1
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Pham C, Stogios PJ, Savchenko A, Mahadevan R. Design and Characterization of a Generalist Biosensor for Indole Derivatives. ACS Synth Biol 2024; 13:2246-2252. [PMID: 38875315 DOI: 10.1021/acssynbio.3c00736] [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: 06/16/2024]
Abstract
Transcription factor (TF)-based biosensors are useful synthetic biology tools for applications in a variety of areas of biotechnology. A major challenge of biosensor circuits is the limited repertoire of identified and well-characterized TFs for applications of interest, in addition to the challenge of optimizing selected biosensors. In this work, we implement the IclR family repressor TF TtgV from Pseudomonas putida DOT-T1E as an indole-derivative biosensor in Escherichia coli. We optimize the genetic circuit utilizing different components, providing insights into biosensor design and expanding on previous studies investigating this TF. We discover novel physiologically relevant ligands of TtgV, such as skatole. The broad specificity of TtgV makes it a useful target for directed evolution and protein engineering toward desired specificity. TtgV, as an indole-derivative biosensor, is a promising genetic component for the detection of compounds with biological activities relevant to health and the gut microbiome.
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Affiliation(s)
- Chester Pham
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
| | - Peter J Stogios
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
| | - Alexei Savchenko
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
- Department of Microbiology, Immunology and Infectious Diseases, University of Calgary, Calgary, Alberta T2N 1N4, Canada
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, Toronto, Ontario M5S 3H7, Canada
- The Institute of Biomedical Engineering, University of Toronto, Toronto, Ontario M5S 3H7, Canada
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2
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Verzino SJ, Priyev SA, Estrada VAS, Crowley GX, Rutkowski A, Lam AC, Nazginov ES, Kotemelo P, Bacelo A, Sukhram DT, Vázquez FX, Juárez JF. Expanding salivary biomarker detection by creating a synthetic neuraminic acid sensor via chimeragenesis. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2024:2024.06.13.598939. [PMID: 38915506 PMCID: PMC11195194 DOI: 10.1101/2024.06.13.598939] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/26/2024]
Abstract
Accurate and timely diagnosis of oral squamous cell carcinoma (OSCC) is crucial in preventing its progression to advanced stages with a poor prognosis. As such, the construction of sensors capable of detecting previously established disease biomarkers for the early and non-invasive diagnosis of this and many other conditions has enormous therapeutic potential. In this work, we apply synthetic biology techniques for the development of a whole-cell biosensor (WCB) that leverages the physiology of engineered bacteria in vivo to promote the expression of an observable effector upon detection of a soluble molecule. To this end, we have constructed a bacterial strain expressing a novel chimeric transcription factor (Sphnx) for the detection of N-acetylneuraminic acid (Neu5Ac), a salivary biomolecule correlated with the onset of OSCC. This WCB serves as the proof-of-concept of a platform that can eventually be applied to clinical screening panels for a multitude of oral and systemic medical conditions whose biomarkers are present in saliva.
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3
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O'Connor E, Micklefield J, Cai Y. Searching for the optimal microbial factory: high-throughput biosensors and analytical techniques for screening small molecules. Curr Opin Biotechnol 2024; 87:103125. [PMID: 38547587 DOI: 10.1016/j.copbio.2024.103125] [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: 01/18/2024] [Revised: 03/06/2024] [Accepted: 03/07/2024] [Indexed: 06/09/2024]
Abstract
High-throughput screening technologies have been lacking in comparison to the plethora of high-throughput genetic diversification techniques developed in biotechnology. This review explores the challenges and advancements in high-throughput screening for high-value natural products, focusing on the critical need to expand ligand targets for biosensors and increase the throughput of analytical techniques in screening microbial cell libraries for optimal strain performance. The engineering techniques to broaden the scope of ligands for biosensors, such as transcription factors, G protein-coupled receptors and riboswitches are discussed. On the other hand, integration of microfluidics with traditional analytical methods is explored, covering fluorescence-activated cell sorting, Raman-activated cell sorting and mass spectrometry, emphasising recent developments in maximising throughput.
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Affiliation(s)
- Eloise O'Connor
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK
| | - Jason Micklefield
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK
| | - Yizhi Cai
- Manchester Institute of Biotechnology, University of Manchester, 131 Princess Street, Manchester M1 7DN, UK.
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4
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Xi C, Diao J, Moon TS. Advances in ligand-specific biosensing for structurally similar molecules. Cell Syst 2023; 14:1024-1043. [PMID: 38128482 PMCID: PMC10751988 DOI: 10.1016/j.cels.2023.10.009] [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: 05/21/2023] [Revised: 08/23/2023] [Accepted: 10/19/2023] [Indexed: 12/23/2023]
Abstract
The specificity of biological systems makes it possible to develop biosensors targeting specific metabolites, toxins, and pollutants in complex medical or environmental samples without interference from structurally similar compounds. For the last two decades, great efforts have been devoted to creating proteins or nucleic acids with novel properties through synthetic biology strategies. Beyond augmenting biocatalytic activity, expanding target substrate scopes, and enhancing enzymes' enantioselectivity and stability, an increasing research area is the enhancement of molecular specificity for genetically encoded biosensors. Here, we summarize recent advances in the development of highly specific biosensor systems and their essential applications. First, we describe the rational design principles required to create libraries containing potential mutants with less promiscuity or better specificity. Next, we review the emerging high-throughput screening techniques to engineer biosensing specificity for the desired target. Finally, we examine the computer-aided evaluation and prediction methods to facilitate the construction of ligand-specific biosensors.
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Affiliation(s)
- Chenggang Xi
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Jinjin Diao
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA
| | - Tae Seok Moon
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO, USA; Division of Biology and Biomedical Sciences, Washington University in St. Louis, St. Louis, MO, USA.
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5
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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: 4] [Impact Index Per Article: 4.0] [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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6
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Li S, Li Z, Tan GY, Xin Z, Wang W. In vitro allosteric transcription factor-based biosensing. Trends Biotechnol 2023; 41:1080-1095. [PMID: 36967257 DOI: 10.1016/j.tibtech.2023.03.001] [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: 01/03/2023] [Revised: 02/15/2023] [Accepted: 03/01/2023] [Indexed: 06/18/2023]
Abstract
A biosensor is an analytical device that converts a biological response into a measurable output signal. Bacterial allosteric transcription factors (aTFs) have been utilized as a novel class of recognition elements for in vitro biosensing, which circumvents the limitations of aTF-based whole-cell biosensors (WCBs) and helps to meet the increasing requirement of small-molecule biosensors for diverse applications. In this review, we summarize the recent advances related to the configuration of aTF-based biosensors in vitro. Particularly, we evaluate the advantages of aTFs for in vitro biosensing and highlight their great potential for the establishment of robust and easy-to-implement biosensing strategies. We argue that key technical innovations and generalizable workflows will enhance the pipeline for facile construction of diverse aTF-based small-molecule biosensors.
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Affiliation(s)
- Shanshan Li
- State Key Laboratory for Biology of Plant Diseases and Insect Pests, Institute of Plant Protection, Chinese Academy of Agricultural Sciences, Beijing 100193, PR China
| | - Zilong Li
- State Key Laboratory of Microbial Resources, Institute of Microbiology, CAS, Beijing 100101, PR China
| | - Gao-Yi Tan
- State Key Laboratory of Bioreactor Engineering and School of Biotechnology, East China University of Science and Technology, Shanghai 200237, PR China
| | - Zhenguo Xin
- State Key Laboratory of Microbial Resources, Institute of Microbiology, CAS, Beijing 100101, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China
| | - Weishan Wang
- State Key Laboratory of Microbial Resources, Institute of Microbiology, CAS, Beijing 100101, PR China; University of Chinese Academy of Sciences, Beijing 100049, PR China.
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7
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Zhou GJ, Zhang F. Applications and Tuning Strategies for Transcription Factor-Based Metabolite Biosensors. BIOSENSORS 2023; 13:428. [PMID: 37185503 PMCID: PMC10136082 DOI: 10.3390/bios13040428] [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: 02/27/2023] [Revised: 03/24/2023] [Accepted: 03/27/2023] [Indexed: 05/17/2023]
Abstract
Transcription factor (TF)-based biosensors are widely used for the detection of metabolites and the regulation of cellular pathways in response to metabolites. Several challenges hinder the direct application of TF-based sensors to new hosts or metabolic pathways, which often requires extensive tuning to achieve the optimal performance. These tuning strategies can involve transcriptional or translational control depending on the parameter of interest. In this review, we highlight recent strategies for engineering TF-based biosensors to obtain the desired performance and discuss additional design considerations that may influence a biosensor's performance. We also examine applications of these sensors and suggest important areas for further work to continue the advancement of small-molecule biosensors.
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Affiliation(s)
- Gloria J. Zhou
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
| | - Fuzhong Zhang
- Department of Energy, Environmental and Chemical Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA;
- Division of Biology & Biomedical Sciences, Washington University in St. Louis, St. Louis, MO 63130, USA
- Institute of Materials Science & Engineering, Washington University in St. Louis, St. Louis, MO 63130, USA
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8
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Glasgow A, Hobbs HT, Perry ZR, Wells ML, Marqusee S, Kortemme T. Ligand-specific changes in conformational flexibility mediate long-range allostery in the lac repressor. Nat Commun 2023; 14:1179. [PMID: 36859492 PMCID: PMC9977783 DOI: 10.1038/s41467-023-36798-1] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/20/2022] [Accepted: 02/17/2023] [Indexed: 03/03/2023] Open
Abstract
Biological regulation ubiquitously depends on protein allostery, but the regulatory mechanisms are incompletely understood, especially in proteins that undergo ligand-induced allostery with few structural changes. Here we used hydrogen-deuterium exchange with mass spectrometry (HDX/MS) to map allosteric effects in a paradigm ligand-responsive transcription factor, the lac repressor (LacI), in different functional states (apo, or bound to inducer, anti-inducer, and/or DNA). Although X-ray crystal structures of the LacI core domain in these states are nearly indistinguishable, HDX/MS experiments reveal widespread differences in flexibility. We integrate these results with modeling of protein-ligand-solvent interactions to propose a revised model for allostery in LacI, where ligand binding allosterically shifts the conformational ensemble as a result of distinct changes in the rigidity of secondary structures in the different states. Our model provides a mechanistic basis for the altered function of distal mutations. More generally, our approach provides a platform for characterizing and engineering protein allostery.
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Affiliation(s)
- Anum Glasgow
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA.
- Department of Biochemistry and Molecular Biophysics, Columbia University, New York, NY, 10032, USA.
| | - Helen T Hobbs
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Zion R Perry
- Department of Molecular Biophysics and Biochemistry, Yale University, New Haven, CT, 06511, USA
| | - Malcolm L Wells
- Department of Physics, Columbia University, New York, NY, 10032, USA
| | - Susan Marqusee
- Department of Chemistry, University of California, Berkeley, Berkeley, CA, 94720, USA
- Department of Molecular & Cell Biology, University of California, Berkeley, Berkeley, CA, 94720, USA
| | - Tanja Kortemme
- Department of Bioengineering and Therapeutic Sciences, University of California, San Francisco, CA, 94158, USA
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9
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Tellechea-Luzardo J, Stiebritz MT, Carbonell P. Transcription factor-based biosensors for screening and dynamic regulation. Front Bioeng Biotechnol 2023; 11:1118702. [PMID: 36814719 PMCID: PMC9939652 DOI: 10.3389/fbioe.2023.1118702] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2022] [Accepted: 01/26/2023] [Indexed: 02/09/2023] Open
Abstract
Advances in synthetic biology and genetic engineering are bringing into the spotlight a wide range of bio-based applications that demand better sensing and control of biological behaviours. Transcription factor (TF)-based biosensors are promising tools that can be used to detect several types of chemical compounds and elicit a response according to the desired application. However, the wider use of this type of device is still hindered by several challenges, which can be addressed by increasing the current metabolite-activated transcription factor knowledge base, developing better methods to identify new transcription factors, and improving the overall workflow for the design of novel biosensor circuits. These improvements are particularly important in the bioproduction field, where researchers need better biosensor-based approaches for screening production-strains and precise dynamic regulation strategies. In this work, we summarize what is currently known about transcription factor-based biosensors, discuss recent experimental and computational approaches targeted at their modification and improvement, and suggest possible future research directions based on two applications: bioproduction screening and dynamic regulation of genetic circuits.
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Affiliation(s)
- Jonathan Tellechea-Luzardo
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Valencia, Spain
| | - Martin T. Stiebritz
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Valencia, Spain
| | - Pablo Carbonell
- Institute of Industrial Control Systems and Computing (AI2), Universitat Politècnica de València (UPV), Valencia, Spain,Institute for Integrative Systems Biology I2SysBio, Universitat de València-CSIC, Paterna, Spain,*Correspondence: Pablo Carbonell,
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10
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Abstract
Chemical biosensors are an increasingly ubiquitous part of our lives. Beyond enzyme-coupled assays, recent synthetic biology advances now allow us to hijack more complex biosensing systems to respond to difficult to detect analytes, such as chemical small molecules. Here, we briefly overview recent advances in the biosensing of small molecules, including nucleic acid aptamers, allosteric transcription factors, and two-component systems. We then look more closely at a recently developed chemical sensing system, G protein-coupled receptor (GPCR)-based sensors. Finally, we consider the chemical sensing capabilities of the largest GPCR subfamily, olfactory receptors (ORs). We examine ORs' role in nature, their potential as a biomedical target, and their ability to detect compounds not amenable for detection using other biological scaffolds. We conclude by evaluating the current challenges, opportunities, and future applications of GPCR- and OR-based sensors.
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Affiliation(s)
- Amisha Patel
- School
of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States
| | - Pamela Peralta-Yahya
- School
of Chemical and Biomolecular Engineering, Georgia Institute of Technology, Atlanta, Georgia 30332, United States,School
of Chemistry and Biochemistry, Georgia Institute
of Technology, Atlanta, Georgia 30332, United States,E-mail:
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11
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Pham C, Stogios PJ, Savchenko A, Mahadevan R. Advances in engineering and optimization of transcription factor-based biosensors for plug-and-play small molecule detection. Curr Opin Biotechnol 2022; 76:102753. [PMID: 35872379 DOI: 10.1016/j.copbio.2022.102753] [Citation(s) in RCA: 8] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 05/31/2022] [Accepted: 06/06/2022] [Indexed: 11/30/2022]
Abstract
Transcription factor (TF)-based biosensors have been applied in biotechnology for a variety of functions, including protein engineering, dynamic control, environmental detection, and point-of-care diagnostics. Such biosensors are promising analytical tools due to their wide range of detectable ligands and modular nature. However, designing biosensors tailored for applications of interest with the desired performance parameters, including ligand specificity, remains challenging. Biosensors often require significant engineering and tuning to meet desired specificity, sensitivity, dynamic range, and operating range parameters. Another limitation is the orthogonality of biosensors across hosts, given the role of the cellular context. Here, we describe recent advances and examples in the engineering and optimization of TF-based biosensors for plug-and-play small molecule detection. We highlight novel developments in TF discovery and biosensor design, TF specificity engineering, and biosensor tuning, with emphasis on emerging computational methods.
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Affiliation(s)
- Chester Pham
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, ON, Canada
| | - Peter J Stogios
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, ON, Canada
| | - Alexei Savchenko
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, ON, Canada; Department of Microbiology, Immunology and Infectious Disease, University of Calgary, AB, Canada
| | - Radhakrishnan Mahadevan
- Department of Chemical Engineering and Applied Chemistry, University of Toronto, ON, Canada; The Institute of Biomedical Engineering, University of Toronto, ON, Canada.
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12
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Liu C, Yu H, Zhang B, Liu S, Liu CG, Li F, Song H. Engineering whole-cell microbial biosensors: Design principles and applications in monitoring and treatment of heavy metals and organic pollutants. Biotechnol Adv 2022; 60:108019. [PMID: 35853551 DOI: 10.1016/j.biotechadv.2022.108019] [Citation(s) in RCA: 28] [Impact Index Per Article: 14.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/01/2022] [Revised: 07/13/2022] [Accepted: 07/13/2022] [Indexed: 01/18/2023]
Abstract
Biosensors have been widely used as cost-effective, rapid, in situ, and real-time analytical tools for monitoring environments. The development of synthetic biology has enabled emergence of genetically engineered whole-cell microbial biosensors. This review updates the design and optimization principles for a diverse array of whole-cell biosensors based on transcription factors (TF) including activators or repressors derived from heavy metal resistance systems, alkanes, and aromatics metabolic pathways of bacteria. By designing genetic circuits, the whole-cell biosensors could be engineered to intelligently sense heavy metals (Hg2+, Zn2+, Pb2+, Au3+, Cd2+, As3+, Ni2+, Cu2+, and UO22+) or organic compounds (alcohols, alkanes, phenols, and benzenes) through one-component or two-component system-based TFs, transduce signals through genetic amplifiers, and response as various outputs such as cell fluorescence and bioelectricity for monitoring heavy metals and organic pollutants in real conditions, synthetic curli and surface metal-binding peptides for in situ bio-sorption of heavy metals. We further review strategies that have been implemented to optimize the selectivity and correlation between ligand concentration and output signal of the TF-based biosensors, so as to meet requirements of practical applications. The optimization strategies include protein engineering to change specificities, promoter engineering to improve sensitivities, and genetic circuit-based amplification to enhance dynamic ranges via designing transcriptional amplifiers, logic gates, and feedback loops. At last, we outlook future trends in developing novel forms of biosensors.
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Affiliation(s)
- Changjiang Liu
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Key Laboratory of Systems Bioengineering, Tianjin University, Tianjin 300072, China; Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Huan Yu
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Key Laboratory of Systems Bioengineering, Tianjin University, Tianjin 300072, China; Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Baocai Zhang
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Key Laboratory of Systems Bioengineering, Tianjin University, Tianjin 300072, China; Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Shilin Liu
- Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China
| | - Chen-Guang Liu
- State Key Laboratory of Microbial Metabolism, Joint International Research Laboratory of Metabolic & Developmental Sciences of Ministry of Education, School of Life Sciences and Biotechnology, Shanghai Jiao Tong University, Shanghai 200240, China
| | - Feng Li
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Key Laboratory of Systems Bioengineering, Tianjin University, Tianjin 300072, China; Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China.
| | - Hao Song
- Frontiers Science Center for Synthetic Biology (Ministry of Education), Key Laboratory of Systems Bioengineering, Tianjin University, Tianjin 300072, China; Collaborative Innovation Center of Chemical Science and Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin 300072, China.
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13
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Metabolite-based biosensors for natural product discovery and overproduction. Curr Opin Biotechnol 2022; 75:102699. [DOI: 10.1016/j.copbio.2022.102699] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/30/2021] [Revised: 01/25/2022] [Accepted: 02/05/2022] [Indexed: 12/22/2022]
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14
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Zhou S, Alper HS, Zhou J, Deng Y. Intracellular biosensor-based dynamic regulation to manipulate gene expression at the spatiotemporal level. Crit Rev Biotechnol 2022; 43:646-663. [PMID: 35450502 DOI: 10.1080/07388551.2022.2040415] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/17/2022]
Abstract
The use of intracellular, biosensor-based dynamic regulation strategies to regulate and improve the production of useful compounds have progressed significantly over previous decades. By employing such an approach, it is possible to simultaneously realize high productivity and optimum growth states. However, industrial fermentation conditions contain a mixture of high- and low-performance non-genetic variants, as well as young and aged cells at all growth phases. Such significant individual variations would hinder the precise controlling of metabolic flux at the single-cell level to achieve high productivity at the macroscopic population level. Intracellular biosensors, as the regulatory centers of metabolic networks, can real-time sense intra- and extracellular conditions and, thus, could be synthetically adapted to balance the biomass formation and overproduction of compounds by individual cells. Herein, we highlight advances in the designing and engineering approaches to intracellular biosensors. Then, the spatiotemporal properties of biosensors associated with the distribution of inducers are compared. Also discussed is the use of such biosensors to dynamically control the cellular metabolic flux. Such biosensors could achieve single-cell regulation or collective regulation goals, depending on whether or not the inducer distribution is only intracellular.
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Affiliation(s)
- Shenghu Zhou
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, Wuxi, Jiangsu, China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, Wuxi, Jiangsu, China
| | - Hal S Alper
- Institute for Cellular and Molecular Biology, The University of Texas at Austin, Austin, TX, USA.,McKetta Department of Chemical Engineering, The University of Texas at Austin, Austin, TX, USA
| | - Jingwen Zhou
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, Wuxi, Jiangsu, China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, Wuxi, Jiangsu, China
| | - Yu Deng
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, Wuxi, Jiangsu, China.,Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, Wuxi, Jiangsu, China
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15
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Nasr M, Timmins LR, Martin VJJ, Kwan DH. A Versatile Transcription Factor Biosensor System Responsive to Multiple Aromatic and Indole Inducers. ACS Synth Biol 2022; 11:1692-1698. [PMID: 35316041 PMCID: PMC9017570 DOI: 10.1021/acssynbio.2c00063] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/04/2022] [Indexed: 12/26/2022]
Abstract
Allosteric transcription factor (aTF) biosensors are valuable tools for engineering microbes toward a multitude of applications in metabolic engineering, biotechnology, and synthetic biology. One of the challenges toward constructing functional and diverse biosensors in engineered microbes is the limited toolbox of identified and characterized aTFs. To overcome this, extensive bioprospecting of aTFs from sequencing databases, as well as aTF ligand-specificity engineering are essential in order to realize their full potential as biosensors for novel applications. In this work, using the TetR-family repressor CmeR from Campylobacter jejuni, we construct aTF genetic circuits that function as salicylate biosensors in the model organisms Escherichia coli and Saccharomyces cerevisiae. In addition to salicylate, we demonstrate the responsiveness of CmeR-regulated promoters to multiple aromatic and indole inducers. This relaxed ligand specificity of CmeR makes it a useful tool for detecting molecules in many metabolic engineering applications, as well as a good target for directed evolution to engineer proteins that are able to detect new and diverse chemistries.
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Affiliation(s)
- Mohamed
A. Nasr
- Department
of Biology, Centre for Applied Synthetic Biology, and Centre for Structural
and Functional Genomics, Concordia University, Montréal, Quebec H4B 1R6, Canada
- PROTEO,
Quebec Network for Research on Protein Function, Structure, and Engineering, Québec City, Quebec G1 V 0A6, Canada
| | - Logan R. Timmins
- Department
of Biology, Centre for Applied Synthetic Biology, and Centre for Structural
and Functional Genomics, Concordia University, Montréal, Quebec H4B 1R6, Canada
- PROTEO,
Quebec Network for Research on Protein Function, Structure, and Engineering, Québec City, Quebec G1 V 0A6, Canada
| | - Vincent J. J. Martin
- Department
of Biology, Centre for Applied Synthetic Biology, and Centre for Structural
and Functional Genomics, Concordia University, Montréal, Quebec H4B 1R6, Canada
| | - David H. Kwan
- Department
of Biology, Centre for Applied Synthetic Biology, and Centre for Structural
and Functional Genomics, Concordia University, Montréal, Quebec H4B 1R6, Canada
- PROTEO,
Quebec Network for Research on Protein Function, Structure, and Engineering, Québec City, Quebec G1 V 0A6, Canada
- Department
of Chemistry and Biochemistry, Concordia
University, Montréal, Quebec H4B 1R6, Canada
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16
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Engineering of Synthetic Transcriptional Switches in Yeast. Life (Basel) 2022; 12:life12040557. [PMID: 35455048 PMCID: PMC9030632 DOI: 10.3390/life12040557] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 03/31/2022] [Accepted: 04/03/2022] [Indexed: 02/04/2023] Open
Abstract
Transcriptional switches can be utilized for many purposes in synthetic biology, including the assembly of complex genetic circuits to achieve sophisticated cellular systems and the construction of biosensors for real-time monitoring of intracellular metabolite concentrations. Although to date such switches have mainly been developed in prokaryotes, those for eukaryotes are increasingly being reported as both rational and random engineering technologies mature. In this review, we describe yeast transcriptional switches with different modes of action and how to alter their properties. We also discuss directed evolution technologies for the rapid and robust construction of yeast transcriptional switches.
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17
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Miller CA, Ho JML, Bennett MR. Strategies for Improving Small-Molecule Biosensors in Bacteria. BIOSENSORS 2022; 12:bios12020064. [PMID: 35200325 PMCID: PMC8869690 DOI: 10.3390/bios12020064] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2021] [Revised: 01/14/2022] [Accepted: 01/18/2022] [Indexed: 05/03/2023]
Abstract
In recent years, small-molecule biosensors have become increasingly important in synthetic biology and biochemistry, with numerous new applications continuing to be developed throughout the field. For many biosensors, however, their utility is hindered by poor functionality. Here, we review the known types of mechanisms of biosensors within bacterial cells, and the types of approaches for optimizing different biosensor functional parameters. Discussed approaches for improving biosensor functionality include methods of directly engineering biosensor genes, considerations for choosing genetic reporters, approaches for tuning gene expression, and strategies for incorporating additional genetic modules.
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Affiliation(s)
- Corwin A. Miller
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA; (C.A.M.); (J.M.L.H.)
| | - Joanne M. L. Ho
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA; (C.A.M.); (J.M.L.H.)
| | - Matthew R. Bennett
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA; (C.A.M.); (J.M.L.H.)
- Department of Bioengineering, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
- Correspondence:
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18
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Lazar JT, Tabor JJ. Bacterial two-component systems as sensors for synthetic biology applications. CURRENT OPINION IN SYSTEMS BIOLOGY 2021; 28:100398. [PMID: 34917859 PMCID: PMC8670732 DOI: 10.1016/j.coisb.2021.100398] [Citation(s) in RCA: 21] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 04/12/2023]
Abstract
Two-component systems (TCSs) are a ubiquitous family of signal transduction pathways that enable bacteria to sense and respond to diverse physical, chemical, and biological stimuli outside and inside the cell. Synthetic biologists have begun to repurpose TCSs for applications in optogenetics, materials science, gut microbiome engineering, and soil nutrient biosensing, among others. New engineering methods including genetic refactoring, DNA-binding domain swapping, detection threshold tuning, and phosphorylation cross-talk insulation are being used to increase the reliability of TCS sensor performance and tailor TCS signaling properties to the requirements of specific applications. There is now potential to combine these methods with large-scale gene synthesis and laboratory screening to discover the inputs sensed by many uncharacterized TCSs and develop a large new family of genetically-encoded sensors that respond to an unrivaled breadth of stimuli.
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Affiliation(s)
- John T Lazar
- Department of Chemical and Biomolecular Engineering, Rice University, Houston, TX, USA
| | - Jeffrey J Tabor
- Department of Bioengineering, Rice University, Houston, TX, USA
- PhD Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, TX, USA
- Department of Biosciences, Rice University, Houston, TX, USA
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19
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Zhang J, Pang Q, Wang Q, Qi Q, Wang Q. Modular tuning engineering and versatile applications of genetically encoded biosensors. Crit Rev Biotechnol 2021; 42:1010-1027. [PMID: 34615431 DOI: 10.1080/07388551.2021.1982858] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2022]
Abstract
Genetically encoded biosensors have a diverse range of detectable signals and potential applications in many fields, including metabolism control and high-throughput screening. Their ability to be used in situ with minimal interference to the bioprocess of interest could revolutionize synthetic biology and microbial cell factories. The performance and functions of these biosensors have been extensively studied and have been rapidly improved. We review here current biosensor tuning strategies and attempt to unravel how to obtain ideal biosensor functions through experimental adjustments. Strategies for expanding the biosensor input signals that increases the number of detectable compounds have also been summarized. Finally, different output signals and their practical requirements for biotechnology and biomedical applications and environmental safety concerns have been analyzed. This in-depth review of the responses and regulation mechanisms of genetically encoded biosensors will assist to improve their design and optimization in various application scenarios.
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Affiliation(s)
- Jian Zhang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Qingxiao Pang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Qi Wang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China
| | - Qingsheng Qi
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China.,CAS Key Lab of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, P. R. China
| | - Qian Wang
- National Glycoengineering Research Center, State Key Laboratory of Microbial Technology, Shandong University, Qingdao, P. R. China.,CAS Key Lab of Biobased Materials, Qingdao Institute of Bioenergy and Bioprocess Technology, Chinese Academy of Sciences, Qingdao, P. R. China
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20
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Yi D, Bayer T, Badenhorst CPS, Wu S, Doerr M, Höhne M, Bornscheuer UT. Recent trends in biocatalysis. Chem Soc Rev 2021; 50:8003-8049. [PMID: 34142684 PMCID: PMC8288269 DOI: 10.1039/d0cs01575j] [Citation(s) in RCA: 122] [Impact Index Per Article: 40.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/19/2020] [Indexed: 12/13/2022]
Abstract
Biocatalysis has undergone revolutionary progress in the past century. Benefited by the integration of multidisciplinary technologies, natural enzymatic reactions are constantly being explored. Protein engineering gives birth to robust biocatalysts that are widely used in industrial production. These research achievements have gradually constructed a network containing natural enzymatic synthesis pathways and artificially designed enzymatic cascades. Nowadays, the development of artificial intelligence, automation, and ultra-high-throughput technology provides infinite possibilities for the discovery of novel enzymes, enzymatic mechanisms and enzymatic cascades, and gradually complements the lack of remaining key steps in the pathway design of enzymatic total synthesis. Therefore, the research of biocatalysis is gradually moving towards the era of novel technology integration, intelligent manufacturing and enzymatic total synthesis.
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Affiliation(s)
- Dong Yi
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Thomas Bayer
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Christoffel P. S. Badenhorst
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Shuke Wu
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Mark Doerr
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Matthias Höhne
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
| | - Uwe T. Bornscheuer
- Department of Biotechnology & Enzyme Catalysis, Institute of Biochemistry, University GreifswaldFelix-Hausdorff-Str. 4D-17487 GreifswaldGermany
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21
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Ding N, Zhou S, Deng Y. Transcription-Factor-based Biosensor Engineering for Applications in Synthetic Biology. ACS Synth Biol 2021; 10:911-922. [PMID: 33899477 DOI: 10.1021/acssynbio.0c00252] [Citation(s) in RCA: 59] [Impact Index Per Article: 19.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/23/2022]
Abstract
Transcription-factor-based biosensors (TFBs) are often used for metabolite detection, adaptive evolution, and metabolic flux control. However, designing TFBs with superior performance for applications in synthetic biology remains challenging. Specifically, natural TFBs often do not meet real-time detection requirements owing to their slow response times and inappropriate dynamic ranges, detection ranges, sensitivity, and selectivity. Furthermore, designing and optimizing complex dynamic regulation networks is time-consuming and labor-intensive. This Review highlights TFB-based applications and recent engineering strategies ranging from traditional trial-and-error approaches to novel computer-model-based rational design approaches. The limitations of the applications and these engineering strategies are additionally reviewed.
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Affiliation(s)
- Nana Ding
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Shenghu Zhou
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
| | - Yu Deng
- National Engineering Laboratory for Cereal Fermentation Technology (NELCF), Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
- Jiangsu Provincial Research Center for Bioactive Product Processing Technology, Jiangnan University, 1800 Lihu Road, Wuxi, Jiangsu 214122, China
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22
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Abstract
One of the most prominent features of genetically encoded biosensors (GEBs) is their evolvability-the ability to invent new sensory functions using mutations. Among the GEBs, the transcription factor-based biosensors (TF-biosensors) is the focus of this review. We also discuss how this class of sensors can be highly evolvable and how we can exploit it. With an established platform for directed evolution, researchers can create, or evolve, new TF-biosensors. Directed evolution experiments have revealed the TF-biosensors' evolvability, which is based partially on their characteristic physicochemical properties.
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Affiliation(s)
- Daisuke Umeno
- Department of Applied Chemistry and Biotechnology, Graduate School of Engineering, Chiba University
| | - Yuki Kimura
- Department of Applied Chemistry and Biotechnology, Graduate School of Engineering, Chiba University
| | - Shigeko Kawai-Noma
- Department of Applied Chemistry and Biotechnology, Graduate School of Engineering, Chiba University
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23
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Wu Y, Jameel A, Xing XH, Zhang C. Advanced strategies and tools to facilitate and streamline microbial adaptive laboratory evolution. Trends Biotechnol 2021; 40:38-59. [PMID: 33958227 DOI: 10.1016/j.tibtech.2021.04.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/20/2020] [Revised: 03/17/2021] [Accepted: 04/01/2021] [Indexed: 12/18/2022]
Abstract
Adaptive laboratory evolution (ALE) has served as a historic microbial engineering method that mimics natural selection to obtain desired microbes. The past decade has witnessed improvements in all aspects of ALE workflow, in terms of growth coupling, genotypic diversification, phenotypic selection, and genotype-phenotype mapping. The developing growth-coupling strategies facilitate ALE to a wider range of appealing traits. In vivo mutagenesis methods and multiplexed automated culture platforms open new gates to streamline its execution. Meanwhile, the application of multi-omics analyses and multiplexed genetic engineering promote efficient knowledge mining. This article provides a comprehensive and updated review of these advances, highlights newest significant applications, and discusses future improvements, aiming to provide a practical guide for implementation of novel, effective, and efficient ALE experiments.
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Affiliation(s)
- Yinan Wu
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Aysha Jameel
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China
| | - Xin-Hui Xing
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China
| | - Chong Zhang
- MOE Key Laboratory for Industrial Biocatalysis, Institute of Biochemical Engineering, Department of Chemical Engineering, Tsinghua University, Beijing 100084, China; Center for Synthetic and Systems Biology, Tsinghua University, Beijing, 100084, China.
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24
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Rondon R, Wilson CJ. Engineering Alternate Ligand Recognition in the PurR Topology: A System of Novel Caffeine Biosensing Transcriptional Antirepressors. ACS Synth Biol 2021; 10:552-565. [PMID: 33689294 DOI: 10.1021/acssynbio.0c00582] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/05/2023]
Abstract
Recent advances in synthetic biology and protein engineering have increased the number of allosteric transcription factors used to regulate independent promoters. These developments represent an important increase in our biological computing capacity, which will enable us to construct more sophisticated genetic programs for a broad range of biological technologies. However, the majority of these transcription factors are represented by the repressor phenotype (BUFFER), and require layered inversion to confer the antithetical logical function (NOT), requiring additional biological resources. Moreover, these engineered transcription factors typically utilize native ligand binding functions paired with alternate DNA binding functions. In this study, we have advanced the state-of-the-art by engineering and redesigning the PurR topology (a native antirepressor) to be responsive to caffeine, while mitigating responsiveness to the native ligand hypoxanthine-i.e., a deamination product of the input molecule adenine. Importantly, the resulting caffeine responsive transcription factors are not antagonized by the native ligand hypoxanthine. In addition, we conferred alternate DNA binding to the caffeine antirepressors, and to the PurR scaffold, creating 38 new transcription factors that are congruent with our current transcriptional programming structure. Finally, we leveraged this system of transcription factors to create integrated NOR logic and related feedback operations. This study represents the first example of a system of transcription factors (antirepressors) in which both the ligand binding site and the DNA binding functions were successfully engineered in tandem.
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Affiliation(s)
- Ronald Rondon
- Georgia Institute of Technology, School of Chemical & Biomolecular Engineering, 311 Ferst Drive, Atlanta, Georgia 30332-0100, United States
| | - Corey J. Wilson
- Georgia Institute of Technology, School of Chemical & Biomolecular Engineering, 311 Ferst Drive, Atlanta, Georgia 30332-0100, United States
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25
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Ho JML, Miller CA, Parks SE, Mattia JR, Bennett M. A suppressor tRNA-mediated feedforward loop eliminates leaky gene expression in bacteria. Nucleic Acids Res 2021; 49:e25. [PMID: 33290521 PMCID: PMC7969014 DOI: 10.1093/nar/gkaa1179] [Citation(s) in RCA: 14] [Impact Index Per Article: 4.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/02/2020] [Revised: 11/11/2020] [Accepted: 11/19/2020] [Indexed: 11/13/2022] Open
Abstract
Ligand-inducible genetic systems are the mainstay of synthetic biology, allowing gene expression to be controlled by the presence of a small molecule. However, 'leaky' gene expression in the absence of inducer remains a persistent problem. We developed a leak dampener tool that drastically reduces the leak of inducible genetic systems while retaining signal in Escherichia coli. Our system relies on a coherent feedforward loop featuring a suppressor tRNA that enables conditional readthrough of silent non-sense mutations in a regulated gene, and this approach can be applied to any ligand-inducible transcription factor. We demonstrate proof-of-principle of our system with the lactate biosensor LldR and the arabinose biosensor AraC, which displayed a 70-fold and 630-fold change in output after induction of a fluorescence reporter, respectively, without any background subtraction. Application of the tool to an arabinose-inducible mutagenesis plasmid led to a 540-fold change in its output after induction, with leak decreasing to the level of background mutagenesis. This study provides a modular tool for reducing leak and improving the fold-induction within genetic circuits, demonstrated here using two types of biosensors relevant to cancer detection and genetic engineering.
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Affiliation(s)
- Joanne M L Ho
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
| | - Corwin A Miller
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
| | - Sydney E Parks
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
| | - Jacob R Mattia
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
| | - Matthew R Bennett
- Department of Biosciences, Rice University MS-140, 6100 Main St., Houston, TX 77005, USA
- Department of Bioengineering, Rice University MS-140, 6100 Main St. Houston, TX 77005, USA
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26
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Otero-Muras I, Carbonell P. Automated engineering of synthetic metabolic pathways for efficient biomanufacturing. Metab Eng 2020; 63:61-80. [PMID: 33316374 DOI: 10.1016/j.ymben.2020.11.012] [Citation(s) in RCA: 30] [Impact Index Per Article: 7.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/22/2020] [Revised: 11/15/2020] [Accepted: 11/20/2020] [Indexed: 12/19/2022]
Abstract
Metabolic engineering involves the engineering and optimization of processes from single-cell to fermentation in order to increase production of valuable chemicals for health, food, energy, materials and others. A systems approach to metabolic engineering has gained traction in recent years thanks to advances in strain engineering, leading to an accelerated scaling from rapid prototyping to industrial production. Metabolic engineering is nowadays on track towards a truly manufacturing technology, with reduced times from conception to production enabled by automated protocols for DNA assembly of metabolic pathways in engineered producer strains. In this review, we discuss how the success of the metabolic engineering pipeline often relies on retrobiosynthetic protocols able to identify promising production routes and dynamic regulation strategies through automated biodesign algorithms, which are subsequently assembled as embedded integrated genetic circuits in the host strain. Those approaches are orchestrated by an experimental design strategy that provides optimal scheduling planning of the DNA assembly, rapid prototyping and, ultimately, brings forward an accelerated Design-Build-Test-Learn cycle and the overall optimization of the biomanufacturing process. Achieving such a vision will address the increasingly compelling demand in our society for delivering valuable biomolecules in an affordable, inclusive and sustainable bioeconomy.
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Affiliation(s)
- Irene Otero-Muras
- BioProcess Engineering Group, IIM-CSIC, Spanish National Research Council, Vigo, 36208, Spain.
| | - Pablo Carbonell
- Institute of Industrial Control Systems and Computing (ai2), Universitat Politècnica de València, 46022, Spain.
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27
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Iwasaki RS, Batey RT. SPRINT: a Cas13a-based platform for detection of small molecules. Nucleic Acids Res 2020; 48:e101. [PMID: 32797156 PMCID: PMC7515716 DOI: 10.1093/nar/gkaa673] [Citation(s) in RCA: 47] [Impact Index Per Article: 11.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Revised: 07/15/2020] [Accepted: 07/31/2020] [Indexed: 12/19/2022] Open
Abstract
Recent efforts in biological engineering have made detection of nucleic acids in samples more rapid, inexpensive and sensitive using CRISPR-based approaches. We expand one of these Cas13a-based methods to detect small molecules in a one-batch assay. Using SHERLOCK-based profiling of in vitrotranscription (SPRINT), in vitro transcribed RNA sequence-specifically triggers the RNase activity of Cas13a. This event activates its non-specific RNase activity, which enables cleavage of an RNA oligonucleotide labeled with a quencher/fluorophore pair and thereby de-quenches the fluorophore. This fluorogenic output can be measured to assess transcriptional output. The use of riboswitches or proteins to regulate transcription via specific effector molecules is leveraged as a coupled assay that transforms effector concentration into fluorescence intensity. In this way, we quantified eight different compounds, including cofactors, nucleotides, metabolites of amino acids, tetracycline and monatomic ions in samples. In this manner, hundreds of reactions can be easily quantified in a few hours. This increased throughput also enables detailed characterization of transcriptional regulators, synthetic compounds that inhibit transcription, or other coupled enzymatic reactions. These SPRINT reactions are easily adaptable to portable formats and could therefore be used for the detection of analytes in the field or at point-of-care situations.
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Affiliation(s)
- Roman S Iwasaki
- Department of Biochemistry, University of Colorado, Boulder, CO 80309-0596, USA
| | - Robert T Batey
- Department of Biochemistry, University of Colorado, Boulder, CO 80309-0596, USA
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28
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Chern M, Garden PM, Baer RC, Galagan JE, Dennis AM. Transcription Factor Based Small‐Molecule Sensing with a Rapid Cell Phone Enabled Fluorescent Bead Assay. Angew Chem Int Ed Engl 2020. [DOI: 10.1002/ange.202007575] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/10/2022]
Affiliation(s)
- Margaret Chern
- Division of Materials Science and Engineering Boston University Boston MA USA
| | - Padric M. Garden
- Department of Biomedical Engineering Boston University Boston MA USA
| | - R C. Baer
- Department of Microbiology Boston University Boston MA USA
| | - James E. Galagan
- Department of Biomedical Engineering Boston University Boston MA USA
- Department of Microbiology Boston University Boston MA USA
- National Emerging Infectious Diseases Laboratories Boston University Boston MA USA
| | - Allison M. Dennis
- Division of Materials Science and Engineering Boston University Boston MA USA
- Department of Biomedical Engineering Boston University Boston MA USA
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29
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Chern M, Garden PM, Baer RC, Galagan JE, Dennis AM. Transcription Factor Based Small-Molecule Sensing with a Rapid Cell Phone Enabled Fluorescent Bead Assay. Angew Chem Int Ed Engl 2020; 59:21597-21602. [PMID: 32945589 DOI: 10.1002/anie.202007575] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Indexed: 12/26/2022]
Abstract
Recently, allosteric transcription factors (TFs) were identified as a novel class of biorecognition elements for in vitro sensing, whereby an indicator of the differential binding affinity between a TF and its cognate DNA exhibits dose-dependent responsivity to an analyte. Described is a modular bead-based biosensor design that can be applied to such TF-DNA-analyte systems. DNA-functionalized beads enable efficient mixing and spatial separation, while TF-labeled semiconductor quantum dots serve as bright fluorescent indicators of the TF-DNA bound (on bead) and unbound states. The prototype sensor for derivatives of the antibiotic tetracycline exhibits nanomolar sensitivity with visual detection of bead fluorescence. Facile changes to the sensor enable sensor response tuning without necessitating changes to the biomolecular affinities. Assay components self-assemble, and readout by eye or digital camera is possible within 5 minutes of analyte addition, making sensor use facile, rapid, and instrument-free.
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Affiliation(s)
- Margaret Chern
- Division of Materials Science and Engineering, Boston University, Boston, MA, USA
| | - Padric M Garden
- Department of Biomedical Engineering, Boston University, Boston, MA, USA
| | - R C Baer
- Department of Microbiology, Boston University, Boston, MA, USA
| | - James E Galagan
- Department of Biomedical Engineering, Boston University, Boston, MA, USA.,Department of Microbiology, Boston University, Boston, MA, USA.,National Emerging Infectious Diseases Laboratories, Boston University, Boston, MA, USA
| | - Allison M Dennis
- Division of Materials Science and Engineering, Boston University, Boston, MA, USA.,Department of Biomedical Engineering, Boston University, Boston, MA, USA
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30
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Naseri G, Koffas MAG. Application of combinatorial optimization strategies in synthetic biology. Nat Commun 2020; 11:2446. [PMID: 32415065 PMCID: PMC7229011 DOI: 10.1038/s41467-020-16175-y] [Citation(s) in RCA: 71] [Impact Index Per Article: 17.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2019] [Accepted: 04/15/2020] [Indexed: 12/26/2022] Open
Abstract
In the first wave of synthetic biology, genetic elements, combined into simple circuits, are used to control individual cellular functions. In the second wave of synthetic biology, the simple circuits, combined into complex circuits, form systems-level functions. However, efforts to construct complex circuits are often impeded by our limited knowledge of the optimal combination of individual circuits. For example, a fundamental question in most metabolic engineering projects is the optimal level of enzymes for maximizing the output. To address this point, combinatorial optimization approaches have been established, allowing automatic optimization without prior knowledge of the best combination of expression levels of individual genes. This review focuses on current combinatorial optimization methods and emerging technologies facilitating their applications.
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Affiliation(s)
- Gita Naseri
- Institut für Chemie, Humboldt Universität zu Berlin, 12489, Berlin, Germany.
| | - Mattheos A G Koffas
- Center for Biotechnology, Rensselaer Polytechnic Institute, Troy, NY, USA.
- Department of Chemical and Biological Engineering, Rensselaer Polytechnic Institute, Troy, NY, USA.
- Department of Biological Sciences, Rensselaer Polytechnic Institute, Troy, NY, USA.
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31
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Genetic Biosensor Design for Natural Product Biosynthesis in Microorganisms. Trends Biotechnol 2020; 38:797-810. [PMID: 32359951 DOI: 10.1016/j.tibtech.2020.03.013] [Citation(s) in RCA: 69] [Impact Index Per Article: 17.3] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/15/2019] [Revised: 03/26/2020] [Accepted: 03/26/2020] [Indexed: 12/28/2022]
Abstract
Low yield and low titer of natural products are common issues in natural product biosynthesis through microbial cell factories. One effective way to resolve such bottlenecks is to design genetic biosensors to monitor and regulate the biosynthesis of target natural products. In this review, we evaluate the most recent advances in the design of genetic biosensors for natural product biosynthesis in microorganisms. In particular, we examine strategies for selection of genetic parts and construction principles for the design and evaluation of genetic biosensors. We also review the latest applications of transcription factor- and riboswitch-based genetic biosensors in natural product biosynthesis. Lastly, we discuss challenges and solutions in designing genetic biosensors for the biosynthesis of natural products in microorganisms.
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32
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Snoek T, Chaberski EK, Ambri F, Kol S, Bjørn SP, Pang B, Barajas JF, Welner DH, Jensen MK, Keasling JD. Evolution-guided engineering of small-molecule biosensors. Nucleic Acids Res 2020; 48:e3. [PMID: 31777933 PMCID: PMC6943132 DOI: 10.1093/nar/gkz954] [Citation(s) in RCA: 79] [Impact Index Per Article: 19.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/20/2019] [Revised: 10/06/2019] [Accepted: 10/24/2019] [Indexed: 11/14/2022] Open
Abstract
Allosteric transcription factors (aTFs) have proven widely applicable for biotechnology and synthetic biology as ligand-specific biosensors enabling real-time monitoring, selection and regulation of cellular metabolism. However, both the biosensor specificity and the correlation between ligand concentration and biosensor output signal, also known as the transfer function, often needs to be optimized before meeting application needs. Here, we present a versatile and high-throughput method to evolve prokaryotic aTF specificity and transfer functions in a eukaryote chassis, namely baker's yeast Saccharomyces cerevisiae. From a single round of mutagenesis of the effector-binding domain (EBD) coupled with various toggled selection regimes, we robustly select aTF variants of the cis,cis-muconic acid-inducible transcription factor BenM evolved for change in ligand specificity, increased dynamic output range, shifts in operational range, and a complete inversion-of-function from activation to repression. Importantly, by targeting only the EBD, the evolved biosensors display DNA-binding affinities similar to BenM, and are functional when ported back into a prokaryotic chassis. The developed platform technology thus leverages aTF evolvability for the development of new host-agnostic biosensors with user-defined small-molecule specificities and transfer functions.
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Affiliation(s)
- Tim Snoek
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Evan K Chaberski
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Francesca Ambri
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Stefan Kol
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Sara P Bjørn
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Bo Pang
- Joint BioEnergy Institute, Emeryville, CA, USA
| | | | - Ditte H Welner
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Michael K Jensen
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark
| | - Jay D Keasling
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, Kgs. Lyngby, Denmark.,Joint BioEnergy Institute, Emeryville, CA, USA.,Biological Systems and Engineering Division, Lawrence Berkeley National Laboratory, Berkeley, CA, USA.,Department of Chemical and Biomolecular Engineering & Department of Bioengineering, University of California, Berkeley, CA, USA.,Center for Synthetic Biochemistry, Institute for Synthetic Biology, Shenzhen Institutes of Advanced Technologies, Shenzhen, China
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Liu X, Silverman AD, Alam KK, Iverson E, Lucks JB, Jewett MC, Raman S. Design of a Transcriptional Biosensor for the Portable, On-Demand Detection of Cyanuric Acid. ACS Synth Biol 2020; 9:84-94. [PMID: 31825601 PMCID: PMC7372534 DOI: 10.1021/acssynbio.9b00348] [Citation(s) in RCA: 35] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/07/2023]
Abstract
Rapid molecular biosensing is an emerging application area for synthetic biology. Here, we engineer a portable biosensor for cyanuric acid (CYA), an analyte of interest for human and environmental health, using a LysR-type transcription regulator (LTTR) from Pseudomonas within the context of Escherichia coli gene expression machinery. To overcome cross-host portability challenges of LTTRs, we rationally engineered hybrid Pseudomonas-E. coli promoters by integrating DNA elements required for transcriptional activity and ligand-dependent regulation from both hosts, which enabled E. coli to function as a whole-cell biosensor for CYA. To alleviate challenges of whole-cell biosensing, we adapted these promoter designs to function within a freeze-dried E. coli cell-free system to sense CYA. This portable, on-demand system robustly detects CYA within an hour from laboratory and real-world samples and works with both fluorescent and colorimetric reporters. This work elucidates general principles to facilitate the engineering of a wider array of LTTR-based environmental sensors.
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Affiliation(s)
- Xiangyang Liu
- Biophysics Graduate Program, University of Wisconsin, Madison, WI, USA
| | - Adam D. Silverman
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
- Center for Synthetic Biology, Northwestern University, Evanston, IL, USA
- Center for Water Research, Northwestern University, Evanston, IL, USA
| | - Khalid K. Alam
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
- Center for Synthetic Biology, Northwestern University, Evanston, IL, USA
- Center for Water Research, Northwestern University, Evanston, IL, USA
| | - Erik Iverson
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA
| | - Julius B. Lucks
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
- Center for Synthetic Biology, Northwestern University, Evanston, IL, USA
- Center for Water Research, Northwestern University, Evanston, IL, USA
| | - Michael C. Jewett
- Department of Chemical and Biological Engineering, Northwestern University, Evanston, IL, USA
- Center for Synthetic Biology, Northwestern University, Evanston, IL, USA
| | - Srivatsan Raman
- Department of Biochemistry, University of Wisconsin, Madison, WI, USA
- Department of Bacteriology, University of Wisconsin, Madison, WI, USA
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34
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Unified rational protein engineering with sequence-based deep representation learning. Nat Methods 2019; 16:1315-1322. [PMID: 31636460 DOI: 10.1038/s41592-019-0598-1] [Citation(s) in RCA: 480] [Impact Index Per Article: 96.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/08/2019] [Accepted: 09/11/2019] [Indexed: 01/03/2023]
Abstract
Rational protein engineering requires a holistic understanding of protein function. Here, we apply deep learning to unlabeled amino-acid sequences to distill the fundamental features of a protein into a statistical representation that is semantically rich and structurally, evolutionarily and biophysically grounded. We show that the simplest models built on top of this unified representation (UniRep) are broadly applicable and generalize to unseen regions of sequence space. Our data-driven approach predicts the stability of natural and de novo designed proteins, and the quantitative function of molecularly diverse mutants, competitively with the state-of-the-art methods. UniRep further enables two orders of magnitude efficiency improvement in a protein engineering task. UniRep is a versatile summary of fundamental protein features that can be applied across protein engineering informatics.
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35
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Custom-made transcriptional biosensors for metabolic engineering. Curr Opin Biotechnol 2019; 59:78-84. [DOI: 10.1016/j.copbio.2019.02.016] [Citation(s) in RCA: 51] [Impact Index Per Article: 10.2] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/26/2018] [Revised: 01/31/2019] [Accepted: 02/19/2019] [Indexed: 01/20/2023]
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36
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Monteiro LMO, Arruda LM, Sanches-Medeiros A, Martins-Santana L, Alves LDF, Defelipe L, Turjanski AG, Guazzaroni ME, de Lorenzo V, Silva-Rocha R. Reverse Engineering of an Aspirin-Responsive Transcriptional Regulator in Escherichia coli. ACS Synth Biol 2019; 8:1890-1900. [PMID: 31362496 DOI: 10.1021/acssynbio.9b00191] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/22/2023]
Abstract
Bacterial transcription factors (TFs) are key devices for the engineering of complex circuits in many biotechnological applications, yet there are few well-characterized inducer-responsive TFs that could be used in the context of an animal or human host. We have deciphered the inducer recognition mechanism of two AraC/XylS regulators from Pseudomonas putida (BenR and XylS) for creating a novel expression system responsive to acetyl salicylate (i.e., aspirin). Using protein homology modeling and molecular docking with the cognate inducer benzoate and a suite of chemical analogues, we identified the conserved binding pocket of BenR and XylS. By means of site-directed mutagenesis, we identified a single amino acid position required for efficient inducer recognition and transcriptional activation. Whereas this modification in BenR abolishes protein activity, in XylS, it increases the response to several inducers, including acetyl salicylic acid, to levels close to those achieved by the canonical inducer. Moreover, by constructing chimeric proteins with swapped N-terminal domains, we created novel regulators with mixed promoter and inducer recognition profiles. As a result, a collection of engineered TFs was generated with an enhanced response to benzoate, 3-methylbenzoate, 2-methylbenzoate, 4-methylbenzoate, salicylic acid, aspirin, and acetylsalicylic acid molecules for eliciting gene expression in E. coli.
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Affiliation(s)
| | - Letı́cia Magalhães Arruda
- Cell and Molecular Biology Department, FMRP − University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - Ananda Sanches-Medeiros
- Cell and Molecular Biology Department, FMRP − University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - Leonardo Martins-Santana
- Cell and Molecular Biology Department, FMRP − University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
| | - Luana de Fátima Alves
- Biology Department, FFCLRP − University of São Paulo, Ribeirão Preto, São Paulo 14040-901, Brazil
| | - Lucas Defelipe
- Departamento de Quı́mica Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina
- IQUIBICEN/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina
| | - Adrian Gustavo Turjanski
- Departamento de Quı́mica Biológica, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina
- IQUIBICEN/UBA-CONICET, Facultad de Ciencias Exactas y Naturales, Universidad de Buenos Aires, Buenos Aires 1428, Argentina
| | | | - Vı́ctor de Lorenzo
- Systems Biology Program, National Center of Biotechnology − CSIC, Madrid 28049, Spain
| | - Rafael Silva-Rocha
- Cell and Molecular Biology Department, FMRP − University of São Paulo, Ribeirão Preto, São Paulo 14049-900, Brazil
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Structural and evolutionary approaches to the design and optimization of fluorescence-based small molecule biosensors. Curr Opin Struct Biol 2019; 57:31-38. [DOI: 10.1016/j.sbi.2019.01.013] [Citation(s) in RCA: 22] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2018] [Revised: 01/10/2019] [Accepted: 01/23/2019] [Indexed: 11/21/2022]
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38
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Engineering CatM, a LysR-Type Transcriptional Regulator, to Respond Synergistically to Two Effectors. Genes (Basel) 2019; 10:genes10060421. [PMID: 31159259 PMCID: PMC6628147 DOI: 10.3390/genes10060421] [Citation(s) in RCA: 11] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2019] [Revised: 05/24/2019] [Accepted: 05/30/2019] [Indexed: 11/19/2022] Open
Abstract
The simultaneous response of one transcriptional regulator to different effectors remains largely unexplored. Nevertheless, such interactions can substantially impact gene expression by rapidly integrating cellular signals and by expanding the range of transcriptional responses. In this study, similarities between paralogs were exploited to engineer novel responses in CatM, a regulator that controls benzoate degradation in Acinetobacter baylyi ADP1. One goal was to improve understanding of how its paralog, BenM, activates transcription in response to two compounds (cis,cis-muconate and benzoate) at levels significantly greater than with either alone. Despite the overlapping functions of BenM and CatM, which regulate many of the same ben and cat genes, CatM normally responds only to cis,cis-muconate. Using domain swapping and site-directed amino acid replacements, CatM variants were generated and assessed for the ability to activate transcription. To create a variant that responds synergistically to both effectors required alteration of both the effector-binding region and the DNA-binding domain. These studies help define the interconnected roles of protein domains and extend understanding of LysR-type proteins, the largest family of transcriptional regulators in bacteria. Additionally, renewed interest in the modular functionality of transcription factors stems from their potential use as biosensors.
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Moser F, Espah Borujeni A, Ghodasara AN, Cameron E, Park Y, Voigt CA. Dynamic control of endogenous metabolism with combinatorial logic circuits. Mol Syst Biol 2018; 14:e8605. [PMID: 30482789 PMCID: PMC6263354 DOI: 10.15252/msb.20188605] [Citation(s) in RCA: 73] [Impact Index Per Article: 12.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/10/2018] [Revised: 10/25/2018] [Accepted: 10/30/2018] [Indexed: 11/09/2022] Open
Abstract
Controlling gene expression during a bioprocess enables real-time metabolic control, coordinated cellular responses, and staging order-of-operations. Achieving this with small molecule inducers is impractical at scale and dynamic circuits are difficult to design. Here, we show that the same set of sensors can be integrated by different combinatorial logic circuits to vary when genes are turned on and off during growth. Three Escherichia coli sensors that respond to the consumption of feedstock (glucose), dissolved oxygen, and by-product accumulation (acetate) are constructed and optimized. By integrating these sensors, logic circuits implement temporal control over an 18-h period. The circuit outputs are used to regulate endogenous enzymes at the transcriptional and post-translational level using CRISPRi and targeted proteolysis, respectively. As a demonstration, two circuits are designed to control acetate production by matching their dynamics to when endogenous genes are expressed (pta or poxB) and respond by turning off the corresponding gene. This work demonstrates how simple circuits can be implemented to enable customizable dynamic gene regulation.
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Affiliation(s)
- Felix Moser
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amin Espah Borujeni
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Amar N Ghodasara
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Ewen Cameron
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Yongjin Park
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
| | - Christopher A Voigt
- Department of Biological Engineering, Synthetic Biology Center, Massachusetts Institute of Technology, Cambridge, MA, USA
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