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8 Publications visible to you, out of a total of 8

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Abstract The human liver has a remarkable capacity to regenerate and thus compensate over decades for fibrosis caused by toxic chemicals, drugs, alcohol, or malnutrition. To date, no protective mechanismsrition. To date, no protective mechanisms have been identified that help the liver tolerate these repeated injuries. In this study, we revealed dysregulation of lipid metabolism and mild inflammation as protective mechanisms by studying longitudinal multi-omic measurements of liver fibrosis induced by repeated CCl 4 injections in mice ( n  = 45). Based on comprehensive proteomics, transcriptomics, blood- and tissue-level profiling, we uncovered three phases of early disease development—initiation, progression, and tolerance. Using novel multi-omic network analysis, we identified multi-level mechanisms that are significantly dysregulated in the injury-tolerant response. Public data analysis shows that these profiles are altered in human liver diseases, including fibrosis and early cirrhosis stages. Our findings mark the beginning of the tolerance phase as the critical switching point in liver response to repetitive toxic doses. After fostering extracellular matrix accumulation as an acute response, we observe a deposition of tiny lipid droplets in hepatocytes only in the Tolerant phase. Our comprehensive study shows that lipid metabolism and mild inflammation may serve as biomarkers and are putative functional requirements to resist further disease progression.

Authors: Seddik Hammad, Christoph Ogris, Amnah Othman, Pia Erdoesi, Wolfgang Schmidt-Heck, Ina Biermayer, Barbara Helm, Yan Gao, Weronika Piorońska, Christian H. Holland, Lorenza A. D’Alessandro, Carolina de la Torre, Carsten Sticht, Sherin Al Aoua, Fabian J. Theis, Heike Bantel, Matthias P. Ebert, Ursula Klingmüller, Jan G. Hengstler, Steven Dooley, Nikola S. Mueller

Date Published: 1st Jul 2023

Publication Type: Journal

Abstract

Not specified

Authors: Christian H. Holland, Ricardo O. Ramirez Flores, Maiju Myllys, Reham Hassan, Karolina Edlund, Ute Hofmann, Rosemarie Marchan, Cristina Cadenas, Jörg Reinders, Stefan Hoehme, Abdel‐latif Seddek, Steven Dooley, Verena Keitel, Patricio Godoy, Brigitte Begher‐Tibbe, Christian Trautwein, Christian Rupp, Sebastian Mueller, Thomas Longerich, Jan G. Hengstler, Julio Saez‐Rodriguez, Ahmed Ghallab

Date Published: 28th Aug 2021

Publication Type: Journal

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BACKGROUND & AIMS: In chronic liver diseases, inflammation induces oxidative stress and thus may contribute to the progression of liver injury, fibrosis, and carcinogenesis. The KEAP1/NRF2 axis is a major regulator of cellular redox balance. In the present study, we investigated whether the KEAP1/NRF2 system is involved in liver disease progression in humans and mice. METHODS: The clinical relevance of oxidative stress was investigated by liver RNA sequencing in a well-characterized cohort of patients with non-alcoholic fatty liver disease (n = 63) and correlated with histological and clinical parameters. For functional analysis, hepatocyte-specific Nemo knockout (NEMO(Deltahepa)) mice were crossed with hepatocyte-specific Keap1 knockout (KEAP1(Deltahepa)) mice. RESULTS: Immunohistochemical analysis of human liver sections showed increased oxidative stress and high NRF2 expression in patients with chronic liver disease. RNA sequencing of liver samples in a human pediatric NAFLD cohort revealed a significant increase of NRF2 activation correlating with the grade of inflammation, but not with the grade of steatosis, which could be confirmed in a second adult NASH cohort. In mice, microarray analysis revealed that Keap1 deletion induces NRF2 target genes involved in glutathione metabolism and xenobiotic stress (e.g., Nqo1). Furthermore, deficiency of one of the most important antioxidants, glutathione (GSH), in NEMO(Deltahepa) livers was rescued after deleting Keap1. As a consequence, NEMO(Deltahepa)/KEAP1(Deltahepa) livers showed reduced apoptosis compared to NEMO(Deltahepa) livers as well as a dramatic downregulation of genes involved in cell cycle regulation and DNA replication. Consequently, NEMO(Deltahepa)/KEAP1(Deltahepa) compared to NEMO(Deltahepa) livers displayed decreased fibrogenesis, lower tumor incidence, reduced tumor number, and decreased tumor size. CONCLUSIONS: NRF2 activation in patients with non-alcoholic steatohepatitis correlates with the grade of inflammation, but not steatosis. Functional analysis in mice demonstrated that NRF2 activation in chronic liver disease is protective by ameliorating fibrogenesis, initiation and progression of hepatocellular carcinogenesis. LAY SUMMARY: The KEAP1 (Kelch-like ECH-associated protein-1)/NRF2 (erythroid 2-related factor 2) axis has a major role in regulating cellular redox balance. Herein, we show that NRF2 activity correlates with the grade of inflammation in patients with non-alcoholic steatohepatitis. Functional studies in mice actually show that NRF2 activation, resulting from KEAP1 deletion, protects against fibrosis and cancer.

Authors: A. Mohs, T. Otto, K. M. Schneider, M. Peltzer, M. Boekschoten, C. H. Holland, C. A. Hudert, L. Kalveram, S. Wiegand, J. Saez-Rodriguez, T. Longerich, J. G. Hengstler, C. Trautwein

Date Published: 22nd Dec 2020

Publication Type: Journal

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Background Many functional analysis tools have been developed to extract functional and mechanistic insight from bulk transcriptome data. With the advent of single-cell RNA sequencing (scRNA-seq), it is in principle possible to do such an analysis for single cells. However, scRNA-seq data has characteristics such as drop-out events and low library sizes. It is thus not clear if functional TF and pathway analysis tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. Results To address this question, we perform benchmark studies on simulated and real scRNA-seq data. We include the bulk-RNA tools PROGENy, GO enrichment, and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compare them against the tools SCENIC/AUCell and metaVIPER, designed for scRNA-seq. For the in silico study, we simulate single cells from TF/pathway perturbation bulk RNA-seq experiments. We complement the simulated data with real scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on simulated and real data reveal comparable performance to the original bulk data. Additionally, we show that the TF and pathway activities preserve cell type-specific variability by analyzing a mixture sample sequenced with 13 scRNA-seq protocols. We also provide the benchmark data for further use by the community. Conclusions Our analyses suggest that bulk-based functional analysis tools that use manually curated footprint gene sets can be applied to scRNA-seq data, partially outperforming dedicated single-cell tools. Furthermore, we find that the performance of functional analysis tools is more sensitive to the gene sets than to the statistic used.

Authors: Christian H. Holland, Jovan Tanevski, Javier Perales-Patón, Jan Gleixner, Manu P. Kumar, Elisabetta Mereu, Brian A. Joughin, Oliver Stegle, Douglas A. Lauffenburger, Holger Heyn, Bence Szalai, Julio Saez-Rodriguez

Date Published: 1st Dec 2020

Publication Type: Journal

Abstract (Expand)

Background & Aims Inflammation in chronic liver diseases induces oxidative stress and thus may contribute to progression of liver injury, fibrosis, and carcinogenesis. The KEAP1/NRF2 axis is a major regulator of cellular redox balance. In the present study, we investigated whether the KEAP1/NRF2 system is involved in liver disease progression in human and mice. Methods The clinical relevance of oxidative stress was investigated in a well-characterized cohort of NAFLD patients (n=63) by liver RNA sequencing and correlated with histological and clinical parameters. For functional analysis hepatocyte-specific NEMO knock-out (NEMO Δhepa) mice were crossed with hepatocyte-specific KEAP1 knock-out (KEAP1 Δhepa) mice. Results Immunohistochemical analysis of human liver sections showed increased oxidative stress and high NRF2 expression in patients with chronic liver disease. RNA sequencing of liver samples in a human pediatric NAFLD cohort revealed a significant increase of NRF2 activation correlating with the grade of inflammation, but not with the grade of steatosis, which could be confirmed in a second adult NASH cohort. In mice, microarray analysis revealed that KEAP1 deletion induces NRF2 target genes involved in glutathione metabolism and xenobiotic stress (e.g., Nqo1). Furthermore, deficiency of one of the most important antioxidants, glutathione (GSH), in NEMO Δhepa livers was rescued after deleting KEAP1. As a consequence, NEMO Δhepa/KEAP1 Δhepa livers showed reduced apoptosis compared to NEMO Δhepa livers as well as a dramatic downregulation of genes involved in cell cycle regulation and DNA replication. Consequently, NEMO Δhepa/KEAP1 Δhepa compared to NEMO Δhepa livers displayed decreased fibrogenesis, lower tumor incidence, reduced tumor number, and decreased tumor size. Conclusions NRF2 activation in NASH patients correlates with the grade of inflammation, but not steatosis. Functional analysis in mice demonstrated that NRF2 activation in chronic liver disease is protective by ameliorating fibrogenesis, initiation and progression of hepatocellular carcinogenesis.

Authors: Antje Mohs, Tobias Otto, Kai Markus Schneider, Mona Peltzer, Mark Boekschoten, Christian H. Holland, Christian A. Hudert, Laura Kalveram, Susanna Wiegand, Julio Saez-Rodriguez, Thomas Longerich, Jan G. Hengstler, Christian Trautwein

Date Published: 1st Oct 2020

Publication Type: Journal

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Little is known about how liver fibrosis influences lobular zonation. To address this question, we used three mouse models of liver fibrosis, repeated CCl4 administration for 2, 6 and 12 months to induce pericentral damage, as well as bile duct ligation (21 days) and mdr2−/− mice to study periportal fibrosis. Analyses were performed by RNA-sequencing, immunostaining of zonated proteins and image analysis. RNA-sequencing demonstrated a significant enrichment of pericentral genes among genes downregulated by CCl4; vice versa, periportal genes were enriched among the upregulated genes. Immunostaining showed an almost complete loss of pericentral proteins, such as cytochrome P450 enzymes and glutamine synthetase, while periportal proteins, such as arginase 1 and CPS1 became expressed also in pericentral hepatocytes. This pattern of fibrosis-associated ‘periportalization’ was consistently observed in all three mouse models and led to complete resistance to hepatotoxic doses of acetaminophen (200 mg/kg). Characterization of the expression response identified the inflammatory pathways TGFβ, NFκB, TNFα, and transcription factors NFKb1, Stat1, Hif1a, Trp53, and Atf1 among those activated, while estrogen-associated pathways, Hnf4a and Hnf1a, were decreased. In conclusion, liver fibrosis leads to strong alterations of lobular zonation, where the pericentral region adopts periportal features. Beside adverse consequences, periportalization supports adaptation to repeated doses of hepatotoxic compounds.

Authors: Ahmed Ghallab, Maiju Myllys, Christian Holland, Ayham Zaza, Walaa Murad, Reham Hassan, Yasser A Ahmed, Tahany Abbas, Eman Abdelrahim, Kai Markus Schneider, Madlen Matz-Soja, Joerg Reinders, Rolf Gebhardt, Theresa Hildegard Wirtz, Maximilian Hatting, Dirk Drasdo, Julio Saez-Rodriguez, Christian Trautwein, Jan Hengstler

Date Published: 1st Dec 2019

Publication Type: Not specified

Abstract (Expand)

Transcriptome profiling followed by differential gene expression analysis often leads to lists of genes that are hard to analyze and interpret. Functional genomics tools are powerful approaches for downstream analysis, as they summarize the large and noisy gene expression space into a smaller number of biological meaningful features. In particular, methods that estimate the activity of processes by mapping transcripts level to process members are popular. However, footprints of either a pathway or transcription factor (TF) on gene expression show superior performance over mapping-based gene sets. These footprints are largely developed for humans and their usability in the broadly-used model organism Mus musculus is uncertain. Evolutionary conservation of the gene regulatory system suggests that footprints of human pathways and TFs can functionally characterize mice data. In this paper we analyze this hypothesis. We perform a comprehensive benchmark study exploiting two state-of-the-art footprint methods, DoRothEA and an extended version of PROGENy. These methods infer TF and pathway activity, respectively. Our results show that both can recover mouse perturbations, confirming our hypothesis that footprints are conserved between mice and humans. Subsequently, we illustrate the usability of PROGENy and DoRothEA by recovering pathway/TF-disease associations from newly generated disease sets. Additionally, we provide pathway and TF activity scores for a large collection of human and mouse perturbation and disease experiments (2374). We believe that this resource, available for interactive exploration and download (https://saezlab.shinyapps.io/footprint_scores/), can have broad applications including the study of diseases and therapeutics.

Authors: Christian H. Holland, Bence Szalai, Julio Saez-Rodriguez

Date Published: 1st Sep 2019

Publication Type: Not specified

Abstract (Expand)

The prediction of transcription factor (TF) activities from the gene expression of their targets (i.e., TF regulon) is becoming a widely used approach to characterize the functional status of transcriptional regulatory circuits. Several strategies and data sets have been proposed to link the target genes likely regulated by a TF, each one providing a different level of evidence. The most established ones are (1) manually curated repositories, (2) interactions derived from ChIP-seq binding data, (3) in silico prediction of TF binding on gene promoters, and (4) reverse-engineered regulons from large gene expression data sets. However, it is not known how these different sources of regulons affect the TF activity estimations and, thereby, downstream analysis and interpretation. Here we compared the accuracy and biases of these strategies to define human TF regulons by means of their ability to predict changes in TF activities in three reference benchmark data sets. We assembled a collection of TF–target interactions for 1541 human TFs and evaluated how different molecular and regulatory properties of the TFs, such as the DNA-binding domain, specificities, or mode of interaction with the chromatin, affect the predictions of TF activity. We assessed their coverage and found little overlap on the regulons derived from each strategy and better performance by literature-curated information followed by ChIP-seq data. We provide an integrated resource of all TF–target interactions derived through these strategies, with confidence scores, as a resource for enhanced prediction of TF activities.

Authors: Luz Garcia-Alonso, Christian H. Holland, Mahmoud M. Ibrahim, Denes Turei, Julio Saez-Rodriguez

Date Published: 1st Aug 2019

Publication Type: Not specified

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