Plasma and intracellular levels of lactate dehydrogenase, phosphohexose isomerase and lysozyme activity in acute leukemia

Plasma and intracellular levels of lactate dehydrogenase (LDH), phosphohexose isomerase (PHI) and lysozyme activities were investigated in 20 patients with acute myelocytic leukemia (AML), 18 patients with acute lymphatic leukemia (ALL) and 10 patients with chronic myelocytic leukemia in blast transformation (CML/BT). Though the plasma levels of LDH and PHI in all patients with acute leukemia were elevated as compared to control persons there was no distinctive pattern which could be of use in the classification of acute leukemia. On the other hand the intracellular levels of these enzymes could be of value in classifying acute leukemia. The leukemic lymphoblasts were characterized by low levels of PHI and lysozyme as compared to leukemic myeloblasts or to normal lymphocytes (p less than 0.01). The LDH/PHI ratio is also significantly higher in leukemic lymphoblasts than in leukemic myeloblasts or in normal lymphocytes (p always less than 0.01). These characteristics might also be made use of in identifying the blasts of CML/BT als "lymphoid" or "myeloid" in corresponding cases.     

Electrophoretic transport of Tl+ in mitochondria

Summary The distribution of Tl⁺ between rat liver mitochondria and the medium was studied; millimolar or smaller concentrations of Tl⁺ were labeled with²⁰⁴Tl. The Tl⁺ distribution responded to transient diffusion potentials in a way that indicated electrophoretic movements of Tl⁺. The diffusion potentials were induced by efflux of K⁺ in response to addition of valinomycin to nonrespiring mitochondria suspended in a medium with low concentrations of K⁺ or by efflux of H⁺ induced by making the medium more alkaline in the presence of a protonophorous (proton-conducting) uncoupling agent. Changes in membrane potential induced by valinomycin were followed with the aid of safranine. Tl⁺ brought about collapse of the diffusion potential. It is concluded that Tl⁺ is able to penetrate the mitochondrial membrane electrophoretically.     

Stacking of safranine in liposomes during valinomycininduced efflux of potassium ions

Liposomes were prepared from phosphatidylcholine and cardiolipin in a KCl medium and suspended in a choline chloride medium with safranine. When efflux of K⁺ was induced by valinomycin, spectral shifts characteristic of stacking were observed. Ca²⁺ inhibited the rate of stacking in a competitive manner with a K_i of about 200 μM, while La³⁺ was about 10 times more potent. When liposomes were prepared from phospholipids with a higher ratio of cardiolipin to phosphatidyl-choline the inhibition was more potent. No effect on the stacking phenomena was seen when Ca²⁺ was added after the stacking was completed. When Ca²⁺ or an organic cation with four charges, spermine, was trapped in the intraliposomal compartment, no significant change in the rate of stacking was seen. However, the extent of stacking was decreased. It is suggested that safranine is driven by a diffusion potential to a site that is inaccessible to Ca²⁺ in the medium, presumably to the inner boundaries of the liposomal membranes.     

Evaluation of metabolomics profiles of grain from maize hybrids derived from near-isogenic GM positive and negative segregant inbreds demonstrates that observed differences cannot be attributed unequivocally to the GM trait

Introduction

Past studies on plant metabolomes have highlighted the influence of growing environments and varietal differences in variation of levels of metabolites yet there remains continued interest in evaluating the effect of genetic modification (GM).

Objectives

Here we test the hypothesis that metabolomics differences in grain from maize hybrids derived from a series of GM (NK603, herbicide tolerance) inbreds and corresponding negative segregants can arise from residual genetic variation associated with backcrossing and that the effect of insertion of the GM trait is negligible.

Methods

Four NK603-positive and negative segregant inbred males were crossed with two different females (testers). The resultant hybrids, as well as conventional comparator hybrids, were then grown at three replicated field sites in Illinois, Minnesota, and Nebraska during the 2013 season. Metabolomics data acquisition using gas chromatography–time of flight-mass spectrometry (GC–TOF-MS) allowed the measurement of 367 unique metabolite features in harvested grain, of which 153 were identified with small molecule standards. Multivariate analyses of these data included multi-block principal component analysis and ANOVA-simultaneous component analysis. Univariate analyses of all 153 identified metabolites was conducted based on significance testing (α = 0.05), effect size evaluation (assessing magnitudes of differences), and variance component analysis.

Results

Results demonstrated that the largest effects on metabolomic variation were associated with different growing locations and the female tester. They further demonstrated that differences observed between GM and non-GM comparators, even in stringent tests utilizing near-isogenic positive and negative segregants, can simply reflect minor genomic differences associated with conventional back-crossing practices.

Conclusion

The effect of GM on metabolomics variation was determined to be negligible and supports that there is no scientific rationale for prioritizing GM as a source of variation.

     

Proposed minimum reporting standards for chemical analysis

There is a general consensus that supports the need for standardized reporting of metadata or information describing large-scale metabolomics and other functional genomics data sets. Reporting of standard metadata provides a biological and empirical context for the data, facilitates experimental replication, and enables the re-interrogation and comparison of data by others. Accordingly, the Metabolomics Standards Initiative is building a general consensus concerning the minimum reporting standards for metabolomics experiments of which the Chemical Analysis Working Group (CAWG) is a member of this community effort. This article proposes the minimum reporting standards related to the chemical analysis aspects of metabolomics experiments including: sample preparation, experimental analysis, quality control, metabolite identification, and data pre-processing. These minimum standards currently focus mostly upon mass spectrometry and nuclear magnetic resonance spectroscopy due to the popularity of these techniques in metabolomics. However, additional input concerning other techniques is welcomed and can be provided via the CAWG on-line discussion forum at or . Further, community input related to this document can also be provided via this electronic forum. The contents of this paper do not necessarily reflect any position of the Government or the opinion of the Food and Drug Administration Sponsor: Metabolomics Society http://www.metabolomicssociety.org/ Reference: http://msi-workgroups.sourceforge.net/bio-metadata/reporting/pbc/ http://msi-workgroups.sourceforge.net/chemical-analysis/ Version: Revision: 5.1 Date: 09 January, 2007     

Metabolomics standards initiative: ontology working group work in progress

In this article we present the activities of the Ontology Working Group (OWG) under the Metabolomics Standards Initiative (MSI) umbrella. Our endeavour aims to synergise the work of several communities, where independent activities are underway to develop terminologies and databases for metabolomics investigations. We have joined forces to rise to the challenges associated with interpreting and integrating experimental process and data across disparate sources (software and databases, private and public). Our focus is to support the activities of the other MSI working groups by developing a common semantic framework to enable metabolomics-user communities to consistently annotate the experimental process and to enable meaningful exchange of datasets. Our work is accessible via a public webpage and a draft ontology has been posted under the Open Biological Ontology umbrella. At the very outset, we have agreed to minimize duplications across omics domains through extensive liaisons with other communities under the OBO Foundry. This is work in progress and we welcome new participants willing to volunteer their time and expertise to this open effort. See the MSI Ontology Working Group website for a complete list of members and contributors. Web URL:     

Identification and quantification of catecholamines in potato plants (Solanum tuberosum) by GC-MS

Dopamine, norepinephrine, and normetanephrine were identified by GC-MS in potato (Solanum tuberosum L.) plants, the latter was new for plants. The highest amount of catecholamines was found in leaves. A developmental stage dependent variation in potato leaf catecholamines accumulation was also observed with highest level in third leaves. Catecholamine contents decrease during cold storage of tubers to undetectable levels. Mechanical wounding of leaves led to a small increase in the level of catecholamines investigated.     

Process for the integrated extraction, identification and quantification of metabolites, proteins and RNA to reveal their co-regulation in biochemical networks

A novel extraction protocol is described with which metabolites, proteins and RNA are sequentially extracted from the same sample, thereby providing a convenient procedure for the analysis of replicates as well as exploiting the inherent biological variation of independent samples for multivariate data analysis. A detection of 652 metabolites, 297 proteins and clear RNA bands in a single Arabidopsis thaliana leaf sample was validated by analysis with gas chromatography coupled to a time of flight mass spectrometer for metabolites, two-dimensional liquid chromatography coupled to mass spectrometry for proteins, and Northern blot analysis for RNA. A subset of the most abundant proteins and metabolites from replicate analysis of different Arabidopsis accessions was merged to form an integrative dataset allowing both classification of different genotypes and the unbiased analysis of the hierarchical organization of proteins and metabolites within a real biochemical network.