Project description:To better understand proteostasis in health and disease, determination of protein half-lives is essential. We improved the precision and accuracy of peptide-ion intensity based quantification in order to enable accurate determination of protein turnover in non-dividing cells using dynamic-SILAC. This enabled precise and accurate protein half-life determination ranging from 10 to more than 1000 hours. We achieve good proteomic coverage ranging from four to six thousand proteins in several types of non-dividing cells, corresponding to a total of 9699 unique proteins over the entire dataset. Good agreement was observed in half-lives between B-cells, natural killer cells and monocytes, while hepatocytes and mouse embryonic neurons showed substantial differences. Our comprehensive dataset enabled extension and statistical validation of the previous observation that subunits of protein complexes tend to have coherent turnover. Furthermore, we observed complex architecture dependent turnover within complexes of the proteasome and the nuclear pore complex. Our method is broadly applicable and might be used to investigate protein turnover in various cell types.
Project description:Identification of unknown peaks in gas chromatography/mass spectrometry (GC/MS)-based discovery metabolomics is challenging, and remains necessary to permit discovery of novel or unexpected metabolites that may elucidate disease processes and/or further our understanding of how genotypes relate to phenotypes. Here, we introduce two new technologies and an analytical workflow that can facilitate the identification of unknown peaks. First, we report on a GC/Quadrupole-Orbitrap mass spectrometer that provides high mass accuracy, high resolution, and high sensitivity analyte detection. Second, with an "intelligent" data-dependent algorithm, termed molecular-ion directed acquisition (MIDA), we maximize the information content generated from unsupervised tandem MS (MS/MS) and selected ion monitoring (SIM) by directing the MS to target the ions of greatest information content, that is, the most-intact ionic species. We combine these technologies with (13)C- and (15)N-metabolic labeling, multiple derivatization and ionization types, and heuristic filtering of candidate elemental compositions to achieve (1) MS/MS spectra of nearly all intact ion species for structural elucidation, (2) knowledge of carbon and nitrogen atom content for every ion in MS and MS/MS spectra, (3) relative quantification between alternatively labeled samples, and (4) unambiguous annotation of elemental composition.
Project description:Fatty acids (FAs) play critical roles in health and disease. The detection of FA imbalances through metabolomics can provide an overview of an individual's health status, particularly as regards chronic inflammatory disorders. In this study, we aimed to establish sensitive reference value ranges for targeted plasma FAs in a well‑defined population of healthy adults. Plasma samples were collected from 159 participants admitted as outpatients. A total of 24 FAs were analyzed using gas chromatography‑mass spectrometry, and physiological values and 95% reference intervals were calculated using an approximate method of analysis. The differences among the age groups for the relative levels of stearic acid (P=0.005), the omega‑6/omega‑3 ratio (P=0.027), the arachidonic acid/eicosapentaenoic acid ratio (P<0.001) and the linoleic acid‑produced dihomo‑gamma‑linolenic acid (P=0.046) were statistically significant. The majority of relative FA levels were higher in males than in females. The levels of myristic acid (P=0.0170) and docosahexaenoic acid (P=0.033) were significantly different between the sexes. The reference values for the FAs examined in this study represent a baseline for further studies examining the reproducibility of this methodology and sensitivities for nutrient deficiency detection and investigating the biochemical background of pathological conditions. The application of these values to clinical practice will allow for the discrimination between health and disease and contribute to early prevention and treatment.
Project description:Exosomes/microvesicles (hereafter referred to as extracellular vesicles) were isolated from the ULF of day 14 cyclic and pregnant ewes using ExoQuick-TC. Extracellular vesicle RNA was pooled (n=4 per status) and analyzed for small RNAs by sequencing on the Ion Torrent PGM platform and analysis with CLC Genomics Workbench small RNA workflow based on the miRBase (Release 19) Bos taurus database. Small RNA analysis of day 14 uterine luminal fluid extracellular vesicles isolated from pregnant and cyclic ewes.
Project description:Rabies is a rapidly progressive lyssavirus encephalitis that is statistically 100% fatal. There are no clinically effective antiviral drugs for rabies. An immunologically naïve teenager survived rabies in 2004 through improvised supportive care; since then, 5 additional survivors have been associated with use of the so-called Milwaukee Protocol (MP). The MP applies critical care focused on the altered metabolic and physiologic states associated with rabies. The aim of this study was to examine the metabolic profile of cerebrospinal fluid (CSF) from rabies patients during clinical progression of rabies encephalitis in survivors and nonsurvivors and to compare these samples with control CSF samples. Unsupervised clustering algorithms distinguished three stages of rabies disease and identified several metabolites that differentiated rabies survivors from those who subsequently died, in particular, metabolites related to energy metabolism and cell volume control. Moreover, for those patients who survived, the trajectory of their metabolic profile tracked toward the control profile and away from the rabies profile. NMR metabolomics of human rabies CSF provide new insights into the mechanisms of rabies pathogenesis, which may guide future therapy of this disease.
Project description:Experimental Autoimmune Encephalomyelitis (EAE) is the most commonly used animal model for Multiple Sclerosis (MScl). CSF metabolomics in an acute EAE rat model was investigated using targetted LC-MS and GC-MS. Acute EAE in Lewis rats was induced by co-injection of Myelin Basic Protein with Complete Freund's Adjuvant. CSF samples were collected at two time points: 10 days after inoculation, which was during the onset of the disease, and 14 days after inoculation, which was during the peak of the disease. The obtained metabolite profiles from the two time points of EAE development show profound differences between onset and the peak of the disease, suggesting significant changes in CNS metabolism over the course of MBP-induced neuroinflammation. Around the onset of EAE the metabolome profile shows significant decreases in arginine, alanine and branched amino acid levels, relative to controls. At the peak of the disease, significant increases in concentrations of multiple metabolites are observed, including glutamine, O-phosphoethanolamine, branched-chain amino acids and putrescine. Observed changes in metabolite levels suggest profound changes in CNS metabolism over the course of EAE. Affected pathways include nitric oxide synthesis, altered energy metabolism, polyamine synthesis and levels of endogenous antioxidants. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1007/s11306-011-0306-3) contains supplementary material, which is available to authorized users.
Project description:A defining characteristic of quiescent cells is their low level of gene activity compared to growing cells. Using a yeast model for cellular quiescence, we compared the genome-wide profiles of multiple histone modifications between growing and quiescent cells, and correlated these profiles with the presence of RNA polymerase II and its transcripts. Quiescent cells retained several forms of histone methylation normally associated with transcriptionally active chromatin and had many transcripts in common with growing cells. Quiescent cells also contained high levels of RNA polymerase II, but only low levels of the canonical initiating and elongating forms of the polymerase. The data suggest that the transcript and histone methylation marks in quiescent cells were either inherited from growing cells or established early during the development of quiescence and then retained in this non-growing cell population. This might ensure that quiescent cells can rapidly adapt to a changing environment to resume growth. RNA-seq analysis was performed in yeast Log-phase cells and purified Quiescent yeast cells and the transcriptomes in each were compared. The RNA data was correlated with genomic RNA polymerase II and histone H3 methylation occupancy profiles in the log and quiescent cells.
Project description:Stinging nettle (Urtica dioica L.) is one fantastic plant widely used in folk medicine, pharmacy, cosmetics, and food. This plant's popularity may be explained by its chemical composition, containing a wide range of compounds significant for human health and diet. This study aimed to investigate extracts of exhausted stinging nettle leaves after supercritical fluid extraction obtained using ultrasound and microwave techniques. Extracts were analyzed to obtain insight into the chemical composition and biological activity. These extracts were shown to be more potent than those of previously untreated leaves. The principal component analysis was applied as a pattern recognition tool to visualize the antioxidant capacity and cytotoxic activity of extract obtained from exhausted stinging nettle leaves. An artificial neural network model is presented for the prediction of the antioxidant activity of samples according to polyphenolic profile data, showing a suitable anticipation property (the r2 value during the training cycle for output variables was 0.999).