Unraveling Cecal Alterations in Colonized Mice through Comprehensive Metabolic Profiling.

The disruption of gut microbiota caused by antibiotics favors the intestinal colonization of - a Gram-positive, spore-forming anaerobic bacterium that causes potentially fatal gastrointestinal infections. In an endeavor to elucidate the complexities of the gut-brain axis in the context of infection (CDI), a murine model has been used to investigate the potential effects of antibiotic administration and subsequent colonization by , as well as the impact of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the cecal metabolome for the first time. This follows our previous research which highlighted the metabolic effect of CDI and these treatments in the brain and employs the same four different metabolomics-based methods (targeted GC-MS/MS, targeted HILIC-MS/MS, untargeted RP-LC-HRMS/MS and untargeted GC-MS).

Use of Machine Learning in Interactive Cybersecurity and Network Education.

Cybersecurity is a complex subject for students to pursue. Hands-on online learning through labs and simulations can help students become more familiar with the subject at security classes to pursue cybersecurity education. There are several online tools and simulation platforms for cybersecurity education.

Metabolic Phenotyping Study of Mouse Brain Following Microbiome Disruption by Colonization.

infection (CDI) is responsible for an increasing number of cases of post-antibiotic diarrhea worldwide, which has high severity and mortality among hospitalized elderly patients. The disruption of gut microbiota due to antibacterial medication facilitates the intestinal colonization of . In the present study, a murine model was used to investigate the potential effects of antibiotic administration and subsequent colonization by , as well as the effects of three different 10-day treatments (metronidazole, probiotics, and fecal microbiota transplantation), on the brain metabolome for the first time.

Metabolic consequences for mice lacking Endosialin: LC-MS/MS-based metabolic phenotyping of serum from C56Bl/6J Control and CD248 knock-out mice.

Introduction: The Endosialin/CD248/TEM1 protein is expressed in adipose tissue and its expression increases with obesity. Recently, genetic deletion of CD248 has been shown to protect mice against atherosclerosis on a high fat diet.

Objectives: We investigated the effect of high fat diet feeding on visceral fat pads and circulating lipid profiles in CD248 knockout mice compared to controls.

Metabolic Phenotyping Study of Mouse Brains Following Acute or Chronic Exposures to Ethanol.

The chronic and acute effect of ethanol administration on the metabolic phenotype of mouse brain was studied in a C57BL/6 mouse model of ethanol abuse using both untargeted and targeted ultra performance liquid chromatography-tandem mass spectrometry. Two experiments based on either chronic (8 week) exposure to ethanol of both male and female mice or acute exposure of male mice for 11 days, plus 2 oral gavage doses of 25% ethanol, were undertaken. Marked differences were found in amino acids, nucleotides, nucleosides, and related metabolites as well as a number of different lipids.

Fully automated sample preparation procedure to measure drugs of abuse in plasma by liquid chromatography tandem mass spectrometry.

For the analysis of drugs and pharmaceutical compounds in biological matrices, extraction procedures are typically used for LC-MS/MS analysis often requiring manual steps in sample preparation. In this study, we report a fully automated extraction method carried out by a programable liquid handler directly coupled to an LC-MS/MS system for the determination of 42 components (illicit drugs and/or metabolites) (plus 20 deuterated internal standards). The acquisition was performed in positive ionization mode with up to 15 MRM transitions per compound, each with optimized collision energy (MRM spectrum mode) to enable qualitative library searching in addition to quantitation.

Endogenous and xenobiotic metabolite profiling of liver extracts from SCID and chimeric humanized mice following repeated oral administration of troglitazone.

1. Metabonomic analysis, via a combination of untargeted and targeted liquid chromatography-mass spectrometry (LC-MS) and untargeted (1)H NMR spectroscopy-based metabolite profiling, was performed on aqueous (AQ) and organic liver extracts from control (SCID) and chimeric humanized (PXB) mice dosed with troglitazone at 0, 300 and 600 mg/kg/day for seven days. 2.

Global metabolite profiling of human colorectal cancer xenografts in mice using HPLC-MS/MS.

Reversed-phase gradient LC-MS was used to perform untargeted metabonomic analysis on extracts of human colorectal cancer (CRC) cell lines (COLO 205, HT-29, HCT 116 and SW620) subcutaneously implanted into age-matched athymic nude male mice to study small molecule metabolic profiles and examine possible correlations with human cancer biopsies. Following high mass accuracy data analysis using MS and MS/MS, metabolites were identified by searching against major metabolite databases including METLIN, MASSBANK, The Human Metabolome Database, PubChem, Biospider, LipidMaps and KEGG. HT-29 and COLO 205 tumor xenografts showed a distribution of metabolites that differed from SW620 and HCT 116 xenografts (predominantly on the basis of relative differences in the amounts of amino acids and lipids detected).

Global metabolic profiling of animal and human tissues via UPLC-MS.

Obtaining comprehensive, untargeted metabolic profiles for complex solid samples, e.g., animal tissues, requires sample preparation and access to information-rich analytical methodologies such as mass spectrometry (MS).

Metabonomic investigation of liver profiles of nonpolar metabolites obtained from alcohol-dosed rats and mice using high mass accuracy MSn analysis.

Alcoholism is a complex disorder that, in man, appears to be genetically influenced, although the underlying genes and molecular pathways are not completely known. Here, the intragastric alcohol feeding model in rodents was used together with high mass accuracy LC-MS(n) analysis to assess the metabonomic changes in nonpolar metabolite profiles for livers from control and alcohol-treated rats and mice. Ion signals with a peak area variance of less than 30% (based on repeat analysis of a pooled quality control sample analyzed throughout the batch) were submitted to multivariate statistical analysis (using principal components analysis, PCA).

Imaging mass spectrometry using chemical inkjet printing reveals differential protein expression in human oral squamous cell carcinoma.

Matrix-assisted laser desorption/ionization (MALDI) imaging mass spectrometry (IMS) is a recently developed technique that generates molecular profiles usually of peptide and protein signals directly from the surface of thin tissue sections and can be coupled with automation to generate two-dimensional ion density maps. This allows specific information to be obtained on the relative abundance and spatial distribution of the analytes of interest. The technique has potential for application in many diseases including cancer with respect to elucidating the molecular pathology and identifying potential biomarkers.

Profiling and biomarker identification in plasma from different Zucker rat strains via high mass accuracy multistage mass spectrometric analysis using liquid chromatography/mass spectrometry with a quadrupole ion trap-time of flight mass spectrometer.

High mass accuracy electrospray ionisation multistage tandem mass spectrometry (MS(n)) was applied to metabolite profiling studies on plasma samples derived from two strains of rat (the Zucker (fa/fa) obese strain and the normal wild type). Using a quadrupole ion trap time-of-flight (QIT-TOF) mass spectrometer, metabolite profiling software was applied to locate components of biological significance that could account for the differences between the two strains of rat and a formula prediction software tool was used to help identify individual components. The primary factor discriminating between the two populations was the concentration of endogenous lipids.