Decoding the dynamics of cellular metabolism and the action of 3-bromopyruvate and 2-deoxyglucose using pulsed stable isotope-resolved metabolomics

BACKGROUND: Cellular metabolism is highly dynamic and continuously adjusts to the physiological program of the cell. The regulation of metabolism appears at all biological levels: (post-) transcriptional, (post-) translational, and allosteric. This regulatory information is expressed in the metabolome, but in a complex manner. To decode such complex information, new methods are needed in order to facilitate dynamic metabolic characterization at high resolution. RESULTS: Here, we describe pulsed stable isotope-resolved metabolomics (pSIRM) as a tool for the dynamic metabolic characterization of cellular metabolism. We have adapted gas chromatography-coupled mass spectrometric methods for metabolomic profiling and stable isotope-resolved metabolomics. In addition, we have improved robustness and reproducibility and implemented a strategy for the absolute quantification of metabolites. CONCLUSIONS: By way of examples, we have applied this methodology to characterize central carbon metabolism of a panel of cancer cell lines and to determine the mode of metabolic inhibition of glycolytic inhibitors in times ranging from minutes to hours. Using pSIRM, we observed that 2-deoxyglucose is a metabolic inhibitor, but does not directly act on the glycolytic cascade

Agricultural landscapes as multi-scale public good and the role of the Common Agricultural Policy

During the last 50 years, the Common Agricultural Policy (CAP) has impacted the evolution of European agricultural landscapes by driving changes in land use and farming practices. We propose a typology characterizing the scales relevant for agricultural landscapes management and argue that action is required on three scales: (1) a landscape oriented management at farm level, (2) the coordination of land managers\u27 actions at landscape level, and (3) the conservation of the diversity of agricultural landscapes in the EU. We provide evidence that the CAP has until now mainly focused on the first scale. We also illustrate how agricultural policy could encourage coordinated actions at the landscape- and EU-scales. In particular, we propose policy instruments to coordinate actions of individual land owners (e.g. collective bonus in agro-environmental contracts or support to environmental cooperatives). We also analyse how the recognition and transposition of the European Landscape Convention could promote trans-frontier landscape cooperation in order, not only to conserve high-quality rural landscapes, but also to ensure the conservation of the diversity of EU landscapes (scale 3). This article provides a knowledge base to support an integrated CAP design in the direction of improved landscape management, as an important component of the EU project towards more sustainable agriculture

Regulatory Impact Assessment: A survey of selected developing and emerging economies

Regulatory impact assessment (RIA) involves a systematic appraisal of the social, economic and environmental impacts of proposed regulations and other kinds of policy instruments before they are adopted. A vast amount of academic literature in the last decade has charted the diffusion of RIA in OECD countries and EU member states. However, relatively little is known about the extent to which RIA has been adopted and implemented in developing countries. The last research attempting to shed light on this issue over a decade ago found that a number of were beginning to apply some form of regulatory assessment but that its development was at an early stage. Since then RIA has become almost universally adopted in OECD and EU member states as well as promoted as a tool for good (regulatory) governance in developing countries by international donors and organizations such as OECD, the International Finance Corporation of the World Bank Group (IFC). What, then, is the extent of RIA adoption and implementation in these countries today? This working paper addresses this question through a survey of RIA in 14 developing and emerging economies based on documentary analysis as well as semi-structured interviews with key stakeholders. The survey explores topics such as the legal and institutional framework of RIA, organizational capacity, and use of tools and methods (e.g. Cost Benefit Analysis). The results suggest that while an increasing number of developing countries have made efforts to introduce RIA in their decision making processes, these efforts have not yet led to a sustainable RIA system which significantly contributes to the good regulatory governance of these countries

p-medicine: a medical informatics platform for integrated large scale heterogeneous patient data

Secure access to patient data is becoming of increasing importance, as medical informatics grows in significance, to both assist with population health studies, and patient specific medicine in support of treatment. However, assembling the many different types of data emanating from the clinic is in itself a difficulty, and doing so across national borders compounds the problem. In this paper we present our solution: an easy to use distributed informatics platform embedding a state of the art data warehouse incorporating a secure pseudonymisation system protecting access to personal healthcare data. Using this system, a whole range of patient derived data, from genomics to imaging to clinical records, can be assembled and linked, and then connected with analytics tools that help us to understand the data. Research performed in this environment will have immediate clinical impact for personalised patient healthcare

Alterations of mTOR signaling impact metabolic stress resistance in colorectal carcinomas with BRAF and KRAS mutations

Metabolic reprogramming is as a hallmark of cancer, and several studies have reported that BRAF and KRAS tumors may be accompanied by a deregulation of cellular metabolism. We investigated how BRAF(V600E) and KRAS(G12V) affect cell metabolism, stress resistance and signaling in colorectal carcinoma cells driven by these mutations. KRAS(G12V) expressing cells are characterized by the induction of glycolysis, accumulation of lactic acid and sensitivity to glycolytic inhibition. Notably mathematical modelling confirmed the critical role of MCT1 designating the survival of KRAS(G12V) cells. Carcinoma cells harboring BRAF(V600E) remain resistant towards alterations of glucose supply or application of signaling or metabolic inhibitors. Altogether these data demonstrate that an oncogene-specific decoupling of mTOR from AMPK or AKT signaling accounts for alterations of resistance mechanisms and metabolic phenotypes. Indeed the inhibition of mTOR in BRAF(V600E) cells counteracts the metabolic predisposition and demonstrates mTOR as a potential target in BRAF(V600E)-driven colorectal carcinomas

Metropolitan Foodsheds as Spatial References for a Landscape-Based Assessment of Regional Food Supply

The Food Planning and Innovation for Sustainable Metropolitan Regions (FOODMETRES) project strives to assess the environmental and socioeconomic impacts of food chains, with regard to the spatial, logistical, and resource dimensions of growing food as well as the questions of food safety and quality as key assets for food planning and governance. Recognizing that food production and consumption are not only linked via food chains in a physical–logistic way, but above all via value chains of social acceptance, FoodMetres is designed to combine quantitative and evidence-based research principles with qualitative and discursive methods, in order to address the wider dimensions of food chains in the context of metropolitan agro-systems. One of the research assets is to assess the location and amount of agriculturally productive land within reach of urban centers, to supply metropolitan populations with regionally grown food. For this purpose, we have developed an accessibility approach that is specifically designed to examine the potential of Metropolitan Agro-Food Systems (MAS) to feed urban populations. Taking into account data on transport infrastructure and land cover as well as the protection status of land, this paper highlights the results for the test cases of Ljubljana, Berlin, London, Milano, and Rotterdam

Enabling trade-offs between accuracy and computational cost: Adaptive algorithms to reduce time to clinical insight

The efficacy of drug treatments depends on how tightly small molecules bind to their target proteins. Quantifying the strength of these interactions (the so called 'binding affinity') is a grand challenge of computational chemistry, surmounting which could revolutionize drug design and provide the platform for patient specific medicine. Recently, evidence from blind challenge predictions and retrospective validation studies has suggested that molecular dynamics (MD) can now achieve useful predictive accuracy (1 kcal/mol) This accuracy is sufficient to greatly accelerate hit to lead and lead optimization. To translate these advances in predictive accuracy so as to impact clinical and/or industrial decision making requires that binding free energy results must be turned around on reduced timescales without loss of accuracy. This demands advances in algorithms, scalable software systems, and intelligent and efficient utilization of supercomputing resources. This work is motivated by the real world problem of providing insight from drug candidate data on a time scale that is as short as possible. Specifically, we reproduce results from a collaborative project between UCL and GlaxoSmithKline to study a congeneric series of drug candidates binding to the BRD4 protein-inhibitors of which have shown promising preclinical efficacy in pathologies ranging from cancer to inflammation. We demonstrate the use of a framework called HTBAC, designed to support the aforementioned requirements of accurate and rapid drug binding affinity calculations. HTBAC facilitates the execution of the numbers of simulations while supporting the adaptive execution of algorithms. Furthermore, HTBAC enables the selection of simulation parameters during runtime which can, in principle, optimize the use of computational resources whilst producing results within a target uncertainty