Abstract (Expand)

Computational systems biology involves integrating heterogeneous datasets in order to generate models. These models can assist with understanding and prediction of biological phenomena. Generating datasets and integrating them into models involves a wide range of scientific expertise. As a result these datasets are often collected by one set of researchers, and exchanged with others researchers for constructing the models. For this process to run smoothly the data and models must be FAIR-findable, accessible, interoperable, and reusable. In order for data and models to be FAIR they must be structured in consistent and predictable ways, and described sufficiently for other researchers to understand them. Furthermore, these data and models must be shared with other researchers, with appropriately controlled sharing permissions, before and after publication. In this chapter we explore the different data and model standards that assist with structuring, describing, and sharing. We also highlight the popular standards and sharing databases within computational systems biology.

Authors: N. J. Stanford, M. Scharm, P. D. Dobson, Martin Golebiewski, M. Hucka, V. B. Kothamachu, D. Nickerson, S. Owen, J. Pahle, U. Wittig, D. Waltemath, C. Goble, P. Mendes, J. Snoep

Date Published: 12th Oct 2019

Journal: Methods Mol Biol

Abstract (Expand)

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, Annika 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

Journal: Cells

Abstract (Expand)

Early disease diagnosis is key to the effective treatment of diseases. Histopathological analysis of human biopsies is the gold standard to diagnose tissue alterations. However, this approach has low resolution and overlooks 3D (three-dimensional) structural changes resulting from functional alterations. Here, we applied multiphoton imaging, 3D digital reconstructions and computational simulations to generate spatially resolved geometrical and functional models of human liver tissue at different stages of non-alcoholic fatty liver disease (NAFLD). We identified a set of morphometric cellular and tissue parameters correlated with disease progression, and discover profound topological defects in the 3D bile canalicular (BC) network. Personalized biliary fluid dynamic simulations predicted an increased pericentral biliary pressure and micro-cholestasis, consistent with elevated cholestatic biomarkers in patients' sera. Our spatially resolved models of human liver tissue can contribute to high-definition medicine by identifying quantitative multiparametric cellular and tissue signatures to define disease progression and provide new insights into NAFLD pathophysiology.

Authors: Fabian Segovia Miranda, H. Morales-Navarrete, Michael Kücken, Vincent Moser, S. Seifert, U. Repnik, Fabian Rost, Mario Brosch, A. Hendricks, S. Hinz, C. Rocken, D. Lutjohann, Y. Kalaidzidis, Clemens Schafmayer, Lutz Brusch, Jochen Hampe, Marino Zerial

Date Published: 2nd Dec 2019

Journal: Nat Med

Abstract (Expand)

The intricate (micro)vascular architecture of the liver has not yet been fully unravelled. Although current models are often idealized simplifications of the complex anatomical reality, correct morphological information is instrumental for scientific and clinical purposes. Previously, both vascular corrosion casting (VCC) and immunohistochemistry (IHC) have been separately used to study the hepatic vasculature. Nevertheless, these techniques still face a number of challenges such as dual casting in VCC and limited imaging depths for IHC. We have optimized both techniques and combined their complementary strengths to develop a framework for multilevel reconstruction of the hepatic circulation in the rat. The VCC and micro-CT scanning protocol was improved by enabling dual casting, optimizing the contrast agent concentration, and adjusting the viscosity of the resin (PU4ii). IHC was improved with an optimized clearing technique (CUBIC) that extended the imaging depth for confocal microscopy more than five-fold. Using in-house developed software (DeLiver), the vascular network - in both VCC and IHC datasets - was automatically segmented and/or morphologically analysed. Our methodological framework allows 3D reconstruction and quantification of the hepatic circulation, ranging from the major blood vessels down to the intertwined and interconnected sinusoids. We believe that the presented framework will have value beyond studies of the liver, and will facilitate a better understanding of various parenchymal organs in general, in physiological and pathological circumstances.

Authors: Geert Peeters, Charlotte Debbaut, Wim Laleman, Adrian Friebel, Diethard Monbaliu, Ingrid Vander Elst, Jan R Detrez, Tim Vandecasteele, Tim Johann, Thomas De Schryver, Luc Van Hoorebeke, Kasper Favere, Jonas Verbeke, Dirk Drasdo, Stefan Hoehme, Patrick Segers, Pieter Cornillie, Winnok H De Vos

Date Published: 28th Dec 2016

Journal: Journal of anatomy

Abstract (Expand)

Non-alcoholic fatty liver disease (NAFLD) is frequent among obese individuals with metabolic syndrome. Variants PNPLA3 p.I148M, TM6SF2 p.E167K and MBOAT7 rs641738 are associated with higher liver fat contents. Here we analyzed 63 biopsied non-obese, non-diabetic patients with NAFLD (39 men, age: 20-72 years) recruited within the German NAFLD CSG program. The frequencies of the PNPLA3, TM6SF2 and MBOAT7 polymorphisms were compared with the remaining patients in the NAFLD CSG cohort and with a control population (n = 174). Serum CK18-M30 was measured by ELISA. In non-obese NAFLD patients, the frequency of the PNPLA3 p.I148M allele (74.6%), but not of the TM6SF2 or MBOAT7 polymorphisms, was significantly (P < 0.05) higher as compared to the other patients in the NAFLD CSG cohort (54.9%) or controls (40.2%). The presence of the minor PNPLA3 p.I148M risk allele increased the risk of developing NAFLD (OR = 3.29, P < 0.001) and was associated with higher steatosis, fibrosis, and serum CK18-M30 levels (all P < 0.05). According to the population attributable fraction (PAF), 49.8% of NAFLD cases could be eliminated if the PNPLA3 mutation was absent. The MBOAT7 polymorphism was more frequent (P = 0.019) in patients with severe hepatic steatosis. In conclusion, PNPLA3, and to a lesser extent, MBOAT7 variants are associated with NAFLD risk and modulate liver injury in non-obese patients without diabetes.

Authors: M. Krawczyk, H. Bantel, M. Rau, J. M. Schattenberg, F. Grunhage, A. Pathil, M. Demir, J. Kluwe, T. Boettler, Susanne Weber, A. Geier, Frank Lammert

Date Published: 28th Feb 2018

Journal: J Hum Genet

Abstract (Expand)

Alternative models explaining the biliary lipid secretion at the canalicular membrane of hepatocytes exist: successive lipid extraction by preformed bile salt micelles, or budding of membrane fragments with formation of mixed micelles. To test the feasibility of the latter mechanism, we developed a mathematical model that describes the formation of lipid microdomains in the canalicular membrane. Bile salt monomers intercalate into the external hemileaflet of the canalicular membrane, to form a rim to liquid disordered domain patches that then pinch off to form nanometer-scale mixed micelles. Model simulations perfectly recapitulate the measured dependence of bile salt-dependent biliary lipid extraction rates upon modulation of the membrane cholesterol (lack or overexpression of the cholesterol transporter Abcg5-Abcg8) and phosphatidylcholine (lack of Mdr2, also known as Abcb4) content. The model reveals a strong dependence of the biliary secretion rate on the protein density of the membrane. Taken together, the proposed model is consistent with crucial experimental findings in the field and provides a consistent explanation of the central molecular processes involved in bile formation.

Authors: Johannes Eckstein, Hergo Holzhütter, N. Berndt

Date Published: 1st Mar 2018

Journal: J Cell Sci

Abstract (Expand)

The purpose of this study was to analyze full-field-of-view maps of renal shear wave speed (SWS) measured by time-harmonic elastography (THE) in healthy volunteers in terms of reproducibility, regional variation and physiologic effects. The kidneys of 37 healthy volunteers were investigated by multifrequency THE. The complete renal parenchyma, as well as cortex and medulla, was analyzed. A subgroup was investigated to test reproducibility (n = 3). Significant differences between SWS in cortex, medulla and full parenchyma were observed (2.10 +/- 0.17, 1.35 +/- 0.11 and 1.71 +/- 0.16 m/s, all p values < 0.001) with mean intra-volunteer standard deviations of repeated measurements of 0.04 m/s (1.6%), 0.06 m/s (4.0%) and 0.08 m/s (4.5%), respectively. No effects of kidney anatomy, age, body mass index, blood pressure and heart rate on SWS were observed. THE allows generation of full-field-of-view SWS maps of native kidneys with high reproducibility.

Authors: S. R. Marticorena Garcia, M. Grossmann, S. T. Lang, M. Nguyen Trong, M. Schultz, Jing Guo, B. Hamm, J. Braun, I. Sack, H. Tzschatzsch

Date Published: 27th Feb 2018

Journal: Ultrasound Med Biol

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: 2019

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

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