Dataset Information

Optimizing single cell proteomics on a trapped ion mobility spectrometry for label-free experiments

ABSTRACT: Although single cell RNA-seq has had a tremendous impact on biological research, a corresponding technology for unbiased mass spectrometric analysis of single cells has only recently become available. Significant technological breakthroughs including miniaturized sample handling have enabled proteome profiling of single cells. Further, a trapped ion mobility spectrometry (TIMS) in combination with parallel accumulation-serial fragmentation operated with data-dependant acquisition mode has allowed improved proteome coverage from low-input samples. It has been demonstrated that modulating ion flux in TIMS affects overall performance of proteome profiling. However, the effect of TIMS settings for analyzing low-input samples has been less investigated. Thus, we sought to optimize conditions of TIMS in regards of ion accumulation/ramp times and ion mobility range for low-input samples. We observed that ion accumulation times of 180 ms and monitoring a narrower ion mobility range from 0.7 to 1.3 Vs cm-2 resulted in a substantial gain in the depth of proteome coverage and in detecting proteins with low abundance. We applied these optimized conditions for proteome profiling of sorted human primary T cells, which yielded an average of 365, 804, 1,116, and 1,651 proteins from single, five, ten, and forty T cells, respectively. Notably, we demonstrated that the depth of proteome coverage from low number of cells was sufficient to delineate several essential metabolic pathways and T cell receptor signaling pathway. Finally, we showed the feasibility of detecting post-translational modifications including phosphorylation and acetylation from single cells. We believe that these parameters could be applied to label-free analysis of single cells obtained from clinically relevant samples.

INSTRUMENT(S): timsTOF SCP

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Primary Cell, T Cell, Blood

SUBMITTER: Akhilesh Pandey

LAB HEAD: Akhilesh Pandey

PROVIDER: PXD039066 | Pride | 2024-08-02

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	2021-05-26-decoys-reviewed-contam-iRT-UP000005640.fas	Other
	Diluted_Peptides_HeLa.zip	Other
	Diluted_Peptides_HeLa_Search_Result.zip	Other
	Diluted_Peptides_Triplicate.zip	Other
	Diluted_Peptides_Triplicate_Search_Result.zip	Other

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Optimizing single cell proteomics using trapped ion mobility spectrometry for label-free experiments.

Mun Dong-Gi DG Bhat Firdous A FA Ding Husheng H Madden Benjamin J BJ Natesampillai Sekar S Badley Andrew D AD Johnson Kenneth L KL Kelly Ryan T RT Pandey Akhilesh A

The Analyst 20230726 15

Although single cell RNA-seq has had a tremendous impact on biological research, a corresponding technology for unbiased mass spectrometric analysis of single cells has only recently become available. Significant technological breakthroughs including miniaturized sample handling have enabled proteome profiling of single cells. Furthermore, trapped ion mobility spectrometry (TIMS) in combination with parallel accumulation-serial fragmentation operated in data-dependent acquisition mode (DDA-PASEF ...[more]

PMID: 37395315

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