Journal
JOURNAL OF PROTEOME RESEARCH
Volume -, Issue -, Pages -Publisher
AMER CHEMICAL SOC
DOI: 10.1021/acs.jproteome.2c00376
Keywords
peptide identification optimization; mass spectrometry; ultrasensitive proteomics; data acquisition; low-input applications; FAIMS-MS
Categories
Funding
- Erasmus grant from the Technical University of Munich - Novo Nordisk Foundation
- Novo Nordisk Foundation as part of the Copenhagen Bioscience PhD
- Leo Foundation
- [NNF21OC0071016]
- [NNF19SA0035442]
- [LF-OC-21-000832]
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The study optimized a method combining orbitrap and linear ion trap for low-input proteomics experiments, improving throughput and sensitivity for large-scale proteomics studies with limited material.
In recent years, the concept of cell heterogeneity in biology has gained increasing attention, concomitant with a push toward technologies capable of resolving such biological complexity at the molecular level. For single-cell proteomics using Mass Spectrometry (scMS) and low-input proteomics experiments, the sensitivity of an orbitrap mass analyzer can sometimes be limiting. Therefore, low-input proteomics and scMS could benefit from linear ion traps, which provide faster scanning speeds and higher sensitivity than an orbitrap mass analyzer, however at the cost of resolution. We optimized an acquisition method that combines the orbitrap and linear ion trap, as implemented on a tribrid instrument, while taking advantage of the high-field asymmetric waveform ion mobility spectrometry (FAIMS) pro interface, with a prime focus on low-input applications. First, we compared the performance of orbitrap-versus linear ion trap mass analyzers. Subsequently, we optimized critical method parameters for low-input measurement by data-independent acquisition on the linear ion trap mass analyzer. We conclude that linear ion traps mass analyzers combined with FAIMS and Whisper flow chromatography are well-tailored for low-input proteomics experiments, and can simultaneously increase the throughput and sensitivity of large-scale proteomics experiments where limited material is available, such as clinical samples and cellular subpopulations.
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