CycSim—an online tool for exploring and experimenting with genome-scale metabolic models

Summary: CycSim is a web application dedicated to in silico experiments with genome-scale metabolic models coupled to the exploration of knowledge from BioCyc and KEGG. Specifically, CycSim supports the design of knockout experiments: simulation of growth phenotypes of single or multiple gene deletions mutants on specified media, comparison of these predictions with experimental phenotypes and direct visualization of both on metabolic maps. The web interface is designed for simplicity, putting constraint-based modelling techniques within easier reach of biologists. CycSim also functions as an online repository of genome-scale metabolic models

MultiMetEval: comparative and multi-objective analysis of genome-scale metabolic models

Comparative metabolic modelling is emerging as a novel field, supported by the development of reliable and standardized approaches for constructing genome-scale metabolic models in high throughput. New software solutions are needed to allow efficient comparative analysis of multiple models in the context of multiple cellular objectives. Here, we present the user-friendly software framework Multi-Metabolic Evaluator (MultiMetEval), built upon SurreyFBA, which allows the user to compose collections of metabolic models that together can be subjected to flux balance analysis. Additionally, MultiMetEval implements functionalities for multi-objective analysis by calculating the Pareto front between two cellular objectives. Using a previously generated dataset of 38 actinobacterial genome-scale metabolic models, we show how these approaches can lead to exciting novel insights. Firstly, after incorporating several pathways for the biosynthesis of natural products into each of these models, comparative flux balance analysis predicted that species like Streptomyces that harbour the highest diversity of secondary metabolite biosynthetic gene clusters in their genomes do not necessarily have the metabolic network topology most suitable for compound overproduction. Secondly, multi-objective analysis of biomass production and natural product biosynthesis in these actinobacteria shows that the well-studied occurrence of discrete metabolic switches during the change of cellular objectives is inherent to their metabolic network architecture. Comparative and multi-objective modelling can lead to insights that could not be obtained by normal flux balance analyses. MultiMetEval provides a powerful platform that makes these analyses straightforward for biologists. Sources and binaries of MultiMetEval are freely available from https://github.com/PiotrZakrzewski/MetEv​al/downloads

FOXC2 controls adult lymphatic endothelial specialization, function, and gut lymphatic barrier preventing multiorgan failure.

The mechanisms maintaining adult lymphatic vascular specialization throughout life and their role in coordinating inter-organ communication to sustain homeostasis remain elusive. We report that inactivation of the mechanosensitive transcription factor Foxc2 in adult lymphatic endothelium leads to a stepwise intestine-to-lung systemic failure. Foxc2 loss compromised the gut epithelial barrier, promoted dysbiosis and bacterial translocation to peripheral lymph nodes, and increased circulating levels of purine metabolites and angiopoietin-2. Commensal microbiota depletion dampened systemic pro-inflammatory cytokine levels, corrected intestinal lymphatic dysfunction, and improved survival. Foxc2 loss skewed the specialization of lymphatic endothelial subsets, leading to populations with mixed, pro-fibrotic identities and to emergence of lymph node-like endothelial cells. Our study uncovers a cross-talk between lymphatic vascular function and commensal microbiota, provides single-cell atlas of lymphatic endothelial subtypes, and reveals organ-specific and systemic effects of dysfunctional lymphatics. These effects potentially contribute to the pathogenesis of diseases, such as inflammatory bowel disease, cancer, or lymphedema

High frequency of central nervous system involvement in transformed Waldenstrom macroglobulinemia

Histologicaltransformation (HT) to diffuse large B-cell lymphoma (DLBCL) is a rare event in Waldenström macroglobulinemia (WM) and is associated with a poor prognosis.1-4 It confers an inferior outcome compared with WM patients without HT.2,3 Most transformed WM patients present with elevated serum lactate dehydrogenase (LDH) levels and extranodal disease.1 Among extranodal sites, the central nervous system (CNS) is one of the most frequently involved sites identified at diagnosis of transformed WM (ranging from 13% to 18%).1,3 However, the prognostic value of CNS involvement is unknown, and the rate of CNS involvement at relapse has not been previously reported in this setting.This work was supported by Cancer Research UK [C355/A26819], FC AECC, and AIRC under the “Accelerator Award Program” [EDITOR] to M.A. and R.G.-S

Modeling of non-steroidal anti-inflammatory drug effect within signaling pathways and miRNA-regulation pathways

To date, it is widely recognized that Non-Steroidal Anti-Inflammatory Drugs (NSAIDs) can exert considerable anti-tumor effects regarding many types of cancers. The prolonged use of NSAIDs is highly associated with diverse side effects. Therefore, tailoring down the NSAID application onto individual patients has become a necessary and relevant step towards personalized medicine. This study conducts the systemsbiological approach to construct a molecular model (NSAID model) containing a cyclooxygenase (COX)-pathway and its related signaling pathways. Four cancer hallmarks are integrated into the model to reflect different developmental aspects of tumorigenesis. In addition, a Flux-Comparative-Analysis (FCA) based on Petri net is developed to transfer the dynamic properties (including drug responsiveness) of individual cellular system into the model. The gene expression profiles of different tumor-types with available drug-response information are applied to validate the predictive ability of the NSAID model. Moreover, two therapeutic developmental strategies, synthetic lethality and microRNA (miRNA) biomarker discovery, are investigated based on the COX-pathway. In conclusion, the result of this study demonstrates that the NSAID model involving gene expression, gene regulation, signal transduction, protein interaction and other cellular processes, is able to predict the individual cellular responses for different therapeutic interventions (such as NS-398 and COX-2 specific siRNA inhibition). This strongly indicates that this type of model is able to reflect the physiological, developmental and pathological processes of an individual. The approach of miRNA biomarker discovery is demonstrated for identifying miRNAs with oncogenic and tumor suppressive functions for individual cell lines of breast-, colon- and lung-tumor. The achieved results are in line with different independent studies that investigated miRNA biomarker related to diagnostics of cancer treatments, therefore it might shed light on the development of biomarker discovery at individual level. Particular results of this study might contribute to step further towards personalized medicine with the systemsbiological approach

Mathematical modelling of clostridial acetone-butanol-ethanol fermentation

Clostridial acetone-butanol-ethanol (ABE) fermentation features a remarkable shift in the cellular metabolic activity from acid formation, acidogenesis, to the production of industrial-relevant solvents, solventogensis. In recent decades, mathematical models have been employed to elucidate the complex interlinked regulation and conditions that determine these two distinct metabolic states and govern the transition between them. In this review, we discuss these models with a focus on the mechanisms controlling intra- and extracellular changes between acidogenesis and solventogenesis. In particular, we critically evaluate underlying model assumptions and predictions in the light of current experimental knowledge. Towards this end, we briefly introduce key ideas and assumptions applied in the discussed modelling approaches, but waive a comprehensive mathematical presentation. We distinguish between structural and dynamical models, which will be discussed in their chronological order to illustrate how new biological information facilitates the ‘evolution’ of mathematical models. Mathematical models and their analysis have significantly contributed to our knowledge of ABE fermentation and the underlying regulatory network which spans all levels of biological organization. However, the ties between the different levels of cellular regulation are not well understood. Furthermore, contradictory experimental and theoretical results challenge our current notion of ABE metabolic network structure. Thus, clostridial ABE fermentation still poses theoretical as well as experimental challenges which are best approached in close collaboration between modellers and experimentalists