Evidence map›Paper›PMID 38889139›Full record

ArticlePloS one2024

Label-free single-vesicle based surface enhanced Raman spectroscopy: A robust approach for investigating the biomolecular composition of small extracellular vesicles.

Zirui Liu, Martin Ng, Siddharth Srivastava, Tieyi Li, Jun Liu, Tuan Anh Phu, Bogdan Mateescu, Yi-Ting Wang, Chia-Feng Tsai, Tao Liu and 2 more

Abstract read
In one paragraph

Article in PloS one, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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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

12 authors.

Zirui LiuDepartment of Materials Science and Engineering, University of California Los Angeles, Los Angeles, California, United States of America.ORCID 0000-0002-2621-7529
Martin NgNorthern California Institute for Research and Education, San Francisco, California, United States of America.
Siddharth SrivastavaDepartment of Materials Science and Engineering, University of California Los Angeles, Los Angeles, California, United States of America.
Tieyi LiDepartment of Materials Science and Engineering, University of California Los Angeles, Los Angeles, California, United States of America.
Jun LiuDepartment of Materials Science and Engineering, University of California Los Angeles, Los Angeles, California, United States of America.
Tuan Anh PhuNorthern California Institute for Research and Education, San Francisco, California, United States of America.
Bogdan MateescuBrain Research Institute, University of Zürich, Zürich, Switzerland.ORCID 0000-0002-0937-352X
Yi-Ting WangBiological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, United States of America.
Chia-Feng TsaiBiological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, United States of America.
Tao LiuBiological Sciences Division, Pacific Northwest National Laboratory, Richland, Washington, United States of America.
Robert L RaffaiDivision of Vascular and Endovascular Surgery, Department of Surgery, University of California San Francisco, San Francisco, California, United States of America.
Ya-Hong XieDepartment of Materials Science and Engineering, University of California Los Angeles, Los Angeles, California, United States of America.ORCID 0000-0003-0971-4280

Funding

AFS/SERS Saliva-based SARS-CoV-2 Earliest Infection and Antibodies DetectionU18TR003778 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI HUANG, TONY JUN, KIM, YONG · 2021 to 2022
$1.8M
Acoustofluidic Separation (AFS), Purification and Raman Spectral Fingerprinting of Single EVs: From Cell of Origin to Target Cell and BiofluidsUH3TR002978 · NCATS · UNIVERSITY OF CALIFORNIA LOS ANGELES · PI GALL, KENNETH A, HUANG, TONY JUN · 2021 to 2022
$1.8M
P.R.I.S.M: Purification of exRNA by Immuno-capture and Sorting using MicrofluidicUG3CA241703 · NCI · NORTHERN CALIFORNIA INSTITUTE/RES/EDU · PI MATEESCU, BOGDAN, RAFFAI, ROBERT · 2019 to 2020
$774k
Exosomes in the Pathogenesis of Diabetic Atherosclerosis & its Treatment OpportunitiesI01BX003928 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI Robert Raffai · 2019 to 2026
–
BLRD Research Career Scientist Award ApplicationIK6BX005692 · VA · VETERANS AFFAIRS MED CTR SAN FRANCISCO · PI RAFFAI, ROBERT · 2021 to 2025
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BLRD VA I01 BX003928BLRD VA IK6 BX005692NCATS NIH HHS U18 TR003778NCATS NIH HHS UH3 TR002978NCI NIH HHS UG3 CA241703
6 · The paper itself

Abstract

Small extracellular vesicles (sEVs) are cell-released vesicles ranging from 30-150nm in size. They have garnered increasing attention because of their potential for both the diagnosis and treatment of disease. The diversity of sEVs derives from their biological composition and cargo content. Currently, the isolation of sEV subpopulations is primarily based on bio-physical and affinity-based approaches. Since a standardized definition for sEV subpopulations is yet to be fully established, it is important to further investigate the correlation between the biomolecular composition of sEVs and their physical properties. In this study, we employed a platform combining single-vesicle surface-enhanced Raman spectroscopy (SERS) and machine learning to examine individual sEVs isolated by size-exclusion chromatography (SEC). The biomolecular composition of each vesicle examined was reflected by its corresponding SERS spectral features (biomolecular "fingerprints"), with their roots in the composition of their collective Raman-active bonds. Origins of the SERS spectral features were validated through a comparative analysis between SERS and mass spectrometry (MS). SERS fingerprinting of individual vesicles was effective in overcoming the challenges posed by EV population averaging, allowing for the possibility of analyzing the variations in biomolecular composition between the vesicles of similar and/or different sizes. Using this approach, we uncovered that each of the size-based fractions of sEVs contained particles with predominantly similar SERS spectral features. Indeed, more than 84% of the vesicles residing within a particular group were clearly distinguishable from that of the other EV sub-populations, despite some spectral variations within each sub-population. Our results suggest the possibility that size-based EV fractionation methods produce samples where similarly eluted sEVs are correlated with their respective biochemical contents, as reflected by their SERS spectra. Our findings therefore highlight the possibility that the biogenesis and respective biological functionalities of the various sEV fractions may be inherently different.

Indexed as

Extracellular VesiclesSpectrum Analysis, RamanChromatography, GelHumansMachine LearningMass Spectrometry

Identifiers

PMID38889139
PMCPMC11185487

What OpenQuestion holds

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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.