35 research outputs found
Molecular toxicity of cerium oxide nanoparticles to the freshwater alga <i>Chlamydomonas reinhardtii</i> is associated with supra-environmental exposure concentrations
<p>Ceria nanoparticles (NPs) are widely used as fuel catalysts and consequently are likely to enter the environment. Their potential impacts on. biota at environmentally relevant concentrations, including uptake and toxicity, remain to be elucidated and quantitative data on which to assess risk are sparse. Therefore, a definitive assessment of the molecular and phenotypic effects of ceria NPs was undertaken, using well-characterised mono-dispersed NPs as their toxicity is likely to be higher, enabling a conservative hazard assessment. Unbiased transcriptomics and metabolomics approaches were used to investigate the potential toxicity of tightly constrained 4–5 nm ceria NPs to the unicellular green alga, <i>Chlamydomonas reinhardtii</i>, a sentinel freshwater species. A wide range of exposure concentrations were investigated from predicted environmental levels, to support hazard assessment, to supra-environmental levels to provide insight into molecular toxicity pathways. Ceria NPs were internalised into intracellular vesicles within <i>C. reinhardtii</i>, yet caused no significant effect on algal growth at any exposure concentration. Molecular perturbations were only detected at supra-environmental ceria NP-concentrations, primarily down-regulation of photosynthesis and carbon fixation with associated effects on energy metabolism. For acute exposures to small mono-dispersed particles, it can be concluded there should be little concern regarding their dispersal into the environment for this trophic level.</p
Exo-Metabolome of <i>Pseudovibrio</i> sp. FO-BEG1 Analyzed by Ultra-High Resolution Mass Spectrometry and the Effect of Phosphate Limitation
<div><p>Oceanic dissolved organic matter (DOM) is an assemblage of reduced carbon compounds, which results from biotic and abiotic processes. The biotic processes consist in either release or uptake of specific molecules by marine organisms. Heterotrophic bacteria have been mostly considered to influence the DOM composition by preferential uptake of certain compounds. However, they also secrete a variety of molecules depending on physiological state, environmental and growth conditions, but so far the full set of compounds secreted by these bacteria has never been investigated. In this study, we analyzed the exo-metabolome, metabolites secreted into the environment, of the heterotrophic marine bacterium <i>Pseudovibrio</i> sp. FO-BEG1 via ultra-high resolution mass spectrometry, comparing phosphate limited with phosphate surplus growth conditions. Bacteria belonging to the <i>Pseudovibrio</i> genus have been isolated worldwide, mainly from marine invertebrates and were described as metabolically versatile <i>Alphaproteobacteria</i>. We show that the exo-metabolome is unexpectedly large and diverse, consisting of hundreds of compounds that differ by their molecular formulae. It is characterized by a dynamic recycling of molecules, and it is drastically affected by the physiological state of the strain. Moreover, we show that phosphate limitation greatly influences both the amount and the composition of the secreted molecules. By assigning the detected masses to general chemical categories, we observed that under phosphate surplus conditions the secreted molecules were mainly peptides and highly unsaturated compounds. In contrast, under phosphate limitation the composition of the exo-metabolome changed during bacterial growth, showing an increase in highly unsaturated, phenolic, and polyphenolic compounds. Finally, we annotated the detected masses using multiple metabolite databases. These analyses suggested the presence of several masses analogue to masses of known bioactive compounds. However, the annotation was successful only for a minor part of the detected molecules, underlining the current gap in knowledge concerning the biosynthetic ability of marine heterotrophic bacteria.</p></div
Hypoxia Triggers Major Metabolic Changes in AML Cells without Altering Indomethacin-Induced TCA Cycle Deregulation
Our previous studies have shown that the nonsteroidal anti-inflammatory drug indomethacin exhibits antileukemic activity <i>in vitro</i> and can inhibit the aldo-keto reductase AKR1C3, which we identified as a novel target in acute myeloid leukemia. However, the antileukemic actions of indomethacin are likely to be complex and extend beyond inhibition of either AKR1C3 or cycloxygenases. To further understand the antileukemic activity of indomethacin we have used untargeted nuclear magnetic resonance-based metabolic analysis to characterize the responses of KG1a and K562 cell lines in both normal culture conditions and in hypoxia, which better represents the tumor environment <i>in vivo</i>. Hypoxia induced dramatic metabolic changes in untreated KG1a and K562, including adaptation of both phospholipid and glycolytic metabolism. Despite these changes, both cell lines sustained relatively unaltered mitochondrial respiration. The administration of indomethacin induced similar metabolic responses regardless of the oxygen level in the environment. Notable exceptions included metabolites associated with <i>de novo</i> fatty acid synthesis and choline phospholipid metabolism. Collectively, these results suggest that leukemia cells have the inherent ability to tolerate changes in oxygen tension while maintaining an unaltered mitochondrial respiration. However, the administration of indomethacin significantly increased oxidative stress in both KG1a and K562, inducing mitochondrial dysfunction, regardless of the oxygenation conditions. These findings emphasize the particular pertinence of the tricarboxylic acid cycle to the survival of cancer cells and may explain why some antileukemic drugs have been discovered and developed successfully despite the use of culture conditions that do not reflect the hypoxic environment of cancer cells <i>in vivo</i>
Percentages of molecular formulae attributed to molecular categories.
<p>Only masses detected in all biological triplicates for each time point were considered.</p
Bacterial growth (A) and concentrations of solid phase extractable dissolved organic carbon (SPE-DOC) (B).
<p>The bars (<b>B</b>) represent the average concentrations of SPE-DOC measured in the solid phase extracts of the biological triplicates collected during growth under both +P<sub>i</sub> (black) and −P<sub>i</sub> conditions (white). The inner panel (<b>A</b>) shows the cell growth, measured as cell density over time, for the two tested conditions. Filled circles represent the cultures growing under +P<sub>i</sub> conditions and empty circles represent the cultures growing under −P<sub>i</sub> conditions. Error bars indicate the standard deviation of biological triplicates</p
Overview of the data obtained from the ESI-negative FT-ICR-MS analysis.
<p>The number of masses detected in all biological triplicates of each time point is shown. The data refer to the dataset obtained after applying the filtration criteria described in the Materials and Methods section. Values in brackets represent the percentages of masses to which a unique molecular formula could be assigned and the percentages of unique molecular formula containing heteroatoms. Isotopologues of assigned molecular formulae are not counted as assigned. Overall, a unique molecular formula could be assigned to 4,122 masses, corresponding to 49% of the obtained <i>m</i>/<i>z</i>.</p
Similarity among the FT-ICR-MS samples analyzed in ESI-negative mode during bacterial growth under +P<sub>i</sub> and −P<sub>i</sub> conditions.
<p>Non metrical multidimensional scaling (NMDS) was performed by employing the Bray-Curtis similarity index and using the data of the unfiltered (<b>A</b>) and filtered (<b>B</b>) datasets. All biological triplicates of +P<sub>i</sub> (filled circles) and −P<sub>i</sub> (empty circles) conditions are shown. Nearest neighbor samples (i.e. most similar) are connected to visualize pairwise sample similarities. The stress value for both plots is 0.06.</p
Partial Least Squares Discriminant Analysis of NMR spectra acquired on blood serum samples.
<p>Scores (<b>A</b> and <b>B</b>) and weights (on LV1; <b>C</b> and <b>D</b>) plots obtained from OSC-PLS-DA performed on the NMR spectra of 37 and 42 blood serum samples for the comparison of groups B versus C1 (<b>A</b> and <b>C</b>) and B versus C2 (<b>B</b> and <b>D</b>). Group B (solid green, 27 samples): patients after chemotherapy; group C1 (solid blue, 10 samples): sustained remission; group C2 (empty blue, 15 samples): in relapse after chemotherapy. Cho: choline; Suc: succinate; Pyr: pyruvate; Ace: acetate; 2HiB: 2-hydroxyisobutyrate; Car: carnitine; AcCar: acetylcarnitine.</p
Partial Least Squares Discriminant Analysis of NMR spectra acquired on blood serum samples.
<p>Scores (<b>A</b>) and weights (on LV1, <b>B</b>, and LV2, <b>C</b>) plots obtained from OSC-PLS-DA performed on the NMR spectra of 44 blood serum samples. Group A (solid red, 19 samples): patients at diagnosis; group C1 (solid blue, 10 samples): sustained remission and group C2 (empty blue, 15 samples): in relapse after chemotherapy. Cho: choline; Cre: creatinine; Pyr: pyruvate; Ala: alanine; 2HiB: 2-hydroxyisobutyrate; Lac: lactate; 2HB: 2-hydroxybutyrate. H-xan: hypoxantine; Glu: glutamate; Gln: glutamine; Ace: acetate.</p
Blood serum concentration of acetylcarnitine and carnitine.
<p>Blood serum concentration of acetylcarnitine (AcCAR) and carnitine (CAR) in MM patients at diagnosis, in remission and after relapse of active disease following chemotherapy. Data shown as mean ± s.e.m. Statistical significance calculated according to Kruskal-Wallis one-way ANOVA (p<0.05).</p