References of "Paglia, Giuseppe"
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See detailA functional metabolic map of Faecalibacterium prausnitzii, a beneficial human gut microbe
Heinken, Almut Katrin UL; Khan, M Tanweer; Paglia, Giuseppe et al

in Journal of Bacteriology (2014), 196(18), 3289-3302

The human gut microbiota plays a central role in human well-being and disease. In this study, we present an integrated, iterative approach of computational modeling, in vitro experiments, metabolomics ... [more ▼]

The human gut microbiota plays a central role in human well-being and disease. In this study, we present an integrated, iterative approach of computational modeling, in vitro experiments, metabolomics, and genomic analysis to accelerate the identification of metabolic capabilities for poorly characterized (anaerobic) microorganisms. We demonstrate this approach for the beneficial human gut microbe Faecalibacterium prausnitzii strain A2-165. We generated an automated draft reconstruction, which we curated against the limited biochemical data. This reconstruction modeling was used to develop in silico and in vitro a chemically defined medium (CDM), which was validated experimentally. Subsequent metabolomic analysis of the spent medium for growth on CDM was performed. We refined our metabolic reconstruction according to in vitro observed metabolite consumption and secretion and propose improvements to the current genome annotation of F. prausnitzii A2-165. We then used the reconstruction to systematically characterize its metabolic properties. Novel carbon source utilization capabilities and inabilities were predicted based on metabolic modeling and validated experimentally. This study resulted in a functional metabolic map of F. prausnitzii, which is available for further applications. The presented workflow can be readily extended to other poorly characterized and uncharacterized organisms to yield novel biochemical insights about the target organism. [less ▲]

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See detailInferring the metabolism of human orphan metabolites from their metabolic network context affirms human gluconokinase activity.
Rolfsson, Ottar; Paglia, Giuseppe; Magnusdottir, Manuela et al

in Biochemical Journal (2013), 449(2), 427-435

Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational ... [more ▼]

Metabolic network reconstructions define metabolic information within a target organism and can therefore be used to address incomplete metabolic information. In the present study we used a computational approach to identify human metabolites whose metabolism is incomplete on the basis of their detection in humans but exclusion from the human metabolic network reconstruction RECON 1. Candidate solutions, composed of metabolic reactions capable of explaining the metabolism of these compounds, were then identified computationally from a global biochemical reaction database. Solutions were characterized with respect to how metabolites were incorporated into RECON 1 and their biological relevance. Through detailed case studies we show that biologically plausible non-intuitive hypotheses regarding the metabolism of these compounds can be proposed in a semi-automated manner, in an approach that is similar to de novo network reconstruction. We subsequently experimentally validated one of the proposed hypotheses and report that C9orf103, previously identified as a candidate tumour suppressor gene, encodes a functional human gluconokinase. The results of the present study demonstrate how semi-automatic gap filling can be used to refine and extend metabolic reconstructions, thereby increasing their biological scope. Furthermore, we illustrate how incomplete human metabolic knowledge can be coupled with gene annotation in order to prioritize and confirm gene functions. [less ▲]

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See detailIntracellular metabolite profiling of platelets: evaluation of extraction processes and chromatographic strategies.
Paglia, Giuseppe; Magnusdottir, Manuela; Thorlacius, Steinunn et al

in Journal of Chromatography. B : Analytical Technologies in the Biomedical & Life Sciences (2012), 898

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is ... [more ▼]

An extraction method for intracellular metabolite profiling should ideally be able to recover the broadest possible range of metabolites present in a sample. However, the development of such methods is hampered by the diversity of the physico-chemical properties of metabolites as well as by the specific characteristics of samples and cells. In this study, we report the optimization of an UPLC-MS method for the metabolite analysis of platelet samples. The optimal analytical protocol was determined by testing seven different extraction methods as well as by employing two different LC-MS methods, in which the metabolites were separated by using hydrophilic interaction liquid chromatography (HILIC) and reversed phase liquid chromatography (RPLC). The optimal conditions were selected using the coverage of the platelets' metabolome, the response of the identified metabolites, the reproducibility of the analytical method, and the time of the analysis as main evaluation criteria. Our results show that methanol-water (7:3) extraction coupled with HILIC-MS method provides the best compromise, allowing identification of 107 metabolites in a platelet cell extract sample, 91% of them with a RSD% lower than 20. A higher number of metabolites could be detected when analyzing the platelet samples with two different LC-MS methods or when using complementary extraction methods in parallel. [less ▲]

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See detailMonitoring metabolites consumption and secretion in cultured cells using ultra-performance liquid chromatography quadrupole-time of flight mass spectrometry (UPLC-Q-ToF-MS).
Paglia, Giuseppe; Hrafnsdottir, Sigrun; Magnusdottir, Manuela et al

in Analytical and Bioanalytical Chemistry (2012), 402(3), 1183-98

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by ... [more ▼]

Here we present an ultra-performance liquid chromatography-mass spectrometry (UPLC-MS) method for extracellular measurements of known and unexpected metabolites in parallel. The method was developed by testing 86 metabolites, including amino acids, organic acids, sugars, purines, pyrimidines, vitamins, and nucleosides, that can be resolved by combining chromatographic and m/z dimensions. Subsequently, a targeted quantitative method was developed for 80 metabolites. The presented method combines a UPLC approach using hydrophilic interaction liquid chromatography (HILIC) and MS detection achieved by a hybrid quadrupole-time of flight (Q-ToF) mass spectrometer. The optimal setup was achieved by evaluating reproducibility and repeatability of the analytical platforms using pooled quality control samples to minimize the drift in instrumental performance over time. Then, the method was validated by analyzing extracellular metabolites from acute lymphoblastic leukemia cell lines (MOLT-4 and CCRF-CEM) treated with direct (A-769662) and indirect (AICAR) AMP activated kinase (AMPK) activators, monitoring uptake and secretion of the targeted compound over time. This analysis pointed towards a perturbed purine and pyrimidine catabolism upon AICAR treatment. Our data suggest that the method presented can be used for qualitative and quantitative analysis of extracellular metabolites and it is suitable for routine applications such as in vitro drug screening. [less ▲]

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