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  • P-III-0950

Deep proteomic characterization of more than 120 cell lines

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Cell Biology Insights

Poster

Deep proteomic characterization of more than 120 cell lines

Thema

  • Cell Biology Insights

Mitwirkende

Johanna Wallner (Freising / DE), Alexander Betz (Freising / DE), Janine Sequeira (Freising / DE), Theresa Keil (Freising / DE), Jan Muntel (Freising / DE), Götz Hagemann (Freising / DE), Stephan Sieber (Garching / DE), Hannes Hahne (Freising / DE)

Abstract

Biomedical research heavily relies on the indispensable utility of cell lines. Due to their ease
of handling, widespread availability, and facilitation of straightforward investigations into
diverse treatments, cell lines play a crucial role in exploring the mechanisms of action during
drug development. To ensure the efficacy of such studies, a profound characterization of cell
lines becomes imperative, aiding in the selection of the most appropriate cell line for a
specific drug.
In our comprehensive study, we conducted a deep proteomic characterization encompassing
over 120 distinct cell lines originating from six different organisms. Employing a semi-
automated workflow, all samples were processed with a KingFisher Apex robot and
subsequently subjected to 2-hour data-independent acquisition (DIA) runs utilizing cutting-
edge LC-MS/MS systems, including the Vanquish Neo UHPLC System, Orbitrap Eclipse
Tribrid Mass Spectrometer, and Orbitrap Exploris480 Mass Spectrometer from Thermo
Fisher Scientific. Additionally, 12 cell lines underwent an extensive characterization
involving six gas-phase fractions (GPF).
In human cell lines, single-shot DIA measurements yielded an average identification of more
than 8,000 unique proteins. The implementation of GPF increased this number, resulting in
the identification of over 10,000 unique protein groups. Mouse cell lines exhibited an average
identification of 7,500 proteins, while rat cell lines displayed an identification of 8,100
proteins.
A key focus of our analysis was the expression profiling of different kinase groups within the
characterized dataset. Human cell lines consistently exhibited the unique identification of 300
to 436 kinases, with 140 to 220 falling under the category of E3 ubiquitin ligases.
Additionally, we identified 40 to 78 proteins belonging to the dark kinome. This rich dataset
empowers researchers to make informed decisions regarding the selection of optimal cell
lines tailored to specific research inquiries.
In summary, our extensive proteomic characterization of diverse cell lines provides a
valuable resource for the scientific community, facilitating the identification of suitable cell
lines for a myriad of research questions and enhancing the understanding of cellular
responses to various treatments in the context of drug development.

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