The binding and contribution of transcription factors (TF) to cell specific gene expression is often deduced from open-chromatin measurements to avoid costly TF ChIP-seq assays. Thus, it is important to develop computational methods for accurate TF binding prediction in open-chromatin regions (OCRs). Here, we report a novel segmentation-based method, TEPIC, to predict TF binding by combining sets of OCRs with position weight matrices. TEPIC can be applied to various open-chromatin data, e.g. DNaseI-seq and NOMe-seq. Additionally, Histone-Marks (HMs) can be used to identify candidate TF binding sites. TEPIC computes TF affinities and uses open-chromatin/HM signal intensity as quantitative measures of TF binding strength. Using machine learning, we find low affinity binding sites to improve our ability to explain gene expression variability compared to the standard presence/absence classification of binding sites. Further, we show that both footprints and peaks capture essential TF binding events and lead to a good prediction performance. In our application, gene-based scores computed by TEPIC with one open-chromatin assay nearly reach the quality of several TF ChIP-seq data sets. Finally, these scores correctly predict known transcriptional regulators as illustrated by the application to novel DNaseI-seq and NOMe-seq data for primary human hepatocytes and CD4+ T-cells, respectively.

The binding and contribution of transcription factors (TF) to cell specific gene Using machine learning, we find low affinity binding sites to improve our ability to 10 explain gene expression variability compared to the standard presence/absence 11 classification of binding sites. Further, we show that both footprints and peaks capture 12 essential TF binding events and lead to a good prediction performance. In our nearly reach the quality of several TF ChIP-seq datasets. Finally, these scores correctly 15

It is well known that isolation and cultivation of primary hepatocytes cause major gene expression alterations. In the present genome-wide, time-resolved study of cultivated human and mouse hepatocytes, we made the observation that expression changes in culture strongly resemble alterations in liver diseases. Hepatocytes of both species were cultivated in collagen sandwich and in monolayer conditions. Genome-wide data were also obtained from human NAFLD, cirrhosis, HCC and hepatitis B virus-infected tissue as well as mouse livers after partial hepatectomy, CCl4 intoxication, obesity, HCC and LPS. A strong similarity between cultivation and disease-induced expression alterations was observed. For example, expression changes in hepatocytes induced by 1-day cultivation and 1-day CCl4 exposure in vivo correlated with R = 0.615 (p < 0.001). Interspecies comparison identified predominantly similar responses in human and mouse hepatocytes but also a set of genes that responded differently. Unsupervised clustering of altered genes identified three main clusters: (1) downregulated genes corresponding to mature liver functions, (2) upregulation of an inflammation/RNA processing cluster and (3) upregulated migration/cell cycle-associated genes. Gene regulatory network analysis highlights overrepresented and deregulated HNF4 and CAR (Cluster 1), Krüppel-like factors MafF and ELK1 (Cluster 2) as well as ETF (Cluster 3) among the interspecies conserved key regulators of expression changes. Interventions ameliorating but not abrogating cultivation-induced responses include removal of non-parenchymal cells, generation of the hepatocytes’ own matrix in spheroids, supplementation with bile salts and siRNA-mediated suppression of key transcription factors. In conclusion, this study shows that gene regulatory network alterations of cultivated hepatocytes resemble those of inflammatory liver diseases and should therefore be considered and exploited as disease models.Electronic supplementary materialThe online version of this article (doi:10.1007/s00204-016-1761-4) contains supplementary material, which is available to authorized users.

Non-alcoholic steatohepatitis (NASH) represents a risk factor for the development of hepatocellular carcinoma (HCC) and is characterized by quantitative and qualitative changes in hepatic lipids. Since elongation of fatty acids from C16 to C18 has recently been reported to promote both hepatic lipid accumulation and inflammation we aimed to investigate whether a frequently used mouse NASH model reflects this clinically relevant feature and whether C16 to C18 elongation can be observed in HCC development. Feeding mice a methionine and choline deficient diet to model NASH not only increased total hepatic fatty acids and cholesterol, but also distinctly elevated the C18/C16 ratio, which was not changed in a model of simple steatosis (ob/ob mice). Depletion of Kupffer cells abrogated both quantitative and qualitative methionine-and-choline deficient (MCD)-induced alterations in hepatic lipids. Interestingly, mimicking inflammatory events in early hepatocarcinogenesis by diethylnitrosamine-induced carcinogenesis (48 h) increased hepatic lipids and the C18/C16 ratio. Analyses of human liver samples from patients with NASH or NASH-related HCC showed an elevated expression of the elongase ELOVL6, which is responsible for the elongation of C16 fatty acids. Taken together, our findings suggest a detrimental role of an altered fatty acid pattern in the progression of NASH-related liver disease.

Endothelial lipase (LIPG) is a cell surface associated lipase that displays phospholipase A1 activity towards phosphatidylcholine present in high‐density lipoproteins (HDL). LIPG was recently reported to be expressed in breast cancer and to support proliferation, tumourigenicity and metastasis. Here we show that severe oxidative stress leading to AMPK activation triggers LIPG upregulation, resulting in intracellular lipid droplet accumulation in breast cancer cells, which supports survival. Neutralizing oxidative stress abrogated LIPG upregulation and the concomitant lipid storage. In human breast cancer, high LIPG expression was observed in a limited subset of tumours and was significantly associated with shorter metastasis‐free survival in node‐negative, untreated patients. Moreover, expression of PLIN2 and TXNRD1 in these tumours indicated a link to lipid storage and oxidative stress. Altogether, our findings reveal a previously unrecognized role for LIPG in enabling oxidative stress‐induced lipid droplet accumulation in tumour cells that protects against oxidative stress, and thus supports tumour progression.