Cargando…

A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors

Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of develop...

Descripción completa

Detalles Bibliográficos
Autores principales: Rempel, Eugen, Hoelting, Lisa, Waldmann, Tanja, Balmer, Nina V., Schildknecht, Stefan, Grinberg, Marianna, Das Gaspar, John Antony, Shinde, Vaibhav, Stöber, Regina, Marchan, Rosemarie, van Thriel, Christoph, Liebing, Julia, Meisig, Johannes, Blüthgen, Nils, Sachinidis, Agapios, Rahnenführer, Jörg, Hengstler, Jan G., Leist, Marcel
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer Berlin Heidelberg 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551554/
https://www.ncbi.nlm.nih.gov/pubmed/26272509
http://dx.doi.org/10.1007/s00204-015-1573-y
_version_ 1782387586661089280
author Rempel, Eugen
Hoelting, Lisa
Waldmann, Tanja
Balmer, Nina V.
Schildknecht, Stefan
Grinberg, Marianna
Das Gaspar, John Antony
Shinde, Vaibhav
Stöber, Regina
Marchan, Rosemarie
van Thriel, Christoph
Liebing, Julia
Meisig, Johannes
Blüthgen, Nils
Sachinidis, Agapios
Rahnenführer, Jörg
Hengstler, Jan G.
Leist, Marcel
author_facet Rempel, Eugen
Hoelting, Lisa
Waldmann, Tanja
Balmer, Nina V.
Schildknecht, Stefan
Grinberg, Marianna
Das Gaspar, John Antony
Shinde, Vaibhav
Stöber, Regina
Marchan, Rosemarie
van Thriel, Christoph
Liebing, Julia
Meisig, Johannes
Blüthgen, Nils
Sachinidis, Agapios
Rahnenführer, Jörg
Hengstler, Jan G.
Leist, Marcel
author_sort Rempel, Eugen
collection PubMed
description Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for 6 days to the histone deacetylase inhibitors (HDACi) valproic acid, trichostatin A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of ‘mercurials’ (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1 and LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00204-015-1573-y) contains supplementary material, which is available to authorized users.
format Online
Article
Text
id pubmed-4551554
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Springer Berlin Heidelberg
record_format MEDLINE/PubMed
spelling pubmed-45515542015-09-01 A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors Rempel, Eugen Hoelting, Lisa Waldmann, Tanja Balmer, Nina V. Schildknecht, Stefan Grinberg, Marianna Das Gaspar, John Antony Shinde, Vaibhav Stöber, Regina Marchan, Rosemarie van Thriel, Christoph Liebing, Julia Meisig, Johannes Blüthgen, Nils Sachinidis, Agapios Rahnenführer, Jörg Hengstler, Jan G. Leist, Marcel Arch Toxicol In Vitro Systems Test systems to identify developmental toxicants are urgently needed. A combination of human stem cell technology and transcriptome analysis was to provide a proof of concept that toxicants with a related mode of action can be identified and grouped for read-across. We chose a test system of developmental toxicity, related to the generation of neuroectoderm from pluripotent stem cells (UKN1), and exposed cells for 6 days to the histone deacetylase inhibitors (HDACi) valproic acid, trichostatin A, vorinostat, belinostat, panobinostat and entinostat. To provide insight into their toxic action, we identified HDACi consensus genes, assigned them to superordinate biological processes and mapped them to a human transcription factor network constructed from hundreds of transcriptome data sets. We also tested a heterogeneous group of ‘mercurials’ (methylmercury, thimerosal, mercury(II)chloride, mercury(II)bromide, 4-chloromercuribenzoic acid, phenylmercuric acid). Microarray data were compared at the highest non-cytotoxic concentration for all 12 toxicants. A support vector machine (SVM)-based classifier predicted all HDACi correctly. For validation, the classifier was applied to legacy data sets of HDACi, and for each exposure situation, the SVM predictions correlated with the developmental toxicity. Finally, optimization of the classifier based on 100 probe sets showed that eight genes (F2RL2, TFAP2B, EDNRA, FOXD3, SIX3, MT1E, ETS1 and LHX2) are sufficient to separate HDACi from mercurials. Our data demonstrate how human stem cells and transcriptome analysis can be combined for mechanistic grouping and prediction of toxicants. Extension of this concept to mechanisms beyond HDACi would allow prediction of human developmental toxicity hazard of unknown compounds with the UKN1 test system. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s00204-015-1573-y) contains supplementary material, which is available to authorized users. Springer Berlin Heidelberg 2015-08-14 2015 /pmc/articles/PMC4551554/ /pubmed/26272509 http://dx.doi.org/10.1007/s00204-015-1573-y Text en © The Author(s) 2015 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided 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.
spellingShingle In Vitro Systems
Rempel, Eugen
Hoelting, Lisa
Waldmann, Tanja
Balmer, Nina V.
Schildknecht, Stefan
Grinberg, Marianna
Das Gaspar, John Antony
Shinde, Vaibhav
Stöber, Regina
Marchan, Rosemarie
van Thriel, Christoph
Liebing, Julia
Meisig, Johannes
Blüthgen, Nils
Sachinidis, Agapios
Rahnenführer, Jörg
Hengstler, Jan G.
Leist, Marcel
A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title_full A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title_fullStr A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title_full_unstemmed A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title_short A transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
title_sort transcriptome-based classifier to identify developmental toxicants by stem cell testing: design, validation and optimization for histone deacetylase inhibitors
topic In Vitro Systems
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4551554/
https://www.ncbi.nlm.nih.gov/pubmed/26272509
http://dx.doi.org/10.1007/s00204-015-1573-y
work_keys_str_mv AT rempeleugen atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT hoeltinglisa atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT waldmanntanja atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT balmerninav atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT schildknechtstefan atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT grinbergmarianna atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT dasgasparjohnantony atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT shindevaibhav atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT stoberregina atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT marchanrosemarie atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT vanthrielchristoph atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT liebingjulia atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT meisigjohannes atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT bluthgennils atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT sachinidisagapios atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT rahnenfuhrerjorg atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT hengstlerjang atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT leistmarcel atranscriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT rempeleugen transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT hoeltinglisa transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT waldmanntanja transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT balmerninav transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT schildknechtstefan transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT grinbergmarianna transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT dasgasparjohnantony transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT shindevaibhav transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT stoberregina transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT marchanrosemarie transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT vanthrielchristoph transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT liebingjulia transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT meisigjohannes transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT bluthgennils transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT sachinidisagapios transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT rahnenfuhrerjorg transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT hengstlerjang transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors
AT leistmarcel transcriptomebasedclassifiertoidentifydevelopmentaltoxicantsbystemcelltestingdesignvalidationandoptimizationforhistonedeacetylaseinhibitors