1
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Hamrick GS, Maddamsetti R, Son HI, Wilson ML, Davis HM, You L. Programming Dynamic Division of Labor Using Horizontal Gene Transfer. ACS Synth Biol 2024; 13:1142-1151. [PMID: 38568420 DOI: 10.1021/acssynbio.3c00615] [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: 04/16/2024]
Abstract
The metabolic engineering of microbes has broad applications, including biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multistep pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is the division of labor (DOL) in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted interstrain population dynamics. Through modeling, we show that dynamic division of labor (DDOL), which we define as the DOL between indiscrete populations capable of dynamic and reversible interchange, can overcome these limitations and enable the robust maintenance of burdensome, multistep pathways. We propose that DDOL can be mediated by horizontal gene transfer (HGT) and use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.
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Affiliation(s)
- Grayson S Hamrick
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
- Center for Biomolecular and Tissue Engineering, Duke University, Durham, North Carolina 27708, United States
| | - Rohan Maddamsetti
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Hye-In Son
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Maggie L Wilson
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Harris M Davis
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, North Carolina 27708, United States
- Center for Quantitative Biodesign, Duke University, Durham, North Carolina 27708, United States
- Center for Biomolecular and Tissue Engineering, Duke University, Durham, North Carolina 27708, United States
- Department of Molecular Genetics and Microbiology, Duke University School of Medicine, Durham, North Carolina 27708, United States
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2
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Mousavi R, Lobo D. Automatic design of gene regulatory mechanisms for spatial pattern formation. NPJ Syst Biol Appl 2024; 10:35. [PMID: 38565850 PMCID: PMC10987498 DOI: 10.1038/s41540-024-00361-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2023] [Accepted: 03/19/2024] [Indexed: 04/04/2024] Open
Abstract
Gene regulatory mechanisms (GRMs) control the formation of spatial and temporal expression patterns that can serve as regulatory signals for the development of complex shapes. Synthetic developmental biology aims to engineer such genetic circuits for understanding and producing desired multicellular spatial patterns. However, designing synthetic GRMs for complex, multi-dimensional spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given two-dimensional spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target spatial pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover complex genetic circuits producing spatial patterns.
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Affiliation(s)
- Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, Baltimore, MD, USA.
- Greenebaum Comprehensive Cancer Center and Center for Stem Cell Biology & Regenerative Medicine, University of Maryland, Baltimore, Baltimore, MD, USA.
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3
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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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4
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Steppe P, Rey-Bedón C, Kumar S, Forrest E, Van Der Wagt N, Tayal A, Tsimring L, Hasty J. Phenotypic Patterning through Copy Number Adaptation to Environmental Gradients. ACS Synth Biol 2024; 13:728-735. [PMID: 38330913 PMCID: PMC11048735 DOI: 10.1021/acssynbio.3c00617] [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] [Indexed: 02/10/2024]
Abstract
We recently described a paradigm for engineering bacterial adaptation using plasmids coupled to the same origin of replication. In this study, we use plasmid coupling to generate spatially separated and phenotypically distinct populations in response to heterogeneous environments. Using a custom microfluidic device, we continuously tracked engineered populations along induced gradients, enabling an in-depth analysis of the spatiotemporal dynamics of plasmid coupling. Our observations reveal a pronounced phenotypic separation within 4 h exposure to an opposing gradient of AHL and arabinose. Additionally, by modulating the burden strength balance between coupled plasmids, we demonstrate the inherent limitations and tunability of this system. Intriguingly, phenotypic separation persists for an extended time, hinting at a biophysical spatial retention mechanism reminiscent of natural speciation processes. Complementing our experimental data, mathematical models provide invaluable insights into the underlying mechanisms and guide optimization of plasmid coupling for prospective applications of environmental copy number adaptation engineering across separated domains.
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Affiliation(s)
- Paige Steppe
- Department of Bioengineering, University of California San Diego,
La Jolla, California 92093, United States
| | - Camilo Rey-Bedón
- Molecular Biology Section, Division of Biological Sciences,
University of California San Diego, La Jolla, California 92093, United
States
| | - Shalni Kumar
- Department of Bioengineering, University of California San Diego,
La Jolla, California 92093, United States
| | - Emerald Forrest
- Synthetic Biology Institute, University of California San Diego, La
Jolla, California 92093, United States
| | - Niklas Van Der Wagt
- Synthetic Biology Institute, University of California San Diego, La
Jolla, California 92093, United States
| | - Arnav Tayal
- Department of Bioengineering, University of California San Diego,
La Jolla, California 92093, United States
| | - Lev Tsimring
- Synthetic Biology Institute, University of California San Diego, La
Jolla, California 92093, United States
| | - Jeff Hasty
- Department of Bioengineering, University of California San Diego,
La Jolla, California 92093, United States; Molecular Biology Section,
Division of Biological Sciences and Synthetic Biology Institute, University
of California San Diego, La Jolla, California 92093, United States
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5
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Lam C, Morsut L. Programming Juxtacrine-Based Synthetic Signaling Networks in a Cellular Potts Framework. Methods Mol Biol 2024; 2760:283-307. [PMID: 38468095 DOI: 10.1007/978-1-0716-3658-9_17] [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
Synthetic development is a synthetic biology subfield aiming to reprogram higher-order eukaryotic cells for tissue formation and morphogenesis. Reprogramming efforts commonly rely upon implementing custom signaling networks into these cells, but the efficient design of these signaling networks is a substantial challenge. It is difficult to predict the tissue/morphogenic outcome of these networks, and in vitro testing of many networks is both costly and time-consuming. We therefore developed a computational framework with an in silico cell line (ISCL) that sports basic but modifiable features such as adhesion, motility, growth, and division. More importantly, ISCL can be quickly engineered with custom genetic circuits to test, improve, and explore different signaling network designs. We implemented this framework in a free cellular Potts modeling software CompuCell3D. In this chapter, we briefly discuss how to start with CompuCell3D and then go through the steps of how to make and modify ISCL. We then go through the steps of programming custom genetic circuits into ISCL to generate an example signaling network.
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Affiliation(s)
- Calvin Lam
- Department of Biochemistry and Molecular Biology, University of Nebraska Medical Center, Omaha, NE, USA.
| | - Leonardo Morsut
- The Eli and Edythe Broad CIRM Center, Department of Stem Cell Biology and Regenerative Medicine, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA
- Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, CA, USA
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6
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Hamrick GS, Maddamsetti R, Son HI, Wilson ML, Davis HM, You L. Programming dynamic division of labor using horizontal gene transfer. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.10.03.560696. [PMID: 37873187 PMCID: PMC10592921 DOI: 10.1101/2023.10.03.560696] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/25/2023]
Abstract
The metabolic engineering of microbes has broad applications, including in biomanufacturing, bioprocessing, and environmental remediation. The introduction of a complex, multi-step pathway often imposes a substantial metabolic burden on the host cell, restraining the accumulation of productive biomass and limiting pathway efficiency. One strategy to alleviate metabolic burden is division of labor (DOL), in which different subpopulations carry out different parts of the pathway and work together to convert a substrate into a final product. However, the maintenance of different engineered subpopulations is challenging due to competition and convoluted inter-strain population dynamics. Through modeling, we show that dynamic division of labor (DDOL) mediated by horizontal gene transfer (HGT) can overcome these limitations and enable the robust maintenance of burdensome, multi-step pathways. We also use plasmid genomics to uncover evidence that DDOL is a strategy utilized by natural microbial communities. Our work suggests that bioengineers can harness HGT to stabilize synthetic metabolic pathways in microbial communities, enabling the development of robust engineered systems for deployment in a variety of contexts.
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7
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Simpson K, L'Homme A, Keymer J, Federici F. Spatial biology of Ising-like synthetic genetic networks. BMC Biol 2023; 21:185. [PMID: 37667283 PMCID: PMC10478219 DOI: 10.1186/s12915-023-01681-4] [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: 12/20/2022] [Accepted: 08/11/2023] [Indexed: 09/06/2023] Open
Abstract
BACKGROUND Understanding how spatial patterns of gene expression emerge from the interaction of individual gene networks is a fundamental challenge in biology. Developing a synthetic experimental system with a common theoretical framework that captures the emergence of short- and long-range spatial correlations (and anti-correlations) from interacting gene networks could serve to uncover generic scaling properties of these ubiquitous phenomena. RESULTS Here, we combine synthetic biology, statistical mechanics models, and computational simulations to study the spatial behavior of synthetic gene networks (SGNs) in Escherichia coli quasi-2D colonies growing on hard agar surfaces. Guided by the combined mechanisms of the contact process lattice simulation and two-dimensional Ising model (CPIM), we describe the spatial behavior of bi-stable and chemically coupled SGNs that self-organize into patterns of long-range correlations with power-law scaling or short-range anti-correlations. These patterns, resembling ferromagnetic and anti-ferromagnetic configurations of the Ising model near critical points, maintain their scaling properties upon changes in growth rate and cell shape. CONCLUSIONS Our findings shed light on the spatial biology of coupled and bistable gene networks in growing cell populations. This emergent spatial behavior could provide insights into the study and engineering of self-organizing gene patterns in eukaryotic tissues and bacterial consortia.
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Affiliation(s)
- Kevin Simpson
- ANID - Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio), Santiago, Chile
| | - Alfredo L'Homme
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Juan Keymer
- Institute for Advanced Studies, Shenzhen X-Institute, Shenzhen, China.
- Schools of Physics and Biology, Pontificia Universidad Católica de Chile, Santiago, Chile.
- Department of Natural Sciences and Technology, Universidad de Aysén, Coyhaique, Chile.
| | - Fernán Federici
- ANID - Millennium Science Initiative Program, Millennium Institute for Integrative Biology (iBio), Santiago, Chile.
- Institute for Biological and Medical Engineering, Schools of Engineering, Medicine and Biological Sciences, Pontificia Universidad Católica de Chile, Santiago, Chile.
- FONDAP Center for Genome Regulation - Department of Molecular Genetics and Microbiology, Pontificia Universidad Católica de Chile, Santiago, Chile.
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8
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Mousavi R, Lobo D. Automatic design of gene regulatory mechanisms for spatial pattern formation. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.07.26.550573. [PMID: 37546866 PMCID: PMC10402059 DOI: 10.1101/2023.07.26.550573] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 08/08/2023]
Abstract
Synthetic developmental biology aims to engineer gene regulatory mechanisms (GRMs) for understanding and producing desired multicellular patterns and shapes. However, designing GRMs for spatial patterns is a current challenge due to the nonlinear interactions and feedback loops in genetic circuits. Here we present a methodology to automatically design GRMs that can produce any given spatial pattern. The proposed approach uses two orthogonal morphogen gradients acting as positional information signals in a multicellular tissue area or culture, which constitutes a continuous field of engineered cells implementing the same designed GRM. To efficiently design both the circuit network and the interaction mechanisms-including the number of genes necessary for the formation of the target pattern-we developed an automated algorithm based on high-performance evolutionary computation. The tolerance of the algorithm can be configured to design GRMs that are either simple to produce approximate patterns or complex to produce precise patterns. We demonstrate the approach by automatically designing GRMs that can produce a diverse set of synthetic spatial expression patterns by interpreting just two orthogonal morphogen gradients. The proposed framework offers a versatile approach to systematically design and discover pattern-producing genetic circuits.
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Affiliation(s)
- Reza Mousavi
- Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
| | - Daniel Lobo
- Department of Biological Sciences, University of Maryland, Baltimore County, 1000 Hilltop Circle, Baltimore, MD 21250, USA
- Greenebaum Comprehensive Cancer Center and Center for Stem Cell Biology & Regenerative Medicine, University of Maryland, School of Medicine, 22 S. Greene Street, Baltimore, MD 21201, USA
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9
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Santos-Moreno J, Tasiudi E, Kusumawardhani H, Stelling J, Schaerli Y. Robustness and innovation in synthetic genotype networks. Nat Commun 2023; 14:2454. [PMID: 37117168 PMCID: PMC10147661 DOI: 10.1038/s41467-023-38033-3] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/11/2022] [Accepted: 04/13/2023] [Indexed: 04/30/2023] Open
Abstract
Genotype networks are sets of genotypes connected by small mutational changes that share the same phenotype. They facilitate evolutionary innovation by enabling the exploration of different neighborhoods in genotype space. Genotype networks, first suggested by theoretical models, have been empirically confirmed for proteins and RNAs. Comparative studies also support their existence for gene regulatory networks (GRNs), but direct experimental evidence is lacking. Here, we report the construction of three interconnected genotype networks of synthetic GRNs producing three distinct phenotypes in Escherichia coli. Our synthetic GRNs contain three nodes regulating each other by CRISPR interference and governing the expression of fluorescent reporters. The genotype networks, composed of over twenty different synthetic GRNs, provide robustness in face of mutations while enabling transitions to innovative phenotypes. Through realistic mathematical modeling, we quantify robustness and evolvability for the complete genotype-phenotype map and link these features mechanistically to GRN motifs. Our work thereby exemplifies how GRN evolution along genotype networks might be driving evolutionary innovation.
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Affiliation(s)
- Javier Santos-Moreno
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015, Lausanne, Switzerland
- Department of Medicine and Life Sciences, Pompeu Fabra University, 00803, Barcelona, Spain
| | - Eve Tasiudi
- Department of Biosystems Science and Engineering, ETH Zurich and SIB Swiss Institute of Bioinformatics, Basel, Switzerland
| | - Hadiastri Kusumawardhani
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015, Lausanne, Switzerland
| | - Joerg Stelling
- Department of Biosystems Science and Engineering, ETH Zurich and SIB Swiss Institute of Bioinformatics, Basel, Switzerland.
| | - Yolanda Schaerli
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015, Lausanne, Switzerland.
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10
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Synthetic biology-inspired cell engineering in diagnosis, treatment, and drug development. Signal Transduct Target Ther 2023; 8:112. [PMID: 36906608 PMCID: PMC10007681 DOI: 10.1038/s41392-023-01375-x] [Citation(s) in RCA: 15] [Impact Index Per Article: 15.0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2022] [Revised: 01/31/2023] [Accepted: 02/15/2023] [Indexed: 03/13/2023] Open
Abstract
The fast-developing synthetic biology (SB) has provided many genetic tools to reprogram and engineer cells for improved performance, novel functions, and diverse applications. Such cell engineering resources can play a critical role in the research and development of novel therapeutics. However, there are certain limitations and challenges in applying genetically engineered cells in clinical practice. This literature review updates the recent advances in biomedical applications, including diagnosis, treatment, and drug development, of SB-inspired cell engineering. It describes technologies and relevant examples in a clinical and experimental setup that may significantly impact the biomedicine field. At last, this review concludes the results with future directions to optimize the performances of synthetic gene circuits to regulate the therapeutic activities of cell-based tools in specific diseases.
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11
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Luo J, Chen J, Huang Y, You L, Dai Z. Engineering living materials by synthetic biology. BIOPHYSICS REVIEWS 2023; 4:011305. [PMID: 38505813 PMCID: PMC10903423 DOI: 10.1063/5.0115645] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/27/2022] [Accepted: 11/18/2022] [Indexed: 03/21/2024]
Abstract
Natural biological materials are programmed by genetic information and able to self-organize, respond to environmental stimulus, and couple with inorganic matter. Inspired by the natural system and to mimic their complex and delicate fabrication process and functions, the field of engineered living materials emerges at the interface of synthetic biology and materials science. Here, we review the recent efforts and discuss the challenges and future opportunities.
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Affiliation(s)
- Jiren Luo
- Materials Synthetic Biology Center, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Jiangfeng Chen
- Materials Synthetic Biology Center, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Yaoge Huang
- Materials Synthetic Biology Center, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, North Carolina, 27708, USA
| | - Zhuojun Dai
- Materials Synthetic Biology Center, CAS Key Laboratory of Quantitative Engineering Biology, Guangdong Provincial Key Laboratory of Synthetic Genomics, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China
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12
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Winkens M, Korevaar PA. Self-Organization Emerging from Marangoni and Elastocapillary Effects Directed by Amphiphile Filament Connections. LANGMUIR : THE ACS JOURNAL OF SURFACES AND COLLOIDS 2022; 38:10799-10809. [PMID: 36005886 PMCID: PMC9454263 DOI: 10.1021/acs.langmuir.2c01241] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/14/2022] [Revised: 08/06/2022] [Indexed: 05/29/2023]
Abstract
Self-organization of meso- and macroscale structures is a highly active research field that exploits a wide variety of physicochemical phenomena, including surface tension, Marangoni flow, and (elasto)capillary effects. The release of surface-active compounds generates Marangoni flows that cause repulsion, whereas capillary forces attract floating particles via the Cheerios effect. Typically, the interactions resulting from these effects are nonselective because the gradients involved are uniform. In this work, we unravel the mechanisms involved in the self-organization of amphiphile filaments that connect and attract droplets floating at the air-water interface, and we demonstrate their potential for directional gradient formation and thereby selective interaction. We simulate Marangoni flow patterns resulting from the release and depletion of amphiphile molecules by source and drain droplets, respectively, and we predict that these flow patterns direct the growth of filaments from the source droplets toward specific drain droplets, based on their amphiphile depletion rate. The interaction between such droplets is then investigated experimentally by charting the flow patterns in their surroundings, while the role of filaments in source-drain attraction is studied using microscopy. Based on these observations, we attribute attraction of drain droplets and even solid objects toward the source to elastocapillary effects. Finally, the insights from our simulations and experiments are combined to construct a droplet-based system in which the composition of drain droplets regulates their ability to attract filaments and as a consequence be attracted toward the source. Thereby, we provide a novel method through which directional attraction can be established in synthetic self-organizing systems and advance our understanding of how complexity arises from simple building blocks.
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13
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Abstract
Bacterial proteases are a promising post-translational regulation strategy in synthetic circuits because they recognize specific amino acid degradation tags (degrons) that can be fine-tuned to modulate the degradation levels of tagged proteins. For this reason, recent efforts have been made in the search for new degrons. Here we review the up-to-date applications of degradation tags for circuit engineering in bacteria. In particular, we pay special attention to the effects of degradation bottlenecks in synthetic oscillators and introduce mathematical approaches to study queueing that enable the quantitative modelling of proteolytic queues.
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Affiliation(s)
- Prajakta Jadhav
- Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USA
| | - Yanyan Chen
- Program for Computational and Systems Biology, Memorial Sloan Kettering Cancer Center, New York, NY, USA
| | - Nicholas Butzin
- Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USA
| | - Javier Buceta
- Institute for Integrative Systems Biology (I2SysBio, CSIC-UV), Paterna, Valencia 46980, Spain
| | - Arantxa Urchueguía
- Department of Biology and Microbiology, South Dakota State University, Brookings, SD, USA.,Institute for Integrative Systems Biology (I2SysBio, CSIC-UV), Paterna, Valencia 46980, Spain
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14
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Escárcega-Bobadilla MV, Maldonado-Domínguez M, Romero-Ávila M, Zelada-Guillén GA. Turing patterns by supramolecular self-assembly of a single salphen building block. iScience 2022; 25:104545. [PMID: 35747384 PMCID: PMC9209723 DOI: 10.1016/j.isci.2022.104545] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2022] [Revised: 05/15/2022] [Accepted: 06/02/2022] [Indexed: 11/02/2022] Open
Abstract
In the 1950s, Alan Turing showed that concerted reactions and diffusion of activating and inhibiting chemical species can autonomously generate patterns without previous positional information, thus providing a chemical basis for morphogenesis in Nature. However, access to these patterns from only one molecular component that contained all the necessary information to execute agonistic and antagonistic signaling is so far an elusive goal, since two or more participants with different diffusivities are a must. Here, we report on a single-molecule system that generates Turing patterns arrested in the solid state, where supramolecular interactions are used instead of chemical reactions, whereas diffusional differences arise from heterogeneously populated self-assembled products. We employ a family of hydroxylated organic salphen building blocks based on a bis-Schiff-base scaffold with portions responsible for either activation or inhibition of assemblies at different hierarchies through purely supramolecular reactions, only depending upon the solvent dielectric constant and evaporation as fuel.
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Affiliation(s)
- Martha V Escárcega-Bobadilla
- School of Chemistry, National Autonomous University of Mexico (UNAM), Circuito Escolar s/n, Ciudad Universitaria, 04510 Mexico City, Mexico
| | - Mauricio Maldonado-Domínguez
- School of Chemistry, National Autonomous University of Mexico (UNAM), Circuito Escolar s/n, Ciudad Universitaria, 04510 Mexico City, Mexico.,Department of Computational Chemistry, J. Heyrovský Institute of Physical Chemistry, The Czech Academy of Sciences, Dolejškova 3, 18223 Prague 8, Czech Republic
| | - Margarita Romero-Ávila
- School of Chemistry, National Autonomous University of Mexico (UNAM), Circuito Escolar s/n, Ciudad Universitaria, 04510 Mexico City, Mexico
| | - Gustavo A Zelada-Guillén
- School of Chemistry, National Autonomous University of Mexico (UNAM), Circuito Escolar s/n, Ciudad Universitaria, 04510 Mexico City, Mexico
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15
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Programming and training rate-independent chemical reaction networks. Proc Natl Acad Sci U S A 2022; 119:e2111552119. [PMID: 35679345 PMCID: PMC9214506 DOI: 10.1073/pnas.2111552119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022] Open
Abstract
To program complex behavior in environments incompatible with electronic controllers such as within bioreactors or engineered cells, we turn to chemical information processors. While chemical reactions can perform computation in the stoichiometric exchange of reactants for products (how many molecules of which reactants result in how many molecules of which products), the control of reaction rates is usually thought to allow more complex computation. Motivated by the fact that correct stoichiometry is easier to ensure than reaction rates, we provide a method for programming and training chemical computation by stoichiometry. We show that such computation can be straightforwardly programmed in a manner analogous to sequential programming, and demonstrate the execution of neural networks capable of complex machine learning tasks. Embedding computation in biochemical environments incompatible with traditional electronics is expected to have a wide-ranging impact in synthetic biology, medicine, nanofabrication, and other fields. Natural biochemical systems are typically modeled by chemical reaction networks (CRNs) which can also be used as a specification language for synthetic chemical computation. In this paper, we identify a syntactically checkable class of CRNs called noncompetitive (NC) whose equilibria are absolutely robust to reaction rates and kinetic rate law, because their behavior is captured solely by their stoichiometric structure. In spite of the inherently parallel nature of chemistry, the robustness property allows for programming as if each reaction applies sequentially. We also present a technique to program NC-CRNs using well-founded deep learning methods, showing a translation procedure from rectified linear unit (ReLU) neural networks to NC-CRNs. In the case of binary weight ReLU networks, our translation procedure is surprisingly tight in the sense that a single bimolecular reaction corresponds to a single ReLU node and vice versa. This compactness argues that neural networks may be a fitting paradigm for programming rate-independent chemical computation. As proof of principle, we demonstrate our scheme with numerical simulations of CRNs translated from neural networks trained on traditional machine learning datasets, as well as tasks better aligned with potential biological applications including virus detection and spatial pattern formation.
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Update on the Development of Toehold Switch-Based Approach for Molecular Diagnostic Tests of COVID-19. J Nucleic Acids 2022; 2022:7130061. [PMID: 35586794 PMCID: PMC9110250 DOI: 10.1155/2022/7130061] [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: 02/18/2022] [Accepted: 04/22/2022] [Indexed: 11/18/2022] Open
Abstract
A high volume of diagnostic tests is needed during the coronavirus disease 2019 (COVID-19) pandemic to obtain representative results. These results can help to design and implement effective policies to prevent the spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Diagnosis using current gold standard methods, i.e., real-time quantitative PCR (RT-qPCR), is challenging, especially in areas with limited trained personnel and health-related infrastructure. The toehold switch-based diagnostic system is a promising alternative method for detecting SARS-CoV-2 that has advantages such as inexpensive cost per testing, rapid, and highly sensitive and specific analysis. Moreover, the system can be applied to paper-based platforms, simplifying the distribution and utilization in low-resource settings. This review provides insight into the development of toehold switch-based diagnostic devices as the most recent methods for detecting SARS-CoV-2.
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Dupin A, Aufinger L, Styazhkin I, Rothfischer F, Kaufmann BK, Schwarz S, Galensowske N, Clausen-Schaumann H, Simmel FC. Synthetic cell-based materials extract positional information from morphogen gradients. SCIENCE ADVANCES 2022; 8:eabl9228. [PMID: 35394842 PMCID: PMC8993112 DOI: 10.1126/sciadv.abl9228] [Citation(s) in RCA: 13] [Impact Index Per Article: 6.5] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Accepted: 02/17/2022] [Indexed: 05/19/2023]
Abstract
Biomaterials composed of synthetic cells have the potential to adapt and differentiate guided by physicochemical environmental cues. Inspired by biological systems in development, which extract positional information (PI) from morphogen gradients in the presence of uncertainties, we here investigate how well synthetic cells can determine their position within a multicellular structure. To calculate PI, we created and analyzed a large number of synthetic cellular assemblies composed of emulsion droplets connected via lipid bilayer membranes. These droplets contained cell-free feedback gene circuits that responded to gradients of a genetic inducer acting as a morphogen. PI is found to be limited by gene expression noise and affected by the temporal evolution of the morphogen gradient and the cell-free expression system itself. The generation of PI can be rationalized by computational modeling of the system. We scale our approach using three-dimensional printing and demonstrate morphogen-based differentiation in larger tissue-like assemblies.
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Affiliation(s)
- Aurore Dupin
- Physics Department (E14), TU Munich, 85748 Garching, Germany
| | - Lukas Aufinger
- Physics Department (E14), TU Munich, 85748 Garching, Germany
| | - Igor Styazhkin
- Physics Department (E14), TU Munich, 85748 Garching, Germany
| | | | - Benedikt K. Kaufmann
- Center for NanoScience (CeNS), Schellingstraße 4, 80799 Munich, Germany
- Center for Applied Tissue Engineering and Regenerative Medicine-CANTER, Munich University of Applied Sciences, Lothstrasse 34, 80335 Munich, Germany
- Heinz-Nixdorf-Chair of Biomedical Electronics, TranslaTUM, TU Munich, 81675 Munich, Germany
| | - Sascha Schwarz
- Center for NanoScience (CeNS), Schellingstraße 4, 80799 Munich, Germany
- Center for Applied Tissue Engineering and Regenerative Medicine-CANTER, Munich University of Applied Sciences, Lothstrasse 34, 80335 Munich, Germany
| | | | - Hauke Clausen-Schaumann
- Center for NanoScience (CeNS), Schellingstraße 4, 80799 Munich, Germany
- Center for Applied Tissue Engineering and Regenerative Medicine-CANTER, Munich University of Applied Sciences, Lothstrasse 34, 80335 Munich, Germany
| | - Friedrich C. Simmel
- Physics Department (E14), TU Munich, 85748 Garching, Germany
- Corresponding author.
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18
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Arboleda-Rivera JC, Machado-Rodríguez G, Rodríguez BA, Gutiérrez J. Elucidating multi-input processing 3-node gene regulatory network topologies capable of generating striped gene expression patterns. PLoS Comput Biol 2022; 18:e1009704. [PMID: 35157698 PMCID: PMC8880922 DOI: 10.1371/journal.pcbi.1009704] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2021] [Revised: 02/25/2022] [Accepted: 11/30/2021] [Indexed: 11/18/2022] Open
Abstract
A central problem in developmental and synthetic biology is understanding the mechanisms by which cells in a tissue or a Petri dish process external cues and transform such information into a coherent response, e.g., a terminal differentiation state. It was long believed that this type of positional information could be entirely attributed to a gradient of concentration of a specific signaling molecule (i.e., a morphogen). However, advances in experimental methodologies and computer modeling have demonstrated the crucial role of the dynamics of a cell’s gene regulatory network (GRN) in decoding the information carried by the morphogen, which is eventually translated into a spatial pattern. This morphogen interpretation mechanism has gained much attention in systems biology as a tractable system to investigate the emergent properties of complex genotype-phenotype maps. In this study, we apply a Markov chain Monte Carlo (MCMC)-like algorithm to probe the design space of three-node GRNs with the ability to generate a band-like expression pattern (target phenotype) in the middle of an arrangement of 30 cells, which resemble a simple (1-D) morphogenetic field in a developing embryo. Unlike most modeling studies published so far, here we explore the space of GRN topologies with nodes having the potential to perceive the same input signal differently. This allows for a lot more flexibility during the search space process, and thus enables us to identify a larger set of potentially interesting and realizable morphogen interpretation mechanisms. Out of 2061 GRNs selected using the search space algorithm, we found 714 classes of network topologies that could correctly interpret the morphogen. Notably, the main network motif that generated the target phenotype in response to the input signal was the type 3 Incoherent Feed-Forward Loop (I3-FFL), which agrees with previous theoretical expectations and experimental observations. Particularly, compared to a previously reported pattern forming GRN topologies, we have uncovered a great variety of novel network designs, some of which might be worth inquiring through synthetic biology methodologies to test for the ability of network design with minimal regulatory complexity to interpret a developmental cue robustly. Systems biology is a fast growing field largely powered by advances in high-performance computing and sophisticated mathematical modeling of biological systems. Based on these advances, we are now in a position to mechanistically understand and accurately predict the behavior of complex biological processes, including cell differentiation and spatial pattern formation during embryogenesis. In this article, we use an in silico approach to probe the design space of multi-input, three-node Gene Regulatory Networks (GRNs) capable of generating a striped gene expression pattern in the context of a simplified 1-D morphogenetic field.
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Affiliation(s)
- Juan Camilo Arboleda-Rivera
- Grupo de Fundamentos y Enseñanza de la Física y los Sistemas Dinámicos, Instituto de Biología, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Medellín, Colombia
- * E-mail:
| | - Gloria Machado-Rodríguez
- Grupo de Fundamentos y Enseñanza de la Física y los Sistemas Dinámicos, Instituto de Biología, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Medellín, Colombia
| | - Boris A. Rodríguez
- Grupo de Fundamentos y Enseñanza de la Física y los Sistemas Dinámicos, Instituto de Física, Facultad de Ciencias Exactas y Naturales, Universidad de Antioquia UdeA, Medellín, Colombia
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19
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Deneer A, Fleck C. Mathematical Modelling in Plant Synthetic Biology. Methods Mol Biol 2022; 2379:209-251. [PMID: 35188665 DOI: 10.1007/978-1-0716-1791-5_13] [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: 06/14/2023]
Abstract
Mathematical modelling techniques are integral to current research in plant synthetic biology. Modelling approaches can provide mechanistic understanding of a system, allowing predictions of behaviour and thus providing a tool to help design and analyse biological circuits. In this chapter, we provide an overview of mathematical modelling methods and their significance for plant synthetic biology. Starting with the basics of dynamics, we describe the process of constructing a model over both temporal and spatial scales and highlight crucial approaches, such as stochastic modelling and model-based design. Next, we focus on the model parameters and the techniques required in parameter analysis. We then describe the process of selecting a model based on tests and criteria and proceed to methods that allow closer analysis of the system's behaviour. Finally, we highlight the importance of uncertainty in modelling approaches and how to deal with a lack of knowledge, noisy data, and biological variability; all aspects that play a crucial role in the cooperation between the experimental and modelling components. Overall, this chapter aims to illustrate the importance of mathematical modelling in plant synthetic biology, providing an introduction for those researchers who are working with or working on modelling techniques.
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Affiliation(s)
- Anna Deneer
- Biometris, Department of Mathematical and Statistical Methods, Wageningen University, Wageningen, The Netherlands
| | - Christian Fleck
- ETH Zurich, Department of Biosystems Science and Engineering, Basel, Switzerland.
- Freiburg Institute for Data Analysis and Mathematical Modelling, University of Freiburg, Freiburg im Breisgau, Germany.
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20
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Vittadello ST, Leyshon T, Schnoerr D, Stumpf MPH. Turing pattern design principles and their robustness. PHILOSOPHICAL TRANSACTIONS. SERIES A, MATHEMATICAL, PHYSICAL, AND ENGINEERING SCIENCES 2021; 379:20200272. [PMID: 34743598 PMCID: PMC8580431 DOI: 10.1098/rsta.2020.0272] [Citation(s) in RCA: 18] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Accepted: 06/24/2021] [Indexed: 05/05/2023]
Abstract
Turing patterns have morphed from mathematical curiosities into highly desirable targets for synthetic biology. For a long time, their biological significance was sometimes disputed but there is now ample evidence for their involvement in processes ranging from skin pigmentation to digit and limb formation. While their role in developmental biology is now firmly established, their synthetic design has so far proved challenging. Here, we review recent large-scale mathematical analyses that have attempted to narrow down potential design principles. We consider different aspects of robustness of these models and outline why this perspective will be helpful in the search for synthetic Turing-patterning systems. We conclude by considering robustness in the context of developmental modelling more generally. This article is part of the theme issue 'Recent progress and open frontiers in Turing's theory of morphogenesis'.
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Affiliation(s)
- Sean T. Vittadello
- School of BioSciences, University of Melbourne, Melbourne, Victoria 3010, Australia
| | - Thomas Leyshon
- Department of Life Sciences, Imperial College London, London, UK
| | - David Schnoerr
- Department of Life Sciences, Imperial College London, London, UK
| | - Michael P. H. Stumpf
- School of BioSciences, University of Melbourne, Melbourne, Victoria 3010, Australia
- School of Mathematics and Statistics, University of Melbourne, Melbourne, Victoria 3010, Australia
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21
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Guiziou S, Chu JC, Nemhauser JL. Decoding and recoding plant development. PLANT PHYSIOLOGY 2021; 187:515-526. [PMID: 35237818 PMCID: PMC8491033 DOI: 10.1093/plphys/kiab336] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 03/02/2021] [Accepted: 06/26/2021] [Indexed: 05/04/2023]
Abstract
The development of multicellular organisms has been studied for centuries, yet many critical events and mechanisms of regulation remain challenging to observe directly. Early research focused on detailed observational and comparative studies. Molecular biology has generated insights into regulatory mechanisms, but only for a limited number of species. Now, synthetic biology is bringing these two approaches together, and by adding the possibility of sculpting novel morphologies, opening another path to understanding biology. Here, we review a variety of recently invented techniques that use CRISPR/Cas9 and phage integrases to trace the differentiation of cells over various timescales, as well as to decode the molecular states of cells in high spatiotemporal resolution. Most of these tools have been implemented in animals. The time is ripe for plant biologists to adopt and expand these approaches. Here, we describe how these tools could be used to monitor development in diverse plant species, as well as how they could guide efforts to recode programs of interest.
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Affiliation(s)
- Sarah Guiziou
- Department of Biology, University of Washington, Seattle, Washington 98195, USA
| | - Jonah C. Chu
- Department of Biology, University of Washington, Seattle, Washington 98195, USA
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22
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Ivanov I, Castellanos SL, Balasbas S, Otrin L, Marušič N, Vidaković-Koch T, Sundmacher K. Bottom-Up Synthesis of Artificial Cells: Recent Highlights and Future Challenges. Annu Rev Chem Biomol Eng 2021; 12:287-308. [PMID: 34097845 DOI: 10.1146/annurev-chembioeng-092220-085918] [Citation(s) in RCA: 17] [Impact Index Per Article: 5.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
The bottom-up approach in synthetic biology aims to create molecular ensembles that reproduce the organization and functions of living organisms and strives to integrate them in a modular and hierarchical fashion toward the basic unit of life-the cell-and beyond. This young field stands on the shoulders of fundamental research in molecular biology and biochemistry, next to synthetic chemistry, and, augmented by an engineering framework, has seen tremendous progress in recent years thanks to multiple technological and scientific advancements. In this timely review of the research over the past decade, we focus on three essential features of living cells: the ability to self-reproduce via recursive cycles of growth and division, the harnessing of energy to drive cellular processes, and the assembly of metabolic pathways. In addition, we cover the increasing efforts to establish multicellular systems via different communication strategies and critically evaluate the potential applications.
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Affiliation(s)
- Ivan Ivanov
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; , , , ,
| | - Sebastián López Castellanos
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; , , , ,
| | - Severo Balasbas
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; , , , ,
| | - Lado Otrin
- Electrochemical Energy Conversion, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; ,
| | - Nika Marušič
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; , , , ,
| | - Tanja Vidaković-Koch
- Electrochemical Energy Conversion, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; ,
| | - Kai Sundmacher
- Process Systems Engineering, Max Planck Institute for Dynamics of Complex Technical Systems, 39106 Magdeburg, Germany; , , , , .,Department of Process Systems Engineering, Otto-von-Guericke University Magdeburg, 39106 Magdeburg, Germany
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23
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Burgos-Morales O, Gueye M, Lacombe L, Nowak C, Schmachtenberg R, Hörner M, Jerez-Longres C, Mohsenin H, Wagner H, Weber W. Synthetic biology as driver for the biologization of materials sciences. Mater Today Bio 2021; 11:100115. [PMID: 34195591 PMCID: PMC8237365 DOI: 10.1016/j.mtbio.2021.100115] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/05/2021] [Revised: 05/16/2021] [Accepted: 05/18/2021] [Indexed: 01/16/2023] Open
Abstract
Materials in nature have fascinating properties that serve as a continuous source of inspiration for materials scientists. Accordingly, bio-mimetic and bio-inspired approaches have yielded remarkable structural and functional materials for a plethora of applications. Despite these advances, many properties of natural materials remain challenging or yet impossible to incorporate into synthetic materials. Natural materials are produced by living cells, which sense and process environmental cues and conditions by means of signaling and genetic programs, thereby controlling the biosynthesis, remodeling, functionalization, or degradation of the natural material. In this context, synthetic biology offers unique opportunities in materials sciences by providing direct access to the rational engineering of how a cell senses and processes environmental information and translates them into the properties and functions of materials. Here, we identify and review two main directions by which synthetic biology can be harnessed to provide new impulses for the biologization of the materials sciences: first, the engineering of cells to produce precursors for the subsequent synthesis of materials. This includes materials that are otherwise produced from petrochemical resources, but also materials where the bio-produced substances contribute unique properties and functions not existing in traditional materials. Second, engineered living materials that are formed or assembled by cells or in which cells contribute specific functions while remaining an integral part of the living composite material. We finally provide a perspective of future scientific directions of this promising area of research and discuss science policy that would be required to support research and development in this field.
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Affiliation(s)
- O. Burgos-Morales
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - M. Gueye
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
| | - L. Lacombe
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
| | - C. Nowak
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - R. Schmachtenberg
- École Supérieure de Biotechnologie de Strasbourg - ESBS, University of Strasbourg, Illkirch, 67412, France
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
| | - M. Hörner
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
| | - C. Jerez-Longres
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Spemann Graduate School of Biology and Medicine - SGBM, University of Freiburg, Freiburg, 79104, Germany
| | - H. Mohsenin
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
| | - H.J. Wagner
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Department of Biosystems Science and Engineering - D-BSSE, ETH Zurich, Basel, 4058, Switzerland
| | - W. Weber
- Faculty of Biology, University of Freiburg, Freiburg, 79104, Germany
- Signalling Research Centres BIOSS and CIBSS, University of Freiburg, Freiburg, 79104, Germany
- Spemann Graduate School of Biology and Medicine - SGBM, University of Freiburg, Freiburg, 79104, Germany
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24
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Genetic Network Architecture and Environmental Cues Drive Spatial Organization of Phenotypic Division of Labor in Streptomyces coelicolor. mBio 2021; 12:mBio.00794-21. [PMID: 34006658 PMCID: PMC8262882 DOI: 10.1128/mbio.00794-21] [Citation(s) in RCA: 12] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022] Open
Abstract
A number of bacteria are known to differentiate into cells with distinct phenotypic traits during processes such as biofilm formation or the development of reproductive structures. These cell types, by virtue of their specialized functions, embody a division of labor. However, how bacteria build spatial patterns of differentiated cells is not well understood. Here, we examine the factors that drive spatial patterns in divisions of labor in colonies of Streptomyces coelicolor, a multicellular bacterium capable of synthesizing an array of antibiotics and forming complex reproductive structures (e.g., aerial hyphae and spores). Using fluorescent reporters, we demonstrate that the pathways for antibiotic biosynthesis and aerial hypha formation are activated in distinct waves of gene expression that radiate outwards in S. coelicolor colonies. We also show that the spatiotemporal separation of these cell types depends on a key activator in the developmental pathway, AdpA. Importantly, when we manipulated local gradients by growing competing microbes nearby, or through physical disruption, expression in these pathways could be decoupled and/or disordered, respectively. Finally, the normal spatial organization of these cell types was partially restored with the addition of a siderophore, a public good made by these organisms, to the growth medium. Together, these results indicate that spatial divisions of labor in S. coelicolor colonies are determined by a combination of physiological gradients and regulatory network architecture, key factors that also drive patterns of cellular differentiation in multicellular eukaryotic organisms.
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Duran-Nebreda S, Pla J, Vidiella B, Piñero J, Conde-Pueyo N, Solé R. Synthetic Lateral Inhibition in Periodic Pattern Forming Microbial Colonies. ACS Synth Biol 2021; 10:277-285. [PMID: 33449631 PMCID: PMC8486170 DOI: 10.1021/acssynbio.0c00318] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
Abstract
Multicellular entities are characterized by intricate spatial patterns, intimately related to the functions they perform. These patterns are often created from isotropic embryonic structures, without external information cues guiding the symmetry breaking process. Mature biological structures also display characteristic scales with repeating distributions of signals or chemical species across space. Many candidate patterning modules have been used to explain processes during development and typically include a set of interacting and diffusing chemicals or agents known as morphogens. Great effort has been put forward to better understand the conditions in which pattern-forming processes can occur in the biological domain. However, evidence and practical knowledge allowing us to engineer symmetry-breaking is still lacking. Here we follow a different approach by designing a synthetic gene circuit in E. coli that implements a local activation long-range inhibition mechanism. The synthetic gene network implements an artificial differentiation process that changes the physicochemical properties of the agents. Using both experimental results and modeling, we show that the proposed system is capable of symmetry-breaking leading to regular spatial patterns during colony growth. Studying how these patterns emerge is fundamental to further our understanding of the evolution of biocomplexity and the role played by self-organization. The artificial system studied here and the engineering perspective on embryogenic processes can help validate developmental theories and identify universal properties underpinning biological pattern formation, with special interest for the area of synthetic developmental biology.
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Affiliation(s)
- Salva Duran-Nebreda
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Evolution of Technology Lab, Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
| | - Jordi Pla
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Blai Vidiella
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Jordi Piñero
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Nuria Conde-Pueyo
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
| | - Ricard Solé
- Institut de Biologia Evolutiva (CSIC-UPF), 08003 Barcelona, Spain
- ICREA-Complex Systems Lab, Universitat Pompeu Fabra, 08003 Barcelona, Spain
- Santa Fe Institute, 1399 Hyde Park Road, Santa Fe, New Mexico 87501, United States
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26
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Santos-Moreno J, Schaerli Y. CRISPR-based gene expression control for synthetic gene circuits. Biochem Soc Trans 2020; 48:1979-1993. [PMID: 32964920 PMCID: PMC7609024 DOI: 10.1042/bst20200020] [Citation(s) in RCA: 27] [Impact Index Per Article: 6.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/03/2020] [Revised: 08/27/2020] [Accepted: 08/28/2020] [Indexed: 12/22/2022]
Abstract
Synthetic gene circuits allow us to govern cell behavior in a programmable manner, which is central to almost any application aiming to harness engineered living cells for user-defined tasks. Transcription factors (TFs) constitute the 'classic' tool for synthetic circuit construction but some of their inherent constraints, such as insufficient modularity, orthogonality and programmability, limit progress in such forward-engineering endeavors. Here we review how CRISPR (clustered regularly interspaced short palindromic repeats) technology offers new and powerful possibilities for synthetic circuit design. CRISPR systems offer superior characteristics over TFs in many aspects relevant to a modular, predictable and standardized circuit design. Thus, the choice of CRISPR technology as a framework for synthetic circuit design constitutes a valid alternative to complement or replace TFs in synthetic circuits and promises the realization of more ambitious designs.
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Affiliation(s)
- Javier Santos-Moreno
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015 Lausanne, Switzerland
| | - Yolanda Schaerli
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015 Lausanne, Switzerland
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27
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Yáñez Feliú G, Vidal G, Muñoz Silva M, Rudge TJ. Novel Tunable Spatio-Temporal Patterns From a Simple Genetic Oscillator Circuit. Front Bioeng Biotechnol 2020; 8:893. [PMID: 33014996 PMCID: PMC7509427 DOI: 10.3389/fbioe.2020.00893] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/08/2020] [Accepted: 07/13/2020] [Indexed: 11/13/2022] Open
Abstract
Multicellularity, the coordinated collective behavior of cell populations, gives rise to the emergence of self-organized phenomena at many different spatio-temporal scales. At the genetic scale, oscillators are ubiquitous in regulation of multicellular systems, including during their development and regeneration. Synthetic biologists have successfully created simple synthetic genetic circuits that produce oscillations in single cells. Studying and engineering synthetic oscillators in a multicellular chassis can therefore give us valuable insights into how simple genetic circuits can encode complex multicellular behaviors at different scales. Here we develop a study of the coupling between the repressilator synthetic genetic ring oscillator and constraints on cell growth in colonies. We show in silico how mechanical constraints generate characteristic patterns of growth rate inhomogeneity in growing cell colonies. Next, we develop a simple one-dimensional model which predicts that coupling the repressilator to this pattern of growth rate via protein dilution generates traveling waves of gene expression. We show that the dynamics of these spatio-temporal patterns are determined by two parameters; the protein degradation and maximum expression rates of the repressors. We derive simple relations between these parameters and the key characteristics of the traveling wave patterns: firstly, wave speed is determined by protein degradation and secondly, wavelength is determined by maximum gene expression rate. Our analytical predictions and numerical results were in close quantitative agreement with detailed individual based simulations of growing cell colonies. Confirming published experimental results we also found that static ring patterns occur when protein stability is high. Our results show that this pattern can be induced simply by growth rate dilution and does not require transition to stationary phase as previously suggested. Our method generalizes easily to other genetic circuit architectures thus providing a framework for multi-scale rational design of spatio-temporal patterns from genetic circuits. We use this method to generate testable predictions for the synthetic biology design-build-test-learn cycle.
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Affiliation(s)
- Guillermo Yáñez Feliú
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Gonzalo Vidal
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Macarena Muñoz Silva
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
| | - Timothy J. Rudge
- Department of Chemical and Bioprocess Engineering, School of Engineering, Pontificia Universidad Católica de Chile, Santiago, Chile
- Institute for Biological and Medical Engineering, Schools of Engineering, Biology and Medicine, Pontificia Universidad Católica de Chile, Santiago, Chile
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28
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Abstract
Gene expression control based on CRISPRi (clustered regularly interspaced short palindromic repeats interference) has emerged as a powerful tool for creating synthetic gene circuits, both in prokaryotes and in eukaryotes; yet, its lack of cooperativity has been pointed out as a potential obstacle for dynamic or multistable synthetic circuit construction. Here we use CRISPRi to build a synthetic oscillator (“CRISPRlator”), bistable network (toggle switch) and stripe pattern-forming incoherent feed-forward loop (IFFL). Our circuit designs, conceived to feature high predictability and orthogonality, as well as low metabolic burden and context-dependency, allow us to achieve robust circuit behaviors in Escherichia coli populations. Mathematical modeling suggests that unspecific binding in CRISPRi is essential to establish multistability. Our work demonstrates the wide applicability of CRISPRi in synthetic circuits and paves the way for future efforts towards engineering more complex synthetic networks, boosted by the advantages of CRISPR technology. Synthetic circuits based on CRISPRi have not achieved multistable and dynamic behaviors. Here the authors build an oscillator, a toggle switch and an incoherent feed-forward loop using CRISPRi, and provide a mathematical model suggesting that unspecific binding in CRISPRi enables multistability.
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Barbier I, Perez‐Carrasco R, Schaerli Y. Controlling spatiotemporal pattern formation in a concentration gradient with a synthetic toggle switch. Mol Syst Biol 2020; 16:e9361. [PMID: 32529808 PMCID: PMC7290156 DOI: 10.15252/msb.20199361] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2019] [Revised: 04/29/2020] [Accepted: 05/08/2020] [Indexed: 11/20/2022] Open
Abstract
The formation of spatiotemporal patterns of gene expression is frequently guided by gradients of diffusible signaling molecules. The toggle switch subnetwork, composed of two cross-repressing transcription factors, is a common component of gene regulatory networks in charge of patterning, converting the continuous information provided by the gradient into discrete abutting stripes of gene expression. We present a synthetic biology framework to understand and characterize the spatiotemporal patterning properties of the toggle switch. To this end, we built a synthetic toggle switch controllable by diffusible molecules in Escherichia coli. We analyzed the patterning capabilities of the circuit by combining quantitative measurements with a mathematical reconstruction of the underlying dynamical system. The toggle switch can produce robust patterns with sharp boundaries, governed by bistability and hysteresis. We further demonstrate how the hysteresis, position, timing, and precision of the boundary can be controlled, highlighting the dynamical flexibility of the circuit.
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Affiliation(s)
- Içvara Barbier
- Department of Fundamental MicrobiologyUniversity of LausanneLausanneSwitzerland
| | - Rubén Perez‐Carrasco
- Department of Life SciencesImperial College LondonSouth Kensington CampusLondonUK
- Department of MathematicsUniversity College LondonLondonUK
| | - Yolanda Schaerli
- Department of Fundamental MicrobiologyUniversity of LausanneLausanneSwitzerland
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30
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Catalán P, Manrubia S, Cuesta JA. Populations of genetic circuits are unable to find the fittest solution in a multilevel genotype-phenotype map. J R Soc Interface 2020; 17:20190843. [PMID: 32486956 PMCID: PMC7328398 DOI: 10.1098/rsif.2019.0843] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2019] [Accepted: 05/12/2020] [Indexed: 01/13/2023] Open
Abstract
The evolution of gene regulatory networks (GRNs) is of great relevance for both evolutionary and synthetic biology. Understanding the relationship between GRN structure and its function can allow us to understand the selective pressures that have shaped a given circuit. This is especially relevant when considering spatio-temporal expression patterns, where GRN models have been shown to be extremely robust and evolvable. However, previous models that studied GRN evolution did not include the evolution of protein and genetic elements that underlie GRN architecture. Here we use toyLIFE, a multilevel genotype-phenotype map, to show that not all GRNs are equally likely in genotype space and that evolution is biased to find the most common GRNs. toyLIFE rules create Boolean GRNs that, embedded in a one-dimensional tissue, develop a variety of spatio-temporal gene expression patterns. Populations of toyLIFE organisms choose the most common GRN out of a set of equally fit alternatives and, most importantly, fail to find a target pattern when it is very rare in genotype space. Indeed, we show that the probability of finding the fittest phenotype increases dramatically with its abundance in genotype space. This phenotypic bias represents a mechanism that can prevent the fixation in the population of the fittest phenotype, one that is inherent to the structure of genotype space and the genotype-phenotype map.
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Affiliation(s)
- Pablo Catalán
- Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid, Spain
- Departamento de Matemáticas, Universidad Carlos III de Madrid, Leganés, Madrid, Spain
| | - Susanna Manrubia
- Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid, Spain
- Departamento de Biología de Sistemas, Centro Nacional de Biotecnología (CSIC), Madrid, Spain
| | - José A. Cuesta
- Grupo Interdisciplinar de Sistemas Complejos (GISC), Madrid, Spain
- Departamento de Matemáticas, Universidad Carlos III de Madrid, Leganés, Madrid, Spain
- Instituto de Biocomputación y Física de Sistemas Complejos (BIFI), Universidad de Zaragoza, Zaragoza, Spain
- UC3M-Santander Big Data Institute (IBiDat), Universidad Carlos III de Madrid, Getafe, Madrid, Spain
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31
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Landge AN, Jordan BM, Diego X, Müller P. Pattern formation mechanisms of self-organizing reaction-diffusion systems. Dev Biol 2020; 460:2-11. [PMID: 32008805 PMCID: PMC7154499 DOI: 10.1016/j.ydbio.2019.10.031] [Citation(s) in RCA: 61] [Impact Index Per Article: 15.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/26/2019] [Revised: 10/29/2019] [Accepted: 10/29/2019] [Indexed: 01/26/2023]
Abstract
Embryonic development is a largely self-organizing process, in which the adult body plan arises from a ball of cells with initially nearly equal potency. The reaction-diffusion theory first proposed by Alan Turing states that the initial symmetry in embryos can be broken by the interplay between two diffusible molecules, whose interactions lead to the formation of patterns. The reaction-diffusion theory provides a valuable framework for self-organized pattern formation, but it has been difficult to relate simple two-component models to real biological systems with multiple interacting molecular species. Recent studies have addressed this shortcoming and extended the reaction-diffusion theory to realistic multi-component networks. These efforts have challenged the generality of previous central tenets derived from the analysis of simplified systems and guide the way to a new understanding of self-organizing processes. Here, we discuss the challenges in modeling multi-component reaction-diffusion systems and how these have recently been addressed. We present a synthesis of new pattern formation mechanisms derived from these analyses, and we highlight the significance of reaction-diffusion principles for developmental and synthetic pattern formation.
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Affiliation(s)
- Amit N Landge
- Systems Biology of Development Group, Friedrich Miescher Laboratory of the Max Planck Society, 72076, Tübingen, Germany
| | - Benjamin M Jordan
- Department of Organismic and Evolutionary Biology, Harvard University, Cambridge, MA, 02143, USA
| | - Xavier Diego
- European Molecular Biology Laboratory, Barcelona Outstation, 08003 Barcelona, Spain
| | - Patrick Müller
- Systems Biology of Development Group, Friedrich Miescher Laboratory of the Max Planck Society, 72076, Tübingen, Germany; Modeling Tumorigenesis Group, Translational Oncology Division, Eberhard Karls University Tübingen, 72076, Tübingen, Germany.
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32
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Perkins ML, Benzinger D, Arcak M, Khammash M. Cell-in-the-loop pattern formation with optogenetically emulated cell-to-cell signaling. Nat Commun 2020; 11:1355. [PMID: 32170129 PMCID: PMC7069979 DOI: 10.1038/s41467-020-15166-3] [Citation(s) in RCA: 25] [Impact Index Per Article: 6.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2019] [Accepted: 02/11/2020] [Indexed: 12/22/2022] Open
Abstract
Designing and implementing synthetic biological pattern formation remains challenging due to underlying theoretical complexity as well as the difficulty of engineering multicellular networks biochemically. Here, we introduce a cell-in-the-loop approach where living cells interact through in silico signaling, establishing a new testbed to interrogate theoretical principles when internal cell dynamics are incorporated rather than modeled. We present an easy-to-use theoretical test to predict the emergence of contrasting patterns in gene expression among laterally inhibiting cells. Guided by the theory, we experimentally demonstrate spontaneous checkerboard patterning in an optogenetic setup, where cell-to-cell signaling is emulated with light inputs calculated in silico from real-time gene expression measurements. The scheme successfully produces spontaneous, persistent checkerboard patterns for systems of sixteen patches, in quantitative agreement with theoretical predictions. Our research highlights how tools from dynamical systems theory may inform our understanding of patterning, and illustrates the potential of cell-in-the-loop for engineering synthetic multicellular systems.
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Affiliation(s)
- Melinda Liu Perkins
- Department of Electrical Engineering, University of California, Berkeley, CA, USA.
| | - Dirk Benzinger
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland
| | - Murat Arcak
- Department of Electrical Engineering, University of California, Berkeley, CA, USA
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering, ETH Zürich, Basel, Switzerland.
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33
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Gaspar VM, Lavrador P, Borges J, Oliveira MB, Mano JF. Advanced Bottom-Up Engineering of Living Architectures. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2020; 32:e1903975. [PMID: 31823448 DOI: 10.1002/adma.201903975] [Citation(s) in RCA: 107] [Impact Index Per Article: 26.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/23/2019] [Revised: 08/30/2019] [Indexed: 05/08/2023]
Abstract
Bottom-up tissue engineering is a promising approach for designing modular biomimetic structures that aim to recapitulate the intricate hierarchy and biofunctionality of native human tissues. In recent years, this field has seen exciting progress driven by an increasing knowledge of biological systems and their rational deconstruction into key core components. Relevant advances in the bottom-up assembly of unitary living blocks toward the creation of higher order bioarchitectures based on multicellular-rich structures or multicomponent cell-biomaterial synergies are described. An up-to-date critical overview of long-term existing and rapidly emerging technologies for integrative bottom-up tissue engineering is provided, including discussion of their practical challenges and required advances. It is envisioned that a combination of cell-biomaterial constructs with bioadaptable features and biospecific 3D designs will contribute to the development of more robust and functional humanized tissues for therapies and disease models, as well as tools for fundamental biological studies.
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Affiliation(s)
- Vítor M Gaspar
- Department of Chemistry, CICECO - Aveiro Institute of Materials, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal
| | - Pedro Lavrador
- Department of Chemistry, CICECO - Aveiro Institute of Materials, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal
| | - João Borges
- Department of Chemistry, CICECO - Aveiro Institute of Materials, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal
| | - Mariana B Oliveira
- Department of Chemistry, CICECO - Aveiro Institute of Materials, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal
| | - João F Mano
- Department of Chemistry, CICECO - Aveiro Institute of Materials, University of Aveiro, Campus Universitário de Santiago, 3810-193, Aveiro, Portugal
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34
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Pseudomonas putida in the quest of programmable chemistry. Curr Opin Biotechnol 2019; 59:111-121. [DOI: 10.1016/j.copbio.2019.03.012] [Citation(s) in RCA: 32] [Impact Index Per Article: 6.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/17/2019] [Revised: 02/15/2019] [Accepted: 03/12/2019] [Indexed: 11/19/2022]
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35
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Santos-Moreno J, Schaerli Y. A Framework for the Modular and Combinatorial Assembly of Synthetic Gene Circuits. ACS Synth Biol 2019; 8:1691-1697. [PMID: 31185158 DOI: 10.1021/acssynbio.9b00174] [Citation(s) in RCA: 9] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/22/2022]
Abstract
Synthetic gene circuits emerge from iterative design-build-test cycles. Most commonly, the time-limiting step is the circuit construction process. Here, we present a hierarchical cloning scheme based on the widespread Gibson assembly method and make the set of constructed plasmids freely available. Our two-step modular cloning scheme allows for simple, fast, efficient, and accurate assembly of gene circuits and combinatorial circuit libraries in Escherichia coli. The first step involves Gibson assembly of transcriptional units from constituent parts into individual intermediate plasmids. In the second step, these plasmids are digested with specific sets of restriction enzymes. The resulting flanking regions have overlaps that drive a second Gibson assembly into a single plasmid to yield the final circuit. This approach substantially reduces time and sequencing costs associated with gene circuit construction and allows for modular and combinatorial assembly of circuits. We demonstrate the usefulness of our framework by assembling a CRISPR-based double-inverter circuit and a combinatorial library of 3-node networks.
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Affiliation(s)
- Javier Santos-Moreno
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015 Lausanne, Switzerland
| | - Yolanda Schaerli
- Department of Fundamental Microbiology, University of Lausanne, Biophore Building, 1015 Lausanne, Switzerland
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36
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Ebrahimkhani MR, Ebisuya M. Synthetic developmental biology: build and control multicellular systems. Curr Opin Chem Biol 2019; 52:9-15. [PMID: 31102790 DOI: 10.1016/j.cbpa.2019.04.006] [Citation(s) in RCA: 33] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/08/2019] [Revised: 04/03/2019] [Accepted: 04/09/2019] [Indexed: 02/08/2023]
Abstract
Synthetic biology offers a bottom-up engineering approach that intends to understand complex systems via design-build-test cycles. Embryonic development comprises complex processes that originate at the level of gene regulatory networks in a cell and emerge into collective cellular behaviors with multicellular forms and functions. Here, we review synthetic biology approaches to development that involve building de novo developmental trajectories or engineering control in stem cell-derived multicellular systems. The field of synthetic developmental biology is rapidly growing with the help of recent advances in artificial gene circuits, self-organizing organoids, and controllable tissue microenvironments. The outcome will be a blueprint to decode principles of morphogenesis and to create programmable organoids with novel designs or improved functions.
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Affiliation(s)
- Mo R Ebrahimkhani
- Biodesign Institute, Arizona State Tempe, AZ, USA; School of Biological and Health Systems Engineering, Arizona State Tempe, AZ, USA; Mayo Clinic College of Medicine and Science, Phoenix, AZ, USA.
| | - Miki Ebisuya
- European Molecular Biology Laboratory (EMBL) Barcelona, Dr. Aiguader, 88, 08003, Barcelona, Spain.
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