Article ; Online: Multi-marker profiling of extracellular vesicles using streaming current and sequential electrostatic labeling.
2023 Volume 227, Page(s) 115142
Abstract: High heterogeneity in the membrane protein expression of small extracellular vesicles (sEVs) means that bulk methods relying on antibody-based capture for expression analysis have a drawback that each type of antibody may capture a different sub- ... ...
Abstract | High heterogeneity in the membrane protein expression of small extracellular vesicles (sEVs) means that bulk methods relying on antibody-based capture for expression analysis have a drawback that each type of antibody may capture a different sub-population. An improved approach is to capture a representative sEV population, without any bias, and then perform a multiplexed protein expression analysis on this population. However, such a possibility has been largely limited to fluorescence-based methods. Here, we present a novel electrostatic labelling strategy and a microchip-based all-electric method for membrane protein analysis of sEVs. The method allows us to profile multiple surface proteins on the captured sEVs using alternating charge labels. It also permits the comparison of expression levels in different sEV-subtypes. The proof of concept was tested by capturing sEVs both non-specifically (unbiased) as well as via anti-CD9 capture probes (biased), and then profiling the expression levels of various surface proteins using the charge labelled antibodies. The method is the first of its kind, demonstrating an all-electrical and microchip based method that allows for unbiased analysis of sEV membrane protein expression, comparison of expression levels in different sEV subsets, and fractional estimation of different sEV sub-populations. These results were also validated in parallel using a single-sEV fluorescence technique. |
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MeSH term(s) | Static Electricity ; Biosensing Techniques ; Extracellular Vesicles ; Electricity ; Antibodies ; Membrane Proteins |
Chemical Substances | Antibodies ; Membrane Proteins |
Language | English |
Publishing date | 2023-02-09 |
Publishing country | England |
Document type | Journal Article |
ZDB-ID | 1011023-9 |
ISSN | 1873-4235 ; 0956-5663 |
ISSN (online) | 1873-4235 |
ISSN | 0956-5663 |
DOI | 10.1016/j.bios.2023.115142 |
Database | MEDical Literature Analysis and Retrieval System OnLINE |
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