Evidence map›Paper›PMID 35793413›Full record

ArticleJournal of proteome research2022

Protein Contaminants Matter: Building Universal Protein Contaminant Libraries for DDA and DIA Proteomics.

Ashley M Frankenfield, Jiawei Ni, Mustafa Ahmed, Ling Hao

Abstract read
In one paragraph

Article in Journal of proteome research, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 168 papers.

0numbers the graph read from it
0cells of the map it votes in
168citing 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

168 citing papers in PubMed.

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  7. Urban PMMolecular neurobiology · 2026
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  10. Palaeoproteomic Deconvolution of Physical and Genetic Collagen Mixtures.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026
    Article
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108 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ashley M FrankenfieldDepartment of Chemistry, The George Washington University, Science and Engineering Hall 4000, 800, 22nd St., Northwest, Washington, DC 20052, United States.
Jiawei NiDepartment of Chemistry, The George Washington University, Science and Engineering Hall 4000, 800, 22nd St., Northwest, Washington, DC 20052, United States.
Mustafa AhmedDepartment of Chemistry, The George Washington University, Science and Engineering Hall 4000, 800, 22nd St., Northwest, Washington, DC 20052, United States.
Ling HaoDepartment of Chemistry, The George Washington University, Science and Engineering Hall 4000, 800, 22nd St., Northwest, Washington, DC 20052, United States.ORCID 0000-0002-0106-5266

Funding

Development of Mass Spectrometry Strategies to Decipher Dynamic Lysosomal Dysfunctions in Frontotemporal DementiaR01NS121608 · NINDS · UNIV OF MARYLAND, COLLEGE PARK · PI Ling Hao · 2021 to 2026
$2.0M
NINDS NIH HHS R01 NS121608
6 · The paper itself

Abstract

Mass spectrometry-based proteomics is constantly challenged by the presence of contaminant background signals. In particular, protein contaminants from reagents and sample handling are almost impossible to avoid. For data-dependent acquisition (DDA) proteomics, an exclusion list can be used to reduce the influence of protein contaminants. However, protein contamination has not been evaluated and is rarely addressed in data-independent acquisition (DIA). How protein contaminants influence proteomic data is also unclear. In this study, we established new protein contaminant FASTA and spectral libraries that are applicable to all proteomic workflows and evaluated the impact of protein contaminants on both DDA and DIA proteomics. We demonstrated that including our contaminant libraries can reduce false discoveries and increase protein identifications, without influencing the quantification accuracy in various proteomic software platforms. With the pressing need to standardize proteomic workflow in the research community, we highly recommend including our contaminant FASTA and spectral libraries in all bottom-up proteomic data analysis. Our contaminant libraries and a step-by-step tutorial to incorporate these libraries in various DDA and DIA data analysis platforms can be valuable resources for proteomic researchers, freely accessible at https://github.com/HaoGroup-ProtContLib.

Indexed as

ProteomeProteomicsMass SpectrometrySoftwareProteomecontaminationDDADIADIA-NNFASTAkeratinprotein contaminantspectral librarySpectronauttrypsin

Identifiers

PMID35793413
PMCPMC10040255

What Socratic holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

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 Socratic graph.