10 research outputs found
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Annotation of the Human Adult Urinary Metabolome and Metabolite Identification Using Ultra High Performance Liquid Chromatography Coupled to a Linear Quadrupole Ion Trap-Orbitrap Mass Spectrometer
Metabolic profiles of biofluids obtained by atmospheric
pressure
ionization mass spectrometry-based technologies contain hundreds to
thousands of features, most of them remaining unknown or at least
not characterized in analytical systems. We report here on the annotation
of the human adult urinary metabolome and metabolite identification
from electrospray ionization mass spectrometry (ESI-MS)-based metabolomics
data sets. Features of biological interest were first of all annotated
using the ESI-MS database of the laboratory. They were also grouped,
thanks to software tools, and annotated using public databases. Metabolite
identification was achieved using two complementary approaches: (i)
formal identification by matching chromatographic retention times,
mass spectra, and also product ion spectra (if required) of metabolites
to be characterized in biological data sets to those of reference
compounds and (ii) putative identification from biological data thanks
to MS/MS experiments for metabolites not available in our chemical
library. By these means, 384 metabolites corresponding to 1484 annotated
features (659 in negative ion mode and 825 in positive ion mode) were
characterized in human urine samples. Of these metabolites, 192 and
66 were formally and putatively identified, respectively, and 54 are
reported in human urine for the first time. These lists of features
could be used by other laboratories to annotate their ESI-MS metabolomics
data sets
Ethanol Induced Brain Lipid Changes in Mice Assessed by Mass Spectrometry
Alcohol abuse is a chronic disease
characterized by the consumption
of alcohol at a level that interferes with physical and mental health
and causes serious and persistent changes in the brain. Lipid metabolism
is of particular interest due to its high concentration in the brain.
Lipids are the main component of cell membranes, are involved in cell
signaling, signal transduction, and energy storage. In this study,
we analyzed lipid composition of chronically ethanol exposed mouse
brains. Juvenile (JUV) and adult (ADU) mice were placed on a daily
limited-access ethanol intake model for 52 days. After euthanasia,
brains were harvested, and total lipids were extracted from brain
homogenates. Samples were analyzed using high resolution mass spectrometry
and processed by multivariate and univariate statistical analysis.
Significant lipid changes were observed in different classes including
sphingolipids, fatty acids, lysophosphatidylcholines, and other glycerophospholipids
Mass Spectrometric Imaging of Ceramide Biomarkers Tracks Therapeutic Response in Traumatic Brain Injury
Traumatic
brain injury (TBI) is a serious public health problem
and the leading cause of death in children and young adults. It also
contributes to a substantial number of cases of permanent disability.
As lipids make up over 50% of the brain mass and play a key role in
both membrane structure and cell signaling, their profile is of particular
interest. In this study, we show that advanced mass spectrometry imaging
(MSI) has sufficient technical accuracy and reproducibility to demonstrate
the anatomical distribution of 50 μm diameter microdomains that
show changes in brain ceramide levels in a rat model of controlled
cortical impact (CCI) 3 days post injury with and without treatment.
Adult male Sprague–Dawley rats received one strike and were
euthanized 3 days post trauma. Brain MS images showed increase in
ceramides in CCI animals compared to control as well as significant
reduction in ceramides in CCI treated animals, demonstrating therapeutic
effect of a peptide agonist. The data also suggests the presence of
diffuse changes outside of the injured area. These results shed light
on the extent of biochemical and structural changes in the brain after
traumatic brain injury and could help to evaluate the efficacy of
treatments
Chronic Ethanol Consumption Profoundly Alters Regional Brain Ceramide and Sphingomyelin Content in Rodents
Ceramides
(CER) are involved in alcohol-induced neuroinflammation.
In a mouse model of chronic alcohol exposure, 16 CER and 18 sphingomyelin
(SM) concentrations from whole brain lipid extracts were measured
using electrospray mass spectrometry. All 18 CER concentrations in
alcohol exposed adults increased significantly (range: 25–607%);
in juveniles, 6 CER decreased (range: −9 to −37%). In
contrast, only three SM decreased in adult and one increased significantly
in juvenile. Next, regional identification at 50 μm spatial
resolution from coronal sections was obtained with matrix implanted
laser desorption/ionization mass spectrometry imaging (MILDI-MSI)
by implanting silver nanoparticulate matrices followed by focused
laser desorption. Most of the CER and SM quantified in whole brain
extracts were detected in MILDI images. Coronal sections from three
brain levels show qualitative regional changes in CER-SM ion intensities,
as a function of group and brain region, in cortex, striatum, accumbens,
habenula, and hippocampus. Highly correlated changes in certain white
matter CER-SM pairs occur in regions across all groups, including
the hippocampus and the lateral (but not medial) cerebellar cortex
of adult mice. Our data provide the first microscale MS evidence of
regional lipid intensity variations induced by alcohol