Abstract
<title>Abstract</title> <p>Cellular secretome profiling is essential for decoding intercellular communication, identifying disease biomarkers, and discovering therapeutic targets. Although mass spectrometry-based proteomics is the gold standard for discovery-driven analysis, deep secretome profiling remains technically challenging because low-abundance signaling molecules are masked by the vast dynamic range of high-background serum supplements. To overcome these limitations, we develop DeepSec, a robust and streamlined method that uses a small-molecule–modulated nanoparticle protein corona to selectively deplete bovine serum albumin from conditioned media. Using an endogenous lipopolysaccharide (LPS) dose-response series, DeepSec preserved biological fold changes relative to a non-depleted workflow and orthogonal ELISA, establishing protein-corona enrichment as a quantitatively faithful strategy for dynamic secretome proteomics. In parallel, DeepSec increased the number of significantly secreted proteins by three-fold. We demonstrate its utility for profiling secretomes from cultured cells and host–pathogen interaction models. Using pathway-specific inhibitors, we further resolve proteins secreted through ER–Golgi- and autophagy-dependent routes following LPS stimulation. Finally, we show the translational utility of DeepSec by profiling patient-derived 3D liver microtissues modeling metabolic dysfunction-associated steatohepatitis, capturing distinct, drug-specific metabolic and extracellular matrix rewiring patterns in response to clinical therapeutics. These results establish DeepSec as a robust platform for interrogating complex extracellular signaling networks across diverse models of health and disease.</p>