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Yang X, Yang J, Huang H, Yan X, Li X, Lin Z. Achieving robust synthetic tolerance in industrial E. coli through negative auto-regulation of a DsrA-Hfq module. Synth Syst Biotechnol 2024; 9:462-469. [PMID: 38634002 PMCID: PMC11021974 DOI: 10.1016/j.synbio.2024.04.003] [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: 02/05/2024] [Revised: 03/29/2024] [Accepted: 04/06/2024] [Indexed: 04/19/2024] Open
Abstract
In industrial fermentation processes, microorganisms often encounter acid stress, which significantly impact their productivity. This study focused on the acid-resistant module composed of small RNA (sRNA) DsrA and the sRNA chaperone Hfq. Our previous study had shown that this module improved the cell growth of Escherichia coli MG1655 at low pH, but failed to obtain this desired phenotype in industrial strains. Here, we performed a quantitative analysis of DsrA-Hfq module to determine the optimal expression mode. We then assessed the potential of the CymR-based negative auto-regulation (NAR) circuit for industrial application, under different media, strains and pH levels. Growth assay at pH 4.5 revealed that NAR-05D04H circuit was the best acid-resistant circuit to improve the cell growth of E. coli MG1655. This circuit was robust and worked well in the industrial lysine-producing strain E. coli SCEcL3 at a starting pH of 6.8 and without pH control, resulting in a 250 % increase in lysine titer and comparable biomass in shaking flask fermentation compared to the parent strain. This study showed the practical application of NAR circuit in regulating DsrA-Hfq module, effectively and robustly improving the acid tolerance of industrial strains, which provides a new approach for breeding industrial strains with tolerance phenotype.
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Affiliation(s)
- Xiaofeng Yang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Jingduan Yang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Haozheng Huang
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Xiaofang Yan
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Xiaofan Li
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
| | - Zhanglin Lin
- School of Biology and Biological Engineering, South China University of Technology, Guangzhou, 510006, China
- School of Biomedicine, Guangdong University of Technology, Guangzhou 510006, China
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2
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Yan H, Cao G, Wang J, Zhu X, Dong S, Huang Y, Chao M, Li Y, Gao F, Hua L. An enzymatically activated AND-gate DNA logic circuit for tumor cells recognition via multi-microRNAs detection. Biosens Bioelectron 2024; 256:116278. [PMID: 38608497 DOI: 10.1016/j.bios.2024.116278] [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] [Received: 12/29/2023] [Revised: 03/26/2024] [Accepted: 04/06/2024] [Indexed: 04/14/2024]
Abstract
The DNA-based logic circuit, constructed to mimic biochemical reaction networks, is highly significant in detecting biomarkers at the molecular level. The differences in the expression levels of microRNAs (miRNAs) within different types of cells provide hope for distinguishing cell subtypes. However, reliance on a single miRNA often leads to unreliable results. Herein, we constructed an enzyme-triggered cascade logic circuit based on the AND gate, which is capable of generating corresponding fluorescence signals in the presence of target miRNAs. The introduction of apurinic/apyrimidinic (AP) sites effectively reduces the likelihood of false signal generation. Amplification of the fluorescence signal relies on the catalytic hairpin assembly and the repetitive reuse of the multicomponent nucleic acid enzyme (MNAzyme). We demonstrated that the logic circuit can not only distinguish cancer cells from normal cells but also identify different types of cancer cells. The programmability of the logic circuits and the simplicity of the assay system allow us to modify the functional sequences to recognize different types of biomarkers, thus providing a reference for the identification of various cell subtypes.
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Affiliation(s)
- Hanrong Yan
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Guojun Cao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China; Department of Laboratory Medicine, Huashan Hospital, Shanghai Medical College, Fudan University, Shanghai, 200040, China
| | - Jin Wang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Xu Zhu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Shuqing Dong
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Yuqi Huang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Minghao Chao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Yuting Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China
| | - Fenglei Gao
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China.
| | - Lei Hua
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, 221004, China; Department of Neurosurgery, The Affiliated Hospital of Xuzhou Medical University, Xuzhou, 221002, China.
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3
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Lu Z, Shen Q, Bandari NC, Evans S, McDonnell L, Liu L, Jin W, Luna-Flores CH, Collier T, Talbo G, McCubbin T, Esquirol L, Myers C, Trau M, Dumsday G, Speight R, Howard CB, Vickers CE, Peng B. LowTempGAL: a highly responsive low temperature-inducible GAL system in Saccharomyces cerevisiae. Nucleic Acids Res 2024:gkae460. [PMID: 38808673 DOI: 10.1093/nar/gkae460] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/19/2023] [Revised: 05/12/2024] [Accepted: 05/16/2024] [Indexed: 05/30/2024] Open
Abstract
Temperature is an important control factor for biologics biomanufacturing in precision fermentation. Here, we explored a highly responsive low temperature-inducible genetic system (LowTempGAL) in the model yeast Saccharomyces cerevisiae. Two temperature biosensors, a heat-inducible degron and a heat-inducible protein aggregation domain, were used to regulate the GAL activator Gal4p, rendering the leaky LowTempGAL systems. Boolean-type induction was achieved by implementing a second-layer control through low-temperature-mediated repression on GAL repressor gene GAL80, but suffered delayed response to low-temperature triggers and a weak response at 30°C. Application potentials were validated for protein and small molecule production. Proteomics analysis suggested that residual Gal80p and Gal4p insufficiency caused suboptimal induction. 'Turbo' mechanisms were engineered through incorporating a basal Gal4p expression and a galactose-independent Gal80p-supressing Gal3p mutant (Gal3Cp). Varying Gal3Cp configurations, we deployed the LowTempGAL systems capable for a rapid stringent high-level induction upon the shift from a high temperature (37-33°C) to a low temperature (≤30°C). Overall, we present a synthetic biology procedure that leverages 'leaky' biosensors to deploy highly responsive Boolean-type genetic circuits. The key lies in optimisation of the intricate layout of the multi-factor system. The LowTempGAL systems may be applicable in non-conventional yeast platforms for precision biomanufacturing.
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Affiliation(s)
- Zeyu Lu
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Qianyi Shen
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Naga Chandra Bandari
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Samuel Evans
- ARC Centre of Excellence in Synthetic Biology, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Liam McDonnell
- ARC Centre of Excellence in Synthetic Biology, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Lian Liu
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- The Queensland Node of Metabolomics Australia and Proteomics Australia (Q-MAP), Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Wanli Jin
- Institute for Molecular Bioscience (IMB), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Carlos Horacio Luna-Flores
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Thomas Collier
- ARC Centre of Excellence in Synthetic Biology, Australia
- School of Natural Sciences, Macquarie University, Sydney, NSW 2109, Australia
| | - Gert Talbo
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- The Queensland Node of Metabolomics Australia and Proteomics Australia (Q-MAP), Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Tim McCubbin
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Lygie Esquirol
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- Environment, Commonwealth Scientific and Industrial Research Organisation, Canberra, ACT 2601, Australia
| | - Chris Myers
- Department of Electrical, Computer, and Energy Engineering University of Colorado, Boulder, CO 80309, USA
| | - Matt Trau
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- School of Chemistry and Molecular Biosciences (SCMB), the University of Queensland, Brisbane, QLD 4072, Australia
| | - Geoff Dumsday
- Manufacturing, Commonwealth Scientific and Industrial Research Organisation, Clayton, VIC, 3169, Australia
| | - Robert Speight
- ARC Centre of Excellence in Synthetic Biology, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
- Advanced Engineering Biology Future Science Platform, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Black Mountain, ACT, 2601, Australia
| | - Christopher B Howard
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
| | - Claudia E Vickers
- ARC Centre of Excellence in Synthetic Biology, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
| | - Bingyin Peng
- ARC Centre of Excellence in Synthetic Biology, Australia
- Australian Institute for Bioengineering and Nanotechnology (AIBN), The University of Queensland, Brisbane, QLD 4072, Australia
- Centre of Agriculture and the Bioeconomy, School of Biology and Environmental Science, Faculty of Science, Queensland University of Technology, Brisbane, QLD 4000, Australia
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4
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Graham AJ, Partipilo G, Dundas CM, Miniel Mahfoud IE, Halwachs KN, Holwerda AJ, Simmons TR, FitzSimons TM, Coleman SM, Rinehart R, Chiu D, Tyndall AE, Sajbel KC, Rosales AM, Keitz BK. Transcriptional regulation of living materials via extracellular electron transfer. Nat Chem Biol 2024:10.1038/s41589-024-01628-y. [PMID: 38783133 DOI: 10.1038/s41589-024-01628-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2023] [Accepted: 04/19/2024] [Indexed: 05/25/2024]
Abstract
Engineered living materials combine the advantages of biological and synthetic systems by leveraging genetic and metabolic programming to control material-wide properties. Here, we demonstrate that extracellular electron transfer (EET), a microbial respiration process, can serve as a tunable bridge between live cell metabolism and synthetic material properties. In this system, EET flux from Shewanella oneidensis to a copper catalyst controls hydrogel cross-linking via two distinct chemistries to form living synthetic polymer networks. We first demonstrate that synthetic biology-inspired design rules derived from fluorescence parameterization can be applied toward EET-based regulation of polymer network mechanics. We then program transcriptional Boolean logic gates to govern EET gene expression, which enables design of computational polymer networks that mechanically respond to combinations of molecular inputs. Finally, we control fibroblast morphology using EET as a bridge for programmed material properties. Our results demonstrate how rational genetic circuit design can emulate physiological behavior in engineered living materials.
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Affiliation(s)
- Austin J Graham
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Gina Partipilo
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Christopher M Dundas
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Ismar E Miniel Mahfoud
- Interdisciplinary Life Sciences Graduate Program, University of Texas at Austin, Austin, TX, USA
| | - Kathleen N Halwachs
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Alexis J Holwerda
- Interdisciplinary Life Sciences Graduate Program, University of Texas at Austin, Austin, TX, USA
| | - Trevor R Simmons
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Thomas M FitzSimons
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Sarah M Coleman
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Rebecca Rinehart
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Darian Chiu
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Avery E Tyndall
- Department of Chemical and Biological Engineering, Colorado School of Mines, Golden, CO, USA
| | - Kenneth C Sajbel
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Adrianne M Rosales
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA
| | - Benjamin K Keitz
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, USA.
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5
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de Oliveira MA, Florentino LH, Sales TT, Lima RN, Barros LRC, Limia CG, Almeida MSM, Robledo ML, Barros LMG, Melo EO, Bittencourt DM, Rehen SK, Bonamino MH, Rech E. Protocol for the establishment of a serine integrase-based platform for functional validation of genetic switch controllers in eukaryotic cells. PLoS One 2024; 19:e0303999. [PMID: 38781126 PMCID: PMC11115199 DOI: 10.1371/journal.pone.0303999] [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: 09/06/2023] [Accepted: 05/04/2024] [Indexed: 05/25/2024] Open
Abstract
Serine integrases (Ints) are a family of site-specific recombinases (SSRs) encoded by some bacteriophages to integrate their genetic material into the genome of a host. Their ability to rearrange DNA sequences in different ways including inversion, excision, or insertion with no help from endogenous molecular machinery, confers important biotechnological value as genetic editing tools with high host plasticity. Despite advances in their use in prokaryotic cells, only a few Ints are currently used as gene editors in eukaryotes, partly due to the functional loss and cytotoxicity presented by some candidates in more complex organisms. To help expand the number of Ints available for the assembly of more complex multifunctional circuits in eukaryotic cells, this protocol describes a platform for the assembly and functional screening of serine-integrase-based genetic switches designed to control gene expression by directional inversions of DNA sequence orientation. The system consists of two sets of plasmids, an effector module and a reporter module, both sets assembled with regulatory components (as promoter and terminator regions) appropriate for expression in mammals, including humans, and plants. The complete method involves plasmid design, DNA delivery, testing and both molecular and phenotypical assessment of results. This platform presents a suitable workflow for the identification and functional validation of new tools for the genetic regulation and reprogramming of organisms with importance in different fields, from medical applications to crop enhancement, as shown by the initial results obtained. This protocol can be completed in 4 weeks for mammalian cells or up to 8 weeks for plant cells, considering cell culture or plant growth time.
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Affiliation(s)
- Marco A. de Oliveira
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, Distrito Federal, Brazil
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
| | - Lilian H. Florentino
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, Distrito Federal, Brazil
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Thais T. Sales
- Department of Cell Biology, Institute of Biological Science, University of Brasília, Brasília, Distrito Federal, Brazil
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Rayane N. Lima
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Luciana R. C. Barros
- Center for Translational Research in Oncology, Instituto do Câncer do Estado de São Paulo, Hospital das Clínicas da Faculdade de Medicina de Universidade de São Paulo, São Paulo, Brazil
| | - Cintia G. Limia
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, Brazil
| | - Mariana S. M. Almeida
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Maria L. Robledo
- Molecular Carcinogenesis Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, Brazil
| | - Leila M. G. Barros
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Eduardo O. Melo
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Daniela M. Bittencourt
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
| | - Stevens K. Rehen
- D’Or Institute for Research and Education (IDOR), Rio de Janeiro, Brazil
- Institute of Biomedical Sciences, Federal University of Rio de Janeiro, Rio de Janeiro, Brazil
| | - Martín H. Bonamino
- Cell and Gene Therapy Program, Research Coordination, National Cancer Institute (INCA), Rio de Janeiro, Brazil
- Vice-Presidency of Research and Biological Collections (VPPCB), FIOCRUZ – Oswaldo Cruz Foundation Institute, Rio de Janeiro, Brazil
| | - Elibio Rech
- National Institute of Science and Technology in Synthetic Biology (INCT BioSyn), Brasília, Distrito Federal, Brazil
- Embrapa Genetic Resources and Biotechnology, Brasília, Distrito Federal, Brazil
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6
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Khan MA, Herring G, Zhu JY, Oliva M, Fourie E, Johnston B, Zhang Z, Potter J, Pineda L, Pflueger J, Swain T, Pflueger C, Lloyd JPB, Secco D, Small I, Kidd BN, Lister R. CRISPRi-based circuits to control gene expression in plants. Nat Biotechnol 2024:10.1038/s41587-024-02236-w. [PMID: 38769424 DOI: 10.1038/s41587-024-02236-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/29/2022] [Accepted: 04/10/2024] [Indexed: 05/22/2024]
Abstract
The construction of synthetic gene circuits in plants has been limited by a lack of orthogonal and modular parts. Here, we implement a CRISPR (clustered regularly interspaced short palindromic repeats) interference (CRISPRi)-based reversible gene circuit platform in plants. We create a toolkit of engineered repressible promoters of different strengths and construct NOT and NOR gates in Arabidopsis thaliana protoplasts. We determine the optimal processing system to express single guide RNAs from RNA Pol II promoters to introduce NOR gate programmability for interfacing with host regulatory sequences. The performance of a NOR gate in stably transformed Arabidopsis plants demonstrates the system's programmability and reversibility in a complex multicellular organism. Furthermore, cross-species activity of CRISPRi-based logic gates is shown in Physcomitrium patens, Triticum aestivum and Brassica napus protoplasts. Layering multiple NOR gates together creates OR, NIMPLY and AND logic functions, highlighting the modularity of our system. Our CRISPRi circuits are orthogonal, compact, reversible, programmable and modular and provide a platform for sophisticated spatiotemporal control of gene expression in plants.
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Affiliation(s)
- Muhammad Adil Khan
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Gabrielle Herring
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Jia Yuan Zhu
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Marina Oliva
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Elliott Fourie
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Benjamin Johnston
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Zhining Zhang
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Jarred Potter
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Luke Pineda
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Jahnvi Pflueger
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia
| | - Tessa Swain
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia
| | - Christian Pflueger
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia
| | - James P B Lloyd
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - David Secco
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Ian Small
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia
| | - Brendan N Kidd
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia.
- CSIRO Synthetic Biology Future Science Platform, Brisbane, Queensland, Australia.
| | - Ryan Lister
- Australian Research Council Centre of Excellence in Plant Energy Biology, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia.
- Australian Research Council Centre of Excellence in Plants for Space, School of Molecular Sciences, The University of Western Australia, Perth, Western Australia, Australia.
- Harry Perkins Institute of Medical Research, The University of Western Australia, Perth, Western Australia, Australia.
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7
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Zevallos-Aliaga D, De Graeve S, Obando-Chávez P, Vaccari NA, Gao Y, Peeters T, Guerra DG. Highly Sensitive Whole-Cell Mercury Biosensors for Environmental Monitoring. BIOSENSORS 2024; 14:246. [PMID: 38785720 PMCID: PMC11117708 DOI: 10.3390/bios14050246] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/24/2024] [Revised: 04/27/2024] [Accepted: 04/30/2024] [Indexed: 05/25/2024]
Abstract
Whole-cell biosensors could serve as eco-friendly and cost-effective alternatives for detecting potentially toxic bioavailable heavy metals in aquatic environments. However, they often fail to meet practical requirements due to an insufficient limit of detection (LOD) and high background noise. In this study, we designed a synthetic genetic circuit specifically tailored for detecting ionic mercury, which we applied to environmental samples collected from artisanal gold mining sites in Peru. We developed two distinct versions of the biosensor, each utilizing a different reporter protein: a fluorescent biosensor (Mer-RFP) and a colorimetric biosensor (Mer-Blue). Mer-RFP enabled real-time monitoring of the culture's response to mercury samples using a plate reader, whereas Mer-Blue was analysed for colour accumulation at the endpoint using a specially designed, low-cost camera setup for harvested cell pellets. Both biosensors exhibited negligible baseline expression of their respective reporter proteins and responded specifically to HgBr2 in pure water. Mer-RFP demonstrated a linear detection range from 1 nM to 1 μM, whereas Mer-Blue showed a linear range from 2 nM to 125 nM. Our biosensors successfully detected a high concentration of ionic mercury in the reaction bucket where artisanal miners produce a mercury-gold amalgam. However, they did not detect ionic mercury in the water from active mining ponds, indicating a concentration lower than 3.2 nM Hg2+-a result consistent with chemical analysis quantitation. Furthermore, we discuss the potential of Mer-Blue as a practical and affordable monitoring tool, highlighting its stability, reliance on simple visual colorimetry, and the possibility of sensitivity expansion to organic mercury.
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Affiliation(s)
- Dahlin Zevallos-Aliaga
- Laboratorio de Moléculas Individuales, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias e Ingeniería, Universidad Peruana Cayetano Heredia, Lima 15102, Peru; (D.Z.-A.); (P.O.-C.); (N.A.V.)
| | - Stijn De Graeve
- Open BioLab Brussels, Erasmushogeschool Brussel, Laarbeeklaan 121, B-1090 Jette, Belgium
| | - Pamela Obando-Chávez
- Laboratorio de Moléculas Individuales, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias e Ingeniería, Universidad Peruana Cayetano Heredia, Lima 15102, Peru; (D.Z.-A.); (P.O.-C.); (N.A.V.)
| | - Nicolás A. Vaccari
- Laboratorio de Moléculas Individuales, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias e Ingeniería, Universidad Peruana Cayetano Heredia, Lima 15102, Peru; (D.Z.-A.); (P.O.-C.); (N.A.V.)
| | - Yue Gao
- Archaeology, Environmental Changes and Geo-Chemistry (AMGC), Vrije Universiteit Brussel, Pleinlaan 2, B-1050 Brussels, Belgium;
| | - Tom Peeters
- Open BioLab Brussels, Erasmushogeschool Brussel, Laarbeeklaan 121, B-1090 Jette, Belgium
| | - Daniel G. Guerra
- Laboratorio de Moléculas Individuales, Laboratorios de Investigación y Desarrollo, Facultad de Ciencias e Ingeniería, Universidad Peruana Cayetano Heredia, Lima 15102, Peru; (D.Z.-A.); (P.O.-C.); (N.A.V.)
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8
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Peccoud S, Berezin CT, Hernandez SI, Peccoud J. PlasCAT: Plasmid Cloud Assembly Tool. Bioinformatics 2024; 40:btae299. [PMID: 38696761 PMCID: PMC11101281 DOI: 10.1093/bioinformatics/btae299] [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: 11/21/2023] [Revised: 04/04/2024] [Accepted: 04/30/2024] [Indexed: 05/04/2024] Open
Abstract
SUMMARY PlasCAT (Plasmid Cloud Assembly Tool) is an easy-to-use cloud-based bioinformatics tool that enables de novo plasmid sequence assembly from raw sequencing data. Nontechnical users can now assemble sequences from long reads and short reads without ever touching a line of code. PlasCAT uses high-performance computing servers to reduce run times on assemblies and deliver results faster. AVAILABILITY AND IMPLEMENTATION PlasCAT is freely available on the web at https://sequencing.genofab.com. The assembly pipeline source code and server code are available for download at https://bitbucket.org/genofabinc/workspace/projects/PLASCAT. Click the Cancel button to access the source code without authenticating. Web servers implemented in React.js and Python, with all major browsers supported.
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Affiliation(s)
| | - Casey-Tyler Berezin
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, United States
| | - Sarah I Hernandez
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, United States
| | - Jean Peccoud
- GenoFAB, Inc., Fort Collins, CO 80528, United States
- Department of Chemical and Biological Engineering, Colorado State University, Fort Collins, CO 80523, United States
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9
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Kieffer C, Rondelez Y, Gines G. Coupling Exponential to Linear Amplification for Endpoint Quantitative Analysis. ADVANCED SCIENCE (WEINHEIM, BADEN-WURTTEMBERG, GERMANY) 2024:e2309386. [PMID: 38593401 DOI: 10.1002/advs.202309386] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/03/2023] [Revised: 03/26/2024] [Indexed: 04/11/2024]
Abstract
Exponential DNA amplification techniques are fundamental in ultrasensitive molecular diagnostics. These systems offer a wide dynamic range, but the quantification requires real-time monitoring of the amplification reaction. Linear amplification schemes, despite their limited sensitivity, can achieve quantitative measurement from a single end-point readout, suitable for low-cost, point-of-care, or massive testing. Reconciling the sensitivity of exponential amplification with the simplicity of end-point readout would thus break through a major design dilemma and open a route to a new generation of massively scalable quantitative bioassays. Here a hybrid nucleic acid-based circuit design is introduced to compute a logarithmic function, therefore providing a wide dynamic range based on a single end-point measurement. CELIA (Coupling Exponential amplification reaction to LInear Amplification) exploits a versatile biochemical circuit architecture to couple a tunable linear amplification stage - optionally embedding an inverter function - downstream of an exponential module in a one-pot format. Applied to the detection of microRNAs, CELIA provides a limit of detection in the femtomolar range and a dynamic range of six decades. This isothermal approach bypasses thermocyclers without compromising sensitivity, thereby opening the way to applications in various diagnostic assays, and providing a simplified, cost-efficient, and high throughput solution for quantitative nucleic acid analysis.
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Affiliation(s)
- Coline Kieffer
- Laboratoire Gulliver, UMR7083 CNRS/ESPCI Paris-PSL Research University, 10 rue Vauquelin, Paris, 75005, France
| | - Yannick Rondelez
- Laboratoire Gulliver, UMR7083 CNRS/ESPCI Paris-PSL Research University, 10 rue Vauquelin, Paris, 75005, France
| | - Guillaume Gines
- Laboratoire Gulliver, UMR7083 CNRS/ESPCI Paris-PSL Research University, 10 rue Vauquelin, Paris, 75005, France
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10
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Sinzger-D'Angelo M, Hanst M, Reinhardt F, Koeppl H. Effects of mRNA conformational switching on translational noise in gene circuits. J Chem Phys 2024; 160:134108. [PMID: 38573847 DOI: 10.1063/5.0186927] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/09/2023] [Accepted: 03/08/2024] [Indexed: 04/06/2024] Open
Abstract
Intragenic translational heterogeneity describes the variation in translation at the level of transcripts for an individual gene. A factor that contributes to this source of variation is the mRNA structure. Both the composition of the thermodynamic ensemble, i.e., the stationary distribution of mRNA structures, and the switching dynamics between those play a role. The effect of the switching dynamics on intragenic translational heterogeneity remains poorly understood. We present a stochastic translation model that accounts for mRNA structure switching and is derived from a Markov model via approximate stochastic filtering. We assess the approximation on various timescales and provide a method to quantify how mRNA structure dynamics contributes to translational heterogeneity. With our approach, we allow quantitative information on mRNA switching from biophysical experiments or coarse-grain molecular dynamics simulations of mRNA structures to be included in gene regulatory chemical reaction network models without an increase in the number of species. Thereby, our model bridges a gap between mRNA structure kinetics and gene expression models, which we hope will further improve our understanding of gene regulatory networks and facilitate genetic circuit design.
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Affiliation(s)
| | - Maleen Hanst
- Centre for Synthetic Biology, Technische Universität Darmstadt, Darmstadt, Germany
| | - Felix Reinhardt
- Centre for Synthetic Biology, Technische Universität Darmstadt, Darmstadt, Germany
| | - Heinz Koeppl
- Centre for Synthetic Biology, Technische Universität Darmstadt, Darmstadt, Germany
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11
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Wu CQ, Wu RY, Zhang QL, Wang LL, Wang Y, Dai C, Zhang CX, Xu L. Harnessing Catalytic RNA Circuits for Construction of Artificial Signaling Pathways in Mammalian Cells. Angew Chem Int Ed Engl 2024; 63:e202319309. [PMID: 38298112 DOI: 10.1002/anie.202319309] [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: 12/14/2023] [Revised: 01/21/2024] [Accepted: 01/31/2024] [Indexed: 02/02/2024]
Abstract
Engineering of genetic networks with artificial signaling pathways (ASPs) can reprogram cellular responses and phenotypes under different circumstances for a variety of diagnostic and therapeutic purposes. However, construction of ASPs between originally independent endogenous genes in mammalian cells is highly challenging. Here we report an amplifiable RNA circuit that can theoretically build regulatory connections between any endogenous genes in mammalian cells. We harness the system of catalytic hairpin assembly with combination of controllable CRISPR-Cas9 function to transduce the signals from distinct messenger RNA expression of trigger genes into manipulation of target genes. Through introduction of these RNA-based genetic circuits, mammalian cells are endowed with autonomous capabilities to sense the changes of RNA expression either induced by ligand stimuli or from various cell types and control the cellular responses and fates via apoptosis-related ASPs. Our design provides a generalized platform for construction of ASPs inside the genetic networks of mammalian cells based on differentiated RNA expression.
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Affiliation(s)
- Chao-Qun Wu
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Ruo-Yue Wu
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Qiu-Long Zhang
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
- School of Pharmacy and Medical Technology, Key Laboratory of Pharmaceutical Analysis and Laboratory Medicine of Fujian Province, Putian University, Putian, 351100, China
| | - Liang-Liang Wang
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Yang Wang
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Chu Dai
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Chen-Xi Zhang
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
| | - Liang Xu
- MOE Key Laboratory of Bioinorganic and Synthetic Chemistry, School of Chemistry, Sun Yat-Sen University, Guangzhou, 510275, China
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12
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Mohsenin H, Wagner HJ, Rosenblatt M, Kemmer S, Drepper F, Huesgen P, Timmer J, Weber W. Design of a Biohybrid Materials Circuit with Binary Decoder Functionality. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2024; 36:e2308092. [PMID: 38118057 DOI: 10.1002/adma.202308092] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/10/2023] [Revised: 12/05/2023] [Indexed: 12/22/2023]
Abstract
Synthetic biology applies concepts from electrical engineering and information processing to endow cells with computational functionality. Transferring the underlying molecular components into materials and wiring them according to topologies inspired by electronic circuit boards has yielded materials systems that perform selected computational operations. However, the limited functionality of available building blocks is restricting the implementation of advanced information-processing circuits into materials. Here, a set of protease-based biohybrid modules the bioactivity of which can either be induced or inhibited is engineered. Guided by a quantitative mathematical model and following a design-build-test-learn (DBTL) cycle, the modules are wired according to circuit topologies inspired by electronic signal decoders, a fundamental motif in information processing. A 2-input/4-output binary decoder for the detection of two small molecules in a material framework that can perform regulated outputs in form of distinct protease activities is designed. The here demonstrated smart material system is strongly modular and can be used for biomolecular information processing for example in advanced biosensing or drug delivery applications.
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Affiliation(s)
- Hasti Mohsenin
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestraße 18, 79104, Freiburg, Germany
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
| | - Hanna J Wagner
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestraße 18, 79104, Freiburg, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Albertstraße 19a, 79104, Freiburg, Germany
| | - Marcus Rosenblatt
- Institute of Physics and Freiburg Center for Data Analysis and Modelling (FDM), University of Freiburg, Hermann-Herder-Straße 3, 79104, Freiburg, Germany
| | - Svenja Kemmer
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
- Institute of Physics and Freiburg Center for Data Analysis and Modelling (FDM), University of Freiburg, Hermann-Herder-Straße 3, 79104, Freiburg, Germany
| | - Friedel Drepper
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
| | - Pitter Huesgen
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
- CIBSS - Centre for Integrative Biological Signalling Studies, University of Freiburg, Schänzlestraße 18, 79104, Freiburg, Germany
| | - Jens Timmer
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestraße 18, 79104, Freiburg, Germany
- Institute of Physics and Freiburg Center for Data Analysis and Modelling (FDM), University of Freiburg, Hermann-Herder-Straße 3, 79104, Freiburg, Germany
| | - Wilfried Weber
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Schänzlestraße 18, 79104, Freiburg, Germany
- INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany
- Faculty of Biology, University of Freiburg, Schänzlestraße 1, 79104, Freiburg, Germany
- Spemann Graduate School of Biology and Medicine (SGBM), University of Freiburg, Albertstraße 19a, 79104, Freiburg, Germany
- Saarland University, Department of Materials Science and Engineering, Campus D2 2, 66123, Saarbrücken, Germany
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13
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Buson F, Gao Y, Wang B. Genetic Parts and Enabling Tools for Biocircuit Design. ACS Synth Biol 2024; 13:697-713. [PMID: 38427821 DOI: 10.1021/acssynbio.3c00691] [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: 03/03/2024]
Abstract
Synthetic biology aims to engineer biological systems for customized tasks through the bottom-up assembly of fundamental building blocks, which requires high-quality libraries of reliable, modular, and standardized genetic parts. To establish sets of parts that work well together, synthetic biologists created standardized part libraries in which every component is analyzed in the same metrics and context. Here we present a state-of-the-art review of the currently available part libraries for designing biocircuits and their gene expression regulation paradigms at transcriptional, translational, and post-translational levels in Escherichia coli. We discuss the necessary facets to integrate these parts into complex devices and systems along with the current efforts to catalogue and standardize measurement data. To better display the range of available parts and to facilitate part selection in synthetic biology workflows, we established biopartsDB, a curated database of well-characterized and useful genetic part and device libraries with detailed quantitative data validated by the published literature.
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Affiliation(s)
- Felipe Buson
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FF, U.K
| | - Yuanli Gao
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3FF, U.K
| | - Baojun Wang
- College of Chemical and Biological Engineering & ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310058, China
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14
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Son SH, Kang J, Shin Y, Lee C, Sung BH, Lee JY, Lee W. Sustainable production of natural products using synthetic biology: Ginsenosides. J Ginseng Res 2024; 48:140-148. [PMID: 38465212 PMCID: PMC10920010 DOI: 10.1016/j.jgr.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/17/2023] [Revised: 12/23/2023] [Accepted: 12/30/2023] [Indexed: 03/12/2024] Open
Abstract
Synthetic biology approaches offer potential for large-scale and sustainable production of natural products with bioactive potency, including ginsenosides, providing a means to produce novel compounds with enhanced therapeutic properties. Ginseng, known for its non-toxic and potent qualities in traditional medicine, has been used for various medical needs. Ginseng has shown promise for its antioxidant and neuroprotective properties, and it has been used as a potential agent to boost immunity against various infections when used together with other drugs and vaccines. Given the increasing demand for ginsenosides and the challenges associated with traditional extraction methods, synthetic biology holds promise in the development of therapeutics. In this review, we discuss recent developments in microorganism producer engineering and ginsenoside production in microorganisms using synthetic biology approaches.
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Affiliation(s)
- So-Hee Son
- Research Center for Bio-Based Chemistry, Korea Research Institute of Chemical Technology (KRICT), Ulsan, Republic of Korea
| | - Jin Kang
- Synthetic Biology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Biosystems and Bioengineering Program, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea
| | - YuJin Shin
- School of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea
| | - ChaeYoung Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea
| | - Bong Hyun Sung
- Synthetic Biology Research Center, Korea Research Institute of Bioscience and Biotechnology (KRIBB), Daejeon, Republic of Korea
- Biosystems and Bioengineering Program, Korea National University of Science and Technology (UST), Daejeon, Republic of Korea
- Graduate School of Engineering Biology, Korea Advanced Institute of Science and Technology (KAIST), Daejeon, Republic of Korea
| | - Ju Young Lee
- Research Center for Bio-Based Chemistry, Korea Research Institute of Chemical Technology (KRICT), Ulsan, Republic of Korea
| | - Wonsik Lee
- School of Pharmacy, Sungkyunkwan University, Suwon, Republic of Korea
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15
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Boo A, Toth T, Yu Q, Pfotenhauer A, Fields BD, Lenaghan SC, Stewart CN, Voigt CA. Synthetic microbe-to-plant communication channels. Nat Commun 2024; 15:1817. [PMID: 38418817 PMCID: PMC10901793 DOI: 10.1038/s41467-024-45897-6] [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: 02/10/2023] [Accepted: 02/07/2024] [Indexed: 03/02/2024] Open
Abstract
Plants and microbes communicate to collaborate to stop pests, scavenge nutrients, and react to environmental change. Microbiota consisting of thousands of species interact with each other and plants using a large chemical language that is interpreted by complex regulatory networks. In this work, we develop modular interkingdom communication channels, enabling bacteria to convey environmental stimuli to plants. We introduce a "sender device" in Pseudomonas putida and Klebsiella pneumoniae, that produces the small molecule p-coumaroyl-homoserine lactone (pC-HSL) when the output of a sensor or circuit turns on. This molecule triggers a "receiver device" in the plant to activate gene expression. We validate this system in Arabidopsis thaliana and Solanum tuberosum (potato) grown hydroponically and in soil, demonstrating its modularity by swapping bacteria that process different stimuli, including IPTG, aTc and arsenic. Programmable communication channels between bacteria and plants will enable microbial sentinels to transmit information to crops and provide the building blocks for designing artificial consortia.
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Affiliation(s)
- Alice Boo
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Tyler Toth
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Qiguo Yu
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Alexander Pfotenhauer
- Center for Agricultural Synthetic Biology, University of Tennessee, Knoxville, TN, 37996, USA
| | - Brandon D Fields
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Scott C Lenaghan
- Center for Agricultural Synthetic Biology, University of Tennessee, Knoxville, TN, 37996, USA
| | - C Neal Stewart
- Center for Agricultural Synthetic Biology, University of Tennessee, Knoxville, TN, 37996, USA
| | - Christopher A Voigt
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA.
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16
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Zhang S, Ma Z, Li W, Shen Y, Xu Y, Liu G, Chang J, Li Z, Qin H, Tian B, Gong H, Liu D, Thuronyi B, Voigt C. EvoAI enables extreme compression and reconstruction of the protein sequence space. RESEARCH SQUARE 2024:rs.3.rs-3930833. [PMID: 38464127 PMCID: PMC10925456 DOI: 10.21203/rs.3.rs-3930833/v1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 03/12/2024]
Abstract
Designing proteins with improved functions requires a deep understanding of how sequence and function are related, a vast space that is hard to explore. The ability to efficiently compress this space by identifying functionally important features is extremely valuable. Here, we first establish a method called EvoScan to comprehensively segment and scan the high-fitness sequence space to obtain anchor points that capture its essential features, especially in high dimensions. Our approach is compatible with any biomolecular function that can be coupled to a transcriptional output. We then develop deep learning and large language models to accurately reconstruct the space from these anchors, allowing computational prediction of novel, highly fit sequences without prior homology-derived or structural information. We apply this hybrid experimental-computational method, which we call EvoAI, to a repressor protein and find that only 82 anchors are sufficient to compress the high-fitness sequence space with a compression ratio of 1048. The extreme compressibility of the space informs both applied biomolecular design and understanding of natural evolution.
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17
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Gao Y, Zhou Y, Ji X, Graham AJ, Dundas CM, Miniel Mahfoud IE, Tibbett BM, Tan B, Partipilo G, Dodabalapur A, Rivnay J, Keitz BK. A hybrid transistor with transcriptionally controlled computation and plasticity. Nat Commun 2024; 15:1598. [PMID: 38383505 PMCID: PMC10881478 DOI: 10.1038/s41467-024-45759-1] [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: 09/20/2023] [Accepted: 02/02/2024] [Indexed: 02/23/2024] Open
Abstract
Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.
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Affiliation(s)
- Yang Gao
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Yuchen Zhou
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Microelectronics Research Center, University of Texas at Austin, Austin, TX, 78758, USA
| | - Xudong Ji
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Simpson Querrey Institute, Northwestern University, Chicago, IL, 60611, USA
| | - Austin J Graham
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Christopher M Dundas
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Biology, Stanford University, Stanford, CA, 94305, USA
| | - Ismar E Miniel Mahfoud
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Bailey M Tibbett
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Benjamin Tan
- Microelectronics Research Center, University of Texas at Austin, Austin, TX, 78758, USA
- Department of Chemistry, University of Texas at Austin, Austin, TX, 78712, USA
| | - Gina Partipilo
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Ananth Dodabalapur
- Department of Electrical and Computer Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Microelectronics Research Center, University of Texas at Austin, Austin, TX, 78758, USA
| | - Jonathan Rivnay
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Simpson Querrey Institute, Northwestern University, Chicago, IL, 60611, USA
| | - Benjamin K Keitz
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA.
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18
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Blanch-Asensio M, Tadimarri VS, Wilk A, Sankaran S. Discovery of a high-performance phage-derived promoter/repressor system for probiotic lactobacillus engineering. Microb Cell Fact 2024; 23:42. [PMID: 38326819 PMCID: PMC10848424 DOI: 10.1186/s12934-024-02302-7] [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: 12/05/2023] [Accepted: 01/10/2024] [Indexed: 02/09/2024] Open
Abstract
BACKGROUND The Lactobacillaceae family comprises many species of great importance for the food and healthcare industries, with numerous strains identified as beneficial for humans and used as probiotics. Hence, there is a growing interest in engineering these probiotic bacteria as live biotherapeutics for animals and humans. However, the genetic parts needed to regulate gene expression in these bacteria remain limited compared to model bacteria like E. coli or B. subtilis. To address this deficit, in this study, we selected and tested several bacteriophage-derived genetic parts with the potential to regulate transcription in lactobacilli. RESULTS We screened genetic parts from 6 different lactobacilli-infecting phages and identified one promoter/repressor system with unprecedented functionality in Lactiplantibacillus plantarum WCFS1. The phage-derived promoter was found to achieve expression levels nearly 9-fold higher than the previously reported strongest promoter in this strain and the repressor was able to almost completely repress this expression by reducing it nearly 500-fold. CONCLUSIONS The new parts and insights gained from their engineering will enhance the genetic programmability of lactobacilli for healthcare and industrial applications.
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Affiliation(s)
- Marc Blanch-Asensio
- Bioprogrammable Materials, INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany
- Saarland University, 66123, Saarbrücken, Germany
| | - Varun Sai Tadimarri
- Bioprogrammable Materials, INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany
- Saarland University, 66123, Saarbrücken, Germany
| | - Alina Wilk
- Bioprogrammable Materials, INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany
- Saarland University, 66123, Saarbrücken, Germany
| | - Shrikrishnan Sankaran
- Bioprogrammable Materials, INM - Leibniz Institute for New Materials, Campus D2 2, 66123, Saarbrücken, Germany.
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19
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Ngo HTT, Nguyen DH, You SH, Van Nguyen K, Kim SY, Hong Y, Min JJ. Reprogramming a Doxycycline-Inducible Gene Switch System for Bacteria-Mediated Cancer Therapy. Mol Imaging Biol 2024; 26:148-161. [PMID: 38017353 DOI: 10.1007/s11307-023-01879-6] [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] [Received: 09/08/2023] [Revised: 11/12/2023] [Accepted: 11/13/2023] [Indexed: 11/30/2023]
Abstract
PURPOSE Attenuated Salmonella typhimurium is a potential biotherapeutic antitumor agent because it can colonize tumors and inhibit their growth. The present study aimed to develop a doxycycline (Doxy)-inducible gene switch system in attenuated S. typhimurium and assess its therapeutic efficacy in various tumor-bearing mice models. PROCEDURES A Doxy-inducible gene switch system comprising two plasmids was engineered to trigger the expression of cargo genes (Rluc8 and clyA). Attenuated S. typhimurium carrying Rluc8 were injected intravenously into BALB/c mice bearing CT26 tumors, and bioluminescence images were captured at specified intervals post-administration of doxycycline. The tumor-suppressive effects of bacteria carrying clyA were evaluated in BALB/c mice bearing CT26 tumors and in C57BL/6 mice bearing MC38 tumors. RESULTS Expression of the fimE gene, induced only in the presence of Doxy, triggered a unidirectional switch of the POXB20 promoter to induce expression of the cargo genes. The switch event was maintained over a long period of bacterial culture. After intravenous injection of transformed Salmonella into mice bearing CT26 tumors, the bacteria transformed with the Doxy-inducible gene switch system for Rluc8 targeted only tumor tissues and expressed the payloads 2 days after Doxy treatment. Notably, bacteria carrying the Doxy-inducible gene switch system for clyA effectively suppressed tumor growth and prolonged survival, even after just one Doxy induction. CONCLUSIONS These results suggest that attenuated S. typhimurium carrying this novel gene switch system elicited significant therapeutic effects through a single induction triggering and were a potential biotherapeutic agent for tumor therapy.
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Affiliation(s)
- Hien Thi-Thu Ngo
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
- Department of Molecular Medicine (BrainKorea21 Plus), Chonnam National University Graduate School, Gwangju, 61469, Republic of Korea
- Department of Biochemistry, Hanoi Medical University, No 1, Ton That Tung St., Dong Da, Hanoi, 100000, Vietnam
| | - Dinh-Huy Nguyen
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
- Department of Molecular Medicine (BrainKorea21 Plus), Chonnam National University Graduate School, Gwangju, 61469, Republic of Korea
| | - Sung-Hwan You
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
- CNCure Biotech, Hwasun, 58128, Republic of Korea
| | - Khuynh Van Nguyen
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
- Department of Molecular Medicine (BrainKorea21 Plus), Chonnam National University Graduate School, Gwangju, 61469, Republic of Korea
| | - So-Young Kim
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea
- CNCure Biotech, Hwasun, 58128, Republic of Korea
| | - Yeongjin Hong
- CNCure Biotech, Hwasun, 58128, Republic of Korea.
- Department of Microbiology, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea.
| | - Jung-Joon Min
- Institute for Molecular Imaging and Theranostics, Chonnam National University Medical School, Gwangju, 61469, Republic of Korea.
- Department of Molecular Medicine (BrainKorea21 Plus), Chonnam National University Graduate School, Gwangju, 61469, Republic of Korea.
- CNCure Biotech, Hwasun, 58128, Republic of Korea.
- Department of Nuclear Medicine, Chonnam National University Medical School and Hwasun Hospital, Gwangju, 61469, Republic of Korea.
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20
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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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21
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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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22
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Trofimova E, Logel DY, Jaschke PR. An Improved Method for Eliminating or Creating Intragenic Bacterial Promoters. Methods Mol Biol 2024; 2760:199-207. [PMID: 38468090 DOI: 10.1007/978-1-0716-3658-9_12] [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: 03/13/2024]
Abstract
Recent advances in genomic refactoring have been hindered by the ever-present complication of internal or cryptic transcriptional regulation. Typical approaches to these features have been to randomize or perform mass alterations to the gene sequences thought to contain the regulatory motifs; however, this approach can cause problems by altering translational speeds, introducing long distance DNA-DNA interaction effects, and inducing RNA toxicity. Previously, we developed a rational design approach named COdon Restrained Promoter SilEncing (CORPSE) which takes externally identified promoter sequences and uses position-specific scoring matrices as proxy promoter strengths to make minimal changes to promoter sequences to disable their activity. Additionally, through inverting our system we were also able to modify weak internal promoters to increase their activity. In this chapter, we augment our previous process with the biophysical model Promoter Calculator v1.0 developed by LaFleur et al. to combine promoter identification and activity prediction, with our algorithm to silently modify promoter sequences, to provide more robust promoter elimination and creation.
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Affiliation(s)
- Ellina Trofimova
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, NSW, Australia
| | - Dominic Y Logel
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, NSW, Australia
| | - Paul R Jaschke
- School of Natural Sciences, Macquarie University, Sydney, NSW, Australia.
- ARC Centre of Excellence in Synthetic Biology, Macquarie University, Sydney, NSW, Australia.
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23
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Asensio‐Calavia A, Ceballos‐Munuera Á, Méndez‐Pérez A, Álvarez B, Fernández LÁ. A tuneable genetic switch for tight control of tac promoters in Escherichia coli boosts expression of synthetic injectisomes. Microb Biotechnol 2024; 17:e14328. [PMID: 37608576 PMCID: PMC10832536 DOI: 10.1111/1751-7915.14328] [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: 04/25/2023] [Revised: 07/27/2023] [Accepted: 08/02/2023] [Indexed: 08/24/2023] Open
Abstract
Biosafety of engineered bacteria as living therapeutics requires a tight regulation to control the specific delivery of protein effectors, maintaining minimum leakiness in the uninduced (OFF) state and efficient expression in the induced (ON) state. Here, we report a three repressors (3R) genetic circuit that tightly regulates the expression of multiple tac promoters (Ptac) integrated in the chromosome of E. coli and drives the expression of a complex type III secretion system injectisome for therapeutic protein delivery. The 3R genetic switch is based on the tetracycline repressor (TetR), the non-inducible lambda repressor cI (ind-) and a mutant lac repressor (LacIW220F ) with higher activity. The 3R switch was optimized with different protein translation and degradation signals that control the levels of LacIW220F . We demonstrate the ability of an optimized switch to fully repress the strong leakiness of the Ptac promoters in the OFF state while triggering their efficient activation in the ON state with anhydrotetracycline (aTc), an inducer suitable for in vivo use. The implementation of the optimized 3R switch in the engineered synthetic injector E. coli (SIEC) strain boosts expression of injectisomes upon aTc induction, while maintaining a silent OFF state that preserves normal growth in the absence of the inducer. Since Ptac is a commonly used promoter, the 3R switch may have multiple applications for tight control of protein expression in E. coli. In addition, the modularity of the 3R switch may enable its tuning for the control of Ptac promoters with different inducers.
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Affiliation(s)
- Alejandro Asensio‐Calavia
- Department of Microbial Biotechnology, Centro Nacional de BiotecnologíaConsejo Superior de Investigaciones Científicas (CNB‐CSIC)MadridSpain
| | - Álvaro Ceballos‐Munuera
- Department of Microbial Biotechnology, Centro Nacional de BiotecnologíaConsejo Superior de Investigaciones Científicas (CNB‐CSIC)MadridSpain
- Programa de Doctorado en Biociencias MolecularesUniversidad Autónoma de Madrid (UAM)MadridSpain
| | - Almudena Méndez‐Pérez
- Department of Microbial Biotechnology, Centro Nacional de BiotecnologíaConsejo Superior de Investigaciones Científicas (CNB‐CSIC)MadridSpain
- Programa de Doctorado en Biociencias MolecularesUniversidad Autónoma de Madrid (UAM)MadridSpain
| | - Beatriz Álvarez
- Department of Microbial Biotechnology, Centro Nacional de BiotecnologíaConsejo Superior de Investigaciones Científicas (CNB‐CSIC)MadridSpain
| | - Luis Ángel Fernández
- Department of Microbial Biotechnology, Centro Nacional de BiotecnologíaConsejo Superior de Investigaciones Científicas (CNB‐CSIC)MadridSpain
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24
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Bello AJ, Popoola A, Okpuzor J, Ihekwaba-Ndibe AE, Olorunniji FJ. A Genetic Circuit Design for Targeted Viral RNA Degradation. Bioengineering (Basel) 2023; 11:22. [PMID: 38247899 PMCID: PMC10813695 DOI: 10.3390/bioengineering11010022] [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: 12/07/2023] [Accepted: 12/19/2023] [Indexed: 01/23/2024] Open
Abstract
Advances in synthetic biology have led to the design of biological parts that can be assembled in different ways to perform specific functions. For example, genetic circuits can be designed to execute specific therapeutic functions, including gene therapy or targeted detection and the destruction of invading viruses. Viral infections are difficult to manage through drug treatment. Due to their high mutation rates and their ability to hijack the host's ribosomes to make viral proteins, very few therapeutic options are available. One approach to addressing this problem is to disrupt the process of converting viral RNA into proteins, thereby disrupting the mechanism for assembling new viral particles that could infect other cells. This can be done by ensuring precise control over the abundance of viral RNA (vRNA) inside host cells by designing biological circuits to target vRNA for degradation. RNA-binding proteins (RBPs) have become important biological devices in regulating RNA processing. Incorporating naturally upregulated RBPs into a gene circuit could be advantageous because such a circuit could mimic the natural pathway for RNA degradation. This review highlights the process of viral RNA degradation and different approaches to designing genetic circuits. We also provide a customizable template for designing genetic circuits that utilize RBPs as transcription activators for viral RNA degradation, with the overall goal of taking advantage of the natural functions of RBPs in host cells to activate targeted viral RNA degradation.
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Affiliation(s)
- Adebayo J. Bello
- School of Pharmacy & Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK; (A.J.B.); (A.P.)
- Department of Biological Sciences, Redeemer’s University, Ede 232101, Osun State, Nigeria
| | - Abdulgafar Popoola
- School of Pharmacy & Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK; (A.J.B.); (A.P.)
- Department of Medical Laboratory Science, Kwara State University, Malete, Ilorin 241102, Kwara State, Nigeria
| | - Joy Okpuzor
- Department of Cell Biology & Genetics, University of Lagos, Akoka, Lagos 101017, Lagos State, Nigeria;
| | | | - Femi J. Olorunniji
- School of Pharmacy & Biomolecular Sciences, Liverpool John Moores University, Liverpool L3 3AF, UK; (A.J.B.); (A.P.)
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25
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Chiang AJ, Hasty J. Design of synthetic bacterial biosensors. Curr Opin Microbiol 2023; 76:102380. [PMID: 37703812 DOI: 10.1016/j.mib.2023.102380] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Revised: 07/19/2023] [Accepted: 08/15/2023] [Indexed: 09/15/2023]
Abstract
Novel whole-cell bacterial biosensor designs require an emphasis on moving toward field deployment. Many current sensors are characterized under specified laboratory conditions, which frequently do not represent actual deployment conditions. To this end, recent developments such as toolkits for probing new host chassis that are more robust to environments of interest, have paved the way for improved designs. Strategies for rational tuning of genetic components or tools such as genetic amplifiers or designs that allow post hoc tuning are essential in optimizing existing biosensors for practical application. Furthermore, recent work has seen a rise in directed evolution techniques, which can be immensely valuable in both tuning existing sensors and developing sensors for new analytes that lack characterized sensors. Combined with advancements in bioinformatics and capabilities in rewiring two-component systems, many new sensors can be established, broadening biosensor use cases. Last, recent work in CRISPR-based dynamic regulation and memory mechanisms, as well as kill-switches for biosafety and innovative output integration concepts, represents promising steps toward designing bacterial biosensors for deployment in dynamic and heterogeneous conditions.
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Affiliation(s)
- Alyssa J Chiang
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA.
| | - Jeff Hasty
- Department of Bioengineering, University of California San Diego, La Jolla, CA, USA; Molecular Biology Section, Division of Biological Sciences, University of California San Diego, La Jolla, CA, USA; Synthetic Biology Institute, University of California San Diego, La Jolla, CA, USA
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26
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Jin X, Gao Y, Chen X, Wang S, Qi Q, Liang Q. The Construction of the Self-Induced Sal System and Its Application in Salicylic Acid Production. Molecules 2023; 28:7825. [PMID: 38067556 PMCID: PMC10708014 DOI: 10.3390/molecules28237825] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/21/2023] [Revised: 11/26/2023] [Accepted: 11/27/2023] [Indexed: 12/18/2023] Open
Abstract
The design and construction of more complex and delicate genetic control circuits suffer from poor orthogonality in quorum sensing (QS) systems. The Sal system, which relies on salicylic acid as a signaling molecule, is an artificially engineered regulatory system with a structure that differs significantly from that of natural QS signaling molecules. Salicylic acid is an important drug precursor, mainly used in the production of drugs such as aspirin and anti-HIV drugs. However, there have been no reports on the construction of a self-induced Sal system in single cells. In this study, a high-copy plasmid backbone was used to construct the regulatory proteins and a self-induced promoter of salicylic acid in E. coli by adjusting the precise regulation of key gene expression; the sensitivity and induction range of this system were improved. Subsequently, the exogenous gene pchBA was introduced in E. coli to extend the shikimate pathway and synthesize salicylic acid, resulting in the construction of the first complete self-induced Sal system. Finally, the self-induced Sal System was combined with artificial trans-encoded sRNAs (atsRNAs) to repress the growth-essential gene ppc and accumulate the precursor substance PEP, thereby increasing the titer of salicylic acid by 151%. This construction of a self-induced artificial system introduces a new tool for selecting communication tools and induction systems in synthetic biology and metabolic engineering, but also demonstrates a self-inducible pathway design strategy for salicylic acid biosynthesis.
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Affiliation(s)
| | | | | | | | | | - Quanfeng Liang
- State Key Laboratory of Microbial Technology, Shandong University, Qingdao 266237, China; (X.J.); (Y.G.); (X.C.); (S.W.); (Q.Q.)
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27
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Van Hove B, De Wannemaeker L, Missiaen I, Maertens J, De Mey M. Taming CRISPRi: Dynamic range tuning through guide RNA diversion. N Biotechnol 2023; 77:50-57. [PMID: 37422184 DOI: 10.1016/j.nbt.2023.07.001] [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] [Received: 03/23/2023] [Accepted: 07/05/2023] [Indexed: 07/10/2023]
Abstract
CRISPRi is a powerful technique to repress gene expression in a targeted and highly efficient manner. However, this potency is a double-edged sword in inducible systems, as even leaky expression of guide RNA results in a repression phenotype, complicating applications such as dynamic metabolic engineering. We evaluated three methods to enhance the controllability of CRISPRi by modulating the level of free and DNA-bound guide RNA complexes. Overall repression can be attenuated through rationally designed mismatches in the reversibility determining region of the guide RNA sequence; decoy target sites can selectively modulate repression at low levels of induction; and the implementation of feedback control not only enhances the linearity of induction, but broadens the dynamic range of the output as well. Furthermore, feedback control significantly enhances the recovery rate after induction is removed. Used in combination, these techniques enable the fine-tuning of CRISPRi to meet restrictions imposed by the target and match the input signal required for induction.
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Affiliation(s)
- Bob Van Hove
- Centre for Synthetic Biology, Ghent University, Coupure links 653, 9000 Ghent, Belgium; Department of Chemical Engineering, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Lien De Wannemaeker
- Centre for Synthetic Biology, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Isolde Missiaen
- Centre for Synthetic Biology, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Jo Maertens
- Centre for Synthetic Biology, Ghent University, Coupure links 653, 9000 Ghent, Belgium
| | - Marjan De Mey
- Centre for Synthetic Biology, Ghent University, Coupure links 653, 9000 Ghent, Belgium.
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28
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Capponi S, Daniels KG. Harnessing the power of artificial intelligence to advance cell therapy. Immunol Rev 2023; 320:147-165. [PMID: 37415280 DOI: 10.1111/imr.13236] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Accepted: 06/17/2023] [Indexed: 07/08/2023]
Abstract
Cell therapies are powerful technologies in which human cells are reprogrammed for therapeutic applications such as killing cancer cells or replacing defective cells. The technologies underlying cell therapies are increasing in effectiveness and complexity, making rational engineering of cell therapies more difficult. Creating the next generation of cell therapies will require improved experimental approaches and predictive models. Artificial intelligence (AI) and machine learning (ML) methods have revolutionized several fields in biology including genome annotation, protein structure prediction, and enzyme design. In this review, we discuss the potential of combining experimental library screens and AI to build predictive models for the development of modular cell therapy technologies. Advances in DNA synthesis and high-throughput screening techniques enable the construction and screening of libraries of modular cell therapy constructs. AI and ML models trained on this screening data can accelerate the development of cell therapies by generating predictive models, design rules, and improved designs.
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Affiliation(s)
- Sara Capponi
- Department of Functional Genomics and Cellular Engineering, IBM Almaden Research Center, San Jose, California, USA
- Center for Cellular Construction, San Francisco, California, USA
| | - Kyle G Daniels
- Department of Cellular and Molecular Pharmacology, University of California, San Francisco, California, USA
- Department of Genetics, Stanford University School of Medicine, Stanford, California, USA
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29
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Tanniche I, Behkam B. Engineered live bacteria as disease detection and diagnosis tools. J Biol Eng 2023; 17:65. [PMID: 37875910 PMCID: PMC10598922 DOI: 10.1186/s13036-023-00379-z] [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: 05/11/2023] [Accepted: 09/18/2023] [Indexed: 10/26/2023] Open
Abstract
Sensitive and minimally invasive medical diagnostics are essential to the early detection of diseases, monitoring their progression and response to treatment. Engineered bacteria as live sensors are being developed as a new class of biosensors for sensitive, robust, noninvasive, and in situ detection of disease onset at low cost. Akin to microrobotic systems, a combination of simple genetic rules, basic logic gates, and complex synthetic bioengineering principles are used to program bacterial vectors as living machines for detecting biomarkers of diseases, some of which cannot be detected with other sensing technologies. Bacterial whole-cell biosensors (BWCBs) can have wide-ranging functions from detection only, to detection and recording, to closed-loop detection-regulated treatment. In this review article, we first summarize the unique benefits of bacteria as living sensors. We then describe the different bacteria-based diagnosis approaches and provide examples of diagnosing various diseases and disorders. We also discuss the use of bacteria as imaging vectors for disease detection and image-guided surgery. We conclude by highlighting current challenges and opportunities for further exploration toward clinical translation of these bacteria-based systems.
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Affiliation(s)
- Imen Tanniche
- Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, 24061, USA
| | - Bahareh Behkam
- Department of Mechanical Engineering, Virginia Tech, Blacksburg, VA, 24061, USA.
- School of Biomedical Engineered and Sciences, Virginia Tech, Blacksburg, VA, 24061, USA.
- Center for Engineered Health, Institute for Critical Technology and Applied Science, Virginia Tech, Blacksburg, VA, 24061, USA.
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30
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Rilievo G, Cecconello A, Fouladi Ghareshiran N, Magro M, Simmel FC, Vianello F. Integration of DNA-RNA-triplex-based regulation of transcription into molecular logic gates. FEBS Lett 2023; 597:2461-2472. [PMID: 37591635 DOI: 10.1002/1873-3468.14721] [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] [Received: 06/28/2023] [Revised: 08/07/2023] [Accepted: 08/08/2023] [Indexed: 08/19/2023]
Abstract
In recent years, increasing numbers of noncoding RNA molecules were identified as possible components of endogenous DNA-RNA hybrid triplexes involved in gene regulation. Triplexes are potentially involved in complex molecular signaling networks that, if understood, would allow the engineering of biological computing components. Here, by making use of the enhancing and inhibiting effects of such triplexes, we demonstrate in vitro the construction of triplex-based molecular gates: 'exclusive OR' (XOR), 'exclusive NOT-OR' (XNOR), and a threshold gate, via transcription of a fluorogenic RNA aptamer. Precise modulation was displayed by the biomolecular-integrated systems over a wide interval of transcriptional outputs, ranging from drastic inhibition to significant enhancement. The present contribution represents a first example of molecular gates developed using DNA-RNA triplex nanostructures.
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Affiliation(s)
- Graziano Rilievo
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Alessandro Cecconello
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | | | - Massimiliano Magro
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
| | - Friedrich C Simmel
- Physik Department, Technische Universitat München, Garching bei München, Germany
| | - Fabio Vianello
- Department of Comparative Biomedicine and Food Science, University of Padova, Legnaro, Italy
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31
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Zhu J, Wang B, Zhang Y, Wei T, Gao T. Living electrochemical biosensing: Engineered electroactive bacteria for biosensor development and the emerging trends. Biosens Bioelectron 2023; 237:115480. [PMID: 37379794 DOI: 10.1016/j.bios.2023.115480] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2023] [Revised: 05/30/2023] [Accepted: 06/14/2023] [Indexed: 06/30/2023]
Abstract
Bioelectrical interfaces made of living electroactive bacteria (EAB) provide a unique opportunity to bridge biotic and abiotic systems, enabling the reprogramming of electrochemical biosensing. To develop these biosensors, principles from synthetic biology and electrode materials are being combined to engineer EAB as dynamic and responsive transducers with emerging, programmable functionalities. This review discusses the bioengineering of EAB to design active sensing parts and electrically connective interfaces on electrodes, which can be applied to construct smart electrochemical biosensors. In detail, by revisiting the electron transfer mechanism of electroactive microorganisms, engineering strategies of EAB cells for biotargets recognition, sensing circuit construction, and electrical signal routing, engineered EAB have demonstrated impressive capabilities in designing active sensing elements and developing electrically conductive interfaces on electrodes. Thus, integration of engineered EAB into electrochemical biosensors presents a promising avenue for advancing bioelectronics research. These hybridized systems equipped with engineered EAB can promote the field of electrochemical biosensing, with applications in environmental monitoring, health monitoring, green manufacturing, and other analytical fields. Finally, this review considers the prospects and challenges of the development of EAB-based electrochemical biosensors, identifying potential future applications.
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Affiliation(s)
- Jin Zhu
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, PR China
| | - Baoguo Wang
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, PR China
| | - Yixin Zhang
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, PR China
| | - Tianxiang Wei
- School of Environment, Nanjing Normal University, Nanjing, 210023, PR China
| | - Tao Gao
- Jiangsu Key Laboratory for Molecular and Medical Biotechnology, College of Life Sciences, Nanjing Normal University, Nanjing, 210023, PR China.
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32
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Lebovich M, Zeng M, Andrews LB. Algorithmic Programming of Sequential Logic and Genetic Circuits for Recording Biochemical Concentration in a Probiotic Bacterium. ACS Synth Biol 2023; 12:2632-2649. [PMID: 37581922 PMCID: PMC10510703 DOI: 10.1021/acssynbio.3c00232] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/14/2023] [Indexed: 08/16/2023]
Abstract
Through the implementation of designable genetic circuits, engineered probiotic microorganisms could be used as noninvasive diagnostic tools for the gastrointestinal tract. For these living cells to report detected biomarkers or signals after exiting the gut, the genetic circuits must be able to record these signals by using genetically encoded memory. Complex memory register circuits could enable multiplex interrogation of biomarkers and signals. A theory-based approach to create genetic circuits containing memory, known as sequential logic circuits, was previously established for a model laboratory strain of Escherichia coli, yet how circuit component performance varies for nonmodel and clinically relevant bacterial strains is poorly understood. Here, we develop a scalable computational approach to design robust sequential logic circuits in probiotic strain Escherichia coli Nissle 1917 (EcN). In this work, we used TetR-family transcriptional repressors to build genetic logic gates that can be composed into sequential logic circuits, along with a set of engineered sensors relevant for use in the gut environment. Using standard methods, 16 genetic NOT gates and nine sensors were experimentally characterized in EcN. These data were used to design and predict the performance of circuit designs. We present a set of genetic circuits encoding both combinational logic and sequential logic and show that the circuit outputs are in close agreement with our quantitative predictions from the design algorithm. Furthermore, we demonstrate an analog-like concentration recording circuit that detects and reports three input concentration ranges of a biochemical signal using sequential logic.
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Affiliation(s)
- Matthew Lebovich
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
- Biotechnology
Training Program, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Min Zeng
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Lauren B. Andrews
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
- Biotechnology
Training Program, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
- Molecular
and Cellular Biology Graduate Program, University
of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
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Velazquez Sanchez AK, Klopprogge B, Zimmermann KH, Ignatova Z. Tailored Synthetic sRNAs Dynamically Tune Multilayer Genetic Circuits. ACS Synth Biol 2023; 12:2524-2535. [PMID: 37595156 DOI: 10.1021/acssynbio.2c00614] [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: 08/20/2023]
Abstract
Predictable and controllable tuning of genetic circuits to regulate gene expression, including modulation of existing circuits or constructs without the need for redesign or rebuilding, is a persistent challenge in synthetic biology. Here, we propose rationally designed new small RNAs (sRNAs) that dynamically modulate gene expression of genetic circuits with a broad range (high, medium, and low) of repression. We designed multiple multilayer genetic circuits in which the variable effector element is a transcription factor (TF) controlling downstream the production of a reporter protein. The sRNAs target TFs instead of a reporter gene, and harnessing the intrinsic RNA-interference pathway in E. coli allowed for a wide range of expression modulation of the reporter protein, including the most difficult to achieve dynamic switch to an OFF state. The synthetic sRNAs are expressed independently of the circuit(s), thus allowing for repression without modifying the circuit itself. Our work provides a frame for achieving independent modulation of gene expression and dynamic and modular control of the multilayer genetic circuits by only including an independent control circuit expressing synthetic sRNAs, without altering the structure of existing genetic circuits.
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Affiliation(s)
- Ana K Velazquez Sanchez
- Biochemistry and Molecular Biology, Department of Chemistry, University of Hamburg, 20146 Hamburg, Germany
| | - Bjarne Klopprogge
- Biochemistry and Molecular Biology, Department of Chemistry, University of Hamburg, 20146 Hamburg, Germany
| | - Karl-Heinz Zimmermann
- Algebraic Engineering, Institute of Embedded Systems, Hamburg University of Technology, 21073 Hamburg, Germany
| | - Zoya Ignatova
- Biochemistry and Molecular Biology, Department of Chemistry, University of Hamburg, 20146 Hamburg, Germany
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Wang Y, Demirer GS. Synthetic biology for plant genetic engineering and molecular farming. Trends Biotechnol 2023; 41:1182-1198. [PMID: 37012119 DOI: 10.1016/j.tibtech.2023.03.007] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/12/2023] [Revised: 03/03/2023] [Accepted: 03/09/2023] [Indexed: 04/03/2023]
Abstract
Many efforts have been put into engineering plants to improve crop yields and stress tolerance and boost the bioproduction of valuable molecules. Yet, our capabilities are still limited due to the lack of well-characterized genetic building blocks and resources for precise manipulation and given the inherently challenging properties of plant tissues. Advancements in plant synthetic biology can overcome these bottlenecks and release the full potential of engineered plants. In this review, we first discuss the recently developed plant synthetic elements from single parts to advanced circuits, software, and hardware tools expediting the engineering cycle. Next, we survey the advancements in plant biotechnology enabled by these recent resources. We conclude the review with outstanding challenges and future directions of plant synthetic biology.
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Affiliation(s)
- Yunqing Wang
- Department of Bioengineering, California Institute of Technology, Pasadena, CA 91125, USA
| | - Gozde S Demirer
- Department of Chemical Engineering, California Institute of Technology, Pasadena, CA 91125, USA.
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Bragdon MDJ, Patel N, Chuang J, Levien E, Bashor CJ, Khalil AS. Cooperative assembly confers regulatory specificity and long-term genetic circuit stability. Cell 2023; 186:3810-3825.e18. [PMID: 37552983 PMCID: PMC10528910 DOI: 10.1016/j.cell.2023.07.012] [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: 05/16/2022] [Revised: 05/17/2023] [Accepted: 07/10/2023] [Indexed: 08/10/2023]
Abstract
A ubiquitous feature of eukaryotic transcriptional regulation is cooperative self-assembly between transcription factors (TFs) and DNA cis-regulatory motifs. It is thought that this strategy enables specific regulatory connections to be formed in gene networks between otherwise weakly interacting, low-specificity molecular components. Here, using synthetic gene circuits constructed in yeast, we find that high regulatory specificity can emerge from cooperative, multivalent interactions among artificial zinc-finger-based TFs. We show that circuits "wired" using the strategy of cooperative TF assembly are effectively insulated from aberrant misregulation of the host cell genome. As we demonstrate in experiments and mathematical models, this mechanism is sufficient to rescue circuit-driven fitness defects, resulting in genetic and functional stability of circuits in long-term continuous culture. Our naturally inspired approach offers a simple, generalizable means for building high-fidelity, evolutionarily robust gene circuits that can be scaled to a wide range of host organisms and applications.
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Affiliation(s)
- Meghan D J Bragdon
- Biological Design Center, Boston University, Boston, MA 02215, USA; Program in Molecular Biology, Cell Biology and Biochemistry, Boston University, Boston, MA 02215, USA
| | - Nikit Patel
- Biological Design Center, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA
| | - James Chuang
- Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Department of Genetics, Harvard Medical School, Boston, MA 02115, USA
| | - Ethan Levien
- Department of Mathematics, Dartmouth College, Hanover, NH 03755, USA
| | - Caleb J Bashor
- Department of Bioengineering, Rice University, Houston, TX 77030, USA; Department of Biosciences, Rice University, Houston, TX 77030, USA
| | - Ahmad S Khalil
- Biological Design Center, Boston University, Boston, MA 02215, USA; Program in Molecular Biology, Cell Biology and Biochemistry, Boston University, Boston, MA 02215, USA; Department of Biomedical Engineering, Boston University, Boston, MA 02215, USA; Wyss Institute for Biologically Inspired Engineering, Harvard University, Boston, MA 02115, USA.
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36
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Moy MA, Collins-McMillen D, Crawford L, Parkins C, Zeltzer S, Caviness K, Zaidi SSA, Caposio P, Goodrum F. Stabilization of the human cytomegalovirus UL136p33 reactivation determinant overcomes the requirement for UL135 for replication in hematopoietic cells. J Virol 2023; 97:e0014823. [PMID: 37565749 PMCID: PMC10506481 DOI: 10.1128/jvi.00148-23] [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: 01/25/2023] [Accepted: 06/20/2023] [Indexed: 08/12/2023] Open
Abstract
Human cytomegalovirus (HCMV) is a beta herpesvirus that persists indefinitely in the human host through a latent infection. The polycistronic UL133-UL138 gene locus of HCMV encodes genes regulating latency and reactivation. While UL138 is pro-latency, restricting virus replication in CD34+ hematopoietic progenitor cells (HPCs), UL135 overcomes this restriction and is required for reactivation. By contrast, UL136 is expressed with later kinetics and encodes multiple proteins with differential roles in latency and reactivation. Like UL135, the largest UL136 isoform, UL136p33, is required for reactivation from latency in HPCs; viruses failing to express either protein are unresponsive to reactivation stimuli. Furthermore, UL136p33 is unstable, and its instability is important for the establishment of latency, and sufficient accumulation of UL136p33 is a checkpoint for reactivation. We hypothesized that stabilizing UL136p33 might overcome the requirement of UL135 for replication. We generated recombinant viruses lacking UL135 that expressed a stabilized variant of UL136p33. Stabilizing UL136p33 did not impact the replication of the UL135 mutant virus in fibroblasts. However, in the context of infection in HPCs, stabilization of UL136p33 strikingly compensated for the loss of UL135, resulting in increased replication in CD34+ HPCs and in humanized NOD-scid IL2Rγcnull (huNSG) mice. This finding suggests that while UL135 is essential for replication in HPCs, it functions largely at steps preceding the accumulation of UL136p33, and that stabilized expression of UL136p33 largely overcomes the requirement for UL135. Taken together, our genetic evidence indicates an epistatic relationship between UL136p33 and UL135, whereby UL135 may initiate events early in reactivation that drive the accumulation of UL136p33 to a threshold required for productive reactivation. IMPORTANCE Human cytomegalovirus (HCMV) is one of nine human herpesviruses and a significant human pathogen. While HCMV establishes a lifelong latent infection that is typically asymptomatic in healthy individuals, its reactivation from latency can have devastating consequences in the immunocompromised. Defining viral genes important in the establishment of or reactivation from latency is important to defining the molecular basis of latent and replicative states and in controlling infection and CMV disease. Here we define a genetic relationship between two viral genes in controlling virus reactivation from latency using primary human hematopoietic progenitor cells and humanized mouse models.
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Affiliation(s)
- Melissa A. Moy
- Cancer Biology Graduate Interdisciplinary Program, University of Arizona, Tucson, Arizona, USA
- Department of Immunobiology, University of Arizona, Tucson, Arizona, USA
- BIO5 Institute, University of Arizona, Tucson, Arizona, USA
| | - Donna Collins-McMillen
- Department of Immunobiology, University of Arizona, Tucson, Arizona, USA
- BIO5 Institute, University of Arizona, Tucson, Arizona, USA
| | - Lindsey Crawford
- Vaccine and Gene Therapy Institute, Oregon Health and Science University, Beaverton, Oregon, USA
| | - Christopher Parkins
- Vaccine and Gene Therapy Institute, Oregon Health and Science University, Beaverton, Oregon, USA
| | - Sebastian Zeltzer
- Department of Immunobiology, University of Arizona, Tucson, Arizona, USA
- BIO5 Institute, University of Arizona, Tucson, Arizona, USA
| | - Katie Caviness
- Department of Immunobiology, University of Arizona, Tucson, Arizona, USA
- BIO5 Institute, University of Arizona, Tucson, Arizona, USA
- Graduate Interdisciplinary Program in Genetics, University of Arizona, Tucson, Arizona, USA
| | | | - Patrizia Caposio
- Vaccine and Gene Therapy Institute, Oregon Health and Science University, Beaverton, Oregon, USA
| | - Felicia Goodrum
- Cancer Biology Graduate Interdisciplinary Program, University of Arizona, Tucson, Arizona, USA
- Department of Immunobiology, University of Arizona, Tucson, Arizona, USA
- BIO5 Institute, University of Arizona, Tucson, Arizona, USA
- Graduate Interdisciplinary Program in Genetics, University of Arizona, Tucson, Arizona, USA
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Gao Y, Zhou Y, Ji X, Graham AJ, Dundas CM, Mahfoud IEM, Tibbett BM, Tan B, Partipilo G, Dodabalapur A, Rivnay J, Keitz BK. A Hybrid Transistor with Transcriptionally Controlled Computation and Plasticity. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.08.16.553547. [PMID: 37645977 PMCID: PMC10462107 DOI: 10.1101/2023.08.16.553547] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/31/2023]
Abstract
Organic electrochemical transistors (OECTs) are ideal devices for translating biological signals into electrical readouts and have applications in bioelectronics, biosensing, and neuromorphic computing. Despite their potential, developing programmable and modular methods for living systems to interface with OECTs has proven challenging. Here we describe hybrid OECTs containing the model electroactive bacterium Shewanella oneidensis that enable the transduction of biological computations to electrical responses. Specifically, we fabricated planar p-type OECTs and demonstrated that channel de-doping is driven by extracellular electron transfer (EET) from S. oneidensis. Leveraging this mechanistic understanding and our ability to control EET flux via transcriptional regulation, we used plasmid-based Boolean logic gates to translate biological computation into current changes within the OECT. Finally, we demonstrated EET-driven changes to OECT synaptic plasticity. This work enables fundamental EET studies and OECT-based biosensing and biocomputing systems with genetically controllable and modular design elements.
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Affiliation(s)
- Yang Gao
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Yuchen Zhou
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
- Microelectronics Research Center, The University of Texas at Austin, Austin, TX, 78758, USA
| | - Xudong Ji
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Simpson Querrey Institute, Northwestern University, Chicago, IL, 60611, USA
| | - Austin J. Graham
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Pharmaceutical Chemistry, University of California San Francisco, San Francisco, CA, 94158, USA
| | - Christopher M. Dundas
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
- Department of Biology, Stanford University, Stanford, CA 94305, USA
| | - Ismar E. Miniel Mahfoud
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Bailey M. Tibbett
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Benjamin Tan
- Microelectronics Research Center, The University of Texas at Austin, Austin, TX, 78758, USA
- Department of Chemistry, University of Texas at Austin, Austin, TX, 78712, USA
| | - Gina Partipilo
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
| | - Ananth Dodabalapur
- Department of Electrical and Computer Engineering, The University of Texas at Austin, Austin, TX, 78712, USA
- Microelectronics Research Center, The University of Texas at Austin, Austin, TX, 78758, USA
| | - Jonathan Rivnay
- Department of Biomedical Engineering, Northwestern University, Evanston, IL, 60208, USA
- Simpson Querrey Institute, Northwestern University, Chicago, IL, 60611, USA
| | - Benjamin K. Keitz
- McKetta Department of Chemical Engineering, University of Texas at Austin, Austin, TX, 78712, USA
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Nasr MA, Martin VJJ, Kwan DH. Divergent directed evolution of a TetR-type repressor towards aromatic molecules. Nucleic Acids Res 2023; 51:7675-7690. [PMID: 37377432 PMCID: PMC10415137 DOI: 10.1093/nar/gkad503] [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: 10/13/2022] [Revised: 05/18/2023] [Accepted: 06/25/2023] [Indexed: 06/29/2023] Open
Abstract
Reprogramming cellular behaviour is one of the hallmarks of synthetic biology. To this end, prokaryotic allosteric transcription factors (aTF) have been repurposed as versatile tools for processing small molecule signals into cellular responses. Expanding the toolbox of aTFs that recognize new inducer molecules is of considerable interest in many applications. Here, we first establish a resorcinol responsive aTF-based biosensor in Escherichia coli using the TetR-family repressor RolR from Corynebacterium glutamicum. We then perform an iterative walk along the fitness landscape of RolR to identify new inducer specificities, namely catechol, methyl catechol, caffeic acid, protocatechuate, L-DOPA, and the tumour biomarker homovanillic acid. Finally, we demonstrate the versatility of these engineered aTFs by transplanting them into the model eukaryote Saccharomyces cerevisiae. This work provides a framework for efficient aTF engineering to expand ligand specificity towards novel molecules on laboratory timescales, which, more broadly, is invaluable across a wide range of applications such as protein and metabolic engineering, as well as point-of-care diagnostics.
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Affiliation(s)
- Mohamed A Nasr
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Québec, Canada
- Department of Biology, Concordia University, Montréal, Québec, Canada
- PROTEO, Québec Network for Research on Protein Function, Structure, and Engineering, Québec City, Québec, Canada
| | - Vincent J J Martin
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Québec, Canada
- Department of Biology, Concordia University, Montréal, Québec, Canada
| | - David H Kwan
- Centre for Applied Synthetic Biology, Concordia University, Montréal, Québec, Canada
- Department of Biology, Concordia University, Montréal, Québec, Canada
- Department of Chemistry and Biochemistry, Concordia University, Montréal, Québec, Canada
- PROTEO, Québec Network for Research on Protein Function, Structure, and Engineering, Québec City, Québec, Canada
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Alba Burbano D, Cardiff RAL, Tickman BI, Kiattisewee C, Maranas CJ, Zalatan JG, Carothers JM. Engineering activatable promoters for scalable and multi-input CRISPRa/i circuits. Proc Natl Acad Sci U S A 2023; 120:e2220358120. [PMID: 37463216 PMCID: PMC10374173 DOI: 10.1073/pnas.2220358120] [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] [Received: 11/30/2022] [Accepted: 06/13/2023] [Indexed: 07/20/2023] Open
Abstract
Dynamic, multi-input gene regulatory networks (GRNs) are ubiquitous in nature. Multilayer CRISPR-based genetic circuits hold great promise for building GRNs akin to those found in naturally occurring biological systems. We develop an approach for creating high-performing activatable promoters that can be assembled into deep, wide, and multi-input CRISPR-activation and -interference (CRISPRa/i) GRNs. By integrating sequence-based design and in vivo screening, we engineer activatable promoters that achieve up to 1,000-fold dynamic range in an Escherichia coli-based cell-free system. These components enable CRISPRa GRNs that are six layers deep and four branches wide. We show the generalizability of the promoter engineering workflow by improving the dynamic range of the light-dependent EL222 optogenetic system from 6-fold to 34-fold. Additionally, high dynamic range promoters enable CRISPRa systems mediated by small molecules and protein-protein interactions. We apply these tools to build input-responsive CRISPRa/i GRNs, including feedback loops, logic gates, multilayer cascades, and dynamic pulse modulators. Our work provides a generalizable approach for the design of high dynamic range activatable promoters and enables classes of gene regulatory functions in cell-free systems.
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Affiliation(s)
- Diego Alba Burbano
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
| | - Ryan A. L. Cardiff
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Benjamin I. Tickman
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cholpisit Kiattisewee
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Cassandra J. Maranas
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
| | - Jesse G. Zalatan
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
- Department of Chemistry, University of Washington, Seattle, WA98195
| | - James M. Carothers
- Department of Chemical Engineering, University of Washington, Seattle, WA98195
- Center for Synthetic Biology, University of Washington, Seattle, WA98195
- Molecular Engineering & Sciences Institute, University of Washington, Seattle, WA98195
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40
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Kocaoglan EG, Radhakrishnan D, Nakayama N. Synthetic developmental biology: molecular tools to re-design plant shoots and roots. JOURNAL OF EXPERIMENTAL BOTANY 2023; 74:3864-3876. [PMID: 37155965 PMCID: PMC10826796 DOI: 10.1093/jxb/erad169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 05/04/2023] [Indexed: 05/10/2023]
Abstract
Plant morphology and anatomy strongly influence agricultural yield. Crop domestication has strived for desirable growth and developmental traits, such as larger and more fruits and semi-dwarf architecture. Genetic engineering has accelerated rational, purpose-driven engineering of plant development, but it can be unpredictable. Developmental pathways are complex and riddled with environmental and hormonal inputs, as well as feedback and feedforward interactions, which occur at specific times and places in a growing multicellular organism. Rational modification of plant development would probably benefit from precision engineering based on synthetic biology approaches. This review outlines recently developed synthetic biology technologies for plant systems and highlights their potential for engineering plant growth and development. Streamlined and high-capacity genetic construction methods (Golden Gate DNA Assembly frameworks and toolkits) allow fast and variation-series cloning of multigene transgene constructs. This, together with a suite of gene regulation tools (e.g. cell type-specific promoters, logic gates, and multiplex regulation systems), is starting to enable developmental pathway engineering with predictable outcomes in model plant and crop species.
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Affiliation(s)
- Elif Gediz Kocaoglan
- Department of Bioengineering, Centre for Synthetic Biology, Imperial College London, London SW7 2AZ, UK
| | - Dhanya Radhakrishnan
- Department of Bioengineering, Centre for Synthetic Biology, Imperial College London, London SW7 2AZ, UK
| | - Naomi Nakayama
- Department of Bioengineering, Centre for Synthetic Biology, Imperial College London, London SW7 2AZ, UK
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Gligorovski V, Sadeghi A, Rahi SJ. Multidimensional characterization of inducible promoters and a highly light-sensitive LOV-transcription factor. Nat Commun 2023; 14:3810. [PMID: 37369667 DOI: 10.1038/s41467-023-38959-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/01/2021] [Accepted: 05/24/2023] [Indexed: 06/29/2023] Open
Abstract
The ability to independently control the expression of different genes is important for quantitative biology. Using budding yeast, we characterize GAL1pr, GALL, MET3pr, CUP1pr, PHO5pr, tetOpr, terminator-tetOpr, Z3EV, blue-light inducible optogenetic systems El222-LIP, El222-GLIP, and red-light inducible PhyB-PIF3. We report kinetic parameters, noise scaling, impact on growth, and the fundamental leakiness of each system using an intuitive unit, maxGAL1. We uncover disadvantages of widely used tools, e.g., nonmonotonic activity of MET3pr and GALL, slow off kinetics of the doxycycline- and estradiol-inducible systems tetOpr and Z3EV, and high variability of PHO5pr and red-light activated PhyB-PIF3 system. We introduce two previously uncharacterized systems: strongLOV, a more light-sensitive El222 mutant, and ARG3pr, which is induced in the absence of arginine or presence of methionine. To demonstrate fine control over gene circuits, we experimentally tune the time between cell cycle Start and mitosis, artificially simulating near-wild-type timing. All strains, constructs, code, and data ( https://promoter-benchmark.epfl.ch/ ) are made available.
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Affiliation(s)
- Vojislav Gligorovski
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Ahmad Sadeghi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland
| | - Sahand Jamal Rahi
- Laboratory of the Physics of Biological Systems, Institute of Physics, École polytechnique fédérale de Lausanne (EPFL), Lausanne, Switzerland.
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42
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Merzbacher C, Mac Aodha O, Oyarzún DA. Bayesian Optimization for Design of Multiscale Biological Circuits. ACS Synth Biol 2023. [PMID: 37339382 PMCID: PMC10367132 DOI: 10.1021/acssynbio.3c00120] [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: 06/22/2023]
Abstract
Recent advances in synthetic biology have enabled the construction of molecular circuits that operate across multiple scales of cellular organization, such as gene regulation, signaling pathways, and cellular metabolism. Computational optimization can effectively aid the design process, but current methods are generally unsuited for systems with multiple temporal or concentration scales, as these are slow to simulate due to their numerical stiffness. Here, we present a machine learning method for the efficient optimization of biological circuits across scales. The method relies on Bayesian optimization, a technique commonly used to fine-tune deep neural networks, to learn the shape of a performance landscape and iteratively navigate the design space toward an optimal circuit. This strategy allows the joint optimization of both circuit architecture and parameters, and provides a feasible approach to solve a highly nonconvex optimization problem in a mixed-integer input space. We illustrate the applicability of the method on several gene circuits for controlling biosynthetic pathways with strong nonlinearities, multiple interacting scales, and using various performance objectives. The method efficiently handles large multiscale problems and enables parametric sweeps to assess circuit robustness to perturbations, serving as an efficient in silico screening method prior to experimental implementation.
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Affiliation(s)
| | - Oisin Mac Aodha
- School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K
- The Alan Turing Institute, London NW1 2DB, U.K
| | - Diego A Oyarzún
- School of Informatics, University of Edinburgh, Edinburgh EH8 9AB, U.K
- The Alan Turing Institute, London NW1 2DB, U.K
- School of Biological Sciences, University of Edinburgh, Edinburgh EH9 3JH, U.K
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43
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Alexandari AM, Horton CA, Shrikumar A, Shah N, Li E, Weilert M, Pufall MA, Zeitlinger J, Fordyce PM, Kundaje A. De novo distillation of thermodynamic affinity from deep learning regulatory sequence models of in vivo protein-DNA binding. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.05.11.540401. [PMID: 37214836 PMCID: PMC10197627 DOI: 10.1101/2023.05.11.540401] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/24/2023]
Abstract
Transcription factors (TF) are proteins that bind DNA in a sequence-specific manner to regulate gene transcription. Despite their unique intrinsic sequence preferences, in vivo genomic occupancy profiles of TFs differ across cellular contexts. Hence, deciphering the sequence determinants of TF binding, both intrinsic and context-specific, is essential to understand gene regulation and the impact of regulatory, non-coding genetic variation. Biophysical models trained on in vitro TF binding assays can estimate intrinsic affinity landscapes and predict occupancy based on TF concentration and affinity. However, these models cannot adequately explain context-specific, in vivo binding profiles. Conversely, deep learning models, trained on in vivo TF binding assays, effectively predict and explain genomic occupancy profiles as a function of complex regulatory sequence syntax, albeit without a clear biophysical interpretation. To reconcile these complementary models of in vitro and in vivo TF binding, we developed Affinity Distillation (AD), a method that extracts thermodynamic affinities de-novo from deep learning models of TF chromatin immunoprecipitation (ChIP) experiments by marginalizing away the influence of genomic sequence context. Applied to neural networks modeling diverse classes of yeast and mammalian TFs, AD predicts energetic impacts of sequence variation within and surrounding motifs on TF binding as measured by diverse in vitro assays with superior dynamic range and accuracy compared to motif-based methods. Furthermore, AD can accurately discern affinities of TF paralogs. Our results highlight thermodynamic affinity as a key determinant of in vivo binding, suggest that deep learning models of in vivo binding implicitly learn high-resolution affinity landscapes, and show that these affinities can be successfully distilled using AD. This new biophysical interpretation of deep learning models enables high-throughput in silico experiments to explore the influence of sequence context and variation on both intrinsic affinity and in vivo occupancy.
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Affiliation(s)
- Amr M. Alexandari
- Department of Computer Science, Stanford University, Stanford, CA 94305
| | | | - Avanti Shrikumar
- Department of Earth System Science, Stanford University, Stanford, CA 94305
| | - Nilay Shah
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Eileen Li
- Department of Genetics, Stanford University, Stanford, CA 94305
| | - Melanie Weilert
- Stowers Institute for Medical Research, Kansas City, MO, USA
| | - Miles A. Pufall
- Department of Biochemistry, Carver College of Medicine, University of Iowa, Iowa City, Iowa 52242, USA
| | - Julia Zeitlinger
- Stowers Institute for Medical Research, Kansas City, MO, USA
- The University of Kansas Medical Center, Kansas City, KS, USA
| | - Polly M. Fordyce
- Department of Genetics, Stanford University, Stanford, CA 94305
- Department of Bioengineering, Stanford University, Stanford, CA 94305
- ChEM-H Institute, Stanford University, Stanford, CA 94305
- Chan Zuckerberg Biohub, San Francisco, CA 94110
| | - Anshul Kundaje
- Department of Computer Science, Stanford University, Stanford, CA 94305
- Department of Genetics, Stanford University, Stanford, CA 94305
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Wang N, Peng H, Yang C, Guo W, Wang M, Li G, Liu D. Metabolic Engineering of Model Microorganisms for the Production of Xanthophyll. Microorganisms 2023; 11:1252. [PMID: 37317226 DOI: 10.3390/microorganisms11051252] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/06/2023] [Revised: 04/19/2023] [Accepted: 05/06/2023] [Indexed: 06/16/2023] Open
Abstract
Xanthophyll is an oxidated version of carotenoid. It presents significant value to the pharmaceutical, food, and cosmetic industries due to its specific antioxidant activity and variety of colors. Chemical processing and conventional extraction from natural organisms are still the main sources of xanthophyll. However, the current industrial production model can no longer meet the demand for human health care, reducing petrochemical energy consumption and green sustainable development. With the swift development of genetic metabolic engineering, xanthophyll synthesis by the metabolic engineering of model microorganisms shows great application potential. At present, compared to carotenes such as lycopene and β-carotene, xanthophyll has a relatively low production in engineering microorganisms due to its stronger inherent antioxidation, relatively high polarity, and longer metabolic pathway. This review comprehensively summarized the progress in xanthophyll synthesis by the metabolic engineering of model microorganisms, described strategies to improve xanthophyll production in detail, and proposed the current challenges and future efforts needed to build commercialized xanthophyll-producing microorganisms.
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Affiliation(s)
- Nan Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Huakang Peng
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Caifeng Yang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Wenfang Guo
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Mengqi Wang
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Gangqiang Li
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
| | - Dehu Liu
- Biotechnology Research Institute, Chinese Academy of Agricultural Sciences, Beijing 100081, China
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45
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Surrett ED, Guckes KR, Cousins S, Ruskoski TB, Cecere AG, Ludvik DA, Okafor CD, Mandel MJ, Miyashiro TI. Two enhancer binding proteins activate σ 54-dependent transcription of a quorum regulatory RNA in a bacterial symbiont. eLife 2023; 12:e78544. [PMID: 37145113 PMCID: PMC10162802 DOI: 10.7554/elife.78544] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/10/2022] [Accepted: 04/20/2023] [Indexed: 05/06/2023] Open
Abstract
To colonize a host, bacteria depend on an ensemble of signaling systems to convert information about the various environments encountered within the host into specific cellular activities. How these signaling systems coordinate transitions between cellular states in vivo remains poorly understood. To address this knowledge gap, we investigated how the bacterial symbiont Vibrio fischeri initially colonizes the light organ of the Hawaiian bobtail squid Euprymna scolopes. Previous work has shown that the small RNA Qrr1, which is a regulatory component of the quorum-sensing system in V. fischeri, promotes host colonization. Here, we report that transcriptional activation of Qrr1 is inhibited by the sensor kinase BinK, which suppresses cellular aggregation by V. fischeri prior to light organ entry. We show that Qrr1 expression depends on the alternative sigma factor σ54 and the transcription factors LuxO and SypG, which function similar to an OR logic gate, thereby ensuring Qrr1 is expressed during colonization. Finally, we provide evidence that this regulatory mechanism is widespread throughout the Vibrionaceae family. Together, our work reveals how coordination between the signaling pathways underlying aggregation and quorum-sensing promotes host colonization, which provides insight into how integration among signaling systems facilitates complex processes in bacteria.
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Affiliation(s)
- Ericka D Surrett
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
| | - Kirsten R Guckes
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
| | - Shyan Cousins
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
| | - Terry B Ruskoski
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
| | - Andrew G Cecere
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
| | - Denise A Ludvik
- Department of Medical Microbiology and Immunology, University of Wisconsin-MadisonMadisonUnited States
| | - C Denise Okafor
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
- Department of Chemistry, Pennsylvania State UniversityUniversity ParkUnited States
| | - Mark J Mandel
- Department of Medical Microbiology and Immunology, University of Wisconsin-MadisonMadisonUnited States
| | - Tim I Miyashiro
- Department of Biochemistry and Molecular Biology, Pennsylvania State UniversityUniversity ParkUnited States
- The Microbiome Center, Huck Institutes of the Life Sciences, Pennsylvania State UniversityUniversity ParkUnited States
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46
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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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47
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Liu L, Huang Y, Wang HH. Fast and efficient template-mediated synthesis of genetic variants. Nat Methods 2023:10.1038/s41592-023-01868-1. [PMID: 37127666 DOI: 10.1038/s41592-023-01868-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/18/2022] [Accepted: 03/29/2023] [Indexed: 05/03/2023]
Abstract
Efficient methods for the generation of specific mutations enable the study of functional variations in natural populations and lead to advances in genetic engineering applications. Here, we present a new approach, mutagenesis by template-guided amplicon assembly (MEGAA), for the rapid construction of kilobase-sized DNA variants. With this method, many mutations can be generated at a time to a DNA template at more than 90% efficiency per target in a predictable manner. We devised a robust and iterative protocol for an open-source laboratory automation robot that enables desktop production and long-read sequencing validation of variants. Using this system, we demonstrated the construction of 31 natural SARS-CoV2 spike gene variants and 10 recoded Escherichia coli genome fragments, with each 4 kb region containing up to 150 mutations. Furthermore, 125 defined combinatorial adeno-associated virus-2 cap gene variants were easily built using the system, which exhibited viral packaging enhancements of up to 10-fold compared with wild type. Thus, the MEGAA platform enables generation of multi-site sequence variants quickly, cheaply, and in a scalable manner for diverse applications in biotechnology.
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Affiliation(s)
- Liyuan Liu
- Department of Systems Biology, Columbia University, New York, NY, USA
| | - Yiming Huang
- Department of Systems Biology, Columbia University, New York, NY, USA
- Integrated Program in Cellular, Molecular, and Biomedical Studies, Columbia University, New York, NY, USA
| | - Harris H Wang
- Department of Systems Biology, Columbia University, New York, NY, USA.
- Department of Pathology and Cell Biology, Columbia University, New York, NY, USA.
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48
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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: 20] [Impact Index Per Article: 20.0] [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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Sharon JA, Dasrath C, Fujiwara A, Snyder A, Blank M, O'Brien S, Aufdembrink LM, Engelhart AE, Adamala KP. Trumpet is an operating system for simple and robust cell-free biocomputing. Nat Commun 2023; 14:2257. [PMID: 37080970 PMCID: PMC10119096 DOI: 10.1038/s41467-023-37752-x] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/08/2022] [Accepted: 03/30/2023] [Indexed: 04/22/2023] Open
Abstract
Biological computation is becoming a viable and fast-growing alternative to traditional electronic computing. Here we present a biocomputing technology called Trumpet: Transcriptional RNA Universal Multi-Purpose GatE PlaTform. Trumpet combines the simplicity and robustness of the simplest in vitro biocomputing methods, adding signal amplification and programmability, while avoiding common shortcomings of live cell-based biocomputing solutions. We have demonstrated the use of Trumpet to build all universal Boolean logic gates. We have also built a web-based platform for designing Trumpet gates and created a primitive processor by networking several gates as a proof-of-principle for future development. The Trumpet offers a change of paradigm in biocomputing, providing an efficient and easily programmable biological logic gate operating system.
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Affiliation(s)
- Judee A Sharon
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Chelsea Dasrath
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Aiden Fujiwara
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Alessandro Snyder
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Mace Blank
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Sam O'Brien
- Department of Computer Science, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Lauren M Aufdembrink
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Aaron E Engelhart
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA
| | - Katarzyna P Adamala
- Department of Genetics, Cellular Biology, and Development, University of Minnesota, Twin Cities, Minneapolis, MN, USA.
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50
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Mahdavi S, Salmon GL, Daghlian P, Garcia HG, Phillips R. Flexibility and sensitivity in gene regulation out of equilibrium. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.04.11.536490. [PMID: 37090612 PMCID: PMC10120662 DOI: 10.1101/2023.04.11.536490] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/25/2023]
Abstract
Cells adapt to environments and tune gene expression by controlling the concentrations of proteins and their kinetics in regulatory networks. In both eukaryotes and prokaryotes, experiments and theory increasingly attest that these networks can and do consume bio-chemical energy. How does this dissipation enable cellular behaviors unobtainable in equilibrium? This open question demands quantitative models that transcend thermodynamic equilibrium. Here we study the control of a simple, ubiquitous gene regulatory motif to explore the consequences of departing equilibrium in kinetic cycles. Employing graph theory, we find that dissipation unlocks nonmonotonicity and enhanced sensitivity of gene expression with respect to a transcription factor's concentration. These features allow a single transcription factor to act as both a repressor and activator at different levels or achieve outputs with multiple concentration regions of locally-enhanced sensitivity. We systematically dissect how energetically-driving individual transitions within regulatory networks, or pairs of transitions, generates more adjustable and sensitive phenotypic responses. Our findings quantify necessary conditions and detectable consequences of energy expenditure. These richer mathematical behaviors-feasibly accessed using biological energy budgets and rates-may empower cells to accomplish sophisticated regulation with simpler architectures than those required at equilibrium. Significance Statement Growing theoretical and experimental evidence demonstrates that cells can (and do) spend biochemical energy while regulating their genes. Here we explore the impact of departing from equilibrium in simple regulatory cycles, and learn that beyond increasing sensitivity, dissipation can unlock more flexible input-output behaviors that are otherwise forbidden without spending energy. These more complex behaviors could enable cells to perform more sophisticated functions using simpler systems than those needed at equilibrium.
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