Comparison of Methods for Quantifying Extracellular Vesicles of Gram-Negative Bacteria.

FM 4-64 NTA NanoOrange Qubit bacterial extracellular vesicle microBCA nanoparticle tracking analysis outer membrane vesicles vesicle quantification

Journal

International journal of molecular sciences
ISSN: 1422-0067
Titre abrégé: Int J Mol Sci
Pays: Switzerland
ID NLM: 101092791

Informations de publication

Date de publication:
11 Oct 2023
Historique:
received: 09 09 2023
revised: 04 10 2023
accepted: 09 10 2023
medline: 30 10 2023
pubmed: 28 10 2023
entrez: 28 10 2023
Statut: epublish

Résumé

There are a variety of methods employed by laboratories for quantifying extracellular vesicles isolated from bacteria. As a result, the ability to compare results across published studies can lead to questions regarding the suitability of methods and buffers for accurately quantifying these vesicles. Within the literature, there are several common methods for vesicle quantification. These include lipid quantification using the lipophilic dye FM 4-64, protein quantification using microBCA, Qubit, and NanoOrange assays, or direct vesicle enumeration using nanoparticle tracking analysis. In addition, various diluents and lysis buffers are also used to resuspend and treat vesicles. In this study, we directly compared the quantification of a bacterial outer membrane vesicle using several commonly used methods. We also tested the impact of different buffers, buffer age, lysis method, and vesicle diluent on vesicle quantification. The results showed that buffer age had no significant effect on vesicle quantification, but the lysis method impacted the reliability of measurements using Qubit and NanoOrange. The microBCA assay displayed the least variability in protein concentration values and was the most consistent, regardless of the buffer or diluent used. MicroBCA also demonstrated the strongest correlation to the NTA-determined particle number across a range of vesicle concentrations. Overall, these results indicate that with appropriate diluent and buffer choice, microBCA vs. NTA standard curves could be generated and the microBCA assay used to estimate the particle number when NTA instrumentation is not readily available.

Identifiants

pubmed: 37894776
pii: ijms242015096
doi: 10.3390/ijms242015096
pmc: PMC10606555
pii:
doi:

Substances chimiques

NanoOrange 0
Organic Chemicals 0

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : National Institutes of Health Clinical Center
ID : R21AI140012
Organisme : USDA National Institute of Food and Agriculture, Research Capacity Fund
ID : 7004422

Déclaration de conflit d'intérêts

The authors declare no conflict of interest.

Références

Int J Mol Sci. 2022 Jul 02;23(13):
pubmed: 35806397
J Extracell Vesicles. 2019 Apr 01;8(1):1596016
pubmed: 30988894
J Proteomics. 2021 Jan 16;231:103994
pubmed: 33007464
Proteomics. 2019 Jan;19(1-2):e1800209
pubmed: 30488570
Microb Cell Fact. 2018 Oct 3;17(1):157
pubmed: 30285743
Biomed Opt Express. 2016 Aug 29;7(9):3736-3746
pubmed: 27699134
J Extracell Vesicles. 2017 Jun 19;6(1):1333883
pubmed: 28717425
Front Microbiol. 2020 Feb 06;11:57
pubmed: 32117106
PLoS One. 2011;6(11):e27958
pubmed: 22114730
Biotechniques. 2003 Apr;34(4):850-4, 856, 858 passim
pubmed: 12703310
Front Immunol. 2021 Dec 17;12:781280
pubmed: 34987509
Cell. 2003 Oct 3;115(1):25-35
pubmed: 14532000
Mol Cell Proteomics. 2018 Feb;17(2):205-215
pubmed: 29203497
Biochem Soc Trans. 2018 Oct 19;46(5):1021-1027
pubmed: 30154095
Annu Rev Microbiol. 2010;64:163-84
pubmed: 20825345
Cell. 2020 Jul 9;182(1):262-262.e1
pubmed: 32649878
J Innate Immun. 2019;11(4):316-329
pubmed: 30844806
BMC Microbiol. 2011 Dec 01;11:258
pubmed: 22133164
J Extracell Vesicles. 2022 Jan;11(1):e12172
pubmed: 34981901
J Vis Exp. 2021 Mar 28;(169):
pubmed: 33843938
Front Microbiol. 2021 Mar 05;12:628801
pubmed: 33746922
Microbiol Mol Biol Rev. 2010 Mar;74(1):81-94
pubmed: 20197500
Nat Rev Microbiol. 2015 Oct;13(10):605-19
pubmed: 26373371
Front Immunol. 2022 Aug 04;13:909949
pubmed: 35990695
Wiley Interdiscip Rev Nanomed Nanobiotechnol. 2023 Jan;15(1):e1835
pubmed: 35898167
Nat Rev Microbiol. 2019 Jan;17(1):13-24
pubmed: 30397270
Microbiol Spectr. 2022 Aug 31;10(4):e0026222
pubmed: 35852325
Sci Rep. 2018 Jun 11;8(1):8812
pubmed: 29891956
Int J Mol Sci. 2022 Dec 13;23(24):
pubmed: 36555442
Microbiol Spectr. 2022 Feb 23;10(1):e0063421
pubmed: 35080445
Anal Biochem. 1985 Oct;150(1):76-85
pubmed: 3843705
J Extracell Vesicles. 2018 Nov 23;7(1):1535750
pubmed: 30637094
Cell Microbiol. 2016 Apr;18(4):488-99
pubmed: 26399913
Front Microbiol. 2020 Jan 17;10:3026
pubmed: 32038523
Sci Total Environ. 2022 Feb 1;806(Pt 4):151403
pubmed: 34742801
Sci Rep. 2015 Oct 20;5:15329
pubmed: 26483327
J Infect Dis. 2022 Feb 15;225(4):650-660
pubmed: 34498079
Microbiol Spectr. 2023 Mar 21;:e0469122
pubmed: 36943087
Res Microbiol. 2017 Jun;168(5):413-418
pubmed: 28263904
Infect Immun. 2023 May 16;91(5):e0043922
pubmed: 37097158

Auteurs

Chanel A Mosby (CA)

Microbiology and Cell Science Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA.

Natalia Perez Devia (N)

Microbiology and Cell Science Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA.

Melissa K Jones (MK)

Microbiology and Cell Science Department, Institute of Food and Agricultural Sciences, University of Florida, Gainesville, FL 32611, USA.

Articles similaires

Humans Middle Aged Female Male Surveys and Questionnaires
Adolescent Child Female Humans Male
Humans Scoliosis Mobile Applications Retrospective Studies Artificial Intelligence

Classifications MeSH