Background

The secretome is a complete set of proteins secreted by cells into the extracellular space [1]. In a cell culture system, the secretome can be profiled from conditioned medium, which is a cell culture medium containing secreted proteins and signaling factors released by the cells during incubation under defined conditions [2]. Mass spectrometry–based proteomic analysis of the secretome is an established strategy for studying extracellular communication, discovering biomarkers, and identifying therapeutic targets [3,4]. In parallel, large-scale mapping of the human proteome highlights the importance of capturing both abundant housekeeping proteins and rare, tissue-specific factors in secretome studies [5]. However, secretome proteins are often present at very low concentrations and are masked by highly abundant serum proteins such as albumin and immunoglobulins [6], which complicates mass spectrometry analysis.

These challenges intensify when processing large volume samples (>5 mL), as often required to obtain sufficient secretome, particularly with primary cells or low-secreting cultures. Without rigorous sample processing, low-abundance proteins like cytokines and chemokines are frequently lost, while high-abundance proteins overshadow the results [6].

Early comparative work established in-gel digestion followed by LC–MS/MS as a robust strategy for protein identification, but this approach is labor-intensive, biased toward higher-abundance proteins, and suboptimal for low-molecular-weight cytokines [7]. More recently, systematic benchmarking studies demonstrated that acetone precipitation with in-solution digestion improved reproducibility and enhanced recovery of small-secreted proteins [8]. However, these protocols were primarily optimized for small input volumes (≤ 2 mL) and did not adequately address challenges of serum protein contamination or scalability.

To overcome these limitations, we developed an optimized protocol specifically designed for high-volume secretome samples (>5 mL) [9]. This workflow integrates three complementary steps: (i) 50 kDa ultrafiltration to generate both concentrate and filtrate fractions, (ii) spin column depletion [10] of abundant serum proteins, and (iii) acetone/TCA precipitation to maximize protein recovery. By processing both the filtrate and depleted concentrate in parallel, the protocol ensures balanced recovery of low-abundance cytokines and chemokines alongside high-molecular-weight extracellular matrix proteins, while minimizing background interference and serum protein contamination. The overall workflow is illustrated in Figure 1.

Figure 1. Workflow for optimized secretome preparation for LC–MS/MS analysis. Conditioned medium is first clarified by centrifugation (500× g, 5 min, 4 °C) and filtered through a 0.22 μm low-protein-binding filter to remove cells and debris. The clarified medium is then concentrated using Amicon Ultra-15 centrifugal filters (50 kDa MWCO), yielding approximately 100 μL of concentrate and 15 mL of filtrate, depending on the initial sample volume. The concentrate is subjected to HSA/IgG depletion to eliminate abundant serum proteins. The depleted concentrate and filtrate are then combined to generate a comprehensive secretome sample, which is subsequently precipitated, digested, and analyzed by LC–MS/MS. This workflow maximizes recovery of both low- and high-molecular-weight secreted proteins while minimizing background from serum components.

This method demonstrates improved sensitivity, reproducibility, and scalability compared to previous protocols. It maintains the identification capabilities of acetone precipitation workflows and extends their use to high-volume samples, which are often necessary for primary or low-secreting cultures. Additionally, it overcomes the reproducibility and coverage limitations associated with in-gel digestion-based approaches and outperforms ultrafiltration-only methods that do not efficiently recover low-molecular-weight proteins. Therefore, this optimized workflow offers a robust and adaptable solution for comprehensive secretome profiling, making it particularly advantageous for biomarker discovery pipelines that require broad dynamic range, scalability, and reproducibility.