Constraint based modelling going multicellular

in Frontiers in Molecular Biosciences (2016), 3(3),

Constraint based modelling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase ... [more ▼]

Constraint based modelling has seen applications in many microorganisms. For example, there are now established methods to determine potential genetic modifications and external interventions to increase the efficiency of microbial strains in chemical production pipelines. In addition, multiple models of multicellular organisms have been created including plants and humans. While initially the focus here was on modelling individual cell types of the multicellular organism, this focus recently started to switch. Models of microbial communities, as well as multitissue models of higher organisms have been constructed. These models thereby can include different parts of a plant, like root, stem or different tissue types in the same organ. Such models can elucidate details of the interplay between symbiotic organisms, as well as the concerted efforts of multiple tissues and can be applied to analyse the effects of drugs or mutations on a more systemic level. In this review we give an overview of the recent development of multi-tissue models using constraint based techniques and the methods employed when investigating these models. We further highlight advances in combining constraint based models with dynamic and regulatory information and give an overview of these types of hybrid or multi-level approaches. [less ▲]

Integrated metabolic modelling reveals cell-type specific epigenetic control points of the macrophage metabolic network

in BMC Genomics (2015), 16(809),

Background: The reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine ... [more ▼]

Background: The reconstruction of context-specific metabolic models from easily and reliably measurable features such as transcriptomics data will be increasingly important in research and medicine. Current reconstruction methods suffer from high computational effort and arbitrary threshold setting. Moreover, understanding the underlying epigenetic regulation might allow the identification of putative intervention points within metabolic networks. Genes under high regulatory load from multiple enhancers or super-enhancers are known key genes for disease and cell identity. However, their role in regulation of metabolism and their placement within the metabolic networks has not been studied. Methods: Here we present FASTCORMICS, a fast and robust workflow for the creation of high-quality metabolic models from transcriptomics data. FASTCORMICS is devoid of arbitrary parameter settings and due to its low computational demand allows cross-validation assays. Applying FASTCORMICS, we have generated models for 63 primary human cell types from microarray data, revealing significant differences in their metabolic networks. Results: To understand the cell type-specific regulation of the alternative metabolic pathways we built multiple models during differentiation of primary human monocytes to macrophages and performed ChIP-Seq experiments for histone H3 K27 acetylation (H3K27ac) to map the active enhancers in macrophages. Focusing on the metabolic genes under high regulatory load from multiple enhancers or super-enhancers, we found these genes to show the most cell type-restricted and abundant expression profiles within their respective pathways. Importantly, the high regulatory load genes are associated to reactions enriched for transport reactions and other pathway entry points, suggesting that they are critical regulatory control points for cell type-specific metabolism. Conclusions: By integrating metabolic modelling and epigenomic analysis we have identified high regulatory load as a common feature of metabolic genes at pathway entry points such as transporters within the macrophage metabolic network. Analysis of these control points through further integration of metabolic and gene regulatory networks in various contexts could be beneficial in multiple fields from identification of disease intervention strategies to cellular reprogramming. [less ▲]

Multiscale model of dynamic neuromodulation integrating neuropeptide-induced signaling pathway activity with membrane electrophysiology.

in Biophysical journal (2015), 108(1), 211-23

We developed a multiscale model to bridge neuropeptide receptor-activated signaling pathway activity with membrane electrophysiology. Typically, the neuromodulation of biochemical signaling and biophysics ... [more ▼]

We developed a multiscale model to bridge neuropeptide receptor-activated signaling pathway activity with membrane electrophysiology. Typically, the neuromodulation of biochemical signaling and biophysics have been investigated separately in modeling studies. We studied the effects of Angiotensin II (AngII) on neuronal excitability changes mediated by signaling dynamics and downstream phosphorylation of ion channels. Experiments have shown that AngII binding to the AngII receptor type-1 elicits baseline-dependent regulation of cytosolic Ca(2+) signaling. Our model simulations revealed a baseline Ca(2+)-dependent response to AngII receptor type-1 activation by AngII. Consistent with experimental observations, AngII evoked a rise in Ca(2+) when starting at a low baseline Ca(2+) level, and a decrease in Ca(2+) when starting at a higher baseline. Our analysis predicted that the kinetics of Ca(2+) transport into the endoplasmic reticulum play a critical role in shaping the Ca(2+) response. The Ca(2+) baseline also influenced the AngII-induced excitability changes such that lower Ca(2+) levels were associated with a larger firing rate increase. We examined the relative contributions of signaling kinases protein kinase C and Ca(2+)/Calmodulin-dependent protein kinase II to AngII-mediated excitability changes by simulating activity blockade individually and in combination. We found that protein kinase C selectively controlled firing rate adaptation whereas Ca(2+)/Calmodulin-dependent protein kinase II induced a delayed effect on the firing rate increase. We tested whether signaling kinetics were necessary for the dynamic effects of AngII on excitability by simulating three scenarios of AngII-mediated KDR channel phosphorylation: (1), an increased steady state; (2), a step-change increase; and (3), dynamic modulation. Our results revealed that the kinetics emerging from neuromodulatory activation of the signaling network were required to account for the dynamical changes in excitability. In summary, our integrated multiscale model provides, to our knowledge, a new approach for quantitative investigation of neuromodulatory effects on signaling and electrophysiology. [less ▲]

Towards improved genome-scale metabolic network reconstructions: unification, transcript specificity and beyond.

in Briefings in bioinformatics (2015)

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from ... [more ▼]

Genome-scale metabolic network reconstructions provide a basis for the investigation of the metabolic properties of an organism. There are reconstructions available for multiple organisms, from prokaryotes to higher organisms and methods for the analysis of a reconstruction. One example is the use of flux balance analysis to improve the yields of a target chemical, which has been applied successfully. However, comparison of results between existing reconstructions and models presents a challenge because of the heterogeneity of the available reconstructions, for example, of standards for presenting gene-protein-reaction associations, nomenclature of metabolites and reactions or selection of protonation states. The lack of comparability for gene identifiers or model-specific reactions without annotated evidence often leads to the creation of a new model from scratch, as data cannot be properly matched otherwise. In this contribution, we propose to improve the predictive power of metabolic models by switching from gene-protein-reaction associations to transcript-isoform-reaction associations, thus taking advantage of the improvement of precision in gene expression measurements. To achieve this precision, we discuss available databases that can be used to retrieve this type of information and point at issues that can arise from their neglect. Further, we stress issues that arise from non-standardized building pipelines, like inconsistencies in protonation states. In addition, problems arising from the use of non-specific cofactors, e.g. artificial futile cycles, are discussed, and finally efforts of the metabolic modelling community to unify model reconstructions are highlighted. [less ▲]

Constitutive activation of oncogenic PDGFRalpha-mutant proteins occurring in GIST patients induces receptor mislocalisation and alters PDGFRalpha signalling characteristics.

in Cell Communication and Signaling (2015), 13

BACKGROUND: Gastrointestinal stromal tumours (GIST) are mainly characterised by the presence of activating mutations in either of the two receptor tyrosine kinases c-KIT or platelet-derived growth factor ... [more ▼]

BACKGROUND: Gastrointestinal stromal tumours (GIST) are mainly characterised by the presence of activating mutations in either of the two receptor tyrosine kinases c-KIT or platelet-derived growth factor receptor-alpha (PDGFRalpha). Most mechanistic studies dealing with GIST mutations have focused on c-KIT and far less is known about the signalling characteristics of the mutated PDGFRalpha proteins. Here, we study the signalling capacities and corresponding transcriptional responses of the different PDGFRalpha proteins under comparable genomic conditions. RESULTS: We demonstrate that the constitutive signalling via the oncogenic PDGFRalpha mutants favours a mislocalisation of the receptors and that this modifies the signalling characteristics of the mutated receptors. We show that signalling via the oncogenic PDGFRalpha mutants is not solely characterised by a constitutive activation of the conventional PDGFRalpha signalling pathways. In contrast to wild-type PDGFRalpha signal transduction, the activation of STAT factors (STAT1, STAT3 and STAT5) is an integral part of signalling mediated via mutated PDGF-receptors. Furthermore, this unconventional STAT activation by mutated PDGFRalpha is already initiated in the endoplasmic reticulum whereas the conventional signalling pathways rather require cell surface expression of the receptor. Finally, we demonstrate that the activation of STAT factors also translates into a biologic response as highlighted by the induction of STAT target genes. CONCLUSION: We show that the overall oncogenic response is the result of different signatures emanating from different cellular compartments. Furthermore, STAT mediated responses are an integral part of mutated PDGFRalpha signalling. [less ▲]

The oncogenic FIP1L1-PDGFRalpha fusion protein displays skewed signaling properties compared to its wild-type PDGFRalpha counterpart.

in JAK-STAT (2015), 4(1), 1062596

Aberrant activation of oncogenic kinases is frequently observed in human cancers, but the underlying mechanism and resulting effects on global signaling are incompletely understood. Here, we demonstrate ... [more ▼]

Aberrant activation of oncogenic kinases is frequently observed in human cancers, but the underlying mechanism and resulting effects on global signaling are incompletely understood. Here, we demonstrate that the oncogenic FIP1L1-PDGFRalpha kinase exhibits a significantly different signaling pattern compared to its PDGFRalpha wild type counterpart. Interestingly, the activation of primarily membrane-based signal transduction processes (such as PI3-kinase- and MAP-kinase- pathways) is remarkably shifted toward a prominent activation of STAT factors. This diverging signaling pattern compared to classical PDGF-receptor signaling is partially coupled to the aberrant cytoplasmic localization of the oncogene, since membrane targeting of FIP1L1-PDGFRalpha restores activation of MAPK- and PI3K-pathways. In stark contrast to the classical cytokine-induced STAT activation process, STAT activation by FIP1L1-PDGFRalpha does neither require Janus kinase activity nor Src kinase activity. Furthermore, we investigated the mechanism of STAT5 activation via FIP1L1-PDGFRalpha in more detail and found that STAT5 activation does not involve an SH2-domain-mediated binding mechanism. We thus demonstrate that STAT5 activation occurs via a non-canonical activation mechanism in which STAT5 may be subject to a direct phosphorylation by FIP1L1-PDGFRalpha. [less ▲]

Transcriptomics profiling of human SGBS adipogenesis

in Genomics Data (2014), 2

Obesity is an ever-growing epidemic where tissue homeostasis is influenced by the differentiation of adipocytes that function in lipid metabolism, endocrine and inflammatory processes. While this ... [more ▼]

Obesity is an ever-growing epidemic where tissue homeostasis is influenced by the differentiation of adipocytes that function in lipid metabolism, endocrine and inflammatory processes. While this differentiation process has been well-characterized in mice, limited data is available from human cells. Applying microarray expression profiling in the human SGBS pre-adipocyte cell line, we identified genes with differential expression during differentiation in combination with constraint-based modeling of metabolic pathway activity. Here we describe the experimental design and quality controls in detail for the gene expression and related results published by Galhardo et al. in Nucleic Acids Research 2014 associated with the data uploaded to NCBI Gene Expression Omnibus (). [less ▲]

Combinatorial regulation of lipoprotein lipase by microRNAs during mouse adipogenesis

in RNA Biology (2014), 11(1), 76-91

MicroRNAs (miRNAs) regulate gene expression directly through base pairing to their targets or indirectly through participating in multi-scale regulatory networks. Often miRNAs take part in feed-forward ... [more ▼]

MicroRNAs (miRNAs) regulate gene expression directly through base pairing to their targets or indirectly through participating in multi-scale regulatory networks. Often miRNAs take part in feed-forward motifs where a miRNA and a transcription factor act on shared targets to achieve accurate regulation of processes such as cell differentiation. Here we show that the expression levels of miR-27a and miR-29a inversely correlate with the mRNA levels of lipoprotein lipase (Lpl), their predicted combinatorial target, and its key transcriptional regulator peroxisome proliferator activated receptor gamma (Pparg) during 3T3-L1 adipocyte differentiation. More importantly, we show that Lpl, a key lipogenic enzyme, can be negatively regulated by the two miRNA families in a combinatorial fashion on the mRNA and functional level in maturing adipocytes. This regulation is mediated through the Lpl 3′UTR as confirmed by reporter gene assays. In addition, a small mathematical model captures the dynamics of this feed-forward motif and predicts the changes in Lpl mRNA levels upon network perturbations. The obtained results might offer an explanation to the dysregulation of LPL in diabetic conditions and could be extended to quantitative modeling of regulation of other metabolic genes under similar regulatory network motifs. [less ▲]

Basic Regulatory Principles of Escherichia coli's Electron Transport Chain for Varying Oxygen Conditions.

in PloS one (2014), 9(9), 107640

For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the ... [more ▼]

For adaptation between anaerobic, micro-aerobic and aerobic conditions Escherichia coli's metabolism and in particular its electron transport chain (ETC) is highly regulated. Although it is known that the global transcriptional regulators FNR and ArcA are involved in oxygen response it is unclear how they interplay in the regulation of ETC enzymes under micro-aerobic chemostat conditions. Also, there are diverse results which and how quinones (oxidised/reduced, ubiquinone/other quinones) are controlling the ArcBA two-component system. In the following a mathematical model of the E. coli ETC linked to basic modules for substrate uptake, fermentation product excretion and biomass formation is introduced. The kinetic modelling focusses on regulatory principles of the ETC for varying oxygen conditions in glucose-limited continuous cultures. The model is based on the balance of electron donation (glucose) and acceptance (oxygen or other acceptors). Also, it is able to account for different chemostat conditions due to changed substrate concentrations and dilution rates. The parameter identification process is divided into an estimation and a validation step based on previously published and new experimental data. The model shows that experimentally observed, qualitatively different behaviour of the ubiquinone redox state and the ArcA activity profile in the micro-aerobic range for different experimental conditions can emerge from a single network structure. The network structure features a strong feed-forward effect from the FNR regulatory system to the ArcBA regulatory system via a common control of the dehydrogenases of the ETC. The model supports the hypothesis that ubiquinone but not ubiquinol plays a key role in determining the activity of ArcBA in a glucose-limited chemostat at micro-aerobic conditions. [less ▲]

Identification of New IkappaBalpha Complexes by an Iterative Experimental and Mathematical Modeling Approach.

in PLoS computational biology (2014), 10(3), 1003528

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the ... [more ▼]

The transcription factor nuclear factor kappa-B (NFkappaB) is a key regulator of pro-inflammatory and pro-proliferative processes. Accordingly, uncontrolled NFkappaB activity may contribute to the development of severe diseases when the regulatory system is impaired. Since NFkappaB can be triggered by a huge variety of inflammatory, pro-and anti-apoptotic stimuli, its activation underlies a complex and tightly regulated signaling network that also includes multi-layered negative feedback mechanisms. Detailed understanding of this complex signaling network is mandatory to identify sensitive parameters that may serve as targets for therapeutic interventions. While many details about canonical and non-canonical NFkappaB activation have been investigated, less is known about cellular IkappaBalpha pools that may tune the cellular NFkappaB levels. IkappaBalpha has so far exclusively been described to exist in two different forms within the cell: stably bound to NFkappaB or, very transiently, as unbound protein. We created a detailed mathematical model to quantitatively capture and analyze the time-resolved network behavior. By iterative refinement with numerous biological experiments, we yielded a highly identifiable model with superior predictive power which led to the hypothesis of an NFkappaB-lacking IkappaBalpha complex that contains stabilizing IKK subunits. We provide evidence that other but canonical pathways exist that may affect the cellular IkappaBalpha status. This additional IkappaBalpha:IKKgamma complex revealed may serve as storage for the inhibitor to antagonize undesired NFkappaB activation under physiological and pathophysiological conditions. [less ▲]