Author(s)

  • Anna Sophie Welter (Presenting Author) | Selbach Lab | Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Max Delbrück Center), Robert-Rössle-Str. 10, 13125, Berlin, Germany
  • Florian Mutschler | Selbach Lab | Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Max Delbrück Center), Robert-Rössle-Str. 10, 13125, Berlin, Germany
  • Maximilian Gerwien | Selbach Lab | Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Max Delbrück Center), Robert-Rössle-Str. 10, 13125, Berlin, Germany
  • Matthias Selbach | Selbach Lab | Max Delbrück Center for Molecular Medicine in the Helmholtz Association (Max Delbrück Center), Robert-Rössle-Str. 10, 13125, Berlin, Germany

Abstract

Recent advances in mass spectrometry instrumentation and data acquisition strategies have made single-cell (sc) proteomics increasingly accessible. However, most sc proteomic studies prioritize protein identifications and suffer from high rates of missing values, limiting biological interpretability and quantitative robustness. To address these challenges, we developed a single-cell data-independent acquisition (DIA) strategy that incorporates a heavy-labelled SILAC spike-in standard (scDIA-SiS) to boost peptide signal intensity and improve quantification accuracy in ultra-low-input samples. This spike-in approach substantially enhances proteome coverage and data completeness, while enabling robust normalization across single cells. We applied scDIA-SiS to individual U2OS cells isolated by FACS according to cell cycle phase. The resulting datasets allow confident quantification of cell cycle-regulated proteins and reveal substantial intercellular variability in protein abundance that persists independently of cell cycle stage or cell size. Ongoing experiments using SILAC pulse-labelling at the single-cell level aim to dissect the contribution of protein turnover to this heterogeneity.