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Zhou T, Reji R, Kairon RS, Chiam KH. A review of algorithmic approaches for cell culture media optimization. Front Bioeng Biotechnol 2023; 11:1195294. [PMID: 37251567 PMCID: PMC10213948 DOI: 10.3389/fbioe.2023.1195294] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/28/2023] [Accepted: 05/03/2023] [Indexed: 05/31/2023] Open
Abstract
Cell culture media composition and culture conditions play a crucial role in product yield, quality and cost of production. Culture media optimization is the technique of improving media composition and culture conditions to achieve desired product outcomes. To achieve this, there have been many algorithmic methods proposed and used for culture media optimization in the literature. To help readers evaluate and decide on a method that best suits their specific application, we carried out a systematic review of the different methods from an algorithmic perspective that classifies, explains and compares the available methods. We also examine the trends and new developments in the area. This review provides recommendations to researchers regarding the suitable media optimization algorithm for their applications and we hope to also promote the development of new cell culture media optimization methods that are better suited to existing and upcoming challenges in this biotechnology field, which will be essential for more efficient production of various cell culture products.
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Affiliation(s)
- Tianxun Zhou
- Bioinformatics Institute, Cellular Image Informatics Division, A*STAR, Singapore, Singapore
| | - Rinta Reji
- Bioinformatics Institute, Cellular Image Informatics Division, A*STAR, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Ryanjit Singh Kairon
- Bioinformatics Institute, Cellular Image Informatics Division, A*STAR, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
| | - Keng Hwee Chiam
- Bioinformatics Institute, Cellular Image Informatics Division, A*STAR, Singapore, Singapore
- School of Biological Sciences, Nanyang Technological University, Singapore, Singapore
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Bleisch R, Freitag L, Ihadjadene Y, Sprenger U, Steingröwer J, Walther T, Krujatz F. Strain Development in Microalgal Biotechnology-Random Mutagenesis Techniques. LIFE (BASEL, SWITZERLAND) 2022; 12:life12070961. [PMID: 35888051 PMCID: PMC9315690 DOI: 10.3390/life12070961] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Subscribe] [Scholar Register] [Received: 05/25/2022] [Revised: 06/15/2022] [Accepted: 06/22/2022] [Indexed: 11/17/2022]
Abstract
Microalgal biomass and metabolites can be used as a renewable source of nutrition, pharmaceuticals and energy to maintain or improve the quality of human life. Microalgae’s high volumetric productivity and low impact on the environment make them a promising raw material in terms of both ecology and economics. To optimize biotechnological processes with microalgae, improving the productivity and robustness of the cell factories is a major step towards economically viable bioprocesses. This review provides an overview of random mutagenesis techniques that are applied to microalgal cell factories, with a particular focus on physical and chemical mutagens, mutagenesis conditions and mutant characteristics.
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Affiliation(s)
- Richard Bleisch
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Leander Freitag
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Yob Ihadjadene
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Una Sprenger
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Juliane Steingröwer
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Thomas Walther
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
| | - Felix Krujatz
- Institute of Natural Materials Technology, Technische Universität Dresden, 01069 Dresden, Germany; (R.B.); (L.F.); (Y.I.); (U.S.); (J.S.); (T.W.)
- Biotopa gGmbH—Center for Applied Aquaculture & Bioeconomy, 01454 Radeberg, Germany
- Faculty of Natural and Environmental Sciences, University of Applied Sciences Zittau/Görlitz, 02763 Zittau, Germany
- Correspondence:
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Khor JG, Lim HR, Chia WY, Chew KW. Automated cultivation system for microalgae: Growth factors and control. CURRENT NUTRITION & FOOD SCIENCE 2022. [DOI: 10.2174/1573401318666220421132428] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/22/2022]
Abstract
Background:
Microalgae have been a hot research topic due to their various biorefinery applications, particularly microalgae as potential alternative nutraceuticals and supplements have a large and rapidly growing market. However, the commercial production is limited due to high processing cost, low efficiency, and scale up of biomass production.
Objective:
It is important to control the microalgae cultivation system with optimal parameters to maximize the biomass productivity. The growth factors including pH, temperature, light intensity, salinity, and nutrients are discussed as these can significantly affect the cultivation. To monitor and control these in real-time, an automated system incorporating advanced digital technologies like sensors, controllers, artificial intelligence (AI), and Internet of Things (IoT) could be applied.
Conclusion:
This perspective provides insights on the implementation of an automated microalgae cultivation system which improves the productivity, effectiveness, and efficiency.
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Affiliation(s)
- Jiun Gia Khor
- School of Energy and Chemical Engineering, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan, Malaysia
| | - Hooi Ren Lim
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
| | - Wen Yi Chia
- Department of Chemical and Environmental Engineering, Faculty of Science and Engineering, University of Nottingham Malaysia, Jalan Broga, 43500 Semenyih, Selangor Darul Ehsan, Malaysia
| | - Kit Wayne Chew
- School of Energy and Chemical Engineering, Xiamen University Malaysia, Jalan Sunsuria, Bandar Sunsuria, 43900 Sepang, Selangor Darul Ehsan, Malaysia
- College of Chemistry and Chemical Engineering, Xiamen University, Xiamen 361005, Fujian, China
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Stephan M, Stute B, von Lieres E, Müller TJJ. Consecutive Three‐component Synthesis of Phenothiazine Based Merocyanines – Bayesian Optimization, Electronic properties, and DSSC Characteristics. European J Org Chem 2022. [DOI: 10.1002/ejoc.202200163] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/11/2022]
Affiliation(s)
- Marvin Stephan
- Heinrich-Heine-Universität Düsseldorf: Heinrich-Heine-Universitat Dusseldorf Institut für Organische Chemie und Makromolekulare Chemie GERMANY
| | - Birgit Stute
- Forschungszentrum Jülich: Forschungszentrum Julich GmbH IBG-1: Biotechnology GERMANY
| | - Eric von Lieres
- Forschungszentrum Jülich: Forschungszentrum Julich GmbH IBG-1: Biotechnology GERMANY
| | - Thomas J. J. Müller
- Heinrich-Heine-Universität Düsseldorf Institut für Organische und Makromolekulare Chemie Universitätsstraße 1Gebäude: 26.43, Raum 00.41 40225 Düsseldorf GERMANY
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Booth M, Spicer A, Kiparissides A. Shedding light on phototrophic biomass production of Chlorella variabilis: The importance of dissolved CO2, light intensity and duty cycle. Biochem Eng J 2022. [DOI: 10.1016/j.bej.2021.108315] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/02/2022]
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Automated Conditional Screening of Multiple Escherichia coli Strains in Parallel Adaptive Fed-Batch Cultivations. Bioengineering (Basel) 2020; 7:bioengineering7040145. [PMID: 33187191 PMCID: PMC7711848 DOI: 10.3390/bioengineering7040145] [Citation(s) in RCA: 9] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/15/2020] [Revised: 11/07/2020] [Accepted: 11/09/2020] [Indexed: 02/06/2023] Open
Abstract
In bioprocess development, the host and the genetic construct for a new biomanufacturing process are selected in the early developmental stages. This decision, made at the screening scale with very limited information about the performance in larger reactors, has a major influence on the efficiency of the final process. To overcome this, scale-down approaches during screenings that show the real cell factory performance at industrial-like conditions are essential. We present a fully automated robotic facility with 24 parallel mini-bioreactors that is operated by a model-based adaptive input design framework for the characterization of clone libraries under scale-down conditions. The cultivation operation strategies are computed and continuously refined based on a macro-kinetic growth model that is continuously re-fitted to the available experimental data. The added value of the approach is demonstrated with 24 parallel fed-batch cultivations in a mini-bioreactor system with eight different Escherichia coli strains in triplicate. The 24 fed-batch cultivations were run under the desired conditions, generating sufficient information to define the fastest-growing strain in an environment with oscillating glucose concentrations similar to industrial-scale bioreactors.
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Wang B, Wang Z, Chen T, Zhao X. Development of Novel Bioreactor Control Systems Based on Smart Sensors and Actuators. Front Bioeng Biotechnol 2020; 8:7. [PMID: 32117906 PMCID: PMC7011095 DOI: 10.3389/fbioe.2020.00007] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/11/2019] [Accepted: 01/07/2020] [Indexed: 01/15/2023] Open
Abstract
Bioreactors of various forms have been widely used in environmental protection, healthcare, industrial biotechnology, and space exploration. Robust demand in the field stimulated the development of novel designs of bioreactor geometries and process control strategies and the evolution of the physical structure of the control system. After the introduction of digital computers to bioreactor process control, a hierarchical structure control system (HSCS) for bioreactors has become the dominant physical structure, having high efficiency and robustness. However, inherent drawbacks of the HSCS for bioreactors have produced a need for a more consolidated solution of the control system. With the fast progress in sensors, machinery, and information technology, the development of a flat organizational control system (FOCS) for bioreactors based on parallel distributed smart sensors and actuators may provide a more concise solution for process control in bioreactors. Here, we review the evolution of the physical structure of bioreactor control systems and discuss the properties of the novel FOCS for bioreactors and related smart sensors and actuators and their application circumstances, with the hope of further improving the efficiency, robustness, and economics of bioprocess control.
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Affiliation(s)
- Baowei Wang
- Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, China
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
| | - Zhiwen Wang
- Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, China
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
| | - Tao Chen
- Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, China
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
| | - Xueming Zhao
- Department of Biochemical Engineering, School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
- SynBio Research Platform, Collaborative Innovation Center of Chemical Science and Engineering (Tianjin), Tianjin, China
- Frontier Science Center for Synthetic Biology and Key Laboratory of Systems Bioengineering (MOE), School of Chemical Engineering and Technology, Tianjin University, Tianjin, China
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Panahi Y, Yari Khosroushahi A, Sahebkar A, Heidari HR. Impact of Cultivation Condition and Media Content on Chlorella vulgaris Composition. Adv Pharm Bull 2019; 9:182-194. [PMID: 31380244 PMCID: PMC6664117 DOI: 10.15171/apb.2019.022] [Citation(s) in RCA: 19] [Impact Index Per Article: 3.8] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/15/2019] [Revised: 04/17/2019] [Accepted: 05/04/2019] [Indexed: 11/09/2022] Open
Abstract
Microalgae are a source material in food, pharmacy, and cosmetics industries for producing various products including high-protein nutritional supplements, synthetic pharmaceuticals, and natural colors. A promising algal source for such productions is Chlorella vulgaris which contains a considerable protein content. Similar to other microalgae, its desirability is minimal nutrient requirements since they are unicellular, photosynthetic, and fast-growing microorganisms. Another propitious option to be produced by C. vulgaris is biodiesel, since it is rich in oil too. Besides, algal well thriving in presence of increased amount of carbon dioxide makes them a practicable alternative biofuel resource without some problems of the traditional ones. At the same time, C. vulgaris is also a promising source for nutraceuticals such as amino acids, vitamins, and antioxidants. This review aims to discuss the conditions need to be observed for achieving a favorable growth efficiency of the C. vulgaris, as well as targeted productions such as biomass, antioxidant, and biofuel. Additionally, different approaches to induce any specific production are also considered comprehensively.
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Affiliation(s)
- Yunes Panahi
- Chemical Injuries Research Center, Systems Biology and Poisoning Institute, Baqiyatallah University of Medical Sciences, Tehran, Iran
| | - Ahmad Yari Khosroushahi
- Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Medical Nanotechnology, Faculty of Advanced Medical Science, Tabriz University of Medical Sciences, Tabriz, Iran
| | - Amirhossein Sahebkar
- Biotechnology Research Center, Pharmaceutical Technology Institute, Mashhad University of Medical Sciences, Mashhad, Iran
| | - Hamid Reza Heidari
- Drug Applied Research Center, Tabriz University of Medical Sciences, Tabriz, Iran
- Department of Pharmaceutical Biotechnology, Faculty of Pharmacy, Tabriz University of Medical Sciences, Tabriz, Iran
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Hemmerich J, Freier L, Wiechert W, von Lieres E, Oldiges M. Generic Protocol for Optimization of Heterologous Protein Production Using Automated Microbioreactor Technology. J Vis Exp 2017. [PMID: 29286407 PMCID: PMC5755569 DOI: 10.3791/56234] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/19/2022] Open
Abstract
A core business in industrial biotechnology using microbial production cell factories is the iterative process of strain engineering and optimization of bioprocess conditions. One important aspect is the improvement of cultivation medium to provide an optimal environment for microbial formation of the product of interest. It is well accepted that the media composition can dramatically influence overall bioprocess performance. Nutrition medium optimization is known to improve recombinant protein production with microbial systems and thus, this is a rewarding step in bioprocess development. However, very often standard media recipes are taken from literature, since tailor-made design of the cultivation medium is a tedious task that demands microbioreactor technology for sufficient cultivation throughput, fast product analytics, as well as support by lab robotics to enable reliability in liquid handling steps. Furthermore, advanced mathematical methods are required for rationally analyzing measurement data and efficiently designing parallel experiments such as to achieve optimal information content. The generic nature of the presented protocol allows for easy adaption to different lab equipment, other expression hosts, and target proteins of interest, as well as further bioprocess parameters. Moreover, other optimization objectives like protein production rate, specific yield, or product quality can be chosen to fit the scope of other optimization studies. The applied Kriging Toolbox (KriKit) is a general tool for Design of Experiments (DOE) that contributes to improved holistic bioprocess optimization. It also supports multi-objective optimization which can be important in optimizing both upstream and downstream processes.
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Affiliation(s)
- Johannes Hemmerich
- IBG-1: Biotechnology, Forschungszentrum Jülich; Research Center Jülich, Bioeconomy Science Center (BioSC)
| | - Lars Freier
- IBG-1: Biotechnology, Forschungszentrum Jülich; Research Center Jülich, Bioeconomy Science Center (BioSC)
| | - Wolfgang Wiechert
- IBG-1: Biotechnology, Forschungszentrum Jülich; Research Center Jülich, Bioeconomy Science Center (BioSC); Computational Systems Biotechnology (AVT.CSB), RWTH Aachen University
| | - Eric von Lieres
- IBG-1: Biotechnology, Forschungszentrum Jülich; Research Center Jülich, Bioeconomy Science Center (BioSC);
| | - Marco Oldiges
- IBG-1: Biotechnology, Forschungszentrum Jülich; Research Center Jülich, Bioeconomy Science Center (BioSC); Institute for Biotechnology, RWTH Aachen University;
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