Cargando…
High content organelle trafficking enables disease state profiling as powerful tool for disease modelling
Neurodegenerative diseases pose a complex field with various neuronal subtypes and distinct differentially affected intra-neuronal compartments. Modelling of neurodegeneration requires faithful in vitro separation of axons and dendrites, their distal and proximal compartments as well as organelle tr...
Autores principales: | , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group
2018
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233479/ https://www.ncbi.nlm.nih.gov/pubmed/30422121 http://dx.doi.org/10.1038/sdata.2018.241 |
_version_ | 1783370570438541312 |
---|---|
author | Pal, Arun Glaß, Hannes Naumann, Marcel Kreiter, Nicole Japtok, Julia Sczech, Ronny Hermann, Andreas |
author_facet | Pal, Arun Glaß, Hannes Naumann, Marcel Kreiter, Nicole Japtok, Julia Sczech, Ronny Hermann, Andreas |
author_sort | Pal, Arun |
collection | PubMed |
description | Neurodegenerative diseases pose a complex field with various neuronal subtypes and distinct differentially affected intra-neuronal compartments. Modelling of neurodegeneration requires faithful in vitro separation of axons and dendrites, their distal and proximal compartments as well as organelle tracking with defined retrograde versus anterograde directionality. We use microfluidic chambers to achieve compartmentalization and established high throughput live organelle imaging at standardized distal and proximal axonal readout sites in iPSC-derived spinal motor neuron cultures from human amyotrophic lateral sclerosis patients to study trafficking phenotypes of potential disease relevance. Our semi-automated pipeline of organelle tracking with FIJI and KNIME yields quantitative, multiparametric high content phenotypic signatures of organelle morphology and their trafficking in axons. We provide here the resultant large datasets to enable systemic signature interrogations for comprehensive and predictive disease modelling, mechanistic dissection and secondary hit validation (e.g. drug screens, genetic screens). Due to the nearly complete coverage of analysed motility events, our quantitative method yields a bias-free statistical power superior over common analyses of a handful of manual kymographs. |
format | Online Article Text |
id | pubmed-6233479 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2018 |
publisher | Nature Publishing Group |
record_format | MEDLINE/PubMed |
spelling | pubmed-62334792018-11-14 High content organelle trafficking enables disease state profiling as powerful tool for disease modelling Pal, Arun Glaß, Hannes Naumann, Marcel Kreiter, Nicole Japtok, Julia Sczech, Ronny Hermann, Andreas Sci Data Data Descriptor Neurodegenerative diseases pose a complex field with various neuronal subtypes and distinct differentially affected intra-neuronal compartments. Modelling of neurodegeneration requires faithful in vitro separation of axons and dendrites, their distal and proximal compartments as well as organelle tracking with defined retrograde versus anterograde directionality. We use microfluidic chambers to achieve compartmentalization and established high throughput live organelle imaging at standardized distal and proximal axonal readout sites in iPSC-derived spinal motor neuron cultures from human amyotrophic lateral sclerosis patients to study trafficking phenotypes of potential disease relevance. Our semi-automated pipeline of organelle tracking with FIJI and KNIME yields quantitative, multiparametric high content phenotypic signatures of organelle morphology and their trafficking in axons. We provide here the resultant large datasets to enable systemic signature interrogations for comprehensive and predictive disease modelling, mechanistic dissection and secondary hit validation (e.g. drug screens, genetic screens). Due to the nearly complete coverage of analysed motility events, our quantitative method yields a bias-free statistical power superior over common analyses of a handful of manual kymographs. Nature Publishing Group 2018-11-13 /pmc/articles/PMC6233479/ /pubmed/30422121 http://dx.doi.org/10.1038/sdata.2018.241 Text en Copyright © 2018, The Author(s) http://creativecommons.org/licenses/by/4.0/ Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/ The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files made available in this article. |
spellingShingle | Data Descriptor Pal, Arun Glaß, Hannes Naumann, Marcel Kreiter, Nicole Japtok, Julia Sczech, Ronny Hermann, Andreas High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title | High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title_full | High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title_fullStr | High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title_full_unstemmed | High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title_short | High content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
title_sort | high content organelle trafficking enables disease state profiling as powerful tool for disease modelling |
topic | Data Descriptor |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6233479/ https://www.ncbi.nlm.nih.gov/pubmed/30422121 http://dx.doi.org/10.1038/sdata.2018.241 |
work_keys_str_mv | AT palarun highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT glaßhannes highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT naumannmarcel highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT kreiternicole highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT japtokjulia highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT sczechronny highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling AT hermannandreas highcontentorganelletraffickingenablesdiseasestateprofilingaspowerfultoolfordiseasemodelling |