Proteomics for cultivated meat: Current insights and research frontiers

Cultivated meat, produced through cellular agriculture, is emerging as an alternative to conventional livestock production. Comprehensive proteome characterization across its production chain is essential for product development, quality control, and food safety assessment, yet proteomics application to cultivated meat faces considerable technical complexity. This work reviews proteomics applications across the cultivated meat production chain, including cell line characterization, culture media optimization, differentiation monitoring, product quality and nutritional evaluation, safety and allergenicity detection, and authenticity traceability. Bottom-up mass spectrometry workflows, data acquisition strategies, and emerging approaches are critically evaluated. While new-generation instruments (e.g., Orbitrap Astral) enable ultradeep proteome coverage, instrumental performance alone cannot overcome between-method variability of up to 45% in protein group identifications reported across different sample-preparation protocols, a dispersion that may be attributable in part to differences in extraction solvents and protein-specific solubility characteristics rather than to poor reproducibility within any individual method. This between-method dispersion remains a key obstacle to cross-laboratory comparability and regulatory acceptance. High-resolution instrumentation, methodological standardization, multi-omics integration, and artificial intelligence for high-dimensional data must therefore operate as complementary layers, forming the analytical infrastructure required to advance cultivated meat from laboratory feasibility to industrial-scale production. SIGNIFICANCE: Cultivated meat represents a paradigm shift in protein production, yet its regulatory approval depends on molecular characterization that proteomics is uniquely positioned to provide. By reviewing proteomics applications across the entire production chain, evaluating analytical platforms, and highlighting between-method variability of up to 45% across sample-preparation protocols as a key bottleneck, this work articulates the urgent need for standardized protocols. The proposed framework for analytical standardization, combined with perspectives on multi-omics integration and AI-driven analysis, offers a roadmap for the proteomics community, regulators, and industry to establish the reproducible analytical infrastructure essential for consumer safety and global market development.