Lipocalin 2 modulates the cellular response to amyloid beta

The production, accumulation and aggregation of amyloid beta (Aß) peptides in Alzheimer's disease (AD) are influenced by different modulators. Among these are iron and iron-related proteins, given their ability to modulate the expression of the amyloid precursor protein and to drive Aß aggregation. Herein, we describe that lipocalin 2 (LCN2), a mammalian acute-phase protein involved in iron homeostasis, is highly produced in response to Aß1-42 by choroid plexus epithelial cells and astrocytes, but not by microglia or neurons. Although Aß1-42 stimulation decreases the dehydrogenase activity and survival of wild-type astrocytes, astrocytes lacking the expression of Lcn2 are not affected. This protection results from a lower expression of the proapoptotic gene Bim and a decreased inflammatory response. Altogether, these findings show that Aß toxicity to astrocytes requires LCN2, which represents a novel mechanism to target when addressing AD.Cell Death and Differentiation advance online publication, 23 May 2014; doi:10.1038/cdd.2014.68.We thank Dr. Ioannis Sotiropoulos for reagents and comments. Sandro Da Mesquita and Ana Catarina Ferreira are recipients of PhD fellowships and Fernanda Marques is recipient of a postdoctoral fellowship by the Fundacao para a Ciencia e Tecnologia (FCT, Portugal)/FEDER. This work was supported by a grant from FCT/FEDER (EXPL/NEUOSD/2196/2013)

Metabolic profiling of serum using Ultra Performance Liquid Chromatography and the LTQ-Orbitrap mass spectrometry system.

Advances in analytical instrumentation can provide significant advantages to the volume and quality of biological knowledge acquired in metabolomic investigations. The interfacing of sub-2 microm liquid chromatography (UPLC ACQUITY) and LTQ-Orbitrap mass spectrometry systems provides many theoretical advantages. The applicability of the interfaced systems was investigated using a simple 11-component metabolite mix and a complex mammalian biofluid, serum. Metabolites were detected in the metabolite mix with signals that were linear with their concentration over 2.5-3.5 orders of magnitude, with correlation coefficients greater than 0.993 and limits of detection less than 1 micromol L(-1). Reproducibility of retention time (RSD<3%) and chromatographic peak area (RSD<15%) and a high mass accuracy (<2 ppm) were observed for 14 QC serum samples interdispersed with other serum samples, analysed over a period of 40 h. The evaluation of a single deconvolution software package (XCMS) was performed and showed that two parameters (snthresh and bw) provided significant changes to the number of peaks detected and the peak area reproducibility for the dataset used. The data were used to indicate possible biomarkers of pre-eclampsia and showed both the instruments and XCMS to be applicable to the reproducible and valid detection of disease biomarkers present in serum

Detection and identification of novel metabolomic biomarkers in preeclampsia.

In a previous study, the ability of gas chromatography time-of-flight mass spectrometry to detect potential metabolic biomarkers in preeclampsia was demonstrated. In this study, the authors sought to validate their preliminary findings in an entirely different patient cohort using a complementary, novel, and powerful combination of analytical tools (ultra performance liquid chromatography and LTQ Orbitrap mass spectrometry system). Eight metabolites that appeared in the authors' previous patient cohort were identified as being statistically significant (P < .01) as discriminatory biomarkers. The chemical identities of these 8 metabolites were established using authentic chemical standards. They included uric acid, 2-oxoglutarate, glutamate, and alanine. This is the first study to identify, in an unbiased manner, a series of small-molecular-weight metabolites that effectively detect preeclampsia in plasma. The identity of these metabolites provides new insights into the pathology of this condition and raises the possibility of the development of a predictive test

Automated workflows for accurate mass-based putative metabolite identification in LC/MS-derived metabolomic datasets

MOTIVATION: The study of metabolites (metabolomics) is increasingly being applied to investigate microbial, plant, environmental and mammalian systems. One of the limiting factors is that of chemically identifying metabolites from mass spectrometric signals present in complex datasets. RESULTS: Three workflows have been developed to allow for the rapid, automated and high-throughput annotation and putative metabolite identification of electrospray LC-MS-derived metabolomic datasets. The collection of workflows are defined as PUTMEDID_LCMS and perform feature annotation, matching of accurate m/z to the accurate mass of neutral molecules and associated molecular formula and matching of the molecular formulae to a reference file of metabolites. The software is independent of the instrument and data pre-processing applied. The number of false positives is reduced by eliminating the inaccurate matching of many artifact, isotope, multiply charged and complex adduct peaks through complex interrogation of experimental data. AVAILABILITY: The workflows, standard operating procedure and further information are publicly available at http://www.mcisb.org/resources/putmedid.html. CONTACT: [email protected]

Effect of L-Ergothioneine on the metabolic plasma profile of the RUPP rat model of preeclampsia

Introduction Pre-eclampsia is a major cause of maternal and fetal mortality and morbidity worldwide. Its pathophysiology remains unclear, but mitochondrial dysfunction and oxidative stress have been implicated. L-Ergothioneine is a naturally occurring, water-soluble betaine, that has demonstrated antioxidant properties. Using the reduced uterine perfusion pressure (RUPP) rat model of pre-eclampsia, this study aimed to define the plasma metabolic profile following treatment with L-Ergothioneine. Methods The effect of L-Ergothioneine (ET) treatment was explored using in vivo treatment in rats: Sham control (SC, n = 5), RUPP control (RC, n = 5), Sham +ET (ST, n = 5), RUPP +ET (RT, n = 5). Differential expression of plasma metabolites were obtained using untargeted liquid chromatography coupled to mass spectrometry. Statistical analysis was performed on normalised data comparing RC to SC, RT to RC, and RT to ST. Metabolites significantly altered (FDR < 0.05) were identified through database search. Results We report significantly lower levels of L-palmitoylcarnitine in RC compared to SC, a fatty acyl substrate involved in beta-oxidation in the mitochondria. We report that a metabolite that has been associated with oxidative stress (Glutamylcysteine) was detected at significantly higher levels in RT vs RC and RT vs ST. Five metabolites associated with inflammation were significantly lower in RT vs RC and three metabolites in RT vs ST, demonstrating the anti-inflammatory effects of ET in the RUPP rat model of pre-eclampsia. Conclusions L-Ergothioneine may help preserve mitochondrial function by increasing antioxidant levels, and reducing inflammatory responses associated with pre-eclampsia. This study shows the potential of L-Ergothioneine as a treatment for pre-eclampsia