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Updated: Aug 10, 2026

Deep Proteome Profiling by Isobaric Labeling, Extensive Liquid Chromatography, Mass Spectrometry, and Software-assisted Quantification
Published on: November 15, 2017
SIGNIFICANT IMPACT OF CONSUMABLE MATERIAL AND BUFFER COMPOSITION FOR LOW-CELL NUMBER PROTEOMIC SAMPLE PREPARATION
Christopher Kune1, Sylvia Tielens2, Dominique Baiwir3
1Mass Spectrometry Laboratory, MolSys Research Unit, University of Liege, Liege B-4000, Belgium.
Abstract:
Proteomics, essential for understanding gene and cell functions, faces challenges with peptide loss due to adsorption onto vial surfaces, especially in samples with low peptide quantities. Using HeLa tryptic digested standard solutions, we demonstrate preferential adsorption of peptides, particularly hydrophobic ones, onto polypropylene (PP) vials, leading to nonuniform signal loss. This phenomenon can alter protein quantification (e.g., Label-Free Quantification, LFQ) if no appropriate data processing is applied. Our study is based on understanding this adsorption phenomenon to establish recommendations for minimizing peptide loss. To address this issue, we evaluated the nature of surface material and buffer additives to reduce peptide-surface noncovalent binding. Here, we report that using vials made from polymer containing polar monomeric units such as poly(methyl methacrylate) (PMMA) or polyethylene terephthalate (PET) drastically reduces the hydrophobic peptide loss, increasing the global proteomics performance (4-fold increase in identified peptides for the single-cell equivalent peptide content range). Additionally, the incorporation of nonionic detergents like poly(ethylene oxide) (PEO) and n-Dodecyl-Beta-Maltoside (DDM) at optimized concentrations (0.0001% and 0.0075%, respectively) improves the overall proteomic performance and consistency, even across different vial materials. Implementing these recommendations on 0.2 ng/μL HeLa tryptic digest results in a 10-fold increase in terms of peptide signal. Application to True Single-Cell sample preparation without specialized instrumentation dramatically improves the performance, allowing for the identification of approximately 650 proteins, a stark contrast to none detected with classical protocols.

