1
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Mao J, Zhang H, Chen Y, Wei L, Liu J, Nielsen J, Chen Y, Xu N. Relieving metabolic burden to improve robustness and bioproduction by industrial microorganisms. Biotechnol Adv 2024; 74:108401. [PMID: 38944217 DOI: 10.1016/j.biotechadv.2024.108401] [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: 02/01/2024] [Revised: 05/04/2024] [Accepted: 06/25/2024] [Indexed: 07/01/2024]
Abstract
Metabolic burden is defined by the influence of genetic manipulation and environmental perturbations on the distribution of cellular resources. The rewiring of microbial metabolism for bio-based chemical production often leads to a metabolic burden, followed by adverse physiological effects, such as impaired cell growth and low product yields. Alleviating the burden imposed by undesirable metabolic changes has become an increasingly attractive approach for constructing robust microbial cell factories. In this review, we provide a brief overview of metabolic burden engineering, focusing specifically on recent developments and strategies for diminishing the burden while improving robustness and yield. A variety of examples are presented to showcase the promise of metabolic burden engineering in facilitating the design and construction of robust microbial cell factories. Finally, challenges and limitations encountered in metabolic burden engineering are discussed.
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Affiliation(s)
- Jiwei Mao
- Department of Life Sciences, Chalmers University of Technology, SE412 96 Gothenburg, Sweden
| | - Hongyu Zhang
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, PR China
| | - Yu Chen
- Key Laboratory of Quantitative Synthetic Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, PR China
| | - Liang Wei
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China
| | - Jun Liu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China; Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China
| | - Jens Nielsen
- Department of Life Sciences, Chalmers University of Technology, SE412 96 Gothenburg, Sweden; BioInnovation Institute, Ole Maaløes Vej 3, DK2200 Copenhagen, Denmark.
| | - Yun Chen
- Department of Life Sciences, Chalmers University of Technology, SE412 96 Gothenburg, Sweden; Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK2800 Kongens Lyngby, Denmark.
| | - Ning Xu
- Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China; College of Life Sciences, University of Chinese Academy of Sciences, Beijing, 100049, PR China; Key Laboratory of Engineering Biology for Low-Carbon Manufacturing, Tianjin Institute of Industrial Biotechnology, Chinese Academy of Sciences, Tianjin 300308, PR China.
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2
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Ahmadi A, Courtney M, Ren C, Ingalls B. A benchmarked comparison of software packages for time-lapse image processing of monolayer bacterial population dynamics. Microbiol Spectr 2024; 12:e0003224. [PMID: 38980028 PMCID: PMC11302142 DOI: 10.1128/spectrum.00032-24] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2024] [Accepted: 04/26/2024] [Indexed: 07/10/2024] Open
Abstract
Time-lapse microscopy offers a powerful approach for analyzing cellular activity. In particular, this technique is valuable for assessing the behavior of bacterial populations, which can exhibit growth and intercellular interactions in a monolayer. Such time-lapse imaging typically generates large quantities of data, limiting the options for manual investigation. Several image-processing software packages have been developed to facilitate analysis. It can thus be a challenge to identify the software package best suited to a particular research goal. Here, we compare four software packages that support the analysis of 2D time-lapse images of cellular populations: CellProfiler, SuperSegger-Omnipose, DeLTA, and FAST. We compare their performance against benchmarked results on time-lapse observations of Escherichia coli populations. Performance varies across the packages, with each of the four outperforming the others in at least one aspect of the analysis. Not surprisingly, the packages that have been in development for longer showed the strongest performance. We found that deep learning-based approaches to object segmentation outperformed traditional approaches, but the opposite was true for frame-to-frame object tracking. We offer these comparisons, together with insight into usability, computational efficiency, and feature availability, as a guide to researchers seeking image-processing solutions. IMPORTANCE Time-lapse microscopy provides a detailed window into the world of bacterial behavior. However, the vast amount of data produced by these techniques is difficult to analyze manually. We have analyzed four software tools designed to process such data and compared their performance, using populations of commonly studied bacterial species as our test subjects. Our findings offer a roadmap to scientists, helping them choose the right tool for their research. This comparison bridges a gap between microbiology and computational analysis, streamlining research efforts.
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Affiliation(s)
- Atiyeh Ahmadi
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
| | - Matthew Courtney
- Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario, Canada
| | - Carolyn Ren
- Department of Mechanical and Mechatronics Engineering, University of Waterloo, Waterloo, Ontario, Canada
| | - Brian Ingalls
- Department of Biology, University of Waterloo, Waterloo, Ontario, Canada
- Department of Applied Mathematics, University of Waterloo, Waterloo, Ontario, Canada
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3
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Cole J, Schulman R. Limiting the Broadcast Range of a Secreting Cell during Intercellular Signaling Using Protease-Mediated Degradation. ACS Synth Biol 2024; 13:2019-2028. [PMID: 38885472 DOI: 10.1021/acssynbio.4c00042] [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: 06/20/2024]
Abstract
Synthetic biology is revolutionizing our approaches to biocomputing, diagnostics, and environmental monitoring through the use of designed genetic circuits that perform a function within a single cell. More complex functions can be performed by multiple cells that coordinate as they perform different subtasks. Cell-cell communication using molecular signals is particularly suited for aiding in this communication, but the number of molecules that can be used in different communication channels is limited. Here we investigate how proteases can limit the broadcast range of communicating cells. We find that adding barrierpepsin to Saccharomyces cerevisiae cells in two-dimensional multicellular networks that use α-factor signaling prevents cells beyond a specific radius from responding to α-factor signals. Such limiting of the broadcast range of cells could allow multiple cells to use the same signaling molecules to direct different communication processes and functions, provided that they are far enough from one another. These results suggest a means by which complex synthetic cellular networks using only a few signals for communication could be created by structuring a community of cells to create distinct broadcast environments.
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Affiliation(s)
- Joshua Cole
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
| | - Rebecca Schulman
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department of Computer Science, Johns Hopkins University, Baltimore, Maryland 21218, United States
- Department of Chemistry, Johns Hopkins University, Baltimore, Maryland 21218, United States
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4
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Chen YC, Destouches L, Cook A, Fedorec AJH. Synthetic microbial ecology: engineering habitats for modular consortia. J Appl Microbiol 2024; 135:lxae158. [PMID: 38936824 DOI: 10.1093/jambio/lxae158] [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: 04/27/2024] [Revised: 06/13/2024] [Accepted: 06/26/2024] [Indexed: 06/29/2024]
Abstract
Microbiomes, the complex networks of micro-organisms and the molecules through which they interact, play a crucial role in health and ecology. Over at least the past two decades, engineering biology has made significant progress, impacting the bio-based industry, health, and environmental sectors; but has only recently begun to explore the engineering of microbial ecosystems. The creation of synthetic microbial communities presents opportunities to help us understand the dynamics of wild ecosystems, learn how to manipulate and interact with existing microbiomes for therapeutic and other purposes, and to create entirely new microbial communities capable of undertaking tasks for industrial biology. Here, we describe how synthetic ecosystems can be constructed and controlled, focusing on how the available methods and interaction mechanisms facilitate the regulation of community composition and output. While experimental decisions are dictated by intended applications, the vast number of tools available suggests great opportunity for researchers to develop a diverse array of novel microbial ecosystems.
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Affiliation(s)
- Yue Casey Chen
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Louie Destouches
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Alice Cook
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
| | - Alex J H Fedorec
- Department of Cell and Developmental Biology, University College London, London WC1E 6BT, UK
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5
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Gao J, Gou Y, Huang L, Lian J. Reconstitution and optimization of complex plant natural product biosynthetic pathways in microbial expression systems. Curr Opin Biotechnol 2024; 87:103136. [PMID: 38705090 DOI: 10.1016/j.copbio.2024.103136] [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: 01/30/2024] [Revised: 03/24/2024] [Accepted: 04/12/2024] [Indexed: 05/07/2024]
Abstract
Plant natural products (PNPs) are a diverse group of chemical compounds synthesized by plants for various biological purposes and play a significant role in the fields of medicine, agriculture, and industry. In recent years, the development of synthetic biology promises the production of PNPs in microbial expression systems in a sustainable, low-cost, and large-scale manner. This review first introduces multiplex genome editing and PNP pathway assembly in microbial expression systems. Then recent technologies and examples geared toward improving PNP biosynthetic efficiency are discussed from three aspects: pathway optimization, chassis optimization, and modular coculture engineering. Finally, the review is concluded with future perspectives on the combination of machine learning and BioFoundry for the reconstitution and optimization of PNP microbial cell factories.
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Affiliation(s)
- Jucan Gao
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310000, China
| | - Yuanwei Gou
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310000, China
| | - Lei Huang
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310000, China
| | - Jiazhang Lian
- Key Laboratory of Biomass Chemical Engineering of Ministry of Education & National Key Laboratory of Biobased Transportation Fuel Technology, College of Chemical and Biological Engineering, Zhejiang University, Hangzhou 310027, China; ZJU-Hangzhou Global Scientific and Technological Innovation Center, Zhejiang University, Hangzhou 310000, China.
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6
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Song YM, Campbell S, Shiau L, Kim JK, Ott W. Noisy Delay Denoises Biochemical Oscillators. PHYSICAL REVIEW LETTERS 2024; 132:078402. [PMID: 38427894 DOI: 10.1103/physrevlett.132.078402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2023] [Accepted: 11/17/2023] [Indexed: 03/03/2024]
Abstract
Genetic oscillations are generated by delayed transcriptional negative feedback loops, wherein repressor proteins inhibit their own synthesis after a temporal production delay. This delay is distributed because it arises from a sequence of noisy processes, including transcription, translocation, translation, and folding. Because the delay determines repression timing and, therefore, oscillation period, it has been commonly believed that delay noise weakens oscillatory dynamics. Here, we demonstrate that noisy delay can surprisingly denoise genetic oscillators. Specifically, moderate delay noise improves the signal-to-noise ratio and sharpens oscillation peaks, all without impacting period and amplitude. We show that this denoising phenomenon occurs in a variety of well-studied genetic oscillators, and we use queueing theory to uncover the universal mechanisms that produce it.
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Affiliation(s)
- Yun Min Song
- Department of Mathematical Sciences, KAIST, Daejeon 34141, Republic of Korea
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Sean Campbell
- Department of Mathematics, University of Houston, Houston, Texas 77204, USA
| | - LieJune Shiau
- Department of Mathematics and Statistics, University of Houston Clear Lake, Houston, Texas 77058, USA
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, KAIST, Daejeon 34141, Republic of Korea
- Biomedical Mathematics Group, Pioneer Research Center for Mathematical and Computational Sciences, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - William Ott
- Department of Mathematics, University of Houston, Houston, Texas 77204, USA
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7
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Zeng M, Sarker B, Rondthaler SN, Vu V, Andrews LB. Identifying LasR Quorum Sensors with Improved Signal Specificity by Mapping the Sequence-Function Landscape. ACS Synth Biol 2024; 13:568-589. [PMID: 38206199 DOI: 10.1021/acssynbio.3c00543] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/12/2024]
Abstract
Programmable intercellular signaling using components of naturally occurring quorum sensing can allow for coordinated functions to be engineered in microbial consortia. LuxR-type transcriptional regulators are widely used for this purpose and are activated by homoserine lactone (HSL) signals. However, they often suffer from imperfect molecular discrimination of structurally similar HSLs, causing misregulation within engineered consortia containing multiple HSL signals. Here, we studied one such example, the regulator LasR from Pseudomonas aeruginosa. We elucidated its sequence-function relationship for ligand specificity using targeted protein engineering and multiplexed high-throughput biosensor screening. A pooled combinatorial saturation mutagenesis library (9,486 LasR DNA sequences) was created by mutating six residues in LasR's β5 sheet with single, double, or triple amino acid substitutions. Sort-seq assays were performed in parallel using cognate and noncognate HSLs to quantify each corresponding sensor's response to each HSL signal, which identified hundreds of highly specific variants. Sensor variants identified were individually assayed and exhibited up to 60.6-fold (p = 0.0013) improved relative activation by the cognate signal compared to the wildtype. Interestingly, we uncovered prevalent mutational epistasis and previously unidentified residues contributing to signal specificity. The resulting sensors with negligible signal crosstalk could be broadly applied to engineer bacteria consortia.
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Affiliation(s)
- Min Zeng
- Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
| | - Biprodev Sarker
- Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
| | - Stephen N Rondthaler
- Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
| | - Vanessa Vu
- Department of Biochemistry and Molecular Biology, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
| | - Lauren B Andrews
- Department of Chemical Engineering, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
- Molecular and Cellular Biology Graduate Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
- Biotechnology Training Program, University of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
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8
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Darvishi F, Rafatiyan S, Abbaspour Motlagh Moghaddam MH, Atkinson E, Ledesma-Amaro R. Applications of synthetic yeast consortia for the production of native and non-native chemicals. Crit Rev Biotechnol 2024; 44:15-30. [PMID: 36130800 DOI: 10.1080/07388551.2022.2118569] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/03/2022] [Revised: 08/03/2022] [Accepted: 08/19/2022] [Indexed: 11/03/2022]
Abstract
The application of microbial consortia is a new approach in synthetic biology. Synthetic yeast consortia, simple or complex synthetic mixed cultures, have been used for the production of various metabolites. Cooperation between the members of a consortium and cross-feeding can be applied to create stable microbial communication. These consortia can: consume a variety of substrates, perform more complex functions, produce metabolites in high titer, rate, and yield (TRY), and show higher stability during industrial fermentations. Due to the new research context of synthetic consortia, few yeasts were used to build these consortia, including Saccharomyces cerevisiae, Pichia pastoris, and Yarrowia lipolytica. Here, application of the yeasts for design of synthetic microbial consortia and their advantages and bottlenecks for effective and robust production of valuable metabolites from bioresource, including: cellulose, xylose, glycerol and so on, have been reviewed. Key trends and challenges are also discussed for the future development of synthetic yeast consortia.
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Affiliation(s)
- Farshad Darvishi
- Department of Microbiology, Faculty of Biological Sciences, Alzahra University, Tehran, Iran
- Research Center for Applied Microbiology and Microbial Biotechnology (CAMB), Alzahra University, Tehran, Iran
| | - Sajad Rafatiyan
- Department of Biotechnology, Faculty of Biological Science and Technology, University of Isfahan, Isfahan, Iran
| | | | - Eliza Atkinson
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
| | - Rodrigo Ledesma-Amaro
- Department of Bioengineering and Imperial College Centre for Synthetic Biology, Imperial College London, London, UK
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9
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Chen X, He C, Zhang Q, Bayakmetov S, Wang X. Modularized Design and Construction of Tunable Microbial Consortia with Flexible Topologies. ACS Synth Biol 2024; 13:183-194. [PMID: 38166159 PMCID: PMC10805104 DOI: 10.1021/acssynbio.3c00420] [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: 07/12/2023] [Revised: 11/17/2023] [Accepted: 11/20/2023] [Indexed: 01/04/2024]
Abstract
Complex and fluid bacterial community compositions are critical to diversity, stability, and function. However, quantitative and mechanistic descriptions of the dynamics of such compositions are still lacking. Here, we develop a modularized design framework that allows for bottom-up construction and the study of synthetic bacterial consortia with different topologies. We showcase the microbial consortia design and building process by constructing amensalism and competition consortia using only genetic circuit modules to engineer different strains to form the community. Functions of modules and hosting strains are validated and quantified to calibrate dynamic parameters, which are then directly fed into a full mechanistic model to accurately predict consortia composition dynamics for both amensalism and competition without further fitting. More importantly, such quantitative understanding successfully identifies the experimental conditions to achieve coexistence composition dynamics. These results illustrate the process of both computationally and experimentally building up bacteria consortia complexity and hence achieve robust control of such fluid systems.
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Affiliation(s)
- Xingwen Chen
- School
of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States
| | - Changhan He
- Department
of Mathematics, University of California
Irvine, Irvine, California 92697, United States
| | - Qi Zhang
- School
of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States
| | - Samat Bayakmetov
- School
of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States
| | - Xiao Wang
- School
of Biological and Health Systems Engineering, Arizona State University, Tempe, Arizona 85287, United States
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10
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Zeng M, Sarker B, Howitz N, Shah I, Andrews LB. Synthetic Homoserine Lactone Sensors for Gram-Positive Bacillus subtilis Using LuxR-Type Regulators. ACS Synth Biol 2024; 13:282-299. [PMID: 38079538 PMCID: PMC10805106 DOI: 10.1021/acssynbio.3c00504] [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: 08/18/2023] [Revised: 10/11/2023] [Accepted: 10/18/2023] [Indexed: 01/23/2024]
Abstract
A universal biochemical signal for bacterial cell-cell communication could facilitate programming dynamic responses in diverse bacterial consortia. However, the classical quorum sensing paradigm is that Gram-negative and Gram-positive bacteria generally communicate via homoserine lactones (HSLs) or oligopeptide molecular signals, respectively, to elicit population responses. Here, we create synthetic HSL sensors for Gram-positive Bacillus subtilis 168 using allosteric LuxR-type regulators (RpaR, LuxR, RhlR, and CinR) and synthetic promoters. Promoters were combinatorially designed from different sequence elements (-35, -16, -10, and transcriptional start regions). We quantified the effects of these combinatorial promoters on sensor activity and determined how regulator expression affects its activation, achieving up to 293-fold activation. Using the statistical design of experiments, we identified significant effects of promoter regions and pairwise interactions on sensor activity, which helped to understand the sequence-function relationships for synthetic promoter design. We present the first known set of functional HSL sensors (≥20-fold dynamic range) in B. subtilis for four different HSL chemical signals: p-coumaroyl-HSL, 3-oxohexanoyl-HSL, n-butyryl-HSL, and n-(3-hydroxytetradecanoyl)-HSL. This set of synthetic HSL sensors for a Gram-positive bacterium can pave the way for designable interspecies communication within microbial consortia.
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Affiliation(s)
- Min Zeng
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Biprodev Sarker
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Nathaniel Howitz
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Ishita Shah
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
| | - Lauren B. Andrews
- Department
of Chemical Engineering, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
- Molecular
and Cellular Biology Graduate Program, University
of Massachusetts Amherst, Amherst, Massachusetts 01003, United States
- Biotechnology
Training Program, University of Massachusetts
Amherst, Amherst, Massachusetts 01003, United States
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11
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Lyu X, Nuhu M, Candry P, Wolfanger J, Betenbaugh M, Saldivar A, Zuniga C, Wang Y, Shrestha S. Top-down and bottom-up microbiome engineering approaches to enable biomanufacturing from waste biomass. J Ind Microbiol Biotechnol 2024; 51:kuae025. [PMID: 39003244 PMCID: PMC11287213 DOI: 10.1093/jimb/kuae025] [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: 04/11/2024] [Accepted: 07/12/2024] [Indexed: 07/15/2024]
Abstract
Growing environmental concerns and the need to adopt a circular economy have highlighted the importance of waste valorization for resource recovery. Microbial consortia-enabled biotechnologies have made significant developments in the biomanufacturing of valuable resources from waste biomass that serve as suitable alternatives to petrochemical-derived products. These microbial consortia-based processes are designed following a top-down or bottom-up engineering approach. The top-down approach is a classical method that uses environmental variables to selectively steer an existing microbial consortium to achieve a target function. While high-throughput sequencing has enabled microbial community characterization, the major challenge is to disentangle complex microbial interactions and manipulate the structure and function accordingly. The bottom-up approach uses prior knowledge of the metabolic pathway and possible interactions among consortium partners to design and engineer synthetic microbial consortia. This strategy offers some control over the composition and function of the consortium for targeted bioprocesses, but challenges remain in optimal assembly methods and long-term stability. In this review, we present the recent advancements, challenges, and opportunities for further improvement using top-down and bottom-up approaches for microbiome engineering. As the bottom-up approach is relatively a new concept for waste valorization, this review explores the assembly and design of synthetic microbial consortia, ecological engineering principles to optimize microbial consortia, and metabolic engineering approaches for efficient conversion. Integration of top-down and bottom-up approaches along with developments in metabolic modeling to predict and optimize consortia function are also highlighted. ONE-SENTENCE SUMMARY This review highlights the microbial consortia-driven waste valorization for biomanufacturing through top-down and bottom-up design approaches and describes strategies, tools, and unexplored opportunities to optimize the design and stability of such consortia.
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Affiliation(s)
- Xuejiao Lyu
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Mujaheed Nuhu
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Pieter Candry
- Laboratory of Systems and Synthetic Biology, Wageningen University & Research, 6708 WE Wageningen, The Netherlands
| | - Jenna Wolfanger
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Michael Betenbaugh
- Department of Chemical and Biomolecular Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
| | - Alexis Saldivar
- Department of Biology, San Diego State University, San Diego, CA 92182-4614, USA
| | - Cristal Zuniga
- Department of Biology, San Diego State University, San Diego, CA 92182-4614, USA
| | - Ying Wang
- Department of Soil and Crop Sciences, Texas A&M University, TX 77843, USA
| | - Shilva Shrestha
- Department of Environmental Health and Engineering, Johns Hopkins University, Baltimore, MD 21218, USA
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12
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Zong DM, Sadeghpour M, Molinari S, Alnahhas RN, Hirning AJ, Giannitsis C, Ott W, Josić K, Bennett MR. Tunable Dynamics in a Multistrain Transcriptional Pulse Generator. ACS Synth Biol 2023; 12:3531-3543. [PMID: 38016068 DOI: 10.1021/acssynbio.3c00434] [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: 11/30/2023]
Abstract
One challenge in synthetic biology is the tuning of regulatory components within gene circuits to elicit a specific behavior. This challenge becomes more difficult in synthetic microbial consortia since each strain's circuit must function at the intracellular level and their combination must operate at the population level. Here we demonstrate that circuit dynamics can be tuned in synthetic consortia through the manipulation of strain fractions within the community. To do this, we construct a microbial consortium comprised of three strains of engineered Escherichia coli that, when cocultured, use homoserine lactone-mediated intercellular signaling to create a multistrain incoherent type-1 feedforward loop (I1-FFL). Like naturally occurring I1-FFL motifs in gene networks, this engineered microbial consortium acts as a pulse generator of gene expression. We demonstrate that the amplitude of the pulse can be easily tuned by adjusting the relative population fractions of the strains. We also develop a mathematical model for the temporal dynamics of the microbial consortium. This model allows us to identify population fractions that produced desired pulse characteristics, predictions that were confirmed for all but extreme fractions. Our work demonstrates that intercellular gene circuits can be effectively tuned simply by adjusting the starting fractions of each strain in the consortium.
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Affiliation(s)
- David M Zong
- Graduate Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, Texas 77005, United States
| | - Mehdi Sadeghpour
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
- Department of Mathematics, University of Houston, Houston, Texas 77004, United States
| | - Sara Molinari
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
| | - Razan N Alnahhas
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
| | - Andrew J Hirning
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
| | - Charilaos Giannitsis
- Graduate Program in Systems, Synthetic, and Physical Biology, Rice University, Houston, Texas 77005, United States
| | - William Ott
- Department of Mathematics, University of Houston, Houston, Texas 77004, United States
| | - Krešimir Josić
- Department of Mathematics, University of Houston, Houston, Texas 77004, United States
- Department of Biology and Biochemistry, University of Houston, Houston, Texas 77004, United States
| | - Matthew R Bennett
- Department of Biosciences, Rice University, Houston, Texas 77005, United States
- Department of Bioengineering, Rice University, Houston, Texas 77005, United States
- Rice Synthetic Biology Institute, Rice University, Houston, Texas 77005, United States
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13
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Ornelas MY, Cournoyer JE, Bram S, Mehta AP. Evolution and synthetic biology. Curr Opin Microbiol 2023; 76:102394. [PMID: 37801925 PMCID: PMC10842511 DOI: 10.1016/j.mib.2023.102394] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/19/2023] [Revised: 08/29/2023] [Accepted: 09/08/2023] [Indexed: 10/08/2023]
Abstract
Evolutionary observations have often served as an inspiration for biological design. Decoding of the central dogma of life at a molecular level and understanding of the cellular biochemistry have been elegantly used to engineer various synthetic biology applications, including building genetic circuits in vitro and in cells, building synthetic translational systems, and metabolic engineering in cells to biosynthesize and even bioproduce complex high-value molecules. Here, we review three broad areas of synthetic biology that are inspired by evolutionary observations: (i) combinatorial approaches toward cell-based biomolecular evolution, (ii) engineering interdependencies to establish microbial consortia, and (iii) synthetic immunology. In each of the areas, we will highlight the evolutionary premise that was central toward designing these platforms. These are only a subset of the examples where evolution and natural phenomena directly or indirectly serve as a powerful source of inspiration in shaping synthetic biology and biotechnology.
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Affiliation(s)
- Marya Y Ornelas
- Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S Matthews Avenue, Urbana, IL 61801, United States
| | - Jason E Cournoyer
- Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S Matthews Avenue, Urbana, IL 61801, United States
| | - Stanley Bram
- Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S Matthews Avenue, Urbana, IL 61801, United States
| | - Angad P Mehta
- Department of Chemistry, University of Illinois at Urbana-Champaign, 600 S Matthews Avenue, Urbana, IL 61801, United States; Institute for Genomic Biology, University of Illinois at Urbana, Champaign, United States; Cancer Center at Illinois, University of Illinois at Urbana, Champaign, United States.
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14
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Jiang Y, Wu R, Zhang W, Xin F, Jiang M. Construction of stable microbial consortia for effective biochemical synthesis. Trends Biotechnol 2023; 41:1430-1441. [PMID: 37330325 DOI: 10.1016/j.tibtech.2023.05.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/16/2023] [Revised: 04/25/2023] [Accepted: 05/19/2023] [Indexed: 06/19/2023]
Abstract
Microbial consortia can complete otherwise arduous tasks through the cooperation of multiple microbial species. This concept has been applied to produce commodity chemicals, natural products, and biofuels. However, metabolite incompatibility and growth competition can make the microbial composition unstable, and fluctuating microbial populations reduce the efficiency of chemical production. Thus, controlling the populations and regulating the complex interactions between different strains are challenges in constructing stable microbial consortia. This Review discusses advances in synthetic biology and metabolic engineering to control social interactions within microbial cocultures, including substrate separation, byproduct elimination, crossfeeding, and quorum-sensing circuit design. Additionally, this Review addresses interdisciplinary strategies to improve the stability of microbial consortia and provides design principles for microbial consortia to enhance chemical production.
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Affiliation(s)
- Yujia Jiang
- State Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, 211800, China.
| | - Ruofan Wu
- State Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, 211800, China
| | - Wenming Zhang
- State Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, 211800, China; Jiangsu Academy of Chemical Inherent Safety, Nanjing, 211800, China
| | - Fengxue Xin
- State Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, 211800, China; Jiangsu Academy of Chemical Inherent Safety, Nanjing, 211800, China.
| | - Min Jiang
- State Key Laboratory of Materials-Oriented Chemical Engineering, College of Biotechnology and Pharmaceutical Engineering, Nanjing Tech University, Nanjing, 211800, China; Jiangsu Academy of Chemical Inherent Safety, Nanjing, 211800, China
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15
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Landman J, Verduyn Lunel SM, Kegel WK. Transcription factor competition facilitates self-sustained oscillations in single gene genetic circuits. PLoS Comput Biol 2023; 19:e1011525. [PMID: 37773967 PMCID: PMC10566692 DOI: 10.1371/journal.pcbi.1011525] [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: 02/20/2023] [Revised: 10/11/2023] [Accepted: 09/18/2023] [Indexed: 10/01/2023] Open
Abstract
Genetic feedback loops can be used by cells to regulate internal processes or to keep track of time. It is often thought that, for a genetic circuit to display self-sustained oscillations, a degree of cooperativity is needed in the binding and unbinding of actor species. This cooperativity is usually modeled using a Hill function, regardless of the actual promoter architecture. Furthermore, genetic circuits do not operate in isolation and often transcription factors are shared between different promoters. In this work we show how mathematical modelling of genetic feedback loops can be facilitated with a mechanistic fold-change function that takes into account the titration effect caused by competing binding sites for transcription factors. The model shows how the titration effect facilitates self-sustained oscillations in a minimal genetic feedback loop: a gene that produces its own repressor directly without cooperative transcription factor binding. The use of delay-differential equations leads to a stability contour that predicts whether a genetic feedback loop will show self-sustained oscillations, even when taking the bursty nature of transcription into account.
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Affiliation(s)
- Jasper Landman
- Physics & Physical Chemistry of Foods, Wageningen University & Research, Wageningen, the Netherlands
| | | | - Willem K. Kegel
- Van ‘t Hoff Laboratory for Physical & Colloid Chemistry, Utrecht University, Utrecht, the Netherlands
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16
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Winkle JJ, Saha S, Essman J, Bennett MR, Ott W, Josić K, Mugler A. Signaling in microbial communities with open boundaries. Biophys J 2023; 122:2808-2817. [PMID: 37300250 PMCID: PMC10397789 DOI: 10.1016/j.bpj.2023.06.002] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Revised: 05/11/2023] [Accepted: 06/05/2023] [Indexed: 06/12/2023] Open
Abstract
Microbial communities such as swarms or biofilms often form at the interfaces of solid substrates and open fluid flows. At the same time, in laboratory environments these communities are commonly studied using microfluidic devices with media flows and open boundaries. Extracellular signaling within these communities is therefore subject to different constraints than signaling within classic, closed-boundary systems such as developing embryos or tissues, yet is understudied by comparison. Here, we use mathematical modeling to show how advective-diffusive boundary flows and population geometry impact cell-cell signaling in monolayer microbial communities. We reveal conditions where the intercellular signaling lengthscale depends solely on the population geometry and not on diffusion or degradation, as commonly expected. We further demonstrate that diffusive coupling with the boundary flow can produce signal gradients within an isogenic population, even when there is no flow within the population. We use our theory to provide new insights into the signaling mechanisms of published experimental results, and we make several experimentally verifiable predictions. Our research highlights the importance of carefully evaluating boundary dynamics and environmental geometry when modeling microbial cell-cell signaling and informs the study of cell behaviors in both natural and synthetic systems.
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Affiliation(s)
- James J Winkle
- Department of Mathematics, University of Houston, Houston, Texas
| | - Soutick Saha
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana
| | - Joseph Essman
- Department of BioSciences, Rice University, Houston, Texas
| | | | - William Ott
- Department of Mathematics, University of Houston, Houston, Texas.
| | - Krešimir Josić
- Department of Mathematics, University of Houston, Houston, Texas; Department of BioSciences, Rice University, Houston, Texas; Department of Biology and Biochemistry, University of Houston, Houston, Texas.
| | - Andrew Mugler
- Department of Physics and Astronomy, Purdue University, West Lafayette, Indiana; Department of Physics and Astronomy, University of Pittsburgh, Pittsburgh, Pennsylvania.
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17
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Jayanthi BE, Jayanthi S, Segatori L. Design of Oscillatory Networks through Post-Translational Control of Network Components. SYNTHETIC BIOLOGY AND ENGINEERING 2023; 1:10004. [PMID: 38590452 PMCID: PMC11000592 DOI: 10.35534/sbe.2023.10004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Indexed: 04/10/2024]
Abstract
Many essential functions in biological systems, including cell cycle progression and circadian rhythm regulation, are governed by the periodic behaviors of specific molecules. These periodic behaviors arise from the precise arrangement of components in biomolecular networks that generate oscillatory output signals. The dynamic properties of individual components of these networks, such as maturation delays and degradation rates, often play a key role in determining the network's oscillatory behavior. In this study, we explored the post-translational modulation of network components as a means to generate genetic circuits with oscillatory behaviors and perturb the oscillation features. Specifically, we used the NanoDeg platform-A bifunctional molecule consisting of a target-specific nanobody and a degron tag-to control the degradation rates of the circuit's components and predicted the effect of NanoDeg-mediated post-translational depletion of a key circuit component on the behavior of a series of proto-oscillating network topologies. We modeled the behavior of two main classes of oscillators, namely relaxation oscillator topologies (the activator-repressor and the Goodwin oscillator) and ring oscillator topologies (repressilators). We identified two main mechanisms by which non-oscillating networks could be induced to oscillate through post-translational modulation of network components: an increase in the separation of timescales of network components and mitigation of the leaky expression of network components. These results are in agreement with previous findings describing the effect of timescale separation and mitigation of leaky expression on oscillatory behaviors. This work thus validates the use of tools to control protein degradation rates as a strategy to modulate existing oscillatory signals and construct oscillatory networks. In addition, this study provides the design rules to implement such an approach based on the control of protein degradation rates using the NanoDeg platform, which does not require genetic manipulation of the network components and can be adapted to virtually any cellular protein. This work also establishes a framework to explore the use of tools for post-translational perturbations of biomolecular networks and generates desired behaviors of the network output.
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Affiliation(s)
- Brianna E.K. Jayanthi
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, Houston, TX 77005, USA
| | - Shridhar Jayanthi
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
| | - Laura Segatori
- Systems, Synthetic, and Physical Biology Graduate Program, Rice University, Houston, TX 77005, USA
- Department of Bioengineering, Rice University, Houston, TX 77005, USA
- Department of Chemical & Biomolecular Engineering, Rice University, Houston, TX 77005, USA
- Department of BioSciences, Rice University, Houston, TX 77005, USA
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18
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Sakkos JK, Santos-Merino M, Kokarakis EJ, Li B, Fuentes-Cabrera M, Zuliani P, Ducat DC. Predicting partner fitness based on spatial structuring in a light-driven microbial community. PLoS Comput Biol 2023; 19:e1011045. [PMID: 37134119 PMCID: PMC10184905 DOI: 10.1371/journal.pcbi.1011045] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Revised: 05/15/2023] [Accepted: 03/22/2023] [Indexed: 05/04/2023] Open
Abstract
Microbial communities have vital roles in systems essential to human health and agriculture, such as gut and soil microbiomes, and there is growing interest in engineering designer consortia for applications in biotechnology (e.g., personalized probiotics, bioproduction of high-value products, biosensing). The capacity to monitor and model metabolite exchange in dynamic microbial consortia can provide foundational information important to understand the community level behaviors that emerge, a requirement for building novel consortia. Where experimental approaches for monitoring metabolic exchange are technologically challenging, computational tools can enable greater access to the fate of both chemicals and microbes within a consortium. In this study, we developed an in-silico model of a synthetic microbial consortia of sucrose-secreting Synechococcus elongatus PCC 7942 and Escherichia coli W. Our model was built on the NUFEB framework for Individual-based Modeling (IbM) and optimized for biological accuracy using experimental data. We showed that the relative level of sucrose secretion regulates not only the steady-state support for heterotrophic biomass, but also the temporal dynamics of consortia growth. In order to determine the importance of spatial organization within the consortium, we fit a regression model to spatial data and used it to accurately predict colony fitness. We found that some of the critical parameters for fitness prediction were inter-colony distance, initial biomass, induction level, and distance from the center of the simulation volume. We anticipate that the synergy between experimental and computational approaches will improve our ability to design consortia with novel function.
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Affiliation(s)
- Jonathan K Sakkos
- Plant Research Laboratory, Michigan State University, East Lansing, Michigan, United States of America
| | - María Santos-Merino
- Plant Research Laboratory, Michigan State University, East Lansing, Michigan, United States of America
| | - Emmanuel J Kokarakis
- Plant Research Laboratory, Michigan State University, East Lansing, Michigan, United States of America
- Department of Microbiology & Molecular Genetics, Michigan State University, East Lansing, Michigan, United States of America
| | - Bowen Li
- School of Computing, Newcastle University, Newcastle upon Tyne, United Kingdom
| | - Miguel Fuentes-Cabrera
- Center for Nanophase Materials Sciences, Oak Ridge National Laboratory, Oak Ridge, Tennessee, United States of America
| | - Paolo Zuliani
- Dipartimento di Informatica, Università di Roma "La Sapienza", Rome, Italy
| | - Daniel C Ducat
- Plant Research Laboratory, Michigan State University, East Lansing, Michigan, United States of America
- Department of Biochemistry and Molecular Biology, Michigan State University, East Lansing, Michigan, United States of America
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19
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Marken JP, Murray RM. Addressable and adaptable intercellular communication via DNA messaging. Nat Commun 2023; 14:2358. [PMID: 37095088 PMCID: PMC10126159 DOI: 10.1038/s41467-023-37788-z] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/26/2022] [Accepted: 03/31/2023] [Indexed: 04/26/2023] Open
Abstract
Engineered consortia are a major research focus for synthetic biologists because they can implement sophisticated behaviors inaccessible to single-strain systems. However, this functional capacity is constrained by their constituent strains' ability to engage in complex communication. DNA messaging, by enabling information-rich channel-decoupled communication, is a promising candidate architecture for implementing complex communication. But its major advantage, its messages' dynamic mutability, is still unexplored. We develop a framework for addressable and adaptable DNA messaging that leverages all three of these advantages and implement it using plasmid conjugation in E. coli. Our system can bias the transfer of messages to targeted receiver strains by 100- to 1000-fold, and their recipient lists can be dynamically updated in situ to control the flow of information through the population. This work lays the foundation for future developments that further utilize the unique advantages of DNA messaging to engineer previously-inaccessible levels of complexity into biological systems.
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Affiliation(s)
- John P Marken
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA.
| | - Richard M Murray
- Division of Biology and Biological Engineering, California Institute of Technology, Pasadena, CA, USA
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20
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Prabhakar RG, Fan G, Alnahhas RN, Hirning AJ, Bennett MR, Shamoo Y. Indirect Enrichment of Desirable, but Less Fit Phenotypes, from a Synthetic Microbial Community Using Microdroplet Confinement. ACS Synth Biol 2023; 12:1239-1251. [PMID: 36929925 PMCID: PMC11259032 DOI: 10.1021/acssynbio.3c00008] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 03/18/2023]
Abstract
Spatial structure within microbial communities can provide nearly limitless opportunities for social interactions and are an important driver for evolution. As metabolites are often molecular signals, metabolite diffusion within microbial communities can affect the composition and dynamics of the community in a manner that can be challenging to deconstruct. We used encapsulation of a synthetic microbial community within microdroplets to investigate the effects of spatial structure and metabolite diffusion on population dynamics and to examine the effects of cheating by one member of the community. The synthetic community was composed of three strains: a "Producer" that makes the diffusible quorum sensing molecule (N-(3-oxododecanoyl)-l-homoserine lactone, C12-oxo-HSL) or AHL; a "Receiver" that is killed by AHL; and a Non-Producer or "cheater" that benefits from the extinction of the Receivers, but without the costs associated with the AHL synthesis. We demonstrate that despite rapid diffusion of AHL between microdroplets, the spatial structure imposed by the microdroplets allows a more efficient but transient enrichment of more rare and slower-growing Producer subpopulations. Eventually, the Non-Producer population drove the Producers to extinction. By including fluorescence-activated microdroplet sorting and providing sustained competition by the Receiver strain, we demonstrate a strategy for indirect enrichment of a rare and unlabeled Producer. The ability to screen and enrich metabolite Producers from a much larger population under conditions of rapid diffusion provides an important framework for the development of applications in synthetic ecology and biotechnology.
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Affiliation(s)
| | - Gaoyang Fan
- Department of Mathematics, University of Houston, Houston, Texas, 77204, United States
| | - Razan N Alnahhas
- Department of Biosciences, Rice University, Houston, Texas, 77005, United States
| | - Andrew J Hirning
- Department of Biosciences, Rice University, Houston, Texas, 77005, United States
| | - Matthew R Bennett
- Department of Biosciences, Rice University, Houston, Texas, 77005, United States
- Department of Bioengineering, Rice University, Houston, Texas, 77005, United States
| | - Yousif Shamoo
- Department of Biosciences, Rice University, Houston, Texas, 77005, United States
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21
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Winkle JJ, Saha S, Essman J, Bennett MR, Ott W, Josić K, Mugler A. Signaling in microbial communities with open boundaries. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.20.524904. [PMID: 36711825 PMCID: PMC9882294 DOI: 10.1101/2023.01.20.524904] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/23/2023]
Abstract
Microbial communities such as swarms or biofilms often form at the interfaces of solid substrates and open fluid flows. At the same time, in laboratory environments these communities are commonly studied using microfluidic devices with media flows and open boundaries. Extracellular signaling within these communities is therefore subject to different constraints than signaling within classic, closed-boundary systems such as developing embryos or tissues, yet is understudied by comparison. Here, we use mathematical modeling to show how advective-diffusive boundary flows and population geometry impact cell-cell signaling in monolayer microbial communities. We reveal conditions where the intercellular signaling lengthscale depends solely on the population geometry and not on diffusion or degradation, as commonly expected. We further demonstrate that diffusive coupling with the boundary flow can produce signal gradients within an isogenic population, even when there is no flow within the population. We use our theory to provide new insights into the signaling mechanisms of published experimental results, and we make several experimentally verifiable predictions. Our research highlights the importance of carefully evaluating boundary dynamics and environmental geometry when modeling microbial cell-cell signaling and informs the study of cell behaviors in both natural and synthetic systems.
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Affiliation(s)
| | - Soutick Saha
- Department of Physics and Astronomy, Purdue University
| | | | | | - William Ott
- Department of Mathematics, University of Houston,Correspondence: , , ,
| | - Krešimir Josić
- Department of Mathematics, University of Houston,Department of BioSciences, Rice University,Department of Biology and Biochemistry, University of Houston,Correspondence: , , ,
| | - Andrew Mugler
- Department of Physics and Astronomy, Purdue University,Department of Physics and Astronomy, University of Pittsburgh,Correspondence: , , ,
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22
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Kokarakis E, Rillema R, Ducat DC, Sakkos JK. Developing Cyanobacterial Quorum Sensing Toolkits: Toward Interspecies Coordination in Mixed Autotroph/Heterotroph Communities. ACS Synth Biol 2023; 12:265-276. [PMID: 36573789 PMCID: PMC9872165 DOI: 10.1021/acssynbio.2c00527] [Citation(s) in RCA: 3] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/06/2022] [Indexed: 12/28/2022]
Abstract
There has been substantial recent interest in the promise of sustainable, light-driven bioproduction using cyanobacteria, including developing efforts for microbial bioproduction using mixed autotroph/heterotroph communities, which could provide useful properties, such as division of metabolic labor. However, building stable mixed-species communities of sufficient productivity remains a challenge, partly due to the lack of strategies for synchronizing and coordinating biological activities across different species. To address this obstacle, we developed an inter-species communication system using quorum sensing (QS) modules derived from well-studied pathways in heterotrophic microbes. In the model cyanobacterium, Synechococcus elongatus PCC 7942 (S. elongatus), we designed, integrated, and characterized genetic circuits that detect acyl-homoserine lactones (AHLs), diffusible signals utilized in many QS pathways. We showed that these receiver modules sense exogenously supplied AHL molecules and activate gene expression in a dose-dependent manner. We characterized these AHL receiver circuits in parallel with Escherichia coli W (E. coli W) to dissect species-specific properties, finding broad agreement, albeit with increased basal expression in S. elongatus. Our engineered "sender" E. coli strains accumulated biologically synthesized AHLs within the supernatant and activated receiver strains similarly to exogenous AHL activation. Our results will bolster the design of sophisticated genetic circuits in cyanobacterial/heterotroph consortia and the engineering of QS-like behaviors across cyanobacterial populations.
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Affiliation(s)
- Emmanuel
J. Kokarakis
- Plant
Research Laboratory, Michigan State University, East Lansing, Michigan48824-1312, United States
- Department
of Microbiology & Molecular Genetics, Michigan State University, East Lansing, Michigan48824-1312, United States
| | - Rees Rillema
- Plant
Research Laboratory, Michigan State University, East Lansing, Michigan48824-1312, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan48824-1312, United States
| | - Daniel C. Ducat
- Plant
Research Laboratory, Michigan State University, East Lansing, Michigan48824-1312, United States
- Department
of Biochemistry and Molecular Biology, Michigan
State University, East Lansing, Michigan48824-1312, United States
| | - Jonathan K. Sakkos
- Plant
Research Laboratory, Michigan State University, East Lansing, Michigan48824-1312, United States
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23
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Prabhakar RG, Fan G, Alnahhas RN, Hirning AJ, Bennett MR, Shamoo Y. Indirect enrichment of desirable, but less fit phenotypes, from a synthetic microbial community using microdroplet confinement. BIORXIV : THE PREPRINT SERVER FOR BIOLOGY 2023:2023.01.11.523444. [PMID: 36711600 PMCID: PMC9882018 DOI: 10.1101/2023.01.11.523444] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Indexed: 01/13/2023]
Abstract
Spatial structure within microbial communities can provide nearly limitless opportunities for social interactions and are an important driver for evolution. As metabolites are often molecular signals, metabolite diffusion within microbial communities can affect the composition and dynamics of the community in a manner that can be challenging to deconstruct. We used encapsulation of a synthetic microbial community within microdroplets to investigate the effects of spatial structure and metabolite diffusion on population dynamics and to examine the effects of cheating by one member of the community. The synthetic community was comprised of three strains: a 'Producer' that makes the diffusible quorum sensing molecule ( N -(3-Oxododecanoyl)-L-homoserine lactone, C12-oxo-HSL) or AHL; a 'Receiver' that is killed by AHL and a Non-Producer or 'cheater' that benefits from the extinction of the Receivers, but without the costs associated with the AHL synthesis. We demonstrate that despite rapid diffusion of AHL between microdroplets, the spatial structure imposed by the microdroplets allow a more efficient but transient enrichment of more rare and slower growing 'Producer' subpopulations. Eventually, the Non-Producer population drove the Producers to extinction. By including fluorescence-activated microdroplet sorting and providing sustained competition by the Receiver strain, we demonstrate a strategy for indirect enrichment of a rare and unlabeled Producer. The ability to screen and enrich metabolite Producers from a much larger population under conditions of rapid diffusion provides an important framework for the development of applications in synthetic ecology and biotechnology. Abstract Figure
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Affiliation(s)
| | - Gaoyang Fan
- Department of Mathematics, University of Houston, Houston, Texas, United States
| | - Razan N Alnahhas
- Department of Biomedical Engineering, Boston University, Boston, Massachusetts 02215, United States
| | - Andrew J Hirning
- Department of Biosciences, Rice University, Houston, United States
| | - Matthew R Bennett
- Department of Biosciences, Rice University, Houston, United States
- Department of Bioengineering, Rice University, Houston, United States
| | - Yousif Shamoo
- Department of Biosciences, Rice University, Houston, United States
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24
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De novo engineering of a bacterial lifestyle program. Nat Chem Biol 2022; 19:488-497. [PMID: 36522463 DOI: 10.1038/s41589-022-01194-1] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/31/2022] [Accepted: 09/30/2022] [Indexed: 12/23/2022]
Abstract
Synthetic biology has shown remarkable potential to program living microorganisms for applications. However, a notable discrepancy exists between the current engineering practice-which focuses predominantly on planktonic cells-and the ubiquitous observation of microbes in nature that constantly alternate their lifestyles on environmental variations. Here we present the de novo construction of a synthetic genetic program that regulates bacterial life cycle and enables phase-specific gene expression. The program is orthogonal, harnessing an engineered protein from 45 candidates as the biofilm matrix building block. It is also highly controllable, allowing directed biofilm assembly and decomposition as well as responsive autonomous planktonic-biofilm phase transition. Coupling to synthesis modules, it is further programmable for various functional realizations that conjugate phase-specific biomolecular production with lifestyle alteration. This work establishes a versatile platform for microbial engineering across physiological regimes, thereby shedding light on a promising path for gene circuit applications in complex contexts.
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25
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Godin R, Karamched BR, Ryan SD. The space between us: Modeling spatial heterogeneity in synthetic microbial consortia dynamics. BIOPHYSICAL REPORTS 2022; 2:100085. [PMID: 36479317 PMCID: PMC9720408 DOI: 10.1016/j.bpr.2022.100085] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 11/14/2022] [Indexed: 06/17/2023]
Abstract
A central endeavor in bioengineering concerns the construction of multistrain microbial consortia with desired properties. Typically, a gene network is partitioned between strains, and strains communicate via quorum sensing, allowing for complex behaviors. Yet a fundamental question of how emergent spatiotemporal patterning in multistrain microbial consortia affects consortial dynamics is not understood well. Here, we propose a computationally tractable and straightforward modeling framework that explicitly allows linking spatiotemporal patterning to consortial dynamics. We validate our model against previously published results and make predictions of how spatial heterogeneity impacts interstrain communication. By enabling the investigation of spatial patterns effects on microbial dynamics, our modeling framework informs experimentalists, helps advance the understanding of complex microbial systems, and supports the development of applications involving them.
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Affiliation(s)
- Ryan Godin
- Department of Chemical and Biological Engineering, Iowa State University, Ames, Iowa
- Department of Biology, Geology, and Environmental Sciences, Cleveland State University, Cleveland, Ohio
- Department of Mathematics and Statistics, Cleveland State University, Cleveland, Ohio
- Center for Applied Data Analysis and Modeling, Cleveland State University, Cleveland, Ohio
| | - Bhargav R. Karamched
- Department of Mathematics, Florida State University, Tallahassee, Florida
- Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida
- Program in Neuroscience, Florida State University, Tallahassee, Florida
| | - Shawn D. Ryan
- Department of Mathematics and Statistics, Cleveland State University, Cleveland, Ohio
- Center for Applied Data Analysis and Modeling, Cleveland State University, Cleveland, Ohio
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26
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Hu H, Wang M, Huang Y, Xu Z, Xu P, Nie Y, Tang H. Guided by the principles of microbiome engineering: Accomplishments and perspectives for environmental use. MLIFE 2022; 1:382-398. [PMID: 38818482 PMCID: PMC10989833 DOI: 10.1002/mlf2.12043] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/12/2022] [Revised: 08/19/2022] [Accepted: 09/02/2022] [Indexed: 06/01/2024]
Abstract
Although the accomplishments of microbiome engineering highlight its significance for the targeted manipulation of microbial communities, knowledge and technical gaps still limit the applications of microbiome engineering in biotechnology, especially for environmental use. Addressing the environmental challenges of refractory pollutants and fluctuating environmental conditions requires an adequate understanding of the theoretical achievements and practical applications of microbiome engineering. Here, we review recent cutting-edge studies on microbiome engineering strategies and their classical applications in bioremediation. Moreover, a framework is summarized for combining both top-down and bottom-up approaches in microbiome engineering toward improved applications. A strategy to engineer microbiomes for environmental use, which avoids the build-up of toxic intermediates that pose a risk to human health, is suggested. We anticipate that the highlighted framework and strategy will be beneficial for engineering microbiomes to address difficult environmental challenges such as degrading multiple refractory pollutants and sustain the performance of engineered microbiomes in situ with indigenous microorganisms under fluctuating conditions.
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Affiliation(s)
- Haiyang Hu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Miaoxiao Wang
- Department of Environmental Systems ScienceETH ZürichZürichSwitzerland
- Department of Environmental MicrobiologyETH ZürichEawagSwitzerland
| | - Yiqun Huang
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Zhaoyong Xu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Ping Xu
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
| | - Yong Nie
- College of EngineeringPeking UniversityBeijingChina
| | - Hongzhi Tang
- State Key Laboratory of Microbial Metabolism, and School of Life Sciences & BiotechnologyShanghai Jiao Tong UniversityShanghaiChina
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27
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Abstract
Microbial communities are complex living systems that populate the planet with diverse functions and are increasingly harnessed for practical human needs. To deepen the fundamental understanding of their organization and functioning as well as to facilitate their engineering for applications, mathematical modeling has played an increasingly important role. Agent-based models represent a class of powerful quantitative frameworks for investigating microbial communities because of their individualistic nature in describing cells, mechanistic characterization of molecular and cellular processes, and intrinsic ability to produce emergent system properties. This review presents a comprehensive overview of recent advances in agent-based modeling of microbial communities. It surveys the state-of-the-art algorithms employed to simulate intracellular biomolecular events, single-cell behaviors, intercellular interactions, and interactions between cells and their environments that collectively serve as the driving forces of community behaviors. It also highlights three lines of applications of agent-based modeling, namely, the elucidation of microbial range expansion and colony ecology, the design of synthetic gene circuits and microbial populations for desired behaviors, and the characterization of biofilm formation and dispersal. The review concludes with a discussion of existing challenges, including the computational cost of the modeling, and potential mitigation strategies.
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Affiliation(s)
- Karthik Nagarajan
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Congjian Ni
- Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States
| | - Ting Lu
- Department of Bioengineering, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Center for Biophysics and Quantitative Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Department of Physics, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,Institute for Genomic Biology, University of Illinois at Urbana-Champaign, Urbana, Illinois 61801, United States.,National Center for Supercomputing Applications, Urbana, Illinois 61801, United States
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28
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Zhao S, Li F, Yang F, Ma Q, Liu L, Huang Z, Fan X, Li Q, Liu X, Gu P. Microbial production of valuable chemicals by modular co-culture strategy. World J Microbiol Biotechnol 2022; 39:6. [PMID: 36346491 DOI: 10.1007/s11274-022-03447-6] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2022] [Accepted: 10/22/2022] [Indexed: 11/11/2022]
Abstract
Nowadays, microbial synthesis has become a common way for producing valuable chemicals. Traditionally, microbial production of valuable chemicals is accomplished by a single strain. For the purpose of increasing the production titer and yield of a recombinant strain, complicated pathways and regulation layers should be fine-tuned, which also brings a heavy metabolic burden to the host. In addition, utilization of various complex and mixed substrates further interferes with the normal growth of the host strain and increases the complexity of strain engineering. As a result, modular co-culture technology, which aims to divide a target complex pathway into separate modules located at different single strains, poses an alternative solution for microbial production. Recently, modular co-culture strategy has been employed for the synthesis of different natural products. Therefore, in this review, various chemicals produced with application of co-cultivation technology are summarized, including co-culture with same species or different species, and regulation of population composition between the co-culture members. In addition, development prospects and challenges of this promising field are also addressed, and possible solution for these issues were also provided.
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Affiliation(s)
- Shuo Zhao
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Fangfang Li
- Yantai Food and Drug Control and Test Center, Yantai, 264003, People's Republic of China
| | - Fan Yang
- Tsingtao Brewery Co., Ltd., Qingdao, 266071, People's Republic of China
| | - Qianqian Ma
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Liwen Liu
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Zhaosong Huang
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Xiangyu Fan
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Qiang Li
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China
| | - Xiaoli Liu
- Key Laboratory of Marine Biotechnology in Universities of Shandong, School of Life Sciences, Ludong University, Yantai, 264025, People's Republic of China
| | - Pengfei Gu
- School of Biological Science and Technology, University of Jinan, Jinan, 250022, People's Republic of China.
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29
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Moškon M, Pušnik Ž, Stanovnik L, Zimic N, Mraz M. A computational design of a programmable biological processor. Biosystems 2022; 221:104778. [PMID: 36099979 DOI: 10.1016/j.biosystems.2022.104778] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/02/2022] [Revised: 08/02/2022] [Accepted: 09/05/2022] [Indexed: 11/29/2022]
Abstract
Basic synthetic information processing structures, such as logic gates, oscillators and flip-flops, have already been implemented in living organisms. Current implementations of these structures have yet to be extended to more complex processing structures that would constitute a biological computer. We make a step forward towards the construction of a biological computer. We describe a model-based computational design of a biological processor that uses transcription and translation resources of the host cell to perform its operations. The proposed processor is composed of an instruction memory containing a biological program, a program counter that is used to address this memory, and a biological oscillator that triggers the execution of the next instruction in the memory. We additionally describe the implementation of a biological compiler that compiles a sequence of human-readable instructions into ordinary differential equation-based models, which can be used to simulate and analyse the dynamics of the processor. The proposed implementation presents the first programmable biological processor that exploits cellular resources to execute the specified instructions. We demonstrate the application of the described processor on a set of simple yet scalable biological programs. Biological descriptions of these programs can be produced manually or automatically using the provided compiler.
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Affiliation(s)
- Miha Moškon
- University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, SI-1000, Slovenia.
| | - Žiga Pušnik
- University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, SI-1000, Slovenia
| | - Lidija Stanovnik
- University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, SI-1000, Slovenia
| | - Nikolaj Zimic
- University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, SI-1000, Slovenia
| | - Miha Mraz
- University of Ljubljana, Faculty of Computer and Information Science, Večna pot 113, Ljubljana, SI-1000, Slovenia
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30
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Toward predictive engineering of gene circuits. Trends Biotechnol 2022; 41:760-768. [PMID: 36435671 DOI: 10.1016/j.tibtech.2022.11.001] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/23/2022] [Revised: 10/26/2022] [Accepted: 11/02/2022] [Indexed: 11/25/2022]
Abstract
Many synthetic biology applications rely on programming living cells using gene circuits - the assembly and wiring of genetic elements to control cellular behaviors. Extensive progress has been made in constructing gene circuits with diverse functions and applications. For many circuit functions, however, it remains challenging to ensure that the circuits operate in a predictable manner. Although the notion of predictability may appear intuitive, close inspection suggests that it is not always clear what constitutes predictability. We dissect this concept and how it can be confounded by the complexity of a circuit, the complexity of the context, and the interplay between the two. We discuss circuit engineering strategies, in both computation and experiment, that have been used to improve the predictability of gene circuits.
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31
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Calibrating spatiotemporal models of microbial communities to microscopy data: A review. PLoS Comput Biol 2022; 18:e1010533. [PMID: 36227846 PMCID: PMC9560168 DOI: 10.1371/journal.pcbi.1010533] [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] [Indexed: 11/19/2022] Open
Abstract
Spatiotemporal models that account for heterogeneity within microbial communities rely on single-cell data for calibration and validation. Such data, commonly collected via microscopy and flow cytometry, have been made more accessible by recent advances in microfluidics platforms and data processing pipelines. However, validating models against such data poses significant challenges. Validation practices vary widely between modelling studies; systematic and rigorous methods have not been widely adopted. Similar challenges are faced by the (macrobial) ecology community, in which systematic calibration approaches are often employed to improve quantitative predictions from computational models. Here, we review single-cell observation techniques that are being applied to study microbial communities and the calibration strategies that are being employed for accompanying spatiotemporal models. To facilitate future calibration efforts, we have compiled a list of summary statistics relevant for quantifying spatiotemporal patterns in microbial communities. Finally, we highlight some recently developed techniques that hold promise for improved model calibration, including algorithmic guidance of summary statistic selection and machine learning approaches for efficient model simulation.
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32
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Lee TA, Steel H. Cybergenetic control of microbial community composition. Front Bioeng Biotechnol 2022; 10:957140. [PMID: 36277404 PMCID: PMC9582452 DOI: 10.3389/fbioe.2022.957140] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/30/2022] [Accepted: 09/20/2022] [Indexed: 11/13/2022] Open
Abstract
The use of bacterial communities in bioproduction instead of monocultures has potential advantages including increased productivity through division of labour, ability to utilise cheaper substrates, and robustness against perturbations. A key challenge in the application of engineered bacterial communities is the ability to reliably control the composition of the community in terms of its constituent species. This is crucial to prevent faster growing species from outcompeting others with a lower relative fitness, and to ensure that all species are present at an optimal ratio during different steps in a biotechnological process. In contrast to purely biological approaches such as synthetic quorum sensing circuits or paired auxotrophies, cybergenetic control techniques - those in which computers interface with living cells-are emerging as an alternative approach with many advantages. The community composition is measured through methods such as fluorescence intensity or flow cytometry, with measured data fed real-time into a computer. A control action is computed using a variety of possible control algorithms and then applied to the system, with actuation taking the form of chemical (e.g., inducers, nutrients) or physical (e.g., optogenetic, mechanical) inputs. Subsequent changes in composition are then measured and the cycle repeated, maintaining or driving the system to a desired state. This review discusses recent and future developments in methods for implementing cybergenetic control systems, contrasts their capabilities with those of traditional biological methods of population control, and discusses future directions and outstanding challenges for the field.
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33
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Qiao L, Zhang ZB, Zhao W, Wei P, Zhang L. Network design principle for robust oscillatory behaviors with respect to biological noise. eLife 2022; 11:76188. [PMID: 36125857 PMCID: PMC9489215 DOI: 10.7554/elife.76188] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2021] [Accepted: 08/22/2022] [Indexed: 11/13/2022] Open
Abstract
Oscillatory behaviors, which are ubiquitous in transcriptional regulatory networks, are often subject to inevitable biological noise. Thus, a natural question is how transcriptional regulatory networks can robustly achieve accurate oscillation in the presence of biological noise. Here, we search all two- and three-node transcriptional regulatory network topologies for those robustly capable of accurate oscillation against the parameter variability (extrinsic noise) or stochasticity of chemical reactions (intrinsic noise). We find that, no matter what source of the noise is applied, the topologies containing the repressilator with positive autoregulation show higher robustness of accurate oscillation than those containing the activator-inhibitor oscillator, and additional positive autoregulation enhances the robustness against noise. Nevertheless, the attenuation of different sources of noise is governed by distinct mechanisms: the parameter variability is buffered by the long period, while the stochasticity of chemical reactions is filtered by the high amplitude. Furthermore, we analyze the noise of a synthetic human nuclear factor κB (NF-κB) signaling network by varying three different topologies and verify that the addition of a repressilator to the activator-inhibitor oscillator, which leads to the emergence of high-robustness motif—the repressilator with positive autoregulation—improves the oscillation accuracy in comparison to the topology with only an activator-inhibitor oscillator. These design principles may be applicable to other oscillatory circuits.
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Affiliation(s)
- Lingxia Qiao
- Beijing International Center for Mathematical Research, Peking University, Beijing, China
| | - Zhi-Bo Zhang
- Center for Quantitative Biology, Peking University, Beijing, China.,Peking-Tsinghua Joint Center for Life Sciences, Academy for Advanced Interdisciplinary Studies, Peking University, Beijing, China
| | - Wei Zhao
- Center for Quantitative Biology, Peking University, Beijing, China
| | - Ping Wei
- Center for Quantitative Biology, Peking University, Beijing, China.,Center for Cell and Gene Circuit Design, CAS Key Laboratory of Quantitative Engineering Biology, Shenzhen Institute of Synthetic Biology, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences, Shenzhen, China
| | - Lei Zhang
- Beijing International Center for Mathematical Research, Peking University, Beijing, China.,Center for Quantitative Biology, Peking University, Beijing, China
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34
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Layered feedback control overcomes performance trade-off in synthetic biomolecular networks. Nat Commun 2022; 13:5393. [PMID: 36104365 PMCID: PMC9474519 DOI: 10.1038/s41467-022-33058-6] [Citation(s) in RCA: 7] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/22/2021] [Accepted: 08/31/2022] [Indexed: 11/08/2022] Open
Abstract
AbstractLayered feedback is an optimization strategy in feedback control designs widely used in engineering. Control theory suggests that layering multiple feedbacks could overcome the robustness-speed performance trade-off limit. In natural biological networks, genes are often regulated in layers to adapt to environmental perturbations. It is hypothesized layering architecture could also overcome the robustness-speed performance trade-off in genetic networks. In this work, we validate this hypothesis with a synthetic biomolecular network in living E. coli cells. We start with system dynamics analysis using models of various complexities to guide the design of a layered control architecture in living cells. Experimentally, we interrogate system dynamics under three groups of perturbations. We consistently observe that the layered control improves system performance in the robustness-speed domain. This work confirms that layered control could be adopted in synthetic biomolecular networks for performance optimization. It also provides insights into understanding genetic feedback control architectures in nature.
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35
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Rhythmic transcription of Bmal1 stabilizes the circadian timekeeping system in mammals. Nat Commun 2022; 13:4652. [PMID: 35999195 PMCID: PMC9399252 DOI: 10.1038/s41467-022-32326-9] [Citation(s) in RCA: 10] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/19/2021] [Accepted: 07/21/2022] [Indexed: 12/14/2022] Open
Abstract
In mammals, the circadian clock consists of transcriptional and translational feedback loops through DNA cis-elements such as E-box and RRE. The E-box-mediated core feedback loop is interlocked with the RRE-mediated feedback loop, but biological significance of the RRE-mediated loop has been elusive. In this study, we established mutant cells and mice deficient for rhythmic transcription of Bmal1 gene by deleting its upstream RRE elements and hence disrupted the RRE-mediated feedback loop. We observed apparently normal circadian rhythms in the mutant cells and mice, but a combination of mathematical modeling and experiments revealed that the circadian period and amplitude of the mutants were more susceptible to disturbance of CRY1 protein rhythm. Our findings demonstrate that the RRE-mediated feedback regulation of Bmal1 underpins the E-box-mediated rhythm in cooperation with CRY1-dependent posttranslational regulation of BMAL1 protein, thereby conferring the perturbation-resistant oscillation and chronologically-organized output of the circadian clock.
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36
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Gutiérrez Mena J, Kumar S, Khammash M. Dynamic cybergenetic control of bacterial co-culture composition via optogenetic feedback. Nat Commun 2022; 13:4808. [PMID: 35973993 PMCID: PMC9381578 DOI: 10.1038/s41467-022-32392-z] [Citation(s) in RCA: 17] [Impact Index Per Article: 8.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/20/2022] [Accepted: 07/29/2022] [Indexed: 12/19/2022] Open
Abstract
Communities of microbes play important roles in natural environments and hold great potential for deploying division-of-labor strategies in synthetic biology and bioproduction. However, the difficulty of controlling the composition of microbial consortia over time hinders their optimal use in many applications. Here, we present a fully automated, high-throughput platform that combines real-time measurements and computer-controlled optogenetic modulation of bacterial growth to implement precise and robust compositional control of a two-strain E. coli community. In addition, we develop a general framework for dynamic modeling of synthetic genetic circuits in the physiological context of E. coli and use a host-aware model to determine the optimal control parameters of our closed-loop compositional control system. Our platform succeeds in stabilizing the strain ratio of multiple parallel co-cultures at arbitrary levels and in changing these targets over time, opening the door for the implementation of dynamic compositional programs in synthetic bacterial communities.
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Affiliation(s)
- Joaquín Gutiérrez Mena
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Sant Kumar
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland
| | - Mustafa Khammash
- Department of Biosystems Science and Engineering (D-BSSE), ETH Zürich, Mattenstrasse 26, 4058, Basel, Switzerland.
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37
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Deter HS, Lu T. Engineering microbial consortia with rationally designed cellular interactions. Curr Opin Biotechnol 2022; 76:102730. [PMID: 35609504 PMCID: PMC10129393 DOI: 10.1016/j.copbio.2022.102730] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/06/2021] [Revised: 03/22/2022] [Accepted: 04/03/2022] [Indexed: 12/14/2022]
Abstract
Synthetic microbial consortia represent a frontier of synthetic biology that promises versatile engineering of cellular functions. They are primarily developed through the design and construction of cellular interactions that coordinate individual dynamics and generate collective behaviors. Here we review recent advances in the engineering of synthetic communities through cellular-interaction programming. We first examine fundamental building blocks for intercellular communication and unidirectional positive and negative interactions. We then recap the assembly of the building blocks for creating bidirectional interactions in two-species ecosystems, which is followed by the discussion of engineering toward complex communities with increasing species numbers, under spatial contexts, and via model-guided design. We conclude by summarizing major challenges and future opportunities of engineered microbial ecosystems.
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Affiliation(s)
- Heather S Deter
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA; Intelligence Community Postdoctoral Research Fellowship Program, University of Illinois Urbana-Champaign, Urbana, IL, USA
| | - Ting Lu
- Department of Bioengineering, University of Illinois Urbana-Champaign, Urbana, IL, USA; Carl R. Woese Institute for Genomic Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA; Department of Physics, University of Illinois Urbana-Champaign, Urbana, IL, USA; Center for Biophysics and Quantitative Biology, University of Illinois Urbana-Champaign, Urbana, IL, USA; National Center for Supercomputing Applications, Urbana, IL, USA.
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38
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Liu X, Inda ME, Lai Y, Lu TK, Zhao X. Engineered Living Hydrogels. ADVANCED MATERIALS (DEERFIELD BEACH, FLA.) 2022; 34:e2201326. [PMID: 35243704 PMCID: PMC9250645 DOI: 10.1002/adma.202201326] [Citation(s) in RCA: 51] [Impact Index Per Article: 25.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 02/09/2022] [Revised: 03/01/2022] [Indexed: 05/31/2023]
Abstract
Living biological systems, ranging from single cells to whole organisms, can sense, process information, and actuate in response to changing environmental conditions. Inspired by living biological systems, engineered living cells and nonliving matrices are brought together, which gives rise to the technology of engineered living materials. By designing the functionalities of living cells and the structures of nonliving matrices, engineered living materials can be created to detect variability in the surrounding environment and to adjust their functions accordingly, thereby enabling applications in health monitoring, disease treatment, and environmental remediation. Hydrogels, a class of soft, wet, and biocompatible materials, have been widely used as matrices for engineered living cells, leading to the nascent field of engineered living hydrogels. Here, the interactions between hydrogel matrices and engineered living cells are described, focusing on how hydrogels influence cell behaviors and how cells affect hydrogel properties. The interactions between engineered living hydrogels and their environments, and how these interactions enable versatile applications, are also discussed. Finally, current challenges facing the field of engineered living hydrogels for their applications in clinical and environmental settings are highlighted.
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Affiliation(s)
- Xinyue Liu
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Maria Eugenia Inda
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Yong Lai
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Timothy K Lu
- Synthetic Biology Group, Research Laboratory of Electronics, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
| | - Xuanhe Zhao
- Department of Mechanical Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
- Department of Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA, 02139, USA
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39
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Peng H, Zhong J, Chen P, Liu R. Identifying the critical states of complex diseases by the dynamic change of multivariate distribution. Brief Bioinform 2022; 23:6590435. [DOI: 10.1093/bib/bbac177] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/02/2022] [Revised: 04/10/2022] [Accepted: 04/18/2022] [Indexed: 11/13/2022] Open
Abstract
Abstract
The dynamics of complex diseases are not always smooth; they are occasionally abrupt, i.e. there is a critical state transition or tipping point at which the disease undergoes a sudden qualitative shift. There are generally a few significant differences in the critical state in terms of gene expressions or other static measurements, which may lead to the failure of traditional differential expression-based biomarkers to identify such a tipping point. In this study, we propose a computational method, the direct interaction network-based divergence, to detect the critical state of complex diseases by exploiting the dynamic changes in multivariable distributions inferred from observable samples and local biomolecular direct interaction networks. Such a method is model-free and applicable to both bulk and single-cell expression data. Our approach was validated by successfully identifying the tipping point just before the occurrence of a critical transition for both a simulated data set and seven real data sets, including those from The Cancer Genome Atlas and two single-cell RNA-sequencing data sets of cell differentiation. Functional and pathway enrichment analyses also validated the computational results from the perspectives of both molecules and networks.
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Affiliation(s)
- Hao Peng
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
| | - Jiayuan Zhong
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
- School of mathematics and big data, Foshan University, Foshan 528225, China
| | - Pei Chen
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
| | - Rui Liu
- School of Mathematics, South China University of Technology, Guangzhou 510640, China
- Pazhou Lab, Guangzhou 510330, China
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40
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Li S, Xiao J, Sun T, Yu F, Zhang K, Feng Y, Xu C, Wang B, Cheng L. Synthetic microbial consortia with programmable ecological interactions. Methods Ecol Evol 2022. [DOI: 10.1111/2041-210x.13894] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Affiliation(s)
- Shuyao Li
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Jing Xiao
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Tianzheng Sun
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Fangjian Yu
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Kaihang Zhang
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Yuantao Feng
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Chenchao Xu
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
| | - Baojun Wang
- Hangzhou Innovation Center & College of Chemical and Biological Engineering Zhejiang University Hangzhou 311200 China
- Research Centre for Biological Computation, Zhejiang Laboratory Hangzhou 311100 China
| | - Lei Cheng
- MOE Key Laboratory of Biosystems Homeostasis & Protection, College of Life Sciences Zhejiang University Hangzhou 310058 China
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41
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Cheong JH, Qiu X, Liu Y, Al-Omari A, Griffith J, Schüttler HB, Mao L, Arnold J. The macroscopic limit to synchronization of cellular clocks in single cells of Neurospora crassa. Sci Rep 2022; 12:6750. [PMID: 35468928 PMCID: PMC9039089 DOI: 10.1038/s41598-022-10612-2] [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: 08/13/2021] [Accepted: 03/29/2022] [Indexed: 11/09/2022] Open
Abstract
AbstractWe determined the macroscopic limit for phase synchronization of cellular clocks in an artificial tissue created by a “big chamber” microfluidic device to be about 150,000 cells or less. The dimensions of the microfluidic chamber allowed us to calculate an upper limit on the radius of a hypothesized quorum sensing signal molecule of 13.05 nm using a diffusion approximation for signal travel within the device. The use of a second microwell microfluidic device allowed the refinement of the macroscopic limit to a cell density of 2166 cells per fixed area of the device for phase synchronization. The measurement of averages over single cell trajectories in the microwell device supported a deterministic quorum sensing model identified by ensemble methods for clock phase synchronization. A strong inference framework was used to test the communication mechanism in phase synchronization of quorum sensing versus cell-to-cell contact, suggesting support for quorum sensing. Further evidence came from showing phase synchronization was density-dependent.
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42
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Jeong EM, Song YM, Kim JK. Combined multiple transcriptional repression mechanisms generate ultrasensitivity and oscillations. Interface Focus 2022; 12:20210084. [PMID: 35450279 PMCID: PMC9010851 DOI: 10.1098/rsfs.2021.0084] [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: 11/10/2021] [Accepted: 02/24/2022] [Indexed: 12/14/2022] Open
Abstract
Transcriptional repression can occur via various mechanisms, such as blocking, sequestration and displacement. For instance, the repressors can hold the activators to prevent binding with DNA or can bind to the DNA-bound activators to block their transcriptional activity. Although the transcription can be completely suppressed with a single mechanism, multiple repression mechanisms are used together to inhibit transcriptional activators in many systems, such as circadian clocks and NF-κB oscillators. This raises the question of what advantages arise if seemingly redundant repression mechanisms are combined. Here, by deriving equations describing the multiple repression mechanisms, we find that their combination can synergistically generate a sharply ultrasensitive transcription response and thus strong oscillations. This rationalizes why the multiple repression mechanisms are used together in various biological oscillators. The critical role of such combined transcriptional repression for strong oscillations is further supported by our analysis of formerly identified mutations disrupting the transcriptional repression of the mammalian circadian clock. The hitherto unrecognized source of the ultrasensitivity, the combined transcriptional repressions, can lead to robust synthetic oscillators with a previously unachievable simple design.
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Affiliation(s)
- Eui Min Jeong
- Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Yun Min Song
- Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon 34126, Republic of Korea
| | - Jae Kyoung Kim
- Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Republic of Korea
- Biomedical Mathematics Group, Institute for Basic Science, Daejeon 34126, Republic of Korea
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Carignano A, Chen DH, Mallory C, Wright RC, Seelig G, Klavins E. Modular, robust and extendible multicellular circuit design in yeast. eLife 2022; 11:74540. [PMID: 35312478 PMCID: PMC9000959 DOI: 10.7554/elife.74540] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/08/2021] [Accepted: 03/20/2022] [Indexed: 11/13/2022] Open
Abstract
Division of labor between cells is ubiquitous in biology but the use of multi-cellular consortia for engineering applications is only beginning to be explored. A significant advantage of multi-cellular circuits is their potential to be modular with respect to composition but this claim has not yet been extensively tested using experiments and quantitative modeling. Here, we construct a library of 24 yeast strains capable of sending, receiving or responding to three molecular signals, characterize them experimentally and build quantitative models of their input-output relationships. We then compose these strains into two- and three-strain cascades as well as a four-strain bistable switch and show that experimentally measured consortia dynamics can be predicted from the models of the constituent parts. To further explore the achievable range of behaviors, we perform a fully automated computational search over all two-, three- and four-strain consortia to identify combinations that realize target behaviors including logic gates, band-pass filters and time pulses. Strain combinations that are predicted to map onto a target behavior are further computationally optimized and then experimentally tested. Experiments closely track computational predictions. The high reliability of these model descriptions further strengthens the feasibility and highlights the potential for distributed computing in synthetic biology.
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Affiliation(s)
- Alberto Carignano
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Dai Hua Chen
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Cannon Mallory
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | | | - Georg Seelig
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
| | - Eric Klavins
- Department of Electrical and Computer Engineering, University of Washington, Seattle, United States
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Lezia A, Csicsery N, Hasty J. Design, mutate, screen: Multiplexed creation and arrayed screening of synchronized genetic clocks. Cell Syst 2022; 13:365-375.e5. [PMID: 35320733 DOI: 10.1016/j.cels.2022.02.005] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/25/2021] [Revised: 11/15/2021] [Accepted: 02/17/2022] [Indexed: 12/25/2022]
Abstract
A major goal in synthetic biology is coordinating cellular behavior using cell-cell interactions; however, designing and testing complex genetic circuits that function only in large populations remains challenging. Although directed evolution has commonly supplemented rational design methods for synthetic gene circuits, this method relies on the efficient screening of mutant libraries for desired phenotypes. Recently, multiple techniques have been developed for identifying dynamic phenotypes from large, pooled libraries. These technologies have advanced library screening for single-cell, time-varying phenotypes but are currently incompatible with population-level phenotypes dependent on cell-cell communication. Here, we utilize directed mutagenesis and multiplexed microfluidics to develop an arrayed-screening workflow for dynamic, population-level genetic circuits. Specifically, we create a mutant library of an existing oscillator, the synchronized lysis circuit, and discover variants with different period-amplitude characteristics. Lastly, we utilize our screening workflow to construct a transcriptionally regulated synchronized oscillator that functions over long timescales. A record of this paper's transparent peer review process is included in the supplemental information.
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Affiliation(s)
- Andrew Lezia
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Nicholas Csicsery
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA
| | - Jeff Hasty
- Department of Bioengineering, University of California, San Diego, La Jolla, CA, USA; Molecular Biology Section, Division of Biological Sciences, University of California, San Diego, La Jolla, CA, USA; BioCircuits Institute, University of California, San Diego, La Jolla, CA, USA.
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45
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Refactoring transcription factors for metabolic engineering. Biotechnol Adv 2022; 57:107935. [PMID: 35271945 DOI: 10.1016/j.biotechadv.2022.107935] [Citation(s) in RCA: 35] [Impact Index Per Article: 17.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2021] [Revised: 02/04/2022] [Accepted: 03/03/2022] [Indexed: 12/19/2022]
Abstract
Due to the ability to regulate target metabolic pathways globally and dynamically, metabolic regulation systems composed of transcription factors have been widely used in metabolic engineering and synthetic biology. This review introduced the categories, action principles, prediction strategies, and related databases of transcription factors. Then, the application of global transcription machinery engineering technology and the transcription factor-based biosensors and quorum sensing systems are overviewed. In addition, strategies for optimizing the transcriptional regulatory tools' performance by refactoring transcription factors are summarized. Finally, the current limitations and prospects of constructing various regulatory tools based on transcription factors are discussed. This review will provide theoretical guidance for the rational design and construction of transcription factor-based metabolic regulation systems.
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46
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Duncker KE, Holmes ZA, You L. Engineered microbial consortia: strategies and applications. Microb Cell Fact 2021; 20:211. [PMID: 34784924 PMCID: PMC8597270 DOI: 10.1186/s12934-021-01699-9] [Citation(s) in RCA: 32] [Impact Index Per Article: 10.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/24/2021] [Accepted: 10/23/2021] [Indexed: 11/10/2022] Open
Abstract
Many applications of microbial synthetic biology, such as metabolic engineering and biocomputing, are increasing in design complexity. Implementing complex tasks in single populations can be a challenge because large genetic circuits can be burdensome and difficult to optimize. To overcome these limitations, microbial consortia can be engineered to distribute complex tasks among multiple populations. Recent studies have made substantial progress in programming microbial consortia for both basic understanding and potential applications. Microbial consortia have been designed through diverse strategies, including programming mutualistic interactions, using programmed population control to prevent overgrowth of individual populations, and spatial segregation to reduce competition. Here, we highlight the role of microbial consortia in the advances of metabolic engineering, biofilm production for engineered living materials, biocomputing, and biosensing. Additionally, we discuss the challenges for future research in microbial consortia.
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Affiliation(s)
- Katherine E Duncker
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA
| | - Zachary A Holmes
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA
| | - Lingchong You
- Department of Biomedical Engineering, Duke University, Durham, NC, 27705, USA.
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Abstract
Circadian clocks are important to much of life on Earth and are of inherent interest to humanity, implicated in fields ranging from agriculture and ecology to developmental biology and medicine. New techniques show that it is not simply the presence of clocks, but coordination between them that is critical for complex physiological processes across the kingdoms of life. Recent years have also seen impressive advances in synthetic biology to the point where parallels can be drawn between synthetic biological and circadian oscillators. This review will emphasize theoretical and experimental studies that have revealed a fascinating dichotomy of coupling and heterogeneity among circadian clocks. We will also consolidate the fields of chronobiology and synthetic biology, discussing key design principles of their respective oscillators.
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Affiliation(s)
- Chris N Micklem
- The Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK.,The Cavendish Laboratory, Department of Physics, University of Cambridge, JJ Thomson Avenue, Cambridge CH3 0HE, UK
| | - James C W Locke
- The Sainsbury Laboratory, University of Cambridge, Bateman Street, Cambridge CB2 1LR, UK
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48
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Winkle JJ, Karamched BR, Bennett MR, Ott W, Josić K. Emergent spatiotemporal population dynamics with cell-length control of synthetic microbial consortia. PLoS Comput Biol 2021; 17:e1009381. [PMID: 34550968 PMCID: PMC8489724 DOI: 10.1371/journal.pcbi.1009381] [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: 04/02/2021] [Revised: 10/04/2021] [Accepted: 08/25/2021] [Indexed: 12/04/2022] Open
Abstract
The increased complexity of synthetic microbial biocircuits highlights the need for distributed cell functionality due to concomitant increases in metabolic and regulatory burdens imposed on single-strain topologies. Distributed systems, however, introduce additional challenges since consortium composition and spatiotemporal dynamics of constituent strains must be robustly controlled to achieve desired circuit behaviors. Here, we address these challenges with a modeling-based investigation of emergent spatiotemporal population dynamics using cell-length control in monolayer, two-strain bacterial consortia. We demonstrate that with dynamic control of a strain's division length, nematic cell alignment in close-packed monolayers can be destabilized. We find that this destabilization confers an emergent, competitive advantage to smaller-length strains-but by mechanisms that differ depending on the spatial patterns of the population. We used complementary modeling approaches to elucidate underlying mechanisms: an agent-based model to simulate detailed mechanical and signaling interactions between the competing strains, and a reductive, stochastic lattice model to represent cell-cell interactions with a single rotational parameter. Our modeling suggests that spatial strain-fraction oscillations can be generated when cell-length control is coupled to quorum-sensing signaling in negative feedback topologies. Our research employs novel methods of population control and points the way to programming strain fraction dynamics in consortial synthetic biology.
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Affiliation(s)
- James J Winkle
- Department of Mathematics, University of Houston, Houston, Texas, United States of America
| | - Bhargav R Karamched
- Department of Mathematics, Florida State University, Tallahassee, Florida, United States of America
- Institute of Molecular Biophysics, Florida State University, Tallahassee, Florida, United States of America
| | - Matthew R Bennett
- Department of Bioengineering, Rice University, Houston, Texas, United States of America
- Department of Biosciences, Rice University, Houston, Texas, United States of America
| | - William Ott
- Department of Mathematics, University of Houston, Houston, Texas, United States of America
| | - Krešimir Josić
- Department of Mathematics, University of Houston, Houston, Texas, United States of America
- Department of Biosciences, Rice University, Houston, Texas, United States of America
- Department of Biology and Biochemistry, University of Houston, Houston, Texas, United States of America
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Cortez MJ, Hong H, Choi B, Kim JK, Josić K. Hierarchical Bayesian models of transcriptional and translational regulation processes with delays. Bioinformatics 2021; 38:187-195. [PMID: 34450624 PMCID: PMC8696106 DOI: 10.1093/bioinformatics/btab618] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/21/2021] [Revised: 08/19/2021] [Accepted: 08/25/2021] [Indexed: 02/05/2023] Open
Abstract
MOTIVATION Simultaneous recordings of gene network dynamics across large populations have revealed that cell characteristics vary considerably even in clonal lines. Inferring the variability of parameters that determine gene dynamics is key to understanding cellular behavior. However, this is complicated by the fact that the outcomes and effects of many reactions are not observable directly. Unobserved reactions can be replaced with time delays to reduce model dimensionality and simplify inference. However, the resulting models are non-Markovian, and require the development of new inference techniques. RESULTS We propose a non-Markovian, hierarchical Bayesian inference framework for quantifying the variability of cellular processes within and across cells in a population. We illustrate our approach using a delayed birth-death process. In general, a distributed delay model, rather than a popular fixed delay model, is needed for inference, even if only mean reaction delays are of interest. Using in silico and experimental data we show that the proposed hierarchical framework is robust and leads to improved estimates compared to its non-hierarchical counterpart. We apply our method to data obtained using time-lapse microscopy and infer the parameters that describe the dynamics of protein production at the single cell and population level. The mean delays in protein production are larger than previously reported, have a coefficient of variation of around 0.2 across the population, and are not strongly correlated with protein production or growth rates. AVAILABILITY AND IMPLEMENTATION Accompanying code in Python is available at https://github.com/mvcortez/Bayesian-Inference. CONTACT kresimir.josic@gmail.com or jaekkim@kaist.ac.kr or cbskust@korea.ac.kr. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Mark Jayson Cortez
- Department of Mathematics, University of Houston, Houston, TX 77204, USA,Institute of Mathematical Sciences and Physics, University of the Philippines Los Baños, Laguna 4031, Philippines
| | - Hyukpyo Hong
- Department of Mathematical Sciences, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea,Biomedical Mathematics Group, Institute for Basic Science, Daejeon 34126, Korea
| | - Boseung Choi
- To whom correspondence should be addressed. or or
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Abstract
Microorganisms live in dense and diverse communities, with interactions between cells guiding community development and phenotype. The ability to perturb specific intercellular interactions in space and time provides a powerful route to determining the critical interactions and design rules for microbial communities. Approaches using optogenetic tools to modulate these interactions offer promise, as light can be exquisitely controlled in space and time. We report new plasmids for rapid integration of an optogenetic system into Saccharomyces cerevisiae to engineer light control of expression of a gene of interest. In a proof-of-principle study, we demonstrate the ability to control a model cooperative interaction, namely, the expression of the enzyme invertase (SUC2) which allows S. cerevisiae to hydrolyze sucrose and utilize it as a carbon source. We demonstrate that the strength of this cooperative interaction can be tuned in space and time by modulating light intensity and through spatial control of illumination. Spatial control of light allows cooperators and cheaters to be spatially segregated, and we show that the interplay between cooperative and inhibitory interactions in space can lead to pattern formation. Our strategy can be applied to achieve spatiotemporal control of expression of a gene of interest in S. cerevisiae to perturb both intercellular and interspecies interactions. IMPORTANCE Recent advances in microbial ecology have highlighted the importance of intercellular interactions in controlling the development, composition, and resilience of microbial communities. In order to better understand the role of these interactions in governing community development, it is critical to be able to alter them in a controlled manner. Optogenetically controlled interactions offer advantages over static perturbations or chemically controlled interactions, as light can be manipulated in space and time and does not require the addition of nutrients or antibiotics. Here, we report a system for rapidly achieving light control of a gene of interest in the important model organism Saccharomyces cerevisiae and demonstrate that by controlling expression of the enzyme invertase, we can control cooperative interactions. This approach will be useful for understanding intercellular and interspecies interactions in natural and synthetic microbial consortia containing S. cerevisiae and serves as a proof of principle for implementing this approach in other consortia.
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