scholarly journals Correction to “Benefits of Ion Mobility Separation and Parallel Accumulation–Serial Fragmentation Technology on timsTOF Pro for the Needs of Fast Photochemical Oxidation of Protein Analysis”

ACS Omega ◽  
2021 ◽  
Author(s):  
Dmitry S. Loginov ◽  
Jan Fiala ◽  
Josef Chmelik ◽  
Peter Brechlin ◽  
Gary Kruppa ◽  
...  
Keyword(s):  
Ion Mobility ◽  
Protein Analysis ◽  
Photochemical Oxidation ◽  
Mobility Separation ◽  
Ion Mobility Separation

Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

2020 ◽  
Author(s):  
Elizabeth Neumann ◽  
Lukasz Migas ◽  
Jamie L. Allen ◽  
Richard Caprioli ◽  
Raf Van de Plas ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Imaging Mass Spectrometry ◽  
Structural Complexity ◽  
Human Kidney ◽  
Resolving Power ◽  
Mobility Separation ◽  
Trapped Ion ◽  
Mobility Data ◽  
Ion Mobility Separation

<div> <div> <p>Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity.</p></div></div>

scholarly journals Ion Mobility Separation of Isomeric Phosphopeptides from a Protein with Variant Modification of Adjacent Residues

2011 ◽  
Vol 83 (13) ◽  
pp. 5078-5085 ◽  
Author(s):  
Alexandre A. Shvartsburg ◽  
David Singer ◽  
Richard D. Smith ◽  
Ralf Hoffmann
Keyword(s):  
Ion Mobility ◽  
Mobility Separation ◽  
Ion Mobility Separation

scholarly journals Ultra-Performance Liquid Chromatography-Ion Mobility Separation-Quadruple Time-of-Flight MS (UHPLC-IMS-QTOF MS) Metabolomics for Short-Term Biomarker Discovery of Orange Intake: A Randomized, Controlled Crossover Study

Nutrients ◽  
2020 ◽  
Vol 12 (7) ◽  
pp. 1916
Author(s):  
Leticia Lacalle-Bergeron ◽  
Tania Portolés ◽  
Francisco J. López ◽  
Juan Vicente Sancho ◽  
Carolina Ortega-Azorín ◽  
...  
Keyword(s):  
Ion Mobility ◽  
New Technologies ◽  
Biomarker Discovery ◽  
High Resolution Mass Spectrometry ◽  
Collision Cross Section ◽  
Ultra Performance Liquid Chromatography ◽  
Untargeted Metabolomics ◽  
Mobility Separation ◽  
Randomized Controlled ◽  
Ion Mobility Separation

A major problem with dietary assessments is their subjective nature. Untargeted metabolomics and new technologies can shed light on this issue and provide a more complete picture of dietary intake by measuring the profile of metabolites in biological samples. Oranges are one of the most consumed fruits in the world, and therefore one of the most studied for their properties. The aim of this work was the application of untargeted metabolomics approach with the novel combination of ion mobility separation coupled to high resolution mass spectrometry (IMS-HRMS) and study the advantages that this technique can bring to the area of dietary biomarker discovery, with the specific case of biomarkers associated with orange consumption (Citrus reticulata) in plasma samples taken during an acute intervention study (consisting of a randomized, controlled crossover trial in healthy individuals). A total of six markers of acute orange consumption, including betonicines and conjugated flavonoids, were identified with the experimental data and previous literature, demonstrating the advantages of ion mobility in the identification of dietary biomarkers and the benefits that an additional structural descriptor, as the collision cross section value (CCS), can provide in this area.

Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

2020 ◽  
Author(s):  
Elizabeth Neumann ◽  
Lukasz Migas ◽  
Jamie L. Allen ◽  
Richard Caprioli ◽  
Raf Van de Plas ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Imaging Mass Spectrometry ◽  
Structural Complexity ◽  
Human Kidney ◽  
Resolving Power ◽  
Mobility Separation ◽  
Trapped Ion ◽  
Mobility Data ◽  
Ion Mobility Separation

<div> <div> <p>Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity.</p></div></div>

Spatial Metabolomics of the Human Kidney Using MALDI Trapped Ion Mobility Imaging Mass Spectrometry

2020 ◽  
Author(s):  
Elizabeth Neumann ◽  
Lukasz Migas ◽  
Jamie L. Allen ◽  
Richard Caprioli ◽  
Raf Van de Plas ◽  
...  
Keyword(s):  
Mass Spectrometry ◽  
Ion Mobility ◽  
Imaging Mass Spectrometry ◽  
Structural Complexity ◽  
Human Kidney ◽  
Resolving Power ◽  
Mobility Separation ◽  
Trapped Ion ◽  
Mobility Data ◽  
Ion Mobility Separation

<div> <div> <p>Small metabolites are essential for normal and diseased biological function but are difficult to study because of their inherent structural complexity. MALDI imaging mass spectrometry (IMS) of small metabolites is particularly challenging as MALDI matrix clusters are often isobaric with metabolite ions, requiring high resolving power instrumentation or derivatization to circumvent this issue. An alternative to this is to perform ion mobility separation before ion detection, enabling the visualization of metabolites without the interference of matrix ions. Here, we use MALDI timsTOF IMS to image small metabolites at high spatial resolution within the human kidney. Through this, we have found metabolites, such as arginic acid, acetylcarnitine, and choline that localize to the cortex, medulla, and renal pelvis, respectively. We have also demonstrated that trapped ion mobility spectrometry (TIMS) can resolve matrix peaks from metabolite signal and separate both isobaric and isomeric metabolites with different localizations within the kidney. The added ion mobility data dimension dramatically increased the peak capacity for molecular imaging experiments. Future work will involve further exploring the small metabolite profiles of human kidneys as a function of age, gender, and ethnicity.</p></div></div>

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