Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm
4′-N-demethyl-vicenistatin is a vicenistatin analogue that has better antitumor activity with promising applications in the pharmaceuticals industry. The harnessing of the complete potential of this compound necessitates a systematic optimization of the culture medium to enable the cost-effective pr...
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| Format: | Article |
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MDPI AG
2024-03-01
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| Series: | Fermentation |
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| Online Access: | https://www.mdpi.com/2311-5637/10/3/154 |
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| author | Zhixin Yu Hongxin Fu Jufang Wang |
| author_facet | Zhixin Yu Hongxin Fu Jufang Wang |
| author_sort | Zhixin Yu |
| collection | DOAJ |
| description | 4′-N-demethyl-vicenistatin is a vicenistatin analogue that has better antitumor activity with promising applications in the pharmaceuticals industry. The harnessing of the complete potential of this compound necessitates a systematic optimization of the culture medium to enable the cost-effective production of 4′-N-demethyl-vicenistatin by <i>Streptomyces parvus</i> SCSIO Mla-L010/Δ<i>vicG</i>. Therefore, in this study, a sequential approach was employed to screen the significant medium compositions, as follows: one-factor-at-a-time (OFAT) and Plackett–Burman designs (PBD) were initially utilized. Cassava starch, glycerol, and seawater salt were identified as the pivotal components influencing 4′-N-demethyl-vicenistatin production. To further investigate the direct and interactive effects of these key components, a three-factor, five-level central composite design (CCD) was implemented. Finally, response surface methodology (RSM) and an artificial-neural-network-genetic-algorithm (ANN-GA) were employed for the modeling and optimization of the medium components to enhance efficient 4′-N-demethyl-vicenistatin production. The ANN-GA model showed superior reliability, achieving the most 4′-N-demethyl-vicenistatin, at 0.1921 g/L, which was 17% and 283% higher than the RSM-optimized and initial medium approaches, respectively. This study represents pioneering work on statistically guided optimization strategies for enhancing 4′-N-demethyl-vicenistatin production through medium optimization. |
| first_indexed | 2024-04-24T18:18:25Z |
| format | Article |
| id | doaj.art-be96d2015d9f46628f2bfe82f46cd7ed |
| institution | Directory Open Access Journal |
| issn | 2311-5637 |
| language | English |
| last_indexed | 2024-04-24T18:18:25Z |
| publishDate | 2024-03-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Fermentation |
| spelling | doaj.art-be96d2015d9f46628f2bfe82f46cd7ed2024-03-27T13:37:59ZengMDPI AGFermentation2311-56372024-03-0110315410.3390/fermentation10030154Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-AlgorithmZhixin Yu0Hongxin Fu1Jufang Wang2School of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, ChinaSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, ChinaSchool of Biology and Biological Engineering, South China University of Technology, Guangzhou 510006, China4′-N-demethyl-vicenistatin is a vicenistatin analogue that has better antitumor activity with promising applications in the pharmaceuticals industry. The harnessing of the complete potential of this compound necessitates a systematic optimization of the culture medium to enable the cost-effective production of 4′-N-demethyl-vicenistatin by <i>Streptomyces parvus</i> SCSIO Mla-L010/Δ<i>vicG</i>. Therefore, in this study, a sequential approach was employed to screen the significant medium compositions, as follows: one-factor-at-a-time (OFAT) and Plackett–Burman designs (PBD) were initially utilized. Cassava starch, glycerol, and seawater salt were identified as the pivotal components influencing 4′-N-demethyl-vicenistatin production. To further investigate the direct and interactive effects of these key components, a three-factor, five-level central composite design (CCD) was implemented. Finally, response surface methodology (RSM) and an artificial-neural-network-genetic-algorithm (ANN-GA) were employed for the modeling and optimization of the medium components to enhance efficient 4′-N-demethyl-vicenistatin production. The ANN-GA model showed superior reliability, achieving the most 4′-N-demethyl-vicenistatin, at 0.1921 g/L, which was 17% and 283% higher than the RSM-optimized and initial medium approaches, respectively. This study represents pioneering work on statistically guided optimization strategies for enhancing 4′-N-demethyl-vicenistatin production through medium optimization.https://www.mdpi.com/2311-5637/10/3/154culture medium optimizationresponse surface methodology4′-N-demethyl-vicenistatin<i>Streptomyces parvus</i>artificial-neural-network-genetic-algorithm |
| spellingShingle | Zhixin Yu Hongxin Fu Jufang Wang Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm Fermentation culture medium optimization response surface methodology 4′-N-demethyl-vicenistatin <i>Streptomyces parvus</i> artificial-neural-network-genetic-algorithm |
| title | Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm |
| title_full | Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm |
| title_fullStr | Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm |
| title_full_unstemmed | Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm |
| title_short | Modeling and Optimization of the Culture Medium for Efficient 4′-N-Demethyl-Vicenistatin Production by <i>Streptomyces parvus</i> Using Response Surface Methodology and Artificial-Neural-Network-Genetic-Algorithm |
| title_sort | modeling and optimization of the culture medium for efficient 4 n demethyl vicenistatin production by i streptomyces parvus i using response surface methodology and artificial neural network genetic algorithm |
| topic | culture medium optimization response surface methodology 4′-N-demethyl-vicenistatin <i>Streptomyces parvus</i> artificial-neural-network-genetic-algorithm |
| url | https://www.mdpi.com/2311-5637/10/3/154 |
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