Evidence map›Paper›PMID 38853953›Full record

ArticlebioRxiv : the preprint server for biology2024

Data Independent Acquisition to Inform the Development of Targeted Proteomics Assays Using a Triple Quadrupole Mass Spectrometer.

Deanna L Plubell, Eric Huang, Sandra E Spencer, Kathleen Poston, Thomas J Montine, Michael J MacCoss

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

6 authors.

Deanna L PlubellUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.
Eric HuangUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.
Sandra E SpencerUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.
Kathleen PostonStanford University, Department of Neurology & Neurological Sciences, Stanford, CA, 94305, USA.ORCID 0000-0003-3424-7143
Thomas J MontineStanford University, Department of Pathology, Stanford, CA, 94305, USA.
Michael J MacCossUniversity of Washington, Department of Genome Sciences, Seattle, WA, 98195, USA.ORCID 0000-0003-1853-0256

Funding

Udall Center Director's meeting poster awardP50NS062684 · NINDS · UNIVERSITY OF WASHINGTON · PI MONTINE, THOMAS J · 2009 to 2020
$18.3M
Project 4: Novel reagent development to enable molecular characterizationU19AG065156 · NIA · UNIVERSITY OF WASHINGTON · PI BAKER, DAVID · 2020 to 2024
$15.9M
Seattle Quant: A Resource for the Skyline Software EcosystemR24GM141156 · NIGMS · UNIVERSITY OF WASHINGTON · PI Michael MacCoss · 2021 to 2026
$6.7M
Quantifying proteins in plasma do democratize personalized medicine for patients with type 1 diabetesU01DK137097 · NIDDK · UNIVERSITY OF WASHINGTON · PI ANDREW N HOOFNAGLE, Michael MacCoss · 2023 to 2026
$3.4M
The ACT annual symposium: a living, learning, national collaboratory to advance Alzheimer's disease and brain aging researchR13AG057087 · NIA · KAISER FOUNDATION RESEARCH INSTITUTE · PI Nicole M. Gatto · 2017 to 2026
$528k
Proteolytic activity profiling of Alzheimer's dementiaF31AG069420 · NIA · UNIVERSITY OF WASHINGTON · PI PLUBELL, DEANNA LISA · 2020 to 2021
$81k
NIA NIH HHS F31 AG069420NIA NIH HHS R13 AG057087NIA NIH HHS U19 AG065156NIDDK NIH HHS U01 DK137097NIGMS NIH HHS R24 GM141156NINDS NIH HHS P50 NS062684
6 · The paper itself

Abstract

Mass spectrometry based targeted proteomics methods provide sensitive and high-throughput analysis of selected proteins. To develop a targeted bottom-up proteomics assay, peptides must be evaluated as proxies for the measurement of a protein or proteoform in a biological matrix. Candidate peptide selection typically relies on predetermined biochemical properties, data from semi-stochastic sampling, or by empirical measurements. These strategies require extensive testing and method refinement due to the difficulties associated with prediction of peptide response in the biological matrix of interest. Gas-phase fractionated (GPF) narrow window data-independent acquisition (DIA) aids in the development of reproducible selected reaction monitoring (SRM) assays by providing matrix-specific information on peptide detectability and quantification by mass spectrometry. To demonstrate the suitability of DIA data for selecting peptide targets, we reimplement a portion of an existing assay to measure 98 Alzheimer's disease proteins in cerebrospinal fluid (CSF). Peptides were selected from GPF-DIA based on signal intensity and reproducibility. The resulting SRM assay exhibits similar quantitative precision to published data, despite the inclusion of different peptides between the assays. This workflow enables development of new assays without additional up-front data acquisition, demonstrated here through generation of a separate assay for an unrelated set of proteins in CSF from the same dataset.

Identifiers

PMID38853953
PMCPMC11160738

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.