Project description:CNS injuries of the anuran amphibian, Xenopus laevis, are uniquely suited for studying the molecular compositions of neuronal regeneration of retinal ganglion cells (RGC) due to a functional recovery of optic axons disparate to adult mammalian analogues. RGCs and their optic nerve axons undergo irreversible neurodegeneration in glaucoma and associated optic neuropathies, resulting in blindness in mammals. Conversely, Xenopus demonstrates RGC lifetime-spanning regenerative capabilities after optic nerve crush [1], inciting opportunities to compare de novo regeneration and develop efficient pharmaceutical approaches for vision restoration. Studies revealing lipidome alterations during optic nerve regeneration are sparse and could serve as a solid foundation for these underlying molecular changes. We profile the lipid changes in a transgenic line of 1 year old Xenopus laevis Tg(islet2b:gfp) frogs that were either left untreated (naïve) or had a monocular surgery of either a left optic crush injury (crush) or sham surgery (sham). Matching controls of uninjured right optic nerves were also collected (control). Tg(islet2b:gfp) frogs were allowed to recover for 7,12,18, and 27 days post optic nerve crush. Following euthanasia, the optic nerves were collected for lipidomic analysis. A modified Bligh and Dyer method [2] was used for lipid extraction, followed by untargeted mass spectrometry lipid profiling with a Q Exactive Orbitrap Mass Spectrometer coupled with a Vanquish Horizon Binary UHPLC LC-MS system (LC MS-MS). The raw scans were analyzed and quantified with LipidSearch 5.0 and the statistical analysis was conducted through Metaboanalyst 5.0. This data is available at Metabolomics Workbench, study ID [ST002414].
Project description:The optic nerve is part of the mammalian adult central nervous system (CNS) and has limited capability to regenerate after injury. Deletion of phosphatase and tensin homolog (PTEN), a negative regulator of the PI3 kinase/Akt pathway, has been shown to promote regeneration in retinal ganglion cells (RGCs) after optic nerve injury [1]. We present the lipidome of adult PTENloxP/loxP mice subjected to intravitreal injection of adeno-associated viruses expressing Cre (AAV-Cre) as a model of CNS neuroregeneration. At 4 weeks old, PTENloxP/loxP mice were intravitreally-injected with 2-3 μl of either AAV-Cre (KO) or AAV-PLAP (control), and two weeks later optic nerve crush was performed. At indicated time-points after crush (0 days, 7 days, 14 days), mice were euthanized and optic nerves were immediately dissected out, and then flash frozen on dry ice. A modified Bligh and Dyer [2] method was used for lipid extraction from the optic nerves, followed by liquid chromatography-mass spectrometry (LC MS-MS) lipid profiling using a Q-Exactive Orbitrap instrument coupled with Accela 600 HPLC. The raw scans were analysed with LipidSearch 4.2 and the statistical analysis was conducted through Metaboanalyst 4.0. This data is available at Metabolomics Workbench, study ID ST001477.
Project description:The right optic nerve of adult, 6 month to 1 year old, female and male Danio rerio were crushed and collected three days after. Matching controls of uninjured left optic nerves were also collected. The tissue was dissected from euthanized fish and frozen on dry ice. Samples were pooled for each category (female crush, female control, male crush, male control) n = 24 to obtain sufficient tissue for analysis. The brain from one male fish was also collected for control/calibration. Lipid extraction was done with the Bligh and Dyer [1] method, followed by untargeted liquid chromatography-mass spectrometry (LC MS-MS) lipid profiling using a Q-Exactive Orbitrap instrument coupled with Vanquish Horizon Binary UHPLC LC-MS system. The lipids were identified and quantified with LipidSearch 4.2.21 and the statistical analysis was conducted through Metaboanalyst 5.0. This data is available at Metabolomics Workbench, Study ID ST001725.
Project description:Garcinia mangostana L. (mangosteen) seed is recalcitrant, prone to low temperature and drying which limit its long-term storage. Therefore, it is imperative to understand the metabolic changes throughout its development, to shed some light into the recalcitrant nature of this seed. We performed metabolomics analysis on mangosteen seed at different stages of development; six, eight, ten, twelve and fourteen weeks after anthesis. Seed samples were subjected to methanol extraction prior analysis using liquid chromatography - mass spectrometry (LC-MS). The MS data acquired were analyzed using ProfileAnalysis (version 2.1). This data article refers to the article entitled "Metabolomics analysis of developing Garcinia mangostana seed reveals modulated levels of sugars, organic acids and phenylpropanoid compounds" (Mazlan et al., 2018) [1].
Project description:Liquid chromatography tandem mass spectrometry (LC-MS/MS) has been used historically in proteomics research for over 20 years. However, until recently LC-MS/MS has only been routinely used in food testing for small molecule contaminant detection, for example pesticide and veterinary residue detection, and not as a replacement of microbiological food testing methods, specifically allergen analysis. Over the last couple of years, articles have started to be published which describe the detection of allergens by LC-MS/MS. In this article we will describe how LC-MS/MS can be applied in the area of gluten detection and how it can be used to specifically differentiate the species of gluten used in food, where specific markers for each variety of gluten can be simultaneously acquired and detected at the same time. The article will discuss the effect of variety on the peptide response observed from different wheat grain varieties and will describe the sample preparation protocol which is essential for generating the peptide markers used for speciation.
Project description:We have begun an early phase of biomarker discovery in three clinically important types of breast cancer using a panel of human cell lines: HER2 positive, hormone receptor positive and HER2 negative, and triple negative (HER2-, ER-, PR-). We identified and characterized the most abundant secreted, sloughed, or leaked proteins released into serum free media from these breast cancer cell lines using a combination of protein fractionation methods before LC-MS/MS mass spectrometry analysis. A total of 249 proteins were detected in the proximal fluid of 7 breast cancer cell lines. The expression of a selected group of high abundance and/or breast cancer-specific potential biomarkers including thromobospondin 1, galectin-3 binding protein, cathepsin D, vimentin, zinc-?2-glycoprotein, CD44, and EGFR from the breast cancer cell lines and in their culture media were further validated by Western blot analysis. Interestingly, mass spectrometry identified a cathepsin D protein single-nucleotide polymorphism (SNP) by alanine to valine replacement from the MCF-7 breast cancer cell line. Comparison of each cell line media proteome displayed unique and consistent biosignatures regardless of the individual group classifications, demonstrating the potential for stratification of breast cancer. On the basis of the cell line media proteome, predictive Tree software was able to categorize each cell line as HER2 positive, HER2 negative, and hormone receptor positive and triple negative based on only two proteins, muscle fructose 1,6-bisphosphate aldolase and keratin 19. In addition, the predictive Tree software clearly identified MCF-7 cell line overexpresing the HER2 receptor with the SNP cathepsin D biomarker.
Project description:Multimodal mass spectrometry imaging (MSI) is a critical technique used for deeply investigating biological systems by combining multiple MSI platforms in order to gain the maximum molecular information about a sample that would otherwise be limited by a single analytical technique. The aim of this work was to create a multimodal MSI approach that measures metabolomic and proteomic data from a single biological organ by combining infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) for metabolomic MSI and nanodroplet processing in one pot for trace samples (nanoPOTS) LC-MS/MS for spatially resolved proteome profiling. Adjacent tissue sections of rat brain were analyzed by each platform, and each data set was individually analyzed using previously optimized workflows. IR-MALDESI data sets were annotated by accurate mass and spectral accuracy using HMDB, METLIN, and LipidMaps databases, while nanoPOTS-LC-MS/MS data sets were searched against the rat proteome using the Sequest HT algorithm and filtered with a 1% FDR. The combined data revealed complementary molecular profiles distinguishing the corpus callosum against other sampled regions of the brain. A multiomic pathway integration showed a strong correlation between the two data sets when comparing average abundances of metabolites and corresponding enzymes in each brain region. This work demonstrates the first steps in the creation of a multimodal MSI technique that combines two highly sensitive and complementary imaging platforms. Raw data files are available in METASPACE (https://metaspace2020.eu/project/pace-2021) and MassIVE (identifier: MSV000088211).
Project description:This study was conducted to optimize a targeted plant proteomics approach from signature peptide selection and liquid chromatography with tandem mass spectrometry (LC-MS/MS) analytical method development and optimization to sample preparation method optimization. Three typical protein extraction and precipitation methods, including trichloroacetic acid (TCA)/acetone method, phenol method, and TCA/acetone/phenol method, and two digestion methods, including trypsin digestion and LysC/trypsin digestion, were evaluated for selected proteins related to the impact of engineered nanomaterials (ENMs) on wheat (Triticum aestivum) plant growth. In addition, we compared two plant tissue homogenization methods: grinding freeze-dried tissue and fresh tissue into a fine powder using a mortar and pestle aided with liquid nitrogen. Wheat plants were grown under a 16 h photoperiod (light intensity 150 μmol·m-2·s-1) for 4 weeks at 22 °C with a relative humidity of 60% and were watered daily to maintain a 70-90% water content in the soil. Processed samples were analyzed with an optimized LC-MS/MS method. The concentration of selected signature peptides for the wheat proteins of interest indicated that the phenol extraction method using fresh plant tissue, coupled with trypsin digestion, was the best sample preparation method for the targeted proteomics study. Overall, the optimized approach yielded the highest total peptide concentration (68,831 ng/g, 2.4 times the lowest concentration) as well as higher signature peptide concentrations for most peptides (19 out of 28). In addition, three of the signature peptides could only be detected using the optimized approach. This study provides a workflow for optimizing targeted proteomics studies.
Project description:This study aims to validate a fast method of simultaneous analysis of 365 LC-amenable and 142 GC-amenable pesticides in hen eggs by liquid chromatography-tandem mass spectrometry (LC-MS/MS) and gas chromatography-tandem mass spectrometry (GC-MS/MS), respectively, operating in multiple reaction monitoring (MRM) acquisition modes. The sample preparation was based on quick, easy, cheap, effective, rugged, and safe (QuEChERS) extraction. Key method performance parameters investigated were specificity, linearity, limit of quantification (LOQ), accuracy, precision and measurement uncertainty. The method was validated at two spiking levels (10 and 50 μg/kg), and good recoveries (70%-120%) and relative standard deviations (RSDs) (≤20) were achieved for 92.9% of LC-amenable and 86.6% of GC-amenable pesticide residues. The LOQs were ≤10 μg/kg for 94.2% of LC-amenable and 92.3% of GC-amenable pesticides. The validated method was further applied to 100 egg samples from caged hens, and none of the pesticides was quantified.
Project description:Liquid chromatography-tandem mass spectrometry (LC-MS/MS)-based proteomics is a powerful tool for identifying and quantifying proteins in biological samples, outperforming conventional antibody-based methods in many aspects. LC-MS/MS-based proteomics studies have revealed the protein abundances of many drug-metabolizing enzymes and transporters (DMETs) in tissues relevant to drug metabolism and disposition. Previous studies have consistently demonstrated marked interindividual variability in DMET protein expression, suggesting that varied DMET function is an important contributing factor for interindividual variability in pharmacokinetics (PK) and pharmacodynamics (PD) of medications. Moreover, differential DMET expression profiles were observed across different species and in vitro models. Therefore, caution must be exercised when extrapolating animal and in vitro DMET proteomics findings to humans. In recent years, DMET proteomics has been increasingly utilized for the development of physiologically based pharmacokinetic models, and DMET proteins have also been proposed as biomarkers for prediction of the PK and PD of the corresponding substrate drugs. In sum, despite the existence of many challenges in the analytical technology and data analysis methods of LC-MS/MS-based proteomics, DMET proteomics holds great potential to advance our understanding of PK behavior at the individual level and to optimize treatment regimens via the DMET protein biomarker-guided precision pharmacotherapy.