Back

LUCID-EV: a robust and quantitative bioluminescent assay for the detection of EV cytosolic delivery in the absence of VSV-G expression

Merle, L.; Martin-Jaular, L.; Thery, C.; Joliot, A.

2026-03-26 cell biology
10.64898/2026.03.24.713260 bioRxiv
Show abstract

Extracellular vesicles are key intercellular messengers that modulate the function of target cells by carrying effectors, either at their surface or in their lumen. In the latter case, their action depends on the ability to deliver their content into the cytosol of target cells. How efficiently EVs deliver their content upon interaction with their target cell is thus a central question for understanding the functional impact of this mode of action. To address this question, signal-driven bimolecular interactions between two partners located respectively in the EV lumen and the target cell cytosol have become a widely used strategy to detect the cytosolic delivery EV content. However, the detection of cytosolic delivery with these assays was often tributary to the artificial enhancement of the fusion between EV and cell membranes, through for instance VSV-G fusogenic protein expression. Here we provide a robust and quantitative LUCiferase-based complementation assay (HiBiT/LgBiT), to quantify the Internalization and cytosolic Delivery of EV content: LUCID-EV. By optimizing the signal-to-noise ratio of the assay, the method for loading HiBiT fragment into EVs (fusion to a lipid-binding domain rather than to tetraspanins), and the intracellular position of LgBiT (associated to membranes), we could quantify cytosolic delivery from various non-VSV-G-expressing EVs into target immune dendritic cells. Importantly, this delivery did not involve the acidic late endosomes environment required for VSV-G-dependent EV cytosolic delivery. The limited efficacy of the process highlights the need for highly sensitive assays like the one described here. Further development of the LUCID-EV assay could help identifying EV/target cells pairs with enhanced cytosolic delivery properties and characterize the cellular route for delivery.

Matching journals

The top 10 journals account for 50% of the predicted probability mass.

1
Journal of Extracellular Vesicles
50 papers in training set
Top 0.1%
10.1%
2
Cell Reports Methods
141 papers in training set
Top 0.1%
10.1%
3
Scientific Reports
3102 papers in training set
Top 24%
4.9%
4
Cytometry Part A
30 papers in training set
Top 0.1%
4.3%
5
Frontiers in Immunology
586 papers in training set
Top 2%
4.0%
6
Journal of Extracellular Biology
18 papers in training set
Top 0.1%
3.6%
7
Viruses
318 papers in training set
Top 2%
3.6%
8
Analytical Chemistry
205 papers in training set
Top 0.8%
3.6%
9
PLOS ONE
4510 papers in training set
Top 39%
3.6%
10
Journal of Cell Science
353 papers in training set
Top 0.5%
3.6%
50% of probability mass above
11
Small
70 papers in training set
Top 0.2%
2.7%
12
Nature Communications
4913 papers in training set
Top 43%
2.7%
13
ACS Applied Bio Materials
21 papers in training set
Top 0.2%
1.9%
14
iScience
1063 papers in training set
Top 13%
1.8%
15
eLife
5422 papers in training set
Top 42%
1.7%
16
PROTEOMICS
35 papers in training set
Top 0.4%
1.7%
17
Biophysical Journal
545 papers in training set
Top 3%
1.5%
18
Journal of Biological Chemistry
641 papers in training set
Top 2%
1.5%
19
International Journal of Molecular Sciences
453 papers in training set
Top 10%
1.3%
20
Fluids and Barriers of the CNS
21 papers in training set
Top 0.2%
1.2%
21
Frontiers in Cell and Developmental Biology
218 papers in training set
Top 6%
1.2%
22
Nano Letters
63 papers in training set
Top 2%
1.1%
23
Molecular & Cellular Proteomics
158 papers in training set
Top 1%
1.0%
24
Frontiers in Bioengineering and Biotechnology
88 papers in training set
Top 2%
1.0%
25
Journal of Nanobiotechnology
10 papers in training set
Top 0.2%
1.0%
26
Traffic
16 papers in training set
Top 0.1%
0.9%
27
mSphere
281 papers in training set
Top 6%
0.7%
28
Journal of Cell Biology
333 papers in training set
Top 4%
0.7%
29
PLOS Pathogens
721 papers in training set
Top 9%
0.7%
30
Communications Biology
886 papers in training set
Top 26%
0.7%