Single Cell Proteomics (SCP) is an emerging field that labs start to implement. It allows to reach a unique level of information using mass spectrometry. The identification and the quantification of the proteome of single cells could lead to the characterization of cell sub-populations with specific proteome signatures and associated regulations. This will participate to develop new strategies for personalized medicine approaches. However, implementation of SCP remains challenging and the "way-to-do" is unclear. Here, we propose a demonstration for the implementation of various technologies.

In this study, HeLa digest was used as standard sample with a dilution range allowing the analysis of 20ng down to 0.05ng. This standard was used for the development of a method on a NanoAcquity liquid chromatography (Waters) coupled with Eclipse mass spectrometer (Thermo). The tests included the change of the analytical column from 25cm to 10cm length, the removal of the pre-column, the gradient optimization (total run time of 30min vs 15min), the addition of FAIMS technology and the evaluation of software as MaxQuant and Proteome Discoverer and DIA-NN. Finally, we propose an easy to implement method on the CellenONE (Scienion) to significantly improved the rate of isolation of viable cells, on MCF7 cells for which apoptosis was enhanced.

This project aims to provide guidelines for the implementation of SCP analysis using broadly used technologies. Publications demonstrated setups specifically developed for SCP analysis, but none of the presented studies highlighted the gain of each of the technologies as a whole [1], [2]. Furthermore, not all the documented technologies [3], [4] are available broadly, limiting the implementation in labs. In this study, demonstrations will be obtained on the gain in analysis throughput using shorter column, the improved depth of analysis with FAIMS technology, for example. Additionally, a method for the capture of viable cells at a higher rate and with a non-toxic and simple method on the CellenONE platform, was demonstrated on MCF7 cells.

[1] Cong et al., Chem. Sci., 2021

[2] Furtwängler et al., Mol. Cell. Proteomics, 2022

[3] Kreimer et al., Anal. Chem., 2023

[4] Mund et al., Nat. Biotechnol., 2022