Deep Single-Shot NanoLC-MS Proteome Profiling with a 1500 Bar UHPLC System, Long Fully Porous Columns, and HRAM MS.
Runsheng ZhengKarel StejskalChristopher PynnKarl MechtlerAlexander BoychenkoPublished in: Journal of proteome research (2022)
This study demonstrates how the latest ultrahigh-performance liquid chromatography (UHPLC) technology can be combined with high-resolution accurate-mass (HRAM) mass spectrometry (MS) and long columns packed with fully porous particles to improve bottom-up proteomics analysis with nanoflow liquid chromatography-mass spectrometry (nanoLC-MS) methods. The increased back pressures from the UHPLC system enabled the use of 75 μm I.D. × 75 cm columns packed with 2 μm particles at a typical 300 nL/min flow rate as well as elevated and reduced flow rates. The constant pressure pump operation at 1500 bar reduced sample loading and column washing/equilibration stages and overall overhead time, which maximizes MS utilization time. The versatility of flow rate optimization to balance the sensitivity, throughput with sample loading amount, and capability of using longer gradients contributes to a greater number of peptide and protein identifications for single-shot bottom-up proteomics experiments. The routine proteome profiling and precise quantification of >7000 proteins with single-shot nanoLC-MS analysis open possibilities for large-scale discovery studies with a deep dive into the protein level alterations. Data are available via ProteomeXchange with identifier PXD035665.
Keyphrases
- mass spectrometry
- liquid chromatography
- high resolution mass spectrometry
- tandem mass spectrometry
- simultaneous determination
- high resolution
- ultra high performance liquid chromatography
- solid phase extraction
- high performance liquid chromatography
- gas chromatography
- ms ms
- capillary electrophoresis
- liquid chromatography tandem mass spectrometry
- single cell
- high throughput
- minimally invasive
- machine learning
- amino acid
- multiple sclerosis
- small molecule
- highly efficient
- artificial intelligence