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 Holland, Mahmoud M. Ibrahim, Denes Turei, Julio Saez-Rodriguez

Date Published: 1st Aug 2019

Journal: Genome Res.

Abstract (Expand)

Many tools have been developed to extract functional and mechanistic insight from bulk transcriptome profiling 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, low library sizes and a comparatively large number of samples/cells. It is thus not clear if functional genomics tools established for bulk sequencing can be applied to scRNA-seq in a meaningful way. To address this question, we performed benchmark studies on in silico and in vitro single-cell RNA-seq data. We included the bulk-RNA tools PROGENy, GO enrichment and DoRothEA that estimate pathway and transcription factor (TF) activities, respectively, and compared them against the tools AUCell and metaVIPER, designed for scRNA-seq. For the in silico study we simulated single cells from TF/pathway perturbation bulk RNA-seq experiments. Our simulation strategy guarantees that the information of the original perturbation is preserved while resembling the characteristics of scRNA-seq data. We complemented the in silico data with in vitro scRNA-seq data upon CRISPR-mediated knock-out. Our benchmarks on both the simulated and real data revealed comparable performance to the original bulk data. Additionally, we showed that the TF and pathway activities preserve cell-type specific variability by analysing a mixture sample sequenced with 13 scRNA-seq different protocols. Our analyses suggest that bulk functional genomics tools can be applied to scRNA-seq data, outperforming dedicated single cell tools. Furthermore we provide a benchmark for further methods development by the community.

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

Date Published: No date defined

Journal: Not specified

Abstract (Expand)

The p38(MAPK) downstream targets MAPKAP kinases (MK) 2 and 3 are critical for the regulation of the macrophage response to LPS. The extents to which these two kinases act cooperatively and distinctly in regulating LPS-induced inflammatory cytokine expression are still unclear. To address this uncertainty, whole transcriptome analyses were performed using bone marrow-derived macrophages (BMDM) generated from MK2(-/-) or MK2/3(-/-) animals and their wild-type littermates. The results suggest that in BMDM, MK2 and MK3 not only cooperatively regulate the transcript expression of signaling intermediates, including IL-10, IL-19, CXCL2 and the IL-4 receptor (IL-4R)alpha subunit, they also exert distinct regulatory effects on the expression of specific transcripts. Based on the differential regulation of gene expression by MK2 and MK3, at least six regulatory patterns were identified. Importantly, we confirmed our previous finding, which showed that in the absence of MK2, MK3 negatively regulates IFN-beta. Moreover, this genome-wide analysis identified the regulation of Cr1A, NOD1 and Serpina3f as similar to that of IFN-beta. In the absence of MK2, MK3 also delayed the nuclear translocation of NFkappaB by delaying the ubiquitination and subsequent degradation of IkappaBbeta, reflecting the substantial plasticity of the response of BMDM to LPS.

Authors: Christian Ehlting, J. Rex, U. Albrecht, R. Deenen, C. Tiedje, K. Kohrer, O. Sawodny, M. Gaestel, D. Haussinger, Johannes Bode

Date Published: 30th Jul 2019

Journal: Sci Rep

Abstract (Expand)

BACKGROUND & AIMS: Activation of transforming growth factor beta (TGFB) promotes liver fibrosis by activating hepatic stellate cells (HSCs), but the mechanism of TGFB activation are not clear. We investigated the role of extracellular matrix protein 1 (ECM1), which interacts with extracellular and structural proteins, in TGFB activation in livers of mice. METHODS: We performed studies with e C57BL/6J mice (controls), ECM1-knockout (ECM1-KO) mice, and mice with hepatocyte-specific knockout of EMC1 (ECM1Deltahep). ECM1 or soluble TGFB receptor 2 (TGFBR2) were expressed in livers of mice following injection of an adeno-associated virus vector. Liver fibrosis was induced by carbon tetrachloride (CCl4) administration. Livers were collected from mice and analyzed by histology, immunohistochemistry, in situ hybridization, and immunofluorescence analyses. Hepatocytes and HSCs were isolated from livers of mice and incubated with ECM1; production of cytokines and activation of reporter genes were quantified. Liver tissues from patients with viral or alcohol-induced hepatitis (with different stages of fibrosis) and individuals with healthy liver were analyzed by immunohistochemistry and in situ hybridization. RESULTS: ECM1-KO mice spontaneously developed liver fibrosis and died by 2 months of age without significant hepatocyte damage or inflammation. In liver tissues of mice, we found that ECM1 stabilized extracellular matrix-deposited TGFB in its inactive form by interacting with alphav integrins to prevent activation of HSCs. In liver tissues from patients and in mice with CCl4-induced liver fibrosis, we found an inverse correlation between level of ECM1 and severity of fibrosis. CCl4-induced liver fibrosis was accelerated in ECM1Deltahep mice compared with control mice. Hepatocytes produced the highest levels of ECM1 in livers of mice. Ectopic expression of ECM1 or soluble TGFBR2 in liver prevented fibrogenesis in ECM1-KO mice and prolonged their survival. Ectopic expression of ECM1 in liver also reduced the severity of CCl4-induced fibrosis in mice. CONCLUSIONS: ECM1, produced by hepatocytes, inhibits activation of TGFB and its activation of HSCs to prevent fibrogenesis in mouse liver. Strategies to increase levels of ECM1 in liver might be developed for treatment of fibrosis.

Authors: W. Fan, T. Liu, W. Chen, Seddik Hammad, T. Longerich, Y. Fu, N. Li, Y. He, C. Liu, Y. Zhang, Q. Lian, Jieling Zhao, C. Yan, L. Li, C. Yi, Z. Ling, L. Ma, Jieling Zhao, H. Xu, P. Wang, M. Cong, H. You, Z. Liu, Y. Wang, J. Chen, D. Li, L. Hui, Steven Dooley, J. Hou, J. Jia, B. Sun

Date Published: 27th Jul 2019

Journal: Gastroenterology

Abstract (Expand)

Human hepatocellular carcinoma (HCC) is the most common type of primary liver cancer in adults and the most common cause of death in people with cirrhosis. While previous metabolic studies of HCC have mainly focused on the glucose metabolism (Warburg effect), less attention has been paid to tumor-specific features of the lipid metabolism. Here, we applied a computational approach to analyze major pathways of fatty acid utilization in individual HCC. To this end, we used protein intensity profiles of eleven human HCCs to parameterize tumor-specific kinetic models of cellular lipid metabolism including formation, enlargement, and degradation of lipid droplets (LDs). Our analysis reveals significant inter-tumor differences in the lipid metabolism. The majority of HCCs show a reduced uptake of fatty acids and decreased rate of beta-oxidation, however, some HCCs display a completely different metabolic phenotype characterized by high rates of beta-oxidation. Despite reduced fatty acid uptake in the majority of HCCs, the content of triacylglycerol is significantly enlarged compared to the tumor-adjacent tissue. This is due to tumor-specific expression profiles of regulatory proteins decorating the surface of LDs and controlling their turnover. Our simulations suggest that HCCs characterized by a very high content of triglycerides comprise regulatory peculiarities that render them susceptible to selective drug targeting without affecting healthy tissue.

Authors: N. Berndt, Johannes Eckstein, Niklas Heucke, R. Gajowski, Martin Stockmann, David Meierhofer, Hergo Holzhütter

Date Published: 27th May 2019

Journal: Cells

Abstract (Expand)

Computational models can help researchers to interpret data, understand biological functions, and make quantitative predictions. The Systems Biology Markup Language (SBML) is a file format for representing computational models in a declarative form that different software systems can exchange. SBML is oriented towards describing biological processes of the sort common in research on a number of topics, including metabolic pathways, cell signaling pathways, and many others. By supporting SBML as an input/output format, different tools can all operate on an identical representation of a model, removing opportunities for translation errors and assuring a common starting point for analyses and simulations. This document provides the specification for Release 2 of Version 2 of SBML Level 3 Core. The specification defines the data structures prescribed by SBML as well as their encoding in XML, the eXtensible Markup Language. Release 2 corrects some errors and clarifies some ambiguities discovered in Release 1. This specification also defines validation rules that determine the validity of an SBML document, and provides many examples of models in SBML form. Other materials and software are available from the SBML project website at

Authors: M. Hucka, F. T. Bergmann, C. Chaouiya, A. Drager, S. Hoops, S. M. Keating, Matthias König, N. L. Novere, C. J. Myers, B. G. Olivier, S. Sahle, J. C. Schaff, R. Sheriff, L. P. Smith, D. Waltemath, D. J. Wilkinson, F. Zhang

Date Published: 20th Jun 2019

Journal: J Integr Bioinform

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics presents an overview of COMBINE standards and their latest specifications. The standards cover representation formats for computational modeling in synthetic and systems biology and include BioPAX, CellML, NeuroML, SBML, SBGN, SBOL and SED-ML. The articles in this issue contain updated specifications of SBGN Process Description Level 1 Version 2, SBML Level 3 Core Version 2 Release 2, SBOL Version 2.3.0, and SBOL Visual Version 2.1.

Authors: Falk Schreiber, Björn Sommer, Gary D. Bader, Padraig Gleeson, Martin Golebiewski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 26th Jun 2019

Journal: Not specified

Abstract (Expand)

Modular Response Analysis (MRA) is a suite of methods that under certain assumptions permits the precise reconstruction of both the directions and strengths of connections between network modules from network responses to perturbations. Standard MRA assumes that modules are insulated, thereby neglecting the existence of inter-modular protein complexes. Such complexes sequester proteins from different modules and propagate perturbations to the protein abundance of a downstream module retroactively to an upstream module. MRA-based network reconstruction detects retroactive, sequestration-induced connections when an enzyme from one module is substantially sequestered by its substrate that belongs to a different module. Moreover, inferred networks may surprisingly depend on the choice of protein abundances that are experimentally perturbed, and also some inferred connections might be false. Here, we extend MRA by introducing a combined computational and experimental approach, which allows for a computational restoration of modular insulation, unmistakable network reconstruction and discrimination between solely regulatory and sequestration-induced connections for a range of signaling pathways. Although not universal, our approach extends MRA methods to signaling networks with retroactive interactions between modules arising from enzyme sequestration effects.

Authors: Daniel Lill, O. S. Rukhlenko, A. J. Mc Elwee, E. Kashdan, Jens Timmer, B. N. Kholodenko

Date Published: 1st Jun 2019

Journal: NPJ Syst Biol Appl

Abstract (Expand)

When non-linear models are fitted to experimental data, parameter estimates can be poorly constrained albeit being identifiable in principle. This means that along certain paths in parameter space, the log-likelihood does not exceed a given statistical threshold but remains bounded. This situation, denoted as practical non-identifiability, can be detected by Monte Carlo sampling or by systematic scanning using the profile likelihood method. In contrast, any method based on a Taylor expansion of the log-likelihood around the optimum, e.g., parameter uncertainty estimation by the Fisher Information Matrix, reveals no information about the boundedness at all. In this work, we present a geometric approach, approximating the original log-likelihood by geodesic coordinates of the model manifold. The Christoffel Symbols in the geodesic equation are fixed to those obtained from second order model sensitivities at the optimum. Based on three exemplary non-linear models we show that the information about the log-likelihood bounds and flat parameter directions can already be contained in this local information. Whereas the unbounded case represented by the Fisher Information Matrix is embedded in the geometric framework as vanishing Christoffel Symbols, non-vanishing constant Christoffel Symbols prove to define prototype non-linear models featuring boundedness and flat parameter directions of the log-likelihood. Finally, we investigate if those models could allow to approximate and replace computationally expensive objective functions originating from non-linear models by a surrogate objective function in parameter estimation problems.

Authors: Daniel Lill, Jens Timmer, Daniel Kaschek

Date Published: 3rd Jun 2019

Journal: PLoS ONE

Abstract (Expand)

Hepatoblastoma (HB), the most common pediatric primary liver neoplasm, shows nuclear localization of beta-catenin and yes-associated protein 1 (YAP1) in almost 80% of the cases. Co-expression of constitutively active S127A-YAP1 and DeltaN90 deletion-mutant beta-catenin (YAP1-DeltaN90-beta-catenin) causes HB in mice. Because heterogeneity in downstream signaling is being identified owing to mutational differences even in the beta-catenin gene alone, we investigated if co-expression of point mutants of beta-catenin (S33Y or S45Y) with S127A-YAP1 led to similar tumors as YAP1-DeltaN90-beta-catenin. Co-expression of S33Y/S45Y-beta-catenin and S127A-YAP1 led to activation of Yap and Wnt signaling and development of HB, with 100% mortality by 13 to 14 weeks. Co-expression with YAP1-S45Y/S33Y-beta-catenin of the dominant-negative T-cell factor 4 or dominant-negative transcriptional enhanced associate domain 2, the respective surrogate transcription factors, prevented HB development. Although histologically similar, HB in YAP1-S45Y/S33Y-beta-catenin, unlike YAP1-DeltaN90-beta-catenin HB, was glutamine synthetase (GS) positive. However, both DeltaN90-beta-catenin and point-mutant beta-catenin comparably induced GS-luciferase reporter in vitro. Finally, using a previously reported 16-gene signature, it was shown that YAP1-DeltaN90-beta-catenin HB tumors exhibited genetic similarities with more proliferative, less differentiated, GS-negative HB patient tumors, whereas YAP1-S33Y/S45Y-beta-catenin HB exhibited heterogeneity and clustered with both well-differentiated GS-positive and proliferative GS-negative patient tumors. Thus, we demonstrate that beta-catenin point mutants can also collaborate with YAP1 in HB development, albeit with a distinct molecular profile from the deletion mutant, which may have implications in both biology and therapy.

Authors: Q. Min, L. Molina, J. Li, A. O. Adebayo Michael, J. O. Russell, M. E. Preziosi, S. Singh, M. Poddar, Madlen Matz-Soja, S. Ranganathan, A. W. Bell, R. Gebhardt, F. Gaunitz, J. Yu, J. Tao, S. P. Monga

Date Published: 23rd Feb 2019

Journal: Am J Pathol

Abstract (Expand)

BACKGROUND & AIMS: The mammalian circadian clock controls various aspects of liver metabolism and integrates nutritional signals. Recently, we described Hedgehog (Hh) signaling as a novel regulator of liver lipid metabolism. Herein, we investigated crosstalk between hepatic Hh signaling and circadian rhythm. METHODS: Diurnal rhythms of Hh signaling were investigated in liver and hepatocytes from mice with ablation of Smoothened (SAC-KO) and crossbreeds with PER2::LUC reporter mice. By using genome-wide screening, qPCR, immunostaining, ELISA and RNAi experiments in vitro we identified relevant transcriptional regulatory steps. Shotgun lipidomics and metabolic cages were used for analysis of metabolic alterations and behavior. RESULTS: Hh signaling showed diurnal oscillations in liver and hepatocytes in vitro. Correspondingly, the level of Indian Hh, oscillated in serum. Depletion of the clock gene Bmal1 in hepatocytes resulted in significant alterations in the expression of Hh genes. Conversely, SAC-KO mice showed altered expression of clock genes, confirmed by RNAi against Gli1 and Gli3. Genome-wide screening revealed that SAC-KO hepatocytes showed time-dependent alterations in various genes, particularly those associated with lipid metabolism. The clock/hedgehog module further plays a role in rhythmicity of steatosis, and in the response of the liver to a high-fat diet or to differently timed starvation. CONCLUSIONS: For the first time, Hh signaling in hepatocytes was found to be time-of-day dependent and to feed back on the circadian clock. Our findings suggest an integrative role of Hh signaling, mediated mainly by GLI factors, in maintaining homeostasis of hepatic lipid metabolism by balancing the circadian clock. LAY SUMMARY: The results of our investigation show for the first time that the Hh signaling in hepatocytes is time-of-day dependent, leading to differences not only in transcript levels but also in the amount of Hh ligands in peripheral blood. Conversely, Hh signaling is able to feed back to the circadian clock.

Authors: E. Marbach-Breitruck, Madlen Matz-Soja, U. Abraham, W. Schmidt-Heck, S. Sales, Christiane Rennert, M. Kern, S. Aleithe, L. Spormann, C. Thiel, R. Gerlini, K. Arnold, N. Kloting, R. Guthke, D. Rozman, R. Teperino, A. Shevchenko, A. Kramer, R. Gebhardt

Date Published: 4th Feb 2019

Journal: J Hepatol

Abstract (Expand)

Background: The extent of resection and the frequency of liver surgery have increased over the past decades, enabled by improved haemostasis provided by electrosurgical liver dissection. Because extensive liver surgery is still associated with lethal complications, further optimisation of the technique and a better molecular understanding of hepatic wound healing and regeneration are needed. Systematic studies and a mouse model reflecting the clinical reality of liver surgery are lacking. Methods: We performed liver resection in mice with a monopolar electrocautery device in comparison to the classical en-bloc ligation method. Regeneration was assessed using liver weight and BrDU immunohistochemistry after sacrifice and non-invasively using micro computed tomography (µCT). Results: Mortality in the electrosurgical model was similar to the ligation method given an identical extent of resection. Regeneration of liver proceeded significantly faster in the electrosurgical group: Liver weight was 25.6% higher at sacrifice after 168h (p=0.0003). Concordantly, both µCT analysis (22.6% higher liver volume at 168h, p=0.008) and BrDU staining (71.4% higher proliferation at 72h, p=0.0005) indicated superior regeneration of liver after electrosurgical partial hepatectomy. Conclusions: The mode of liver resection has a profound impact on regeneration and should be studied molecularly using the presented novel model of electrosurgical liver resection.

Authors: W. von Schonfels, Clemens Schafmayer, Jochen Hampe

Date Published: No date defined

Journal: prepublication

Abstract (Expand)

Transcriptome profiling followed by differential gene expression analysis often leads to lists of genes that are hard to analyse and interpret. Functional genomic 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 (2,374). We believe that this resource, available for interactive exploration and download (, can have broad applications including the study of diseases and therapeutics.

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

Date Published: No date defined

Journal: Not specified

Abstract (Expand)

Many cellular organelles, including endosomes, show compartmentalization into distinct functional domains, which however cannot be resolved by diffraction-limited light microscopy. Single molecule localization microscopy (SMLM) offers nanoscale resolution but data interpretation is often inconclusive when the ultrastructural context is missing. Correlative light electron microscopy (CLEM) combining SMLM with electron microscopy (EM) enables correlation of functional sub-domains of organelles in relation to their underlying ultrastructure at nanometer resolution. However, the specific demands for EM sample preparation and the requirements for fluorescent single-molecule photo-switching are opposed. Here, we developed a novel superCLEM workflow that combines triple-colour SMLM (dSTORM & PALM) and electron tomography using semi-thin Tokuyasu thawed cryosections. We applied the superCLEM approach to directly visualize nanoscale compartmentalization of endosomes in HeLa cells. Internalized, fluorescently labelled Transferrin and EGF were resolved into morphologically distinct domains within the same endosome. We found that the small GTPase Rab5 is organized in nano-domains on the globular part of early endosomes. The simultaneous visualization of several proteins in functionally distinct endosomal sub-compartments demonstrates the potential of superCLEM to link the ultrastructure of organelles with their molecular organization at nanoscale resolution. This article is protected by copyright. All rights reserved.

Authors: C. Franke, U. Repnik, S. Segeletz, N. Brouilly, Y. Kalaidzidis, J. M. Verbavatz, Marino Zerial

Date Published: 17th Jun 2019

Journal: Traffic

Abstract (Expand)

Functional tissue architecture originates by self-assembly of distinct cell types, following tissue-specific rules of cell-cell interactions. In the liver, a structural model of the lobule was pioneered by Elias in 1949. This model, however, is in contrast with the apparent random 3D arrangement of hepatocytes. Since then, no significant progress has been made to derive the organizing principles of liver tissue. To solve this outstanding problem, we computationally reconstructed 3D tissue geometry from microscopy images of mouse liver tissue and analyzed it applying soft-condensed-matter-physics concepts. Surprisingly, analysis of the spatial organization of cell polarity revealed that hepatocytes are not randomly oriented but follow a long-range liquid-crystal order. This does not depend exclusively on hepatocytes receiving instructive signals by endothelial cells, since silencing Integrin-beta1 disrupted both liquid-crystal order and organization of the sinusoidal network. Our results suggest that bi-directional communication between hepatocytes and sinusoids underlies the self-organization of liver tissue.

Authors: H. Morales-Navarrete, H. Nonaka, A. Scholich, F. Segovia-Miranda, W. de Back, K. Meyer, R. L. Bogorad, V. Koteliansky, Lutz Brusch, Y. Kalaidzidis, F. Julicher, B. M. Friedrich, Marino Zerial

Date Published: 17th Jun 2019

Journal: Elife

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