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Challenging the Astral™mass analyzer - up to 5300 proteins per single-cell at unseen quantitative accuracy to study cellular heterogeneity

蛋白质组 蛋白质组学 计算生物学 人口 定量蛋白质组学 化学 计算机科学 生物 生物信息学 基因 遗传学 社会学 人口学
作者
Julia A. Bubis,Tabiwang N. Arrey,Eugen Damoc,Bernard Delanghe,Jana Slováková,Theresa Maria Sommer,Harunobu Kagawa,Peter Pichler,Nicolas Rivron,Karl Mechtler,Manuel Matzinger
标识
DOI:10.1101/2024.02.01.578358
摘要

ABSTRACT A detailed proteome map is crucial for understanding molecular pathways and protein functions. Despite significant advancements in sample preparation, instrumentation, and data analysis, single-cell proteomics is currently limited by proteomic depth and quantitative performance. We combine a zero dead-end volume chromatographic column running at high throughput with the Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer running in DIA mode. We demonstrate unprecedented depth of proteome coverage as well as accuracy and precision for quantification of ultra-low input amounts. Using a tailored library, we identify up to 7400 protein groups from as little as 250 pg HeLa at a throughput of 50 samples per day (SPD). We benchmark multiple data analysis strategies, estimate their influence on FDR and show that FDR on protein level can easily be maintained at 1 %. Using a two-proteome mix, we check for optimal parameters of quantification and show that fold change differences of 2 can still be successfully determined at single-cell level inputs. Eventually, we apply our workflow to A549 cells yielding a proteome coverage of up to 5300 protein groups from a single cell, which allows the observation of heterogeneity in a cellular population and studying dependencies between cell size and cell-cycle phase. Additionally, our work-flow enables us to distinguish between in vitro analogs of two human blastocyst lineages: naïve human pluripotent stem cells (epiblast) and trophectoderm (TE)-like cells. Gene Ontology analysis of enriched proteins in TE-like cells harmoniously aligns with transcriptomic data, indicating that single-cell proteomics possesses the capability to identify biologically relevant differences between these two lineages within the blastocyst.
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