Publications

246 Publications visible to you, out of a total of 246

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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

Not specified

Authors: Kamalakannan Radhakrishnan, Yong-Hoon Kim, Yoon Seok Jung, Jina Kim, Don-Kyu Kim, Sung Jin Cho, In-Kyu Lee, Steven Dooley, Chul-Ho Lee, Hueng-Sik Choi

Date Published: 1st Oct 2020

Publication Type: Journal

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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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BACKGROUND & AIMS: A common genetic variant near MBOAT7 (rs641738C>T) has been previously associated with hepatic fat and advanced histology in non-alcoholic fatty liver disease (NAFLD), however, these findings have not been consistently replicated in the literature. We aimed to establish whether rs641738C>T is a risk factor across the spectrum of NAFLD and characterize its role in the regulation of related metabolic phenotypes through meta-analysis. METHODS: We performed meta-analysis of studies with data on the association between rs641738C>T genotype and: liver fat, NAFLD histology, and serum ALT, lipids, or insulin. These included directly genotyped studies and population-level data from genome-wide association studies (GWAS). We performed random effects meta-analysis using recessive, additive, and dominant genetic models. RESULTS: Data from 1,066,175 participants (9,688 with liver biopsies) across 42 studies were included in the meta-analysis. rs641738C>T was associated with higher liver fat on CT/MRI (+0.03 standard deviations [95% CI: 0.02 - 0.05], pz=4.8x10(-5)) and diagnosis of NAFLD (OR 1.17 [95% CI 1.05 - 1.3], pz=0.003) in Caucasian adults. The variant was also positively associated with presence of advanced fibrosis (OR 1.22 [95% CI: 1.03 - 1.45], pz=0.021) in Caucasian adults using a recessive model of inheritance (CC+CT vs. TT). Meta-analysis of data from previous GWAS found the variant to be associated with higher ALT (pz=0.002) and lower serum triglycerides (pz=1.5x10(-4)). rs641738C>T was not associated with fasting insulin and no effect was observed in children with NAFLD. CONCLUSION: Our study validates rs641738C>T near MBOAT7 as a risk factor for the presence and severity of NAFLD in individuals of European descent.

Authors: K. Teo, K. W. M. Abeysekera, L. Adams, E. Aigner, Q. M. Anstee, J. M. Banales, R. Banerjee, P. Basu, T. Berg, P. Bhatnagar, S. Buch, A. Canbay, S. Caprio, A. Chatterjee, Y. D. Ida Chen, A. Chowdhury, A. K. Daly, C. Datz, D. de Gracia Hahn, J. K. DiStefano, J. Dong, A. Duret, C. Emdin, M. Fairey, G. S. Gerhard, X. Guo, J. Hampe, M. Hickman, L. Heintz, C. Hudert, H. Hunter, M. Kelly, J. Kozlitina, M. Krawczyk, F. Lammert, C. Langenberg, J. Lavine, L. Li, H. K. Lim, R. Loomba, P. K. Luukkonen, P. E. Melton, T. A. Mori, N. D. Palmer, C. A. Parisinos, S. G. Pillai, F. Qayyum, M. C. Reichert, S. Romeo, J. I. Rotter, Y. R. Im, N. Santoro, C. Schafmayer, E. K. Speliotes, S. Stender, F. Stickel, C. D. Still, P. Strnad, K. D. Taylor, A. Tybjaerg-Hansen, G. R. Umano, M. Utukuri, L. Valenti, L. E. Wagenknecht, N. J. Wareham, R. M. Watanabe, J. Wattacheril, H. Yaghootkar, H. Yki-Jarvinen, K. A. Young, J. P. Mann

Date Published: 31st Aug 2020

Publication Type: Journal

Abstract (Expand)

Physiological liver cell replacement is central to maintaining the organ’s high metabolic activity, although its characteristics are difficult to study in humans. Using retrospective 14C birth dating of cells, we report that human hepatocytes show continuous and lifelong turnover, maintaining the liver a young organ (average age < 3 years). Hepatocyte renewal is highly dependent on the ploidy level. Diploid hepatocytes show an seven-fold higher annual exchange rate than polyploid hepatocytes. These observations support the view that physiological liver cell renewal in humans is mainly dependent on diploid hepatocytes, whereas polyploid cells are compromised in their ability to divide. Moreover, cellular transitions between these two subpopulations are limited, with minimal contribution to the respective other ploidy class under homeostatic conditions. With these findings, we present a new integrated model of homeostatic liver cell generation in humans that provides fundamental insights into liver cell turnover dynamics.

Authors: Paula Heinke, Fabian Rost, Julian Rode, Thilo Welsch, Kanar Alkass, Joshua Feddema, Mehran Salehpour, Göran Possnert, Henrik Druid, Lutz Brusch, Olaf Bergmann

Date Published: 7th Aug 2020

Publication Type: Unpublished

Abstract (Expand)

Biological models often contain elements that have inexact numerical values, since they are based on values that are stochastic in nature or data that contains uncertainty. The Systems Biology Markup Language (SBML) Level 3 Core specification does not include an explicit mechanism to include inexact or stochastic values in a model, but it does provide a mechanism for SBML packages to extend the Core specification and add additional syntactic constructs. The SBML Distributions package for SBML Level 3 adds the necessary features to allow models to encode information about the distribution and uncertainty of values underlying a quantity.

Authors: Lucian P. Smith, Stuart L. Moodie, Frank T. Bergmann, Colin Gillespie, Sarah M. Keating, Matthias König, Chris J. Myers, Maciek J. Swat, Darren J. Wilkinson, Michael Hucka

Date Published: 1st Aug 2020

Publication Type: Journal

Abstract (Expand)

In the liver, energy homeostasis is mainly regulated by mechanistic target of rapamycin (mTOR) signalling, which influences relevant metabolic pathways, including lipid metabolism. However, the Hedgehog (Hh) pathway is one of the newly identified drivers of hepatic lipid metabolism. Although the link between mTOR and Hh signalling was previously demonstrated in cancer development and progression, knowledge of their molecular crosstalk in healthy liver is lacking. To close this information gap, we used a transgenic mouse model, which allows hepatocyte-specific deletion of the Hh pathway, and in vitro studies to reveal interactions between Hh and mTOR signalling. The study was conducted in male and female mice to investigate sexual differences in the crosstalk of these signalling pathways. Our results reveal that the conditional Hh knockout reduces mitochondrial adenosine triphosphate (ATP) production in primary hepatocytes from female mice and inhibits autophagy in hepatocytes from both sexes. Furthermore, in vitro studies show a synergistic effect of cyclopamine and rapamycin on the inhibition of mTor signalling and oxidative respiration in primary hepatocytes from male and female C57BL/6N mice. Overall, our results demonstrate that the impairment of Hh signalling influences mTOR signalling and therefore represses oxidative phosphorylation and autophagy.

Authors: Luise Spormann, Christiane Rennert, Erik Kolbe, Fritzi Ott, Carolin Lossius, Robert Lehmann, Rolf Gebhardt, Thomas Berg, Madlen Matz-Soja

Date Published: 1st Aug 2020

Publication Type: Journal

Abstract (Expand)

AIMS: Unlike other Toll-like receptors (TLRs), the role of toll like receptor 2 (TLR-2) in the pathogenesis of chronic liver disease and hepatocellular carcinoma (HCC) is not well studied. We, therefore, set out to investigate the expression of TLR-2 in different chronic liver disease states along with other markers of cell death, cellular proliferation and tissue vascularisation METHODS AND RESULTS: Immunohistochemistry was performed on liver tissue microarrays comprising hepatitis, cirrhosis and HCC patient samples using antibodies against TLR-2, Ki-67, Caspase-3 and VEGF. This was done in order to characterise receptor expression and translocation, apoptosis, cell proliferation and vascularisation. Cytoplasmic TLR-2 expression was found to be weak in 5/8 normal liver cases, 10/19 hepatitis cases and 8/21 cirrhosis patients. Moderate to strong TLR-2 expression was observed in some cases of hepatitis and cirrhosis. Both, nuclear and cytoplasmic TLR-2 expression was present in HCC with weak intensity in 11/41 cases, and moderate to strong staining in 19/41 cases. Eleven HCC cases were TLR-2 negative. Surprisingly, both cytoplasmic and nuclear TLR-2 expression in HCC were found to significantly correlate with proliferative index (r = 0.24 and 0.37), Caspase-3 expression (r = 0.27 and 0.38) and vascularisation (r = 0.56 and 0.23). Further, nuclear TLR-2 localisation was predominant in HCC, whereas cytoplasmic expression was more prevalent in hepatitis and cirrhosis. Functionally, treatment of HUH7 HCC cells with a TLR-2 agonist induced the expression of cellular proliferation and vascularisation markers CD34 and VEGF. CONCLUSIONS: Our results demonstrate a positive correlation between the expression of TLR-2 and other markers of proliferation and vascularisation in HCC which suggests a possible role for TLR-2 in HCC pathogenesis.

Authors: F. E. A. Mohamed, S. Hammad, T. V. Luong, B. Dewidar, R. Al-Jehani, N. Davies, S. Dooley, R. Jalan

Date Published: 25th Jul 2020

Publication Type: Journal

Abstract (Expand)

Despite the ever-progressing technological advances in producing data in health and clinical research, the generation of new knowledge for medical benefits through advanced analytics still lags behind its full potential. Reasons for this obstacle are the inherent heterogeneity of data sources and the lack of broadly accepted standards. Further hurdles are associated with legal and ethical issues surrounding the use of personal/patient data across disciplines and borders. Consequently, there is a need for broadly applicable standards compliant with legal and ethical regulations that allow interpretation of heterogeneous health data through in silico methodologies to advance personalized medicine. To tackle these standardization challenges, the Horizon2020 Coordinating and Support Action EU-STANDS4PM initiated an EU-wide mapping process to evaluate strategies for data integration and data-driven in silico modelling approaches to develop standards, recommendations and guidelines for personalized medicine. A first step towards this goal is a broad stakeholder consultation process initiated by an EU-STANDS4PM workshop at the annual COMBINE meeting (COMBINE 2019 workshop report in same issue). This forum analysed the status quo of data and model standards and reflected on possibilities as well as challenges for cross-domain data integration to facilitate in silico modelling approaches for personalized medicine.

Authors: S. Brunak, C. Bjerre Collin, K. Eva O Cathaoir, M. Golebiewski, M. Kirschner, I. Kockum, H. Moser, D. Waltemath

Date Published: 24th Jul 2020

Publication Type: Journal

Abstract (Expand)

Tightly interlinked feedback regulators control the dynamics of intracellular responses elicited by the activation of signal transduction pathways. Interferon alpha (IFNalpha) orchestrates antiviral responses in hepatocytes, yet mechanisms that define pathway sensitization in response to prestimulation with different IFNalpha doses remained unresolved. We establish, based on quantitative measurements obtained for the hepatoma cell line Huh7.5, an ordinary differential equation model for IFNalpha signal transduction that comprises the feedback regulators STAT1, STAT2, IRF9, USP18, SOCS1, SOCS3, and IRF2. The model-based analysis shows that, mediated by the signaling proteins STAT2 and IRF9, prestimulation with a low IFNalpha dose hypersensitizes the pathway. In contrast, prestimulation with a high dose of IFNalpha leads to a dose-dependent desensitization, mediated by the negative regulators USP18 and SOCS1 that act at the receptor. The analysis of basal protein abundance in primary human hepatocytes reveals high heterogeneity in patient-specific amounts of STAT1, STAT2, IRF9, and USP18. The mathematical modeling approach shows that the basal amount of USP18 determines patient-specific pathway desensitization, while the abundance of STAT2 predicts the patient-specific IFNalpha signal response.

Authors: F. Kok, M. Rosenblatt, M. Teusel, T. Nizharadze, V. Goncalves Magalhaes, C. Dachert, T. Maiwald, A. Vlasov, M. Wasch, S. Tyufekchieva, K. Hoffmann, G. Damm, D. Seehofer, T. Boettler, M. Binder, J. Timmer, M. Schilling, U. Klingmuller

Date Published: 23rd Jul 2020

Publication Type: Journal

Abstract (Expand)

Can three-dimensional, microvasculature networks still ensure blood supply if individual links fail? We address this question in the sinusoidal network, a plexus-like microvasculature network, which transports nutrient-rich blood to every hepatocyte in liver tissue, by building on recent advances in high-resolution imaging and digital reconstruction of adult mice liver tissue. We find that the topology of the three-dimensional sinusoidal network reflects its two design requirements of a space-filling network that connects all hepatocytes, while using shortest transport routes: sinusoidal networks are sub-graphs of the Delaunay graph of their set of branching points, and also contain the corresponding minimum spanning tree, both to good approximation. To overcome the spatial limitations of experimental samples and generate arbitrarily-sized networks, we developed a network generation algorithm that reproduces the statistical features of 0.3-mm-sized samples of sinusoidal networks, using multi-objective optimization for node degree and edge length distribution. Nematic order in these simulated networks implies anisotropic transport properties, characterized by an empirical linear relation between a nematic order parameter and the anisotropy of the permeability tensor. Under the assumption that all sinusoid tubes have a constant and equal flow resistance, we predict that the distribution of currents in the network is very inhomogeneous, with a small number of edges carrying a substantial part of the flow-a feature known for hierarchical networks, but unexpected for plexus-like networks. We quantify network resilience in terms of a permeability-at-risk, i.e., permeability as function of the fraction of removed edges. We find that sinusoidal networks are resilient to random removal of edges, but vulnerable to the removal of high-current edges. Our findings suggest the existence of a mechanism counteracting flow inhomogeneity to balance metabolic load on the liver.

Authors: J. Karschau, A. Scholich, J. Wise, H. Morales-Navarrete, Y. Kalaidzidis, M. Zerial, B. M. Friedrich

Date Published: 1st Jul 2020

Publication Type: Journal

Abstract (Expand)

Systems biology has experienced dramatic growth in the number, size and complexity of computational models describing biology. To reproduce simulation results and reuse models, researchers need to exchange precise and unambiguous descriptions of model structure and meaning. SBML (the Systems Biology Markup Language) is a community-developed format for this purpose. The latest edition, called SBML Level 3, has a modular structure, with a core suited to representing reaction-based models, and packages that extend the core with features suited for a variety of model types. Examples include constraint-based models, reaction-diffusion models, logical network models, and rule-based models. SBML and its rich software ecosystem have transformed the way systems biologists build and interact with models, and has played an important role in increasing model interoperability and reuse over the past two decades. More recently, a rise of multiscale models of whole cells and organs, and new data sources such as single cells measurements and live imaging, have precipitated new ways of integrating data and models. SBML Level 3 provides the foundation needed to support this evolution.

Authors: SM Keating, D Waltemath, M König, F Zhang, A Dräger, C Chaouiya, FT Bergmann, A Finney, CS Gillespie, T Helikar, S Hoops, RS Malik-Sheriff, SL Moodie, II Moraru, CJ Myers, A Naldi, BG Olivier, S Sahle, JC Schaff, LP Smith, MJ Swat, DT, L Watanabe, DJ Wilkinson, ML Blinov, K Begley, JR Faeder, HF Gómez, TM Hamm, Y Inagaki, W Liebermeister, AL Lister, D Lucio, E Mjolsness, CJ Proctor, K Raman, N Rodriguez, CA Shaffer, BE Shapiro, J Stelling, N Swainston, N Tanimura, J Wagner, M Meier-Schellersheim, HM Sauro, B Palsson, H Bolouri, H Kitano, Akira Funahashi, H Hermjakob, JC Doyle, M Hucka, SBML Community members

Date Published: 1st Jul 2020

Publication Type: Journal

Abstract

sbmlsim: Python utilities for simulating SBML models available at https://github.com/matthiaskoenig/sbmlsim.

Author: Matthias König

Date Published: 1st Jul 2020

Publication Type: Misc

Abstract (Expand)

This paper presents a report on outcomes of the 10th Computational Modeling in Biology Network (COMBINE) meeting that was held in Heidelberg, Germany, in July of 2019. The annual event brings together researchers, biocurators and software engineers to present recent results and discuss future work in the area of standards for systems and synthetic biology. The COMBINE initiative coordinates the development of various community standards and formats for computational models in the life sciences. Over the past 10 years, COMBINE has brought together standard communities that have further developed and harmonized their standards for better interoperability of models and data. COMBINE 2019 was co-located with a stakeholder workshop of the European EU-STANDS4PM initiative that aims at harmonized data and model standardization for in silico models in the field of personalized medicine, as well as with the FAIRDOM PALs meeting to discuss findable, accessible, interoperable and reusable (FAIR) data sharing. This report briefly describes the work discussed in invited and contributed talks as well as during breakout sessions. It also highlights recent advancements in data, model, and annotation standardization efforts. Finally, this report concludes with some challenges and opportunities that this community will face during the next 10 years.

Authors: Dagmar Waltemath, Martin Golebiewski, Michael L Blinov, Padraig Gleeson, Henning Hermjakob, Michael Hucka, Esther Thea Inau, Sarah M Keating, Matthias König, Olga Krebs, Rahuman S Malik-Sheriff, David Nickerson, Ernst Oberortner, Herbert M Sauro, Falk Schreiber, Lucian Smith, Melanie I Stefan, Ulrike Wittig, Chris J Myers

Date Published: 29th Jun 2020

Publication Type: Journal

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics presents papers related to the 10th COMBINE meeting together with the annual update of COMBINE standards in systems and synthetic biology.Not specified

Authors: Falk Schreiber, Björn Sommer, Tobias Czauderna, Martin Golebiewski, Thomas E. Gorochowski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 29th Jun 2020

Publication Type: Journal

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