1. Academic Validation
  2. Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics

Slice-PASEF: Maximising Ion Utilisation in LC-MS Proteomics

  • bioRxiv. 2025 Sep 2:2022.10.31.514544. doi: 10.1101/2022.10.31.514544.
Ludwig R Sinn 1 Lukasz Szyrwiel 1 Justus Grossmann 1 Kate Lau 1 Katharina Faisst 1 Di Qin 2 3 Florian Mutschler 4 5 Luke Khoury 6 Andrew Leduc 6 Markus Ralser 1 Fabian Coscia 2 Matthias Selbach 4 Nikolai Slavov 6 Nagarjuna Nagaraj 7 Martin Steger 8 Vadim Demichev 1
Affiliations

Affiliations

  • 1 Department of Biochemistry, Charité - Universitätsmedizin Berlin, Berlin, Germany.
  • 2 Spatial Proteomics Group, Max-Delbrück-Center for Molecular Medicine in the Helmholtz Association, Berlin, Germany.
  • 3 Charité - Universitätsmedizin Berlin.
  • 4 Proteome Dynamics, Max Delbrück Center for Molecular Medicine in the Helmholtz Association (MDC), Berlin, Germany.
  • 5 Faculty of Life Sciences, Humboldt-Universität zu Berlin, Berlin Germany.
  • 6 Departments of Bioengineering, Biology, Chemistry and Chemical Biology, Single Cell Proteomics Center and Barnett Institute, Northeastern University, Boston, MA, USA; Parallel Squared Technology Institute, Watertown, MA, USA.
  • 7 Evotec International GmbH, Neuried, Germany.
  • 8 NEOsphere Biotechnologies GmbH, Planegg, Germany.
Abstract

Quantitative mass spectrometry (MS)-based proteomics has become a streamlined technology with a wide range of usage. Many emerging applications, such as single-cell proteomics, spatial proteomics of tissue sections and the profiling of low-abundant posttranslational modifications, require the analysis of minimal sample amounts and are thus constrained by the sensitivity of the workflow. Here, we present Slice-PASEF, a mass spectrometry technology that leverages trapped ion mobility separation of ions to attain the theoretical maximum of tandem MS sensitivity. We implement Slice-PASEF using a new module in our DIA-NN software and show that Slice-PASEF uniquely enables precise quantitative proteomics of low sample amounts. We further demonstrate its utility towards a range of applications, including single cell proteomics and degrader drug screens via ubiquitinomics.

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