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.

N1 - Publisher Copyright: © 2023, Springer Nature Limited.

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

AN - SCOPUS:85171890083

VL - 14

JO - Nature Communications

JF - Nature Communications

SN - 2041-1723

M1 - 5910

ER -