Details

Autor(en) / Beteiligte

• Sinn, Ludwig R
• Giese, Sven H
• Stuiver, Marchel
• Rappsilber, Juri

Titel

Leveraging Parameter Dependencies in High-Field Asymmetric Waveform Ion-Mobility Spectrometry and Size Exclusion Chromatography for Proteome-wide Cross-Linking Mass Spectrometry

Ist Teil von

• Analytical chemistry (Washington), 2022-03, Vol.94 (11), p.4627-4634

Ort / Verlag

United States: American Chemical Society

Erscheinungsjahr

2022

Link zum Volltext

Quelle

MEDLINE

Beschreibungen/Notizen

• Ion-mobility spectrometry shows great promise to tackle analytically challenging research questions by adding another separation dimension to liquid chromatography–mass spectrometry. The understanding of how analyte properties influence ion mobility has increased through recent studies, but no clear rationale for the design of customized experimental settings has emerged. Here, we leverage machine learning to deepen our understanding of field asymmetric waveform ion-mobility spectrometry for the analysis of cross-linked peptides. Knowing that predominantly m/z and then the size and charge state of an analyte influence the separation, we found ideal compensation voltages correlating with the size exclusion chromatography fraction number. The effect of this relationship on the analytical depth can be substantial as exploiting it allowed us to almost double unique residue pair detections in a proteome-wide cross-linking experiment. Other applications involving liquid- and gas-phase separation may also benefit from considering such parameter dependencies.