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Updated: Jun 30, 2026

Identification of Protein Interaction Partners in Mammalian Cells Using SILAC-immunoprecipitation Quantitative Proteomics
Published on: July 6, 2014
A robust protocol for proteomic profiling of secreted proteins in conditioned culture medium
Takayoshi Otsuka1, Atsushi Hatano2, Masaki Matsumoto2
1Department of Neuroscience of Disease, Brain Research Institute, Niigata University, Niigata 951-8585, Japan.
Abstract:
Reliable secretome analysis is crucial for understanding cellular communication and developing therapeutic strategies. However, conventional protein quantification methods, such as the bicinchoninic acid (BCA) assay, can overestimate protein concentrations in concentrated culture media, leading to inconsistent protein loading and compromised quantitative accuracy in mass spectrometry-based proteomics. To address this methodological challenge, we developed an improved sample preparation method for secretome analysis. Our approach introduces a concentration rate-based normalization method that adjusts sample volumes according to the ultrafiltration concentration ratio, ensuring more consistent protein loading across samples. This method enabled reliable identification of 3468 secreted proteins with high reproducibility (r > 0.93) in a model system of nuclear DNA (nucDNA)-induced inflammation in HeLa cells. Secretome profiles were distinctly altered by nucDNA transfection, with 89 proteins showing significant differential release between control and nucDNA-transfected wild-type HeLa cells. Furthermore, we identified a subset of proteins, including chaperone and proteasome complexes, that were consistently released across all conditions, suggesting their potential utility as internal controls for secretome analysis. This study presents a practical solution to the methodological challenge in secretome analysis, enabling more reliable and reproducible secretome profiling. This improved methodology represents an important step toward establishing standardized protocols for secretome analysis, ultimately enhancing the quality and comparability of research in this rapidly growing field.
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