TY - JOUR
T1 - Exploration of cell state heterogeneity using single-cell proteomics through sensitivity-tailored data-independent acquisition
AU - Petrosius, Valdemaras
AU - Aragon-Fernandez, Pedro
AU - Üresin, Nil
AU - Kovacs, Gergo
AU - Phlairaharn, Teeradon
AU - Furtwängler, Benjamin
AU - Op De Beeck, Jeff
AU - Skovbakke, Sarah L.
AU - Goletz, Steffen
AU - Thomsen, Simon Francis
AU - Keller, Ulrich Auf dem
AU - Natarajan, Kedar N.
AU - Porse, Bo T.
AU - Schoof, Erwin M.
PY - 2023
Y1 - 2023
N2 - Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
AB - Single-cell resolution analysis of complex biological tissues is fundamental to capture cell-state heterogeneity and distinct cellular signaling patterns that remain obscured with population-based techniques. The limited amount of material encapsulated in a single cell however, raises significant technical challenges to molecular profiling. Due to extensive optimization efforts, single-cell proteomics by Mass Spectrometry (scp-MS) has emerged as a powerful tool to facilitate proteome profiling from ultra-low amounts of input, although further development is needed to realize its full potential. To this end, we carry out comprehensive analysis of orbitrap-based data-independent acquisition (DIA) for limited material proteomics. Notably, we find a fundamental difference between optimal DIA methods for high- and low-load samples. We further improve our low-input DIA method by relying on high-resolution MS1 quantification, thus enhancing sensitivity by more efficiently utilizing available mass analyzer time. With our ultra-low input tailored DIA method, we are able to accommodate long injection times and high resolution, while keeping the scan cycle time low enough to ensure robust quantification. Finally, we demonstrate the capability of our approach by profiling mouse embryonic stem cell culture conditions, showcasing heterogeneity in global proteomes and highlighting distinct differences in key metabolic enzyme expression in distinct cell subclusters.
U2 - 10.1038/s41467-023-41602-1
DO - 10.1038/s41467-023-41602-1
M3 - Journal article
C2 - 37737208
SN - 2041-1723
VL - 14
JO - Nature Communications
JF - Nature Communications
M1 - 5910
ER -