Evidence map›Paper›PMID 36329610›Full record

ArticleJournal of extracellular vesicles2022

Characterizing single extracellular vesicles by droplet barcode sequencing for protein analysis.

Mahsan Banijamali, Pontus Höjer, Abel Nagy, Petra Hååg, Elizabeth Paz Gomero, Christiane Stiller, Vitaliy O Kaminskyy, Simon Ekman, Rolf Lewensohn, Amelie Eriksson Karlström and 2 more

Open access · goldAbstract read
In one paragraph

Article in Journal of extracellular vesicles, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing papers in PubMed
3.3field-weighted citation impact, top 6% of its field
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

27 citing papers in PubMed, 42 citations in OpenAlex.

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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 at 5 institutions in 1 country.

Mahsan BanijamaliRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, Science for Life Laboratory, Solna, Sweden.
Pontus HöjerRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, Science for Life Laboratory, Solna, Sweden.
Abel NagyRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Protein Science, AlbaNova University Center, Stockholm, Sweden.
Petra HåågDepartment of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Elizabeth Paz GomeroRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Protein Science, AlbaNova University Center, Stockholm, Sweden.
Christiane StillerRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Protein Science, AlbaNova University Center, Stockholm, Sweden.
Vitaliy O KaminskyyDepartment of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Simon EkmanDepartment of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Rolf LewensohnDepartment of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Amelie Eriksson KarlströmRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Protein Science, AlbaNova University Center, Stockholm, Sweden.
Kristina ViktorssonDepartment of Oncology-Pathology, Karolinska Institutet, Solna, Sweden.
Afshin AhmadianRoyal Institute of Technology (KTH), School of Engineering Sciences in Chemistry, Biotechnology and Health, Department of Gene Technology, Science for Life Laboratory, Solna, Sweden.
KTH Royal Institute of Technology · SEKarolinska Institutet · SEKarolinska University Hospital · SEAlbaNova · SEScience for Life Laboratory · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Small extracellular vesicles (sEVs) have in recent years evolved as a source of biomarkers for disease diagnosis and therapeutic follow up. sEV samples derived from multicellular organisms exhibit a high heterogeneous repertoire of vesicles which current methods based on ensemble measurements cannot capture. In this work we present droplet barcode sequencing for protein analysis (DBS-Pro) to profile surface proteins on individual sEVs, facilitating identification of sEV-subtypes within and between samples. The method allows for analysis of multiple proteins through use of DNA barcoded affinity reagents and sequencing as readout. High throughput single vesicle profiling is enabled through compartmentalization of individual sEVs in emulsion droplets followed by droplet barcoding through PCR. In this proof-of-concept study we demonstrate that DBS-Pro allows for analysis of single sEVs, with a mixing rate below 2%. A total of over 120,000 individual sEVs obtained from a NSCLC cell line and from malignant pleural effusion (MPE) fluid of NSCLC patients have been analyzed based on their surface proteins. We also show that the method enables single vesicle surface protein profiling and by extension characterization of sEV-subtypes, which is essential to identify the cellular origin of vesicles in heterogenous samples.

Indexed as

Extracellular VesiclesBiomarkersCell LineHumansMembrane ProteinsBiomarkersMembrane Proteinsdroplet barcode sequencing (DBS)droplet barcode sequencing for protein analysis (DBS-Pro)protein profilingsEV subtypessingle vesiclesmall extracellular vesicles (sEVs)surface protein

Identifiers

PMID36329610
PMCPMC9633998
OpenAlexW4308327559

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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 OpenQuestion graph.