2,177 research outputs found
MetaboLab - advanced NMR data processing and analysis for metabolomics
Background\ud
Despite wide-spread use of Nuclear Magnetic Resonance (NMR) in metabolomics for the analysis of biological samples there is a lack of graphically driven, publicly available software to process large one and two-dimensional NMR data sets for statistical analysis.\ud
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Results\ud
Here we present MetaboLab, a MATLAB based software package that facilitates NMR data processing by providing automated algorithms for processing series of spectra in a reproducible fashion. A graphical user interface provides easy access to all steps of data processing via a script builder to generate MATLAB scripts, providing an option to alter code manually. The analysis of two-dimensional spectra (1H,13C-HSQC spectra) is facilitated by the use of a spectral library derived from publicly available databases which can be extended readily. The software allows to display specific metabolites in small regions of interest where signals can be picked. To facilitate the analysis of series of two-dimensional spectra, different spectra can be overlaid and assignments can be transferred between spectra. The software includes mechanisms to account for overlapping signals by highlighting neighboring and ambiguous assignments.\ud
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Conclusions\ud
The MetaboLab software is an integrated software package for NMR data processing and analysis, closely linked to the previously developed NMRLab software. It includes tools for batch processing and gives access to a wealth of algorithms available in the MATLAB framework. Algorithms within MetaboLab help to optimize the flow of metabolomics data preparation for statistical analysis. The combination of an intuitive graphical user interface along with advanced data processing algorithms facilitates the use of MetaboLab in a broader metabolomics context.\ud
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Metabolomic Evidence for a Field Effect in Histologically Normal and Metaplastic Tissues in Patients with Esophageal Adenocarcinoma
Patients with Barrett's esophagus (BO) are at increased risk of developing esophageal adenocarcinoma (EAC). Most Barrett's patients, however, do not develop EAC, and there is a need for markers that can identify those most at risk. This study aimed to see if a metabolic signature associated with the development of EAC existed. For this, tissue extracts from patients with EAC, BO, and normal esophagus were analyzed using 1H nuclear magnetic resonance. Where possible, adjacent histologically normal tissues were sampled in those with EAC and BO. The study included 46 patients with EAC, 7 patients with BO, and 68 controls who underwent endoscopy for dyspeptic symptoms with normal appearances. Within the cancer cohort, 9 patients had nonneoplastic Barrett's adjacent to the cancer suitable for biopsy. It was possible to distinguish between histologically normal, BO, and EAC tissue in EAC patients [area under the receiver operator curve (AUROC) 1.00, 0.86, and 0.91] and between histologically benign BO in the presence and absence of EAC (AUROC 0.79). In both these cases, sample numbers limited the power of the models. Comparison of histologically normal tissue proximal to EAC versus that from controls (AUROC 1.00) suggests a strong field effect which may develop prior to overt EAC and hence be useful for identifying patients at high risk of developing EAC. Excellent sensitivity and specificity were found for this model to distinguish histologically normal squamous esophageal mucosa in EAC patients and healthy controls, with 8 metabolites being very significantly altered. This may have potential diagnostic value if a molecular signature can detect tissue from which neoplasms subsequently arise
Improved stability and spectral quality in ex situ dissolution DNP using an improved transfer device
Dissolution dynamic nuclear polarization (DNP) has become one of the predominant implementations for DNP. However, the technical implementation of transferring the sample from the polarizer to the nuclear magnetic resonance (NMR) system remains challenging. There is a need for additional technical optimizations in order to use dissolution DNP for biochemical and chemical applications. Here we show how a newly designed pressure dissolution kit considerably improves spectral quality and stability by enabling highly reliable and fast sample transfer to the NMR system
Molecular basis for the hormonal regulation of the tyrosine aminotransferase and tryptophane oxygenase genes
Crosstalk between AML and stromal cells triggers acetate secretion through the metabolic rewiring of stromal cells
Acute myeloid leukaemia (AML) cells interact and modulate components of their surrounding microenvironment into their own benefit. Stromal cells have been shown to support AML survival and progression through various mechanisms. Nonetheless, whether AML cells could establish beneficial metabolic interactions with stromal cells is underexplored. By using a combination of human AML cell lines and AML patient samples together with mouse stromal cells and a MLL-AF9 mouse model, here we identify a novel metabolic crosstalk between AML and stromal cells where AML cells prompt stromal cells to secrete acetate for their own consumption to feed the tricarboxylic acid cycle (TCA) and lipid biosynthesis. By performing transcriptome analysis and tracer-based metabolic NMR analysis, we observe that stromal cells present a higher rate of glycolysis when co-cultured with AML cells. We also find that acetate in stromal cells is derived from pyruvate via chemical conversion under the influence of reactive oxygen species (ROS) following ROS transfer from AML to stromal cells via gap junctions. Overall, we present a unique metabolic communication between AML and stromal cells and propose two different molecular targets, ACSS2 and gap junctions, that could potentially be exploited for adjuvant therapy
Metabolomic Profiling of Drug Responses in Acute Myeloid Leukaemia Cell Lines
Combined bezafibrate (BEZ) and medroxyprogesterone acetate (MPA) exert unexpected antileukaemic activities against acute myeloid leukaemia (AML) and these activities are associated with the generation of reactive oxygen species (ROS) within the tumor cells. Although the generation of ROS by these drugs is supported by preceding studies including our own, the interrelationship between the cellular effects of the drugs and ROS generation is not well understood. Here we report the use of NMR metabolomic profiling to further study the effect of BEZ and MPA on three AML cell lines and to shed light on the underlying mechanism of action. For this we focused on drug effects induced during the initial 24 hours of treatment prior to the onset of overt cellular responses and examined these in the context of basal differences in metabolic profiles between the cell lines. Despite their ultimately profound cellular effects, the early changes in metabolic profiles engendered by these drugs were less pronounced than the constitutive metabolic differences between cell types. Nonetheless, drug treatments engendered common metabolic changes, most markedly in the response to the combination of BEZ and MPA. These responses included changes to TCA cycle intermediates consistent with recently identified chemical actions of ROS. Notable amongst these was the conversion of α-ketoglutarate to succinate which was recapitulated by the treatment of cell extracts with exogenous hydrogen peroxide. These findings indicate that the actions of combined BEZ and MPA against AML cells are indeed mediated downstream of the generation of ROS rather than some hitherto unsuspected mechanism. Moreover, our findings demonstrate that metabolite profiles represent highly sensitive markers for genomic differences between cells and their responses to external stimuli. This opens new perspectives to use metabolic profiling as a tool to study the rational redeployment of drugs in new disease settings
AFe2As2 (A = Ca, Sr, Ba, Eu) and SrFe_(2-x)TM_(x)As2 (TM = Mn, Co, Ni): crystal structure, charge doping, magnetism and superconductivity
The electronic structure and physical properties of the pnictide compound
families OFeAs ( = La, Ce, Pr, Nd, Sm), FeAs ( = Ca,
Sr, Ba, Eu), LiFeAs and FeSe are quite similar. Here, we focus on the members
of the FeAs family whose sample composition, quality and single
crystal growth are better controllable compared to the other systems. Using
first principles band structure calculations we focus on understanding the
relationship between the crystal structure, charge doping and magnetism in
FeAs systems. We will elaborate on the tetragonal to
orthorhombic structural distortion along with the associated magnetic order and
anisotropy, influence of doping on the site as well as on the Fe site, and
the changes in the electronic structure as a function of pressure.
Experimentally, we investigate the substitution of Fe in
SrFeAs by other 3 transition metals, = Mn, Co, Ni.
In contrast to a partial substitution of Fe by Co or Ni (electron doping) a
corresponding Mn partial substitution does not lead to the supression of the
antiferromagnetic order or the appearance of superconductivity. Most calculated
properties agree well with the measured properties, but several of them are
sensitive to the As position. For a microscopic understanding of the
electronic structure of this new family of superconductors this structural
feature related to the Fe-As interplay is crucial, but its correct ab initio
treatment still remains an open question.Comment: 27 pages, single colum
Automated image quality assessment for selecting among multiple magnetic resonance image acquisitions in the German National Cohort study
Glucose utilization via glycogen phosphorylase sustains proliferation and prevents premature senescence in cancer cells.
Metabolic reprogramming of cancer cells provides energy and multiple intermediates critical for cell growth. Hypoxia in tumors represents a hostile environment that can encourage these transformations. We report that glycogen metabolism is upregulated in tumors in vivo and in cancer cells in vitro in response to hypoxia. In vitro, hypoxia induced an early accumulation of glycogen, followed by a gradual decline. Concordantly, glycogen synthase (GYS1) showed a rapid induction, followed by a later increase of glycogen phosphorylase (PYGL). PYGL depletion and the consequent glycogen accumulation led to increased reactive oxygen species (ROS) levels that contributed to a p53-dependent induction of senescence and markedly impaired tumorigenesis in vivo. Metabolic analyses indicated that glycogen degradation by PYGL is important for the optimal function of the pentose phosphate pathway. Thus, glycogen metabolism is a key pathway induced by hypoxia, necessary for optimal glucose utilization, which represents a targetable mechanism of metabolic adaptation
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