Synthetic Biology-Driven Innovation in the Production of Cosmetic Ingredients: From Natural Mimicry to Precision Creation

Abstract

The cosmetics industry is undergoing a historic transition from natural extraction to precision biomanufacturing. Amino acid derivatives, as a kind of core functional cosmetic ingredient, have witnessed synthetic biology-based production technologies overcome traditional bottlenecks in efficiency and cost. In this Perspective, grounded in recent advances in the construction of amino acid derivative cell factories, we propose the core trends for the future development of cosmetic ingredients: enzyme engineering, dynamic metabolic control, and irrational strategies are converging to enable both functional customization and production intelligence. Star molecules such as ergothioneine, spermidine, and bioactive peptides are poised to redefine the boundaries of anti-aging efficacy, while AI-driven R&D paradigms offer broad prospects but must still overcome cost, regulatory, and consumer perception barriers. We emphasize that only by establishing an integrated “efficient synthesis-precise delivery-validated activity” end-to-end chain can cosmetic ingredients move from laboratory to market, achieving an industrial leap from chemical addition to biological empowerment.

Keywords

Synthetic biology / Amino acid derivatives / Cosmetics / Dynamic regulation / AI-driven design

Statement of the Use of Generative AI and AI-Assisted Technologies in the Writing Process

During the preparation of this manuscript, the author(s) used DeepL and ChatGPT in order to improve readability and language editing. After using these tools, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

Acknowledgments

We thank members of the laboratory for helpful discussions.

Author Contributions

Writing—Original Draft Preparation, J.Y.; Visualization, M.Z. and F.H.; Writing—Review & Editing, H.W. and Q.M.; Project Administration, X.X.; Funding Acquisition, X.X.

Ethics Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

No datasets were generated or analyzed during the current study.

Funding

This research received funding from the National Key Research and Development Program of China (2022YFA0911800), Key Research and Development Program of Ningxia Hui Autonomous Region (2025BEE02021), National Natural Science Foundation of China (22378315, 32200038), Natural Science Foundation of Tianjin (24JCYBJC00830).

Declaration of Competing Interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

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