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NPJ Systems Biology and Applications

H Alexander Ebhardt, Alex Root, Yansheng Liu, Nicholas Paul Gauthier, Chris Sander, Ruedi Aebersold
In the United States alone one in five newly diagnosed cancers in men are prostate carcinomas (PCa). Androgen receptor (AR) status and the PI3K-AKT-mTOR signal transduction pathway are critical in PCa. After initial response to single drugs targeting these pathways resistance often emerges, indicating the need for combination therapy. Here, we address the question of efficacy of drug combinations and development of resistance mechanisms to targeted therapy by a systems pharmacology approach. We combine targeted perturbation with detailed observation of the molecular response by mass spectrometry...
2018: NPJ Systems Biology and Applications
Amitabh Sharma, Arda Halu, Julius L Decano, Megha Padi, Yang-Yu Liu, Rashmi B Prasad, Joao Fadista, Marc Santolini, Jörg Menche, Scott T Weiss, Marc Vidal, Edwin K Silverman, Masanori Aikawa, Albert-László Barabási, Leif Groop, Joseph Loscalzo
Probing the dynamic control features of biological networks represents a new frontier in capturing the dysregulated pathways in complex diseases. Here, using patient samples obtained from a pancreatic islet transplantation program, we constructed a tissue-specific gene regulatory network and used the control centrality (Cc) concept to identify the high control centrality (HiCc) pathways, which might serve as key pathobiological pathways for Type 2 Diabetes (T2D). We found that HiCc pathway genes were significantly enriched with modest GWAS p -values in the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) study...
2018: NPJ Systems Biology and Applications
Stephen Wilson, Fabian Volker Filipp
Coordinated experiments focused on transcriptional responses and chromatin states are well-equipped to capture different epigenomic and transcriptomic levels governing the circuitry of a regulatory network. We propose a workflow for the genome-wide identification of epigenomic and transcriptional cooperation to elucidate transcriptional networks in cancer. Gene promoter annotation in combination with network analysis and sequence-resolution of enriched transcriptional motifs in epigenomic data reveals transcription factor families that act synergistically with epigenomic master regulators...
2018: NPJ Systems Biology and Applications
Angela Oppelt, Daniel Kaschek, Suzanna Huppelschoten, Rowena Sison-Young, Fang Zhang, Marie Buck-Wiese, Franziska Herrmann, Sebastian Malkusch, Carmen L Krüger, Mara Meub, Benjamin Merkt, Lea Zimmermann, Amy Schofield, Robert P Jones, Hassan Malik, Marcel Schilling, Mike Heilemann, Bob van de Water, Christopher E Goldring, B Kevin Park, Jens Timmer, Ursula Klingmüller
Drug-induced liver injury (DILI) has become a major problem for patients and for clinicians, academics and the pharmaceutical industry. To date, existing hepatotoxicity test systems are only poorly predictive and the underlying mechanisms are still unclear. One of the factors known to amplify hepatotoxicity is the tumor necrosis factor alpha (TNFα), especially due to its synergy with commonly used drugs such as diclofenac. However, the exact mechanism of how diclofenac in combination with TNFα induces liver injury remains elusive...
2018: NPJ Systems Biology and Applications
Ruth Stoney, David L Robertson, Goran Nenadic, Jean-Marc Schwartz
Molecular interaction networks are routinely used to map the organization of cellular function. Edges represent interactions between genes, proteins, or metabolites. However, in living cells, molecular interactions are dynamic, necessitating context-dependent models. Contextual information can be integrated into molecular interaction networks through the inclusion of additional molecular data, but there are concerns about completeness and relevance of this data. We developed an approach for representing the organization of human cellular processes using pathways as the nodes in a network...
2018: NPJ Systems Biology and Applications
Alexander Mazein, Marek Ostaszewski, Inna Kuperstein, Steven Watterson, Nicolas Le Novère, Diane Lefaudeux, Bertrand De Meulder, Johann Pellet, Irina Balaur, Mansoor Saqi, Maria Manuela Nogueira, Feng He, Andrew Parton, Nathanaël Lemonnier, Piotr Gawron, Stephan Gebel, Pierre Hainaut, Markus Ollert, Ugur Dogrusoz, Emmanuel Barillot, Andrei Zinovyev, Reinhard Schneider, Rudi Balling, Charles Auffray
The development of computational approaches in systems biology has reached a state of maturity that allows their transition to systems medicine. Despite this progress, intuitive visualisation and context-dependent knowledge representation still present a major bottleneck. In this paper, we describe the Disease Maps Project, an effort towards a community-driven computationally readable comprehensive representation of disease mechanisms. We outline the key principles and the framework required for the success of this initiative, including use of best practices, standards and protocols...
2018: NPJ Systems Biology and Applications
Fatemeh Vafaee, Connie Diakos, Michaela B Kirschner, Glen Reid, Michael Z Michael, Lisa G Horvath, Hamid Alinejad-Rokny, Zhangkai Jason Cheng, Zdenka Kuncic, Stephen Clarke
Recent advances in high-throughput technologies have provided an unprecedented opportunity to identify molecular markers of disease processes. This plethora of complex-omics data has simultaneously complicated the problem of extracting meaningful molecular signatures and opened up new opportunities for more sophisticated integrative and holistic approaches. In this era, effective integration of data-driven and knowledge-based approaches for biomarker identification has been recognised as key to improving the identification of high-performance biomarkers, and necessary for translational applications...
2018: NPJ Systems Biology and Applications
Zak Costello, Hector Garcia Martin
New synthetic biology capabilities hold the promise of dramatically improving our ability to engineer biological systems. However, a fundamental hurdle in realizing this potential is our inability to accurately predict biological behavior after modifying the corresponding genotype. Kinetic models have traditionally been used to predict pathway dynamics in bioengineered systems, but they take significant time to develop, and rely heavily on domain expertise. Here, we show that the combination of machine learning and abundant multiomics data (proteomics and metabolomics) can be used to effectively predict pathway dynamics in an automated fashion...
2018: NPJ Systems Biology and Applications
Jingyu Zhang, Xiao-Jun Tian, Yi-Jiun Chen, Weikang Wang, Simon Watkins, Jianhua Xing
The detection and transmission of the temporal quality of intracellular and extracellular signals is an essential cellular mechanism. It remains largely unexplored how cells interpret the duration information of a stimulus. In this paper, we performed an integrated quantitative and computational analysis on TGF-β induced activation of SNAIL1, a key transcription factor that regulates several subsequent cell fate decisions such as apoptosis and epithelial-to-mesenchymal transition. We demonstrate that crosstalk among multiple TGF-β activated pathways forms a relay from SMAD to GLI1 that initializes and maintains SNAILl expression, respectively...
2018: NPJ Systems Biology and Applications
Aouefa Amoussouvi, Lotte Teufel, Matthias Reis, Martin Seeger, Julia Katharina Schlichting, Gabriele Schreiber, Andreas Herrmann, Edda Klipp
Gene expression is a stochastic process and its appropriate regulation is critical for cell cycle progression. Cellular stress response necessitates expression reprogramming and cell cycle arrest. While previous studies are mostly based on bulk experiments influenced by synchronization effects or lack temporal distribution, time-resolved methods on single cells are needed to understand eukaryotic cell cycle in context of noisy gene expression and external perturbations. Using smFISH, microscopy and morphological markers, we monitored mRNA abundances over cell cycle phases and calculated transcriptional noise for SIC1 , CLN2 , and CLB5 , the main G1/S transition regulators in budding yeast...
2018: NPJ Systems Biology and Applications
Megha Padi, John Quackenbush
Complex traits and diseases like human height or cancer are often not caused by a single mutation or genetic variant, but instead arise from functional changes in the underlying molecular network. Biological networks are known to be highly modular and contain dense "communities" of genes that carry out cellular processes, but these structures change between tissues, during development, and in disease. While many methods exist for inferring networks and analyzing their topologies separately, there is a lack of robust methods for quantifying differences in network structure...
2018: NPJ Systems Biology and Applications
Martin Hoffmann, Jörg Galle
Kinetic models are at the heart of system identification. A priori chosen rate functions may, however, be unfitting or too restrictive for complex or previously unanticipated regulation. We applied general purpose piecewise linear functions for stochastic system identification in one dimension using published flow cytometry data on E.coli and report on identification results for equilibrium state and dynamic time series. In metabolic labelling experiments during yeast osmotic stress response, we find mRNA production and degradation to be strongly co-regulated...
2018: NPJ Systems Biology and Applications
Kaoru Ohashi, Masashi Fujii, Shinsuke Uda, Hiroyuki Kubota, Hisako Komada, Kazuhiko Sakaguchi, Wataru Ogawa, Shinya Kuroda
Insulin plays a central role in glucose homeostasis, and impairment of insulin action causes glucose intolerance and leads to type 2 diabetes mellitus (T2DM). A decrease in the transient peak and sustained increase of circulating insulin following an infusion of glucose accompany T2DM pathogenesis. However, the mechanism underlying this abnormal temporal pattern of circulating insulin concentration remains unknown. Here we show that changes in opposite direction of hepatic and peripheral insulin clearance characterize this abnormal temporal pattern of circulating insulin concentration observed in T2DM...
2018: NPJ Systems Biology and Applications
Rajiv Gandhi Govindaraj, Misagh Naderi, Manali Singha, Jeffrey Lemoine, Michal Brylinski
Rare, or orphan, diseases are conditions afflicting a small subset of people in a population. Although these disorders collectively pose significant health care problems, drug companies require government incentives to develop drugs for rare diseases due to extremely limited individual markets. Computer-aided drug repositioning, i.e., finding new indications for existing drugs, is a cheaper and faster alternative to traditional drug discovery offering a promising venue for orphan drug research. Structure-based matching of drug-binding pockets is among the most promising computational techniques to inform drug repositioning...
2018: NPJ Systems Biology and Applications
Marc Santolini, Milagros C Romay, Clara L Yukhtman, Christoph D Rau, Shuxun Ren, Jeffrey J Saucerman, Jessica J Wang, James N Weiss, Yibin Wang, Aldons J Lusis, Alain Karma
A traditional approach to investigate the genetic basis of complex diseases is to identify genes with a global change in expression between diseased and healthy individuals. However, population heterogeneity may undermine the effort to uncover genes with significant but individual contribution to the spectrum of disease phenotypes within a population. Here we investigate individual changes of gene expression when inducing hypertrophy and heart failure in 100 + strains of genetically distinct mice from the Hybrid Mouse Diversity Panel (HMDP)...
2018: NPJ Systems Biology and Applications
Jingqi Q X Gong, Eric A Sobie
Quantitative mismatches between human physiology and experimental models can be problematic for the development of effective therapeutics. When the effects of drugs on human adult cardiac electrophysiology are of interest, phenotypic differences with animal cells, and more recently stem cell-derived models, can present serious limitations. We addressed this issue through a combination of mechanistic mathematical modeling and statistical analyses. Physiological metrics were simulated in heterogeneous populations of models describing cardiac myocytes from adult ventricles and those derived from induced pluripotent stem cells (iPSC-CMs)...
2018: NPJ Systems Biology and Applications
Henrik Cordes, Christoph Thiel, Vanessa Baier, Lars M Blank, Lars Kuepfer
Drug-induced perturbations of the endogenous metabolic network are a potential root cause of cellular toxicity. A mechanistic understanding of such unwanted side effects during drug therapy is therefore vital for patient safety. The comprehensive assessment of such drug-induced injuries requires the simultaneous consideration of both drug exposure at the whole-body and resulting biochemical responses at the cellular level. We here present a computational multi-scale workflow that combines whole-body physiologically based pharmacokinetic (PBPK) models and organ-specific genome-scale metabolic network (GSMN) models through shared reactions of the xenobiotic metabolism...
2018: NPJ Systems Biology and Applications
Sylvie Delhalle, Sebastian F N Bode, Rudi Balling, Markus Ollert, Feng Q He
Big data generation and computational processing will enable medicine to evolve from a "one-size-fits-all" approach to precise patient stratification and treatment. Significant achievements using "Omics" data have been made especially in personalized oncology. However, immune cells relative to tumor cells show a much higher degree of complexity in heterogeneity, dynamics, memory-capability, plasticity and "social" interactions. There is still a long way ahead on translating our capability to identify potentially targetable personalized biomarkers into effective personalized therapy in immune-centralized diseases...
2018: NPJ Systems Biology and Applications
Friederike Langhauser, Ana I Casas, Vu-Thao-Vi Dao, Emre Guney, Jörg Menche, Eva Geuss, Pamela W M Kleikers, Manuela G López, Albert-L Barabási, Christoph Kleinschnitz, Harald H H W Schmidt
Network medicine utilizes common genetic origins, markers and co-morbidities to uncover mechanistic links between diseases. These links can be summarized in the diseasome, a comprehensive network of disease-disease relationships and clusters. The diseasome has been influential during the past decade, although most of its links are not followed up experimentally. Here, we investigate a high prevalence unmet medical need cluster of disease phenotypes linked to cyclic GMP. Hitherto, the central cGMP-forming enzyme, soluble guanylate cyclase (sGC), has been targeted pharmacologically exclusively for smooth muscle modulation in cardiology and pulmonology...
2018: NPJ Systems Biology and Applications
Jorge Júlvez, Duygu Dikicioglu, Stephen G Oliver
Mathematical models that combine predictive accuracy with explanatory power are central to the progress of systems and synthetic biology, but the heterogeneity and incompleteness of biological data impede our ability to construct such models. Furthermore, the robustness displayed by many biological systems means that they have the flexibility to operate under a range of physiological conditions and this is difficult for many modeling formalisms to handle. Flexible nets (FNs) address these challenges and represent a paradigm shift in model-based analysis of biological systems...
2018: NPJ Systems Biology and Applications
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