Science & Insights

@article{Rempel2015,

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

author = {Eugen Rempel and Lisa Hoelting and Tanja Waldmann and Nina V. Balmer and Stefan Schildknecht and Marianna Grinberg and John A. Gaspar and Vaibhav Shinde and Regina Stöber and Rosemarie Marchan and Christoph van Thriel and Julia Liebing and Johannes Meisig and Nils Blüthgen and Agapios Sachinidis and Jörg Rahnenführer and Jan G. Hengstler and Marcel Leist},

url = {https://trenzyme.com/cell-culture-services/stem-cell-differentiation-service/, Stem Cell Differentiation Service

https://trenzyme.com/cell-culture-services/cell-based-assay-development-service/, Cell Based Development Service},

doi = {10.1007/s00204-015-1573-y},

issn = {1432-0738},

year  = {2015},

date = {2015-09-00},

urldate = {2015-09-00},

journal = {Arch Toxicol},

volume = {89},

number = {9},

pages = {1599--1618},

publisher = {Springer Science and Business Media LLC},

abstract = {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.},

keywords = {HDACi},

pubstate = {published},

tppubtype = {article}

}

@article{Shinde2015,

title = {Human Pluripotent Stem Cell Based Developmental Toxicity Assays for Chemical Safety Screening and Systems Biology Data Generation},

author = {Vaibhav Shinde and Stefanie Klima and Perumal Srinivasan Sureshkumar and Kesavan Meganathan and Smita Jagtap and Eugen Rempel and Jörg Rahnenführer and Jan G. Hengstler and Tanja Waldmann and Jürgen Hescheler and Marcel Leist and Agapios Sachinidis},

url = {https://trenzyme.com/cell-culture-services/stem-cell-differentiation-service/, Stem Cell Differentiation Service

https://trenzyme.com/cell-culture-services/cell-based-assay-development-service/, Cell Based Development Service},

doi = {10.3791/52333},

issn = {1940-087X},

year  = {2015},

date = {2015-00-00},

urldate = {2015-00-00},

journal = {JoVE},

number = {100},

publisher = {MyJove Corporation},

abstract = {Efficient protocols to differentiate human pluripotent stem cells to various tissues in combination with -omics technologies opened up new horizons for in vitro toxicity testing of potential drugs. To provide a solid scientific basis for such assays, it will be important to gain quantitative information on the time course of development and on the underlying regulatory mechanisms by systems biology approaches. Two assays have therefore been tuned here for these requirements. In the UKK test system, human embryonic stem cells (hESC) (or other pluripotent cells) are left to spontaneously differentiate for 14 days in embryoid bodies, to allow generation of cells of all three germ layers. This system recapitulates key steps of early human embryonic development, and it can predict human-specific early embryonic toxicity/teratogenicity, if cells are exposed to chemicals during differentiation. The UKN1 test system is based on hESC differentiating to a population of neuroectodermal progenitor (NEP) cells for 6 days. This system recapitulates early neural development and predicts early developmental neurotoxicity and epigenetic changes triggered by chemicals. Both systems, in combination with transcriptome microarray studies, are suitable for identifying toxicity biomarkers. Moreover, they may be used in combination to generate input data for systems biology analysis. These test systems have advantages over the traditional toxicological studies requiring large amounts of animals. The test systems may contribute to a reduction of the costs for drug development and chemical safety evaluation. Their combination sheds light especially on compounds that may influence neurodevelopment specifically.},

keywords = {hESC},

pubstate = {published},

tppubtype = {article}

}

@article{Grinberg2014,

title = {Toxicogenomics directory of chemically exposed human hepatocytes},

author = {Marianna Grinberg and Regina Stöber and Karolina Edlund and Eugen Rempel and Patricio Godoy and Raymond Reif and Agata Widera and Katrin Madjar and Wolfgang Schmidt-Heck and Rosemarie Marchan and Agapios Sachinidis and Dimitry Spitkovsky and Jürgen Hescheler and Helena Carmo and Marcelo D. Arbo and Bob van de Water and Steven Wink and Mathieu Vinken and Vera Rogiers and Sylvia Escher and Barry Hardy and Dragana Mitic and Glenn Myatt and Tanja Waldmann and Adil Mardinoglu and Georg Damm and Daniel Seehofer and Andreas Nüssler and Thomas S. Weiss and Axel Oberemm and Alfons Lampen and Mirjam M. Schaap and Mirjam Luijten and Harry van Steeg and Wolfgang E. Thasler and Jos C. S. Kleinjans and Rob H. Stierum and Marcel Leist and Jörg Rahnenführer and Jan G. Hengstler},

url = {https://trenzyme.com/cell-culture-services/cell-based-assay-development-service/, Cell Based Development Service},

doi = {10.1007/s00204-014-1400-x},

issn = {1432-0738},

year  = {2014},

date = {2014-12-00},

urldate = {2014-12-00},

journal = {Arch Toxicol},

volume = {88},

number = {12},

pages = {2261--2287},

publisher = {Springer Science and Business Media LLC},

abstract = {A long-term goal of numerous research projects is to identify biomarkers for in vitro systems predicting toxicity in vivo. Often, transcriptomics data are used to identify candidates for further evaluation. However, a systematic directory summarizing key features of chemically influenced genes in human hepatocytes is not yet available. To bridge this gap, we used the Open TG-GATES database with Affymetrix files of cultivated human hepatocytes incubated with chemicals, further sets of gene array data with hepatocytes from human donors generated in this study, and publicly available genome-wide datasets of human liver tissue from patients with non-alcoholic steatohepatitis (NASH), cirrhosis, and hepatocellular cancer (HCC). After a curation procedure, expression data of 143 chemicals were included into a comprehensive biostatistical analysis. The results are summarized in the publicly available toxicotranscriptomics directory (http://wiki.toxbank.net/toxicogenomics-map/) which provides information for all genes whether they are up- or downregulated by chemicals and, if yes, by which compounds. The directory also informs about the following key features of chemically influenced genes: (1) Stereotypical stress response. When chemicals induce strong expression alterations, this usually includes a complex but highly reproducible pattern named ‘stereotypical response.’ On the other hand, more specific expression responses exist that are induced only by individual compounds or small numbers of compounds. The directory differentiates if the gene is part of the stereotypical stress response or if it represents a more specific reaction. (2) Liver disease-associated genes. Approximately 20 % of the genes influenced by chemicals are up- or downregulated, also in liver disease. Liver disease genes deregulated in cirrhosis, HCC, and NASH that overlap with genes of the aforementioned stereotypical chemical stress response include CYP3A7, normally expressed in fetal liver; the phase II metabolizing enzyme SULT1C2; ALDH8A1, known to generate the ligand of RXR, one of the master regulators of gene expression in the liver; and several genes involved in normal liver functions: CPS1, PCK1, SLC2A2, CYP8B1, CYP4A11, ABCA8, and ADH4. (3) Unstable baseline genes. The process of isolating and the cultivation of hepatocytes was sufficient to induce some stress leading to alterations in the expression of genes, the so-called unstable baseline genes. (4) Biological function. Although more than 2,000 genes are transcriptionally influenced by chemicals, they can be assigned to a relatively small group of biological functions, including energy and lipid metabolism, inflammation and immune response, protein modification, endogenous and xenobiotic metabolism, cytoskeletal organization, stress response, and DNA repair. In conclusion, the introduced toxicotranscriptomics directory offers a basis for a rationale choice of candidate genes for biomarker evaluation studies and represents an easy to use source of background information on chemically influenced genes.},

keywords = {HCC},

pubstate = {published},

tppubtype = {article}

}

@article{Weng2014,

title = {Lineage-Specific Regulation of Epigenetic Modifier Genes in Human Liver and Brain},

author = {Matthias K. Weng and Karthick Natarajan and Diana Scholz and Violeta N. Ivanova and Agapios Sachinidis and Jan G. Hengstler and Tanja Waldmann and Marcel Leist},

editor = {Devin C. Koestler},

url = {https://trenzyme.com/cell-culture-services/stem-cell-differentiation-service/, Stem Cell Differentiation Service},

doi = {10.1371/journal.pone.0102035},

issn = {1932-6203},

year  = {2014},

date = {2014-07-23},

urldate = {2014-07-23},

journal = {PLoS ONE},

volume = {9},

number = {7},

publisher = {Public Library of Science (PLoS)},

abstract = {Despite an abundance of studies on chromatin states and dynamics, there is an astonishing dearth of information on the expression of genes responsible for regulating histone and DNA modifications. We used here a set of 156 defined epigenetic modifier genes (EMG) and profiled their expression pattern in cells of different lineages. As reference value, expression data from human embryonic stem cells (hESC) were used. Hepatocyte-like cells were generated from hESC, and their EMG expression was compared to primary human liver cells. In parallel, we generated postmitotic human neurons (Lu d6), and compared their relative EMG expression to human cortex (Ctx). Clustering analysis of all cell types showed that neuronal lineage samples grouped together (94 similarly regulated EMG), as did liver cells (61 similarly-regulated), while the two lineages were clearly distinct. The general classification was followed by detailed comparison of the major EMG groups; genes that were higher expressed in differentiated cells than in hESC included the acetyltransferase KAT2B and the methyltransferase SETD7. Neuro-specific EMGs were the histone deacetylases HDAC5 and HDAC7, and the arginine-methyltransferase PRMT8. Comparison of young (Lu d6) and more aged (Ctx) neuronal samples suggested a maturation-dependent switch in the expression of functionally homologous proteins. For instance, the ratio of the histone H3 K27 methyltransfereases, EZH1 to EZH2, was high in Ctx and low in Lu d6. The same was observed for the polycomb repressive complex 1 (PRC1) subunits CBX7 and CBX8. A large proportion of EMGs in differentiated cells was very differently expressed than in hESC, and absolute levels were significantly higher in neuronal samples than in hepatic cells. Thus, there seem to be distinct qualitative and quantitative differences in EMG expression between cell lineages.},

keywords = {hESC},

pubstate = {published},

tppubtype = {article}

}

@article{Balmer2014,

title = {From transient transcriptome responses to disturbed neurodevelopment: role of histone acetylation and methylation as epigenetic switch between reversible and irreversible drug effects},

author = {Nina V. Balmer and Stefanie Klima and Eugen Rempel and Violeta N. Ivanova and Raivo Kolde and Matthias K. Weng and Kesavan Meganathan and Margit Henry and Agapios Sachinidis and Michael R. Berthold and Jan G. Hengstler and Jörg Rahnenführer and Tanja Waldmann and Marcel Leist},

url = {https://trenzyme.com/cell-culture-services/cell-based-assay-development-service/, Cell Based Development Service},

doi = {10.1007/s00204-014-1279-6},

issn = {1432-0738},

year  = {2014},

date = {2014-07-00},

urldate = {2014-07-00},

journal = {Arch Toxicol},

volume = {88},

number = {7},

pages = {1451--1468},

publisher = {Springer Science and Business Media LLC},

abstract = {The superordinate principles governing the transcriptome response of differentiating cells exposed to drugs are still unclear. Often, it is assumed that toxicogenomics data reflect the immediate mode of action (MoA) of drugs. Alternatively, transcriptome changes could describe altered differentiation states as indirect consequence of drug exposure. We used here the developmental toxicants valproate and trichostatin A to address this question. Neurally differentiating human embryonic stem cells were treated for 6 days. Histone acetylation (primary MoA) increased quickly and returned to baseline after 48 h. Histone H3 lysine methylation at the promoter of the neurodevelopmental regulators PAX6 or OTX2 was increasingly altered over time. Methylation changes remained persistent and correlated with neurodevelopmental defects and with effects on PAX6 gene expression, also when the drug was washed out after 3–4 days. We hypothesized that drug exposures altering only acetylation would lead to reversible transcriptome changes (indicating MoA), and challenges that altered methylation would lead to irreversible developmental disturbances. Data from pulse-chase experiments corroborated this assumption. Short drug treatment triggered reversible transcriptome changes; longer exposure disrupted neurodevelopment. The disturbed differentiation was reflected by an altered transcriptome pattern, and the observed changes were similar when the drug was washed out during the last 48 h. We conclude that transcriptome data after prolonged chemical stress of differentiating cells mainly reflect the altered developmental stage of the model system and not the drug MoA. We suggest that brief exposures, followed by immediate analysis, are more suitable for information on immediate drug responses and the toxicity MoA.},

keywords = {MoA},

pubstate = {published},

tppubtype = {article}

}