Evidence map›Paper›PMID 38496642›Full record

ArticlebioRxiv : the preprint server for biology2024

Deep Plasma Proteome Profiling by Modulating Single Nanoparticle Protein Corona with Small Molecules.

Ali Akbar Ashkarran, Hassan Gharibi, Seyed Amirhossein Sadeghi, Seyed Majed Modaresi, Qianyi Wang, Teng-Jui Lin, Ghafar Yerima, Ali Tamadon, Maryam Sayadi, Maryam Jafari and 9 more

Open access · greenAbstract readPreprint
PubMed Full text at PMC Publisher
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, 6 citations in OpenAlex.

No citing paper in PubMed yet.

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

19 authors at 7 institutions in 3 countries.

Ali Akbar AshkarranDepartment of Radiology and Precision Health Program, Michigan State University, East Lansing, MI 48824, USA.
Hassan GharibiDivision of Chemistry I, Department of Medical Biochemistry and Biophysics, Karolinska Institutet, Stockholm, Sweden.
Seyed Amirhossein SadeghiDepartment of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, MI 48824, United States.
Seyed Majed ModaresiBiozentrum, University of Basel, 4056 Basel, Switzerland.
Qianyi WangDepartment of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, MI 48824, United States.
Teng-Jui LinDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.
Ghafar YerimaMolecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California Berkeley, Berkeley, CA 94720, USA.
Ali TamadonMolecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California Berkeley, Berkeley, CA 94720, USA.
Maryam SayadiDepartment of Biomedical Engineering, Michigan State University, East Lansing, MI 48824, USA.
Maryam JafariDivision of ENT Diseases, Department of Clinical Science, Intervention and Technology, Karolinska Institutet, Stockholm, Sweden.
Zijin LinDepartment of Radiology and Precision Health Program, Michigan State University, East Lansing, MI 48824, USA.
Danilo RitzProteomics Core Facility, Biozentrum, University of Basel, 4056 Basel, Switzerland.
David KakhniashviliProteomics and Metabolomics Core Facility, University of Tennessee Health Science Center, Memphis, TN, USA.
Avirup GuhaCardio-Oncology Program, Medical College of Georgia at Augusta University, Augusta, GA 30912, USA.
Mohammad R K MofradMolecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California Berkeley, Berkeley, CA 94720, USA.ORCID 0000-0001-7004-4859
Liangliang SunDepartment of Chemistry, Michigan State University, 578 South Shaw Lane, East Lansing, MI 48824, United States.
Markita P LandryDepartment of Chemical and Biomolecular Engineering, University of California, Berkeley, Berkeley, CA 94720, USA.
Amir Ata SaeiBiozentrum, University of Basel, 4056 Basel, Switzerland.
Morteza MahmoudiDepartment of Radiology and Precision Health Program, Michigan State University, East Lansing, MI 48824, USA.ORCID 0000-0002-2575-9684
Michigan State University · USUniversity of Basel · CHKarolinska Institutet · SEUniversity of California, Berkeley · USAugusta University · USChan Zuckerberg Initiative (United States) · USUniversity of Tennessee Health Science Center · US

Funding

A Nanostructured Skin Patch to Heal Chronic WoundsR01DK131417 · NIDDK · MICHIGAN STATE UNIVERSITY · PI Morteza Mahmoudi · 2022 to 2026
$2.0M
Quantitative top-down proteomics of human colorectal cancer cells and tumorsR01CA247863 · NCI · MICHIGAN STATE UNIVERSITY · PI HUMMON, AMANDA B., LIU, XIAOWEN · 2021 to 2025
$1.9M
NCI NIH HHS R01 CA247863NIDDK NIH HHS R01 DK131417
6 · The paper itself

Abstract

The protein corona, a dynamic biomolecular layer that forms on nanoparticle (NP) surfaces upon exposure to biological fluids is emerging as a valuable diagnostic tool for improving plasma proteome coverage analyzed by liquid chromatography-mass spectrometry (LC-MS/MS). Here, we show that spiking small molecules, including metabolites, lipids, vitamins, and nutrients (namely, glucose, triglyceride, diglycerol, phosphatidylcholine, phosphatidylethanolamine, L-α-phosphatidylinositol, inosine 5'-monophosphate, and B complex), into plasma can induce diverse protein corona patterns on otherwise identical NPs, significantly enhancing the depth of plasma proteome profiling. The protein coronas on polystyrene NPs when exposed to plasma treated with an array of small molecules (n=10) allowed for detection of 1793 proteins marking an 8.25-fold increase in the number of quantified proteins compared to plasma alone (218 proteins) and a 2.63-fold increase relative to the untreated protein corona (681 proteins). Furthermore, we discovered that adding 1000 μg/ml phosphatidylcholine could singularly enable the detection of 897 proteins. At this specific concentration, phosphatidylcholine selectively depleted the four most abundant plasma proteins, including albumin, thus reducing the dynamic range of plasma proteome and enabling the detection of proteins with lower abundance. By employing an optimized data-independent acquisition (DIA) approach, the inclusion of phosphatidylcholine led to the detection of 1436 proteins in a single plasma sample. Our molecular dynamic results revealed that phosphatidylcholine interacts with albumin via hydrophobic interactions, h-bonds, and water-bridges. Addition of phosphatidylcholine also enabled the detection of 337 additional proteoforms compared to untreated protein corona using a top-down proteomics approach. These significant achievements are made utilizing only a single NP type and one small molecule to analyze a single plasma sample, setting a new standard in plasma proteome profiling. Given the critical role of plasma proteomics in biomarker discovery and disease monitoring, we anticipate widespread adoption of this methodology for identification and clinical translation of proteomic biomarkers into FDA approved diagnostics.

Identifiers

PMID38496642
PMCPMC10942461
OpenAlexW4392630712

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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Registered trials

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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.