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Hybrid experimental-machine learning framework for media optimization enhances antioxidant production in Micrococcus

Md Sourav Sarker1, Asmamaw Abat Getu1, Juvens Sugira Murekezi1

  • 1State Key Laboratory of Regional and Urban Ecology, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen, Fujian 361021, PR China; University of Chinese Academy of Sciences, Beijing 100049, China.

Journal of Microbiological Methods
|April 18, 2026
PubMed
Summary

Optimizing microbial antioxidant production requires advanced methods. A hybrid approach using neural networks and genetic algorithms successfully enhanced antioxidant activity in Micrococcus endophyticus SS-1, validated by reduced half-maximal effective concentration.

Keywords:
Antioxidant activityGenetic algorithmMachine learningMedia optimizationNeural networkOrthogonal array

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Area of Science:

  • Microbiology
  • Biotechnology
  • Computational Biology

Background:

  • Microbial antioxidant production is vital but difficult to optimize due to complex nutrient interactions.
  • Systematic optimization of culture media for antioxidant yield is challenging.

Purpose of the Study:

  • To develop and validate a hybrid experimental-computational framework for optimizing antioxidant production in Micrococcus endophyticus SS-1.
  • To identify novel culture media formulations that enhance antioxidant potency.

Main Methods:

  • Implemented a hybrid framework combining orthogonal array design, neural network surrogate modeling, and genetic algorithm optimization.
  • Evaluated ten nutritional and cultivation factors using an L81 orthogonal array.
  • Validated optimized media through 2,2-diphenyl-1-picrylhydrazyl radical-scavenging assays and dose-response experiments.

Main Results:

  • The genetic algorithm-optimized medium significantly increased antioxidant activity compared to baseline and orthogonal array formulations.
  • Experimentally validated optimized media demonstrated enhanced antioxidant potency, indicated by a reduced half-maximal effective concentration (EC50).

Conclusions:

  • The hybrid experimental-computational approach is effective for optimizing microbial antioxidant production.
  • The optimized medium enhances the intrinsic potency of antioxidants produced by Micrococcus endophyticus SS-1.