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Ray A, Kundu P, Ghosh A. Reconstruction of a Genome-Scale Metabolic Model of Scenedesmus obliquus and Its Application for Lipid Production under Three Trophic Modes. ACS Synth Biol 2023; 12:3463-3481. [PMID: 37852251 DOI: 10.1021/acssynbio.3c00516] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/20/2023]
Abstract
Green microalgae have emerged as beneficial feedstocks for biofuel production. A systems-level understanding of the biochemical network is needed to harness the microalgal metabolic capacity for bioproduction. Genome-scale metabolic modeling (GEM) showed immense potential in rational metabolic engineering, utilizing biochemical flux distribution analysis. Here, we report the first GEM for the green microalga, Scenedesmus obliquus (iAR632), a promising biodiesel feedstock with high lipid-storing capability. iAR632 comprises 1467 reactions, 734 metabolites, and 632 genes distributed among 7 compartments. The model was optimized under three different trophic modes of microalgal cultivation, i.e., autotrophy, mixotrophy, and heterotrophy. The robustness of the reconstructed network was confirmed by analyzing its sensitivity to the biomass components. Pathway-level flux profiles were analyzed, and significant flux space expansion was noticed majorly in reactions associated with lipid biosynthesis. In agreement with the experimental observation, iAR632 predicted about 3.8-fold increased biomass and almost 4-fold higher lipid under mixotrophy than the other trophic modes. Thus, the assessment of the condition-specific metabolic flux distribution of iAR632 suggested that mixotrophy is the preferred cultivation condition for improved microalgal growth and lipid production. Overall, the reconstructed GEM and subsequent analyses will provide a systematic framework for developing model-driven strategies to improve microalgal bioproduction.
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Affiliation(s)
- Ayusmita Ray
- P.K. Sinha Centre for Bioenergy and Renewables, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Pritam Kundu
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
| | - Amit Ghosh
- School of Energy Science and Engineering, Indian Institute of Technology Kharagpur, Kharagpur, West Bengal 721302, India
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Systems biology's role in leveraging microalgal biomass potential: Current status and future perspectives. ALGAL RES 2022. [DOI: 10.1016/j.algal.2022.102963] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/31/2022]
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Pathania R, Srivastava A, Srivastava S, Shukla P. Metabolic systems biology and multi-omics of cyanobacteria: Perspectives and future directions. BIORESOURCE TECHNOLOGY 2022; 343:126007. [PMID: 34634665 DOI: 10.1016/j.biortech.2021.126007] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/08/2021] [Revised: 09/17/2021] [Accepted: 09/19/2021] [Indexed: 06/13/2023]
Abstract
Cyanobacteria are oxygenic photoautotrophs whose metabolism contains key biochemical pathways to fix atmospheric CO2 and synthesize various metabolites. The development of bioengineering tools has enabled the manipulation of cyanobacterial chassis to produce various valuable bioproducts photosynthetically. However, effective utilization of cyanobacteria as photosynthetic cell factories needs a detailed understanding of their metabolism and its interaction with other cellular processes. Implementing systems and synthetic biology tools has generated a wealth of information on various metabolic pathways. However, to design effective engineering strategies for further improvement in growth, photosynthetic efficiency, and enhanced production of target biochemicals, in-depth knowledge of their carbon/nitrogen metabolism, pathway fluxe distribution, genetic regulation and integrative analyses are necessary. In this review, we discuss the recent advances in the development of genome-scale metabolic models (GSMMs), omics analyses (metabolomics, transcriptomics, proteomics, fluxomics), and integrative modeling approaches to showcase the current understanding of cyanobacterial metabolism.
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Affiliation(s)
- Ruchi Pathania
- Systems Biology for Biofuels Group, International Centre for Genetic Engineering and Biotechnology, ICGEB Campus, Aruna Asaf Ali Marg, New Delhi 110067, India
| | - Amit Srivastava
- Department of Chemistry, Purdue University, West Lafayette, IN 47907, United States
| | - Shireesh Srivastava
- Systems Biology for Biofuels Group, International Centre for Genetic Engineering and Biotechnology, ICGEB Campus, Aruna Asaf Ali Marg, New Delhi 110067, India; DBT-ICGEB Center for Advanced Bioenergy Research, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Pratyoosh Shukla
- School of Biotechnology, Institute of Science, Banaras Hindu University, Varanasi 221005, Uttar Pradesh, India; Enzyme Technology and Protein Bioinformatics Laboratory, Department of Microbiology, Maharshi Dayanand University, Rohtak 124001, Haryana, India.
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Gupta JK, Srivastava S. The Effect of Promoter and RBS Combination on the Growth and Glycogen Productivity of Sodium-Dependent Bicarbonate Transporter (SbtA) Overexpressing Synechococcus sp. PCC 7002 Cells. Front Microbiol 2021; 12:607411. [PMID: 33927699 PMCID: PMC8076525 DOI: 10.3389/fmicb.2021.607411] [Citation(s) in RCA: 3] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/17/2020] [Accepted: 03/22/2021] [Indexed: 12/20/2022] Open
Abstract
Sodium dependent bicarbonate transporter, SbtA is a high-affinity, inducible bicarbonate transporter in cyanobacterial cells. Our previous work has shown that overexpression of this transporter can significantly increase growth and glycogen accumulation in Synechococcus sp. PCC 7002 cells. In this work, we have tested the effect of two different RBS sequences (RBS1: GGAGGA and RBS2: AGGAGA) and three different promoters (PcpcB, PcpcB560, and PrbcL2) on the growth and glycogen production in SbtA-overexpressing Synechococcus sp. PCC 7002 cells. Our results show that PcpcB or PcpcB560 were more effective than PrbcL2 in increasing the growth and glycogen content. The choice of RBS sequence had relatively minor effect, though RBS2 was more effective than RBS1. The transformant E, with PcpcB560 and RBS2, showed the highest growth. The biomass after 5 days of growth on air or 1% CO2 was increased by about 90% in the strain E compared to PCC 7002 cells. All transformants overexpressing SbtA had higher glycogen content. However, growing the cells with bubbling of 1% CO2 did not increase cellular glycogen content any further. The strain E had about 80% higher glycogen content compared to WT PCC 7002 cells. Therefore, the glycogen productivity of the strain E grown with air-bubbling was about 2.5-fold that of the WT PCC 7002 cells grown similarly. Additionally, some of the transformants had higher chlorophyll content while all the transformants had higher carotenoid content compared to the PCC 7002 cells, suggesting interaction between carbon transport and pigment levels. Thus, this work shows that the choice of photosynthetic promoters and RBSs sequences can impact growth and glycogen accumulation in SbtA-overexpressing cells.
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Affiliation(s)
- Jai Kumar Gupta
- Systems Biology for Biofuels Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India
| | - Shireesh Srivastava
- Systems Biology for Biofuels Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi, India.,Department of Biotechnology-International Centre for Genetic Engineering and Biotechnology (DBT-ICGEB), Centre for Advanced Bioenergy Research, New Delhi, India
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Vijayakumar S, Rahman PK, Angione C. A Hybrid Flux Balance Analysis and Machine Learning Pipeline Elucidates Metabolic Adaptation in Cyanobacteria. iScience 2020; 23:101818. [PMID: 33354660 PMCID: PMC7744713 DOI: 10.1016/j.isci.2020.101818] [Citation(s) in RCA: 15] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/26/2020] [Revised: 10/23/2020] [Accepted: 11/13/2020] [Indexed: 01/20/2023] Open
Abstract
Machine learning has recently emerged as a promising tool for inferring multi-omic relationships in biological systems. At the same time, genome-scale metabolic models (GSMMs) can be integrated with such multi-omic data to refine phenotypic predictions. In this work, we use a multi-omic machine learning pipeline to analyze a GSMM of Synechococcus sp. PCC 7002, a cyanobacterium with large potential to produce renewable biofuels. We use regularized flux balance analysis to observe flux response between conditions across photosynthesis and energy metabolism. We then incorporate principal-component analysis, k-means clustering, and LASSO regularization to reduce dimensionality and extract key cross-omic features. Our results suggest that combining metabolic modeling with machine learning elucidates mechanisms used by cyanobacteria to cope with fluctuations in light intensity and salinity that cannot be detected using transcriptomics alone. Furthermore, GSMMs introduce critical mechanistic details that improve the performance of omic-based machine learning methods.
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Affiliation(s)
- Supreeta Vijayakumar
- Department of Computer Science and Information Systems, Teesside University, Middlesbrough, North Yorkshire TS1 3BX, UK
| | - Pattanathu K.S.M. Rahman
- Centre for Enzyme Innovation, Institute of Biological and Biomedical Sciences, School of Biological Sciences, University of Portsmouth, Portsmouth, Hampshire PO1 2UP, UK
- Tara Biologics, Woking, Surrey GU21 6BP, UK
| | - Claudio Angione
- Department of Computer Science and Information Systems, Teesside University, Middlesbrough, North Yorkshire TS1 3BX, UK
- Centre for Digital Innovation, Teesside University, Middlesbrough TS1 3BX, UK
- Healthcare Innovation Centre, Teesside University, Middlesbrough TS1 3BX, UK
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Jeong Y, Cho SH, Lee H, Choi HK, Kim DM, Lee CG, Cho S, Cho BK. Current Status and Future Strategies to Increase Secondary Metabolite Production from Cyanobacteria. Microorganisms 2020; 8:E1849. [PMID: 33255283 PMCID: PMC7761380 DOI: 10.3390/microorganisms8121849] [Citation(s) in RCA: 12] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/29/2020] [Revised: 11/15/2020] [Accepted: 11/23/2020] [Indexed: 12/16/2022] Open
Abstract
Cyanobacteria, given their ability to produce various secondary metabolites utilizing solar energy and carbon dioxide, are a potential platform for sustainable production of biochemicals. Until now, conventional metabolic engineering approaches have been applied to various cyanobacterial species for enhanced production of industrially valued compounds, including secondary metabolites and non-natural biochemicals. However, the shortage of understanding of cyanobacterial metabolic and regulatory networks for atmospheric carbon fixation to biochemical production and the lack of available engineering tools limit the potential of cyanobacteria for industrial applications. Recently, to overcome the limitations, synthetic biology tools and systems biology approaches such as genome-scale modeling based on diverse omics data have been applied to cyanobacteria. This review covers the synthetic and systems biology approaches for advanced metabolic engineering of cyanobacteria.
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Affiliation(s)
- Yujin Jeong
- Department of Biological Sciences and KAIST Institutes for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; (Y.J.); (S.-H.C.)
| | - Sang-Hyeok Cho
- Department of Biological Sciences and KAIST Institutes for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; (Y.J.); (S.-H.C.)
| | - Hookeun Lee
- Institute of Pharmaceutical Research, College of Pharmacy, Gachon University, Incheon 21999, Korea;
| | | | - Dong-Myung Kim
- Department of Chemical Engineering and Applied Chemistry, Chungnam National University, Daejeon 34134, Korea;
| | - Choul-Gyun Lee
- Department of Biological Engineering, Inha University, Incheon 22212, Korea;
| | - Suhyung Cho
- Department of Biological Sciences and KAIST Institutes for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; (Y.J.); (S.-H.C.)
| | - Byung-Kwan Cho
- Department of Biological Sciences and KAIST Institutes for the BioCentury, Korea Advanced Institute of Science and Technology, Daejeon 34141, Korea; (Y.J.); (S.-H.C.)
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Ahmad A, Tiwari A, Srivastava S. A Genome-Scale Metabolic Model of Thalassiosira pseudonana CCMP 1335 for a Systems-Level Understanding of Its Metabolism and Biotechnological Potential. Microorganisms 2020; 8:microorganisms8091396. [PMID: 32932853 PMCID: PMC7563145 DOI: 10.3390/microorganisms8091396] [Citation(s) in RCA: 6] [Impact Index Per Article: 1.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/30/2020] [Revised: 07/31/2020] [Accepted: 08/07/2020] [Indexed: 01/27/2023] Open
Abstract
Thalassiosira pseudonana is a transformable and biotechnologically promising model diatom with an ability to synthesise nutraceuticals such as fucoxanthin and store a significant amount of polyglucans and lipids including omega-3 fatty acids. While it was the first diatom to be sequenced, a systems-level analysis of its metabolism has not been done yet. This work presents first comprehensive, compartmentalized, and functional genome-scale metabolic model of the marine diatom Thalassiosira pseudonana CCMP 1335, which we have termed iThaps987. The model includes 987 genes, 2477 reactions, and 2456 metabolites. Comparison with the model of another diatom Phaeodactylum tricornutum revealed presence of 183 unique enzymes (belonging primarily to amino acid, carbohydrate, and lipid metabolism) in iThaps987. Model simulations showed a typical C3-type photosynthetic carbon fixation and suggested a preference of violaxanthin-diadinoxanthin pathway over violaxanthin-neoxanthin pathway for the production of fucoxanthin. Linear electron flow was found be active and cyclic electron flow was inactive under normal phototrophic conditions (unlike green algae and plants), validating the model predictions with previous reports. Investigation of the model for the potential of Thalassiosira pseudonana CCMP 1335 to produce other industrially useful compounds suggest iso-butanol as a foreign compound that can be synthesized by a single-gene addition. This work provides novel insights about the metabolism and potential of the organism and will be helpful to further investigate its metabolism and devise metabolic engineering strategies for the production of various compounds.
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Affiliation(s)
- Ahmad Ahmad
- Systems Biology for Biofuel Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi 110067, India;
- Department of Biotechnology, Noida International University (NIU), Noida 203201, India
| | - Archana Tiwari
- Department of Biotechnology, Noida International University (NIU), Noida 203201, India
- Correspondence: (A.T.); (S.S.); Tel.: +91-958-264-9114 (A.T.); +91-11-2674-1361 (S.S.)
| | - Shireesh Srivastava
- Systems Biology for Biofuel Group, International Centre for Genetic Engineering and Biotechnology (ICGEB), New Delhi 110067, India;
- Correspondence: (A.T.); (S.S.); Tel.: +91-958-264-9114 (A.T.); +91-11-2674-1361 (S.S.)
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