AUTHOR=Zhou Tingting , Huangfu Ningbo , Wang Li , Luo Junyu , Cui Jinjie , Zhu Xiangzhen , Wan Sumei , Gao Xueke 

TITLE=Stage-specific metabolic allocation: nutrient investment strategies during Lysiphlebia japonica Ashmead development

JOURNAL=Frontiers in Nutrition

VOLUME=Volume 12 - 2025

YEAR=2025

URL=https://www.frontiersin.org/journals/nutrition/articles/10.3389/fnut.2025.1636519

DOI=10.3389/fnut.2025.1636519

ISSN=2296-861X

ABSTRACT=IntroductionParasitic wasps are key biological control agents that rely on precise nutrient allocation to regulate host exploitation and optimize their own development. Nutrients, particularly lipids and energy-related metabolites, play a critical role in shaping stage-specific growth and survival strategies in parasitic wasps.MethodsTo analyze the allocation patterns of metabolite resources during development of parasitoid wasps, the multi-omics analysis was employed to systematically investigate nutrient dynamics across three growth periods in Lysiphlebia japonica Ashmead, a major parasitoid of cotton aphid (Aphis gossypii Glover).ResultsHere, a total of 753 metabolites were detected by untargeted metabolomics, with numerous nutritionally critical compounds including amino acids, fatty acids and carbohydrates showed stage-specific variations. A total of 31 fatty acids (11 SFAs, 9 MUFAs, 11 PUFAs) were identified by targeted fatty acid detection, exhibiting a notable variation across development notably, PUFAs remained consistently dominant throughout all stages, suggesting their essential role in parasitoid growth. Correlation analysis further indicated that α-ketoglutaric acid and glutamic acid were functionally associated with fatty acids, serving as potential developmental biomarkers.DiscussionThis study presented the first comprehensive metabolomic atlas of L. japonica development, uncovering nutrient allocation strategies that synchronize with its life cycle. By identifying key metabolites and fatty acids involved in its growth, our work provided a theoretical foundation for enhanced artificial rearing of parasitic wasps. Overall, these findings offered novel insights for translating omics data into practical applications, with significant theoretical and practical implications for developing improved biological control strategies.