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Xue T, Chen D, Zhang T, Chen Y, Fan H, Huang Y, Zhong Q, Li B. Chromosome-scale assembly and population diversity analyses provide insights into the evolution of Sapindus mukorossi. HORTICULTURE RESEARCH 2022; 9:6529164. [PMID: 35178562 PMCID: PMC8854635 DOI: 10.1093/hr/uhac012] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/27/2021] [Accepted: 12/03/2021] [Indexed: 05/25/2023]
Abstract
Sapindus mukorossi is an environmentally friendly plant and renewable energy source whose fruit has been widely used for biomedicine, biodiesel, and biological chemicals due to its richness in saponin and oil contents. Here, we report the first chromosome-scale genome assembly of S. mukorossi (covering ~391 Mb with a scaffold N50 of 24.66 Mb) and characterize its genetic architecture and evolution by resequencing 104 S. mukorossi accessions. Population genetic analyses showed that genetic diversity in the southwestern distribution area was relatively higher than that in the northeastern distribution area. Gene flow events indicated that southwest species may be the donor population for the distribution areas in China. Genome-wide selective sweep analysis showed that a large number of genes are involved in defense responses, growth and development, including SmRPS2, SmRPS4, SmRPS7, SmNAC2, SmNAC23, SmNAC102, SmWRKY6, SmWRKY26, and SmWRKY33. We also identified several candidate genes controlling six agronomic traits by genome-wide association studies, including SmPCBP2, SmbHLH1, SmCSLD1, SmPP2C, SmLRR-RKs, and SmAHP. Our study not only provides a rich genomic resource for further basic research on Sapindaceae woody trees but also identifies several economically significant genes for genomics-enabled improvements in molecular breeding.
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Affiliation(s)
- Ting Xue
- Fujian Provincial Key Laboratory for Plant Eco-physiology, State Key Laboratory for Subtropical Mountain Ecology of the Ministry of Science and Technology and Fujian Province, College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
- College of Life Sciences, Fujian Normal University, Fuzhou 350117, China
| | - Duo Chen
- College of Life Sciences, Fujian Normal University, Fuzhou 350117, China
| | - Tianyu Zhang
- Shunchang County Forestry Science and Technology Center of Fujian Province, Forestry Bureau of Shunchang, Shunchang 353200, China
| | - Youqiang Chen
- College of Life Sciences, Fujian Normal University, Fuzhou 350117, China
| | - Huihua Fan
- Research Institute of Forestry, Fujian Research Institute of Forestry, Fuzhou 350000, China
| | - Yunpeng Huang
- Research Institute of Forestry, Fujian Research Institute of Forestry, Fuzhou 350000, China
| | - Quanlin Zhong
- Fujian Provincial Key Laboratory for Plant Eco-physiology, State Key Laboratory for Subtropical Mountain Ecology of the Ministry of Science and Technology and Fujian Province, College of Geographical Sciences, Fujian Normal University, Fuzhou 350007, China
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Zheng X, Chen D, Chen B, Liang L, Huang Z, Fan W, Chen J, He W, Chen H, Huang L, Chen Y, Zhu J, Xue T. Insights into salvianolic acid B biosynthesis from chromosome-scale assembly of the Salvia bowleyana genome. JOURNAL OF INTEGRATIVE PLANT BIOLOGY 2021; 63:1309-1323. [PMID: 33634943 DOI: 10.1111/jipb.13085] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2021] [Accepted: 02/26/2021] [Indexed: 05/21/2023]
Abstract
Salvia bowleyana is a traditional Chinese medicinal plant that is a source of nutritional supplements rich in salvianolic acid B and a potential experimental system for the exploration of salvianolic acid B biosynthesis in the Labiatae. Here, we report a high-quality chromosome-scale genome assembly of S. bowleyana covering 462.44 Mb, with a scaffold N50 value of 57.96 Mb and 44,044 annotated protein-coding genes. Evolutionary analysis revealed an estimated divergence time between S. bowleyana and its close relative S. miltiorrhiza of ~3.94 million years. We also observed evidence of a whole-genome duplication in the S. bowleyana genome. Transcriptome analysis showed that SbPAL1 (PHENYLALANINE AMMONIA-LYASE1) is highly expressed in roots relative to stem and leaves, paralleling the location of salvianolic acid B accumulation. The laccase gene family in S. bowleyana outnumbered their counterparts in both S. miltiorrhiza and Arabidopsis thaliana, suggesting that the gene family has undergone expansion in S. bowleyana. Several laccase genes were also highly expressed in roots, where their encoded proteins may catalyze the oxidative reaction from rosmarinic acid to salvianolic acid B. These findings provide an invaluable genomic resource for understanding salvianolic acid B biosynthesis and its regulation, and will be useful for exploring the evolution of the Labiatae.
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Affiliation(s)
- Xuehai Zheng
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Duo Chen
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Binghua Chen
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Limin Liang
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Zhen Huang
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Wenfang Fan
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Jiannan Chen
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Wenjin He
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Huibin Chen
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Luqiang Huang
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Youqiang Chen
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Jinmao Zhu
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
| | - Ting Xue
- The Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Southern Institute of Oceanography, College of Life Sciences, Fujian Normal University, Fuzhou, 350117, China
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3
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Legrand J, Artu A, Pruvost J. A review on photobioreactor design and modelling for microalgae production. REACT CHEM ENG 2021. [DOI: 10.1039/d0re00450b] [Citation(s) in RCA: 13] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/18/2022]
Abstract
From the cell to the photobioreactor and to the industrial exploitation of microalgae, through the controlled experiments and modelling.
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Affiliation(s)
- Jack Legrand
- University of Nantes
- CNRS, ONIRIS, GEPEA, UMR6144
- 44602 Saint-Nazaire Cedex
- France
| | - Arnaud Artu
- Total, Direction générale Raffinage-Chimie
- Division Biofuels
- Tour Coupole
- 92078 Paris La Défense
- France
| | - Jérémy Pruvost
- University of Nantes
- CNRS, ONIRIS, GEPEA, UMR6144
- 44602 Saint-Nazaire Cedex
- France
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Correa SM, Fernie AR, Nikoloski Z, Brotman Y. Towards model-driven characterization and manipulation of plant lipid metabolism. Prog Lipid Res 2020; 80:101051. [PMID: 32640289 DOI: 10.1016/j.plipres.2020.101051] [Citation(s) in RCA: 21] [Impact Index Per Article: 5.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/07/2020] [Revised: 06/20/2020] [Accepted: 06/21/2020] [Indexed: 01/09/2023]
Abstract
Plant lipids have versatile applications and provide essential fatty acids in human diet. Therefore, there has been a growing interest to better characterize the genetic basis, regulatory networks, and metabolic pathways that shape lipid quantity and composition. Addressing these issues is challenging due to context-specificity of lipid metabolism integrating environmental, developmental, and tissue-specific cues. Here we systematically review the known metabolic pathways and regulatory interactions that modulate the levels of storage lipids in oilseeds. We argue that the current understanding of lipid metabolism provides the basis for its study in the context of genome-wide plant metabolic networks with the help of approaches from constraint-based modeling and metabolic flux analysis. The focus is on providing a comprehensive summary of the state-of-the-art of modeling plant lipid metabolic pathways, which we then contrast with the existing modeling efforts in yeast and microalgae. We then point out the gaps in knowledge of lipid metabolism, and enumerate the recent advances of using genome-wide association and quantitative trait loci mapping studies to unravel the genetic regulations of lipid metabolism. Finally, we offer a perspective on how advances in the constraint-based modeling framework can propel further characterization of plant lipid metabolism and its rational manipulation.
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Affiliation(s)
- Sandra M Correa
- Genetics of Metabolic Traits Group, Max Planck Institute for Molecular Plant Physiology, Potsdam 14476, Germany; Department of Life Sciences, Ben-Gurion University of the Negev, 8410501 Beer-Sheva, Israel; Departamento de Ciencias Exactas y Naturales, Universidad de Antioquia, Medellín 050010, Colombia.
| | - Alisdair R Fernie
- Central Metabolism Group, Max Planck Institute for Molecular Plant Physiology, Potsdam 14476, Germany; Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria
| | - Zoran Nikoloski
- Center of Plant Systems Biology and Biotechnology, Plovdiv, Bulgaria; Bioinformatics, Institute of Biochemistry and Biology, University of Potsdam, 14476 Potsdam, Germany; Systems Biology and Mathematical Modelling Group, Max Planck Institute for Molecular Plant Physiology, Potsdam-Golm 14476, Germany.
| | - Yariv Brotman
- Genetics of Metabolic Traits Group, Max Planck Institute for Molecular Plant Physiology, Potsdam 14476, Germany; Department of Life Sciences, Ben-Gurion University of the Negev, 8410501 Beer-Sheva, Israel
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5
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Xue T, Zheng X, Chen D, Liang L, Chen N, Huang Z, Fan W, Chen J, Cen W, Chen S, Zhu J, Chen B, Zhang X, Chen Y. A high-quality genome provides insights into the new taxonomic status and genomic characteristics of Cladopus chinensis (Podostemaceae). HORTICULTURE RESEARCH 2020; 7:46. [PMID: 32257232 PMCID: PMC7109043 DOI: 10.1038/s41438-020-0269-5] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/02/2019] [Revised: 02/08/2020] [Accepted: 02/11/2020] [Indexed: 05/08/2023]
Abstract
The Podostemaceae are ecologically and morphologically unusual aquatic angiosperms that survive only in rivers with pristine hydrology and high water quality and are at a relatively high risk of extinction. The taxonomic status of Podostemaceae has always been controversial. Here, we report the first high-quality genome assembly for Cladopus chinensis of Podostemaceae, obtained by incorporating Hi-C, Illumina and PacBio sequencing. We generated an 827.92 Mb genome with a contig N50 of 1.42 Mb and 27,370 annotated protein-coding genes. The assembled genome size was close to the estimated size, and 659.42 Mb of the assembly was assigned to 29 superscaffolds (scaffold N50 21.22 Mb). A total of 59.20% repetitive sequences were identified, among which long terminal repeats (LTRs) were the most abundant class (28.97% of the genome). Genome evolution analysis suggested that the divergence time of Cladopus chinensis (106 Mya) was earlier than that of Malpighiales (82 Mya) and that this taxon diverged into an independent branch of Podestemales. A recent whole-genome duplication (WGD) event occurred 4.43 million years ago. Comparative genomic analysis revealed that the expansion and contraction of oxidative phosphorylation, photosynthesis and isoflavonoid metabolism genes in Cladopus chinensis are probably related to the genomic characteristics of this growing submerged species. Transcriptome analysis revealed that upregulated genes in the shoot group compared to the root group were enriched in the NAC gene family and transcription factors associated with shoot development and defense responses, including WUSCHEL (WUS), ASYMMETRIC LEAVES (ASL), SHOOT MERISTEMLESS (STM), NAC2, NAC8, NAC29, NAC47, NAC73, NAC83 and NAC102. These findings provide new insights into the genomic diversity of unusual aquatic angiosperms and serve as a valuable reference for the taxonomic status and unusual shoot apical meristem of Podostemaceae.
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Affiliation(s)
- Ting Xue
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
- Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Southern Institute of Oceanography, Fujian Normal University, Fuzhou, China
| | - Xuehai Zheng
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Duo Chen
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Limin Liang
- Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Southern Institute of Oceanography, Fujian Normal University, Fuzhou, China
| | - Nan Chen
- College of Fine Arts, Fujian Normal University, Fuzhou, China
| | - Zhen Huang
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Wenfang Fan
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Jiannan Chen
- Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Southern Institute of Oceanography, Fujian Normal University, Fuzhou, China
| | - Wan Cen
- Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Southern Institute of Oceanography, Fujian Normal University, Fuzhou, China
| | - Shuai Chen
- FAFU and UIUC-SIB Joint Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Jinmao Zhu
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Binghua Chen
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
| | - Xingtan Zhang
- FAFU and UIUC-SIB Joint Center for Genomics and Biotechnology, Fujian Provincial Key Laboratory of Haixia Applied Plant Systems Biology, Key Laboratory of Genetics, Breeding and Multiple Utilization of Crops, Ministry of Education, Fujian Agriculture and Forestry University, Fuzhou, China
| | - Youqiang Chen
- Public Service Platform for Industrialization Development Technology of Marine Biological Medicine and Products of the State Oceanic Administration, Fujian Key Laboratory of Special Marine Bioresource Sustainable Utilization, Key Laboratory of Developmental and Neural Biology, College of Life Sciences, Fujian Normal University, Fuzhou, China
- Center of Engineering Technology Research for Microalga Germplasm Improvement of Fujian, Southern Institute of Oceanography, Fujian Normal University, Fuzhou, China
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Shahid A, Rehman AU, Usman M, Ashraf MUF, Javed MR, Khan AZ, Gill SS, Mehmood MA. Engineering the metabolic pathways of lipid biosynthesis to develop robust microalgal strains for biodiesel production. Biotechnol Appl Biochem 2020; 67:41-51. [DOI: 10.1002/bab.1812] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2019] [Accepted: 09/03/2019] [Indexed: 01/29/2023]
Affiliation(s)
- Ayesha Shahid
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
| | - Abd ur Rehman
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
| | - Muhammad Usman
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
| | - Muhammad Umer Farooq Ashraf
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
| | - Muhammad Rizwan Javed
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
| | - Aqib Zafar Khan
- State Key Laboratory of Microbial MetabolismJoint International Research Laboratory of Metabolic & Developmental Sciences of Ministry of Education, School of Life Science and BiotechnologyShanghai Jiao Tong University Shanghai People's Republic of China
| | - Saba Shahid Gill
- Department of Plant and Environmental SciencesNew Mexico State University Las Cruces NM USA
| | - Muhammad Aamer Mehmood
- Bioenergy Research CenterDepartment of Bioinformatics and BiotechnologyGovernment College University Faisalabad Faisalabad Pakistan
- School of BioengineeringSichuan University of Science & Engineering Zigong People's Republic of China
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INDISIM-Denitrification, an individual-based model for study the denitrification process. J Ind Microbiol Biotechnol 2019; 47:1-20. [PMID: 31691030 DOI: 10.1007/s10295-019-02245-8] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2019] [Accepted: 10/28/2019] [Indexed: 12/21/2022]
Abstract
Denitrification is one of the key processes of the global nitrogen (N) cycle driven by bacteria. It has been widely known for more than 100 years as a process by which the biogeochemical N-cycle is balanced. To study this process, we develop an individual-based model called INDISIM-Denitrification. The model embeds a thermodynamic model for bacterial yield prediction inside the individual-based model INDISIM and is designed to simulate in aerobic and anaerobic conditions the cell growth kinetics of denitrifying bacteria. INDISIM-Denitrification simulates a bioreactor that contains a culture medium with succinate as a carbon source, ammonium as nitrogen source and various electron acceptors. To implement INDISIM-Denitrification, the individual-based model INDISIM was used to give sub-models for nutrient uptake, stirring and reproduction cycle. Using a thermodynamic approach, the denitrification pathway, cellular maintenance and individual mass degradation were modeled using microbial metabolic reactions. These equations are the basis of the sub-models for metabolic maintenance, individual mass synthesis and reducing internal cytotoxic products. The model was implemented in the open-access platform NetLogo. INDISIM-Denitrification is validated using a set of experimental data of two denitrifying bacteria in two different experimental conditions. This provides an interactive tool to study the denitrification process carried out by any denitrifying bacterium since INDISIM-Denitrification allows changes in the microbial empirical formula and in the energy-transfer-efficiency used to represent the metabolic pathways involved in the denitrification process. The simulator can be obtained from the authors on request.
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8
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León-Saiki GM, Ferrer Ledo N, Lao-Martil D, van der Veen D, Wijffels RH, Martens DE. Metabolic modelling and energy parameter estimation of Tetradesmus obliquus. ALGAL RES 2018. [DOI: 10.1016/j.algal.2018.09.008] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/09/2023]
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Tibocha-Bonilla JD, Zuñiga C, Godoy-Silva RD, Zengler K. Advances in metabolic modeling of oleaginous microalgae. BIOTECHNOLOGY FOR BIOFUELS 2018; 11:241. [PMID: 30202436 PMCID: PMC6124020 DOI: 10.1186/s13068-018-1244-3] [Citation(s) in RCA: 26] [Impact Index Per Article: 4.3] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2018] [Accepted: 08/27/2018] [Indexed: 06/08/2023]
Abstract
Production of biofuels and bioenergy precursors by phototrophic microorganisms, such as microalgae and cyanobacteria, is a promising alternative to conventional fuels obtained from non-renewable resources. Several species of microalgae have been investigated as potential candidates for the production of biofuels, for the most part due to their exceptional metabolic capability to accumulate large quantities of lipids. Constraint-based modeling, a systems biology approach that accurately predicts the metabolic phenotype of phototrophs, has been deployed to identify suitable culture conditions as well as to explore genetic enhancement strategies for bioproduction. Core metabolic models were employed to gain insight into the central carbon metabolism in photosynthetic microorganisms. More recently, comprehensive genome-scale models, including organelle-specific information at high resolution, have been developed to gain new insight into the metabolism of phototrophic cell factories. Here, we review the current state of the art of constraint-based modeling and computational method development and discuss how advanced models led to increased prediction accuracy and thus improved lipid production in microalgae.
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Affiliation(s)
- Juan D. Tibocha-Bonilla
- Grupo de Investigación en Procesos Químicos y Bioquímicos, Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Av. Carrera 30 No. 45-03, Bogotá, D.C. Colombia
| | - Cristal Zuñiga
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0760 USA
| | - Rubén D. Godoy-Silva
- Grupo de Investigación en Procesos Químicos y Bioquímicos, Departamento de Ingeniería Química y Ambiental, Universidad Nacional de Colombia, Av. Carrera 30 No. 45-03, Bogotá, D.C. Colombia
| | - Karsten Zengler
- Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0760 USA
- Department of Bioengineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0412 USA
- Center for Microbiome Innovation, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0436 USA
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10
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Arora N, Pienkos PT, Pruthi V, Poluri KM, Guarnieri MT. Leveraging algal omics to reveal potential targets for augmenting TAG accumulation. Biotechnol Adv 2018; 36:1274-1292. [PMID: 29678388 DOI: 10.1016/j.biotechadv.2018.04.005] [Citation(s) in RCA: 37] [Impact Index Per Article: 6.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/20/2017] [Revised: 04/11/2018] [Accepted: 04/15/2018] [Indexed: 02/08/2023]
Abstract
Ongoing global efforts to commercialize microalgal biofuels have expedited the use of multi-omics techniques to gain insights into lipid biosynthetic pathways. Functional genomics analyses have recently been employed to complement existing sequence-level omics studies, shedding light on the dynamics of lipid synthesis and its interplay with other cellular metabolic pathways, thus revealing possible targets for metabolic engineering. Here, we review the current status of algal omics studies to reveal potential targets to augment TAG accumulation in various microalgae. This review specifically aims to examine and catalog systems level data related to stress-induced TAG accumulation in oleaginous microalgae and inform future metabolic engineering strategies to develop strains with enhanced bioproductivity, which could pave a path for sustainable green energy.
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Affiliation(s)
- Neha Arora
- Department of Biotechnology, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
| | - Philip T Pienkos
- National Bioenergy Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
| | - Vikas Pruthi
- Department of Biotechnology, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
| | - Krishna Mohan Poluri
- Department of Biotechnology, Indian Institute of Technology Roorkee, Uttarakhand 247667, India
| | - Michael T Guarnieri
- National Bioenergy Center, National Renewable Energy Laboratory, Golden, CO 80401, USA.
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Moejes FW, Matuszynska A, Adhikari K, Bassi R, Cariti F, Cogne G, Dikaios I, Falciatore A, Finazzi G, Flori S, Goldschmidt-Clermont M, Magni S, Maguire J, Le Monnier A, Müller K, Poolman M, Singh D, Spelberg S, Stella GR, Succurro A, Taddei L, Urbain B, Villanova V, Zabke C, Ebenhöh O. A systems-wide understanding of photosynthetic acclimation in algae and higher plants. JOURNAL OF EXPERIMENTAL BOTANY 2017; 68:2667-2681. [PMID: 28830099 DOI: 10.1093/jxb/erx137] [Citation(s) in RCA: 15] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/12/2016] [Accepted: 03/28/2017] [Indexed: 05/27/2023]
Abstract
The ability of phototrophs to colonise different environments relies on robust protection against oxidative stress, a critical requirement for the successful evolutionary transition from water to land. Photosynthetic organisms have developed numerous strategies to adapt their photosynthetic apparatus to changing light conditions in order to optimise their photosynthetic yield, which is crucial for life on Earth to exist. Photosynthetic acclimation is an excellent example of the complexity of biological systems, where highly diverse processes, ranging from electron excitation over protein protonation to enzymatic processes coupling ion gradients with biosynthetic activity, interact on drastically different timescales from picoseconds to hours. Efficient functioning of the photosynthetic apparatus and its protection is paramount for efficient downstream processes, including metabolism and growth. Modern experimental techniques can be successfully integrated with theoretical and mathematical models to promote our understanding of underlying mechanisms and principles. This review aims to provide a retrospective analysis of multidisciplinary photosynthetic acclimation research carried out by members of the Marie Curie Initial Training Project, AccliPhot, placing the results in a wider context. The review also highlights the applicability of photosynthetic organisms for industry, particularly with regards to the cultivation of microalgae. It intends to demonstrate how theoretical concepts can successfully complement experimental studies broadening our knowledge of common principles in acclimation processes in photosynthetic organisms, as well as in the field of applied microalgal biotechnology.
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Affiliation(s)
- Fiona Wanjiku Moejes
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
- Bantry Marine Research Station, Gearhies, Bantry, Co. Cork, Ireland P75 AX07
| | - Anna Matuszynska
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
| | - Kailash Adhikari
- Department of Biological and Medical Sciences, Oxford Brookes University, United Kingdom
| | - Roberto Bassi
- University of Verona, Department of Biotechnology, Italy
| | - Federica Cariti
- Department of Botany and Plant Biology, University of Geneva, Switzerland
| | | | | | - Angela Falciatore
- Sorbonne Universités, UPMC, Institut de Biologie Paris-Seine, CNRS, Laboratoire de Biologie Computationnelle et Quantitative, 15 rue de l'Ecole de Médecine, 75006 Paris, France
| | - Giovanni Finazzi
- Laboratoire de Physiologie Cellulaire et Végétale, UMR 5168, Centre National de la Recherche Scientifique (CNRS), Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Institut National Recherche Agronomique (INRA), Institut de Biosciences et Biotechnologie de Grenoble (BIG), Université Grenoble Alpes (UGA), Grenoble 38100, France
| | - Serena Flori
- Laboratoire de Physiologie Cellulaire et Végétale, UMR 5168, Centre National de la Recherche Scientifique (CNRS), Commissariat à l'Energie Atomique et aux Energies Alternatives (CEA), Institut National Recherche Agronomique (INRA), Institut de Biosciences et Biotechnologie de Grenoble (BIG), Université Grenoble Alpes (UGA), Grenoble 38100, France
| | | | - Stefano Magni
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
| | - Julie Maguire
- Bantry Marine Research Station, Gearhies, Bantry, Co. Cork, Ireland P75 AX07
| | | | - Kathrin Müller
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
| | - Mark Poolman
- Bantry Marine Research Station, Gearhies, Bantry, Co. Cork, Ireland P75 AX07
| | - Dipali Singh
- Bantry Marine Research Station, Gearhies, Bantry, Co. Cork, Ireland P75 AX07
| | - Stephanie Spelberg
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
| | - Giulio Rocco Stella
- Sorbonne Universités, UPMC, Institut de Biologie Paris-Seine, CNRS, Laboratoire de Biologie Computationnelle et Quantitative, 15 rue de l'Ecole de Médecine, 75006 Paris, France
| | - Antonella Succurro
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
| | - Lucilla Taddei
- Sorbonne Universités, UPMC, Institut de Biologie Paris-Seine, CNRS, Laboratoire de Biologie Computationnelle et Quantitative, 15 rue de l'Ecole de Médecine, 75006 Paris, France
| | - Brieuc Urbain
- LUNAM, University of Nantes, GEPEA, UMR-CNRS 6144, France
| | | | | | - Oliver Ebenhöh
- Cluster of Excellence on Plant Sciences (CEPLAS), Institute of Quantitative and Theoretical Biology, Heinrich Heine University Düsseldorf, Germany
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12
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Sweetlove LJ, Nielsen J, Fernie AR. Engineering central metabolism - a grand challenge for plant biologists. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2017; 90:749-763. [PMID: 28004455 DOI: 10.1111/tpj.13464] [Citation(s) in RCA: 46] [Impact Index Per Article: 6.6] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/05/2016] [Revised: 12/14/2016] [Accepted: 12/15/2016] [Indexed: 06/06/2023]
Abstract
The goal of increasing crop productivity and nutrient-use efficiency is being addressed by a number of ambitious research projects seeking to re-engineer photosynthetic biochemistry. Many of these projects will require the engineering of substantial changes in fluxes of central metabolism. However, as has been amply demonstrated in simpler systems such as microbes, central metabolism is extremely difficult to rationally engineer. This is because of multiple layers of regulation that operate to maintain metabolic steady state and because of the highly connected nature of central metabolism. In this review we discuss new approaches for metabolic engineering that have the potential to address these problems and dramatically improve the success with which we can rationally engineer central metabolism in plants. In particular, we advocate the adoption of an iterative 'design-build-test-learn' cycle using fast-to-transform model plants as test beds. This approach can be realised by coupling new molecular tools to incorporate multiple transgenes in nuclear and plastid genomes with computational modelling to design the engineering strategy and to understand the metabolic phenotype of the engineered organism. We also envisage that mutagenesis could be used to fine-tune the balance between the endogenous metabolic network and the introduced enzymes. Finally, we emphasise the importance of considering the plant as a whole system and not isolated organs: the greatest increase in crop productivity will be achieved if both source and sink metabolism are engineered.
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Affiliation(s)
- Lee J Sweetlove
- Department of Plant Sciences, University of Oxford, South Parks Road, Oxford, OX1 3RB, UK
| | - Jens Nielsen
- Department of Biology and Biological Engineering, Chalmers University of Technology, SE41128, Gothenburg, Sweden
- Novo Nordisk Foundation Center for Biosustainability, Technical University of Denmark, DK2800, Lyngby, Denmark
- Science for Life Laboratory, Royal Institute of Technology, SE17121, Stockholm, Sweden
| | - Alisdair R Fernie
- Max-Planck-Institut für Molekulare Pflanzenphysiologie, Potsdam-Golm, Germany
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13
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Current advances in molecular, biochemical, and computational modeling analysis of microalgal triacylglycerol biosynthesis. Biotechnol Adv 2016; 34:1046-1063. [DOI: 10.1016/j.biotechadv.2016.06.004] [Citation(s) in RCA: 64] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/26/2016] [Revised: 06/08/2016] [Accepted: 06/12/2016] [Indexed: 12/12/2022]
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14
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Toure O, Dussap CG. Determination of Gibbs energies of formation in aqueous solution using chemical engineering tools. BIORESOURCE TECHNOLOGY 2016; 213:359-368. [PMID: 26965669 DOI: 10.1016/j.biortech.2016.02.109] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.4] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2015] [Revised: 02/18/2016] [Accepted: 02/20/2016] [Indexed: 06/05/2023]
Abstract
Standard Gibbs energies of formation are of primary importance in the field of biothermodynamics. In the absence of any directly measured values, thermodynamic calculations are required to determine the missing data. For several biochemical species, this study shows that the knowledge of the standard Gibbs energy of formation of the pure compounds (in the gaseous, solid or liquid states) enables to determine the corresponding standard Gibbs energies of formation in aqueous solutions. To do so, using chemical engineering tools (thermodynamic tables and a model enabling to predict activity coefficients, solvation Gibbs energies and pKa data), it becomes possible to determine the partial chemical potential of neutral and charged components in real metabolic conditions, even in concentrated mixtures.
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Affiliation(s)
- Oumar Toure
- Université Clermont Auvergne, Université Blaise Pascal, Institut Pascal (Axe GePEB), BP 10448, F-63000 Clermont-Ferrand, France; CNRS, UMR6602, IP, F-63178 Aubière, France.
| | - Claude-Gilles Dussap
- Université Clermont Auvergne, Université Blaise Pascal, Institut Pascal (Axe GePEB), BP 10448, F-63000 Clermont-Ferrand, France; CNRS, UMR6602, IP, F-63178 Aubière, France
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15
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Souliès A, Legrand J, Marec H, Pruvost J, Castelain C, Burghelea T, Cornet JF. Investigation and modeling of the effects of light spectrum and incident angle on the growth ofChlorella vulgarisin photobioreactors. Biotechnol Prog 2016; 32:247-61. [DOI: 10.1002/btpr.2244] [Citation(s) in RCA: 30] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2015] [Revised: 12/23/2015] [Indexed: 11/11/2022]
Affiliation(s)
- Antoine Souliès
- CNRS, Laboratoire de Génie des Procédés - Environnement - Agroalimentaire; Université De Nantes, UMR 6144; 37 Boulevard De L'université, BP 406 Saint-Nazaire Cedex 44602 France
| | - Jack Legrand
- CNRS, Laboratoire de Génie des Procédés - Environnement - Agroalimentaire; Université De Nantes, UMR 6144; 37 Boulevard De L'université, BP 406 Saint-Nazaire Cedex 44602 France
| | - Hélène Marec
- CNRS, Laboratoire de Génie des Procédés - Environnement - Agroalimentaire; Université De Nantes, UMR 6144; 37 Boulevard De L'université, BP 406 Saint-Nazaire Cedex 44602 France
| | - Jérémy Pruvost
- CNRS, Laboratoire de Génie des Procédés - Environnement - Agroalimentaire; Université De Nantes, UMR 6144; 37 Boulevard De L'université, BP 406 Saint-Nazaire Cedex 44602 France
| | - Cathy Castelain
- CNRS, Laboratoire de Thermocinétique de Nantes; Université De Nantes, UMR 6607; La Chantrerie, Rue Christian-Pauc, BP 50609 Nantes Cedex 3 44306 France
| | - Teodor Burghelea
- CNRS, Laboratoire de Thermocinétique de Nantes; Université De Nantes, UMR 6607; La Chantrerie, Rue Christian-Pauc, BP 50609 Nantes Cedex 3 44306 France
| | - Jean-François Cornet
- Université Clermont Auvergne, Sigma-Clermont; Institut Pascal; UMR CNRS 6602 BP 10448 F63000 Clermont-Ferrand France
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Pruvost J, Le Borgne F, Artu A, Cornet JF, Legrand J. Industrial Photobioreactors and Scale-Up Concepts. PHOTOBIOREACTION ENGINEERING 2016. [DOI: 10.1016/bs.ache.2015.11.002] [Citation(s) in RCA: 27] [Impact Index Per Article: 3.4] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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17
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A reductionist approach to model photosynthetic self-regulation in eukaryotes in response to light. Biochem Soc Trans 2015; 43:1133-9. [PMID: 26614650 DOI: 10.1042/bst20150136] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
Abstract
Along with the development of several large-scale methods such as mass spectrometry or micro arrays, genome wide models became not only a possibility but an obvious tool for theoretical biologists to integrate and analyse complex biological data. Nevertheless, incorporating the dynamics of photosynthesis remains one of the major challenges while reconstructing metabolic networks of plants and other photosynthetic organisms. In this review, we aim to provide arguments that small-scale models are still a suitable choice when it comes to discovering organisational principles governing the design of biological systems. We give a brief overview of recent modelling efforts in understanding the interplay between rapid, photoprotective mechanisms and the redox balance within the thylakoid membrane, discussing the applicability of a reductionist approach in modelling self-regulation in plants and outline possible directions for further research.
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18
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Rügen M, Bockmayr A, Steuer R. Elucidating temporal resource allocation and diurnal dynamics in phototrophic metabolism using conditional FBA. Sci Rep 2015; 5:15247. [PMID: 26496972 PMCID: PMC4620596 DOI: 10.1038/srep15247] [Citation(s) in RCA: 45] [Impact Index Per Article: 5.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/12/2015] [Accepted: 09/15/2015] [Indexed: 11/09/2022] Open
Abstract
The computational analysis of phototrophic growth using constraint-based optimization requires to go beyond current time-invariant implementations of flux-balance analysis (FBA). Phototrophic organisms, such as cyanobacteria, rely on harvesting the sun’s energy for the conversion of atmospheric CO2 into organic carbon, hence their metabolism follows a strongly diurnal lifestyle. We describe the growth of cyanobacteria in a periodic environment using a new method called conditional FBA. Our approach enables us to incorporate the temporal organization and conditional dependencies into a constraint-based description of phototrophic metabolism. Specifically, we take into account that cellular processes require resources that are themselves products of metabolism. Phototrophic growth can therefore be formulated as a time-dependent linear optimization problem, such that optimal growth requires a differential allocation of resources during different times of the day. Conditional FBA then allows us to simulate phototrophic growth of an average cell in an environment with varying light intensity, resulting in dynamic time-courses for all involved reaction fluxes, as well as changes in biomass composition over a diurnal cycle. Our results are in good agreement with several known facts about the temporal organization of phototrophic growth and have implications for further analysis of resource allocation problems in phototrophic metabolism.
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Affiliation(s)
- Marco Rügen
- Humboldt-Universität zu Berlin, Institut für Theoretische Biologie (ITB), Invalidenstr. 43, D-10115 Berlin, Germany.,Freie Universität Berlin, Research Center Matheon, FB Mathematik und Informatik, Arnimallee 6, D-14195 Berlin, Germany
| | - Alexander Bockmayr
- Freie Universität Berlin, Research Center Matheon, FB Mathematik und Informatik, Arnimallee 6, D-14195 Berlin, Germany
| | - Ralf Steuer
- Humboldt-Universität zu Berlin, Institut für Theoretische Biologie (ITB), Invalidenstr. 43, D-10115 Berlin, Germany
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Abstract
Background Sampling methods have proven to be a very efficient and intuitive method to understand properties of complicated spaces that cannot easily be computed using deterministic methods. Therefore, sampling methods became a popular tool in the applied sciences. Results Here, we show that sampling methods are not an appropriate tool to analyze qualitative properties of complicated spaces unless RP = NP. We illustrate these results on the example of the thermodynamically feasible flux space of genome-scale metabolic networks and show that with artificial centering hit and run (ACHR) not all reactions that can have variable flux rates are sampled with variables flux rates. In particular a uniform sample of the flux space would not sample the flux variabilities completely. Conclusion We conclude that unless theoretical convergence results exist, qualitative results obtained from sampling methods should be considered with caution and if possible double checked using a deterministic method.
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Affiliation(s)
- Arne C. Reimers
- Life Sciences Group, Centrum Wiskunde & Informatica, Amsterdam, Netherlands
- * E-mail:
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20
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Baroukh C, Muñoz-Tamayo R, Bernard O, Steyer JP. Mathematical modeling of unicellular microalgae and cyanobacteria metabolism for biofuel production. Curr Opin Biotechnol 2015; 33:198-205. [DOI: 10.1016/j.copbio.2015.03.002] [Citation(s) in RCA: 40] [Impact Index Per Article: 4.4] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2014] [Revised: 02/18/2015] [Accepted: 03/05/2015] [Indexed: 11/24/2022]
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21
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Scaife MA, Nguyen GTDT, Rico J, Lambert D, Helliwell KE, Smith AG. Establishing Chlamydomonas reinhardtii as an industrial biotechnology host. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 82:532-546. [PMID: 25641561 PMCID: PMC4515103 DOI: 10.1111/tpj.12781] [Citation(s) in RCA: 115] [Impact Index Per Article: 12.8] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 11/28/2014] [Revised: 01/19/2015] [Accepted: 01/20/2015] [Indexed: 05/20/2023]
Abstract
Microalgae constitute a diverse group of eukaryotic unicellular organisms that are of interest for pure and applied research. Owing to their natural synthesis of value-added natural products microalgae are emerging as a source of sustainable chemical compounds, proteins and metabolites, including but not limited to those that could replace compounds currently made from fossil fuels. For the model microalga, Chlamydomonas reinhardtii, this has prompted a period of rapid development so that this organism is poised for exploitation as an industrial biotechnology platform. The question now is how best to achieve this? Highly advanced industrial biotechnology systems using bacteria and yeasts were established in a classical metabolic engineering manner over several decades. However, the advent of advanced molecular tools and the rise of synthetic biology provide an opportunity to expedite the development of C. reinhardtii as an industrial biotechnology platform, avoiding the process of incremental improvement. In this review we describe the current status of genetic manipulation of C. reinhardtii for metabolic engineering. We then introduce several concepts that underpin synthetic biology, and show how generic parts are identified and used in a standard manner to achieve predictable outputs. Based on this we suggest that the development of C. reinhardtii as an industrial biotechnology platform can be achieved more efficiently through adoption of a synthetic biology approach.
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Affiliation(s)
- Mark A Scaife
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
- *For correspondence (e-mails or )
| | - Ginnie TDT Nguyen
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
| | - Juan Rico
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
| | - Devinn Lambert
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
| | - Katherine E Helliwell
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
| | - Alison G Smith
- Department of Plant Science, University of CambridgeDowning Street, Cambridge, CB2 3EA, UK
- *For correspondence (e-mails or )
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22
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Baroukh C, Muñoz-Tamayo R, Steyer JP, Bernard O. A state of the art of metabolic networks of unicellular microalgae and cyanobacteria for biofuel production. Metab Eng 2015; 30:49-60. [PMID: 25916794 DOI: 10.1016/j.ymben.2015.03.019] [Citation(s) in RCA: 50] [Impact Index Per Article: 5.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/24/2014] [Revised: 02/05/2015] [Accepted: 03/26/2015] [Indexed: 11/27/2022]
Abstract
The most promising and yet challenging application of microalgae and cyanobacteria is the production of renewable energy: biodiesel from microalgae triacylglycerols and bioethanol from cyanobacteria carbohydrates. A thorough understanding of microalgal and cyanobacterial metabolism is necessary to master and optimize biofuel production yields. To this end, systems biology and metabolic modeling have proven to be very efficient tools if supported by an accurate knowledge of the metabolic network. However, unlike heterotrophic microorganisms that utilize the same substrate for energy and as carbon source, microalgae and cyanobacteria require light for energy and inorganic carbon (CO2 or bicarbonate) as carbon source. This double specificity, together with the complex mechanisms of light capture, makes the representation of metabolic network nonstandard. Here, we review the existing metabolic networks of photoautotrophic microalgae and cyanobacteria. We highlight how these networks have been useful for gaining insight on photoautotrophic metabolism.
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Affiliation(s)
- Caroline Baroukh
- INRA UR0050, Laboratoire des Biotechnologies de l׳Environnement, avenue des étangs, 11100 Narbonne, France; Inria, BIOCORE, 2004 route des lucioles, 06902 Sophia-Antipolis, France.
| | | | - Jean-Philippe Steyer
- INRA UR0050, Laboratoire des Biotechnologies de l׳Environnement, avenue des étangs, 11100 Narbonne, France
| | - Olivier Bernard
- Inria, BIOCORE, 2004 route des lucioles, 06902 Sophia-Antipolis, France; LOV, UPMC, CNRS, UMR 7093, Station Zoologique, B.P. 28, 06234 Villefranche-sur-mer, France
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23
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Sarkar D, Shimizu K. An overview on biofuel and biochemical production by photosynthetic microorganisms with understanding of the metabolism and by metabolic engineering together with efficient cultivation and downstream processing. BIORESOUR BIOPROCESS 2015. [DOI: 10.1186/s40643-015-0045-9] [Citation(s) in RCA: 35] [Impact Index Per Article: 3.9] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/10/2023] Open
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24
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Reimers AC, Goldstein Y, Bockmayr A. Generic flux coupling analysis. Math Biosci 2015; 262:28-35. [PMID: 25619608 DOI: 10.1016/j.mbs.2015.01.003] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2014] [Revised: 01/08/2015] [Accepted: 01/14/2015] [Indexed: 12/24/2022]
Abstract
Flux coupling analysis (FCA) has become a useful tool for aiding metabolic reconstructions and guiding genetic manipulations. Originally, it was introduced for constraint-based models of metabolic networks that are based on the steady-state assumption. Recently, we have shown that the steady-state assumption can be replaced by a weaker lattice-theoretic property related to the supports of metabolic fluxes. In this paper, we further extend our approach and develop an efficient algorithm for generic flux coupling analysis that works with any kind of qualitative pathway model. We illustrate our method by thermodynamic flux coupling analysis (tFCA), which allows studying steady-state metabolic models with loop-law thermodynamic constraints. These models do not satisfy the lattice-theoretic properties required in our previous work. For a selection of genome-scale metabolic network reconstructions, we discuss both theoretically and practically, how thermodynamic constraints strengthen the coupling results that can be obtained with classical FCA. A prototype implementation of tFCA is available at http://hoverboard.io/L4FC.
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Affiliation(s)
- Arne C Reimers
- Freie Universität Berlin, Arnimallee 6, Room 101, 14195 Berlin, Germany; Berlin Mathematical School, Berlin, Germany; International Max Planck Research School for Computational Biology and Scientific Computing, Max Planck Institute for Molecular Genetics, Ihnestr 63-73, 14195 Berlin, Germany.
| | - Yaron Goldstein
- Freie Universität Berlin, Arnimallee 6, Room 101, 14195 Berlin, Germany; Forschungszentrum Matheon, Technische Universität Berlin, Straße des 17. Juni 136, 10623 Berlin, Germany.
| | - Alexander Bockmayr
- Freie Universität Berlin, Arnimallee 6, Room 101, 14195 Berlin, Germany; Forschungszentrum Matheon, Technische Universität Berlin, Straße des 17. Juni 136, 10623 Berlin, Germany.
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25
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Modelling of Microalgae Culture Systems with Applications to Control and Optimization. ADVANCES IN BIOCHEMICAL ENGINEERING/BIOTECHNOLOGY 2015; 153:59-87. [PMID: 25604163 DOI: 10.1007/10_2014_287] [Citation(s) in RCA: 23] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
Abstract
Mathematical modeling is becoming ever more important to assess the potential, guide the design, and enable the efficient operation and control of industrial-scale microalgae culture systems (MCS). The development of overall, inherently multiphysics, models involves coupling separate submodels of (i) the intrinsic biological properties, including growth, decay, and biosynthesis as well as the effect of light and temperature on these processes, and (ii) the physical properties, such as the hydrodynamics, light attenuation, and temperature in the culture medium. When considering high-density microalgae culture, in particular, the coupling between biology and physics becomes critical. This chapter reviews existing models, with a particular focus on the Droop model, which is a precursor model, and it highlights the structure common to many microalgae growth models. It summarizes the main developments and difficulties towards multiphysics models of MCS as well as applications of these models for monitoring, control, and optimization purposes.
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26
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Colombié S, Nazaret C, Bénard C, Biais B, Mengin V, Solé M, Fouillen L, Dieuaide-Noubhani M, Mazat JP, Beauvoit B, Gibon Y. Modelling central metabolic fluxes by constraint-based optimization reveals metabolic reprogramming of developing Solanum lycopersicum (tomato) fruit. THE PLANT JOURNAL : FOR CELL AND MOLECULAR BIOLOGY 2015; 81:24-39. [PMID: 25279440 PMCID: PMC4309433 DOI: 10.1111/tpj.12685] [Citation(s) in RCA: 24] [Impact Index Per Article: 2.7] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/06/2014] [Revised: 09/19/2014] [Accepted: 09/19/2014] [Indexed: 05/18/2023]
Abstract
Modelling of metabolic networks is a powerful tool to analyse the behaviour of developing plant organs, including fruits. Guided by our current understanding of heterotrophic metabolism of plant cells, a medium-scale stoichiometric model, including the balance of co-factors and energy, was constructed in order to describe metabolic shifts that occur through the nine sequential stages of Solanum lycopersicum (tomato) fruit development. The measured concentrations of the main biomass components and the accumulated metabolites in the pericarp, determined at each stage, were fitted in order to calculate, by derivation, the corresponding external fluxes. They were used as constraints to solve the model by minimizing the internal fluxes. The distribution of the calculated fluxes of central metabolism were then analysed and compared with known metabolic behaviours. For instance, the partition of the main metabolic pathways (glycolysis, pentose phosphate pathway, etc.) was relevant throughout fruit development. We also predicted a valid import of carbon and nitrogen by the fruit, as well as a consistent CO2 release. Interestingly, the energetic balance indicates that excess ATP is dissipated just before the onset of ripening, supporting the concept of the climacteric crisis. Finally, the apparent contradiction between calculated fluxes with low values compared with measured enzyme capacities suggest a complex reprogramming of the metabolic machinery during fruit development. With a powerful set of experimental data and an accurate definition of the metabolic system, this work provides important insight into the metabolic and physiological requirements of the developing tomato fruits.
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Affiliation(s)
- Sophie Colombié
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
- *For correspondence (e-mail )
| | - Christine Nazaret
- Institut de Mathématiques de Bordeaux, ENSTBB-Institut Polytechnique de Bordeaux351 Cours de la Liberation, Talence, F-33400, France
| | - Camille Bénard
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
| | - Benoît Biais
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
| | - Virginie Mengin
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
| | - Marion Solé
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
| | - Laëtitia Fouillen
- CNRS, UMR 5200Laboratoire de Biogenèse Membranaire, Villenave D'Ornon, F-33883, France
- Univ. Bordeaux146 rue Léo-Saignat, Bordeaux Cedex, F-33076, France
| | - Martine Dieuaide-Noubhani
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
- Univ. Bordeaux146 rue Léo-Saignat, Bordeaux Cedex, F-33076, France
| | - Jean-Pierre Mazat
- Univ. Bordeaux146 rue Léo-Saignat, Bordeaux Cedex, F-33076, France
- IBGC-CNRS1 rue Camille Saint-Saëns, Bordeaux Cedex, F-33077, France
| | - Bertrand Beauvoit
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
- Univ. Bordeaux146 rue Léo-Saignat, Bordeaux Cedex, F-33076, France
| | - Yves Gibon
- INRAUMR 1332 Biologie du Fruit et Pathologie, Villenave d'Ornon, F-33883, France
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Reijnders MJ, van Heck RG, Lam CM, Scaife MA, Santos VAMD, Smith AG, Schaap PJ. Green genes: bioinformatics and systems-biology innovations drive algal biotechnology. Trends Biotechnol 2014; 32:617-26. [DOI: 10.1016/j.tibtech.2014.10.003] [Citation(s) in RCA: 46] [Impact Index Per Article: 4.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/16/2014] [Revised: 09/30/2014] [Accepted: 10/01/2014] [Indexed: 01/18/2023]
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DRUM: a new framework for metabolic modeling under non-balanced growth. Application to the carbon metabolism of unicellular microalgae. PLoS One 2014; 9:e104499. [PMID: 25105494 PMCID: PMC4126706 DOI: 10.1371/journal.pone.0104499] [Citation(s) in RCA: 49] [Impact Index Per Article: 4.9] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/07/2014] [Accepted: 07/12/2014] [Indexed: 11/23/2022] Open
Abstract
Metabolic modeling is a powerful tool to understand, predict and optimize bioprocesses, particularly when they imply intracellular molecules of interest. Unfortunately, the use of metabolic models for time varying metabolic fluxes is hampered by the lack of experimental data required to define and calibrate the kinetic reaction rates of the metabolic pathways. For this reason, metabolic models are often used under the balanced growth hypothesis. However, for some processes such as the photoautotrophic metabolism of microalgae, the balanced-growth assumption appears to be unreasonable because of the synchronization of their circadian cycle on the daily light. Yet, understanding microalgae metabolism is necessary to optimize the production yield of bioprocesses based on this microorganism, as for example production of third-generation biofuels. In this paper, we propose DRUM, a new dynamic metabolic modeling framework that handles the non-balanced growth condition and hence accumulation of intracellular metabolites. The first stage of the approach consists in splitting the metabolic network into sub-networks describing reactions which are spatially close, and which are assumed to satisfy balanced growth condition. The left metabolites interconnecting the sub-networks behave dynamically. Then, thanks to Elementary Flux Mode analysis, each sub-network is reduced to macroscopic reactions, for which simple kinetics are assumed. Finally, an Ordinary Differential Equation system is obtained to describe substrate consumption, biomass production, products excretion and accumulation of some internal metabolites. DRUM was applied to the accumulation of lipids and carbohydrates of the microalgae Tisochrysis lutea under day/night cycles. The resulting model describes accurately experimental data obtained in day/night conditions. It efficiently predicts the accumulation and consumption of lipids and carbohydrates.
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Béchet Q, Shilton A, Guieysse B. Modeling the effects of light and temperature on algae growth: State of the art and critical assessment for productivity prediction during outdoor cultivation. Biotechnol Adv 2013; 31:1648-63. [DOI: 10.1016/j.biotechadv.2013.08.014] [Citation(s) in RCA: 207] [Impact Index Per Article: 18.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/11/2012] [Revised: 08/12/2013] [Accepted: 08/17/2013] [Indexed: 10/26/2022]
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Grafahrend-Belau E, Junker A, Schreiber F, Junker BH. Flux balance analysis as an alternative method to estimate fluxes without labeling. Methods Mol Biol 2013; 1090:281-99. [PMID: 24222422 DOI: 10.1007/978-1-62703-688-7_17] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/18/2023]
Abstract
The analysis of plant metabolic networks essentially contributes to the understanding of the efficiency of plant systems in terms of their biotechnological usage. Metabolic fluxes are determined by biochemical parameters such as metabolite concentrations as well as enzyme properties and activities, which in turn are the result of various regulatory events at various levels between control of transcription and posttranslational regulation of enzyme protein activity. Thus, knowledge about metabolic fluxes on a large scale provides an integrated view on the functional state of a metabolically active cell, organ, or system. In this chapter, we introduce flux balance analysis as a constraint-based method for the prediction of optimal metabolic fluxes in a given metabolic network. Furthermore, we provide a step-by-step protocol for metabolic network reconstruction and constraint-based analysis using the COBRA Toolbox.
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Affiliation(s)
- Eva Grafahrend-Belau
- Leibniz-Institute of Plant Genetics and Crop Plant Research Gatersleben (IPK), Gatersleben, Germany
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Koskimaki JE, Blazier AS, Clarens AF, Papin JA. Computational Models of Algae Metabolism for Industrial Applications. Ind Biotechnol (New Rochelle N Y) 2013. [DOI: 10.1089/ind.2013.0012] [Citation(s) in RCA: 7] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/20/2023] Open
Affiliation(s)
- Jacob E. Koskimaki
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA
| | - Anna S. Blazier
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA
| | - Andres F. Clarens
- Department of Civil and Environmental Engineering, University of Virginia, Charlottesville, VA
| | - Jason A. Papin
- Department of Biomedical Engineering, University of Virginia, Charlottesville, VA
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Mao L, Verwoerd WS. Model-driven elucidation of the inherent capacity of Geobacter sulfurreducens for electricity generation. J Biol Eng 2013; 7:14. [PMID: 23718629 PMCID: PMC3673867 DOI: 10.1186/1754-1611-7-14] [Citation(s) in RCA: 17] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/20/2013] [Accepted: 05/21/2013] [Indexed: 11/16/2022] Open
Abstract
Background G. sulfurreducens is one of the commonest microbes used in microbial fuel cells (MFCs) for organic-to-electricity biotransformation. In MFCs based on this microorganism, electrons can be conveyed to the anode via three ways: 1) direct electron transfer (DET) mode, in which electrons of reduced c-type cytochromes in the microbial outer membrane are directly oxidized by the anode; 2) mediated electron transfer (MET) mode, in which the reducing potential available from cell metabolism in the form of NADH is targeted as an electron source for electricity generation with the aid of exogenous mediators; and 3) a putative mixed operation mode involving both electron transfer mechanisms described above (DET and MET). However, the potential of G. sulfurreducens for current output in these three operation modes and the metabolic mechanisms underlying the extraction of the reducing equivalents are still unknown. Results In this study, we performed flux balance analysis (FBA) of the genome-scale metabolic network to compute the fundamental metabolic potential of G. sulfurreducens for current output that is compatible with reaction stoichiometry, given a realistic nutrient uptake rate. We also developed a method, flux variability analysis with target flux minimization (FATMIN) to eliminate futile NADH cycles. Our study elucidates the possible metabolic strategies to sustain the NADH for current production under the MET and Mixed modes. The results showed that G. sulfurreducens had a potential to output current at up to 3.710 A/gDW for DET mode, 2.711 A/gDW for MET mode and 3.272 A/gDW for a putative mixed MET and DET mode. Compared with DET, which relies on only one contributing reaction, MET and Mixed mode were more resilient with ten and four reactions respectively for high current production. Conclusions The DET mode can achieve a higher maximum limit of the current output than the MET mode, but the MET has an advantage of higher power output and more flexible metabolic choices to sustain the electric current. The MET and DET modes compete with each other for the metabolic resource for the electricity generation.
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Affiliation(s)
- Longfei Mao
- Centre for Advanced Computational Solutions, Wine, Food & Molecular Bioscience Department, Lincoln University, Ellesmere Junction Road, Lincoln, 7647, New Zealand.
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Abstract
MOTIVATION Flux variability analysis (FVA) is an important tool to further analyse the results obtained by flux balance analysis (FBA) on genome-scale metabolic networks. For many constraint-based models, FVA identifies unboundedness of the optimal flux space. This reveals that optimal flux solutions with net flux through internal biochemical loops are feasible, which violates the second law of thermodynamics. Such unbounded fluxes may be eliminated by extending FVA with thermodynamic constraints. RESULTS We present a new algorithm for efficient flux variability (and flux balance) analysis with thermodynamic constraints, suitable for analysing genome-scale metabolic networks. We first show that FBA with thermodynamic constraints is NP-hard. Then we derive a theoretical tractability result, which can be applied to metabolic networks in practice. We use this result to develop a new constraint programming algorithm Fast-tFVA for fast FVA with thermodynamic constraints (tFVA). Computational comparisons with previous methods demonstrate the efficiency of the new method. For tFVA, a speed-up of factor 30-300 is achieved. In an analysis of genome-scale metabolic networks in the BioModels database, we found that in 485 of 716 networks, additional irreversible or fixed reactions could be detected. AVAILABILITY AND IMPLEMENTATION Fast-tFVA is written in C++ and published under GPL. It uses the open source software SCIP and libSBML. There also exists a Matlab interface for easy integration into Matlab. Fast-tFVA is available from page.mi.fu-berlin.de/arnem/fast-tfva.html. SUPPLEMENTARY INFORMATION Supplementary data are available at Bioinformatics online.
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Affiliation(s)
- Arne C Müller
- Department of Mathematics and Computer Science, Freie Universität Berlin, 14195 Berlin, Germany.
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Noor E, Lewis NE, Milo R. A proof for loop-law constraints in stoichiometric metabolic networks. BMC SYSTEMS BIOLOGY 2012; 6:140. [PMID: 23146116 PMCID: PMC3560238 DOI: 10.1186/1752-0509-6-140] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 07/05/2012] [Accepted: 10/30/2012] [Indexed: 02/08/2023]
Abstract
Background Constraint-based modeling is increasingly employed for metabolic network analysis. Its underlying assumption is that natural metabolic phenotypes can be predicted by adding physicochemical constraints to remove unrealistic metabolic flux solutions. The loopless-COBRA approach provides an additional constraint that eliminates thermodynamically infeasible internal cycles (or loops) from the space of solutions. This allows the prediction of flux solutions that are more consistent with experimental data. However, it is not clear if this approach over-constrains the models by removing non-loop solutions as well. Results Here we apply Gordan’s theorem from linear algebra to prove for the first time that the constraints added in loopless-COBRA do not over-constrain the problem beyond the elimination of the loops themselves. Conclusions The loopless-COBRA constraints can be reliably applied. Furthermore, this proof may be adapted to evaluate the theoretical soundness for other methods in constraint-based modeling.
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Affiliation(s)
- Elad Noor
- Department of Plant Sciences, 234 Herzl St., Weizmann Institute of Science, Rehovot 76100, Israel.
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Takache H, Pruvost J, Cornet JF. Kinetic modeling of the photosynthetic growth of Chlamydomonas reinhardtii in a photobioreactor. Biotechnol Prog 2012; 28:681-92. [DOI: 10.1002/btpr.1545] [Citation(s) in RCA: 73] [Impact Index Per Article: 6.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/09/2011] [Revised: 03/13/2012] [Indexed: 01/09/2023]
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Network reduction in metabolic pathway analysis: elucidation of the key pathways involved in the photoautotrophic growth of the green alga Chlamydomonas reinhardtii. Metab Eng 2012; 14:458-67. [PMID: 22342232 DOI: 10.1016/j.ymben.2012.01.009] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/14/2011] [Revised: 01/13/2012] [Accepted: 01/31/2012] [Indexed: 11/21/2022]
Abstract
Metabolic pathway analysis aims at discovering and analyzing meaningful routes and their interactions in metabolic networks. A major difficulty in applying this technique lies in the decomposition of metabolic flux distributions into elementary mode or extreme pathway activity patterns, which in general is not unique. We propose a network reduction approach based on the decomposition of a set of flux vectors representing adaptive microbial metabolic behavior in bioreactors into a minimal set of shared pathways. Several optimality criteria from the literature were compared in order to select the most appropriate objective function. We further analyze photoautotrophic metabolism of the green alga Chlamydomonas reinhardtii growing in a photobioreactor under maximal growth rate conditions. Key pathways involved in its adaptive metabolic response to changes in light influx are identified and discussed using an energetic approach.
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Sweetlove LJ, Ratcliffe RG. Flux-balance modeling of plant metabolism. FRONTIERS IN PLANT SCIENCE 2011; 2:38. [PMID: 22645533 PMCID: PMC3355794 DOI: 10.3389/fpls.2011.00038] [Citation(s) in RCA: 92] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2011] [Accepted: 07/28/2011] [Indexed: 05/17/2023]
Abstract
Flux-balance modeling of plant metabolic networks provides an important complement to (13)C-based metabolic flux analysis. Flux-balance modeling is a constraints-based approach in which steady-state fluxes in a metabolic network are predicted by using optimization algorithms within an experimentally bounded solution space. In the last 2 years several flux-balance models of plant metabolism have been published including genome-scale models of Arabidopsis metabolism. In this review we consider what has been learnt from these models. In addition, we consider the limitations of flux-balance modeling and identify the main challenges to generating improved and more detailed models of plant metabolism at tissue- and cell-specific scales. Finally we discuss the types of question that flux-balance modeling is well suited to address and its potential role in metabolic engineering and crop improvement.
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