Published March 2, 2020 | Version v1
Journal article Open

Variability in protein cargo detection in technical and biological replicates of exosome-enriched extracellular vesicles

  • 1. University of Chicago
  • 2. University of Michigan

Description

Exosomes are extracellular vesicles (EVs) of ~20–200 nm diameter that shuttle DNAs, RNAs, proteins and other biomolecules between cells. The large number of biomolecules present in exosomes demands the frequent use of high-throughput analysis. This, in turn, requires technical replicates (TRs), and biological replicates (BRs) to produce accurate results. As the number and abundance of identified biomolecules varies between replicates (Rs), establishing the replicate variability predicted for the event under study is essential in determining the number of Rs required. Although there have been few reports of replicate variability in high throughput biological data, none of them focused on exosomes. Herein, we determined the replicate variability in protein profiles found in exosomes released from 3 lung adenocarcinoma cell lines, H1993, A549 and H1975. Since exosome isolates are invariably contaminated by a small percentage of ~200–300 nm microvesicles, we refer to our samples as exosome-enriched EVs (EE-EVs). We generated BRs of EE-EVs from each cell line, and divided each group into 3 TRs. All Rs were analyzed by liquid chromatography/mass spectrometry (LC/MS/MS) and customized bioinformatics and biostatistical workflows (raw data available via ProteomeXchange: PXD012798). We found that the variability among TRs as well as BRs, was largely qualitative (protein present or absent) and higher among BRs. By contrast, the quantitative (protein abundance) variability was low, save for the H1975 cell line where the quantitative variability was significant. Importantly, our replicate strategy identified 90% of the most abundant proteins, thereby establishing the utility of our approach.

Data availability

All mass spectrometry proteomics data files are available from the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD012798 and 10.6019/PXD012798

Files

journal.pone.0228871.pdf

Files (5.7 MB)

Name Size Download all
Article
md5:2d3cb7c5154077292ba1db704d833559
2.6 MB Preview Download
md5:9850370997d16fb5db61395aa9b6f1a8
2.8 MB Preview Download
md5:ae0d37cabc03d622a718a7012e0988f8
279.6 kB Preview Download

Additional details

Identifiers

DOI
10.1371/journal.pone.0228871
Other
oai:uchicago.tind.io:6251

Funding

National Institutes of Health
R01 HL132870
National Institutes of Health
R01 HL128228

UChicago Information

Division(s)
Biological Sciences Division
Department(s)
Pathology
Center(s) or Institute(s)
Center for Research Informatics