Cargando…

High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production

Outer membrane vesicles (OMVs) are spherical membrane nanoparticles released by Gram-negative bacteria. OMVs can be quantified in complex matrices by nanoparticle tracking analysis (NTA). NTA can be performed in static mode or with continuous sample flow that results in analysis of more particles in...

Descripción completa

Detalles Bibliográficos
Autores principales: Gerritzen, Matthias J. H., Martens, Dirk E., Wijffels, René H., Stork, Michiel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Taylor & Francis 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505008/
https://www.ncbi.nlm.nih.gov/pubmed/28717425
http://dx.doi.org/10.1080/20013078.2017.1333883
_version_ 1783249396217937920
author Gerritzen, Matthias J. H.
Martens, Dirk E.
Wijffels, René H.
Stork, Michiel
author_facet Gerritzen, Matthias J. H.
Martens, Dirk E.
Wijffels, René H.
Stork, Michiel
author_sort Gerritzen, Matthias J. H.
collection PubMed
description Outer membrane vesicles (OMVs) are spherical membrane nanoparticles released by Gram-negative bacteria. OMVs can be quantified in complex matrices by nanoparticle tracking analysis (NTA). NTA can be performed in static mode or with continuous sample flow that results in analysis of more particles in a smaller time-frame. Flow measurements must be performed manually despite the availability of a sample changer on the NanoSight system. Here we present a method for automated measurements in flow mode. OMV quantification in flow mode results in lower variance in particle quantification (coefficient of variation (CV) of 6%, CV static measurements of 14%). Sizing of OMVs was expected to be less favorable in flow mode due to the increased movement of the particles. However, we observed a CV of 3% in flow mode and a CV of 8% in static measurements. Flow rates of up to 5 µL/min displayed correct size and particle measurements, however, particle concentration was slightly lower than in static measurements. The automated method was used to assess OMV release of batch cultures of Neisseria meningitidis. The bacteria released more OMVs in stationary growth phase, while the size of the vesicles remained constant throughout the culture. Taken together, this study shows that automated measurements in flow mode can be established with advanced scripting to reduce the workload for the user.
format Online
Article
Text
id pubmed-5505008
institution National Center for Biotechnology Information
language English
publishDate 2017
publisher Taylor & Francis
record_format MEDLINE/PubMed
spelling pubmed-55050082017-07-17 High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production Gerritzen, Matthias J. H. Martens, Dirk E. Wijffels, René H. Stork, Michiel J Extracell Vesicles Research Article Outer membrane vesicles (OMVs) are spherical membrane nanoparticles released by Gram-negative bacteria. OMVs can be quantified in complex matrices by nanoparticle tracking analysis (NTA). NTA can be performed in static mode or with continuous sample flow that results in analysis of more particles in a smaller time-frame. Flow measurements must be performed manually despite the availability of a sample changer on the NanoSight system. Here we present a method for automated measurements in flow mode. OMV quantification in flow mode results in lower variance in particle quantification (coefficient of variation (CV) of 6%, CV static measurements of 14%). Sizing of OMVs was expected to be less favorable in flow mode due to the increased movement of the particles. However, we observed a CV of 3% in flow mode and a CV of 8% in static measurements. Flow rates of up to 5 µL/min displayed correct size and particle measurements, however, particle concentration was slightly lower than in static measurements. The automated method was used to assess OMV release of batch cultures of Neisseria meningitidis. The bacteria released more OMVs in stationary growth phase, while the size of the vesicles remained constant throughout the culture. Taken together, this study shows that automated measurements in flow mode can be established with advanced scripting to reduce the workload for the user. Taylor & Francis 2017-06-19 /pmc/articles/PMC5505008/ /pubmed/28717425 http://dx.doi.org/10.1080/20013078.2017.1333883 Text en © 2017 Intravacc, part of the Ministry of Health Welfare and Sports http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution-NonCommercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Article
Gerritzen, Matthias J. H.
Martens, Dirk E.
Wijffels, René H.
Stork, Michiel
High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title_full High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title_fullStr High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title_full_unstemmed High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title_short High throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
title_sort high throughput nanoparticle tracking analysis for monitoring outer membrane vesicle production
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5505008/
https://www.ncbi.nlm.nih.gov/pubmed/28717425
http://dx.doi.org/10.1080/20013078.2017.1333883
work_keys_str_mv AT gerritzenmatthiasjh highthroughputnanoparticletrackinganalysisformonitoringoutermembranevesicleproduction
AT martensdirke highthroughputnanoparticletrackinganalysisformonitoringoutermembranevesicleproduction
AT wijffelsreneh highthroughputnanoparticletrackinganalysisformonitoringoutermembranevesicleproduction
AT storkmichiel highthroughputnanoparticletrackinganalysisformonitoringoutermembranevesicleproduction