Evaluating the Performance of the Astral Mass Analyzer for Quantitative Proteomics Using Data Independent Acquisition.


Journal

bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187

Informations de publication

Date de publication:
07 Aug 2023
Historique:
pubmed: 3 7 2023
medline: 3 7 2023
entrez: 3 7 2023
Statut: epublish

Résumé

We evaluate the quantitative performance of the newly released Asymmetric Track Lossless (Astral) analyzer. Using data independent acquisition, the Thermo Scientific™ Orbitrap™ Astral™ mass spectrometer quantifies 5 times more peptides per unit time than state-of-the-art Thermo Scientific™ Orbitrap™ mass spectrometers, which have long been the gold standard for high resolution quantitative proteomics. Our results demonstrate that the Orbitrap Astral mass spectrometer can produce high quality quantitative measurements across a wide dynamic range. We also use a newly developed extra-cellular vesicle enrichment protocol to reach new depths of coverage in the plasma proteome, quantifying over 5,000 plasma proteins in a 60-minute gradient with the Orbitrap Astral mass spectrometer.

Identifiants

pubmed: 37398334
doi: 10.1101/2023.06.03.543570
pmc: PMC10312564
pii:
doi:

Types de publication

Preprint

Langues

eng

Commentaires et corrections

Type : UpdateIn

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Auteurs

Lilian R Heil (LR)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Eugen Damoc (E)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Tabiwang N Arrey (TN)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Anna Pashkova (A)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Eduard Denisov (E)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Johannes Petzoldt (J)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Amelia C Peterson (AC)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Chris Hsu (C)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Brian C Searle (BC)

Pelotonia Institute for Immuno-Oncology, The Ohio State University Comprehensive Cancer Center, Columbus, Ohio 43210, United States.
Department of Biomedical Informatics, The Ohio State University, Columbus, Ohio 43210, United States.

Nicholas Shulman (N)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Michael Riffle (M)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Brian Connolly (B)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Brendan X MacLean (BX)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Philip M Remes (PM)

Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States.

Michael W Senko (MW)

Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States.

Hamish I Stewart (HI)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Christian Hock (C)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Alexander A Makarov (AA)

Thermo Fisher Scientific, Hanna-Kunath Ste. 11, 28199 Bremen, Germany.

Daniel Hermanson (D)

Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States.

Vlad Zabrouskov (V)

Thermo Fisher Scientific, 355 River Oaks Parkway, San Jose, California 95134, United States.

Christine C Wu (CC)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Michael J MacCoss (MJ)

Department of Genome Sciences, University of Washington, 3720 15th Street NE, Seattle, Washington 98195, United States.

Classifications MeSH