Scientific, Austin, TX, USA
| | - Nestor Rodriguez
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA
| | - Junghyun Kim
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA
| | - Elizabeth C Gardner
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA
- Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, TX, USA
| | | | - Sibum Sung
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.
| | - Andrew D Ellington
- Department of Molecular Biosciences, University of Texas at Austin, Austin, TX, USA.
- Center for Systems and Synthetic Biology, University of Texas at Austin, Austin, TX, USA.
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44
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Casas A, Bultelle M, Motraghi C, Kitney R. PASIV: A Pooled Approach-Based Workflow to Overcome Toxicity-Induced Design of Experiments Failures and Inefficiencies. ACS Synth Biol 2022; 11:1272-1291. [PMID: 35261238 PMCID: PMC8938949 DOI: 10.1021/acssynbio.1c00562] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
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We present here a
newly developed workflow—which we have
called PASIV—designed to provide a solution to a practical
problem with design of experiments (DoE) methodology: i.e., what can
be done if the scoping phase of the DoE cycle is severely hampered
by burden and toxicity issues (caused by either the metabolite or
an intermediary), making it unreliable or impossible to proceed to
the screening phase? PASIV—standing for pooled approach, screening,
identification, and visualization—was designed so the (viable)
region of interest can be made to appear through an interplay between
biology and software. This was achieved by combining multiplex construction
in a pooled approach (one-pot reaction) with a viability assay and
with a range of bioinformatics tools (including a novel construct
matching tool). PASIV was tested on the exemplar of the lycopene pathway—under
stressful constitutive expression—yielding a region of interest
with comparatively stronger producers.
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Affiliation(s)
- Alexis Casas
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2BX, United Kingdom
| | - Matthieu Bultelle
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2BX, United Kingdom
| | - Charles Motraghi
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2BX, United Kingdom
| | - Richard Kitney
- Department of Bioengineering, Imperial College London, Exhibition Road, London SW7 2BX, United Kingdom
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45
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Szydlo K, Ignatova Z, Gorochowski TE. Improving the Robustness of Engineered Bacteria to Nutrient Stress Using Programmed Proteolysis. ACS Synth Biol 2022; 11:1049-1059. [PMID: 35174698 PMCID: PMC9097571 DOI: 10.1021/acssynbio.1c00490] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Indexed: 11/30/2022]
Abstract
The use of short peptide tags in synthetic genetic circuits allows for the tuning of gene expression dynamics and release of amino acid resources through targeted protein degradation. Here, we use elements of the Escherichia coli and Mesoplasma florum transfer-mRNA (tmRNA) ribosome rescue systems to compare endogenous and foreign proteolysis systems in E. coli. We characterize the performance and burden of each and show that, while both greatly shorten the half-life of a tagged protein, the endogenous system is approximately 10 times more efficient. On the basis of these results we then demonstrate using mathematical modeling and experiments how proteolysis can improve cellular robustness through targeted degradation of a reporter protein in auxotrophic strains, providing a limited secondary source of essential amino acids that help partially restore growth when nutrients become scarce. These findings provide avenues for controlling the functional lifetime of engineered cells once deployed and increasing their tolerance to fluctuations in nutrient availability.
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Affiliation(s)
- Klara Szydlo
- Institute
of Biochemistry and Molecular Biology, University
of Hamburg, 20146, Hamburg, Germany
| | - Zoya Ignatova
- Institute
of Biochemistry and Molecular Biology, University
of Hamburg, 20146, Hamburg, Germany
| | - Thomas E. Gorochowski
- School
of Biological Sciences, University of Bristol, BS8 1TQ, Bristol, United Kingdom
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46
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Upadhyay A, Feltman NR, Sychla A, Janzen A, Das SR, Maselko M, Smanski M. Genetically engineered insects with sex-selection and genetic incompatibility enable population suppression. eLife 2022; 11:71230. [PMID: 35108195 PMCID: PMC8860436 DOI: 10.7554/elife.71230] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/12/2021] [Accepted: 01/31/2022] [Indexed: 11/18/2022] Open
Abstract
Engineered Genetic Incompatibility (EGI) is a method to create species-like barriers to sexual reproduction. It has applications in pest control that mimic Sterile Insect Technique when only EGI males are released. This can be facilitated by introducing conditional female-lethality to EGI strains to generate a sex-sorting incompatible male system (SSIMS). Here, we demonstrate a proof of concept by combining tetracycline-controlled female lethality constructs with a pyramus-targeting EGI line in the model insect Drosophila melanogaster. We show that both functions (incompatibility and sex-sorting) are robustly maintained in the SSIMS line and that this approach is effective for population suppression in cage experiments. Further we show that SSIMS males remain competitive with wild-type males for reproduction with wild-type females, including at the level of sperm competition.
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Affiliation(s)
- Ambuj Upadhyay
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Minneapolis, United States
| | - Nathan R Feltman
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Saint Paul, United States
| | - Adam Sychla
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Saint Paul, United States
| | - Anna Janzen
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Saint Paul, United States
| | - Siba R Das
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Saint Paul, United States
| | | | - Michael Smanski
- Department of Biochemistry, Molecular Biology and Biophysics, University of Minnesota, Saint Paul, United States
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47
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Casas A, Bultelle M, Motraghi C, Kitney R. Removing the Bottleneck: Introducing cMatch - A Lightweight Tool for Construct-Matching in Synthetic Biology. Front Bioeng Biotechnol 2022; 9:785131. [PMID: 35083201 PMCID: PMC8784771 DOI: 10.3389/fbioe.2021.785131] [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: 09/28/2021] [Accepted: 12/14/2021] [Indexed: 11/30/2022] Open
Abstract
We present a software tool, called cMatch, to reconstruct and identify synthetic genetic constructs from their sequences, or a set of sub-sequences—based on two practical pieces of information: their modular structure, and libraries of components. Although developed for combinatorial pathway engineering problems and addressing their quality control (QC) bottleneck, cMatch is not restricted to these applications. QC takes place post assembly, transformation and growth. It has a simple goal, to verify that the genetic material contained in a cell matches what was intended to be built - and when it is not the case, to locate the discrepancies and estimate their severity. In terms of reproducibility/reliability, the QC step is crucial. Failure at this step requires repetition of the construction and/or sequencing steps. When performed manually or semi-manually QC is an extremely time-consuming, error prone process, which scales very poorly with the number of constructs and their complexity. To make QC frictionless and more reliable, cMatch performs an operation we have called “construct-matching” and automates it. Construct-matching is more thorough than simple sequence-matching, as it matches at the functional level-and quantifies the matching at the individual component level and across the whole construct. Two algorithms (called CM_1 and CM_2) are presented. They differ according to the nature of their inputs. CM_1 is the core algorithm for construct-matching and is to be used when input sequences are long enough to cover constructs in their entirety (e.g., obtained with methods such as next generation sequencing). CM_2 is an extension designed to deal with shorter data (e.g., obtained with Sanger sequencing), and that need recombining. Both algorithms are shown to yield accurate construct-matching in a few minutes (even on hardware with limited processing power), together with a set of metrics that can be used to improve the robustness of the decision-making process. To ensure reliability and reproducibility, cMatch builds on the highly validated pairwise-matching Smith-Waterman algorithm. All the tests presented have been conducted on synthetic data for challenging, yet realistic constructs - and on real data gathered during studies on a metabolic engineering example (lycopene production).
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Affiliation(s)
- Alexis Casas
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Matthieu Bultelle
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Charles Motraghi
- Department of Bioengineering, Imperial College London, London, United Kingdom
| | - Richard Kitney
- Department of Bioengineering, Imperial College London, London, United Kingdom
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48
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Tripathi S, Brahmachari S, Onuchic JN, Levine H. DNA supercoiling-mediated collective behavior of co-transcribing RNA polymerases. Nucleic Acids Res 2021; 50:1269-1279. [PMID: 34951454 PMCID: PMC8860607 DOI: 10.1093/nar/gkab1252] [Citation(s) in RCA: 15] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2021] [Revised: 12/02/2021] [Accepted: 12/06/2021] [Indexed: 11/14/2022] Open
Abstract
Multiple RNA polymerases (RNAPs) transcribing a gene have been known to exhibit collective group behavior, causing the transcription elongation rate to increase with the rate of transcription initiation. Such behavior has long been believed to be driven by a physical interaction or ‘push’ between closely spaced RNAPs. However, recent studies have posited that RNAPs separated by longer distances may cooperate by modifying the DNA segment under transcription. Here, we present a theoretical model incorporating the mechanical coupling between RNAP translocation and the DNA torsional response. Using stochastic simulations, we demonstrate DNA supercoiling-mediated long-range cooperation between co-transcribing RNAPs. We find that inhibiting transcription initiation can slow down the already recruited RNAPs, in agreement with recent experimental observations, and predict that the average transcription elongation rate varies non-monotonically with the rate of transcription initiation. We further show that while RNAPs transcribing neighboring genes oriented in tandem can cooperate, those transcribing genes in divergent or convergent orientations can act antagonistically, and that such behavior holds over a large range of intergenic separations. Our model makes testable predictions, revealing how the mechanical interplay between RNAPs and the DNA they transcribe can govern transcriptional dynamics.
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Affiliation(s)
- Shubham Tripathi
- PhD Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA.,Center for Theoretical Biological Physics & Department of Physics, Northeastern University, Boston, MA, USA
| | | | - José N Onuchic
- Center for Theoretical Biological Physics, Rice University, Houston, TX, USA.,Department of Physics and Astronomy, Department of Chemistry, & Department of Biosciences, Rice University, Houston, TX, USA
| | - Herbert Levine
- Center for Theoretical Biological Physics & Department of Physics, Northeastern University, Boston, MA, USA
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49
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Schladt T, Engelmann N, Kubaczka E, Hochberger C, Koeppl H. Automated Design of Robust Genetic Circuits: Structural Variants and Parameter Uncertainty. ACS Synth Biol 2021; 10:3316-3329. [PMID: 34807573 PMCID: PMC8689692 DOI: 10.1021/acssynbio.1c00193] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/06/2023]
Abstract
![]()
Genetic design automation
methods for combinational circuits often
rely on standard algorithms from electronic design automation in their
circuit synthesis and technology mapping. However, those algorithms
are domain-specific and are hence often not directly suitable for
the biological context. In this work we identify aspects of those
algorithms that require domain-adaptation. We first demonstrate that
enumerating structural variants for a given Boolean specification
allows us to find better performing circuits and that stochastic gate
assignment methods need to be properly adjusted in order to find the
best assignment. Second, we present a general circuit scoring scheme
that accounts for the limited accuracy of biological device models
including the variability across cells and show that circuits selected
according to this score exhibit higher robustness with respect to
parametric variations. If gate characteristics in a library are just
given in terms of intervals, we provide means to efficiently propagate
signals through such a circuit and compute corresponding scores. We
demonstrate the novel design approach using the Cello gate library
and 33 logic functions that were synthesized and implemented in vivo
recently (Nielsen, A., et al., Science, 2016, 352 (6281), DOI: 10.1126/science.aac7341). Across this set of functions, 32 of them can be improved by simply
considering structural variants yielding performance gains of up to
7.9-fold, whereas 22 of them can be improved with gains up to 26-fold
when selecting circuits according to the novel robustness score. We
furthermore report on the synergistic combination of the two proposed
improvements.
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Affiliation(s)
- Tobias Schladt
- Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany
| | - Nicolai Engelmann
- Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany
| | - Erik Kubaczka
- Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany
| | - Christian Hochberger
- Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany
| | - Heinz Koeppl
- Department of Electrical Engineering and Information Technology, TU Darmstadt, Darmstadt 64283, Germany
- Centre for Synthetic Biology, TU Darmstadt, Darmstadt 64283, Germany
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50
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McBride CD, Del Vecchio D. Predicting Composition of Genetic Circuits with Resource Competition: Demand and Sensitivity. ACS Synth Biol 2021; 10:3330-3342. [PMID: 34780149 DOI: 10.1021/acssynbio.1c00281] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
The design of genetic circuits typically relies on characterization of constituent modules in isolation to predict the behavior of modules' composition. However, it has been shown that the behavior of a genetic module changes when other modules are in the cell due to competition for shared resources. In order to engineer multimodule circuits that behave as intended, it is thus necessary to predict changes in the behavior of a genetic module when other modules load cellular resources. Here, we introduce two characteristics of circuit modules: the demand for cellular resources and the sensitivity to resource loading. When both are known for every genetic module in a circuit library, they can be used to predict any module's behavior upon addition of any other module to the cell. We develop an experimental approach to measure both characteristics for any circuit module using a resource sensor module. Using the measured resource demand and sensitivity for each module in a library, the outputs of the modules can be accurately predicted when they are inserted in the cell in arbitrary combinations. These resource competition characteristics may be used to inform the design of genetic circuits that perform as predicted despite resource competition.
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Affiliation(s)
- Cameron D. McBride
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02142, United States
| | - Domitilla Del Vecchio
- Department of Mechanical Engineering, Massachusetts Institute of Technology, 77 Massachusetts Avenue, Cambridge, Massachusetts 02142, United States
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