1
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Elgaml A, Elshazli R, Miyoshi SI. Editorial: The role of regulatory networks in virulence and antimicrobial resistance of microbial pathogens. Front Microbiol 2024; 15:1370093. [PMID: 38410383 PMCID: PMC10896426 DOI: 10.3389/fmicb.2024.1370093] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/13/2024] [Accepted: 01/30/2024] [Indexed: 02/28/2024] Open
Affiliation(s)
- Abdelaziz Elgaml
- Microbiology and Immunology Department, Faculty of Pharmacy, Mansoura University, Mansoura, Egypt
- Microbiology and Immunology Department, Faculty of Pharmacy, Horus University - Egypt, New Damietta, Egypt
| | - Rami Elshazli
- Biochemistry and Molecular Genetics Department, Faculty of Physical Therapy, Horus University - Egypt, New Damietta, Egypt
| | - Shin-Ichi Miyoshi
- Graduate School of Medicine, Dentistry and Pharmaceutical Sciences, Okayama University, Okayama, Japan
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2
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Wang Q, Liu Z, Yan B, Chou WC, Ettwiller L, Ma Q, Liu B. A novel computational framework for genome-scale alternative transcription units prediction. Brief Bioinform 2021; 22:6265223. [PMID: 33957668 DOI: 10.1093/bib/bbab162] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/21/2021] [Revised: 03/18/2021] [Accepted: 04/07/2021] [Indexed: 11/12/2022] Open
Abstract
Alternative transcription units (ATUs) are dynamically encoded under different conditions and display overlapping patterns (sharing one or more genes) under a specific condition in bacterial genomes. Genome-scale identification of ATUs is essential for studying the emergence of human diseases caused by bacterial organisms. However, it is unrealistic to identify all ATUs using experimental techniques because of the complexity and dynamic nature of ATUs. Here, we present the first-of-its-kind computational framework, named SeqATU, for genome-scale ATU prediction based on next-generation RNA-Seq data. The framework utilizes a convex quadratic programming model to seek an optimum expression combination of all of the to-be-identified ATUs. The predicted ATUs in Escherichia coli reached a precision of 0.77/0.74 and a recall of 0.75/0.76 in the two RNA-Sequencing datasets compared with the benchmarked ATUs from third-generation RNA-Seq data. In addition, the proportion of 5'- or 3'-end genes of the predicted ATUs, having documented transcription factor binding sites and transcription termination sites, was three times greater than that of no 5'- or 3'-end genes. We further evaluated the predicted ATUs by Gene Ontology and Kyoto Encyclopedia of Genes and Genomes functional enrichment analyses. The results suggested that gene pairs frequently encoded in the same ATUs are more functionally related than those that can belong to two distinct ATUs. Overall, these results demonstrated the high reliability of predicted ATUs. We expect that the new insights derived by SeqATU will not only improve the understanding of the transcription mechanism of bacteria but also guide the reconstruction of a genome-scale transcriptional regulatory network.
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Affiliation(s)
- Qi Wang
- School of Mathematics, Shandong University, Jinan 250200, China
| | - Zhaoqian Liu
- School of Mathematics, Shandong University, Jinan 250200, China.,Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Bo Yan
- New England Biolabs Inc., Ipswich, MA 01938, USA
| | - Wen-Chi Chou
- Infectious Disease and Microbiome Program, Broad Institute of MIT and Harvard, Cambridge, MA 02142, USA
| | | | - Qin Ma
- Department of Biomedical Informatics, College of Medicine, The Ohio State University, Columbus, OH 43210, USA
| | - Bingqiang Liu
- School of Mathematics, Shandong University, Jinan 250200, China
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3
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King ZA, Lloyd CJ, Feist AM, Palsson BO. Next-generation genome-scale models for metabolic engineering. Curr Opin Biotechnol 2015; 35:23-9. [DOI: 10.1016/j.copbio.2014.12.016] [Citation(s) in RCA: 130] [Impact Index Per Article: 14.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2014] [Revised: 12/06/2014] [Accepted: 12/17/2014] [Indexed: 11/26/2022]
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4
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Simons M, Saha R, Guillard L, Clément G, Armengaud P, Cañas R, Maranas CD, Lea PJ, Hirel B. Nitrogen-use efficiency in maize (Zea mays L.): from 'omics' studies to metabolic modelling. JOURNAL OF EXPERIMENTAL BOTANY 2014; 65:5657-71. [PMID: 24863438 DOI: 10.1093/jxb/eru227] [Citation(s) in RCA: 32] [Impact Index Per Article: 3.2] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 05/18/2023]
Abstract
In this review, we will present the latest developments in systems biology with particular emphasis on improving nitrogen-use efficiency (NUE) in crops such as maize and demonstrating the application of metabolic models. The review highlights the importance of improving NUE in crops and provides an overview of the transcriptome, proteome, and metabolome datasets available, focusing on a comprehensive understanding of nitrogen regulation. 'Omics' data are hard to interpret in the absence of metabolic flux information within genome-scale models. These models, when integrated with 'omics' data, can serve as a basis for generating predictions that focus and guide further experimental studies. By simulating different nitrogen (N) conditions at a pseudo-steady state, the reactions affecting NUE and additional gene regulations can be determined. Such models thus provide a framework for improving our understanding of the metabolic processes underlying the more efficient use of N-based fertilizers.
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Affiliation(s)
- Margaret Simons
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Rajib Saha
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Lenaïg Guillard
- Adaptation des Plantes à leur Environnement, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, RD 10, 78026 Versailles cedex, France
| | - Gilles Clément
- Plateau Technique Spécifique de Chimie du Végétal, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Route de St Cyr, F-78026 Versailles Cedex, France
| | - Patrick Armengaud
- Adaptation des Plantes à leur Environnement, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, RD 10, 78026 Versailles cedex, France
| | - Rafael Cañas
- Adaptation des Plantes à leur Environnement, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, RD 10, 78026 Versailles cedex, France
| | - Costas D Maranas
- Department of Chemical Engineering, The Pennsylvania State University, University Park, PA 16802, USA
| | - Peter J Lea
- Lancaster Environment Centre, Lancaster University, Lancaster LA1 4YQ, UK
| | - Bertrand Hirel
- Adaptation des Plantes à leur Environnement, Unité Mixte de Recherche 1318, INRA-Agro-ParisTech, Institut Jean-Pierre Bourgin, Institut National de la Recherche Agronomique (INRA), Centre de Versailles-Grignon, RD 10, 78026 Versailles cedex, France
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5
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Brophy JAN, Voigt CA. Principles of genetic circuit design. Nat Methods 2014; 11:508-20. [PMID: 24781324 DOI: 10.1038/nmeth.2926] [Citation(s) in RCA: 566] [Impact Index Per Article: 56.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/24/2014] [Accepted: 03/18/2014] [Indexed: 12/17/2022]
Abstract
Cells navigate environments, communicate and build complex patterns by initiating gene expression in response to specific signals. Engineers seek to harness this capability to program cells to perform tasks or create chemicals and materials that match the complexity seen in nature. This Review describes new tools that aid the construction of genetic circuits. Circuit dynamics can be influenced by the choice of regulators and changed with expression 'tuning knobs'. We collate the failure modes encountered when assembling circuits, quantify their impact on performance and review mitigation efforts. Finally, we discuss the constraints that arise from circuits having to operate within a living cell. Collectively, better tools, well-characterized parts and a comprehensive understanding of how to compose circuits are leading to a breakthrough in the ability to program living cells for advanced applications, from living therapeutics to the atomic manufacturing of functional materials.
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Affiliation(s)
- Jennifer A N Brophy
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
| | - Christopher A Voigt
- Synthetic Biology Center, Department of Biological Engineering, Massachusetts Institute of Technology, Cambridge, Massachusetts, USA
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6
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Physiological and Molecular Timing of the Glucose to Acetate Transition in Escherichia coli. Metabolites 2013; 3:820-37. [PMID: 24958151 PMCID: PMC3901295 DOI: 10.3390/metabo3030820] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/07/2013] [Revised: 08/28/2013] [Accepted: 09/04/2013] [Indexed: 11/17/2022] Open
Abstract
The glucose-acetate transition in Escherichia coli is a classical model of metabolic adaptation. Here, we describe the dynamics of the molecular processes involved in this metabolic transition, with a particular focus on glucose exhaustion. Although changes in the metabolome were observed before glucose exhaustion, our results point to a massive reshuffling at both the transcriptome and metabolome levels in the very first min following glucose exhaustion. A new transcriptional pattern, involving a change in genome expression in one-sixth of the E. coli genome, was established within 10 min and remained stable until the acetate was completely consumed. Changes in the metabolome took longer and stabilized 40 min after glucose exhaustion. Integration of multi-omics data revealed different modifications and timescales between the transcriptome and metabolome, but both point to a rapid adaptation of less than an hour. This work provides detailed information on the order, timing and extent of the molecular and physiological events that occur during the glucose-acetate transition and that are of particular interest for the development of dynamic models of metabolism.
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Somvanshi PR, Venkatesh KV. A conceptual review on systems biology in health and diseases: from biological networks to modern therapeutics. SYSTEMS AND SYNTHETIC BIOLOGY 2013; 8:99-116. [PMID: 24592295 DOI: 10.1007/s11693-013-9125-3] [Citation(s) in RCA: 40] [Impact Index Per Article: 3.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/07/2013] [Accepted: 09/10/2013] [Indexed: 12/28/2022]
Abstract
Human physiology is an ensemble of various biological processes spanning from intracellular molecular interactions to the whole body phenotypic response. Systems biology endures to decipher these multi-scale biological networks and bridge the link between genotype to phenotype. The structure and dynamic properties of these networks are responsible for controlling and deciding the phenotypic state of a cell. Several cells and various tissues coordinate together to generate an organ level response which further regulates the ultimate physiological state. The overall network embeds a hierarchical regulatory structure, which when unusually perturbed can lead to undesirable physiological state termed as disease. Here, we treat a disease diagnosis problem analogous to a fault diagnosis problem in engineering systems. Accordingly we review the application of engineering methodologies to address human diseases from systems biological perspective. The review highlights potential networks and modeling approaches used for analyzing human diseases. The application of such analysis is illustrated in the case of cancer and diabetes. We put forth a concept of cell-to-human framework comprising of five modules (data mining, networking, modeling, experimental and validation) for addressing human physiology and diseases based on a paradigm of system level analysis. The review overtly emphasizes on the importance of multi-scale biological networks and subsequent modeling and analysis for drug target identification and designing efficient therapies.
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Affiliation(s)
- Pramod Rajaram Somvanshi
- Biosystems Engineering, Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076 Maharashtra India
| | - K V Venkatesh
- Biosystems Engineering, Department of Chemical Engineering, Indian Institute of Technology Bombay, Powai, Mumbai, 400076 Maharashtra India
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8
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Mackenzie A. Synthetic biology and the technicity of biofuels. STUDIES IN HISTORY AND PHILOSOPHY OF BIOLOGICAL AND BIOMEDICAL SCIENCES 2013; 44:190-198. [PMID: 23591047 DOI: 10.1016/j.shpsc.2013.03.014] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/02/2023]
Abstract
The principal existing real-world application of synthetic biology is biofuels. Several 'next generation biofuel' companies-Synthetic Genomics, Amyris and Joule Unlimited Technologies-claim to be using synthetic biology to make biofuels. The irony of this is that highly advanced science and engineering serves the very mundane and familiar realm of transport. Despite their rather prosaic nature, biofuels could offer an interesting way to highlight the novelty of synthetic biology from several angles at once. Drawing on the French philosopher of technology and biology Gilbert Simondon, we can understand biofuels as technical objects whose genesis involves processes of concretisation that negotiate between heterogeneous geographical, biological, technical, scientific and commercial realities. Simondon's notion of technicity, the degree of concretisation of a technical object, usefully conceptualises this relationality. Viewed in terms of technicity, we might understand better how technical entities, elements, and ensembles are coming into being in the name of synthetic biology. The broader argument here is that when we seek to identify the newness of disciplines, their newness might be less epistemic and more logistic.
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Affiliation(s)
- Adrian Mackenzie
- Centre for Economic and Social Aspects of Genomics (Cesagen), Lancaster University, Bailrigg LA14YD, UK.
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9
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Cho BK, Palsson B, Zengler K. Deciphering the regulatory codes in bacterial genomes. Biotechnol J 2011; 6:1052-63. [PMID: 21845736 DOI: 10.1002/biot.201000349] [Citation(s) in RCA: 9] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/02/2011] [Revised: 06/30/2011] [Accepted: 07/25/2011] [Indexed: 12/24/2022]
Abstract
Interactions between cis-regulatory elements and trans-acting factors are fundamental for cellular functions such as transcription. With the revolution in microarrays and sequencing technologies, genome-wide binding locations of trans-acting factors are being determined in large numbers. The richness of the genome-scale information has revealed that the nature of the bacterial transcriptome and regulome are considerably more complex than previously expected. In addition, the emerging view of the bacterial transcriptome is revising the concept of the operon organization of the genome. This review describes current advances in the genome-scale analysis of the interaction between cis-regulatory elements and trans-acting factors in microorganisms.
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Affiliation(s)
- Byung-Kwan Cho
- Department of Biological Sciences, Korea Advanced Institute of Science and Technology, Daejeon, Korea.
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10
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Ferenci T, Galbiati HF, Betteridge T, Phan K, Spira B. The constancy of global regulation across a species: the concentrations of ppGpp and RpoS are strain-specific in Escherichia coli. BMC Microbiol 2011; 11:62. [PMID: 21439067 PMCID: PMC3074542 DOI: 10.1186/1471-2180-11-62] [Citation(s) in RCA: 46] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2011] [Accepted: 03/25/2011] [Indexed: 12/21/2022] Open
Abstract
Background Sigma factors and the alarmone ppGpp control the allocation of RNA polymerase to promoters under stressful conditions. Both ppGpp and the sigma factor σS (RpoS) are potentially subject to variability across the species Escherichia coli. To find out the extent of strain variation we measured the level of RpoS and ppGpp using 31 E. coli strains from the ECOR collection and one reference K-12 strain. Results Nine ECORs had highly deleterious mutations in rpoS, 12 had RpoS protein up to 7-fold above that of the reference strain MG1655 and the remainder had comparable or lower levels. Strain variation was also evident in ppGpp accumulation under carbon starvation and spoT mutations were present in several low-ppGpp strains. Three relationships between RpoS and ppGpp levels were found: isolates with zero RpoS but various ppGpp levels, strains where RpoS levels were proportional to ppGpp and a third unexpected class in which RpoS was present but not proportional to ppGpp concentration. High-RpoS and high-ppGpp strains accumulated rpoS mutations under nutrient limitation, providing a source of polymorphisms. Conclusions The ppGpp and σS variance means that the expression of genes involved in translation, stress and other traits affected by ppGpp and/or RpoS are likely to be strain-specific and suggest that influential components of regulatory networks are frequently reset by microevolution. Different strains of E. coli have different relationships between ppGpp and RpoS levels and only some exhibit a proportionality between increasing ppGpp and RpoS levels as demonstrated for E. coli K-12.
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Affiliation(s)
- Thomas Ferenci
- School of Molecular and Microbial Biosciences, The University of Sydney, NSW, Australia
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11
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Chen Y. Development and application of co-culture for ethanol production by co-fermentation of glucose and xylose: a systematic review. J Ind Microbiol Biotechnol 2010; 38:581-97. [PMID: 21104106 DOI: 10.1007/s10295-010-0894-3] [Citation(s) in RCA: 113] [Impact Index Per Article: 8.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2010] [Accepted: 10/21/2010] [Indexed: 01/29/2023]
Abstract
This article reviews current co-culture systems for fermenting mixtures of glucose and xylose to ethanol. Thirty-five co-culture systems that ferment either synthetic glucose and xylose mixture or various biomass hydrolysates are examined. Strain combinations, fermentation modes and conditions, and fermentation performance for these co-culture systems are compared and discussed. It is noted that the combination of Pichia stipitis with Saccharomyces cerevisiae or its respiratory-deficient mutant is most commonly used. One of the best results for fermentation of glucose and xylose mixture is achieved by using co-culture of immobilized Zymomonas mobilis and free cells of P. stipitis, giving volumetric ethanol production of 1.277 g/l/h and ethanol yield of 0.49-0.50 g/g. The review discloses that, as a strategy for efficient conversion of glucose and xylose, co-culture fermentation for ethanol production from lignocellulosic biomass can increase ethanol yield and production rate, shorten fermentation time, and reduce process costs, and it is a promising technology although immature.
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Affiliation(s)
- Yanli Chen
- Department of Chemical Engineering, Auburn University, Auburn, AL 36849, USA.
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12
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Gowen CM, Fong SS. Genome-scale metabolic model integrated with RNAseq data to identify metabolic states of Clostridium thermocellum. Biotechnol J 2010; 5:759-67. [PMID: 20665646 DOI: 10.1002/biot.201000084] [Citation(s) in RCA: 47] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/13/2022]
Abstract
Constraint-based genome-scale metabolic models are becoming an established tool for using genomic and biochemical information to predict cellular phenotypes. While these models provide quantitative predictions for individual reactions and are readily scalable for any biological system, they have inherent limitations. Using current methods, it is difficult to computationally elucidate a specific network state that directly depicts an in vivo state, especially in the instances where the organism might be functionally in a suboptimal state. In this study, we generated RNA sequencing data to characterize the transcriptional state of the cellulolytic anaerobe, Clostridium thermocellum, and algorithmically integrated these data with a genome-scale metabolic model. The phenotypes of each calculated metabolic flux state were compared to 13 experimentally determined physiological parameters to identify the flux mapping that best matched the in vitro growth of C. thermocellum. By this approach we found predicted fluxes for 88 reactions to be changed between the best solely computational prediction (flux balance analysis) and the best experimentally derived prediction. The alteration of these 88 reaction fluxes led to a detailed network-wide flux mapping that was able to capture the suboptimal cellular state of C. thermocellum.
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Affiliation(s)
- Christopher M Gowen
- Chemical and Life Science Engineering, Virginia Commonwealth University, 601 W. Main Street, Richmond, VA 23284, USA
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Clancy K, Voigt CA. Programming cells: towards an automated 'Genetic Compiler'. Curr Opin Biotechnol 2010; 21:572-81. [PMID: 20702081 PMCID: PMC2950163 DOI: 10.1016/j.copbio.2010.07.005] [Citation(s) in RCA: 48] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/06/2010] [Accepted: 07/08/2010] [Indexed: 10/19/2022]
Abstract
One of the visions of synthetic biology is to be able to program cells using a language that is similar to that used to program computers or robotics. For large genetic programs, keeping track of the DNA on the level of nucleotides becomes tedious and error prone, requiring a new generation of computer-aided design (CAD) software. To push the size of projects, it is important to abstract the designer from the process of part selection and optimization. The vision is to specify genetic programs in a higher-level language, which a genetic compiler could automatically convert into a DNA sequence. Steps towards this goal include: defining the semantics of the higher-level language, algorithms to select and assemble parts, and biophysical methods to link DNA sequence to function. These will be coupled to graphic design interfaces and simulation packages to aid in the prediction of program dynamics, optimize genes, and scan projects for errors.
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Affiliation(s)
- Kevin Clancy
- Life Technologies, 5791 Van Allen Way, Carlsbad, CA, 90028
| | - Christopher A. Voigt
- Department of Pharmaceutical Chemistry, University of California-San Francisco, MC 2540, Room 408C, 1700 4 Street, San Francisco, CA 94158
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Boghigian BA, Shi H, Lee K, Pfeifer BA. Utilizing elementary mode analysis, pathway thermodynamics, and a genetic algorithm for metabolic flux determination and optimal metabolic network design. BMC SYSTEMS BIOLOGY 2010; 4:49. [PMID: 20416071 PMCID: PMC2880971 DOI: 10.1186/1752-0509-4-49] [Citation(s) in RCA: 31] [Impact Index Per Article: 2.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/24/2009] [Accepted: 04/23/2010] [Indexed: 12/25/2022]
Abstract
BACKGROUND Microbial hosts offer a number of unique advantages when used as production systems for both native and heterologous small-molecules. These advantages include high selectivity and benign environmental impact; however, a principal drawback is low yield and/or productivity, which limits economic viability. Therefore a major challenge in developing a microbial production system is to maximize formation of a specific product while sustaining cell growth. Tools to rationally reconfigure microbial metabolism for these potentially conflicting objectives remain limited. Exhaustively exploring combinations of genetic modifications is both experimentally and computationally inefficient, and can become intractable when multiple gene deletions or insertions need to be considered. Alternatively, the search for desirable gene modifications may be solved heuristically as an evolutionary optimization problem. In this study, we combine a genetic algorithm and elementary mode analysis to develop an optimization framework for evolving metabolic networks with energetically favorable pathways for production of both biomass and a compound of interest. RESULTS Utilization of thermodynamically-weighted elementary modes for flux reconstruction of E. coli central metabolism revealed two clusters of EMs with respect to their Delta Gp degrees. For proof of principle testing, the algorithm was applied to ethanol and lycopene production in E. coli. The algorithm was used to optimize product formation, biomass formation, and product and biomass formation simultaneously. Predicted knockouts often matched those that have previously been implemented experimentally for improved product formation. The performance of a multi-objective genetic algorithm showed that it is better to couple the two objectives in a single objective genetic algorithm. CONCLUSION A computationally tractable framework is presented for the redesign of metabolic networks for maximal product formation combining elementary mode analysis (a form of convex analysis), pathway thermodynamics, and a genetic algorithm to optimize the production of two industrially-relevant products, ethanol and lycopene, from E. coli. The designed algorithm can be applied to any small-scale model of cellular metabolism theoretically utilizing any substrate and applied towards the production of any product.
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Affiliation(s)
- Brett A Boghigian
- Tufts University, Department of Chemical & Biological Engineering, Science & Technology Center, 4 Colby Street, Medford, MA 02155, USA
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15
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Dietz S, Panke S. Microbial systems engineering: First successes and the way ahead. Bioessays 2010; 32:356-62. [DOI: 10.1002/bies.200900174] [Citation(s) in RCA: 11] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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16
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Dauner M. From fluxes and isotope labeling patterns towards in silico cells. Curr Opin Biotechnol 2010; 21:55-62. [DOI: 10.1016/j.copbio.2010.01.014] [Citation(s) in RCA: 25] [Impact Index Per Article: 1.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/14/2009] [Revised: 01/23/2010] [Accepted: 01/31/2010] [Indexed: 10/19/2022]
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17
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Synthetic biology: tools to design, build, and optimize cellular processes. J Biomed Biotechnol 2010; 2010:130781. [PMID: 20150964 PMCID: PMC2817555 DOI: 10.1155/2010/130781] [Citation(s) in RCA: 52] [Impact Index Per Article: 3.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/05/2009] [Accepted: 10/28/2009] [Indexed: 11/17/2022] Open
Abstract
The general central
dogma frames the emergent properties of life,
which make biology both necessary and difficult
to engineer. In a process engineering paradigm,
each biological process stream and process unit
is heavily influenced by regulatory interactions
and interactions with the surrounding
environment. Synthetic biology is developing the
tools and methods that will increase control
over these interactions, eventually resulting in
an integrative synthetic biology that will allow
ground-up cellular optimization. In this review,
we attempt to contextualize the areas of
synthetic biology into three tiers: (1) the
process units and associated streams of the
central dogma, (2) the intrinsic regulatory
mechanisms, and (3) the extrinsic physical and
chemical environment. Efforts at each of these
three tiers attempt to control cellular systems
and take advantage of emerging tools and
approaches. Ultimately, it will be possible to
integrate these approaches and realize the
vision of integrative synthetic biology when
cells are completely rewired for
biotechnological goals. This review will
highlight progress towards this goal as well as
areas requiring further research.
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18
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Cho BK, Zengler K, Qiu Y, Park YS, Knight EM, Barrett CL, Gao Y, Palsson BØ. The transcription unit architecture of the Escherichia coli genome. Nat Biotechnol 2009; 27:1043-9. [PMID: 19881496 DOI: 10.1038/nbt.1582] [Citation(s) in RCA: 200] [Impact Index Per Article: 13.3] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/20/2009] [Accepted: 10/09/2009] [Indexed: 01/26/2023]
Abstract
Bacterial genomes are organized by structural and functional elements, including promoters, transcription start and termination sites, open reading frames, regulatory noncoding regions, untranslated regions and transcription units. Here, we iteratively integrate high-throughput, genome-wide measurements of RNA polymerase binding locations and mRNA transcript abundance, 5' sequences and translation into proteins to determine the organizational structure of the Escherichia coli K-12 MG1655 genome. Integration of the organizational elements provides an experimentally annotated transcription unit architecture, including alternative transcription start sites, 5' untranslated region, boundaries and open reading frames of each transcription unit. A total of 4,661 transcription units were identified, representing an increase of >530% over current knowledge. This comprehensive transcription unit architecture allows for the elucidation of condition-specific uses of alternative sigma factors at the genome scale. Furthermore, the transcription unit architecture provides a foundation on which to construct genome-scale transcriptional and translational regulatory networks.
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Affiliation(s)
- Byung-Kwan Cho
- Department of Bioengineering, University of California, San Diego, La Jolla, California, USA
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Jayaraman A, Wood TK. Bacterial quorum sensing: signals, circuits, and implications for biofilms and disease. Annu Rev Biomed Eng 2008; 10:145-67. [PMID: 18647113 DOI: 10.1146/annurev.bioeng.10.061807.160536] [Citation(s) in RCA: 200] [Impact Index Per Article: 12.5] [Reference Citation Analysis] [Abstract] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/09/2022]
Abstract
Communication between bacteria, belonging to the same species or to different species, is mediated through different chemical signals that are synthesized and secreted by bacteria. These signals can either be cell-density related (autoinducers) or be produced by bacteria at different stages of growth, and they allow bacteria to monitor their environment and alter gene expression to derive a competitive advantage. The properties of these signals and the response elicited by them are important in ensuring bacterial survival and propagation in natural environments (e.g., human oral cavity) where hundreds of bacterial species coexist. First, the interaction between a signal and its receptor is very specific, which underlies intraspecies communication and quorum sensing. Second, when multiple signals are synthesized by the same bacterium, the signaling circuits utilized by the different signals are coordinately regulated with distinct overall circuit architecture so as to maximize the overall response. Third, the recognition of a universal communication signal synthesized by different bacterial species (interspecies communication), as well that of signals produced by eukaryotic cells (interkingdom communication), is also integral to the formation of multispecies biofilm communities that are important in infection and disease. The focus of this review is on the principles underlying signal-mediated bacterial communication, with specific emphasis on the potential for using them in two applications-development of synthetic biology modules and circuits, and the control of biofilm formation and infection.
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Affiliation(s)
- Arul Jayaraman
- Departments of Chemical Engineering and Biomedical Engineering, Texas A&M University, College Station, TX 77843, USA.
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