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385 Publications visible to you, out of a total of 385
Computational Modeling of Lipid Metabolism in Yeast.

Abstract (Expand)

Lipid metabolism is essential for all major cell functions and has recently gained increasing attention in research and health studies. However, mathematical modeling by means of classical approaches … such as stoichiometric networks and ordinary differential equation systems has not yet provided satisfactory insights, due to the complexity of lipid metabolism characterized by many different species with only slight differences and by promiscuous multifunctional enzymes. Here, we present an object-oriented stochastic model approach as a way to cope with the complex lipid metabolic network. While all lipid species are treated objects in the model, they can be modified by the respective converting reactions based on reaction rules, a hybrid method that integrates benefits of agent-based and classical stochastic simulation. This approach allows to follow the dynamics of all lipid species with different fatty acids, different degrees of saturation and different headgroups over time and to analyze the effect of parameter changes, potential mutations in the catalyzing enzymes or provision of different precursors. Applied to yeast metabolism during one cell cycle period, we could analyze the distribution of all lipids to the various membranes in time-dependent manner. The presented approach allows to efficiently treat the complexity of cellular lipid metabolism and to derive conclusions on the time- and location-dependent distributions of lipid species and their properties such as saturation. It is widely applicable, easily extendable and will provide further insights in healthy and diseased states of cell metabolism.

Authors: V. Schutzhold, J. Hahn, K. Tummler, E. Klipp

Date Published: 27th Sep 2016

Publication Type: Not specified

L1 regularization facilitates detection of cell type-specific parameters in dynamical systems.

Abstract (Expand)

MOTIVATION: A major goal of drug development is to selectively target certain cell types. Cellular decisions influenced by drugs are often dependent on the dynamic processing of information. Selective … responses can be achieved by differences between the involved cell types at levels of receptor, signaling, gene regulation or further downstream. Therefore, a systematic approach to detect and quantify cell type-specific parameters in dynamical systems becomes necessary. RESULTS: Here, we demonstrate that a combination of nonlinear modeling with L1 regularization is capable of detecting cell type-specific parameters. To adapt the least-squares numerical optimization routine to L1 regularization, sub-gradient strategies as well as truncation of proposed optimization steps were implemented. Likelihood-ratio tests were used to determine the optimal regularization strength resulting in a sparse solution in terms of a minimal number of cell type-specific parameters that is in agreement with the data. By applying our implementation to a realistic dynamical benchmark model of the DREAM6 challenge we were able to recover parameter differences with an accuracy of 78%. Within the subset of detected differences, 91% were in agreement with their true value. Furthermore, we found that the results could be improved using the profile likelihood. In conclusion, the approach constitutes a general method to infer an overarching model with a minimum number of individual parameters for the particular models. AVAILABILITY AND IMPLEMENTATION: A MATLAB implementation is provided within the freely available, open-source modeling environment Data2Dynamics. Source code for all examples is provided online at http://www.data2dynamics.org/ CONTACT: bernhard.steiert@fdm.uni-freiburg.de.

Authors: B. Steiert, J. Timmer, C. Kreutz

Date Published: 3rd Sep 2016

Publication Type: Not specified

Driving the Model to Its Limit: Profile Likelihood Based Model Reduction.

Abstract (Expand)

In systems biology, one of the major tasks is to tailor model complexity to information content of the data. A useful model should describe the data and produce well-determined parameter estimates and … predictions. Too small of a model will not be able to describe the data whereas a model which is too large tends to overfit measurement errors and does not provide precise predictions. Typically, the model is modified and tuned to fit the data, which often results in an oversized model. To restore the balance between model complexity and available measurements, either new data has to be gathered or the model has to be reduced. In this manuscript, we present a data-based method for reducing non-linear models. The profile likelihood is utilised to assess parameter identifiability and designate likely candidates for reduction. Parameter dependencies are analysed along profiles, providing context-dependent suggestions for the type of reduction. We discriminate four distinct scenarios, each associated with a specific model reduction strategy. Iterating the presented procedure eventually results in an identifiable model, which is capable of generating precise and testable predictions. Source code for all toy examples is provided within the freely available, open-source modelling environment Data2Dynamics based on MATLAB available at http://www.data2dynamics.org/, as well as the R packages dMod/cOde available at https://github.com/dkaschek/. Moreover, the concept is generally applicable and can readily be used with any software capable of calculating the profile likelihood.

Authors: T. Maiwald, H. Hass, B. Steiert, J. Vanlier, R. Engesser, A. Raue, F. Kipkeew, H. H. Bock, D. Kaschek, C. Kreutz, J. Timmer

Date Published: 3rd Sep 2016

Publication Type: Not specified

The genetics of alcohol dependence and alcohol-related liver disease.

Abstract (Expand)

The susceptibility to developing alcohol dependence and significant alcohol-related liver injury is determined by a number of constitutional, environmental and genetic factors, although the nature and … level of interplay between them remains unclear. The familiality and heritability of alcohol dependence is well-documented but, to date, no strong candidate genes conferring increased risk have emerged, although variants in alcohol dehydrogenase and acetaldehyde dehydrogenase have been shown to confer protection, predominantly in individuals of East Asian ancestry. Population contamination with confounders such as drug co-dependence and psychiatric and physical co-morbidity may explain the essentially negative genome-wide association studies in this disorder. The familiality and hereditability of alcohol-related cirrhosis is not as well-documented but three strong candidate genes PNPLA3, TM6SF2 and MBOAT7, have been identified. The mechanisms by which variants in these genes confer risk and the nature of the functional interplay between them remains to be determined but, when elucidated, will undoubtedly increase our understanding of the pathophysiology of this disease. The way in which this genetic information could potentially inform patient management has yet to be determined and tested.

Authors: F. Stickel, C. Moreno, J. Hampe, M. Y. Morgan

Date Published: 27th Aug 2016

Publication Type: Not specified

Identification of Cell Type-Specific Differences in Erythropoietin Receptor Signaling in Primary Erythroid and Lung Cancer Cells.

Abstract (Expand)

Lung cancer, with its most prevalent form non-small-cell lung carcinoma (NSCLC), is one of the leading causes of cancer-related deaths worldwide, and is commonly treated with chemotherapeutic drugs … such as cisplatin. Lung cancer patients frequently suffer from chemotherapy-induced anemia, which can be treated with erythropoietin (EPO). However, studies have indicated that EPO not only promotes erythropoiesis in hematopoietic cells, but may also enhance survival of NSCLC cells. Here, we verified that the NSCLC cell line H838 expresses functional erythropoietin receptors (EPOR) and that treatment with EPO reduces cisplatin-induced apoptosis. To pinpoint differences in EPO-induced survival signaling in erythroid progenitor cells (CFU-E, colony forming unit-erythroid) and H838 cells, we combined mathematical modeling with a method for feature selection, the L1 regularization. Utilizing an example model and simulated data, we demonstrated that this approach enables the accurate identification and quantification of cell type-specific parameters. We applied our strategy to quantitative time-resolved data of EPO-induced JAK/STAT signaling generated by quantitative immunoblotting, mass spectrometry and quantitative real-time PCR (qRT-PCR) in CFU-E and H838 cells as well as H838 cells overexpressing human EPOR (H838-HA-hEPOR). The established parsimonious mathematical model was able to simultaneously describe the data sets of CFU-E, H838 and H838-HA-hEPOR cells. Seven cell type-specific parameters were identified that included for example parameters for nuclear translocation of STAT5 and target gene induction. Cell type-specific differences in target gene induction were experimentally validated by qRT-PCR experiments. The systematic identification of pathway differences and sensitivities of EPOR signaling in CFU-E and H838 cells revealed potential targets for intervention to selectively inhibit EPO-induced signaling in the tumor cells but leave the responses in erythroid progenitor cells unaffected. Thus, the proposed modeling strategy can be employed as a general procedure to identify cell type-specific parameters and to recommend treatment strategies for the selective targeting of specific cell types.

Authors: R. Merkle, B. Steiert, F. Salopiata, S. Depner, A. Raue, N. Iwamoto, M. Schelker, H. Hass, M. Wasch, M. E. Bohm, O. Mucke, D. B. Lipka, C. Plass, W. D. Lehmann, C. Kreutz, J. Timmer, M. Schilling, U. Klingmuller

Date Published: 6th Aug 2016

Publication Type: Not specified

Delta-Like Ligand 4 Modulates Liver Damage by Down-Regulating Chemokine Expression

Abstract

Not specified

Authors: Zhe Shen, Yan Liu, Bedair Dewidar, Junhao Hu, Ogyi Park, Teng Feng, Chengfu Xu, Chaohui Yu, Qi Li, Christoph Meyer, Iryna Ilkavets, Alexandra Müller, Carolin Stump-Guthier, Stefan Munker, Roman Liebe, Vincent Zimmer, Frank Lammert, Peter R. Mertens, Hai Li, Peter ten Dijke, Hellmut G. Augustin, Jun Li, Bin Gao, Matthias P. Ebert, Steven Dooley, Youming Li, Hong-Lei Weng

Date Published: 1st Jul 2016

Publication Type: Not specified

Comparison of Gene Expression Patterns Between Mouse Models of Nonalcoholic Fatty Liver Disease and Liver Tissues From Patients.

Abstract (Expand)

BACKGROUND & AIMS: Nonalcoholic fatty liver disease (NAFLD) is the most common chronic liver disorder in industrialized countries. Mouse models of NAFLD have been used in studies of pathogenesis … and treatment, and have certain features of the human disease. We performed a systematic transcriptome-wide analysis of liver tissues from patients at different stages of NAFLD progression (ranging from healthy obese individuals to those with steatosis), as well as rodent models of NAFLD, to identify those that most closely resemble human disease progression in terms of gene expression patterns. METHODS: We performed a systematic evaluation of genome-wide messenger RNA expression using liver tissues collected from mice fed a standard chow diet (controls) and 9 mouse models of NAFLD: mice on a high-fat diet (with or without fructose), mice on a Western-type diet, mice on a methionine- and choline-deficient diet, mice on a high-fat diet given streptozotocin, and mice with disruption of Pten in hepatocytes. We compared gene expression patterns with those of liver tissues from 25 patients with nonalcoholic steatohepatitis (NASH), 27 patients with NAFLD, 15 healthy obese individuals, and 39 healthy nonobese individuals (controls). Liver samples were obtained from patients undergoing liver biopsy for suspected NAFLD or NASH, or during liver or bariatric surgeries. Data sets were analyzed using the limma R-package. Overlap of functional profiles was analyzed by gene set enrichment analysis profiles. RESULTS: We found differences between human and mouse transcriptomes to be significantly larger than differences between disease stages or models. Of the 65 genes with significantly altered expression in patients with NASH and 177 genes with significantly altered expression in patients with NAFLD, compared with controls, only 1-18 of these genes also differed significantly in expression between mouse models of NAFLD and control mice. However, expression of genes that regulate pathways associated with the development of NAFLD were altered in some mouse models (such as pathways associated with lipid metabolism). On a pathway level, gene expression patterns in livers of mice on the high-fat diet were associated more closely with human fatty liver disease than other models. CONCLUSIONS: In comparing gene expression profiles between liver tissues from different mouse models of NAFLD and patients with different stages of NAFLD, we found very little overlap. Our data set is available for studies of pathways that contribute to the development of NASH and NAFLD and selection of the most applicable mouse models (http://www.nash-profiler.com).

Authors: A. Teufel, T. Itzel, W. Erhart, M. Brosch, X. Y. Wang, Y. O. Kim, W. von Schonfels, A. Herrmann, S. Bruckner, F. Stickel, J. F. Dufour, T. Chavakis, C. Hellerbrand, R. Spang, T. Maass, T. Becker, S. Schreiber, C. Schafmayer, D. Schuppan, J. Hampe

Date Published: 19th Jun 2016

Publication Type: Not specified

Evolving Insights on Metabolism, Autophagy, and Epigenetics in Liver Myofibroblasts.

Abstract (Expand)

Liver myofibroblasts (MFB) are crucial mediators of extracellular matrix (ECM) deposition in liver fibrosis. They arise mainly from hepatic stellate cells (HSCs) upon a process termed "activation." … To a lesser extent, and depending on the cause of liver damage, portal fibroblasts, mesothelial cells, and fibrocytes may also contribute to the MFB population. Targeting MFB to reduce liver fibrosis is currently an area of intense research. Unfortunately, a clog in the wheel of antifibrotic therapies is the fact that although MFB are known to mediate scar formation, and participate in liver inflammatory response, many of their molecular portraits are currently unknown. In this review, we discuss recent understanding of MFB in health and diseases, focusing specifically on three evolving research fields: metabolism, autophagy, and epigenetics. We have emphasized on therapeutic prospects where applicable and mentioned techniques for use in MFB studies. Subsequently, we highlighted uncharted territories in MFB research to help direct future efforts aimed at bridging gaps in current knowledge.

Authors: Z. C. Nwosu, H. Alborzinia, S. Wolfl, S. Dooley, Y. Liu

Date Published: 18th Jun 2016

Publication Type: Not specified

Transforming Growth Factor β1 (TGF-β1) Activates Hepcidin mRNA Expression in Hepatocytes

Abstract

Not specified

Authors: Simeng Chen, Teng Feng, Maja Vujić Spasić, Sandro Altamura, Katja Breitkopf-Heinlein, Jutta Altenöder, Thomas S. Weiss, Steven Dooley, Martina U. Muckenthaler

Date Published: 17th Jun 2016

Publication Type: Not specified

Gender, Contraceptives and Individual Metabolic Predisposition Shape a Healthy Plasma Lipidome.

Abstract (Expand)

Lipidomics of human blood plasma is an emerging biomarker discovery approach that compares lipid profiles under pathological and physiologically normal conditions, but how a healthy lipidome varies … within the population is poorly understood. By quantifying 281 molecular species from 27 major lipid classes in the plasma of 71 healthy young Caucasians whose 35 clinical blood test and anthropometric indices matched the medical norm, we provided a comprehensive, expandable and clinically relevant resource of reference molar concentrations of individual lipids. We established that gender is a major lipidomic factor, whose impact is strongly enhanced by hormonal contraceptives and mediated by sex hormone-binding globulin. In lipidomics epidemiological studies should avoid mixed-gender cohorts and females taking hormonal contraceptives should be considered as a separate sub-cohort. Within a gender-restricted cohort lipidomics revealed a compositional signature that indicates the predisposition towards an early development of metabolic syndrome in ca. 25% of healthy male individuals suggesting a healthy plasma lipidome as resource for early biomarker discovery.

Authors: S. Sales, J. Graessler, S. Ciucci, R. Al-Atrib, T. Vihervaara, K. Schuhmann, D. Kauhanen, M. Sysi-Aho, S. R. Bornstein, M. Bickle, C. V. Cannistraci, K. Ekroos, A. Shevchenko

Date Published: 14th Jun 2016

Publication Type: Not specified

A targeted analysis reveals relevant shifts in the methylation and transcription of genes responsible for bile acid homeostasis and drug metabolism in non-alcoholic fatty liver disease.

Abstract (Expand)

BACKGROUND: Non-alcoholic fatty liver disease (NAFLD) is associated with a high risk for liver cirrhosis and cancer. Recent studies demonstrate that NAFLD significantly impacts on the genome wide … methylation and expression reporting top hit genes to be associated with e.g. diabetes mellitus. In a targeted analysis we specifically investigate to what extent NAFLD is associated with methylation and transcriptional changes in gene networks responsible for drug metabolism (DM) and bile acid (BA) homeostasis, which may trigger liver and system toxic events. METHODS: We performed a systematic analysis of 73 genes responsible for BA homeostasis and DM based on liver derived methylation and expression data from three cohort studies including 103 NAFLD and 75 non-NAFLD patients. Using multiple linear regression models, we detected methylation differences in proximity to the transcriptional start site of these genes in two NAFLD cohorts and correlated the methylation of significantly changed CpG sites to transcriptional expression in a third cohort using robust multiple linear regression approaches. RESULTS: We detected 64 genes involved in BA homeostasis and DM to be significantly differentially methylated. In 26 of these genes, methylation significantly correlated with RNA expression, detecting i.e. genes such as CYP27A1, OSTa, and SLC27A5 (BA homeostasis), and SLCO2B1, SLC47A1, and several UGT and CYP genes (DM) to be NAFLD dependently modulated. CONCLUSIONS: NAFLD is associated with significant shifts in the methylation of key genes responsible for BA and DM that are associated with transcriptional modulations. These findings have implications for BA composition, BA regulated metabolic pathways and for drug safety and efficacy.

Authors: H. B. Schioth, A. Bostrom, S. K. Murphy, W. Erhart, J. Hampe, C. Moylan, J. Mwinyi

Date Published: 14th Jun 2016

Publication Type: Not specified

Toward Community Standards and Software for Whole-Cell Modeling.

Abstract (Expand)

OBJECTIVE: Whole-cell (WC) modeling is a promising tool for biological research, bioengineering, and medicine. However, substantial work remains to create accurate comprehensive models of complex cells. … METHODS: We organized the 2015 Whole-Cell Modeling Summer School to teach WC modeling and evaluate the need for new WC modeling standards and software by recoding a recently published WC model in the Systems Biology Markup Language. RESULTS: Our analysis revealed several challenges to representing WC models using the current standards. CONCLUSION: We, therefore, propose several new WC modeling standards, software, and databases. SIGNIFICANCE: We anticipate that these new standards and software will enable more comprehensive models.

Authors: D. Waltemath, J. R. Karr, F. T. Bergmann, V. Chelliah, M. Hucka, M. Krantz, W. Liebermeister, P. Mendes, C. J. Myers, P. Pir, B. Alaybeyoglu, N. K. Aranganathan, K. Baghalian, A. T. Bittig, P. E. Burke, M. Cantarelli, Y. H. Chew, R. S. Costa, J. Cursons, T. Czauderna, A. P. Goldberg, H. F. Gomez, J. Hahn, T. Hameri, D. F. Gardiol, D. Kazakiewicz, I. Kiselev, V. Knight-Schrijver, C. Knupfer, M. Konig, D. Lee, A. Lloret-Villas, N. Mandrik, J. K. Medley, B. Moreau, H. Naderi-Meshkin, S. K. Palaniappan, D. Priego-Espinosa, M. Scharm, M. Sharma, K. Smallbone, N. J. Stanford, J. H. Song, T. Theile, M. Tokic, N. Tomar, V. Toure, J. Uhlendorf, T. M. Varusai, L. H. Watanabe, F. Wendland, M. Wolfien, J. T. Yurkovich, Y. Zhu, A. Zardilis, A. Zhukova, F. Schreiber

Date Published: 10th Jun 2016

Publication Type: Not specified

Hedgehog signaling is a potent regulator of liver lipid metabolism and reveals a GLI-code associated with steatosis.

Abstract (Expand)

Non-alcoholic fatty liver disease (NAFLD) is the most common liver disease in industrialized countries and is increasing in prevalence. The pathomechanisms, however, are poorly understood. This study … assessed the unexpected role of the Hedgehog pathway in adult liver lipid metabolism. Using transgenic mice with conditional hepatocyte-specific deletion of Smoothened in adult mice, we showed that hepatocellular inhibition of Hedgehog signaling leads to steatosis by altering the abundance of the transcription factors GLI1 and GLI3. This steatotic 'Gli-code' caused the modulation of a complex network of lipogenic transcription factors and enzymes, including SREBP1 and PNPLA3, as demonstrated by microarray analysis and siRNA experiments and could be confirmed in other steatotic mouse models as well as in steatotic human livers. Conversely, activation of the Hedgehog pathway reversed the "Gli-code" and mitigated hepatic steatosis. Collectively, our results reveal that dysfunctions in the Hedgehog pathway play an important role in hepatic steatosis and beyond.

Authors: M. Matz-Soja, C. Rennert, K. Schonefeld, S. Aleithe, J. Boettger, W. Schmidt-Heck, T. S. Weiss, A. Hovhannisyan, S. Zellmer, N. Kloting, A. Schulz, J. Kratzsch, R. Guthke, R. Gebhardt

Date Published: 17th May 2016

Publication Type: Not specified

DNA Methylation of ADME Genes.

Abstract (Expand)

The epigenetic regulation of expression of genes involved in the absorption, distribution, metabolism, and excretion (ADME) of drugs contributes to interindividual variability in drug response. Epigenetic … mechanisms include DNA methylation, histone modifications, and miRNAs. This review systematically outlines the influence of DNA methylation on ADME gene expression and highlights the consequences for interindividual variability in drug response or drug-induced toxicity and the implications for personalized medicine.

Authors: P. Fisel, E. Schaeffeler, M. Schwab

Date Published: 12th Apr 2016

Publication Type: Not specified

TGF-β1 and TGF-β2 abundance in liver diseases of mice and men

Abstract

Not specified

Authors: Anne Dropmann, Tatjana Dediulia, Katja Breitkopf-Heinlein, Hanna Korhonen, Michel Janicot, Susanne N. Weber, Maria Thomas, Albrecht Piiper, Esther Bertran, Isabel Fabregat, Kerstin Abshagen, Jochen Hess, Peter Angel, Cédric Coulouarn, Steven Dooley, Nadja M. Meindl-Beinker

Date Published: 12th Apr 2016

Publication Type: Not specified

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