A Proteomic Atlas of Human Milk: Uncovering Milk Functional Components
TL;DR
A large-scale meta-analysis of mass spectrometry–based proteomics datasets was performed to construct a unified, queryable human milk proteome atlas for system-level interpretation, highlighting the systems-level relevance of milk proteins and their potential role in maternal–infant regulation in health and disease.
Abstract
Human milk is a complex and highly organized biofluid whose molecular composition underpins neonatal nutrition, immune protection, and developmental regulation. Despite extensive proteomic profiling, its global organizational structure remains fragmented and poorly integrated. Here, we performed a large-scale meta-analysis of mass spectrometry–based proteomics datasets to construct a unified, queryable human milk proteome atlas for system-level interpretation. By harmonizing datasets through standardized preprocessing and normalization, we defined a core human milk proteome comprising the most recurrent and consistently detected proteins and peptides. An established machine-learning-based method was applied to predict binary protein–protein interactions from this core set, enabling reconstruction of a dense interaction network and moving beyond isolated protein catalogues toward a systems-level representation of milk organization. Network analysis revealed functional modules related to immune defence, vesicle-mediated secretion, and proteostatic control, while protein regulatory networks were also reconstructed. These results highlight the systems-level relevance of milk proteins and their potential role in maternal–infant regulation in health and disease. The integrative framework and web resource (http://atlas-galatea.insybio.com/) provide a foundation for comparative proteomics and network-based studies of the regulatory architecture of human milk.