Lineage-Specific Regulation of Epigenetic Modifier Genes in Human Liver and Brain

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.

Toxicogenomics directory of chemically exposed human hepatocytes

“…Gene array analysis performed on the livers of rats facilitated the differentiation between genotoxic and non-genotoxic carcinogens (Ellinger-Ziegelbauer et al 2008;. These successful toxicogenomics studies in vivo prompted several ambitious research programs, including the EU-funded SEURAT-1 network and the ESNATs project Krug et al 2013;Schug et al 2013;Weng et al 2014;Balmer et al 2014;Campos et al 2014), with the aim to identify biomarkers of toxicity in vitro. One long-term goal of these projects is to identify biomarkers in the in vitro systems that can predict certain mechanisms of toxicity in vivo.…”

In vitro systems: current limitations and future perspectives

“…Clearly, in vitro systems represent one of the most popular topics in our journal (Godoy et al 2013;Azqueta and Collins 2013;Hessel et al 2013;Jiang et al 2013;Liu et al 2013;Fraczek et al 2013;Leist and Hartung 2013). This seems to represent a general trend in toxicological sciences (Weng et al 2014;Waldmann et al 2014;Karlsson et al 2013;Onrubia et al 2013;Lake et al 2013;Houston et al 2012;Hardelauf et al 2011;Ilowski et al 2011;Gabriel et al 2012;Hammad et al 2013) but also in other disciplines of biomedical research (Zellmer et al 2010;Godoy et al 2009Godoy et al , 2010aIlowski et al 2010;Meyer et al 2011). In the Archives of Toxicology, in vitro systems are used to study mechanisms of action of toxic compounds, a traditional strategy since decades (Chen et al 2013;Qu et al 2013; One possibility would be to identify compounds for which in vivo blood concentrations (nonprotein bound) in humans are known and the risk of adverse effects in humans is clearly established.…”

Highlight report: hepatotoxicity of triazole fungicides

“…Currently, much effort is invested to improve the possibilities of in vitro systems of hepatotoxicity (Luckert et al 2017;Grinberg et al 2014Grinberg et al , 2018Braeuning et al 2019;Gu et al 2018). Traditionally, in vitro systems served to identify the molecular mechanisms responsible for adverse effects (Weng et al 2014;Frey et al 2014;Arbo et al 2016) and more recently have also been used to predict doses and blood concentrations causing an increased risk of toxicity in humans (Albrecht et al 2019; Sachinidis et al 2019). This is an approach that often is supported by methods of systems modeling (Ghallab et al 2016;Hoehme et al 2010).…”