Dataset Information

15 cm Aurora Gen3 column benchmarking on an Exploris 480

ABSTRACT: A comprehensive proteome map is essential to elucidate molecular pathways and protein functions. Although great improvements in sample preparation, instrumentation and data analysis already yield-ed impressive results, current studies suffer from a limited proteomic depth and dynamic range there-fore lacking low abundant or highly hydrophobic proteins. Here, we combine and benchmark advanced micro pillar array columns (µPAC) operated at nanoflow with Wide Window Acquisition (WWA) and the AI-based CHIMERYS search engine for data analysis to maximize chromatographic separation power, sensitivity and proteome coverage. Our data shows that µPAC columns clearly outperform classical packed bed columns boosting peptide IDs by up to 50% and protein IDs by up to 24%. Using the above-mentioned analysis platform, more than 10,000 proteins could be identified from a single 2 h gradient shotgun analysis for a triple proteome mix of human, yeast and E. coli digests. At high sample loads of 400 ng all three uPAC types yielded comparable number of protein identifications, whereas the 50cm neo column performed best when lower inputs of less than 200 ng were injected. This additional dataset comprises additional data generated with the Aurora Elite G3 column (150 mm x 75 µm, 1.7 µm, IonOpticks) for comparison to the aforementioned µPAC technology.

INSTRUMENT(S): Orbitrap Exploris 480

ORGANISM(S): Homo Sapiens (human)

TISSUE(S): Cell Culture, Lymphoblast

SUBMITTER: Rupert Mayer

LAB HEAD: Karl Mechtler

PROVIDER: PXD045457 | Pride | 2024-02-13

REPOSITORIES: Pride

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Dataset's files

Source:

			Action	DRS
	20230811_E0_NEO6_FAIMS_15cmAUR3_pepmapTrap_QC4L_2c3kV_01.pdResult	Other
	20230811_E0_NEO6_FAIMS_15cmAUR3_pepmapTrap_QC4L_2c3kV_01.raw	Raw
	20230811_E0_NEO6_FAIMS_15cmAUR3_pepmapTrap_QC4L_2c3kV_02.pdResult	Other
	20230811_E0_NEO6_FAIMS_15cmAUR3_pepmapTrap_QC4L_2c3kV_02.raw	Raw
	20230811_E0_NEO6_FAIMS_15cmAUR3_pepmapTrap_QC4L_2c3kV_03.pdResult	Other

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Publications

Micropillar arrays, wide window acquisition and AI-based data analysis improve comprehensiveness in multiple proteomic applications.

Matzinger Manuel M Schmücker Anna A Yelagandula Ramesh R Stejskal Karel K Krššáková Gabriela G Berger Frédéric F Mechtler Karl K Mayer Rupert L RL

Nature communications 20240203 1

Comprehensive proteomic analysis is essential to elucidate molecular pathways and protein functions. Despite tremendous progress in proteomics, current studies still suffer from limited proteomic coverage and dynamic range. Here, we utilize micropillar array columns (µPACs) together with wide-window acquisition and the AI-based CHIMERYS search engine to achieve excellent proteomic comprehensiveness for bulk proteomics, affinity purification mass spectrometry and single cell proteomics. Our data ...[more]

PMID: 38310095

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